Category: Hi-C

A Year in Review: 2024

Posted on December 19, 2024 by Benjamin Mitchell - Cytogenomics, Genomics, Hi-C, Metagenomics

Phase Genomics continues to pioneer genomic innovation, driving advancements in human health and life science research over another impactful year. Our efforts range from developing novel tools for detecting chromosomal abnormalities to managing the world’s most extensive phage-host interaction atlas, thereby accelerating genomic research and promoting a healthier future.

Our ultra-long-range sequencing technology is fostering advancements across a wide array of research applications, both at Phase Genomics and in laboratories worldwide. Utilizing our microbial platform, we are driving transformative discovery in metagenomics and ecology while making bounds in human health with cutting-edge approaches to antimicrobial research and oncology.

Thank you to our supporters, collaborators, and clients for their contributions to making this an outstanding year. Here are some key highlights from 2024.

Insights in oncology

This year, our cytogenetic platform uncovered novel, clinically-relevant chromosomal aberrations critical for assessing patient care in oncology. Genomic Proximity Mapping™ (GPM) is an upgraded approach to cytogenetic analysis – meeting and surpassing current risk stratification assessments. Over the summer, researchers at Fred Hutchinson Cancer Center and University of Washington Medical Center published research that used GPM to analyze 48 patient samples, identifying known and novel chromosomal aberrations. Read the MedRxiv preprint to discover the expanding possibilities in leukemia research here »

Cow burps, super bugs, and our enemy’s enemy–phages

We are actively developing solutions to address the growing threat of antimicrobial resistance and in the same stroke, advancing environmental health efforts with lysin discovery. By leveraging metagenomic data and AI, scientists can harness the evolutionary power of bacteriophages to target and eliminate harmful microbial pathogens with precision. Discover how we are turning the tables using our antimicrobial discovery platform with support from the Bill & Melinda Gates Foundation in our blog here »

A novel approach to vaccination

Phase Genomics’ metagenomic deconvolution technology helped crack the code on a potential new vaccine for farmed salmon to defend against sea lice by targeting the parasite’s microbiome. Published in The Economist, researcher Cristian Gallardo Escárate shares results that led to the creation of the groundbreaking invention that could ease global environmental impacts of salmon farming. More here »

Diving into the data

Two new data analysis tools were made available to ProxiMeta and CytoTerra platform users this year: ProxiMeta™ Explorer and CytoTerra® Curator.

ProxiMeta™ Explorer is an interactive, cloud-based genome-resolved metagenomic analysis platform for data visualization and exploration. The platform provides fully customizable analyses and reports for tracking genomes across time, conditions, groups, and more with a click of a button.

CytoTerra® Curator enables users to effortlessly review, revise, and generate reports from cytogenetic data – no prior bioinformatics experience required. From curating calls to constructing circos plots, Curator provides fast, accurate insights for human genomics and oncology research.

Tune in to this year’s podcasts

Listen to Phase Genomics CEO, Ivan Liachko, discuss the breadth of applications supported by Phase Genomics’ ultra-long-range sequencing technology in these podcast episodes. Discover the story behind commercializing and implementing biotech innovations and get a glimpse at where this technology is taking us.

Looking Forward

In 2025, we aim to elevate our technology to new heights and broaden our impact across science and medicine. We hope you will follow us on our journey on X, LinkedIn, and BlueSky as we lead genomics innovation to an insightful and healthy future.

Happy New Year from our team at Phase Genomics!

Catching Evolution in the Act

Posted on August 4, 2022 by Benjamin Mitchell - Genomics, Hi-C, Proximo

Genome sequencing has confirmed some long-held theories about the blueprints of life. But it has also unearthed quite a few surprises. Scientists once hypothesized that the human genome consisted of upward of 100,000 genes. The decades-long Human Genome Project — as well as many next-generation sequencing studies — have prompted the downward revision of that figure to a relatively spartan 20,000 genes, more or less.

Evolution in action

If there is a lesson in this vast overestimation to our gene load, it is perhaps that evolution shapes genomes in unexpected ways.

The advent of more nimble and lithe methods for genome assembly and analysis holds the promise to unearth the surprises that evolution has wrought. These relatively new advancements include tools like Phase Genomics’ ultra-long-range sequencing, which reconstructs the sequence of chromosomes by using positional relationships between DNA sequences in the genome. These methods have grown sufficiently sophisticated to catch the quick transitions that transform populations and species.

Recently a team led by Dr. Leonid Kruglyak at UCLA employed these tools to catch evolution at work. Their discovery relates to sex determination, a complex developmental process that, in animals, generally kicks off when an immature gonad develops into either testes or ovaries. In humans and many animals, sex determination is governed largely by genes, and in turn shapes their genomes and evolutionary trajectories like few other biological processes can.

That special pair

For species with full genetic control over sex determination, the process often leaves its imprint on the genome in the form of sex chromosomes. In most animals, genomes consist of pairs of chromosomes called autosomes. But in addition to those autosomes, many animals — including us — harbor another set of chromosomes called the sex chromosomes. Sex chromosomes govern — or at least try to govern — whether the gonads develop into ovaries or testes, which in turn influences the development of genitals and secondary sex characteristics.

Scientists have long theorized that sex chromosomes evolve from autosomes. Studies of young, relatively new sex chromosome systems, like those in the medaka, indicate that the transition happens fast. Yet the steps that transform a pair of autosomes into sex chromosomes are at best murky, with many questions unresolved. Much could be answered by catching this transition from autosome to sex chromosome in the act.

Behind the curtain

In a paper published June 1 in Nature, Dr. Kruglyak and his colleagues announced that they have found just such a transition: an animal with a pair of autosomes that is beginning to act like sex chromosomes. The researchers utilized Phase Genomics’ Proximo™ genome scaffolding platform and PacBio long reads to sequence and assemble a highly complete genome for a microscopic, freshwater flatworm, Schmidtea mediterranea. In many parts of its natural habitat across the Mediterranean basin, S. mediterranea reproduces by budding, without the need for sex. But some populations in Corsica and Sardinia produce the next generation through sexual reproduction.

The team, including lead and co-corresponding author Dr. Longhua Guo at UCLA, discovered that in these sexual strains of S. mediterranea, one pair of autosomes shows evidence of almost no genetic exchange, also known as recombination, during reproduction. This is a telltale signature of sex chromosomes. In addition, they saw that the unusual pair of autosomes harbors a large contingent of genes that play a role in developing sex-specific characteristics. Taken together, these genomic data finger these autosomes as a “sex-primed” pair that are in the process of evolving into fully fledged sex chromosomes.

Photo finishes

Future studies of S. mediterranea’s nascent sex chromosomes will likely fuel fresh inquiry and debate about this rarely-seen evolutionary transition. The answers will stretch far beyond flatworms. Studies of other recently evolved systems, such as in stickleback fish, show that sex chromosomes can play a decisive role in other poorly understood evolutionary transitions, such as the rise of a new species.

Beyond sex chromosomes, this study demonstrates the raw interrogative power of modern genome assembly and analysis methods. They can capture transitions — even the most brief and ephemeral. Applied appropriately, methods like these can help scientists make sense of a myriad of messy, complex processes that evolution shapes. These include some issues that hit as close to home as gonads, from curbing the spread of antibiotic resistance to protecting pollinators from annihilation. Evolution moves quickly. Now, so can we.

Better together: long-range and long-read DNA sequencing methods close age-old blindspots in microbiome research

Posted on January 19, 2022 by Benjamin Mitchell - Hi-C, Metagenomics, ProxiMeta

Since its debut, next-generation sequencing has not rested on its laurels. Improved sequencing platforms have reduced error and lengthened reads into the tens of thousands of bases. The debut of ultra-long-range sequencing methods that are based on proximity ligation (aka Hi-C) has brought a new order-of-magnitude into reach by linking DNA strands with their neighbors before sequencing.

Rapid progress in this field has birthed genome-resolved metagenomics, the sequencing and assembly of genomes from environmental samples to study ecosystem dynamics. But metagenomic experiments often undersample microbial diversity, missing rare residents, overlooking closely related organisms (like bacterial strains), losing rich genetic data (like viruses and metabolite gene clusters), and ignoring host-viral or host-plasmid interactions.

A revolution within a revolution

New sequencing platforms and methods can reform metagenomics from within. Phase Genomics has been a leader in genome-resolved metagenomics with its ProxiMeta™ platform, which leverages a method that physically connects DNA molecules inside cells before sequencing to generate highly complete genomes for novel bacteria and viruses. Boosting proximity-fueled methods with long-read platforms, such as the PacBio® Sequel® IIe system that can yield HiFi reads of up to 15,000 base pairs with error rates below 1%, could stretch its potential even further.

In a study published in Nature Biotechnology, a team — led by Dr. Timothy Smith and Dr. Derek Bickhart at the U.S. Department of Agriculture and Dr. Pavel Pevzner at the University of California, San Diego — employed both PacBio HiFi sequencing and ProxiMeta in a deep sequencing experiment to uncover record levels of microbial diversity from a fecal sample of a Katahdin lamb. Combined, PacBio HiFi sequencing and ProxiMeta eased assembly, recovered rare microbes, resolved hundreds of strains and their haplotypes, and revealed hundreds of novel plasmid and viral interactions.

Deeper diversity

The team constructed SMRTbell® libraries to generate HiFi data, and ProxiMeta™ libraries to generate long-range sequencing data. The two datasets allowed them to assemble contigs and create draft genomes without manual curation.

Researchers compared the breadth and depth of HiFi data-derived metagenome-assembled genomes, or MAGs, to control MAGs from assemblies of the same sample made using long, more error-prone reads. HiFi data yielded 428 complete MAGs from bacteria and archaea — a record number from a single sample. HiFi data also generated more low-prevalence MAGs, capturing a larger slice of the community’s diversity by picking up more genomes from less common residents.

The hidden actors

But no assembly method could be considered “complete” if it overlooked viruses, the most numerous members of virtually all ecological niches on Earth. These tiny players shape microbial communities in ways scientists are still trying to understand. For example, as agents of horizontal gene transfer, they help spread antibiotic resistance genes. And conversely, they have recently grown in popularity as a means to kill resistant bacteria in our ever-waging war against antibiotic resistance.

Phase Genomics’ ProxiPhage™ tool can already assemble high-fidelity viral genomes from microbial communities, even using only short-read sequencing data. But the new study shows that having HiFi helps considerably. The team identified 424 unique viral-host interactions, including 60 between viruses and archaea, which is a more than 7-fold increase over control samples. In total, the HiFi library included nearly 400 viral contigs, more than half of which came from a single family that infects bacteria and archaea. The ability to connect viruses with their microbial hosts in vivo is a unique property of Phase Genomics’ technology.

HiFi family trees

The long-range ProxiMeta libraries contained information that yielded more than 1,400 complete and 350 partial sets of gene clusters from archaea and bacteria for synthesizing metabolites such as proteasome inhibitors — the most uncovered to date. These clusters likely help some of these microbes colonize the gut. HiFi data picked up about 40% more clusters than control MAGs, illustrating just how much data is lost when long reads aren’t also highly accurate reads.

The team also used the HiFi-based MAGs to trace lineages within the community. They computationally resolved 220 MAGs into strain haplotypes, based largely on variations within single-copy genes. One MAG had 25 different haplotypes, which are likely strains of the same genus or species.

ProxiMeta ultra-long-range sequencing also linked nearly 300 HiFi-assembled plasmids to specific MAGs — revealing the species that hosted them in vivo. One plasmid, for example, was found in bacteria from 13 different genera. Long-range data also identified the first plasmids associated with three archaea, including Methanobrevibacter and Methanosphaera.

What’s around the bend?

This study has lessons beyond one lamb’s gastrointestinal tract. It shows decisively that the discovery power innate to long-range sequencing methods like ProxiMeta are greatly enhanced when wedded to high-accuracy sequencing methods like HiFi. Together, the two generate increasingly sophisticated metagenome assemblies for biologists to interrogate.

Applied to other environmental samples, this platform could illuminate the diversity and complexity of other microbial communities — from the bottom of the sea to mountain peaks, and within the body of every human being. It could probe pressing issues of our day, such as disease, soil health, and antibiotic resistance, a scourge whose spread and potential solutions — such as phage therapy — can only be forged through a thorough understanding of microbial diversity, interactions, and ecology.

Better together: long-range and long-read DNA sequencing methods, combined, reach record heights in microbiome discovery

Posted on May 27, 2021 by Benjamin Mitchell - Genomics, Hi-C, Metagenomics, ProxiMeta

Click here for an updated blog post.

Since its debut, next-generation sequencing has not rested on its laurels. Improved sequencing platforms have reduced error and lengthened reads into the tens of thousands of bases. The debut of long-range sequencing methods that are based on proximity ligation (aka Hi-C) has brought a new order-of-magnitude into reach by linking DNA strands with their neighbors before sequencing.

This progress has birthed high-resolution metagenomics, the sequencing and assembly of genomes from environmental samples to study ecosystem dynamics. But metagenomic experiments often undersample microbial diversity, missing rare residents, overlooking closely related organisms (like bacterial strains), losing rich genetic data (like metabolite gene clusters), and ignoring host-viral or host-plasmid interactions.

A revolution within a revolution

New sequencing platforms and methods can reform metagenomics from within. Long-read platforms, such as the PacBio® Sequel® IIe system, now yield HiFi reads of up to 15,000 base pairs with error rates below 1%. In addition, Phase Genomics created ProxiMeta™ kits to generate proximity-ligated long-range sequencing libraries, which preserve associations between DNA strands originating in the same cell.

In a study posted May 4 to bioRxiv, a team — led by Dr. Timothy Smith and Dr. Derek Bickhart at the U.S. Department of Agriculture and Dr. Pavel Pevzner at the University of California, San Diego — employed both PacBio HiFi sequencing and ProxiMeta in a deep sequencing experiment to uncover record levels of microbial diversity from a fecal sample of a Katahdin lamb. Combined, PacBio HiFi sequencing and ProxiMeta eased assembly, recovered rare microbes, resolved hundreds of strains and haplotypes, and preserved hundreds of plasmid and viral interactions.

HiFi family trees

The team constructed SMRTbell® libraries to generate HiFi data, and ProxiMeta kits to generate long-range libraries. The two datasets, along with the metaFlye and ProxiMeta algorithms, allowed them to assemble contigs and create draft genomes without manual curation.

Researchers compared the breadth and depth of HiFi data-derived metagenome-assembled genomes, or MAGs, to control MAGs from assemblies of the same sample made using long, error-prone reads. HiFi data yielded more complete MAGs — 428 versus 335 — from more bacteria and archaea. HiFi data also generated more low-prevalence MAGs, capturing a larger slice of the community’s diversity by picking up more genomes from less common residents.

The HiFi MAGs also contained more than 1,400 complete and 350 partial sets of gene clusters for synthesizing metabolites such as proteasome inhibitors, which likely help some of these microbes colonize the gut. HiFi data picked up about 40% more of such clusters than control MAGs, illustrating just how much data is lost when long reads aren’t also highly accurate reads.

The team also used the HiFi MAGs to trace lineages within the community. They computationally resolved 220 MAGs into strain haplotypes, based largely on variations within single-copy genes. One MAG had 25 different haplotypes, which are likely strains of the same genus or species.

ProxiMeta’s long-range discoveries

The ProxiMeta-generated libraries added flesh to these MAG frames skeletons by unveiling additional rich biological information. Long-range sequencing linked nearly 300 HiFi-assembled plasmids to specific MAGs — revealing the species that hosted them. One plasmid, for example, was found in bacteria from 13 different genera. Long-range data also identified the first plasmids associated with two archaea, Methanobrevibacter and Methanosphaera.

Long-range sequencing illuminated the viral burden in this community. The HiFi library included nearly 400 viral contigs, more than half of which came from a single family of viruses that infect both bacteria and archaea. The team identified 424 unique viral-host interactions, including 60 between viruses and archaea, which is a more than 7-fold increase over controls.

What’s around the bend?

This study has lessons beyond one lamb’s gastrointestinal tract. It shows decisively that the highly accurate long reads generated by HiFi sequencing ideal partners for Hi-C-derived methods like ProxiMeta — together generating increasingly sophisticated metagenome assemblies for biologists to interrogate.

Applied to other environmental samples, this platform could illuminate the diversity and complexity of other microbial communities — from the bottom of the sea to mountain peaks, and within the stomach of every human being. It could probe pressing issues of our day, such as antibiotic resistance, soil health, or how microbes can break down pollutants. These endeavors will not just fuel the engines of scientific inquiry. Broader use of this method could generate new insights into pressing problems of our times, including antibiotic resistance.

New genome assembly method makes fruitful advances in genomic technology

Posted on April 29, 2021 by Benjamin Mitchell - Genomics, Hi-C, Proximo

A collaboration between Phase Genomics and Pacific Biosciences of California is bringing about the next generation of genome assembly technology. A newly published software tool, FALCON-Phase, combines genomic proximity ligation methods developed by Phase Genomics™, with the high accuracy, long-read sequencing data from PacBio®, enabling researchers to create haplotype-resolved genome sequences on a chromosomal scale, without having parental genome data. This method and its application to several animal genomes was published today in Nature Communications.

cow, zebra finch, and human hand arranged in a collage

Humans, as well as other animals, carry DNA sequence copies from both parents. These parental sequence “haplotypes” can carry millions of mutations unique to one of the parents and are often very relevant to diseases and other genetic traits. Until recently, accurately separating paternal and maternal mutations on the whole-genome scale required sequence information from the individual parents or extensive efforts that relied heavily on imputation from population studies. The new method employs the physical proximity information captured by proximity ligation (a technology also known as “Hi-C”) to separate maternal and paternal haplotype information from long-read genome assemblies. This development significantly increases the actionable information content coming out of genome sequencing studies.

“It’s an exciting time for genome assembly and PacBio HiFi sequencing continues to lead the way in this area with its powerful combination of read length and accuracy,” wrote Jonas Korlach, Chief Scientific Officer at Pacific Biosciences. “Phase Genomics Hi-C complements PacBio technology by extending our data into the ultra-long-range domain, enabling us to connect phase blocks and deliver chromosome-scale diploid assemblies without parental data. We are fortunate to have this excellent partnership with Phase Genomics, and we look forward to continuing to work together to create the highest quality reference genomes available.”

Assembling two fully-phased genomes in a single, streamlined process not only saves on the costs of research, but it also enables scientists to upgrade their genome assembly pipelines and obtain previously unobtainable information.

Dr. Erich Jarvis, professor at Rockefeller University and chair of the international Vertebrate Genomes Project, wrote, “Chromosome-scale haplotype phasing is critical for generating accurate genome assemblies and for understanding genomic variation within a species.” Furthermore, FALCON-Phase produces maternal and paternal haplotypes without family-trio data, so it can be applied to wild-caught samples or organisms lacking pedigree information. Jarvis notes, “In wild populations that many work with, parental samples are usually unavailable and therefore we need a method that can phase paternal and maternal sequences in the offspring individuals. With FALCON-Phase, we are able to use the Hi-C data that we have already generated for genome scaffolding and add a new dimension to every genome assembly, even retrospectively for previous projects. Our collaboration with Phase Genomics and PacBio has been extremely fruitful and the combination of the two technologies through FALCON-Phase will be highly beneficial to genomic sequencing efforts focused on conservation.”

FALCON-Phase is applicable to any diploid genome, including plants, animals, and fungi. It is available as free of charge open-source software (https://github.com/phasegenomics/FALCON-Phase) and Phase Genomics offers services that include the application of this method to varying genome projects. See the latest news and publications on this and other genome assembly methods at https://phasegenomics.com/resources-and-support/publications/.

For more information, email us at info@phasegenomics.com.

Startup Stories: Navigating the Ins and Outs of Incubators and Accelerators

Posted on March 17, 2021 by Kayla Young - Hi-C, Webinar

Insights from the Trenches with Genomics Startup Founders

In the first Genome Startup Day event of 2021, we highlighted one of the most critical decisions facing early-stage founders: whether or not to enter an accelerator or incubator. Three genomics startup founders from across the US shared how their unique experiences helped shape their company’s foundation and path to success. From mentorship to hiring to building community in a virtual world, these founders’ candid and frank stories deliver tangible and educational takeaways for new and future founders alike.

Watch the video here or read the full transcript below.

Transcription results:

S4: 30:15	[Ed Winnick] Okay, great. Hello, everyone. As Ivan noted, I’m Ed Winnick. I’m editor-in-chief at GenomeWeb. I’m really happy to be participating in this event today. We have a great panel of startup founders today from three companies. We’ve got Natalie Ma of Felix Biotechnology. We’ve got Joe Miller from [Cqua?], and we’ve got Alex Rosenberg from Split Biosciences, which as of a day ago, is now called Parse Biosciences. And I’m sure Alex will tell us more about that in a moment. So what I like to do is start off by giving each of you a little bit time here to tell us about yourself, your company, and why you chose the path of being involved with an incubator, an accelerator, both or neither. So let’s start with Natalie, and then we’ll go to Joe, and then, Alex.
S5: 31:06	[Natalie Ma] Great. Thanks, Ed, and thank you again, Kayla and Ivan for setting this up and inviting us. This is a fantastic event, hopefully, very informative for all of you. I am co-founder and head of business at Felix Biotechnology, where we develop phage technologies to essentially overcome the key limitations of phage therapy and produce commercially viable phage products. And so a lot of what we were interested in is solving two problems. One of them is evolution of resistance to [inaudible] microbes. And then, the second one is how strange a phage, because that’s a key challenge. They tend to be exquisite, essentially microbiome, skiable. If you want to edit a strain, a species, or even a strain with species of a genome or change the microbiome in some way, they’re perfect [inaudible] anything else if you get to host phage naturally, right? So what we do is we develop generalized therapies. So we’re essentially creating phages that are engineered from [tuned?] host range and then, we leverage the way the phages work against the host to actually try evolution to our advantage by targeting phages to specific mechanisms of the virulence, antibiotic resistance, whatever treatment you want to edit out of the genome, and allows you to take advantage of evolution instead of trying to fight it. So the resulting microbe usually because the phage ends up then being [inaudible] with antibiotics or less virulent [inaudible] the patient or lacking some trait you just want to get rid of.
S5: 32:36	So quick background on myself and who I am and how I got involved with this super awesome work is I’ve PhD in Synthetic Biology or Molecular Biology, depending on who you’re talking to and how much trouble I’m trying to cause. And after that, went into management consulting in the healthcare space helping companies commercialize therapies and then jumped to essentially helping launch startups out of my, the same program I went to for PhD at Yale, where I helped roughly eight faculty, three ventures got off the ground by the end of my year there to the tune of about three million combined. And Felix by far was the coolest venture that I worked with. And our strategy was to go through an accelerator program. We were part of Illumina Accelerator. For us, sort of at a high level because I’m sure we’ll get into more questions around this, Ed, is the value to us was having a really well outfitted space, and then the sequencing that Illumina provided, because, again, we’re heavily data-driven startup, really we need to understand phage and host interactions and use that as the seed data for our machine-learning platform to understand what are the key genetic determinants of host range. So the services and support that Illumina’s provided were invaluable for us to get our first data set and understanding how these phages work.
S4: 33:58	Great, Joe, why don’t you go next?
S6: 34:00	[Joe Mellor] Thanks, Ed. Yeah, so I’m Joe Miller, I’m the founder and CEO at seqWell. So our company focuses on creating sophisticated library prep tools to sort of help power sequencers and collect more information. Our technologies are really focused on how to improve the scalability of multiplexed genomic assays focused on a variety of areas, single cell sequencing, high-throughput sequencing of other things, recently doing some really cool work to help accelerate some of the incredibly important COVID sequencing effort that’s now scaling up around the US and the world. When I started the company, myself and my co-founder, Jack Leonard, I would say the availability of incubator space was crucial. The sort of thinking of a company, especially at its early stages, a sort of a young person having a place to live is very, very basic on the hierarchy of needs. And the benefits from it were not just being in a space where we had the ability to really kind of test early product concepts and really do some of the work that was required. But also it put you in a space where there were other companies at that same stage of life. And that turns out to have all sorts of, I think, healthy psychological benefits. As a founder I think we don’t spend enough time probably as founders ruminating on the stress that it causes, but it is very stressful. And having other people around you who are going through the same thing is incredibly helpful. And really, it acts as a way of calibrating your own experiences with other companies. And you realize, hey, what we’re going through is very similar to what any company in nearly any space at our stage of growth would be going through.
S6: 36:20	And I think back on the comments that Mostafa made a few minutes ago about the importance of team. Again, I firmly believe a company is really its team, and I feel incredibly fortunate to have brought in some incredible team members over the past few years as we’ve grown. And to me, that is what building the company is all about. The talent and getting everybody kind of rowing in the same direction is really what building the company entails. And the products are in some ways a consequence of doing things the right way and really, I think that has for us been, I think, the learning experience. You have to be willing to take those risks and make a few mistakes along the way, and I think, but certainly, I would definitely recommend any company getting started to take advantage of any incubator opportunity that they can. And again, I think seeing your company as part of an ecosystem with other companies, and incubators are a special place where multiple boats can rise at the same time.
S4: 37:49	Okay, thanks, Joe. And Alex, how about you?
S7: 37:52	[Alex Rosenberg] Sure, thanks, Ed. So I’m Alex Rosenberg, the co-founder and CEO of Parse Biosciences, and as Ed was just mentioning before, we actually recently yesterday just announced our Series A and rebrand from Split Biosciences to Parse Biosciences. And so the company what we’re doing is we’re offering a scalable single-cell sequencing solution where the key thing is you don’t need an instrument to use this technology. So it’s an all-inclusive kit that allows anyone to get started with single-cell sequencing and really scale up their experiments. And just in terms of my background, how I got into this, this was something I co-developed with my co-founder while I was a postdoc at the University of Washington. And so at the time, I think we were very focused on just technology, on developing. And as we’re kind of going along, single-cell sequencing was getting a lot bigger. We actually had a lot of people reaching out to us, “How do we get this working in our lab?” And for us, it’s really important to actually get this out to people. And I think a lot of times what you see is academic methods, they kind of die in academia. And to actually get it out to a lot of people and allow them to use it takes a lot of effort, and that’s not something that academia is well suited for. And so for us, we started the company. This is early 2018. It was about the same time we ended up publishing the work, and since then, we’ve really been pushing the company, growing. We’re 16 people at the company now, when I guess with respect to incubators, we were actually really lucky. So we spun out of the University of Washington, and they actually have a lot of support for companies and sort of a very entrepreneurial spirit in general at the university. And so one of the nice things is they actually have lab space for spin-out companies. And so it’s kind of like a pseudo incubator that has a lot of the resources you would expect at other incubators. But as Natalie and Joe have mentioned, getting lab space when you’re small is critical and just being able to operate in the beginning there is super important. We also, through the incubator, as Joe was mentioning, we were able to interact with other companies. A lot of people, I think, emphasized, it’s really important to talk to a lot of people when you’re getting started, especially when you’re coming out of academia, that there’s just a lot you don’t know that you’re going to have to learn. And some of that’s going to be from customers that you’re going to have to keep talking to customers. I think in some ways, given that I worked in kind of the same fields that my customers are, I had a pretty good sense of the customers, but you still want to talk to them. But a lot of the sort of business aspects that you’re trying to pick up, those are the things that you want to have good people around you, good advisors, also talking to other companies, learning about what other company’s doing. Maybe there’s better ways that you could be modeling things based on those other companies.
S4: 41:06	[EW] Great, thanks a lot, Alex. Natalie, I’m going to give it back to you here. Can you talk a little bit about the process of joining the accelerator and explain the attendees who might be a little less familiar with how they work, what a typical arrangement looks like? And tell us in the world that we’re in now, pandemic, people not being able to go into offices and lab spaces, would it be worth it to do without the access to the physical space?
S5: 41:36	[NM] Yeah, that’s a great question, Ed. So in terms of the accelerator program process, it’s typically an application that you fill out, and there are generally pre-set terms, and that’s typically a percentage of equity stake in the company in exchange for the lab space and additionally, in our case, services through Illumina Accelerator. So you go to the application process and this sort of speaks, I think, one of the things that’s really nice about the accelerator programs is they’re often not just a lab space, but also, I think a mark of validations that way, right, because someone has vetted you, and so that can open doors. And so that, for us was helpful as well. So that’s how we got into Illumina Accelerator. In terms of the second part of the question, speaking to that value proposition, I think it’s incredibly valuable. One, because of that mark up, again, validation, it’s like, hey, we’re an Illumina Accelerator company. Mostafa and [inaudible] had looked at our program and thought, “Hey, they’re doing something super cool. We should support them, and we think that there is a path forward.” So I think there is still a lot of value there. And I know in the case of lab space, at least here in South SF, the lab folks are considered essential employees. Access to that lab space still exists, at least again in our area, are going to continue to exist unless something really existential happens. The office space, I think, there is value to it, but at least what we found is many of the connections that were valuable were came through digitally anyway. And so the other thing that was great was that the staff and Amanda could help us understand like who should we talk to to leverage our platforms and build out additional partnerships in addition to getting data on our lead asset? So both of those things, I think, are still really valuable for the sort of accelerator route, despite sort of the the changes that the pandemic has brought.
S4: 43:31	[EW] Okay, thanks, and Joe, your experience was slightly different. You did an incubator. So how did that differ from the experience Natalie just explained?
S6: 43:41	[JM] Yeah. So there was certainly a phase of trying to apply to get the space in that incubator, and certainly, there’s a process that requires a certain level of having things really well articulated and lined up in order to be able to do that, and I think that was certainly helpful. For me, I think joining the incubator again was– we were there for less than a year. And I think part of the reason why is because one of the benefits of being there we quickly sort of outgrew, which was the amount of space that we needed. And I think we certainly had a great experience there and the support structure that was there to kind of even in the case of the lab space that we moved into after we left the incubator was owned by a firm that was closely tied to the same organization. The network effects that kind of are created by tapping into a resource like this or you don’t really see them ahead of time. But so again, it’s really– but it’s an investment really in kind of the future of the company to put yourself in a situation where those effects are allowed to really work in your favor. So, again, I think I almost can’t imagine starting a company without that sort of resource in place. I think that especially a company that’s not starting with a huge sort of check up front, so I think it was clear in our experience.
S4: 45:47	[EW] Okay, thank you. And Alex, you actually didn’t go through an accelerator or incubator, but you did get help from UW. Just wondering what was different about your experience compared to that explained by Joe and Natalie?
S7: 46:03	[AR] Sure, I mean, I think ultimately you got to get to the same place that you have to build your network. You have to understand how have other people before you done this, and especially coming at it from the academic side where technically you might be good, but there’s still so much you got to learn. And as Mostafa was talking about earlier, the technical side, the idea is just one aspect of it. There’s all sorts of execution and different aspects that you’re going to have to learn from other people and bring people on to the company. And so I think for us, we were really lucky that University of Washington, they helped us start to build that network, and they have different people who have started companies, angel investors, who’ve started companies in the past and been successful and sort of want to give back and help younger entrepreneurs. And so that was, I would say, a good way to start building our network. Obviously, from there, I think what you have to do is really branch out, and every person you get introduced to, you have to make sure you’re asking them if there’s other people they can introduce you to, and it’s kind of just this spiraling effect that if you really put effort into it, you’re going to meet a ton of people and that aspect is critical. So I think there’s different ways to go at it, and it sounds like a lot of these accelerator programs are actually a great way to do it in a very condensed time-frame. I think, in a lot of ways, we were lucky we had the support at the University of Washington.
S4: 47:43	[EW] Yeah, great. And that’s a great lead into the next question, which is about mentors. Usually, if you belong to one of these programs, you have access to mentors. And I’m curious about your experiences with that. And can you talk about where you found mentorship or coaching or community to support you as you’ve gone through the startup process? Natalie, why don’t you go first?
S5: 48:07	[NM] Yeah, yeah, and I just wanted to follow up on the last thing, I think the pathways in general will very much depend on your venture or your startup, right? So there’s not a right answer here. It’s very much what is the key next step you need to figure out and what tools will help you get there. So on the venture side, we again had great access to mentors, the folks that were connected to Illumina Accelerator, people who were interested both in DC as well as on the regulatory side, which was incredibly helpful for us. Again, because we’re a therapeutics oriented company, our lead asset is now in a phase one, two clinical trial. So all of that was incredibly helpful to help us know, okay, again, what’s the next step we need to do, and what is needed to get things off the ground?
S5: 48:55	In general, there are sort of three buckets of folks I’d say you encounter in the venture or not the venture, the sort of startup space. There are folks looking who are for consulting services and want to see you transition as a client. They’ll provide some initial upfront help. There are folks who are looking for their next gig. So they would want to join you generally in a C-suite position, and they’re looking across multiple things. They might provide some help to you, but their idea is to get that next role. And then, there are folks who have been through the process, and really, I would say they sort of help out of our memory of having been there and someone helped them. So they’re paying it forward and helping you solve problems that they would want to have had help with if they were starting out. And so those three groups of people sort of can serve different roles and have different specialty, but understanding where the person’s coming from helps you frame the right questions.
S6: 49:50	[JM] Yeah, I definitely agree with the value of that last category that Natalie just outlined. We had the benefit of, again, a network of in some cases, serial entrepreneurs who had worked in companies, perhaps some in life-science, but some not. I think when you’re a– especially when you’re a first time founder, the number of sort of unknown unknowns is extremely high, and you have to really collect as much of that type of advice as possible from people who have been there and done it. They’ve been through that. They were at some point the first-time founder or CEO themselves. But quickly realize, the goal was not necessarily to know everything, but certainly to know what I didn’t know and know where I might be able to go find it. And I think having people who have literally been there and done it who can help you think through and be a sounding board or just provide the pointers that are kind of critical in those early days, I think, is extremely important.
S4: 51:10	[EW] Alex, you have anything to add on that?
S7: 51:14	[AR] Yeah, I mean, I think Joe and Natalie hit it right on the head here. You really do need, I think, different types of mentors too. You’re going to have peer mentors who are maybe at similar stage with their company’s view. You’re going to have people who maybe they’ve done this multiple times, had several successful exits or high up at a big company. And you’re going to get different advice, I think, from different people here. And so I think it’s always good to kind of average out over the advice you get over different people because it’s always going to be very specific to that person. And a lot of times, people are sort of actually just rationalizing the decisions they made in the past, and it’s kind of important to see which of their pieces of advice actually apply to you. And we’re a bit different. For us, getting advice from someone who has started a therapeutics company, some of that advice, I think is still going to be very applicable. Some of it’s going to be different for us. And that’s kind of where you have to take that advice, but also as you’re moving forward in practice, you’ve got to think about how you should be applying it.
S4: 52:28	[EW] Yeah, that’s great, thanks, Alex. So we talked a lot about the benefits of joining these programs, but were there any unexpected drawbacks or challenges that you found with being involved with an incubator or an accelerator, Natalie?
S5: 52:44	[NM] Okay, I’ll start off, but I think mine’s going to be pretty short. For IA, it is the nicest lab space you’re going to have for a while because it’s part of Illumina, and so the lab space is phenomenal. I mean, we’re now housed in J Labs at [Easter?] point. So it’s also incredibly nice lab space. But as we were looking around landscape transitioning out of Illumina Accelerator, we’re going from a place that had everything set up for us to more sending up on our own, which we knew was going to happen, but it always is in the moment like, oh, okay. We’re going to have to account for all of these things that we once relied on Illumina for.
S4: 53:25	Joe?
S6: 53:26	[JM] Yeah, no, I mean, if I was to kind of to simply summarize what Natalie just said, you can get spoiled. And I think, again, the role of the incubator is to get you kind of on your feet and on a path, but I think it’s incredibly important to realize that the goal when you’re there is to leave. And again, some incubators have kind of more rigid timelines as to when that needs to occur, sort of dates on the calendar that you– we need to be have some cash flow by this point in time. I think if I was to sort of generalize from what I have seen as a pitfall, is if there isn’t a kind of push to help companies leave the nest, I think they can linger sometimes. And again, it’s comfortable. It’s usually, well, very affordable, if not subsidized lab space. And so I think it’s important to keep that in mind as a founder that your goal in going to an incubator is [supposed?] to join, but then to also leave.
S4: 54:36	[EW] Okay, thanks. Alex, I don’t know, given your situation was differently, if the challenges were similar or different for you.
S7: 54:48	[AR] I mean, I would echo. I think in general, we were extremely lucky with our incubator space and just the support we had from everyone. I mean it. So really nothing negative to say there, Ed.
S4: 54:59	[EW] Okay, great. So you all mentioned the importance of teams for [inaudible] startup. Do you think there’s a different combination of skills or personality that’s necessary for your team to be successful? Joe, why don’t you go first on this one?
S6: 55:16	[JM] Yeah, I mean that’s a good question. I feel probably to really answer that question well, I would need to have more than one and number of companies. I can tell you from what my experience was, those early employees have to really– those co-founders and early employees have to be able to do nearly anything. Again, it’s wearing sometimes any hat any day. And I think so there’s a mindset that comes with that that is not going to– it’s not easily boiled down, but you hope that you learn to recognize that because those kinds of people are extremely helpful. So I think there’s certainly a mix that there’s probably– some mixes that are better than others, but ultimately that kind of flexible mindset to me really supersedes and dominates that, I think.
S4: 56:25	[EW] Yeah, Natalie, do you have any further thoughts on that?
S5: 56:27	[NM] Yeah, I definitely agree with what Joe said. Spot on. And I would only add being very, very acutely aware of what your skills and strengths and your weaknesses are, and then getting along with the team because that was one of the major reasons, when I had options to join various ventures, I chose Felix was by far the best team to work with in terms of compatibility, because you, as a co-founder, is going to be spending a lot of time together, and you want it to be enjoyable as well as fulfilling and world-changing, right?
S4: 57:03	[EW] Yeah, great. Thanks, Natalie. Alex, how about you?
S7: 57:07	[AR] Yeah, I mean, it’s just that [inaudible] some of those things. I think in general you have to have a mix of diverse people on your team with different skill sets. I think one of the things it’s extremely cliche, but I think when you’re running the company, you realize it is that teamwork is just incredibly important, and there’s very few things that are being done in isolation. It’s very different coming from academia where you have one project maybe you’re working on with one or two other people where that’s really there’s nothing like that. Very few things are like that in the company. Everything you have to communicate with other people. And so I think bringing– we’ve been extremely lucky to have people who are really excited to work together and all motivated towards the same goal. And that’s something I’m sure everyone has heard as advice. But I think when you live it, it’s really important.
S4: 58:04	Okay, thanks a lot, Alex.

Founders: Why You Should Consider a Chief Janitorial Officer

Posted on March 3, 2021 by Kayla Young - Hi-C, Webinar

Insights for biotech founders from a leading voice in genomics commercialization

What’s in a fancy startup C-suite title? The answer from luminaries is: “nothing if the startup fails.” In the first Genome Startup Day of 2021, Phase Genomics’ Founder and CEO Ivan Liachko, PhD, sat down with Mostafa Ronaghi, PhD, Senior VP for Entrepreneurial Development for illumina (retired), founder of multiple companies, and longtime champion of genomics commercialization. In the fireside chat, Dr. Ronaghi spoke of how startup founders should not focus as heavily on their and others professional titles and instead focus more on taking care of their growing team and getting the important work done.

“In order to get the right team, you really need to be generous and have the right people driving the right function. The startup is not about the title… everybody is doing whatever they can,” Dr. Ronaghi said. “So, I announce myself as CJO, I’m the Chief Janitorial Officer, and if you want to, you can give me a title. But the title doesn’t have any value. I mean, you are basically a CEO of a one-man company or a two-man, three-man company, so that doesn’t mean anything. You are there to do something.” (view video clip at 11:39)

Dr. Ronaghi also addressed his thoughts on what newly founded startups (view video clip at 15:04) should aim to optimize first (hint: it’s not revenue). Watch the full fireside chat or read the entire transcript below the video.

Transcription:

S2: 02:19	[Ivan Liachko] Hello, everyone. Thanks for coming to another installment of Genome Startup Day. As you can see from my outfit, we’re about to do a fireside chat. We’re very fortunate today we have with us Dr. Mostafa Ronaghi from, well, I was going to say from Illumina, which is largely true. And Mostafa, starting at 2008, he was the Chief Technology Officer and also Senior VP at Illumina. Before that, he was at the Stanford Genome Technology Center. He also founded a number of companies. He was one of the early pioneers of Pyrosequencing technology, and he’s founded a number of startups, including Pyrosequencing AB, ParAllele Bioscience, Nextbio, and Avantome. Just a couple of days ago, he announced his retirement from Illumina, but we’re lucky to have him here to talk to us about– to talk about startups and sort of his history in the space. Mostafa, thank you so much for coming.
S3: 03:36	[Mostafa Ronaghi] Thank you.
S2: 03:39	[IL]So you’ve been a sort of a champion of entrepreneurship for a while. You’ve been with Illumina for a long time. That’s kind of the sort of the top line item on the biographies. But you’ve actually done so much in the entrepreneurship sphere. What sort of drives your interest in supporting biotech commercialization and startups in general?
S3: 04:02	[MR] Thanks, Ivan, for having me and thanks, Kayla, for organizing the event. So, yes, I think it has been, of course, a passion, but the passion comes from the impact that you’re making on human life. So when I was in high school, I decided to be in the field of medicine. I wanted to become a doctor, a physician, and after going to different practices and clinics with my uncle, so I decided doctor is not my thing, but I love medicine, and I want to be an entrepreneur in this field. So when I moved from Iran to Sweden for my education, I knew exactly genetic is the area that I want to focus on. And I did my PhD in Genetic Engineering, and I ended up developing Pyrosequencing technology, which was the first next-generation sequencing technology. And the word of sequencing by synthesis actually was going in my first publication basically which was describing the Pyrosequencing technology, and there are a lot of technologies that we have in offshoot of that. But when I look back, that’s the technology, of course, but that technology was fundamental in enabling a lot of applications. And we knew that some of those applications are going to be developed by other people, which was absolutely fantastic. And we really wanted to see how we can enable people to make that impact. If people think are enabled to make an impact, so I feel that I have impacted people’s life. And that was the biggest satisfaction and the drive during the course of my life.
S2: 05:58	[IL] That’s awesome. Yeah, I mean, one of the kind of themes behind this event, one of the reasons why we started it was really to kind of introduce kind of academics to the biotech life and sort of the switching from the kind of the research community over to the– maybe not switching, but people who are sort of on the cusp of transitioning maybe from academia to biotech, and a lot of folks are thinking about it these days, and so we’re sort of at that interface. And so I kind of want– I like to hear perspectives of folks who sort of have made the switch. So what would you say is your favorite thing about working with startups, especially early-stage startups because you’re involved in the Biotech Incubator or the Illumina Accelerator. So what do you like most about these?
S3: 06:52	[MR] The agility and the fact that you can make fast decisions and honestly startups, they are a source of inspiration for me. And when I look at entrepreneurs that they are in the mission of changing people’s life, and that’s a huge source of energy. And you see that they’re actually doing that. Any technology or any applications that they have been leveraging sequencing or genomic technologies, most of them, they have come into the clinical space, of course, and they are changing [your?] lives in the form of discovery or diagnostics. So I feel that the whole revolution has started. You’re not even in day one of that revolution. And so it’s amazing to see on the side and sometimes be in the action and to watch that revolution that’s happening.
S2: 08:01	[IL] Yeah, well, we’ve certainly seen that, I mean, this year, I think, or at least 2020 and 2021 have shown sort of highlighted how important biotech is for humanity. I get to sit in a lot of these events, and we spend so much money on things that are like the military, etc., and all these other things. But when a big pandemic or something comes through, the biotech groups are the ones who start kind of showing their value. What do you think sort of on the counter side of this, what do you think is maybe the biggest challenge that early-stage founders, especially sort of academic founders have in the genomics space? What have you seen that’s the most difficult to transition?
S3: 08:57	[MR] So when I look at academia, so I have been in academia and Stanford, so Stanford probably is a bit different than other academia. So it’s not taboo to start a company. You get actually a lot of credit to start a company, but the biggest hurdle I see that people, they think that it’s all about the idea. And I would say that probably idea is important, but when I look at how I weight start-up and having been involved in research in academia and going to start a company in scaling and then commercializing at the global level, so there are multiple touch points that are critical. One, of course, critical step is how to transition from academia to the company.
S3: 10:03	[IL] So at that time, you really need to think that who are the right people that I really need to have in the bus? You’re going from point A to point B, and the people are absolutely critical component of how you can make things happen. And they should have enough of incentive to basically take on that mission or to join you in the bus from going from point A to point B. So when you look at a company, at the time you start, so it’s all about team. Of course, the idea that you have is on PowerPoint or on paper. So it’s all about the team. So you should do the evaluation based on the team. And as you make progress, you get to the series A level. So, of course, at that time, people, they look at the team, but they look at what you have achieved, which, in a way, defines how good team you have had. And so you really need have a concept for a biotech or genomic company. And at the time you reach Series B, so you really need to have some sort of revenue validation. So your product should be in the market and you should have some sort of validation, which, in a way, shows how good a team you have had. So it’s all about team, team, team, team.
S3: 11:39	[MR] And in order to get the right team, you really need to be generous and have the right people driving the right function. So the startup is not about the title. So basically everybody is doing whatever they can. So I announce myself usually at startup, I’m the CJO, I’m the chief janitorial officer, and if you want to give me a title. But the title doesn’t have any value. I mean, you are basically a CEO of a one-man company or a two-man, three-man company, so that doesn’t mean anything. So you are there to do something.
S3: 12:20	[MR] And I usually advise startup not to give any title honestly. You have one person like CEO, but other than that, so you have Head of Technology, Head of Product, or Head of Revenue and so on. As you grow and you have significant ownership in the company, you really need to bring value to your shareholders, which means that you bring value to your share, which means that you are making progress on your product or the road-map of the company. So if that’s the case and if you see that by hiring a person to increase that value, you should do it. Even, they would take your job. And that’s the struggle that I see people they have at the company. And you have to realize, okay, this is your capacity, and I could bring experience at this point, or I could bring someone with a different expertise to take the torch and run as fast as you can to go to point B.
S2: 13:36	[IL] Yeah, I can definitely– I mean, definitely emphasize with the fact that as the company grows, having to relinquish and delegate a lot of responsibilities and things like that along the way is definitely one of the challenges, because you start out, like you said, doing everything yourself. And little by little, you have to specialize and try to get the right people for the right jobs and things like that. What do you think– in your experience, what do you think is the most common sort of mistake in the space that startups make? Is it that they just give everybody [Steve?] titles at first and then a weird theme thing?
S3: 14:15	[MR] That’s a red flag. That’s a red flag when I see that a lot of– see their title in a lot of big companies. Easy to give titles, but it’s very difficult to take it back, and people, they’re emotional and you don’t want to be in that position. That’s a red flag usually for me.
S2: 14:32	[IL] Is there something that you see that young sort of early-stage startup neglect that they really should focus more on? I mean, for me, for example– just an example, for me, clearly, sort of marketing and sales in the early days was not something that I was paying enough attention to as much as should have been because coming out of academia is not something you’re familiar with. But are there other things like that that you see that are common patterns that young startups tend to sort of not do right?
S3: 15:04	[MR] Yeah. So usually, the scientific founder, they think that they have done everything and this is it, and they should have the majority of the ownership. And when you look at the cap table, so it’s heavily on the scientific founder. And then, other people, they are not going to have enough incentive, and those companies usually don’t go anywhere. So the way you want to think in a startup is that, okay, there’s a pie, but the size of the pie you define. And if the pie is this small and you have the entire ownership of that pie is not that much. But if the pie is huge and even if you have a slice of that, so that’s a lot. So I really think that you should usually think about how you can make a difference, how you can bring a product to make that difference to the market. You have to look at what’s going to happen. So number one factor for me when I start a company is I can make this company successful, not on how much I’m going to make at this company. So especially for first [a month?] entrepreneurs, they should be super sensitive about this because they should not optimize for their financials, they should optimize for how fast and how good a product they can get into the market because if you get it once, then you can always repeat that. That’s a good thing with entrepreneurship. Everybody wants to work with you, oh, you have some unique experience. You took actually one idea, and you turn that to a product, that’s a unique experience. Everybody wants to work with you, and you are going to have access to amazing, amazing people and work on even larger ideas. So I really think that at the end goes back on your position yourself in starting the company and bringing the right people to the team and give them enough of incentive. Number one goal should be how fast I can go from point A to point B.
S2: 17:17	[IL] Do you think that that sort of roots itself in the idea that most, I guess, at least academic technical founders think that the idea is good, technology is good, this thing is definitely going to work? And so, you try to kind of maximize your outcome, and you don’t realize that the greatest danger is not that your pie slice is going to be too small. The greatest danger is that your entire pie is going to be worth zero.
S3: 17:43	[MR] Exactly, exactly. Yeah. And when I look at a lot of ideas, revolutionary ideas, I usually call them the ideas that they have a miracle to overcome, and usually you see that, okay, there are some miracles that they have overcome in academia, but to make that a product that would require– of course, it doesn’t require a miracle. So, the type of brainpower that you need to have to overcome the miracles are different for type of people that they focus on how to make a product, a concept to feasible product and how to make it a robust product. And those are all different brains. And all of them, they are valuable in a company. And you shouldn’t think that, oh, okay, since I’m the guy who has overcome the miracle and have addressed the challenging issues, which is true, but they shouldn’t think that they should have everything at the company of course. Other people, they are needed.
S2: 18:56	[IL] So, yeah. So, if I may summarize, focus very heavily on the team because that’s what’s going to keep your company, determine if the company is successful or not, spend less time fighting over early-stage equity, and focus on getting the best people and motivating them as much as you can, and not everybody needs to be the same technical mindset. You need to have a diverse set of brains trying to make your company successful.
S3: 19:23	[MR] That’s right. I usually even at this stage when I start a company, people are different that they would have different value. I go equal ownership actually in those companies. That’s basically the way I have done, and I’m interested more having in ownership
	I put the money in, so, and get some preferred share. But I think you should see yourself on how you can bring value to the company and work hard for the share that you have got. I mean, of course, some people, they feel that they have got less, or they have got more, but the goal of a company is not to financially address some needs of people. The goal of the company is to get their product out, and you really need to have the right people.
S2: 20:15	[IL] Yes. I’m thinking about the company that the company, if you’re the founder, the company is not you. You work for the company, and the company is really an effort of all of these people. That was another kind of thing I had to learn. What do you think in the greater scheme of things? So right now, obviously, there’s all sorts of tumult going on, but innovation is going so fast these days driven by what seems like millions of startups just all over the place. What do you think– what are you seeing today sort of in the larger scale of things that gets you the most excited? What do you think is the most exciting change that biotech is bringing to the world these days?
S3: 20:57	[MR] I think the sheer amount of data that we have. We have entered into a data-driven biology. It was based on your gut feel a couple of decades ago, but probably even a decade ago, but now we are getting into a data-driven biology, so. And AI is playing a huge factor in it. So I think that’s one of the most exciting area of AI. So if you would bring an AI person to biology, so they are not going to be that actually, right, but if you would bring a genomics guy with AI background so they understand the complexity, and of course, they could have other AI people, but you really need to have a good understanding about the complexity of the biology. Still, your gut feel matters a lot, but we are actually using a lot of data to validate what our gut feel is telling us.
S2: 22:00	[IL] Cool. Yeah. Yeah, definitely. So we’re up in Seattle, which is full of tech AI folks. So we definitely understand the power of that technology has been as well, sort of demonstrated. So we have some questions from the audience. And I think, Kayla, are you going to do them? I do them. Okay. I haven’t been reading the questions along the way. So Mostafa, you mentioned AI, but beyond just AI itself, could you list maybe some of the most important kind of must-know skills that a bio [informatician?] should sort of know in order to effectively transition to biotech? A lot of the– a lot of the point to this event is really to kind of address people who are in academia, like, what’s the best way to get into biotech? What are the most important skills? What should they work on?
S3: 23:07	[MR] So you’re asking specifically about the buying from my people, so is that correct?
S2: 23:13	[IL] More or less, yeah.
S3: 23:14	[MR] Yes, the AI is amazing. But of course, love analytical tools and coding, those are great to know, but one thing that I’ve been super impressed with is from the people that they understand the [inaudible] models. So you’re basically, you look at– to begin with, you have to produce a good set of data. If you don have a lot of junk, of course, you’re going to produce junk. So if you have a noisy model, so it will be quite difficult to analyze the noisy biology. But I’ve seen some people that they have very unique thinking on how they set up their noise model and how they treat noise and they classify that. And those are the people that I saw, well, they are making a huge, huge impact. And that was exactly how when we started GRAIL. GRAIL is a super noisy data and you are going to cancer screening, which would require detection of radio frequency of 1 in 10 to 100,000. And you have basically a tiny tumor, like a chickpea size, and that one is basically you are going to put that in the context of all the tissues in the body. So the DNA that’s secreted from that little, small tumor, you don’t know from there in the body it is, and, of course, it’s circulating among all the other free DNA in the blood. So how would you go about identifying that needle in the haystack? And that, I saw that people that they had a good understanding about the noise model, they were the one that made a huge impact. Otherwise, we were dealing with a lot of noisy data. It was very difficult to interpret. I think people that they have got good signal processing background and they have good understanding about biology and with the noise could potentially have come from, those are the ones that they have an upper hand in the industry.
S2: 25:46	[IL] Cool. Here’s another good one. How do you see– how do you see data security, data sharing, data ownership issues getting out because, again, now that there’s a huge influx of data coming in, what happens in terms of security? What happens in terms of privatizing?
S3: 26:06	[MR] That’s a very, very, of course, good question and a very important question, because health data, if you go to the dark web, I haven’t been there, but my whole day tell about the health data in the dark web actually, full disclosure. In the dark web actually one of the highest money you can get is for the health data, and definitely, there’s security and privacy of the data are of critical issues. But from what I’m seeing and hearing from the experts is that they tell that [X-rayed?] are good, advanced technology that are coming into space that could address the issue. The vulnerability’s mostly at the junction point where we have API. Of course, you could have a secure system, but as soon as you want to go from point A to point B at the junction, so those are the places that you have vulnerability.
S3: 27:16	[MR] And what I’m hearing is that the type of encryption like [morphy?] encryption and those kind of things actually are becoming a reality, so and it’s becoming– I mean, it was not a reality a year or two years ago, but now I see that actually people they have started using those things, and they could address some of the security issues. But absolutely, it’s critical to think about it. If you are a data company, you really need to make sure that you have full privacy and full security of the data.
S2: 27:54	[IL] Great. Well, thank you so much. That’s all the time we have for this segment. Thank you for participating. It’s been really great to hear your insight.
S3: 28:04	[MR] You’re welcome.
S2: 28:07	[IL] And I hope you have a lot of cool startup stories to tell in the future as well. Maybe we’ll hear about them. Maybe in the future you’ll come back.
S3: 28:15	[MR] Hopefully.

Phase Genomics Developing Cost-Effective Genomic Tools to Track and Understand Crop Disease with New Funding

Posted on February 25, 2021 by Kayla Young - Genomics, Hi-C

The impact of fungal rust pathogens is measured in tens of thousands of acres of lost crops annually and an increasingly vulnerable supply chain. An outbreak of oat crown rust devastated yields in South Dakota and Minnesota, wiping out as much as 50% of the crop in 2014 alone.

Current surveillance rust collections are not enough to develop effective countermeasures against fungal rust pathogens such as oat crown rust, wheat stem rust, and many others. Now Phase Genomics has received a National Institute of Food and Agriculture grant to develop a cutting-edge genomic diagnostic test to affordably identify existing and novel strains of fungal pathogens in the wild.

Phase Genomics’ proprietary technology allows it to generate full chromosome-scale rust genomes and separate their constituent sub-genomes, creating a unique genomic resource that will provide the sequence information needed to identify, track, and study virulent fungal strains. Since the platform will employ machine learning tools combined with genomics, as the dataset grows it will potentially enable scientists to proactively predict the virulence of new wild strains before they have a chance to decimate crops. Costs from traditional diagnostic techniques are expected to be reduced by up to 90%.

The same proven and proprietary technology was demonstrated by researchers producing a first-of-its-kind reference genome for the wheat stem rust pathogenic strain Ug99. The economically destructive pathogen with a dikaryotic genome structure (two independent nuclei) is a crop killer on several continents.

The new ability to leverage high-quality genomic information from sets of rust strains will transform researchers’ ability to diagnose, track crop disease spread and understand the evolution of fungal virulence.

Learn more about leveraging this technology in your agricultural research here.

Year in Review: New Products, Projects, & Partnerships Amidst a Pandemic

Posted on January 4, 2021 by Kayla Young - Hi-C

Greetings from, mercifully, the beginning days of 2021.

As the world reels from Covid-19, all of our personal and professional lives have all been turned upside down. Despite this challenging environment, Phase Genomics has celebrated some big wins in 2020, amidst a tumultuous year. This year’s successes include releasing a dedicated Proximo Hi-C Kit for fungal samples, receiving $5.4M in grants, and announcing our licensing agreement with QIAGEN, among others. We want to thank our clients for their support, our incredible employees for their hard work, and the adaptability of leadership to maintain business operations throughout this unpredictable year.

Here’s a quick look at our highlights from 2020:

New Products

Grants

- “Phase Genomics Wins $1.5M for Proximity Ligation-Based AMR Tracking“- GenomeWeb
- “Phase Genomics lands $3.9M in grants to improve testing for chromosomal abnormalities“- Geekwire

Awards

- 2020 FLC Midwest Excellence in Technology Transfer Award
- 2020 Cannabis Innovation Award from The Cannabist Scientist

Publications

- 12 Metagenomics Publications
- 29 Genome Assembly Publications

In the News

- “Famine in Africa and the Middle East? Devastating stem rust fungus threatens global staple crop, but genomic solution may finally be on the horizon”- Genetic Literacy Project
- “University of Washington spinout Phase Genomics promoted Kayla Young to chief operating officer”- Geekwire
- “‘Start innovating like crazy’: Fast-moving genomics startup turns to R&D to navigate the pandemic”- Geekwire
- “Phase Genomics and Qiagen partner to bring Hi-C epigenetics solutions to US market“- GenomeWeb
- “Genomics Analysis Moves to the Next Level“- Genetic Engineering and & Biotechnology News

Genome Startup Day

Baby Boom!

- Welcomed three new Phasebabies to the Phase Genomics team!

See You (Fingers Crossed) in 2021!

In 2021, we are hopeful that we will be able to return to conferences and see our friends and clients in person. We plan to release exciting new features on our ProxiMeta microbiome platform, grow our team, and continue to serve all of our clients with cutting-edge tools, including some upcoming surprises. Follow Phase Genomics and the latest developments in our ecosystem in real-time on Twitter and LinkedIn or by subscribing to our quarterly newsletter – PhaseBook.

We hope you had a safe, healthy, and relaxing Holiday Season and we look forward to seeing you in the New Year!

Phase Genomics and QIAGEN Partner to Bring Hi-C Epigenetics Solutions to U.S. Market

Posted on October 29, 2020 by Kayla Young - Hi-C

In the last few years, Hi-C technology has grown in popularity within the epigenetics community. The chief application this proprietary method is to measure the three-dimensional architecture of genomes to better understand complex nuclear dynamics. Being a leader in this space, we at Phase Genomics seek to maximize the commercial footprint of our technology. As interest in this method has increased significantly, we have partnered with QIAGEN to increase its commercial availability. Read about the new EpiTect Hi-C kits available now through our collaborative effort.

QIAGEN expands its existing Epigenomic offering in the United States with Sample to Insight solution for Hi-C NGS analysis

• EpiTect Hi-C Kit helps researchers to better understand key aspects of long-range genome architecture
• License agreement enables QIAGEN to sell Phase Genomics’ proprietary proximity-ligation technology in the United States research market
• Adds to QIAGEN’s epigenomic capabilities in identification of individual methylation marks and histone modification at the nucleotide level

Hilden, Germany, and Germantown, Maryland, October 29, 2020 – QIAGEN today announced a non-exclusive agreement with Phase Genomics, Inc. to license specific patents to sell its EpiTect Hi-C kits in the United States. Through this agreement, QIAGEN now has access to support chromatin research in the largest research market in the world.

Chromatin conformation research, including chromatin conformational analysis (Hi-C), is an emerging and growing market area of genomic research that is refining our knowledge of the interconnectivity and organization of the genome. Hi-C has become a vital tool for understanding the structures and organization associated with cell biology. The EpiTect Hi-C Kit provides a simplified, single-box solution, requiring less than 250,000 mammalian cells to generate sequence-ready libraries.

“QIAGEN’s EpiTect portfolio has until now focused on identifying individual methylation marks and histone modification in the genome at the nucleotide level,” said Kerstin Steinert, Vice President of Product Development & Research Services at QIAGEN. “With the QIAGEN EpiTect Hi-C Kit, we are providing an end-to-end solution to study the 3-D genome and identify larger structural aspects of chromatin conformation and genomic architecture.”

“This partnership demonstrates a strong confidence in the value of Phase Genomics’ technology. Now, scientists studying epigenetics can more fully understand changes in genome architecture that may trigger disease in ways that are more cost-effective than ever before,” said Ivan Liachko, PhD, Founder and CEO of Phase Genomics. “Our Hi-C proximity-ligation technology, now available through QIAGEN, will help accelerate treatments to market and discover new paths toward the prevention of disease.”

In keeping with the QIAGEN commitment to provide Sample to Insight solutions, customers will have two options to analyze data from experiments. The EpiTect Hi-C Portal, located on GeneGlobe Data Analysis Center, provides multiple analysis types, including contact matrices and maps. In addition, Phase Genomics will provide a comprehensive suite of computational analytic services for Hi-C data analysis to QIAGEN EpiTect Hi-C Kit customers through a cloud-based bioinformatic platform that employs novel computational approaches and algorithms to analyze and interrogate proximity ligation (Hi-C) data.

Unlocking New Frontiers in our Understanding of Human Disease through Deep Learning and Three-Dimensional Genomics

Posted on July 16, 2020 by Maryke Appel - Genomics, Hi-C, Proximo, Science

By Ivan Liachko, Ph.D – Founder & CEO, Phase Genomics

As we enter the era of personalized medicine, novel genomic technologies are enabling a much deeper understanding of the biology of individual people. Such knowledge improves our ability to detect and diagnose diseases, offering personalized treatments that leverage each person’s unique genetic makeup for maximum safety and efficacy. However, human biology is very complex, and – despite decades of advances in DNA sequencing and analysis methods – we have yet to realize the full promise of genomics-enabled personalized medicine.

To truly realize the benefits of genomics in healthcare, we must go beyond basic sequencing efforts that look at mutations or gene expression patterns, and study the higher-order structure of the genome, i.e. its organization and shape. These are known to drive many kinds of human diseases including cancer, autism, and infertility.

Phase Genomics has commercialized a new genome sequencing technology that enables us to look beyond the genetic code and characterize the higher-order organization of genomes. This technology, called “proximity ligation“, not only detects sequence differences. It enables us to identify and characterize changes in genome structure called “structural variation”, as well as patterns in the three-dimensional organization of the genome.

Phase Genomics has developed and commercialized several products that leverage proximity ligation in different research contexts. We are now combining the technology with deep learning to deliver new research and diagnostic capabilities for human disease.

The new, revolutionary approach currently in development at Phase Genomics combines deep learning with several other supervised and unsupervised machine learning methods to identify, recognize, and contextualize structural variants or other perturbations in a human genomic sample, based on recognizing structural signatures hidden deep within the proximity ligation data. Once variants are detected, they can be connected to the body of research and medical literature to provide actionable clinical information. The high-throughput nature of both the biological and computational underpinnings of this technology means that the approach is not only more effective than other methods; it is also faster, cheaper, and more scalable.

Phase Genomics will be announcing additional products delivering new dimensions of genomic insights into human disease in the coming months. For now, the research, development, and testing continue.

Built on Amazon’s AWS cloud computing and machine learning technology, and in consultation with 1Strategy – a leading cloud architecture and development firm – Phase Genomics’ proximity ligation plus deep learning technology is poised to open new frontiers in human clinical diagnostics.

Breaking the Mold: New Tech Sheds Light on 5 Mysteries of the Fungal World

Posted on February 10, 2020 by admin - Hi-C, Proximo

This month Phase Genomics is celebrating #FungusFebruary by highlighting some of the unique capabilities of our Hi-C technology to solve age-old mysteries in the world of fungal genetics and deliver new potential for researchers to understand fungi, all while helping solve global crop crises and develop new groundbreaking pharmaceuticals.

While we wield the power of genomics to explore the wonders of fungi today, a few centuries ago people dismissed them as just weird plants. Eventually microscopes and anatomical studies revealed fungi as a distinct flavor of life — some varieties quite tasty — but educational experts today continue to bemoan the lack of lessons on fungi in biology curricula, and research on fungi — even those that cause disease — lags.

As a result, scientists lack much basic information on the genetics, life cycles, and reproductive habits of many fungi — even though members of this kingdom could help address a bevy of challenges in food and energy production, illuminate the evolution of complex life and even shelter us on Mars.

Genome studies on fungi of all stripes can resolve evolutionary relationships and ecosystem dynamics, identify metabolites of commercial and medical interest and — for fungi that cause disease — reveal biochemical and genetic targets to help us fight pathogenicity.

Like their animal and plant cousins, fungal genomes also have their challenging parts, including repeats, duplications and structural elements that complicate both sequencing and assembly. Recently, the chromosome conformation method “Hi-C” and advances in next-generation sequencing have helped untangle some of these sticky genomic knots, and show promise in taming genomes across this diverse and neglected kingdom of life.

1. High-resolution mapping of centromeres

Hi-C’s power lies in its ability to identify regions of the genome that reside in close proximity to one another in the nucleus — information that essentially captures the 3D organization of the genome. But Hi-C doesn’t just identify where particular chromosomes reside within the nucleus. It can also help identify functional elements in genomes that are difficult to identify in other ways.

That is what two groups of researchers (from the Pasteur Institute and the University of Washington) did when they used Hi-C to track down functional elements in yeast genomes — centromeres and rDNA clusters — both of which are typically repeat-rich and difficult to identify without laborious experiments involving functional assays or mapping the binding sites of rare centromere proteins. In fungal species, centromeres are held tightly together at the spindle pole body, and the team used this shared proximity to identify centromere locations in the genomes of numerous yeasts (and subsequently other fungi), despite not knowing their centromeric DNA sequence. Ribosomal DNA clusters similarly congregate in yeast nuclei, which one team exploited to identify their positions in Debaryomyces hansenii.

2. High-quality genomes illuminate biochemical pathways

Fungi harbor a wide array of genes for synthesizing secondary metabolites, which range from harmful toxins to helpful pharmaceuticals. In fungi, genes for synthesizing secondary metabolites tend to occur in clusters, which are also thought to be sites of rapid evolution.

Phase Genomics worked with a University of Minnesota-led team and used Hi-C to generate high-quality genomes of six strains of Tolypocladium inflatum, an insect pathogen that has already given us the immunosuppressant drug cyclosporin. The new assemblies revealed major differences in secondary metabolite production between T. inflatum strains, including novel clusters, transpositions and clusters that may be involved in toxin synthesis. The bevy of discoveries from these assemblies showed how recombination can drive significant divergence even within a single species — and how important it is to build multiple high-quality genome assemblies that can capture that diversity.

3. Fungal dikaryons and the hidden nuclear dance

The genetic differences between strains also apply to pathogenic fungi, like the stem rust, which parasitizes wheat. Phase Genomics partnered with a team led by scientists at CSIRO in Australia to apply Hi-C to stem rust – the particularly deadly scourge Ug99. Like many fungi, stem rust genomes are divided between two haploid nuclei. The team used Hi-C data to assemble complete haplotypes for both haploid genomes of both strains, and discovered that Ug99, a recent arrival that is decimating whole fields of wheat in Africa, has an unexpected origin: The strain arose through “somatic hybridization,” when hyphae from two strains exchange haploid nuclei. This may explain the strain’s sudden rise and deadly wake, and gives scientists new genomic information to understand Ug99’s virulence and identify weaknesses that could give wheat a leg up.

4. Hybrids, beer, and fungal metagenomics

The ability to separate two nuclei from within the same cell can be extended to more complex samples. Yeasts, which are integral players in brewing, will often hybridize to form new species containing genomes from two organisms at once (the famous lager-producing yeast Sacharomyces carlsbergensis is one example of such a hybrid). But in a mixed microbial community, such as beer, wine, or a microbiome sample, how can DNA sequencing detect which genomes co-exist within the same cell? One special power of Hi-C is that it traps sequences that are within touching distance of each other, and therefore must come from inside the same cell. The Dunham lab at the University of Washington used this property to analyze an open-fermentation beer from a local brewery. The exciting result was that they were able to discover a new hybrid yeast, later named Pichia apotheca, using Hi-C data to identify it as a hybrid bearing two genomes from related organisms. This new hybrid species has since been used by home-brewers to ply their craft and gives beer a very unique flavor.

5. The Epigenetics of Symbiosis

Nature has plenty of examples of plants and fungi getting along. One of them is Epichloë festucae, a filamentous fungus that has evolved a symbiotic relationship with certain grass species. When Phase Genomics worked with a Massey University-led team, they discovered that E. festucae’s genome carries hallmarks of this symbiosis. The analysis of Hi-C data revealed that important genes are clustered into blocks separated by repeat-rich regions. Hi-C and RNA-seq data together showed that genes within the blocks have similar expression patterns — indicating that genes needed for symbiosis with their grass hosts tend to cluster together in the same blocks.

Looking Forward

Cutting edge genomic technologies like Hi-C have the potential to keep making up for lost time and reveal even more intimate details of the hidden lives of fungi. This #FungusFebruary, it’s worth asking: What other mysteries about this long-overlooked kingdom are worth solving?

2019: A Year in Review with Phase Genomics

Posted on January 9, 2020 by admin - Hi-C

From scaling up the ProxiMeta Platform to publishing numerous Hi-C papers, Phase Genomics has had a year filled with new products, new discoveries, and new applications. Proximity ligation technology is continuing to fuel genomic and metagenomic research. Here is a brief recap of newsworthy items from 2019.

Metagenomics Publications

MAY 30, 2019

The ISME Journal

Linking the Resistome and Plasmidome to the Microbiome »

AUGUST 2, 2019

Genome Biology

Assignment of virus and antimicrobial resistance genes to microbial hosts in a complex microbial community by combined long-read assembly and proximity ligation »

SEPTEMBER 7, 2019

Frontiers in Microbiology

Degradation of recalcitrant polyurethane and xenobiotic additives by a selected landfill microbial community and its biodegradative potential revealed by proximity ligation-based metagenomic analysis »

Genome Assembly Papers

FEBRUARY 7, 2019

BMC Genomics

Chromosome rearrangements shape the diversification of secondary metabolism in the cyclosporin producing fungus Tolypocladium inflatum »

FEBRUARY 13, 2019

Journal of the American Society of Nephrology

Integrated Functional Genomic Analysis Enables Annotation of Kidney Genome-Wide Association Study Loci »

MARCH 18, 2019

BioRxiv

Exceptional subgenome stability and functional divergence in allotetraploid teff, the primary cereal crop in Ethiopia »

APRIL 15, 2019

BMC Genomics

A hybrid de novo genome assembly of the honeybee, Apis mellifera, with chromosome-length scaffolds »

JUNE 3, 2019

GigaScience

A chromosome-scale assembly of the major African malaria vector Anopheles funestus »

SEPTEMBER 16, 2019

BioRxiv

A de novo chromosome-level genome assembly of Coregonus sp. “Balchen”: one representative of the Swiss Alpine whitefish radiation »

SEPTEMBER 16, 2019

BioRxiv

Chromosome-scale de novo assembly and phasing of a Chinese indigenous pig genome »

OCTOBER 1, 2019

Communications Biology

Divergent evolutionary trajectories following speciation in two ectoparasitic honey bee mites »

OCTOBER 1, 2019

KeyGene

KeyGene delivers first-ever fully phased red raspberry genome »

NOVEMBER 8, 2019

Nature Communications

Emergence of the Ug99 lineage of the wheat stem rust pathogen through somatic hybridisation »

NOVEMBER 25, 2019

New Zealand Journal of Crop and Horticultural Science

A whole genome assembly of Leptospermum scoparium (Myrtaceae) for mānuka research »

DECEMBER 12, 2019

BioRxiv Preprint

Assembly of a young vertebrate Y chromosome reveals convergent signatures of sex chromosome evolution »

DECEMBER 20, 2019

BioRxiv Preprint

Identifying the causes and consequences of assembly gaps using a multiplatform 2 genome assembly of a bird-of-paradise »

Phase Genomics in the News

JANUARY 22, 2019

Market Insider

Medicinal Genomics Releases Industry’s First Comprehensive Cannabis Reference Genome »

JANUARY 23, 2019

Podcast: How to Live to 200

Dr. Ivan Liachko on Cat Poop and the Secrets of the Microbiome »

FEBRUARY 25, 2019

Genome Web

Phase Genomics wins $200K grant to develop microbiome discovery technology »

MARCH 6, 2019

Podcast: How On Earth

Dr. Ivan Liachko on Tagging the Bugs that Carry Antibiotic Resistance »

APRIL 5, 2019

ZME Science

Saving the Honeybee: Can New Genomic Clues Help Solve the Colony Collapse Mystery? »

APRIL 25, 2019

Genes to Genomes

Chromosome-scale genome assembly gives African mosquito and malaria vector fewer places to hide its secrets »

MAY 9, 2019

The Genetic Literacy Project

Dissecting the cannabis genome in the quest for a better bud and effective medicines »

JUNE 20, 2019

New Product

Phase Genomics Accelerates Microbiome Discovery and Antibiotic Resistance tracking with New ProxiMeta™ 8-Pack Including Bundled Analysis »

AUGUST 6, 2019

New Application

Phase Genomics’ Platform Links Viruses and Antibiotic Resistance Genes to the Microbiome in Study of a Highly Complex Microbial Community »

SEPTEMBER 23, 2019

Xconomy

An Entrepreneur’s Quest to Make Seattle a Genome Sciences Hub »

OCTOBER 22, 2019

Biodiesel Magazine

Phase Genomics awarded DOE grant for algae biofuel research »

Blog Posts

JANUARY 13, 2019

The Era of Platinum Genomes Has Arrived »

APRIL 5, 2019

Q&A with Co-Authors About Bees, Mites, and Their Genomes »

APRIL 25, 2019

Q&A with Co-Author Dr. Nora Besansky about Malaria, Mosquitos, Insecticides and Adaptations! »

MAY 8, 2019

The Highest-Quality Genomes: Q&A on Cannabis Genomics »

JUNE 3, 2019

Project ProxiMeta: 2019 Metagenomics Award »

JUNE 19, 2019

Dr. Ivan Liachko, LinkedIn Article: No longer beyond the horizon: Capturing the flow of antibiotic resistance genes through the microbiome with next-gen proximity ligation sequencing »

AUGUST 7, 2019

Dr. Ivan Liachko, LinkedIn Article: A more complete microbiome: Using proximity-ligation next generation sequencing to uncover host-viral links in complex microbial ecosystems »

SEPTEMBER 3, 2019

Choose This Year’s Metagenomics Award Winner »

OCTOBER 28, 2019

Phase Genomics Transformative Genome Phasing Tool (FALCON-Phase) Now Compatible with Nanopore Sequencing »

OCTOBER 29, 2019

Dr. Ivan Liachko, LinkedIn Article: Help Build Genome Startup Day 2020 »

Phase Genomics Events and Awards

SEPTEMBER 23, 2019

Genome Startup Day

Phase Genomics hosted the inaugural Genome Startup day this year with an attendance of over two hundred scientists, students, and investors.

SEPTEMBER 11, 2019

Project ProxiMeta Winner

Dr. Ben Tully: The Complete Hydrothermal Microbial Metal Metabolism »

Q&A with Co-Authors About Bees, Mites, and Their Genomes

Posted on April 5, 2019 by admin - Hi-C, Proximo, Science

Co-authors Dr. Alexander Mikheyev of the Okinawa Institute of Science and Technology and Dr. Jay Evans from the U.S. Department of Agriculture’s Bee Research Laboratory had such great answers that we wanted to share some of them. This research was also featured in ZME Science.

Why is it important and useful to have a high-quality genome for Varroa species? Is there any combined value with the recently published bee genome?

Dr. Mikheyev: Understanding the mechanisms of parasitism requires detailed information about the organization of the genome. Many recent ideas for fighting Varroa rely on molecular tools, which in turn rely on genomic data. Furthermore, a good genome enables us to understand the coevolutionary interactions between mites and the bees. For now, our studies are focused on understanding how the mite has evolved to become a better parasite. However, my lab is also looking at the bee side of the coevolutionary interaction. Having high-quality genomes for both will allow us to identify genomic regions and genes involved in coevolution.

Why did you choose to use Hi-C? Why did you need chromosomes for your genome assembly?

Dr. Evans: From prior genome efforts, we had no information on the physical positions of mite gene features. Now with these in place, we can leverage synteny information from other arthropod genomes and narrow searches for some hard-to-find proteins like olfactory receptors, which often occur in clusters. Generally, the improved genome helps us know what might be unique to Varroa — and therefore a novel clue into their biology and control.

Dr. Mikheyev: One element of this study was to look at patterns of gene duplication, which could indicate diversification of particular gene families. Having a contiguous genome allows us to better localize these duplications and confirm that the different copies are homologous. In the future, when we’ll be looking at signatures of selection, a really powerful approach is to identify genomic regions with reduced genetic diversity. Having adequate chromosomal scaffolding will be essential there.

What genomic clues were found in the two Varroa species that may contribute to parasitism?

Dr. Evans: We found a clear set of genes for the proteins — olfactory receptors and others — that these mites must be using to react to their bee hosts. Hopefully, knowing these proteins will lead to smarter controls and insights into why each species maintains a specific host preference.

Dr. Mikheyev: For us, the most striking finding is this: The evolutionary trajectories of both mites, despite their similarities and close relatedness, were completely dissimilar. At this stage, it is still a bit hard to tell specifically what the selective pressures were and what the mites are adapting to. Curiously, in both species, genes involved in stress tolerance and detoxification were already under selection. This most likely happened before they ever faced miticides and suggests that they may have pre-adapted strategies for dealing with our chemical warfare strategies against them. We hope to tackle this in an upcoming study looking at population-level differences between mites adapted to original and novel hosts.

How do you hope these genomes will be used to help save honey bees?

Dr. Evans: Prior genome drafts had enough gaps that we missed candidate proteins for mite control. These mite genomes will lead to focused efforts to target pathways or traits not found in bees by techniques like small molecules, biological controls, and RNA interference.

Dr. Mikheyev: They can be used to develop new strategies for Varroa control. Also, in upcoming studies looking at how mite populations are adapted to original vs. switched hosts, we hope to identify genes and genomic regions that are specifically important in host switches.

Is there any genomic evidence that the western honeybee could be developing resistance to these pests?

Dr. Evans: Yes. Some bee breeders are targeting these traits, from behaviors to virus resistance. A recent, improved assembly of the honey bee genome — aided in part by Hi-C sequencing — is being used for trait identification and marker-assisted breeding right now.

Dr. Mikheyev: They most definitely are. Intriguingly, wild populations of honey bees seem to evolve tolerance to the mites relatively quickly. In one of my favorite studies, a USDA-monitored population in Louisiana first saw high mortality upon the arrival of Varroa, but a few years later colonies lived even longer than before. There are resistant populations known in the U.S. and in Europe, and resistance is a trait that can be selected. How this adaptation takes place in the bee is really interesting, and something we’ll continue to look into.

Isolating Varroa mites from bees involves a creative use of powdered sugar. How do you think this technique came about?

Dr. Mikheyev: We don’t know. The papers describing this method are pretty prosaic. It seems that in the late 1980s, wheat flour was used to control Varroa by knocking them off the bees — and eventually, someone tried sugar.

Dr. Evans: Since they’re attached to their bee hosts, researchers have used a variety of ‘irritants’ to get mites to fall off. Powdered sugar is safe for the bees and might even be an extra calorie boost. The bees pull sugar from each other and the mites fall off — mostly because of the sugar itself, but also because the grooming bees find them.

What is your favorite weird food that involves honey?

Dr. Mikheyev: It’s not really a food since it is honey, but I love the fact that the giant honey bees of Nepal make psychedelic honey from Rhododendron flowers. The story is worth tracking down for no other reason than the dramatic photos of the men that harvest this honey from sheer cliffs.

Dr. Evans: Honey lemonade. Sorry, I am required by my kids to not say weird things.

The Era of Platinum Genomes Has Arrived

Posted on January 13, 2019 by admin - Genomics, Hi-C, Proximo

Phase Genomics is dedicating the rest of this month (January, 2019) to the beginning of “The Era of Platinum Genomes” to celebrate recent advancements in genome assembly; researchers now have the ability to generate chromosome-scale, fully-phased diploid genome assemblies for any species by combining two technologies: long-read sequencing data from PacBio and Phase Genomics’ Hi-C.

At the end of this month, we will be giving away a “Platinum Genome Project” which includes a full Hi-C service or kit project to an attendee at the International Plant and Animal Genome Conference 2019 (PAGXXVII). This project includes using Proximo Genome Scaffolding to generate chromosome-scale scaffolds and FALCON-Phase to phase haplotypes across the entire genome. Attendees can enter the raffle by stopping by our booth (#208) throughout the conference, or enter using the form at the bottom of this page. Stay tuned for the winner announcement on January 31st, 2019 by following our twitter account @PhaseGenomics. Offer subject to sweepstakes terms. No purchase necessary.

WHAT ARE PLATINUM GENOMES?

Much like the music industry ranks albums as gold or platinum, genomes can also be classified using the same terminology based on the completeness of the assembly and quality of phasing (i.e. haplotype resolution). High-quality genomes have complete chromosomes and haplotype resolution in critical sections of the genome qualify as a “gold genome,” whereas “platinum genomes” are assemblies with full chromosome scaffold and haplotypes resolved across the entire genome.

Since publishing the first human genome assembly, research from the 1000 genomes project and other groups have created several platinum human genomes to represent different human populations. In fact, one of our latest projects in collaboration with PacBio, generated the most contiguous, haplotype resolved, human genome to-date. However, there are only a few platinum genomes for non-human organisms, as scaffolding and haplotyping entire genomes is very labor-intensive using standard tools. We are excited to offer tools such as Proximo and FALCON-Phase to help usher in the era of straightforward platinum genome assemblies to researchers studying plants and animals.

RESOURCES

Phase Genomics Workshop at PAGXXVII: Add it to your schedule.

Standard Projects Outline

Phase Genomics Platinum Genome Sweepstakes guidelines

A Year in Review with Phase Genomics

Posted on January 2, 2019 by admin - Genomics, Hi-C, Random

From releasing the world’s first Hi-C kits for plants and animals to publishing the most contiguous human genome assembly to date, Phase Genomics has had a year filled with new papers, new discoveries, and new applications. Proximity-Guided Assembly is continuing to fuel genomic research and here is a brief recap of newsworthy items in 2018.

PAPERS

Genetic Engineering and Biotechnology News (GEN), November 14th, 2018
Precision Medicine Looks beyond DNA Sequences

Boise State Radio, December 18th, 2018
University Of Idaho Scientists Put Crosshairs On Antibiotic-Resistant Bacteria

Hi-C Technology Links Antimicrobial Resistance Genes to the Microbiome

Posted on December 4, 2018 by admin - Hi-C, Metagenomics, ProxiMeta, Uncategorized

Antibiotic resistance is a rapidly growing global health threat as bacteria share and spread resistance genes via plasmids and other mobile genetic elements. Several teams of researchers applied a new method to understand which microorganisms house genes for antibiotic resistance within complex microbiome communities.
Read the paper, Linking the Resistome and Plasmidome to the Microbiome.

ANTIMICROBIAL RESISTANCE ON THE RISE

According to the World Health Organization, antimicrobial resistance (AMR) in microbial pathogens is expected to take 10 million lives by 2050 if there are no new pharmaceutical or technological advancements dedicated to combating this pressing problem. For almost a century, medicine has made remarkable impact on human life by using antibiotics to treat infections, but this has led to a very concerning overuse problem, stoking an arms race between antibiotics and the pathogens they target. The CDC points out that at least 30% of antibiotic prescriptions are unnecessary and there is a massive contribution to antibiotic overuse in the food and agriculture industry where each year 130,000 tons of antibiotics are given to food animal livestock. Both of these problems correlate with the rise of AMR.

Though there are naturally occurring antibiotic-resistant bacteria, there are two mechanisms by which bacteria can acquire antimicrobial resistance genes (ARGs) and become resistant: 1) through spontaneous genetic mutations and/or 2) by acquiring genetic material from other microbes via plasmids, viruses, or other means of horizontal gene transfer. Due to the evolutionary pressure exerted on microbes by antibiotic overuse, pathogens resistant to these antibiotics within our body, hospitals, and the environment become reservoirs of transmittable AMR genes that can rapidly spread and accumulate within a single microbe contributing to the emergence of multidrug-resistant microbes commonly known as superbugs.

PROXIMITY-LIGATION (HI-C) LINKS ARG AND PLASMIDS TO THEIR HOSTS

One of the biggest obstacles faced by scientists when studying AMR is the inability to determine which microbes are carrying and spreading specific ARGs. Because these genes often travel on mobile elements, they can move dynamically between different species and can therefore be found in numerous organisms without one clear parental host. When attempting to sequence the DNA of a mixed microbial sample, all the DNA is purified from all the cells at the same time and the host-plasmid connection is severed, making it nearly impossible to determine where each mobile element came from or if they were shared among several species. In this newly published paper, researchers highlight a novel method for linking ARGs and other mobile genetic elements to their hosts directly from microbiome samples using the latest version of the proximity-ligation (Hi-C) data analysis tool, ProxiMeta Hi-C.

Phase Genomics CEO, Dr. Ivan Liachko, describes how our Hi-C platform solves one of microbiologists’ greatest problems pertaining to the linking of plasmids with their hosts.

Hi-C utilizes in vivo proximity-ligation which can assemble complete genomes down to the strain-level directly from mixed-population samples as well as physically links plasmids/ARGs to their host. This method is particularly useful for researchers studying the “dark-matter” of the microbiome because the method does not require culturing nor a priori information about a sample.

USING HI-C TO TRACK ARGs IN THE MICROBIOME

Lead author Thibault Stalder from the University of Idaho used the ProxiMeta Hi-C kit on a complex microbiome wastewater community, a suspected AMR reservoir, to learn more about which bacteria carry ARGs. After the Hi-C library was sequenced, Phase Genomics used the data to inform contig clustering of hundreds of genomes, most of which are novel, with our cloud-based software – ProxiMeta. Using the genome clusters found by ProxiMeta, the Hi-C linkages of each ARG-, plasmid-, and integron-bearing contigs to each genome were measured to determine which species physically hosted the relevant mobile elements.

ProxiMeta was able to cluster contigs into >1000 genome clusters and search for over 30 groups of ARGs, plasmids, and integrons which speed up the adaptive process of newly integrated ARGs (Figure 1, circle plot). For each of these genes, we inferred hosts (Figure 2). Moreover, these organisms generally belonged to families known to host each known gene (marked with an “X” in Figure 2), supporting the accuracy of the analysis. In the future, this information will allow us to track the spread of AMR in complex communities consisting of many diverse organisms.

Microbiome Antibiotic Resistance Genes and Plasmids

Figure 1: Hi-C linkage between ARGs, plasmid markers, and integrons among clusters belonging to Alpha, Beta, Gamma and Delta Proteobacteria.

Over 200 genome clusters had strong Hi-C links to ARGs, of which 12 had high-quality assemblies. These resultant genomes include both gram positive and gram-negative bacteria and most belonged to species that were previously unsequenced. ARGs were mostly linked to genome clusters belonging to the Gammaproteobacteria, Betaproteobacteria and Bacteroidetes (Figure 2, below).

Microbiome Antibiotic Resistance Genes AMR and Plasmids

Figure 2: Normalized Hi-C links between ARGs, plasmids, and families of bacteria.

FUTURE DIRECTIONS

This method can be useful for researchers not only studying the microbiome, but the virome as well. Phages, or viruses, also distribute genetic information amongst bacteria to influence host biology, much like plasmids. Several previous studies showed that in vivo proximity-ligation can be used to link phages with their hosts directly from mixed complex samples, much like was done with plasmids and AMR genes in this study. This information could be crucial to labs and companies that are now engineering phages that could replace the widespread use of antibiotics and combat AMR.

This year, antibiotic resistant bugs have infected more than 2 million people globally; 23,000 of those individuals will die because of our inability to fight these superbugs. By using ProxiMeta Hi-C to better understand the genomics of microbial communities suspected to be AMR reservoirs, researchers can identify ARG carriers down to the strain-level and quantify how prevalent these genes are. With further exploration, this tool could one day offer a new solution to limit the spread of these genes and reverse the trend of increasing antibiotic resistance and save lives.

BRING A HI-C KIT INTO YOUR LAB TODAY

Phase Genomics offers a wide variety of proximity-ligation products and services including Hi-C preparation kits and a range of different cloud-based bioinformatic analysis platforms. Power your microbiome research with ProxiMeta Hi-C and our easy Hi-C kits; assemble hundreds of complete genomes for novel, unculturable microbes, and associate plasmids with hosts directly from raw microbiome samples using ProxiMeta Hi-C.

Earth’s Wine Cellar: Digging into the Microbiome of Vineyards

Posted on September 6, 2018 by admin - Hi-C, Metagenomics, ProxiMeta, Uncategorized

Phase Genomics partnered with Browne Family Vineyards to begin to understand, the microbiome makeup of soils within different vineyards across the state of Washington. The findings were unveiled at the Pacific Science Center’s “STEM: Science Uncorked” winetasting event.

There are many different factors that contribute to soil composition, such as parent material, topography, climate, geological time, and the thousands of different and undiscovered microbes living in the soil—the least understood factor. In April of 2018, Browne Family Vineyards staff visited five of their vineyards, filled a bag with soil from each site, and sent it to Phase Genomics to analyze the microbiome in each of the soil samples.

SYMBIOSIS BETWEEN PLANTS AND MICROBES

Plants rely heavily on their microbiome to live, grow, and protect themselves from pathogens. One example of this symbiotic relationship is that plants release chemicals into the soil in order to attract microbes. These microbes bring nutrients such as nitrogen, iron, potassium, and phosphorus to the plants in exchange for sugar, which the microbes require to survive. Microbes also play an important role in nitrogen fixation, organic decay, and biofilm production to protect the plant roots from drought. It is evident that this symbiotic relationship between microbes and plants is critical to the health and survival of both, but further research into this complex community is inhibited by two main problems: It is impossible to isolate microbes in such a complex mix and most of the microbes have never been discovered before.

THE DARK MATTER OF THE MICROBIOME

Microbes live in communities where they rely on each other. This makes it difficult to isolate or culture (i.e. grow) microbes without killing them or altering their genetic makeup. Moreover, there can be millions of microbes living in a single teaspoon of soil, making these samples extremely complex environments. This causes most of the microbial world to be unknown, sometimes referred to as the “Dark Matter of the Microbiome”.

The most effective way to identify the microbes in the community is to look at the genetic makeup of the microbiome to try to classify microbial genomes present. Standard practices include sequencing of 16S (a hypervariable genomic region) and shotgun sequencing. By combining these standard practices with Hi-C, researchers are now able to fully reconstruct genomes from a mix because Hi-C captures the DNA within each microbe to exploit key genetic features unique to each individual in the community. The Phase Genomics Hi-C kit and software, ProxiMeta^TM, uses this information to capture even novel genomes straight from the sample without culturing—illuminating the dark matter of the microbiome.

THE PROCEDURE

Figure 1: Shotgun Sequencing Procedure and Difficulties

Once the soil samples were collected from the five vineyards, Phase Genomics produced shotgun libraries to obtain DNA from all of the microbes in each sample (Figure 1)—essentially taking the soil sample, breaking open all of the microbial cells then purifying the DNA (1.A). Since DNA is fragile, most of it gets broken into smaller pieces during this process, leaving a mix of many DNA fragments from all of the microbes that were present in the original soil sample. The fragmented DNA is then sequenced and the “sequence reads” are uploaded into a database of known microbial genomes (1.B). This database then searches for matches or “hits” to see if the reads are similar to anything in the database (1.C).

A problem with relying on shotgun data is that it’s unclear which DNA fragments belong to which microbe, thus relying heavily on computational techniques and the accuracy of the reference database for classification. This results in little improvement or clarity on the makeup of the sample, again, leaving the microbiome in the dark. Though shotgun sequencing only provides a glimpse into the microbial community, this data allows scientists to differentiate the taxonomy (phyla, genera, species) of the microorganisms living in the soil.

THE RESULTS

Shotgun sequencing identified over 10,000 different species from each of the vineyard soil samples; however, it is impossible to know if this is the true number of species because only ~ 20% of the reads matched the database, indicating ~80% was either incomplete or undiscovered (see table below).

Table 1: Vineyard Read Classification
Vineyard	Total Reads	Percent of Reads Classified	Number of Organisms Found	Percent of Unknown Organisms
Canyon	19,001,222	15.95%	10,726	73.32%
Canoe Ridge	21,214,190	17.66%	11,721	55.55%
Waterbrook	19,469,954	19.6%	10,782	50.58%
Skyfall	63,850,810	16.17%	15,101	80.08%
Willow Crest	43,941,026	17.13%	13,914	71.84%

Moreover, of assigned reads, >50% did not match to a genus or species—hinting that many of the organisms found are novel. Without digging too deep into the microbiome analysis, it is evident that the microbial makeup is different for each of the samples. Varying levels of reads from each vineyard were able to be classified (Table 1), and among the classified reads, the vineyards have 3-4 microbes that vary in abundance in common. These microbes, such as Proteobacteria, Rhizobacteria, and Actinobacteria, generally, are very common in soil.

Proteobacteria

There are obvious differences in the biodiversity of the soil samples both in number of species and relative abundance. For example, Canoe Ridge and Waterbrook samples were >20%, Delftia, while the microbes in the other vineyards were more evenly distributed, with abundance closer to 1-5%. Interestingly, Delftia, a rod-shaped bacterium, has the ability to break down toxic chemicals and to produce gold.

Actinobacteria

There are two main components that influence microbe classification in these samples: the desired taxonomy level, and the statistical threshold, or minimum number of reads, set to define it. Much like zooming in and out, the most “zoomed out” analysis is achieved by a stringent threshold and will reveal phylum, while the most “zoomed in” analysis is achieved by a more lenient threshold and will reveal genus and species

If the data is “zoomed in” further, about 37% of the microbes in each community can be identified by genus. On average, 63% of the communities do not match to a genus at all, hinting that these microbes may have never been sequenced. The most abundant microbe genera present in these samples are Bradyrhizobium, Streptomyces, and Nocardiodes.

As discussed earlier, this data highlights the issues that are present with shotgun data and the corresponding analysis: there is still far too much that is unknown. In order to better understand these samples, we also performed Hi-C on two of the samples which will be discussed in further detail in the next section.

HI-C AND FINDING NOVEL GENOMES

One thing all these soil samples have in common is that they are composed of numerous novel species. To obtain more information on the microbes present in these samples, and solve the issue discussed earlier surrounding shotgun data, Hi-C was performed on two of the soil samples, Skyfall and Willow Crest. Essentially, Hi-C assigns DNA fragments from shotgun sequencing to the correct species by connecting DNA while the cells are still intact.

Hi-C enables clustering of shotgun assemblies and subsequently yields complete genomes from a microbiome, even if the genome has never been sequenced before. With complete microbe genomes, it becomes easier to classify organisms down to the strain-level—a step even further than species. By having the genome, we can essentially read a microorganism’s blueprint and learn more about its genes, evolution, and even function once the genome is annotated.

For example, preliminary data from the Willow Crest soil sample yielded 400 different genome clusters. When compared to known bacterial genomes in the RefSeq database, which aggregates all published microbial genomic data, over half of the extracted genomes are unable to be identified at a genus level and thus likely represent newly discovered bacterial organisms.

SCIENCE UNCORKED

When the microbiome data from the vineyards were presented to the public at the Pacific Science Center, two questions consistently arose: How does this influence wine taste, and how can growers select for a healthy microbiome? These very forward-thinking questions unfortunately cannot be answered—yet.

Scientists do know that soil plays a big role in plant health, and this could in part be due to the plants’ symbiotic relationship with microbes, as discussed earlier. It has also been shown that biodiversity can benefit plants because of the diverse functions individual microbes have, i.e. with more microbes, there are more potential functions being served versus 1 microbe serving one function. However, nailing down answers to these questions will take a lot of research. With emerging technologies, like Hi-C, the answers have become much more obtainable.

Though the term “microbiome” may not be household vocabulary, many of the attendees were very aware about the role that microbes play in human health, and how they influence the world around us. It goes to show that the rapid developments in the microbiome field are reaching beyond just research and becoming more tangible for the general public. Relevant stories—like looking into the microbiome of vineyards— are helping them understand the intricate concept of microbial life.

Learn more about ProxiMeta Hi-C and the microbiome by visiting our website www.phasegenomics.com and connect with us on twitter by following @PhaseGenomics

Lil BUB Aids in Discovery of New Bacteria

Posted on August 1, 2018 by admin - Hi-C, Metagenomics, ProxiMeta, Random, Science

Published author, talk show host, movie star, musician, and philanthropist—Lil BUB has now also helped to discover novel microbial life living in her gut in collaboration with AnimalBiome, KittyBiome, and Phase Genomics. Enter to sequence your cat’s microbiome in our #Meowcrobiome twitter raffle!

We live in an era of discovery, especially as it relates to the microbiome and how microbial diversity influences our world, our health—and even our pet’s health. To better understand the microbial life of our feline friends, Lil BUB volunteered to sequence her gut microbiome. Thanks to a recent collaboration with AnimalBiome, KittyBiome, and Phase Genomics, Lil BUB helped discover 22 new microbes living in cats which, in time, could reveal new insights into cat health and happiness.

When KittyBiome started back in 2015 with an intent to understand the cat microbiome, Lil BUB’s owner Mike “Dude” Bridavsky provided a sample of her poop to be analyzed. Because of Lil BUB and over 1,000 other cats, KittyBiome’s microbial census will help us identify what microbes are associated with healthy cats and work towards helping cats with Inflammatory Bowel Disease (IBD), diabetes and other ailments likely to be associated with the microbiome.

USING GENOMICS TO FIND MICROBES

Late last year, Phase Genomics offered to analyze samples from Lil BUB and another cat, Danny (belonging to Jennifer Gardy—a microbiologist at the University of British Columbia and science TV host), using our ProxiMeta™ Hi-C Metagenomic Deconvolution platform to obtain complete microbial genomes from their samples. This method solves a huge problem in microbiome research—how to tell apart different species when their DNA is all mixed up in one sample (imagine a thousand jigsaw puzzles mixed together).

ProxiMeta Hi-C revealed about two hundred different species of microorganisms living in Lil BUB and Danny’s poop, many of which have never been seen before. The genome sequences of the microorganisms found in these samples were analyzed using our software and other microbiome analysis tools to measure the quality of the different assembled genomes and to see if those genomes matched any known microbes (Lil BUB’s and Danny’s data are available for free on our website). Without using our ProxiMeta Hi-C platform to extract these genomes, many of them would have been undetectable and gone unseen.

Phase Genomics sequenced both Lil BUB (left) and Danny’s (right) poop samples.

OVER 20 NEW BACTERIAL GENOMES DISCOVERED

Together, Lil BUB and her buddy Danny carry 22 previously undescribed bacterial species in their guts. Lil BUB’s poop sample had 13 species and Danny’s sample had 9 species that have never before been fully sequenced or characterized.

These new bacterial species mostly belong to the order Clostridiales, and the team is currently analyzing the genomes to better characterize them. This discovery will help continue to build a database that contains cat bacteria that are new to science, so we can better identify the contributions of the microbiome to various health conditions.

This cool discovery, made with the help of Lil BUB and Danny, highlights that there’s a universe of undiscovered microbial life out there. If we found 22 potentially novel species in only two cats, just imagine what else is out there, and what the implications might be for new ways to support and improve the health of our pets.

WHO ARE OUR HERO CATS?

Lil BUB is a one of a kind critter, made famous on the Internet due to her adorable genetic anomalies. She is a “perma-kitten”, which means she will stay kitten-sized and maintain kitten-like features her entire life. She has an extreme case of dwarfism, which means her limbs are disproportionately small relative to the rest of her body. Her lower jaw is significantly shorter than her upper jaw, and her teeth never grew in so her tongue is always hanging out. Lil BUB is also a polydactyl cat, meaning she has extra toes – 22 toes total! Lil BUB and Her Dude travel all over the country raising hundreds of thousands of dollars for animals in need.

Danny, an exotic shorthair with a face much like Grumpy Cat, is equally adorable. He is the companion cat of one of KittyBiome’s original researchers, Jennifer Gardy, and was one of the very first cats to lend his poop profile to the KittyBiome initiative. He is a very healthy cat and his microbial profile has helped us learn what a balanced gut in cats looks like.

WHAT’S NEXT?

Phase Genomics and AnimalBiome are eager to learn more about these newly-discovered bacterial species. They hope to work with the scientific community to analyze, identify, characterize and publish these genomes, starting with exploring their identities based on 16S rRNA and other marker genes.

HOW TO GET INVOLVED

Help characterize the new bacteria: If you know of a researcher, scientist or cat-lover who would like to help us, we are soliciting input on the analysis that needs to be done to properly characterize and publish these genomes. Participants who contribute in a substantive manner to the project will be co-authors on the publication. All data associated with the project will be deposited into publicly available databases and we will publish the findings in open access journals, so all pet lovers can read them. We will hold a raffle to award one lucky contributor a free Hi-C sample kit from Phase Genomics. If interested, contact us at team@animalbiome.com to learn more.

Name the new bacteria: We’re looking for input from the community on what we should name these 22 new bacteria, so if you have any fun ideas, please drop us an email at team@animalbiome.com. The format should follow standard practices of scientific nomenclature, so it should be constructed like this: “Clostridium _________.”

Find out what your pet’s microbiome looks like: If you’re interested in having your cat’s microbiome assessed to see how your cat’s gut compares to healthy cats, you can order a Kitty Kit – Microbiome Testing for Cats (or a Doggy Kit – Microbiome Testing for Dogs).

Submit your pet’s sample for genomic research: If you don’t win the raffle and still want your pet to contribute to scientific knowledge through the identification of new bacterial species, please contact us at team@animalbiome.com. We can provide you with the details and pricing involved for us to identify new species in your cat or dog through in depth analyses like we did for Lil BUB and Danny using the Hi-C approach pioneered by Phase Genomics, which would also result in a publication.

Improving databases of the microbiome of cats (and dogs) with new bacteria like this could help us learn more about how the gut microbiome helps support the digestive health of all pets.

ENTER YOUR CAT IN OUR TWITTER RAFFLE

Phase Genomics, AnimalBiome and KittyBiome are hosting a twitter raffle where you can enter to sequence your cat’s microbiome! All you have to do is go to either the Phase Genomics’ or AnimalBiome’s original tweet of this blog, retweet it with a picture and introduction of your cat with the hashtag #Meowcrobiome. On August 8^th 2018, we will randomly draw one (1) winner whose cat poop will be scientifically analyzed by Phase Genomics with ProxiMeta Hi-C to search for novel microbes, and three (3) additional winners whose cat poop will receive a Kitty Kit to have their cat’s poop analyzed by Animal Biome to compare their cat’s gut to healthy cat guts. Send in your cat’s poop, and you too can help discover new microbial life!

LIL BUB AND DANNY’S STORY FEATURED ON GEEKWIRE PODCAST

GeekWire discussed Lil BUB, Danny, and the new bacteria found in their poop in their weekly Week in Geek podcast. Check out the full podcast on their website (the segment begins around 22:58), or play just the segment about Lil BUB and Danny below.

A sweet new genome for the black raspberry using Proximo™ Hi-C

Posted on March 28, 2018 by admin - Genomics, Hi-C, Proximo, Science

The Black Raspberry, known for its sweetness and health benefits studied further to reveal its chromosome-scale genome.

What is a black raspberry you may ask? Jams, preserves, pies, and liqueur are just a few of the delicious products made with black raspberry. The black raspberry offers much more beyond its exquisite flavors. For instance, did you know it contains a compound called anthocyanins that is used as a dye? It is also used in anti-aging beauty products and contains compounds that may help fight cancer. The useful properties of black raspberry are encoded within the genome.

A multi-national team of scientists have built a full map of the Black Raspberry genome. Teams from New Zealand, Canada, and the U.S.A. contributed to the project led by Drs. Rubina Jibran and David Chagné. The work was published in Nature, Horticulture Research. In the project they leverage Proximo™ Hi-C to order and orient short-read contigs into chromosome-scale scaffolds.

A chromosome-scale reference genome is an important step for basic biology and for breeding programs. Breeders can use this genome while crossing plants to select for traits like color or taste. To learn more about how Hi-C technology was used to improve the black raspberry genome we contacted Dr. Chagné and Dr. Jibran for a Q&A session. We also wanted their take on the scientific value of Proximo Hi-C and to share their experiences working with us.

What is a black raspberry? How is it different from the blackberries we have in Seattle?

The black raspberry we used is no different from the ones found in Seattle. Actually, I remember seeing some black raspberries (also called black-caps) at Pike market few years ago! Washington and Oregon are the largest producers of this delicious crop. Raspberries belong to the genus Rubus, which includes red (Rubus idaeus) and black (R. occidentalis) raspberries, blackberries, loganberries and boysenberries.

There are many curious uses of black raspberries, what’s yours?

Black and red raspberries are great on top of Pavlova, alongside slices of kiwifruit. Pavlova is New Zealand’s iconic dessert served around Christmas time, which is the berry fruit season down under here.

What are molecular breeding technologies? What are some of the traits in black raspberry you’d like to breed for?

Molecular Breeding techniques use DNA to inform selection decisions. My colleague Cameron Peace from Washington State University did a very good review about the use of DNA-informed breeding in fruit tree. Plant & Food Research is leading in the use of molecular tools for breeding fruit species, for example we are using genetic markers to predict if apple seedlings carry certain loci for black spot resistance or if they are likely to be red fruited. The breeding goals for Plant & Food Research’s raspberry breeding programme are high fruit flavour, berry anti-oxidant content, pest and disease resistance and higher productivity.

The initial black raspberry genome assembly was built from short-read data. Why did you choose to scaffold the short-read contigs rather than create a new long-read assembly? Would you get chromosome scale contigs from a long-read assembly?

Actually we took both approaches and we decided we would like to see how much of the short-read assembly we would be putting together using Proximo Hi-C. A long-read based assembly will be released soon and the comparison of both assemblies will be extremely informative on what strategy to use for future assemblies of other crop species.

How did you validate the Proximity Guided Assembly (PGA) scaffolds? How did you correct errors in the scaffolds?

The PGA for black raspberry was first validated by aligning it to a linkage map and then by aligning it to the genome of strawberry (Fragaria vesca) as they have syntenic genomes.

What was the process like in working with Phase Genomics? Would you recommend them to your colleagues?

I enjoy a lot working with Phase Genomics. Black raspberry is not the first genome that we collaborated with Phase Genomics, as we had assembled genomes for kiwifruit and New Zealand manuka previously. The way we work with Phase Genomics is very iterative and they are excellent at trying new methods and assembly parameters until we are satisfied with our assemblies. Every organism has its own challenges when it comes to genome assembly and working with Phase Genomics in a very collaborative way is extremely useful. I have recommended Phase Genomics to colleagues.

New Video: From Contigs to Chromosomes

Posted on March 15, 2018 by admin - Genomics, Hi-C, Metagenomics, ProxiMeta, Proximo, Webinar

Phase Genomics CEO and Founder Ivan Liachko, Ph.D. offers an inside look at our ProxiMeta™ Hi-C and Proximo™ Hi-C technology. He explains in this 40 minute presentation how Hi-C is revolutionizing genome and metagenome assembly. Watch “From Contigs to Chromosomes” now and reach out to http://phasegenomics.com/contact-us/ with any questions.

Thanks to IMMSA for hosting this webinar.

Uncovering the microbiome: What will you do with metagenomics?

Posted on March 1, 2018 by admin - Hi-C, Metagenomics, ProxiMeta, Science

In this Nature Microbiology blog post, Mick Watson shares his journey into the depths of the rumen microbiome. Read more here to learn how Phase Genomics ProxiMeta Hi-C Metagenomic Deconvolution techniques are helping investigators advance their metagenomic research in complex samples. This study successfully assembled 913 genomes and will help to improve our understanding of the microbial population in cow rumen in an unprecedented way using these new metagenomics techniques. We look forward to seeing what else comes from Microbiome 2.0. and are proud to be a part of this impressive piece of work.

Hundreds of Genomes Isolated from Single Fecal Sample with Hi-C Kit

Posted on October 18, 2017 by admin - Hi-C, Metagenomics, ProxiMeta, Science

A Phase Genomics Hi-C kit for any sample type are now available!

Phase Genomics recently launched its ProxiMeta™ Hi-C metagenome deconvolution kit + software
product, enabling researchers to bring this powerful technology (previously only available through the ProxiMeta service) into their own labs. A new paper posted to biorxiv describes the results of employing ProxiMeta technology to deconvolute a human gut microbiome sample.

In the paper, ProxiMeta was used on a single human gut microbiome sample and isolated 252 individual microbial genomes or genome fragments, with 50 of these genomes meeting the “near-complete” threshold typically used as the standard according to the CheckM tool (>90% complete, <10% contaminated). Examining the tRNA and rRNA content of the genomes found 10 to meet “high-quality” and 75 to meet “medium-quality” thresholds. Additionally, 14 of the genomes represent near-complete assemblies of novel species or strains not found in RefSeq, showing that even after many years of research, there remain numerous unknown microbes in the human gut that are discoverable with new approaches.

ProxiMeta’s results were compared to those achieved with MaxBin, a common tool used to perform metagenomic binning based on heuristics such as shotgun read depth and tetranucleotide profiles. MaxBin was able to create 29 near-complete genomes (cf. 50 for ProxiMeta), with only 5 meeting high-quality (cf. 10) and 44 meeting medium-quality (cf. 75) thresholds based on tRNA and rRNA content. In terms of ability to construct similar sets of near-complete genomes, ProxiMeta and MaxBin constructed 27 of approximately the same genomes, with ProxiMeta constructing an additional 32 genomes that MaxBin did not, and MaxBin constructing 9 genomes that ProxiMeta did not. ProxiMeta’s assembled genomes also exhibited a much lower amount of contamination than MaxBin’s assembled genomes, with 43% of MaxBin’s assemblies exceeding the 10% contamination limit that is the typical standard for genome quality, compared to only 2% of ProxiMeta’s assemblies.

Other results unique to ProxiMeta include the discovery of near-complete genomes for 14 novel species or strains and various associations of plasmids with their hosts. Of the 14 novel genomes, 10 appear to be of the class Clostridia, a common group of gut microbes that are poorly characterized due to their difficulty to culture. ProxiMeta also assigned 137 contigs containing plasmid content to a cluster and identified candidate plasmid sequences as being present across multiple, distantly related bacteria. For example, ProxiMeta placed a known megaplasmid into an assembly for Eubacterium eligens that included homologous plasmid sequences placed into several other genomes, suggesting either the presence of the megaplasmid into other species, or variants of the megaplasmid being found on other mobile elements spread through the metagenome.

The depth of the resulting data and results offers the opportunity to learn much more about this microbial niche and research continues to unlock new discoveries about this community. Phase Genomics is thrilled to be able to offer all researchers the same new power to dig deeper into their mixed samples than ever before, especially now with a product that puts the power of discovery in their hands.

To learn more about ordering our kits or services, just send us an email at info@phasegenomics.com

Orphan Crop Gains Reference Genome with Proximo Hi-C

Posted on September 1, 2017 by admin - Genomics, Hi-C, Proximo, Science

Amaranth genome assembly brought to the chromosome-scale using Phase Genomics’ Proximo Hi-C technology.

“Orphan crops” are growing in popularity because they have the potential to feed the world’s expanding population. You may have heard of orphan crops like quinoa or spelt, but have you heard of amaranth? The amaranth genus (Amaranthus) is a hearty group of plants that produce nutritious (high in protein and vitamin content) leaves and seeds. Amaranth species grow strongly across a wide geographic range, including South America, Mesoamerica, and Asia. Amaranth was likely domesticated by the Aztec civilization and has been a staple food of Mesoamericans for thousands of years. Breeders wish to enhance amaranth’s beneficial properties like drought resistance, nutrition, and seed production to improve the usefulness of amaranth as a food source. However, effective plant husbandry requires genetic and genomic resources, and building these resources has been inhibited by the high cost of genome sequencing and assembly.

Dr. Jeff Maughan (left) and Dr. Damien Lightfoot (right), are the primary authors of the amaranth genome paper.

Dr. Jeff Maughan, professor at Brigham Young University, is a champion of orphan crop genomics. Over the past year, Dr. Maughan and his team built a reference-quality amaranth genome on a tight budget. They built upon an earlier, short-read assembly by adding Hi-C data, which measures the conformation of chromatin in vivo, as well as low coverage long reads and optical mapping data. After using optical mapping to correct assembly errors in the short read assembly, the Hi-C data was used to cluster the short genome fragments into nearly complete chromosomes using Phase Genomics’ Proximity-Guided Assembly platform, Proximo™ Hi-C, Then, the long reads were used to close remaining gaps on the chromosomes. This cost-effective strategy recovered over 98% of the 16 amaranth chromosomes.

The completed reference genome provides an important resource for the community and will boost the efforts of plant breeders to unlock more agricultural benefits for amaranth. In their paper, Dr. Maughan’s team demonstrated the utility of the reference quality genome in at least two ways. First, they looked at chromosomal evolution by comparing the amaranth genome to the beet genome, which enables researchers to better understand amaranth in the context of how plants evolved, and second, they mapped the genetic locus responsible for stem color, which clarifies the scientific understanding of a useful agricultural trait. Dr. Maughan points out that both of these experiments would have been impossible without the chromosome-scale genome assembly afforded by Proximo Hi-C.

A high-quality reference genome is the first of many important steps towards creating a modern breeding program for amaranth. We contacted Dr. Maughan to learn more about how he is improving amaranth genomics and the importance of orphan crops.

What is an orphan crop?

According to the FAO (Food and Agriculture Organization of the United Nations) the world has approximately 7,000 cultivated edible plant species, but just five of them (rice, wheat, corn, millet, and sorghum) are estimated to provide 60% of the world’s energy intake and just 30 species account for nearly all (95%) of all human food energy needs. The remaining species are underutilized and often referred to as “orphan crops”.

How is genomics relevant to orphan crops?

Would you invest your entire 401K savings in just three stocks? In essence, that is what we are doing with world food security. This comes with tremendous risk. If we are going to diversify our food crops, it will be with these orphan crops. Modern plant breeding programs leverage genomics to significantly enhance genetic gain (yield), such methods will undoubtedly expedite the development of advanced varieties in orphan crop species.

What are the challenges facing researchers interested in orphan crop genomics? How have you overcome them?

Funding has long been the main obstacle to developing genomic resources for orphaned crops. The development of cheap, high-quality next-generation sequencing technology has dramatically ameliorated this problem – making genomics accessible for most plant species.

You used two scaffolding technologies for your assembly, Hi-C, and BioNano. How did they compare?

Both technologies are extremely useful and complementary but address different genome assembly challenges. The Hi-C data allows for the production of chromosome length scaffolds, while the BioNano data allows for fine-tuning and verification of the assembly.

Beyond building a high-quality genome assembly, what other genomic resources are required to encourage the adoption of orphan crops?

While genomic resources (such as genome assemblies and genetic markers) are fundamental for developing a modern plant breeding program, often what is missing with orphan crops is the collection of diverse germplasm (or gene bank) that is the foundation of a hybrid breeding program. The U.S. and other nations have extensive collections (tens of thousands of accessions) that serve as the genetic foundation for staple crop breeding programs – unfortunately, such collections are minimal or non-existent for orphan crops.

Who stands to benefit the most from a complete amaranth genome? How do you disseminate your work to them?

We collaborate extensively with researchers throughout South and Central America, where amaranth is already valued as a regionally important crop. Dissemination of our research occurs though traditional methods (e.g., peer reviewed publications) as well as through sponsored scientist and student exchanges.

Amaranth is used in a variety of interesting foods, what’s your favorite dish?

Alegría, which is made with popped amaranth and honey, and is common throughout Mexico.

Threespine Stickleback Genome Upgraded Using Proximo™ Hi-C

Posted on August 11, 2017 by admin - Genomics, Hi-C, Proximo

Proximo Hi-C genome scaffolding not only improved the well-studied threespine stickleback assembly, but also found structural differences that would have otherwise been missed.

This week researchers from the University of Bern and the University of Georgia released a new high-quality reference threespine stickleback genome. The results of this project, a joint collaboration between Dr. Catherine Peichel, Dr. Michael White, and Phase Genomics, were publiaried in the Journal of Heredity. By applying a relatively new scaffolding technology, Proximo Hi-C, the team was able place 60% of previously unassigned sequence to chromosomes. These previously unplaced sequences make up ~5% (13 Megabases) of the stickleback genome and contain multiple genes and other functional DNA. The assembly was generated from an individual from a different lake than the previous stickleback reference genome, and the structural information generated by Proximo Hi-C allowed the team to identify novel structural variants between the two populations. These improvements and new structural information will benefit many research groups that use this model organism to study genetics and evolution.

The first efforts to sequence and assemble the threespine stickleback genome from 2012 used a costly sequencing method called Sanger sequencing. This assembly was followed by two revisions in 2013 and 2015 that used standard short-read sequencing technologies. Short reads can be assembled together into larger fragments of the genome called contigs, but some regions of the genome are difficult to assemble because they are long, highly repetitive, or otherwise ambiguous. In the end, these efforts left researchers with a decent yet highly fragmented picture of the stickleback’s chromosomes, with other large portions of its genetic sequence left in individual contigs unassociated to any chromosome.

Dr. Catherine (Katie) Peichel and Dr. Michael White

Dr. Catherine (Katie) Peichel (left), Head of the Division Evolutionary Ecology, University of Bern, and Dr. Michael White, Assistant Professor, Department of Genetics, University of Georgia, used Proximo Hi-C genome scaffolding to make many improvements to the Threespine stickleback genome and detect structural variation.

Dr. Peichel and Dr. White used Phase Genomics’ Proximo Hi-C genome scaffolding technology to resolve many of these issues and create the new reference genome. Proximo Hi-C genome scaffolding uses a protocol called Hi-C to measure the physical structure of an organism’s genome and then uses that information to place contigs into chromosome-scale de novo assemblies. Phase Genomics was founded by the inventors of this genome assembly approach and has been making its Proximo Hi-C genome scaffolding technology available to researchers since 2015. The company specializes in generating and analyzing Hi-C data for the scaffolding of genomes such as the Threespine stickleback, as well as for analyzing microbial communities and other metagenomic samples through its ProxiMeta™ Hi-C metagenomic deconvolution technology.

We know that scientific tools are only as good as the resulting scientific findings. We sent a brief Q&A to both Dr. Peichel and Dr. White to get their take on the scientific value of Proximo Hi-C and share their experiences in working with us.

Why is the stickleback genome important?

Sticklebacks are a “supermodel” for evolutionary genetics, in that they have been one of the leading model systems for identifying the genetic and molecular basis of phenotypic changes in natural populations. Thus, it is important to have a complete genome sequence so that one can correctly identify all the genes that are present in a genomic region that is associated with a phenotype of interest. -CP

Why did the original genome need improvement?

A high-quality Sanger-sequenced genome was published in 2012 and has undergone two revisions since this time. Despite incorporating dense linkage maps to help assign many of the unanchored scaffolds to linkage groups, over 26.7 Mb of the 460 Mb genome still remained unassigned to linkage groups. We needed to apply other approaches to try and assign these remaining scaffolds. -MW

How did Proximo Hi-C scaffolding improve the contiguity of the genome?

We were able to assign over 60% of the unassigned contigs to chromosomes. -CP

What other applications of the Hi-C data are useful to your biological questions?

Hi-C is a useful way to identify structural variation (like inversions) among stickleback populations. We are also excited about the possibility of using Hi-C for assembly of the hard-to-assemble regions of the genome like Y chromosomes. -CP

Why did you choose to work with Phase Genomics?

I was impressed by their interest in our biological questions and dedication to working with us until we were satisfied with the assembly. -CP

We chose to work with Phase Genomics because of the ease of the entire pipeline. Phase Genomics was fast and kept us updated at every step along the way. It was great to work with a group that was so communicative and open to trying different approaches to get the best assembly. -MW

Spotlight on Hi-C in Science: New Technologies Boost Genome Quality

Posted on July 7, 2017 by admin - Genomics, Hi-C, Proximo, Science

Science writer, Elizabeth Pennisi, outlines available genomics technologies that are helping researchers improve genome assemblies with a focus on Hi-C’s ability to bring genome assembly to the chromosome-scale.

This article, by Elizabeth Pennisi, focuses on how new technologies are making genome quality much better. Long-reads, optical maps, and Hi-C data are being synergistically applied to improve modern genome assemblies including goat (Dr. Tim Smith), humming bird (Dr. Eric Jarvis), maize, and more. Importantly, Hi-C provides the finishing touch to these genomes, by providing ultra-long contiguity information that can scaffold entire chromosomes. We, at Phase Genomics, are glad researchers have chosen Proximo Hi-C to scaffold the goat, hummingbird, and hundreds of other assemblies into contiguous chromosome-scale reference genomes.

Read the article here

Hi-C Used to Assemble Extremely Large, Difficult Barley Genome

Posted on April 27, 2017 by admin - Hi-C, Science

Barley is the 4^th most cultivated plant in the world and has been a reliable food source for over 10,000 years. Genome Web reports on the exceptional state of the genome assembly and how researchers used Hi-C technology to tackle this extremely complex genome.

The barley genome, like many other grains, is notorious for being extremely difficult to assemble due to extensive polyploidy, long repeat regions, and its large genome size (5.3 Gb). However, the Barley Genome Sequencing Consortium (IBSC) used Hi-C to tackle this genome assembly, producing chromosome-level scaffolds representing over 95% of the genome in an attempt to understand the biology of this widely cultivated plant. After completing the assembly, the researchers began annotating the genome and identified over 87,000 different genes, publishing their findings in Nature.

Obtaining reference-quality assemblies for complex genomes, such as barley, used to be an extremely challenging endeavor. With Hi-C, obstacles like polyploidy and multi-Gb genomes are manageable due to its ability capture ultra-long-range genomic contiguity information from unbroken chromosomes, replacing the need for genetic maps. This ability enables researchers to answer questions otherwise difficult or impossible, including structural variation, complex gene structure, gene linkage, gene regulation, and more. While the researchers performed the barley assembly themselves, Phase Genomics’ Proximo Hi-C service makes it easy for any researcher to obtain similar results and has been used to assemble hundreds of genomes to chromosome-scale over the past two years, including complex genomes like barley.

Read more about the barley genome on Genome Web.

Spotlight on Hi-C in The Atlantic: The Game-Changing Technique That Cracked the Zika-Mosquito Genome

Posted on March 29, 2017 by admin - Genomics, Hi-C, Proximo, Science

One of the most prolific science writers, Ed Yong, profiles how Hi-C sequencing technologies can make genome assembly easier and more cost-effective than ever before.

Science writer Ed Yong covers the narrative on the researchers’ tackling the disease carrying Aedes aegypti genome, and how Hi-C “knitted” the genome from 36,000 pieces into complete and contiguous chromosomes. Yong points out that the completed genome will not only help scientists better understand the biology of the mosquito at a much deeper level, but it also marks a technological pivot in genomics: Hi-C makes genome assembly cheaper, more accurate and faster than ever before. Also, mentioned in the article: our collaborator, Dr. Catherine Piechel’s newly published three-spine stickleback genome, and Dr. Erich Jarvis’s hummingbird were also cited as examples of the power of Proximo Hi-C scaffolding.

Read the article here

Papadum’s Recipe for an Outstanding, Chromosome-Scale Genome with Hi-C

Posted on March 6, 2017 by admin - Hi-C, Proximo, Science

Meet Papadum the Goat! Papadum is a descendent from a rare population of goats that used to inhabit the San Clemente Island, and notably, Papadum also now holds the world record for the most contiguous non-model mammalian genome. The recipe for a his amazing de novo genome assembly? Long reads, optical mapping, and Proximo Hi-C genome scaffolding. Read NIH’s article about Papadum’s genome here.

The goat genome has been of scientific interest for several reasons: goats are important suppliers of milk, cloth, meat, and more. But prior to the Papadum genome, scientists’ ability to fully understand how the goat genome controls its biology was limited. As a part of the “Feed the Future” initiative, in 2014 the U.S. Agency for International Development awarded innovative scientists Dr. Tim Smith, Dr. Derek Bickhart and Dr. Adam Phillippy a grant to attempt to eliminate these limitations by assembling Papadum’s genome. As pioneers in the genomics field, the scientists teamed up to leverage two rather young technologies, long reads and Hi-C, to create an ultra-high-quality new assembly of the goat genome.

Their efforts ultimately led to the creation of the highest quality de novo genome assembly of a mammal to date and are published in Nature Genetics. With this new reference-quality goat genome, scientists will have a better understanding of goat biology and health to guide better breeding decisions, improving traits like milk production, meat quality, and resilience from disease.

The Papadum genome assembly includes large DNA sequences called “chromosome-scale scaffolds” which are nearly complete representations of entire chromosomes from Papadum. These chromosome-scale scaffolds are critical achievement that allows far better understanding of the mechanics of the goat genome than earlier, less advanced results, which included thousands of tiny fragments of chromosomes and lacked the overall structure of the goat genome. The difference is not unlike having an entire intact book, versus a jumble of all the individual words from the book.

The ability to reconstruct nearly complete chromosomes was made possible largely by a new technique called Proximity-Guided Assembly, performed with Phase Genomics’ Proximo^TM Hi-C scaffolding technology. This process was followed by a tool called PBJelly, which identifies and closes gaps (regions of uncertainty) in the chromosome-scale scaffolds. After Proximo and PBJelly, the resulting assembly included 31 chromosome-scale scaffolds containing only 663 gaps total across the 3 billion base pair diploid genome. Descended from research first published in 2013, Phase Genomics has since successfully demonstrated the success of the Proximo Hi-C scaffolding method in the genomes of plants, animals, fungi and more.

Papadum’s genome marks the beginning of an era where reference-quality genomes are achievable and affordable for any organism, not just extensively studied model organisms like mice, fruit flies, and humans. The availability of these extraordinarily complete genomes enables scientists to answer many new biological questions that have the potential to help farmers, government agencies, agricultural companies, and developing countries solve a significant part of the food security problem.

Read more about the grant, the scientists, and Papadum’s genome on the NIH’s National Human Genome Research Institute website.

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Why is it important and useful to have a high-quality genome for Varroa species? Is there any combined value with the recently published bee genome?

Why did you choose to use Hi-C? Why did you need chromosomes for your genome assembly?

What genomic clues were found in the two Varroa species that may contribute to parasitism?

How do you hope these genomes will be used to help save honey bees?

Is there any genomic evidence that the western honeybee could be developing resistance to these pests?

Isolating Varroa mites from bees involves a creative use of powdered sugar. How do you think this technique came about?

What is your favorite weird food that involves honey?

WHAT ARE PLATINUM GENOMES?

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Published Hi-C Genome Assemblies:

Published Metagenomic Projects:

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ANTIMICROBIAL RESISTANCE ON THE RISE

PROXIMITY-LIGATION (HI-C) LINKS ARG AND PLASMIDS TO THEIR HOSTS

USING HI-C TO TRACK ARGs IN THE MICROBIOME

FUTURE DIRECTIONS

BRING A HI-C KIT INTO YOUR LAB TODAY

SYMBIOSIS BETWEEN PLANTS AND MICROBES

THE DARK MATTER OF THE MICROBIOME

THE PROCEDURE

THE RESULTS

HI-C AND FINDING NOVEL GENOMES

SCIENCE UNCORKED

USING GENOMICS TO FIND MICROBES

OVER 20 NEW BACTERIAL GENOMES DISCOVERED

WHO ARE OUR HERO CATS?

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ENTER YOUR CAT IN OUR TWITTER RAFFLE

LIL BUB AND DANNY’S STORY FEATURED ON GEEKWIRE PODCAST

What is a black raspberry? How is it different from the blackberries we have in Seattle?

There are many curious uses of black raspberries, what’s yours?

What are molecular breeding technologies? What are some of the traits in black raspberry you’d like to breed for?

The initial black raspberry genome assembly was built from short-read data. Why did you choose to scaffold the short-read contigs rather than create a new long-read assembly? Would you get chromosome scale contigs from a long-read assembly?

How did you validate the Proximity Guided Assembly (PGA) scaffolds? How did you correct errors in the scaffolds?

What was the process like in working with Phase Genomics? Would you recommend them to your colleagues?

What is an orphan crop?

How is genomics relevant to orphan crops?

What are the challenges facing researchers interested in orphan crop genomics? How have you overcome them?

You used two scaffolding technologies for your assembly, Hi-C, and BioNano. How did they compare?

Beyond building a high-quality genome assembly, what other genomic resources are required to encourage the adoption of orphan crops?

Who stands to benefit the most from a complete amaranth genome? How do you disseminate your work to them?

Amaranth is used in a variety of interesting foods, what’s your favorite dish?

Why is the stickleback genome important?

Why did the original genome need improvement?

How did Proximo Hi-C scaffolding improve the contiguity of the genome?

What other applications of the Hi-C data are useful to your biological questions?

Why did you choose to work with Phase Genomics?

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