Tag: agriculture

An Ancient Fungal Affair

Posted on February 14, 2024 by Benjamin Mitchell - Genomics

two fungi exchange love letters in a whimsical forest scene

New genomic technology reveals the parental past of “ancient asexuals,” paving a route to crop engineering and soil remediation with symbiotic fungi

In a warming, crowded world, we need more help than ever from plants. But maximizing the bounty from crops — from food to fuel to fibers — means coaxing plants to draw minerals and nutrients from soil more effectively, and paying special heed to the tiny, often-overlooked fungi that make this possible.

Plant roots have symbiotic relationships with fungi that stretch back eons. For example, arbuscular mycorrhizal fungi, or AMF, have been cozying up to plant roots for at least 400 million years. In exchange for carbon-rich lipids from their hosts, AMF — named for the branch-like structures their bodies form within plant roots — help host defenses against pathogens, deliver water and increase absorption of nutrients rich in nitrogen, potassium and phosphorus. They also boost plant diversity.

Thanks to this ecological generosity, AMF are used as crop stimulants and in soil remediation. Their lipid lust also makes them good at carbon sequestration. Theoretically, engineered AMF strains could mount an even better performance in these essential tasks. But scientists have long viewed certain features of AMF, particularly their genetic structure and life cycle, as evolutionary puzzles that must be solved to make strain engineering possible and build better symbionts.

Working with Phase Genomics, scientists at the University of Ottawa recently overcame this barrier, successfully sequencing the genomes of four strains of the most widely studied AMF species, Rhizophagus irregularis. Using Phase’s proximity-ligation sequencing techology, they showed for the first time that the genomes of AMF are simultaneously more straightforward and more surprising than many mycologists had dared to dream.

Armed with this knowledge, scientists can plan new approaches to engineer AMF strains for applications in biomass production, soil remediation — and beyond.

The mysterious kary carryall

For years, the more scientists looked at AMF, the more questions they had. AMF bodies are essentially bags of haploid nuclei — tens of thousands, all sharing a common cytoplasm. And that’s not all.

“There were many, many outstanding questions about AMF,” said Dr. Nicolas Corradi, leader of the University of Ottawa team. “This was primarily because these fungi are always multinucleated and lack observable sex. It was suggested that AMF have an ‘oddball’ genetics and evolution.”

They were assumed to be “ancient asexuals,” who must’ve somehow thrived without the gene-shuffling benefits of sexual reproduction.

Dr. Corradi and his colleagues were determined to find out if that’s the case, and in the process began to shatter AMF’s asexual reputation. In 2016, they showed that Rhizophagus irregularis strains harbor evidence of sexual reproduction, including finding some of the genes needed for it. In some strains, all nuclei were genetically identical. But other, more robust and resilient AMF strains — termed heterokaryons — harbored two distinct populations of nuclei in their cytoplasm. More recently, Dr. Corradi and his team reported that the two populations of nuclei in heterokaryons change in abundance, depending on their host plant.

“But these were, however, based on fragmented genome datasets,” said Dr. Corradi.

To know for sure what was going on in AMF heterokaryons, the team needed a method to sequence the complete genomes of both populations of nuclei, allowing more complex studies of gene expression, genetic exchange and evolution in these puzzling fungal packages.

Would you prefer carrots or chicory?

Working with Phase Genomics, Dr. Corradi and his team employed a combination of proximity ligation (Hi-C) and PacBio HiFi data to sequence the genomes of both nuclear populations in four Rhizophagus AMF heterokaryon strains. Surprisingly, all four strains harbored genomes largely similar in structure — 32 chromosomes, with clear delineations between gene-rich and gene-poor regions — but highly divergent in sequence. For all four strains, the two populations of nuclei were essentially haplotypes, derived from parental strains during prior sexual reproduction.

Equipped with eight complete genomes — two haplotypes among four strains — the team followed-up with gene-expression analyses and discovered that each haplotype was transcriptionally active. But within an individual strain, haplotype gene expression patterns were not equal.

“AMF heterokaryons carry two haplotypes that physically separate among many thousands — potentially millions — of co-existing nuclei,” said Dr. Corradi. “This is unheard of in any other organism. But each ‘parental genome’ also regulates different biological functions, and these change depending on the plant host.”

They recorded at times dramatic shifts in haplotype abundance and expression depending on the AMF heterokaryon’s plant host — carrot versus chicory, for example. This suggests that each haplotype makes specific and unique contributions to the AMF heterokaryon’s phenotype. Future studies will have to tease out what role the plant host is playing, if any, in these shifting expression and abundance patterns.

Sex, but when? And more new mysteries

In assembling these long-sought genomes that co-exist within a common cytoplasm, Hi-C has revealed that Rhizophagus AMF heterokaryons are not as complex as once thought, or feared. Both haplotypes within each heterokaryon appear to arise through some past sexual reproduction event, contribute to the AMF’s phenotype and have unique gene expression patterns based on plant host. Their surprisingly ordinary genetic behavior — at least, ordinary for fungi — means it could be possible to engineer AMF that are even better symbionts for specific hosts, helping to boost crop biomass or improve resilience, for example. Engineered strains could also aid in soil remediation, or store carbon that would otherwise end up above ground or in the air.

The findings, coupled with the team’s previous experiments, also bring new mysteries into focus: AMF strains appear to employ a mixture of sexual and asexual reproduction, similar to other fungi. But scientists have never witnessed AMF sexual reproduction — a potentially useful tool for engineering strains. The new genome sequences will also serve as a point of comparison as scientists investigate whether the hundreds of other AMF species are similar to Rhizophagus — and their potential to transform agriculture.

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.

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

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.