Updated October 30, 2020:
Progress overview: Overall, the project addresses the RFP’s stated goal of “gene discovery and germplasm development” for traits critical to soybean growers, namely yield enhancement and seed composition improvement. The heart of the project focuses on developing soybean mutant genetic resources that will increase our understanding of the genes that underlie traits of agronomic importance. The development of these resources has been designed to overcome factors that have limited similar projects in the past; such factors include issues with seed source, seed purity (minimizing background genetic heterogeneity), mutagenesis source, genotyping, phenotyping, and seed storage. The new mutant resources will allow researchers to identify mutant stocks for their gene(s) of interest by simply searching a genomic database that will be developed by this project. This will provide an unparalleled public resource in which researchers can quickly identify the mutations, order mutant seeds, and test the agricultural function and importance of the gene(s). Our research objectives and current progress are summarized below.
Objective 1: Generate greater numbers of unique mutant lines.
Progress: A third batch of seeds were mutagenized and grown in the greenhouse during the winter of 2019-20, this time using MN1312CN as the genetic background. MN1312CN is a modern cultivar well adapted to Minnesota and less prone to lodging than MN1806CN. Approximately 400 seeds were harvested and planted in the field during the summer of 2020, of which about 220 germinated and were harvested this October. These lines have been phenotypically evaluated for various traits (such as leaf color, plant architecture, height, fertility) and tissue was collected from each plant for future genotyping applications. A subset of these lines will be grown as M3 rows in the field next year.
Objective 2: Perform genome and gene space resequencing on a collection of M2-derived soybean ENU/EMS mutants.
Progress: As described previously, in 2018 a set of fifty mutant plants, some with interesting characteristics important to agronomic traits, were selected for whole genome resequencing to discover novel mutations. In this reporting period we developed a pipeline to analyze this dataset which minimizes the false mutation discovery rate, resulting in a set of high confidence SNPs for these lines. Among these fifty lines approximately 605,000 mutagenesis derived SNPs were discovered, with a range of about 4000-24000 SNPs per M2 plant. These SNPs occur on all twenty chromosomes of the soybean genome, and we are now investigating which occur in known genes. Considering over 1200 independent M1 families have been generated thus far, and average mutation rate of 12000 mutations per line would imply that this collection contains 14.4 million novel SNPs throughout the soybean genome.
We have also developed several sets of M3 families segregating for unique phenotypes to highlight the potential of this mutant collection for gene discovery. Whole-genome sequencing will be performed on these families in conjunction with bulked segregant analysis to identify the causal SNPs.
Objective 3: Create a searchable public database that hosts all of the sequence polymorphism information for the resequenced mutant plants.
Progress: None to date, as the resequencing data will need to be fully analyzed before we can meet this objective.
Objective 4: Store M3 seeds for the collection. Distribute seed to users in the research community based on their specific needs and requests.
Progress: M3 seed was successfully harvested and stored from approximately 3000 M2 plants grown during the 2019 field season. Seed from an additional 220 M2 plants from the MN1312CN background were harvested in the 2020 field season.
Deliverables: None to date.
Performance Metrics:
This project addresses the RFP’s stated goal of “gene discovery and germplasm development” for traits critical to soybean growers, namely yield enhancement and seed composition improvement. This project provides a new mutant genetic resource for public use, including breeding and gene discovery efforts. This population will have the advantage of having already identified mutations in specific genes, such that researchers can do targeted breeding and gene discovery work on gene with previously predicted or known functions. Here are some measurables so far generated by this project, mostly within the realm of resource development:
4300 M2-generation mutant plants were phenotyped in the field in 2018 or 2019 for morphological traits; M3 seed has been harvested and stored for almost all of these plants
50 plants have been sequenced at the whole-genome scale to identify all new mutations
220 new M2 plants belonging to 30 families with the 'MN1312CN' background were grown in the field to expand the size of this mutant population and provide even greater genetic diversity.
Researchers throughout the soybean community will be able to order seeds from this population in the future. Common targets of mutation breeding are yield and seed composition traits.
A poster describing this project, its current progress, and future plans was presented in 2019. Reference: Mulkey SE, Patil G, Roessler J, Stec AO, Belzile F, Hyten DL, Stupar RM. Development of an ENU and EMS Induced Mutant Resource for Functional Genomics in Soybean. Plant and Animal Genome Conference, San Diego, CA, Jan 2019.
Novel chemical mutant populations were developed in the soybean genotypes 'MN1806CN' and 'MN1312CN' using a combination of ENU and EMS mutagenesis. These populations demonstrated a range of unique traits in the M2 generation, indicating successful mutagenesis. We have sequenced the whole genomes of 50 mutant plants from this population to identify which genes and regulatory regions have mutations. Further sequencing is in progress on several sets of mutants to identify the mutations controlling interesting traits. When fully analyzed, this sequencing data will be shared on a public database, allowing researchers to identify mutations in genes of interest and order these lines from our population. This will allow for more efficient breeding with novel traits and discovery of gene functions.