Location: Crop Genetics and Breeding Research
2023 Annual Report
Objectives
1. Elucidate the interactions of responses in peanut to multiple biotic and abiotic stress factors, such as drought, tomato spotted wilt virus, leaf spots, white mold, and root-knot nematode; determine overlapping response pathways; discover selection targets (genes or networks); and work with breeders to use the information in developing peanut varieties with broad spectrum stress resistance/tolerance.
1A. Develop next-generation fine-mapping population segregating multiple traits of interest, such as Multi-parent Advanced Generation Inter-Cross (MAGIC), and conduct phenotypes in the field.
1B. Construct high resolution genetic and trait maps using single nucleotide polymorphism (SNP) markers for fine-mapping of QTLs/markers linked to the traits of interest.
1C. Apply molecular markers in breeding and trait stacking/pyramiding to develop superior lines of peanut using Marker Assisted Recurrent Selection (MARS) breeding scheme.
Approach
1. Identifying natural allelic variation that underlies quantitative trait variation remains a challenge in genetic studies. Development and phenotypic evaluation of a multi-parental MAGIC mapping population, along with high density genotyping tools available, such as newly developed peanut 58K SNP array and/or whole genome re-sequencing (WGRS), will be essential for quantitative trait loci/marker and trait mapping analyses. The primary aim of this objective is to develop the first next-generation fine-mapping population of peanut that can be used by the peanut research community, and to conduct high-resolution phenotyping of this population. Because of the size of the population, as large as 2,000 to 3,000, the entire population will be genotyped. A core subset (or different core subsets) of the entire population will be developed (divided) based on the genetic similarity or based on unique marker scores for different trait (disease resistance). Therefore, the subset of individuals could be manageable in a replicated test in the field or greenhouse for testing a specific trait of disease resistance such as nematode resistance. Drought stress study will include irrigation and non-irrigation.
2. We will use the WGRS approach for the parental lines “SunOleic 97R and NC94022”, “Tifrunner and GT-C20”, and the derived RILs (referred to as the “S” and the “T” populations) to identify the SNPs and genotype the populations. In order to improve the map density and fine-map the QTLs for MAS, we plan to use WGRS approach to genotype this population to improve the genetic map density and to identify genomic regions/candidate genes controlling the resistant traits. SNP marker validation will be conducted through KASP assay. The KASP genotyping assay is a fluorescence based assay for identification of biallelic SNPs. KASP marker data will be analyzed using SNPviewer software (LGC Genomics) (http://www.lgcgroup.com) to generate genotype calls for each RIL and parental line, and were correlated with observed disease ratings (phenotypes) in the field for selection.
3. Recurrent selection is defined as re-selection generation after generation, with inter-mating of selected lines, such as RILs, to produce the population for the next cycle of selection. There are two methods using MAS in breeding selection for breeders. Recurrent selection is an efficient breeding method for increasing the frequency of superior genes for various economic characters. One RIL population described in Sub-objective 1B is the “S” population, and QTL mapping has been completed for targeted traits: total oil content, oil quality, disease resistance to early leaf spot (ELS), late leaf spot (LLS), and TSWV. Therefore, we propose to select eight RIL lines (founders) with known markers/QTL associated with specific traits for inter-crossing in order to stack/pyramid all favorable alleles in peanut breeding for superior cultivars with multiple traits. All traits of interest will be considered concurrently. The goal is to develop superior peanut lines, which have either high oil content (50% or above) or low oil content (40% or less) with high oleic acid and resistance to ELS, LLS, and TSWV.
Progress Report
The primary focus of this project 6048-21000-028-000D, “Improvement of Genetic Resistance to Multiple Biotic and Abiotic Stresses in Peanut,” is to develop genetic resources and tools for breeding superior peanut cultivars with multiple-stress resistance traits. [301, 1A, 1B, 3A]
Identification of two peanut late leaf spot resistance loci, PLLSR-1 and PLLSR-2, using a nested association mapping: Identification of candidate genes and molecular markers for late leaf spot disease resistance in peanut has been a focus of molecular breeding for the U.S. industry funded peanut genome project. Efforts have been hindered by limited mapping resolution due to low levels of genetic recombination and marker density available in traditional biparental mapping populations. To address this, a multi-parental nested association mapping (NAM) population has been used and genotyped with the peanut 58 K SNP array and phenotyped for leaf spot disease severity in the field for three years. Joint linkage-based mapping and genome-wide association study were applied in this study and two genomic regions were identified on chromosome B02 and chromosome B03 in association with the resistance, which was designated as peanut late leaf spot resistance loci, PLLSR-1 and PLLSR-2, respectively. This study highlights the power of multi-parent populations for genetic mapping and marker-trait association studies in peanut.
Using double stranded RNA (dsRNA) strategies to mitigate aflatoxin contamination in corn and peanut: ARS researchers in Tifton, Georgia, in collaboration with scientists in the University of Georgia and Louisiana State University have initiated a new strategy to mitigate aflatoxin contamination. In recent years, biotechnology developments have enabled effective molecular manipulation of plant physiology by application of biomolecules like small RNA. One application is using RNA interference (RNAi) induced by topical application of small interfering RNA (siRNA) that demonstrates to be an effective technology for protecting plants against pathogens. Initially, four target genes have been selected and primers with appropriate restriction sites have been designed for cloning part of these genes into an Escherichia (E.) coli based bacterial dsRNA production system. Bioassays in vitro and in vivo have been established. Successful application of this strategy to prevent Aspergillus flavus infection and aflatoxin production in corn and peanut will provide an environmental-friendly and sustainable non-Genetically Modified Organism (GMO) approach that may be used to control preharvest and postharvest aflatoxin contamination issues in corn and peanut.
This project has been expired and will be replaced by project #6048-21000-032-000D Genomics and Genetic Improvement of Crop Resistance to Multiple Biotic and Abiotic Stresses in Peanut.
Peanut is vulnerable to a range of biotic and abiotic stresses, such as tomato spotted wilt (TSWV) and leaf spots, which cause yield loss, reduce peanut quality, and increase production cost. Abiotic stress like drought stress causes aflatoxin contamination, another concern to growers and industry. During the life of this project, two bi-parent genetic mapping populations have been applied in genetic mapping for identification of molecular markers linked to resistance to the diseases including TSWV, early and late leaf spots and potential aflatoxin contamination. Multi-parent populations, such as NAM (nested association mapping) and MAGIC (multi-parent advanced generation inter-cross) have been developed and ready for research community as a new genetic resource for high-definition trait mapping and breeding application. Recent advances in genome sequencing and computational bioinformatics provide unprecedented possibilities for trait discovery and identification of genetic markers for breeding. Therefore, in the “post reference-genomic” era, genotyping of large complex populations by whole genome sequencing is feasible, however, precise phenotyping is required for dissection of complex traits.
The research progress has been monitored by meeting and conference calls, such as American Peanut Research and Education Society (APRES), American Phytopathology Society (APS), and Plant and Animal Genome (PAG) Conference.
Accomplishments
1. Aspergillus flavus pan-genome uncovers novel aflatoxin producing genes. Aspergillus flavus is a well-known carcinogenic aflatoxin-producing fungal pathogen and different isolates are very diverse in adaptation to various environments and in aflatoxin production. Recently, ARS scientists in Tifton, Georgia, and collaborators reported two reference genomes of two contrasting A. flavus isolates, AF13 producing high aflatoxin and NRRL3357 producing lower aflatoxin, with significant genomic variants between them, which suggests the inadequacy of using a single-isolate as the reference genome for Aspergillus fungal population genetic and genomic comparative studies. Therefore, ARS scientists in Tifton, Georgia, and collaborators collected and sequenced 225 new isolates of A. flavus from different field soils and corn plants. Total 346 diverse genome sequences, including these 225 new genome sequences and 121 from public database, were evaluated and analyzed for fungal population comparative study. A new pan-genome for A. flavus has been developed from this largest collection by far, and the “core” genes, presence in all isolates, and the “accessory” genes, presence or absence in different isolates, were categorized. Using this large diverse genomic dataset for pan-genome wide association study, 256 novel pan-genes have been detected, which will be used in future study for developing effective strategies in mitigating aflatoxin contamination and food safety.
2. MAGIC peanut, a new genetic resource for high-definition trait mapping and breeding selection. In peanut genetic mapping studies, bi-parental populations, derived from two parent crosses, have been the “standard” for mapping traits of interest, which hindered the marker-trait studies because of the limited recombination and the complexity of peanut genomes. Recent advances in genome sequencing and computational bioinformatics provide unprecedented possibilities for trait discovery and identification of genetic markers for breeding. ARS researchers in Tifton, Georgia, have developed a multi-parent advanced generation inter-cross (MAGIC) population with 2,775 recombinant inbred lines (RIL) derived from eight diverse peanut parents, called MAGIC Peanut. The characterization of 310 MAGIC Core peanut lines shows that this MAGIC Peanut population is a balanced and evenly differentiated mosaic of chromosomal segments from all eight parents. This subset of MAGIC Peanut achieved a high mapping power and resolution across different analyses for single locus and multi-locus traits such as high oleic acid and shelling percentage, respectively. Therefore, this MAGIC Peanut will be made available to the peanut community for functional mapping of interest traits, such as disease resistance, and breeding selection for high yield peanuts with better disease resistance and quality.
Review Publications
Gangurde, S., Xavier, A., Naik, Y., Jha, U., Rangari, S., Kumar, R., Channale, S., Elango, D., Rouf Mir, R., Pandey, M., Punnuri, S., Mendu, V., Reddy, U., Guo, B., Gangarao, N., Sharma, V., Wang, X., Zhao, C., Thudi, M. 2022. Two decades of association mapping: Insights on disease resistance in major crops. Frontiers in Plant Science. 13:1064059. https://doi.org/https://doi.org/10.3389/fpls.2022.1064059.
Ahmad, N., Zhang, K., Ma, J., Yuan, M., Hao, S., Wang, M., Deng, L., Ren, L., Gangurde, S.S., Pan, J., Ma, C., Li, C., Guo, B., Wang, X., Li, A., Zhao, C. 2023. Transcriptional networks orchestrating red and pink testa color in peanut. BMC Plant Biology. 23:44. https://doi.org/10.1186/s12870-023-04041-0.
Gangurde, S., Pasupuleti, J., Parmar, S., Variath, M.T., Bomireddy, D., Manohar, S.S., Varshney, R.K., Prashant, S., Guo, B., Pandey, M.K. 2023. Genetic mapping identifies genomic regions and candidate genes for seed weight and shelling percentage in groundnut. Frontiers in Genetics. 14:1128182. https://doi.org/10.3389/fgene.2023.1128182.
Garg, V., Dudchenko, O., Wang, J., Khan, A.W., Gupta, S., Kaur, P., Han, K., Saxena, R.K., Kale, S.M., Pham, M., Yu, J., Chitikineni, A., Zhang, Z., Fan, G., Lui, C., Valluri, V., Meng, F., Bhandari, A., Liu, X., Yang, T., Chen, H., Valliyodan, B., Roorkiwal, M., Shi, C., Yang, H., Durand, N.C., Pandey, M.K., Li, G., Barmukh, R., Wang, X., Chen, X., Lam, H., Jiang, H., Zong, X., Liang, X., Liu, X., Liao, B., Guo, B., Jackson, S., Nguyen, H.T., Zhuang, W., Wan, S., Wang, X., Aiden, E.L., Bennetzen, J.L., Varshney, R.K. 2021. Chromosome-length genome assemblies of six legume species provide insights into genome organization, evolution, and agronomic traits for crop improvement. Journal of Advanced Research. 42:315-329. https://doi.org/10.1016/j.jare.2021.10.009.
Kumar, M., Prusty, M.R., Pandey, M.K., Singh, P.K., Bohra, A., Guo, B., Varshney, R.K. 2023. Application of CRISPR/Cas9-Mediated gene editing for abiotic stress management in crop plants. Frontiers in Plant Science. 14:1157678. https://doi.org/10.3389/fpls.2023.1157678.
