Location: Crop Genetics and Breeding Research
2020 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 6048-21000-028-00D, “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.
Tomato spotted wilt virus (TSWV) is a devastating disease to peanut growers in the Southeastern region of the United States. Newly released peanut cultivars must have some levels of resistance to TSWV. A whole genome resequencing approach was used by ARS researchers at Tifton, Georgia, to sequence one mapping population derived from peanut lines of SunOleic 97R and NC94022, resulting in the development of the first bin-based map. Utility of this bin map has resulted in identification of three genetic regions, which were colocalized on chromosome A01 and had a cluster of genes coding for chitinases and NBS-LRR proteins. SNPs linked to this region were used by ARS researchers at Tifton, Georgia, to develop specific markers for breeding use. Therefore, this bin-map and markers associated with TSWV resistance made it possible for functional gene mapping, map-based cloning, and marker-assisted breeding.
Multiparental genetic population such as nested association mapping (NAM) population has great potential for investigating quantitative traits and finding their genomic control, leading to faster discovery of candidate genes and markers. To date, only biparental and natural populations were used in peanut for conducting trait mapping studies. The U.S. peanut research community developed structured recombinant inbred line (RIL) populations with two runner cultivars (Tifrunner and Florida-07) as common parents. ARS researchers at Tifton, Georgia, objectives were to demonstrate the utility and power of the NAM populations by using a subset of the available individual RIL populations developed in peanut community for mapping peanut seed weight (SW) and pod weight (PW). ARS researchers at Tifton, Georgia, applied the high-density SNP genotyping assay using 58K peanut SNPs, which further improved the resolution of trait mapping. ARS researchers at Tifton, Georgia, carried out the genetic and genome-wide association studies (GWAS) analyses and identified potential genomic regions and candidate genes over eight chromosomes for seed weight and pod weight. Identified candidate genes and markers for assistance in breeding selection for new cultivars with desired seed and pod weight.
Accomplishments
1. Development of novel strategies for mitigating aflatoxin contamination using -omics approaches. Aspergillus flavus is a fungal pathogen of several important crops including corn and peanut, producing carcinogenic mycotoxins known as aflatoxins, particularly under drought stress conditions. This results in significant losses in crop value and poses a threat to food safety and security globally. Understanding how this fungus responds to environmental stresses related to drought may allow ARS researchers at Tifton, Georgia, to identify novel methods of mitigating aflatoxin contamination. ARS researchers at Tifton, Georgia, analyzed the accumulation of a broad series of metabolites over time in two isolates of A. flavus with differing stress tolerance and aflatoxin production capabilities in response to drought-related oxidative stress and identified several metabolites and mechanisms in A. flavus which allow it to cope with environmental oxidative stress and may influence aflatoxin production and fungal growth. These may serve as potential targets for selection in breeding programs for the development of new cultivars, or for alteration using genetic engineering approaches to mitigate excessive aflatoxin contamination under drought stress.
Review Publications
Agarwal, G., Clevenger, J., Kale, S.M., Wang, H., Pandey, M.K., Choudhary, D., Yuan, M., Wang, X., Culbreath, A.K., Holbrook Jr, C.C., Lui, X., Jackson, S.A., Varshney, R.K., Guo, B. 2019. Recombination bin-map facilitates identification of major QTL on chromosome A01 and potential candidate genes for resistance to Tomato spotted wilt virus in peanut (Arachis hypogaea). Journal of Experimental Botany. 9:18246. https://doi.org/10.1038/s41598-019-54747-1.
Pekar, J.J., Murray, S.C., Isakeit, T.S., Scully, B.T., Guo, B., Knoll, J.E., Ni, X., Abbas, H.K., Williams, W.P., Xu, W. 2019. Evaluation of elite maize inbred lines for reduced Aspergillus flavus infection, aflatoxin accumulation, and agronomic traits. Crop Science. 59:2562-2571. https://doi.org/10.2135/cropsci2019.04.0206.
Gangurde, S.S., Wang, H., Yaduru, S., Pandey, M.K., Fountain, J.C., Chu, Y., Isleib, T.G., Holbrook Jr, C.C., Xavier, A., Culbreath, A., Ozias-Akins, P., Varshney, R.K., Guo, B. 2019. Nested-association mapping (NAM)-based genetic dissection uncovers candidate genes for seed and pod weights in peanut (Arachis hypogaea). Plant Biotechnology Journal. https://doi.org/10.1111/pbi.13311.
Fountain, J.C., Yang, L., Pandey, M.K., Bajaj, P., Alexander, D., Chen, S., Kemerait, R.C., Varshney, R.K., Guo, B. 2019. Carbohydrate, glutathione, and polyamine metabolism are central to Aspergillus flavus oxidative stress responses over time. BMC Microbiology. https://doi.org/10.1186/s12866-019-1580-x.
Sinha, P., Bajaj, P., Pazhamala, L.T., Nayak, S.N., Pandey, N.K., Chitikineni, A., Huai, D., Khan, A.W., Desai, A., Jiang, H., Zhuang, W., Guo, B., Liao, B., Varshney, R.K. 2020. A global gene expression atlas of cultivated groundnut provides insights into seed development, oil biosynthesis and allergens. Plant Biotechnology Journal. pp. 1-14. https://doi.org/10.1111/pbi.13374.
Zhao, C., Li, T., Zhao, Y., Zhao, B., Zhao, S., Hou, L., Xia, H., Guo, B., Wang, X. 2020. Integrated small RNA and mRNA expression profiles reveals miRNAs and their target genes in response to Aspergillus flavus infection in peanut stress. RNA Biology. 20:215. https://doi.org/10.1186/s12870-020-02426-z.
Pandey, M.K., Pandey, A.K., Kumar, R., Nwosu, V., Guo, B., Wright, G., Bhat, R.S., Chen, X., Bera, S.K., Yuan, M., Jiang, H., Faye, I., Radhakrishnan, T., Wang, X., Liang, X., Liao, B., Zhang, X., Varshney, R.K., Zhuang, W. 2020. Translational genomics for achieving genetic gains in post-genome era in groundnut. Theoretical and Applied Genetics. 133:1678-1702. https://doi.org/10.1007/s00122-020-03592-2.
