Location: Crop Protection and Management Research2018 Annual Report
1a. Objectives (from AD-416):
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.
1b. Approach (from AD-416):
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.
3. Progress Report:
This new project 6048-21000-028-00D, "Improvement of Genetic Resistance to Multiple Biotic and Abiotic Stresses in Peanut" began February 2018. We have developed a multi-parent advanced generation inter-cross (MAGIC) population, which can provide an increased level of recombination and mapping resolution by integrating multiple alleles from different parents for fine-mapping of complex quantitative traits and for breeding selection of improved/diverse lines with novel genetic variation/traits. This MAGIC population was derived from eight founders: SunOleic 97R, NC94022, Tifrunner, GT-C20, Florida 07, SPT06-06, Georgia 13M, and TifNV-High O/L. InterCrosses (2-way, 4-way, 8-way) have been made using a simple ‘funnel’ breeding scheme with the founders combined in equal proportions, followed by a single seed descent (SSD) to develop the MAGIC population. Currently, this MAGIC has been advanced to F2/F3 generation with 3575 F2:3 families in the Tifton summer nursery. These preliminary results will be presented at the AAGB-2018, International Peanut Genome Conference in Saly, Senegal. Whole genome re-sequencing (WGRS) data for the “T” RILs (Tifrunner × GT-C20) have been generated, and a SNP-based high-density genetic map has been developed with 8,869 SNPs assigned to 20 linkage groups, representing 20 chromosomes. The quantitative trait locus (QTL) analysis identified two QTLs for ELS on B05 with 47.42% PVE and B03 with 47.38% PVE, two QTLs for LLS on A05 with 47.63% and B03 with 34.03% PVE, and one QTL for TSWV on B09 with 40.71% PVE. These data have been presented at 2018 American Peanut Research and Education Society (APRES) annual conference.