High-density genetic map using whole-genome resequencing for fine mapping and candidate gene discovery for disease resistance in peanut

Abstract

Whole-genome resequencing (WGRS) of mapping populations has facilitated development of high-density genetic maps essential for fine mapping and candidate gene discovery for traits of interest in crop species. Leaf spots, including early leaf spot (ELS) and late leaf spot (LLS), and Tomato spotted wilt virus (TSWV) are devastating diseases in peanut causing significant yield loss. We generated WGRS data on a recombinant inbred line population, developed a SNP-based high-density genetic map, and conducted fine mapping, candidate gene discovery and marker validation for ELS, LLS and TSWV. The first sequence-based high-density map was constructed with 8869 SNPs assigned to 20 linkage groups, representing 20 chromosomes, for the 'T' population (Tifrunner × GT-C20) with a map length of 3120 cM and an average distance of 1.45 cM. The quantitative trait locus (QTL) analysis using high-density genetic map and multiple season phenotyping data identified 35 main-effect QTLs with phenotypic variation explained (PVE) from 6.32% to 47.63%. Among major-effect QTLs mapped, there were 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. The epistasis and environment interaction analyses identified significant environmental effects on these traits. The identified QTL regions had disease resistance genes including R-genes and transcription factors. KASP markers were developed for major QTLs and validated in the population and are ready for further deployment in genomics-assisted breeding in peanut.

Keywords: Tomato spotted wilt virus; early leaf spot; high-density genetic map; late leaf spot; quantitative trait loci; whole-genome resequencing.

Figure 1

Circos plots showing the distribution of SNPs. (a) Homeologous SNPs: A01‐A10 represent A‐subgenome chromosomes, and corresponding originating threads represent SNPs identified on A‐chromosome but mapped on corresponding B‐LGs and vice versa for B01‐B10. (b) Translocated SNPs: SNPs identified on A‐ or B‐chromosomes but mapped on other chromosomes of either subgenome except for their homeologous (corresponding) chromosomes. Different coloured blocks represent the different LGs. Connecting coloured lines represent the homeologous and translocated SNP movement across various LGs based on the obtained LGs.

Figure 2

Genetic and QTL map of all the identified QTLs comprising SNP and SSR markers in the T‐population. (a) It represents the LOD values from 0 to 20 at an interval of 2 for each QTL, (b) it represents the QTLs identified in the study, (c) it represents the cM position of the SNP and SSR markers on the genetic map, and (d) it represents the LGs generated in the genetic map. Red corresponds to ELS QTL, green corresponds to LLS QTL, and black corresponds to TSWV QTL.

Figure 3

Snapshot displaying SNP genotyping with KASP assays using markers flanking the major QTLs for ELS and LLS. Different scenarios of validation of major QTL flanking SNPs B05_22527171 (a‐c) and A06_14301316 (d‐f) associated with ELS, A05_20406182 (g‐i), A03_134198144 (j‐l) and A05_82270000 (m‐o) associated with LLS segregating in the RIL population. Marker genotyping data generated for each genotype were viewed using the SNPviewer software (LGC Genomics). The scatter plot along x and y axes represents allelic discrimination for a particular marker in the examined population. Red and blue clusters represent the homozygous alleles showing polymorphism.

Figure 4

Graph showing correlation between the average disease severity scores (phenotype) and the five KASP validated SNPs. Vertical axis represents the average of disease severity, and horizontal axis shows the markers. Disease scores for the parents, Tifrunner (P1) and GT‐C20 (P2) for the season in that which QTL was detected are also shown for each marker. Unpaired t‐test was performed, and P‐values were estimated using the phenotyping data for number of alleles in population coming from Tifrunner and GT‐C20. Extremely statistically significant correlations are marked using *** with P‐value < 0.0001. Significant correlations are marked with *.