Identification of two major quantitative trait locus for fresh seed dormancy using the diversity arrays technology and diversity arrays technology-seq based genetic map in Spanish-type peanuts

Seed quality for both germination in the next generation and for human consumption is adversely affected due to preharvest sprouting in peanut. It also makes seeds more vulnerable to infection by a number of pathogens. Therefore, it is desirable to have 2–3 weeks of fresh seed dormancy (FSD) in the peanut varieties. In this context, one F2 population was developed from a cross between non-dormant (ICGV 00350) and dormant (ICGV 97045) genotypes. Phenotyping of this population showed control of the trait by two recessive genes. In parallel, genotyping of the population with Diversity Arrays Technology (DArT) and DArT-seq markers provided a genetic map with 1152 loci covering a map distance of 2423.12 cM and map density of 2.96 cM/loci. Quantitative trait locus (QTL) analysis identified two major QTLs, namely qfsd-1 and qfsd-2 explaining 22.14% and 71.21% of phenotypic variation, respectively. These QTLs, after validation in different genetic backgrounds, may be useful for molecular breeding for FSD in peanut

Improvement of three popular Indian groundnut varieties for foliar disease resistance and high oleic acid using SSR markers and SNP array in marker-assisted backcrossing

Foliar fungal diseases (rust and late leaf spot) incur large yield losses, in addition to the deterioration of fodder quality in groundnut worldwide. High oleic acid has emerged as a key market trait in groundnut, as it increases the shelf life of the produce/products in addition to providing health benefits to consumers. Marker-assisted backcrossing (MABC) is the most successful approach to introgressing or pyramiding one or more traits using traitlinked markers. We used MABC to improve three popular Indian cultivars (GJG 9, GG 20, and GJGHPS 1) for foliar disease resistance (FDR) and high oleic acid content. A total of 22 BC3F4 and 30 BC2F4 introgression lines (ILs) for FDR and 46 BC3F4 and 41 BC2F4 ILs for high oleic acid were developed. Recurrent parent genome analysis using the 58 K Axiom_Arachis array identified several lines showing upto 94% of genome recovery among second and third backcross progenies. Phenotyping of these ILs revealed FDR scores comparable to the resistant parent, GPBD 4, and ILs with high (~80%) oleic acid in addition to high genome recovery. These ILs provide further opportunities for pyramiding FDR and high oleic acid in all three genetic backgrounds as well as for conducting multi-location yield trials for further evaluation and release for cultivation in target regions of India

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

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

Whole‐genome resequencing‐based QTL ‐seq identified candidate genes and molecular markers for fresh seed dormancy in groundnut

The subspecies fastigiata of cultivated groundnut lost fresh seed dormancy (FSD) during domestication and human‐made selection. Groundnut varieties lacking FSD experience precocious seed germination during harvest imposing severe losses. Development of easy‐to‐use genetic markers enables early‐generation selection in different molecular breeding approaches. In this context, one recombinant inbred lines (RIL) population (ICGV 00350 × ICGV 97045) segregating for FSD was used for deploying QTL‐seq approach for identification of key genomic regions and candidate genes. Whole‐genome sequencing (WGS) data (87.93 Gbp) were generated and analysed for the dormant parent (ICGV 97045) and two DNA pools (dormant and nondormant). After analysis of resequenced data from the pooled samples with dormant parent (reference genome), we calculated delta‐SNP index and identified a total of 10,759 genomewide high‐confidence SNPs. Two candidate genomic regions spanning 2.4 Mb and 0.74 Mb on the B05 and A09 pseudomolecules, respectively, were identified controlling FSD. Two candidate genes—RING‐H2 finger protein and zeaxanthin epoxidase—were identified in these two regions, which significantly express during seed development and control abscisic acid (ABA) accumulation. QTL‐seq study presented here laid out development of a marker, GMFSD1, which was validated on a diverse panel and could be used in molecular breeding to improve dormancy in groundnut

Molecular breeding for introgression of fatty acid desaturase mutant alleles (ahFAD2A and ahFAD2B) enhances oil quality in high and low oil containing peanut genotypes

High oleate peanuts have two marketable benefits, health benefits to consumers and extended shelf life of peanut products. Two mutant alleles present on linkage group a09 ( ahFAD2A) and b09 ( ahFAD2B) control composition of three major fatty acids, oleic, linoleic and palmitic acids which together determine peanut oil quality. In conventional breeding, selection for fatty acid composition is delayed to advanced generations. However by using DNA markers, breeders can reject large number of plants in early generations and therefore can optimize time and resources. Here, two approaches of molecular breeding namely marker-assisted backcrossing (MABC) and marker-assisted selection (MAS) were employed to transfer two FAD2mutant alleles from SunOleic 95R into the genetic background of ICGV 6110, ICGV 6142 and ICGV 6420. In summary, 82 MABC and 387 MAS derived introgression lines (ILs) were developed using DNA markers with elevated oleic acid varying from 62 to 83%. Oleic acid increased by 0.5-1.1 folds, with concomitant reduction of linoleic acid by 0.4-1.0 folds and palmitic acid by 0.1-0.6 folds among ILs compared to recurrent parents. Finally, high oleate ILs, 27 with high oil (53.0-57.9%), and 28 ILs with low oil content (42.4-49.9%) were selected that may be released for cultivation upon further evaluation

Genome-based trait prediction in multi- environment breeding trials in groundnut

Genomic selection (GS) can be an efficient and cost-effective breeding approach which captures both small- and large-effect genetic factors and therefore promises to achieve higher genetic gains for complex traits such as yield and oil content in groundnut. A training population was constituted with 340 elite lines followed by genotyping with 58 K ‘Axiom_Arachis’ SNP array and phenotyping for key agronomic traits at three locations in India. Four GS models were tested using three different random cross-validation schemes (CV0, CV1 and CV2). These models are: (1) model 1 (M1 = E + L) which includes the main effects of environment (E) and line (L); (2) model 2 (M2 = E + L + G) which includes the main effects of markers (G) in addition to E and L; (3) model 3 (M3 = E + L + G + GE), a naïve interaction model; and (4) model 4 (E + L + G + LE + GE), a naïve and informed interaction model. Prediction accuracy estimated for four models indicated clear advantage of the inclusion of marker information which was reflected in better prediction accuracy achieved with models M2, M3 and M4 as compared to M1 model. High prediction accuracies (> 0.600) were observed for days to 50% flowering, days to maturity, hundred seed weight, oleic acid, rust@90 days, rust@105 days and late leaf spot@90 days, while medium prediction accuracies (0.400–0.600) were obtained for pods/plant, shelling %, and total yield/plant. Assessment of comparative prediction accuracy for different GS models to perform selection for untested genotypes, and unobserved and unevaluated environments provided greater insights on potential application of GS breeding in groundnut

Molecular mapping of oil content and fatty acids using dense genetic maps in groundnut (Arachis hypogaea L.)

Enhancing seed oil content with desirable fatty acid composition is one of the most important objectives of groundnut breeding programs globally. Genomics-assisted breeding facilitates combining multiple traits faster, however, requires linked markers. In this context, we have developed two different F2 mapping populations, one for oil content (OC-population, ICGV 07368 × ICGV 06420) and another for fatty acid composition (FA-population, ICGV 06420 × SunOleic 95R). These two populations were phenotyped for respective traits and genotyped using Diversity Array Technology (DArT) and DArTseq genotyping platforms. Two genetic maps were developed with 854 (OC-population) and 1,435 (FA-population) marker loci with total map distance of 3,526 and 1,869 cM, respectively. Quantitative trait locus (QTL) analysis using genotyping and phenotyping data identified eight QTLs for oil content including two major QTLs, qOc-A10 and qOc-A02, with 22.11 and 10.37% phenotypic variance explained (PVE), respectively. For seven different fatty acids, a total of 21 QTLs with 7.6–78.6% PVE were identified and 20 of these QTLs were of major effect. Two mutant alleles, ahFAD2B and ahFAD2A, also had 18.44 and 10.78% PVE for palmitic acid, in addition to oleic (33.8 and 17.4% PVE) and linoleic (41.0 and 19.5% PVE) acids. Furthermore, four QTL clusters harboring more than three QTLs for fatty acids were identified on the three LGs. The QTLs identified in this study could be further dissected for candidate gene discovery and development of diagnostic markers for breeding improved groundnut varieties with high oil content and desirable oil quality

Whole‐genome resequencing‐based QTL ‐seq identified candidate genes and molecular markers for fresh seed dormancy in groundnut

The subspecies fastigiata of cultivated groundnut lost fresh seed dormancy (FSD) during domestication and human‐made selection. Groundnut varieties lacking FSD experience precocious seed germination during harvest imposing severe losses. Development of easy‐to‐use genetic markers enables early‐generation selection in different molecular breeding approaches. In this context, one recombinant inbred lines (RIL) population (ICGV 00350 × ICGV 97045) segregating for FSD was used for deploying QTL‐seq approach for identification of key genomic regions and candidate genes. Whole‐genome sequencing (WGS) data (87.93 Gbp) were generated and analysed for the dormant parent (ICGV 97045) and two DNA pools (dormant and nondormant). After analysis of resequenced data from the pooled samples with dormant parent (reference genome), we calculated delta‐SNP index and identified a total of 10,759 genomewide high‐confidence SNPs. Two candidate genomic regions spanning 2.4 Mb and 0.74 Mb on the B05 and A09 pseudomolecules, respectively, were identified controlling FSD. Two candidate genes—RING‐H2 finger protein and zeaxanthin epoxidase—were identified in these two regions, which significantly express during seed development and control abscisic acid (ABA) accumulation. QTL‐seq study presented here laid out development of a marker, GMFSD1, which was validated on a diverse panel and could be used in molecular breeding to improve dormancy in groundnut

SSR markers associated to early leaf spot disease resistance through selective genotyping and single marker analysis in groundnut ( Arachis hypogaea L.)

Groundnut (Arachis hypogaea L.) is an important oilseed and food crop of the world. Breeding for disease resistance is one of major objectives in groundnut breeding. Early leaf spot (ELS) is one of the major destructive diseases worldwide and in West Africa, particularly in Burkina Faso causing significant yield losses. Conventional breeding approaches have been employed to develop improved varieties resistant to ELS. Molecular dissection of resistance traits using QTL analysis can improve the efficiency of resistance breeding. In the present study, an ELS susceptible genotype QH243C and an ELS resistant genotype NAMA were crossed and the F2 population genotypic and F3 progenies phenotypic data were used for marker-trait association analysis. Parents were surveyed with 179 simple sequence repeat (SSR) markers out of which 103 SSR markers were found to be polymorphic between the parents. These polymorphic markers were utilized to genotype the F2 population followed by marker-trait analysis through single marker analysis (SMA) and selective genotyping of the population using 23 resistant and 23 susceptible genotypes. The SMA revealed 13 markers while the selective genotyping method identified 8 markers associated with ELS resistance. Four markers (GM1911, GM1883, GM1000 and Seq13E09) were found common between the two trait mapping methods. These four markers could be employed in genomics-assisted breeding for selection of ELS resistant genotypes in groundnut breeding

Identification of two major quantitative trait locus for fresh seed dormancy using the diversity arrays technology and diversity arrays technology-seq based genetic map in Spanish-type peanuts

Seed quality for both germination in the next generation and for human consumption is adversely affected due to preharvest sprouting in peanut. It also makes seeds more vulnerable to infection by a number of pathogens. Therefore, it is desirable to have 2–3 weeks of fresh seed dormancy (FSD) in the peanut varieties. In this context, one F2 population was developed from a cross between non-dormant (ICGV 00350) and dormant (ICGV 97045) genotypes. Phenotyping of this population showed control of the trait by two recessive genes. In parallel, genotyping of the population with Diversity Arrays Technology (DArT) and DArT-seq markers provided a genetic map with 1152 loci covering a map distance of 2423.12 cM and map density of 2.96 cM/loci. Quantitative trait locus (QTL) analysis identified two major QTLs, namely qfsd-1 and qfsd-2 explaining 22.14% and 71.21% of phenotypic variation, respectively. These QTLs, after validation in different genetic backgrounds, may be useful for molecular breeding for FSD in peanut