High oleic trait, resistance to rust and late leaf spot (LLS) are important breeding objectives in groundnut. Rust and LLS cause significant economic loss, and high oleic trait is an industry preferred trait that enhances economic returns. This study reports marker-assisted selection to introgress high oleic content, resistance to LLS and rust into Kadiri 6 (K 6), a popular cultivar. The alleles for target traits were selected using linked allele-specific, simple sequence repeats and single nucleotide polymorphic markers. The F 1 s (384), intercrossed F 1 s (441), BC 1 F 1 s (380), BC 1 F 2 s (195), and BC 1 F 3 s (343) were genotyped to obtain desired allelic combination. Sixteen plants were identified with homozygous high oleic, LLS and rust resistance alleles in BC 1 F 2 , which were advanced to BC 1 F 3 and evaluated for disease resistance, yield governing and nutritional quality traits. Phenotyping with Near-Infrared Reflectance Spectroscopy identified three lines (BC 1 F 3 -76, BC 1 F 3 -278, and BC 1 F 3 -296) with >80% oleic acid. The identified lines exhibit high levels of resistance to LLS and rust diseases (score of 3.0-4.0) with preferred pod and kernel features. The selected lines are under yield testing trials in multi-locations for release and commercialization. The lines reported here demonstrated combining high oleic trait with resistance to LLS and rust diseases.

Profiling the genetic composition and relationships among groundnut germplasm collections is essential for the breeding of new cultivars. The objectives of this study were to assess the genetic diversity and population structure among 100 improved groundnut genotypes using agronomic traits and high-density single nucleotide polymorphism (SNP) markers. The genotypes were evaluated for agronomic traits and drought tolerance at the International Crop Research Institute for the Semi-Arid Tropics (ICRISAT)/India across two seasons. Ninety-nine of the test genotypes were profiled with 16363 SNP markers. Pod yield per plant (PY), seed yield per plant (SY), and harvest index (HI) were significantly (p < 0.05) affected by genotype × environment interaction effects. Genotypes ICGV 07222, ICGV 06040, ICGV 01260, ICGV 15083, ICGV 10143, ICGV 03042, ICGV 06039, ICGV 14001, ICGV 11380, and ICGV 13200 ranked top in terms of pod yield under both drought-stressed and optimum conditions. PY exhibited a significant (p ≤ 0.05) correlation with SY, HI, and total biomass (TBM) under both test conditions. Based on the principal component (PC) analysis, PY, SY, HSW, shelling percentage (SHP), and HI were allocated in PC 1 and contributed to the maximum variability for yield under the two water regimes. Hence, selecting these traits could be successful for screening groundnut genotypes under drought-stressed and optimum conditions. The model-based population structure analysis grouped the studied genotypes into three sub-populations. Dendrogram for phenotypic and genotypic also grouped the studied 99 genotypes into three heterogeneous clusters. Analysis of molecular variance revealed that 98% of the total genetic variation was attributed to individuals, while only 2% of the total variance was due to variation among the subspecies. The genetic distance between the Spanish bunch and Virginia bunch types ranged from 0.11 to 0.52. The genotypes ICGV 13189, ICGV 95111, ICGV 14421, and ICGV 171007 were selected for further breeding based on their wide genetic divergence. Data presented in this study will guide groundnut cultivar development emphasizing economic traits and adaptation to water-limited agro-ecologies, including in Ethiopia.

The groundnut breeding program at International Crops Research Institute for the Semi-Arid Tropics routinely performs marker-based early generation selection (MEGS) in thousands of segregating populations. The existing MEGS includes planting of segregating populations in fields or glasshouses, label tagging, and sample collection using leaf-punch from 20–25 day old plants followed by genotyping with 10 single nucleotide polymorphisms based early generation selection marker panels in a high throughput genotyping (HTPG) platform. The entire process is laborious, time consuming, and costly. Therefore, in order to save the time of the breeder and to reduce the cost during MEGS, we optimized a single seed chipping (SSC) process based MEGS protocol and deployed on large scale by genotyping >3000 samples from ongoing groundnut breeding program. In SSC-based MEGS, we used a small portion of cotyledon by slicing-off the posterior end of the single seed and transferred to the 96-deep well plate for DNA isolation and genotyping at HTPG platform. The chipped seeds were placed in 96-well seed-box in the same order of 96-well DNA sampling plate to enable tracking back to the selected individual seed. A high germination rate of 95–99% from the chipped seeds indicated that slicing of seeds from posterior end does not significantly affect germination percentage. In addition, we could successfully advance 3.5 generations in a year using a low-cost rapid generation turnover glass-house facility as compared to routine practice of two generations in field conditions. The integration of SSC based genotyping and rapid generation advancement (RGA) could significantly reduce the operational requirement of person-hours and expenses, and save a period of 6–8 months in groundnut genetics and breeding research.

Spanish bunch groundnut varieties occupy most of the cultivated area in Asia and Africa, and these varieties lack required 2-3 weeks of fresh seed dormancy (FSD) hampering kernel quality. Genomic breeding can help to improve commercial groundnut cultivars for FSD in a shorter time with greater precision. In this regard, a recombinant inbred line (RIL) population from the cross ICGV 02266 (non-dormant) × ICGV 97045 (dormant) was developed and genotyped with a 5 K mid-density genotyping assay. A linkage map was constructed with 325 SNP loci spanning a total map length of 2335.3 cM and five major QTLs were identified on chromosomes Ah01, Ah11, Ah06, Ah16 and Ah17. Based on differential gene expression using transcriptomic information from dormant (Tifrunner) and non-dormant (ICGV 91114) genotypes, histone deacetylases, histone-lysine N-methyltransferase, cytochrome P450, protein kinases, and ethylene-responsive transcription factor were identified as key regulators involved in the hormonal regulation of dormancy. Six Kompetitive Allele Specific PCR (KASP) markers were successfully validated in the diverse panel including selected RILs of the same population and germplasm lines. These validated KASP markers could facilitate faster breeding of new varieties with desired dormancy using marker-assisted early generation selection.