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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.

Iron deficiency chlorosis (IDC) under calcareous and alkaline soils is a significant abiotic stress affecting the growth and yield of peanut. In this study, the genomic regions governing IDC tolerance were mapped using a recombinant inbred line (RIL) population derived from TMV 2 (susceptible to IDC) and TMV 2-NLM (tolerant to IDC), which was phenotyped during the rainy seasons of 2019 and 2020 in the iron-deficient calcareous plots. The best linear unbiased prediction (BLUP) values for IDC tolerance traits like visual chlorotic rating (VCR), and SPAD chlorophyll meter reading (SCMR) were used for QTL analysis along with a genetic map carrying 700 GBS-derived SNP, AhTE and SSR markers. In total, 11 and 12 main-effect QTLs were identified for VCR and SCMR, respectively. Among them three QTLs were major with the phenotypic variance explained (PVE) of 10.3–34.4% for VCR, and two QTL were major for SCMR with PVE of 11.5–11.7%. A region (159.3–178.3 cM) on chromosome Ah13 carrying two QTLs (one each for VCR and SCMR) was consistent with the previous report. A SNP marker, Ah14_138037990 identified from single marker analysis for VCR was located in the intronic region of the gene Arahy.QA0C1, which is important for protein-binding. Overall, this study identified new QTLs and also validated QTL for IDC tolerance. These genomic resources could be useful for genomics-assisted breeding of peanut for IDC tolerance.

Genomic regions governing water deficit stress tolerance were identified in peanut using a recombinant inbred line (RIL) population derived from an elite variety TMV 2 and its narrow leaf mutant TMV 2-NLM, which was evaluated over six-seasons at Dharwad (non-stress) and Tirupati (water-stress) in India. Stress condition could differentiate the RILs much better than the non-stress condition for the physiological traits. A linkage map with 700 markers was used to identify the quantitative trait loci (QTLs). Three sets of best linear unbiased predictions (BLUPs) were estimated for the drought tolerance traits for the rainy and post-rainy seasons at Dharwad and post-rainy seasons at Tirupati, and employed for single marker analysis, composite interval mapping and multiple QTL mapping. Of the 305 significant marker-trait associations for the 11 traits, only 21 were of major effect for pod yield per plant (PYPP), specific dry weight at 70 days after sowing (SDW_70) and specific leaf area at 70 DAS (SLA_70). Three major main effect QTLs were identified for PYPP with the highest phenotypic variance explained (PVE) of 10.5%. Nine QTLs with the highest PVE of 18.4% were identified for SDW_70, of which four QTLs were also governing SLA_70 with the highest PVE of 15.7%. A few of them were also involved in epistatic interactions, and formed multiple QTL mapping models. Five major QTLs for SDW_70 were stable over both the locations. Candidate genes with SNPs and AhMITE1 insertion were identified for the major QTL regions. A rare nonsynonymous SNP at Ah02_1558700 within the gene ArahyW1P0U6 governing PYPP was detected. Functional analysis of these candidate genes may be useful for future genetic modifications in addition to validating and using the linked markers for improving drought tolerance in peanut.

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.

Late leaf spot (LLS) caused by fungus Nothopassalora personata in groundnut is responsible for up to 50% yield loss. To dissect the complex nature of LLS resistance, comparative transcriptome analysis was performed using resistant (GPBD 4), susceptible (TAG 24) and a resistant introgression line (ICGV 13208) and identified a total of 12,164 and 9954 DEGs (differentially expressed genes) respectively in A- and B-subgenomes of tetraploid groundnut. There were 135 and 136 unique pathways triggered in A- and B-subgenomes, respectively, upon N. personata infection. Highly upregulated putative disease resistance genes, an RPP-13 like (Aradu.P20JR) and a NBS-LRR (Aradu.Z87JB) were identified on chromosome A02 and A03, respectively, for LLS resistance. Mildew resistance Locus (MLOs)-like proteins, heavy metal transport proteins, and ubiquitin protein ligase showed trend of upregulation in susceptible genotypes, while tetratricopeptide repeats (TPR), pentatricopeptide repeat (PPR), chitinases, glutathione S-transferases, purple acid phosphatases showed upregulation in resistant genotypes. However, the highly expressed ethylene responsive factor (ERF) and ethylene responsive nuclear protein (ERF2), and early responsive dehydration gene (ERD) might be related to the possible causes of defoliation in susceptible genotypes. The identified disease resistance genes can be deployed in genomics-assisted breeding for development of LLS resistant cultivars to reduce the yield loss in groundnut.

Aflatoxins are secondary metabolites produced by soilborne saprophytic fungus Aspergillus flavus and closely related species that infect several agricultural commodities including groundnut and maize. The consumption of contaminated commodities adversely affects the health of humans and livestock. Aflatoxin contamination also causes significant economic and financial losses to producers. Research efforts and significant progress have been made in the past three decades to understand the genetic behavior, molecular mechanisms, as well as the detailed biology of host-pathogen interactions. A range of omics approaches have facilitated better understanding of the resistance mechanisms and identified pathways involved during host-pathogen interactions. Most of such studies were however undertaken in groundnut and maize. Current efforts are geared toward harnessing knowledge on host-pathogen interactions and crop resistant factors that control aflatoxin contamination. This study provides a summary of the recent progress made in enhancing the understanding of the functional biology and molecular mechanisms associated with host-pathogen interactions during aflatoxin contamination in groundnut and maize.

A deep understanding of the genetic control of drought tolerance and iron deficiency tolerance is essential to hasten the process of developing improved varieties with higher tolerance through genomics-assisted breeding. In this context, an improved genetic map with 1205 loci was developed spanning 2598.3 cM with an average 2.2 cM distance between loci in the recombinant inbred line (TAG 24 × ICGV 86031) population using high-density 58K single nucleotide polymorphism (SNP) “Axiom_Arachis” array. Quantitative trait locus (QTL) analysis was performed using extensive phenotyping data generated for 20 drought tolerance- and two iron deficiency tolerance-related traits from eight seasons (2004–2015) at two locations in India, one in Niger, and one in Senegal. The genome-wide QTL discovery analysis identified 19 major main-effect QTLs with 10.0–33.9% phenotypic variation explained (PVE) for drought tolerance- and iron deficiency tolerance- related traits. Major main-effect QTLs were detected for haulm weight (20.1% PVE), SCMR (soil plant analytical development (SPAD) chlorophyll meter reading, 22.4% PVE), and visual chlorosis rate (33.9% PVE). Several important candidate genes encoding glycosyl hydrolases; malate dehydrogenases; microtubule-associated proteins; and transcription factors such as MADS-box, basic helix-loop-helix (bHLH), NAM, ATAF, and CUC (NAC), and myeloblastosis (MYB) were identified underlying these QTL regions. The putative function of these genes indicated their possible involvement in plant growth, development of seed and pod, and photosynthesis under drought or iron deficiency conditions in groundnut. These genomic regions and candidate genes, after validation, may be useful to develop molecular markers for deploying genomics-assisted breeding for enhancing groundnut yield under drought stress and iron-deficient soil conditions.

Multiparental genetic mapping populations such as nested‐association mapping (NAM) have great potential for investigating quantitative traits and associated genomic regions leading to rapid discovery of candidate genes and markers. To demonstrate the utility and power of this approach, two NAM populations, NAM_Tifrunner and NAM_Florida‐07, were used for dissecting genetic control of 100‐pod weight (PW) and 100‐seed weight (SW) in peanut. Two high‐density SNP‐based genetic maps were constructed with 3341 loci and 2668 loci for NAM_Tifrunner and NAM_Florida‐07, respectively. The quantitative trait locus (QTL) analysis identified 12 and 8 major effect QTLs for PW and SW, respectively, in NAM_Tifrunner, and 13 and 11 major effect QTLs for PW and SW, respectively, in NAM_Florida‐07. Most of the QTLs associated with PW and SW were mapped on the chromosomes A05, A06, B05 and B06. A genomewide association study (GWAS) analysis identified 19 and 28 highly significant SNP–trait associations (STAs) in NAM_Tifrunner and 11 and 17 STAs in NAM_Florida‐07 for PW and SW, respectively. These significant STAs were co‐localized, suggesting that PW and SW are co‐regulated by several candidate genes identified on chromosomes A05, A06, B05, and B06. This study demonstrates the utility of NAM population for genetic dissection of complex traits and performing high‐resolution trait mapping in peanut.

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 trait-linked 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.

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.

Groundnut (Arachis hypogaea) is an important global crop commodity and serves as a major source of cooking oil, diverse confectionery preparations and livestock feed. Stem rot disease caused by Sclerotium rolfsii is the most devastating disease of groundnut and can cause up to 100% yield loss. Genomic-assisted breeding (GAB) has potential for accelerated development of stem rot resistance varieties in short period with more precision. In this context, linkage analysis and quantitative trait locus (QTL) mapping for resistance to stem rot disease was performed in a bi-parental recombinant inbred line population developed from TG37A (susceptible) × NRCG-CS85 (resistant) comprising of 270 individuals. Genotyping-by-sequencing approach was deployed to generate single nucleotide polymorphism (SNP) genotyping data leading to development of a genetic map with 585 SNP loci spanning map distance of 2430 cM. QTL analysis using multi-season phenotyping and genotyping data could not detect any major main-effect QTL but identified 44 major epistatic QTLs with phenotypic variation explained ranging from 14.32 to 67.95%. Large number interactions indicate the complexity of genetic architecture of resistance to stem rot disease. A QTL of physical map length 5.2 Mb identified on B04 comprising 170 different genes especially leucine reach repeats, zinc finger motifs and ethyleneresponsive factors, etc., was identified. The identified genomic regions and candidate genes will further validate and facilitate marker development to deploy GAB for developing stem rot disease resistance groundnut varieties.

Aflatoxin is considered a “hidden poison” due to its slow and adverse effect on various biological pathways in humans, particularly among children, in whom it leads to delayed development, stunted growth, liver damage, and liver cancer. Unfortunately, the unpredictable behavior of the fungus as well as climatic conditions pose serious challenges in precise phenotyping, genetic prediction and genetic improvement, leaving the complete onus of preventing aflatoxin contamination in crops on post-harvest management. Equipping popular crop varieties with genetic resistance to aflatoxin is key to effective lowering of infection in farmer’s fields. A combination of genetic resistance for in vitro seed colonization (IVSC), pre-harvest aflatoxin contamination (PAC) and aflatoxin production together with pre- and post-harvest management may provide a sustainable solution to aflatoxin contamination. In this context, modern “omics” approaches, including next-generation genomics technologies, can provide improved and decisive information and genetic solutions. Preventing contamination will not only drastically boost the consumption and trade of the crops and products across nations/regions, but more importantly, stave off deleterious health problems among consumers across the globe.

About 90% of total groundnut is cultivated in the semi-arid tropic (SAT) regions of the world as a major oilseed and food crop and provides essential nutrients required by human diet. Climate change is the main threat to yield and quality of the produce in the SAT regions, and effects are already being seen in some temperate areas also. Rising CO2 levels, erratic rainfall, humidity, short episodes of high temperature and salinity hamper the physiology, disease resistance, fertility and yield as well as seed nutrient levels of groundnut. To meet growing demands of the increasing population against the threats of climate change, it is necessary to develop climate-smart varieties with enhanced and stable genetic improvements. Identifying key traits affected by climate change in groundnut will be important for developing an appropriate strategy for developing new varieties. Fast-changing scenarios of product ecologies as a consequence of climate change need faster development and replacement of improved varieties in the farmers’ fields to sustain yield and quality. Use of modern genomics technology is likely to help in improved understanding and efficient breeding for climate-smart traits such as tolerance to drought and heat, and biotic stresses such as foliar diseases, stem rot, peanut bud necrosis disease, and preharvest aflatoxin contamination. The novel promising technologies such as genomic selection and genome editing need to be tested for their potential utility in developing climate-smart groundnut varieties. System modeling may further improve the understanding and characterization of the problems of target ecologies for devising strategies to overcome the problem. The combination of conventional breeding techniques with genomics and system modeling approaches will lead to a new era of system biology assisted breeding for sustainable agricultural production to feed the ever-growing population.