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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.

Pre-harvest aflatoxin contamination (PAC) in groundnut is a serious quality concern globally, and drought stress before harvest further exacerbate its intensity, leading to the deterioration of produce quality. Understanding the host–pathogen interaction and identifying the candidate genes responsible for resistance to PAC will provide insights into the defense mechanism of the groundnut. In this context, about 971.63 million reads have been generated from 16 RNA samples under controlled and Aspergillus flavus infected conditions, from one susceptible and seven resistant genotypes. The RNA-seq analysis identified 45,336 genome-wide transcripts under control and infected conditions. This study identified 57 transcription factor (TF) families with major contributions from 6570 genes coding for bHLH (719), MYB-related (479), NAC (437), FAR1 family protein (320), and a few other families. In the host (groundnut), defense-related genes such as senescence-associated proteins, resveratrol synthase, seed linoleate, pathogenesis-related proteins, peroxidases, glutathione-S-transferases, chalcone synthase, ABA-responsive gene, and chitinases were found to be differentially expressed among resistant genotypes as compared to susceptible genotypes. This study also indicated the vital role of ABA-responsive ABR17, which co-regulates the genes of ABA responsive elements during drought stress, while providing resistance against A. flavus infection. It belongs to the PR-10 class and is also present in several plant–pathogen interactions.

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.

Spatio‐temporal and developmental stage‐specific transcriptome analysis plays a crucial role in systems biology‐based improvement of any species. In this context, we report here the Arachis hypogaea gene expression atlas (AhGEA) for the world's widest cultivated subsp. fastigiata based on RNA‐seq data using 20 diverse tissues across five key developmental stages. Approximately 480 million paired‐end filtered reads were generated followed by identification of 81 901 transcripts from an early‐maturing, high‐yielding, drought‐tolerant groundnut variety, ICGV 91114. Further, 57 344 genome‐wide transcripts were identified with ≥1 FPKM across different tissues and stages. Our in‐depth analysis of the global transcriptome sheds light into complex regulatory networks namely gravitropism and photomorphogenesis, seed development, allergens and oil biosynthesis in groundnut. Importantly, interesting insights into molecular basis of seed development and nodulation have immense potential for translational genomics research. We have also identified a set of stable expressing transcripts across the selected tissues, which could be utilized as internal controls in groundnut functional genomics studies. The AhGEA revealed potential transcripts associated with allergens, which upon appropriate validation could be deployed in the coming years to develop consumer‐friendly groundnut varieties. Taken together, the AhGEA touches upon various important and key features of cultivated groundnut and provides a reference for further functional, comparative and translational genomics research for various economically important traits.

Aflatoxin production by isolates of Aspergillus flavus varies, ranging from highly toxigenic to completely atoxigenic. Several mechanisms have been identified which regulate aflatoxin production including medium carbon source and oxidative stress. In recent studies, aflatoxin production has been implicated in partially ameliorating oxidative stress in A. flavus. To better understand the role of aflatoxin production in oxidative stress responses, a selection of toxigenic and atoxigenic isolates of A. flavus with moderate to high oxidative stress tolerance were exposed to increasing concentrations of H2O2 in both aflatoxin-conducive and non-conducive media. Mycelial mats were collected for global transcriptome sequencing followed by differential expression, functional prediction, and weighted co-expression analyses. Oxidative stress and medium carbon source had a significant effect on the expression of several secondary metabolite gene clusters including those for aflatoxin, aflatrem, aflavarin, cyclopiazonic acid, and kojic acid. Atoxigenic biological control isolates showed less differential expression under stress than other atoxigenic isolates suggesting expression profiles may be useful in screening. Increasing stress also resulted in regulation of SakA/Hog1 and MpkA MAP kinase signalling pathways pointing to their potential roles in regulating oxidative stress responses. Their expression was also influenced by medium carbon source. These results suggest that aflatoxin production along with that of other mycotoxins may occur as part of a concerted coping mechanism for oxidative stress and its effects in the environment. This mechanism is also regulated by availability of simple sugars and glycolytic compounds for their biosynthesis.

Drought is one of the main constraints in peanut production in West Texas and eastern New Mexico regions due to the depletion of groundwater. A multi-seasonal phenotypic analysis of 10 peanut genotypes revealed C76-16 (C-76) and Valencia-C (Val-C) as the best and poor performers under deficit irrigation (DI) in West Texas, respectively. In order to decipher transcriptome changes under DI, RNA-seq was performed in C-76 and Val-C. Approximately 369 million raw reads were generated from 12 different libraries of two genotypes subjected to fully irrigated (FI) and DI conditions, of which ~329 million (90.2%) filtered reads were mapped to the diploid ancestors of peanut. The transcriptome analysis detected 4,508 differentially expressed genes (DEGs), 1554 genes encoding transcription factors (TFs) and a total of 514 single nucleotide polymorphisms (SNPs) among the identified DEGs. The comparative analysis between the two genotypes revealed higher and integral tolerance in C-76 through activation of key genes involved in ABA and sucrose metabolic pathways. Interestingly, one SNP from the gene coding F-box protein (Araip.3WN1Q) and another SNP from gene coding for the lipid transfer protein (Aradu.03ENG) showed polymorphism in selected contrasting genotypes. These SNPs after further validation may be useful for performing early generation selection for selecting drought-responsive genotypes.

Aflatoxin-affected groundnut or peanut presents a major global health issue to both commercial and subsistence farming. Therefore, understanding the genetic and molecular mechanisms associated with resistance to aflatoxin production during host–pathogen interactions is crucial for breeding groundnut cultivars with minimal level of aflatoxin contamination. Here, we performed gene expression profiling to better understand the mechanisms involved in reduction and prevention of aflatoxin contamination resulting from Aspergillus flavus infection in groundnut seeds. RNA sequencing (RNA-Seq) of 16 samples from different time points during infection (24 h, 48 h, 72 h and the 7th day after inoculation) in U 4-7-5 (resistant) and JL 24 (susceptible) genotypes yielded 840.5 million raw reads with an average of 52.5 million reads per sample. A total of 1779 unique differentially expressed genes (DEGs) were identified. Furthermore, comprehensive analysis revealed several pathways, such as disease resistance, hormone biosynthetic signaling, flavonoid biosynthesis, reactive oxygen species (ROS) detoxifying, cell wall metabolism and catabolizing and seed germination. We also detected several highly upregulated transcription factors, such as ARF, DBB, MYB, NAC and C2H2 in the resistant genotype in comparison to the susceptible genotype after inoculation. Moreover, RNA-Seq analysis suggested the occurrence of coordinated control of key pathways controlling cellular physiology and metabolism upon A. flavus infection, resulting in reduced aflatoxin production.

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.

Peanut or groundnut (Arachis hypogaea), grown and consumed in several Asian and African countries in addition to Americas, plays an important role in providing daily nutritional requirement for large population of the world. Aflatoxin contamination and allergens are the major quality and food safety concerns across globe which adversely impact the global peanut trade and commerce. On the other hand, high oleic acid is an industry preferred trait for imparting increased shelf life to peanut-based products. Through precise phenotyping, genomics, transcriptomics and molecular breeding approaches, we are developing better understanding of these traits, conducting trait mapping and candidate gene discovery, and deploying molecular breeding for developing improved peanut varieties. For example, transcriptome analysis have identified several important candidate genes and pathways for three different types of resistance mechanisms of aflatoxin contamination namely in vitro seed colonization (IVSC), pre-harvest aflatoxin contamination (PAC), and aflatoxin production (AP). Further, genetic analysis of multi-parent advanced generation intercross (MAGIC) and genome-wide association study (GWAS) on a diverse association mapping panel are likely to provide associated genomic regions and candidate genes for aflatoxin contamination. Development and deployment of precise ELISA-based methods for quantifying five major and important peanut allergens (Ara h 1, Ara h 2, Ara h 3, Ara h 6 and Ara h 8) have led to the identification of several hypoallergenic lines. Subsequently sequence/GWAS analysis is likely to identify the alleles responsible for making peanut, hypo or hyper allergenic. Allele-specific genetic markers were successfully deployed for developing several high oleic molecular breeding lines in multiple genetic backgrounds. Many of these lines are in final year of testing in India and are most likely to get released in 2019 for cultivation. Identification and development of i

Aspergillus flavus is an opportunistic pathogen of plants such as maize and peanut under conducive conditions such as drought stress resulting in significant aflatoxin production. Drought-associated oxidative stress also exacerbates aflatoxin production by A. flavus. The objectives of this study were to use proteomics to provide insights into the pathogen responses to H2O2-derived oxidative stress, and to identify potential biomarkers and targets for host resistance breeding. Three isolates, AF13, NRRL3357, and K54A with high, moderate, and no aflatoxin production, were cultured in medium supplemented with varying levels of H2O2, and examined using an iTRAQ (Isobaric Tags for Relative and Absolute Quantification) approach. Overall, 1,173 proteins were identified and 220 were differentially expressed (DEPs). Observed DEPs encompassed metabolic pathways including antioxidants, carbohydrates, pathogenicity, and secondary metabolism. Increased lytic enzyme, secondary metabolite, and developmental pathway expression in AF13 was correlated with oxidative stress tolerance, likely assisting in plant infection and microbial competition. Elevated expression of energy and cellular component production in NRRL3357 and K54A implies a focus on oxidative damage remediation. These trends explain isolate-to-isolate variation in oxidative stress tolerance and provide insights into mechanisms relevant to host plant interactions under drought stress allowing for more targeted efforts in host resistance research.

The published online version of this article unfortunately missed to capture Rajeev K. Varshney as co-corresponding author. There should have been two corresponding authors for this paper (Rajeev K. Varshney and Ramesh S. Bhat). The correct declaration is shown below.

Aflatoxin contamination, caused by fungal pathogen Aspergillus flavus, is a major quality and health problem delimiting the trade and consumption of groundnut (Arachis hypogaea L.) worldwide. RNA-seq approach was deployed to understand the host-pathogen interaction by identifying differentially expressed genes (DEGs) for resistance to in-vitro seed colonization (IVSC) at four critical stages after inoculation in J 11 (resistant) and JL 24 (susceptible) genotypes of groundnut. About 1,344.04 million sequencing reads have been generated from sixteen libraries representing four stages in control and infected conditions. About 64% and 67% of quality filtered reads (1,148.09 million) were mapped onto A (A. duranensis) and B (A. ipaёnsis) subgenomes of groundnut respectively. About 101 million unaligned reads each from J 11 and JL 24 were used to map onto A. flavus genome. As a result, 4,445 DEGs including defense-related genes like senescence-associated proteins, resveratrol synthase, 9s-lipoxygenase, pathogenesis-related proteins were identified. In A. flavus, about 578 DEGs coding for growth and development of fungus, aflatoxin biosynthesis, binding, transport, and signaling were identified in compatible interaction. Besides identifying candidate genes for IVSC resistance in groundnut, the study identified the genes involved in host-pathogen cross-talks and markers that can be used in breeding resistant varieties.

Biotic stress in legume crops is one of the major threats to crop yield and productivity. Being sessile organisms, plants have evolved a myriad of mechanisms to combat different stresses imposed on them. One such mechanism, deciphered in the last decade, is small RNA (sRNA) mediated defense in plants. Small RNAs (sRNAs) have emerged as one of the major players in gene expression regulation in plants during developmental stages and under stress conditions. They are known to act both at transcriptional and post-transcriptional levels. Dicer-like (DCL), Argonaute (AGO), and RNA dependent RNA polymerase (RDR) constitute the major components of sRNA biogenesis machinery and are known to play a significant role in combating biotic and abiotic stresses. This study is, therefore, focused on identification and characterization of sRNA biogenesis proteins in three important legume crops, namely chickpea, pigeonpea, and groundnut. Phylogenetic analysis of these proteins between legume species classified them into distinct clades and suggests the evolutionary conservation of these genes across the members of Papillionidoids subfamily. Variable expression of sRNA biogenesis genes in response to the biotic stresses among the three legumes indicate the possible existence of specialized regulatory mechanisms in different legumes. This is the first ever study to understand the role of sRNA biogenesis genes in response to pathogen attacks in the studied legumes.

Single nucleotide polymorphisms (SNPs) are the most abundant DNA sequence variation in the genomes which can be used to associate genotypic variation to the phenotype. Therefore, availability of a high-density SNP array with uniform genome coverage can advance genetic studies and breeding applications. Here we report the development of a high-density SNP array ‘Axiom_Arachis’ with 58 K SNPs and its utility in groundnut genetic diversity study. In this context, from a total of 163,782 SNPs derived from DNA resequencing and RNA-sequencing of 41 groundnut accessions and wild diploid ancestors, a total of 58,233 unique and informative SNPs were selected for developing the array. In addition to cultivated groundnuts (Arachis hypogaea), fair representation was kept for other diploids (A. duranensis, A. stenosperma, A. cardenasii, A. magna and A. batizocoi). Genotyping of the groundnut ‘Reference Set’ containing 300 genotypes identified 44,424 polymorphic SNPs and genetic diversity analysis provided in-depth insights into the genetic architecture of this material. The availability of the high-density SNP array ‘Axiom_Arachis’ with 58 K SNPs will accelerate the process of high resolution trait genetics and molecular breeding in cultivated groundnut.

Peanut (Arachis hypogaea; 2n = 4x = 40) is a nutritious food and a good source of vitamins, minerals, and healthy fats. Expansion of genetic and genomic resources for genetic enhancement of cultivated peanut has gained momentum from the sequenced genomes of the diploid ancestors of cultivated peanut. To facilitate high-throughput genotyping of Arachis species, 20 genotypes were re-sequenced and genome-wide single nucleotide polymorphisms (SNPs) were selected to develop a large-scale SNP genotyping array. For flexibility in genotyping applications, SNPs polymorphic between tetraploid and diploid species were included for use in cultivated and interspecific populations. A set of 384 accessions was used to test the array resulting in 54 564 markers that produced high-quality polymorphic clusters between diploid species, 47 116 polymorphic markers between cultivated and interspecific hybrids, and 15 897 polymorphic markers within A. hypogaea germplasm. An additional 1193 markers were identified that illuminated genomic regions exhibiting tetrasomic recombination. Furthermore, a set of elite cultivars that make up the pedigree of US runner germplasm were genotyped and used to identify genomic regions that have undergone positive selection. These observations provide key insights on the inclusion of new genetic diversity in cultivated peanut and will inform the development of high-resolution mapping populations. Due to its efficiency, scope, and flexibility, the newly developed SNP array will be very useful for further genetic and breeding applications in Arachis.

Genome complexity and narrow genetic base are the major problems that hinder achieving accelerated genetic gains in groundnut or peanut, a major source of vegetable oil (48%) and protein (25%). High density genotyping is a must-have genomic resource in a crop for use in several genetic and breeding applications. Availability of genome sequence for both the diploid genome progenitors of cultivated groundnut has provided an opportunity for discovery of structural variations in large-scale including single nucleotide polymorphisms (SNPs), the most abundant DNA sequence variation in the genomes. In this context, we developed a high-density SNP array ‘Axiom_Arachis’ with 58K SNPs with uniform genome coverage. We identified initially a total of 163,782 SNPs that included 118,860 SNPs (58,438 SNPs for A-genome and 60,422 SNPs for B-genome) from 30 tetraploids and 44,922 SNPs (39,937 SNPs for A-genome and 4,985 SNPs for B-genome) from 11 diploids. Finally, a total of 58,233 highly informative SNPs with genome specificity were used for array development. In addition to cultivated groundnuts (Arachis hypogaea), this array has fair representation of other diploids (A. duranensis, A. stenosperma, A. cardenasii, A. magna and A. batizocoi). Genotyping of the groundnut ‘Reference Set’ containing 300 genotypes identified 44,424 polymorphic SNPs and genetic diversity analysis provided in-depth insights into the genetic architecture of this material. In summary, this high-density SNP array will accelerate the process of trait dissection and molecular breeding including genomic selection for achieving higher genetic gains in groundnut.

Aflatoxin contamination, caused by fungal pathogen Aspergillus flavus, is the major quality and health problem delimiting the trade and consumption of groundnut (Arachis hypogaea L.) worldwide. Three types of aflatoxin resistance mechanisms namely, resistance to in-vitro seed colonization (IVSC), pre-harvest aflatoxin contamination (PAC) and aflatoxin production (AP) have been reported in groundnut. Transcriptome sequencing approach was used to study the differentially expressed genes that differ in-vitro seed colonization (IVSC) in resistant (J 11) and susceptible (JL 24) genotypes. A total of 1,344 million raw reads with an average of 84 million reads per sample were generated from 16 libraries from four different stages of fungal infection. A total of 737.75 and 770.83 million reads were mapped on the progenitor genomes- A subgenome (A. duranensis) and B subgenome (A. ipaensis) of cultivated groundnut (A. hypogaea), respectively. In groundnut, defense related genes like senescence associated proteins, resveratrol synthase, seed linoleate 9s-lipoxygenases (9s-LOX), pathogenesis related proteins, peroxidases, glutathione- S-transferases, chalcone synthase, defensin and chitinases were differentially expressed. In A. flavus, the genes involved in growth and development of fungus, aflatoxin biosynthesis, binding and transporter proteins were found to be induced in compatible interaction. In addition to IVSC resistance, we have also carried out transcriptome sequencing for PAC and AP resistance. In summary, this study will provide greater insights on the resistance mechanisms and discovery of candidate genes for all the three mechanisms that can further be used as expression markers in genomics-enabled aflatoxin resistance breeding.

Valencia peanuts are highly susceptible to drought stress. The yield reduction due to stress can result in more than 50% reduction resulting in high aflatoxin contamination. In our present study we have compared Valencia-C genotype with a highly drought tolerant runner type peanut C76-16 using transcriptome sequencing to investigate tissue-specific gene expression and response to abiotic stress. We evaluated the two genotypes under field conditions under irrigated and stress plots in 4 replications. We found that genotype C76-16 outperformed yield compared to Valencia-C under drought stress conditions with only a 30 % reduction in yield while Valencia-C showed a higher loss of up to 70%. Each year the yield varied widely due to the environmental factors but C76-16 was consistently ranked among the top and suffered a minimal loss of yield suggesting that it is best suited for the erratic climatic conditions of southwest U.S. Leave samples were harvested from the control and stress conditions and used for RNA isolation and sequencing. A total of 340 million paired-end reads were generated and were used to find differentially expressed genes and transcripts between tolerant and susceptible genotypes. The pathways and candidate genes involved in drought tolerance will provide basic information and expression markers for drought tolerance in peanut. We will present our findings on genic content and tissue-specific gene expression and discuss the challenges and opportunities of unifying transcript sequence data for the peanut community.

Advances in availability of genomic resources coupled with genetic resources have accelerated the process of developing better understanding of cytogenetics and genetics of peanut using modern technologies. The cytogenetic studies provided greater insights on chromosomal structures and behaviour of different Arachis species along with their genetic relationship with each other. Researchers are moving faster now in using single nucleotide polymorphism (SNP) markers in their genetic studies as simple sequence repeats (SSRs) did not provide optimum genome density for genetic mapping studies in peanut. Due to availability of reference genome of diploid progenitors, resequencing of some genotypes and soon to be available tetraploid genome, a high-density genotyping array with 58 K SNPs is now available for conducting high-resolution mapping in peanut. ICRISAT has developed next generation genetic mapping populations such as multi-parent advanced generation intercross (MAGIC) and nested association mapping (NAM) populations for conducting high-resolution trait mapping for multiple traits in one go. Affordability of sequencing also encouraged initiation of sequence-based trait mapping such as QTL-seq for dissecting foliar disease resistance trait. Few successful examples are available in peanut regarding development of diagnostic markers and their deployment in breeding to develop improved genotypes, which may see a significant increase in coming years for developing appropriate genomics tools for breeding in peanut.

Marker-assisted selection (MAS) is a method of selecting desirable individuals in a breeding program based on molecular markers with or without consideration of their trait values. This allows indirect selection of specific characteristics of a plant based on the encoding genomic region. The introduction of next-generation sequencing technology and the availability of inexpensive and high-throughput marker systems have made molecular breeding more attractive. Marker-assisted breeding strategies such as marker-assisted backcross breeding, marker-assisted recurrent selection, and genomic selection were known to be successful in crop improvement. Nonetheless, conventional breeding and MAS are not mutually exclusive, instead they complement each other in most of the breeding methods, and therefore, in true sense they constitute integrated breeding. Definition and Background: The objective of plant breeding is to identify and develop superior individual(s) with desirable traits by selection, hybridization, heterosis, or mutation. Until twentieth century, plant breeding was based on the phenotypic selection based on yield, plant architecture preference, quality traits, ease of cultivation, and tolerance to biotic and abiotic stresses. Over the years, plant breeding technologies, such as pedigree, backcrossing, recurrent selection, and progeny testing, made an impact on crop improvement. With the discovery of molecular markers during the late twentieth century, the scenario of plant breeding started changing gradually. The fact that desirable lines can be selected based on molecular markers linked to the traits, at the seedling stage in a short time period is an attractive option for plant breeders, who in general spend about 5–8 years for the varietal release. Molecular markers are used as a substitute/supplement for the phenotypic selection to alter or improve the traits for crop improvement. In the initial years, breeders were reluctant to use the markers in their routi

Cultivated peanut (Arachis hypogaea) is an allotetraploid with closely related subgenomes of a total size of ~2.7 Gb. To understand the genome of the cultivated peanut, it is prerequisite to know the genome organization of its diploid progenitors, A-genome—Arachis duranensis and B-genome—A. ipaensis. Two genome sequencing projects conducted sequencing and analysis of the genomes of diploid ancestors: (1) International Peanut Genome Initiative (IPGI) reported the sequencing of both A- and B-genomes; while (2) Diploid Progenitor Peanut Arachis Genome Sequencing Consortium (DPPAGSC) reported the sequencing of A-genome. IPGI study showed that these genomes are similar to cultivated peanut’s A- and B-subgenomes and used them to identify candidate disease resistance genes, to guide tetraploid transcript assemblies and to detect genetic exchange between cultivated peanut’s subgenomes thus providing evidence about direct descendant of the B subgenome in cultivated peanut. The DPPAGSC study, on the other hand, provided new insights into geocarpy, oil biosynthesis, and allergens in addition to providing information about evolution and polyploidization. These genome sequencing efforts have improved the understanding about the complex peanut genome and genome architecture which will play a very important role in peanut applied genomics and breeding.

The infection of maize and peanut with Aspergillus flavus and subsequent contamination with aflatoxin pose a threat to global food safety and human health, and is exacerbated by drought stress. Drought stress-responding compounds such as reactive oxygen species (ROS) are associated with fungal stress responsive signaling and secondary metabolite production, and can stimulate the production of aflatoxin by A. flavus in vitro. These secondary metabolites have been shown to possess diverse functions in soil-borne fungi including antibiosis, competitive inhibition of other microbes, and abiotic stress alleviation. Previously, we observed that isolates of A. flavus showed differences in oxidative stress tolerance which correlated with their aflatoxin production capabilities. In order to better understand these isolate-specific oxidative stress responses, we examined the transcriptional responses of field isolates of A. flavus with varying levels of aflatoxin production (NRRL3357, AF13, and Tox4) to H2O2-induced oxidative stress using an RNA sequencing approach. These isolates were cultured in an aflatoxin-production conducive medium amended with various levels of H2O2. Whole transcriptomes were sequenced using an Illumina HiSeq platform with an average of 40.43 million filtered paired-end reads generated for each sample. The obtained transcriptomes were then used for differential expression, gene ontology, pathway, and co-expression analyses. Isolates which produced higher levels of aflatoxin tended to exhibit fewer differentially expressed genes than isolates with lower levels of production. Genes found to be differentially expressed in response to increasing oxidative stress included antioxidant enzymes, primary metabolism components, antibiosis-related genes, and secondary metabolite biosynthetic components specifically for aflatoxin, aflatrem, and kojic acid. The expression of fungal development-related genes including aminobenzoate degradation genes and conidiation

Contamination of crops with aflatoxin is a serious global threat to food safety. Aflatoxin production by Aspergillus flavus is exacerbated by drought stress in the field and by oxidative stress in vitro. We examined transcriptomes of three toxigenic and three atoxigenic isolates of A. flavus in aflatoxin conducive and non-conducive media with varying levels of H2O2 to investigate the relationship of secondary metabolite production, carbon source, and oxidative stress. We found that toxigenic and atoxigenic isolates employ distinct mechanisms to remediate oxidative damage, and that carbon source affected the isolates’ expression profiles. Iron metabolism, monooxygenases, and secondary metabolism appeared to participate in isolate oxidative responses. The results suggest that aflatoxin and aflatrem biosynthesis may remediate oxidative stress by consuming excess oxygen and that kojic acid production may limit iron-mediated, non-enzymatic generation of reactive oxygen species. Together, secondary metabolite production may enhance A. flavus stress tolerance, and may be reduced by enhancing host plant tissue antioxidant capacity though genetic improvement by breeding selection.

The colonization of maize (Zea mays L.) and peanut (Arachis hypogaea L.) by the fungal pathogen Aspergillus flavus results in the contamination of kernels with carcinogenic mycotoxins known as aflatoxins leading to economic losses and potential health threats to humans. The regulation of aflatoxin biosynthesis in various Aspergillus spp. has been extensively studied, and has been shown to be related to oxidative stress responses. Given that environmental stresses such as drought and heat stress result in the accumulation of reactive oxygen species (ROS) within host plant tissues, host-derived ROS may play an important role in cross-kingdom communication between host plants and A. flavus. Recent technological advances in plant breeding have provided the tools necessary to study and apply knowledge derived from metabolomic, proteomic, and transcriptomic studies in the context of productive breeding populations. Here, we review the current understanding of the potential roles of environmental stress, ROS, and aflatoxin in the interaction between A. flavus and its host plants, and the current status in molecular breeding and marker discovery for resistance to A. flavus colonization and aflatoxin contamination in maize and peanut. We will also propose future directions and a working model for continuing research efforts linking environmental stress tolerance and aflatoxin contamination resistance in maize and peanut.

Chickpea is an important food legume crop for the semi-arid regions, however, its productivity is adversely affected by various biotic and abiotic stresses. Identification of candidate genes associated with abiotic stress response will help breeding efforts aiming to enhance its productivity. With this objective, 10 abiotic stress responsive candidate genes were selected on the basis of prior knowledge of this complex trait. These 10 genes were subjected to allele specific sequencing across a chickpea reference set comprising 300 genotypes including 211 genotypes of chickpea mini core collection. A total of 1.3 Mbp sequence data were generated. Multiple sequence alignment (MSA) revealed 79 SNPs and 41 indels in nine genes while the CAP2 gene was found to be conserved across all the genotypes. Among 10 candidate genes, the maximum number of SNPs (34) was observed in abscisic acid stress and ripening (ASR) gene including 22 transitions, 11 transversions and one tri-allelic SNP. Nucleotide diversity varied from 0.0004 to 0.0029 while polymorphism information content (PIC) values ranged from 0.01 (AKIN gene) to 0.43 (CAP2 promoter). Haplotype analysis revealed that alleles were represented by more than two haplotype blocks, except alleles of the CAP2 and sucrose synthase (SuSy) gene, where only one haplotype was identified. These genes can be used for association analysis and if validated, may be useful for enhancing abiotic stress, including drought tolerance, through molecular breeding.

To understand the genetic basis of tolerance to drought and heat stresses in chickpea, a comprehensive association mapping approach has been undertaken. Phenotypic data were generated on the reference set (300 accessions, including 211 mini-core collection accessions) for drought tolerance related root traits, heat tolerance, yield and yield component traits from 1–7 seasons and 1–3 locations in India (Patancheru, Kanpur, Bangalore) and three locations in Africa (Nairobi, Egerton in Kenya and Debre Zeit in Ethiopia). Diversity Array Technology (DArT) markers equally distributed across chickpea genome were used to determine population structure and three sub-populations were identified using admixture model in STRUCTURE. The pairwise linkage disequilibrium (LD) estimated using the squared-allele frequency correlations (r2; when r2<0.20) was found to decay rapidly with the genetic distance of 5 cM. For establishing marker-trait associations (MTAs), both genome-wide and candidate gene-sequencing based association mapping approaches were conducted using 1,872 markers (1,072 DArTs, 651 single nucleotide polymorphisms [SNPs], 113 gene-based SNPs and 36 simple sequence repeats [SSRs]) and phenotyping data mentioned above employing mixed linear model (MLM) analysis with optimum compression with P3D method and kinship matrix. As a result, 312 significant MTAs were identified and a maximum number of MTAs (70) was identified for 100-seed weight. A total of 18 SNPs from 5 genes (ERECTA, 11 SNPs; ASR, 4 SNPs; DREB, 1 SNP; CAP2 promoter, 1 SNP and AMDH, 1SNP) were significantly associated with different traits. This study provides significant MTAs for drought and heat tolerance in chickpea that can be used, after validation, in molecular breeding for developing superior varieties with enhanced drought and heat tolerance.

Chickpea (Cicer arietinum L.) is the second most important grain legume cultivated by resource poor farmers in the arid and semi-arid regions of the world. Drought is one of the major constraints leading up to 50 % production losses in chickpea. In order to dissect the complex nature of drought tolerance and to use genomics tools for enhancing yield of chickpea under drought conditions, two mapping populations—ICCRIL03 (ICC 4958 × ICC 1882) and ICCRIL04 (ICC 283 × ICC 8261) segregating for drought tolerance-related root traits were phenotyped for a total of 20 drought component traits in 1–7 seasons at 1–5 locations in India. Individual genetic maps comprising 241 loci and 168 loci for ICCRIL03 and ICCRIL04, respectively, and a consensus genetic map comprising 352 loci were constructed (http://cmap.icrisat.ac.in/cmap/sm/cp/varshney/). Analysis of extensive genotypic and precise phenotypic data revealed 45 robust main-effect QTLs (M-QTLs) explaining up to 58.20 % phenotypic variation and 973 epistatic QTLs (E-QTLs) explaining up to 92.19 % phenotypic variation for several target traits. Nine QTL clusters containing QTLs for several drought tolerance traits have been identified that can be targeted for molecular breeding. Among these clusters, one cluster harboring 48 % robust M-QTLs for 12 traits and explaining about 58.20 % phenotypic variation present on CaLG04 has been referred as “QTL-hotspot”. This genomic region contains seven SSR markers (ICCM0249, NCPGR127, TAA170, NCPGR21, TR11, GA24 and STMS11). Introgression of this region into elite cultivars is expected to enhance drought tolerance in chickpea.

Chickpea (Cicer arietinum L.) is the third most important cool season food legume, cultivated in arid and semi-arid regions of the world. The goal of this study was to develop novel molecular markers such as microsatellite or simple sequence repeat (SSR) markers from bacterial artificial chromosome (BAC)-end sequences (BESs) and diversity arrays technology (DArT) markers, and to construct a high-density genetic map based on recombinant inbred line (RIL) population ICC 4958 (C. arietinum)×PI 489777 (C. reticulatum). A BAC-library comprising 55,680 clones was constructed and 46,270 BESs were generated. Mining of these BESs provided 6,845 SSRs, and primer pairs were designed for 1,344 SSRs. In parallel, DArT arrays with ca. 15,000 clones were developed, and 5,397 clones were found polymorphic among 94 genotypes tested. Screening of newly developed BES-SSR markers and DArT arrays on the parental genotypes of the RIL mapping population showed polymorphism with 253 BES-SSR markers and 675 DArT markers. Segregation data obtained for these polymorphic markers and 494 markers data compiled from published reports or collaborators were used for constructing the genetic map. As a result, a comprehensive genetic map comprising 1,291 markers on eight linkage groups (LGs) spanning a total of 845.56 cM distance was developed (http://cmap.icrisat.ac.in/cmap/sm/cp/thudi/). The number of markers per linkage group ranged from 68 (LG 8) to 218 (LG 3) with an average inter-marker distance of 0.65 cM. While the developed resource of molecular markers will be useful for genetic diversity, genetic mapping and molecular breeding applications, the comprehensive genetic map with integrated BES-SSR markers will facilitate its anchoring to the physical map (under construction) to accelerate map-based cloning of genes in chickpea and comparative genome evolution studies in legumes.

This study presents the development and mapping of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers in chickpea. The mapping population is based on an inter-specific cross between domesticated and non-domesticated genotypes of chickpea (Cicer arietinum ICC 4958 × C. reticulatum PI 489777). This same population has been the focus of previous studies, permitting integration of new and legacy genetic markers into a single genetic map. We report a set of 311 novel SSR markers (designated ICCM—ICRISAT chickpea microsatellite), obtained from an SSR-enriched genomic library of ICC 4958. Screening of these SSR markers on a diverse panel of 48 chickpea accessions provided 147 polymorphic markers with 2–21 alleles and polymorphic information content value 0.04–0.92. Fifty-two of these markers were polymorphic between parental genotypes of the inter-specific population. We also analyzed 233 previously published (H-series) SSR markers that provided another set of 52 polymorphic markers. An additional 71 gene-based SNP markers were developed from transcript sequences that are highly conserved between chickpea and its near relative Medicago truncatula. By using these three approaches, 175 new marker loci along with 407 previously reported marker loci were integrated to yield an improved genetic map of chickpea. The integrated map contains 521 loci organized into eight linkage groups that span 2,602 cM, with an average inter-marker distance of 4.99 cM. Gene-based markers provide anchor points for comparing the genomes of Medicago and chickpea, and reveal extended synteny between these two species. The combined set of genetic markers and their integration into an improved genetic map should facilitate chickpea genetics and breeding, as well as translational studies between chickpea and Medicago.

Using next-generation sequencing technologies it is possible to resequence entire plant genomes or sample entire transcriptomes more efficiently and economically and in greater depth than ever before. Rather than sequencing individual genomes, we envision the sequencing of hundreds or even thousands of related genomes to sample genetic diversity within and between germplasm pools. Identification and tracking of genetic variation are now so efficient and precise that thousands of variants can be tracked within large populations. In this review, we outline some important areas such as the large-scale development of molecular markers for linkage mapping, association mapping, wide crosses and alien introgression, epigenetic modifications, transcript profiling, population genetics and de novo genome/organellar genome assembly for which these technologies are expected to advance crop genetics and breeding, leading to crop improvement.

The progress made in DNA marker technology has been remarkable and exciting in recent years. DNA markers have proved valuable tools in various analyses in plant breeding, for example, early generation selection, enrichment of complex F(1)s, choice of donor parent in backcrossing, recovery of recurrent parent genotype in backcrossing, linkage block analysis and selection. Other main areas of applications of molecular markers in plant breeding include germplasm characterization/fingerprinting, determining seed purity, systematic sampling of germplasm, and phylogenetic analysis. Molecular markers, thus, have proved powerful tools in replacing the bioassays and there are now many examples available to show the efficacy of such markers. We have illustrated some basic concepts and methodology of applying molecular markers for enhancing the selection efficiency in plant breeding. Some successful examples of product developments of molecular breeding have also been presented.

The transcription factor, DREB2A, is one of the promising candidate genes involved in dehydration tolerance in crop plants. In order to isolate DREB2A homologues across cereals (rice, barley and sorghum) and legumes (common bean and chickpea), specific or degenerate primers were used. Gene/phylogenetic trees were constructed using a non-redundant set of 19 DREB1A and 27 DREB2A amino acid sequences and were combined with taxonomic/species tree to prepare reconciled phylogenetic trees. In total, 86 degenerate primers were designed for different clades and 295 degenerate primer combinations were used to amplify DREB homologues in targeted crop species. Successful amplification of DREB2A was obtained in case of sorghum. In parallel, gene-specific primers were used to amplify DREB2A homologues in rice, barley, common bean and chickpea. Seven to eight diverse genotypes from targeted species were used for sequence analysis at DREB2A locus identified/isolated. A maximum of eight SNPs were found in the common bean DREB2A, indicating two distinct haplotypes, three SNPs with five haplotypes were observed in barley whereas a single SNP was observed in rice, sorghum and chickpea. Parsimony based phylogenetic tree revealed distinct clustering of cereals and legumes. Furthermore, alignment of corresponding amino acid sequences showed conservation of AP2 domain across the targeted species.

To increase the number of polymorphic simple sequence repeat markers (SSRs) in chickpea, a genomic library was constructed, and the SSRs derived from this approach are characterized. A genomic DNA library from the chickpea genotype ICC 4958 was constructed after digesting total DNA of ICC 4958 with MBO/Sau and TaqI at University of Frankfurt, Germany. The study increases the existing SSR repertoire in chickpea, which will help to enhance the coverage of linkage maps especially in intraspecific crosses where marker polymorphism is found to be very less.

A total of 1499 ESTs generated from 26 different Cicer species, available in the public domain at the time of analysis, were used for in silico identification of SNPs using the bioinformatic tools developed at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) (http://hpc.icrisat.org/PBSWeb). Cluster analysis provided a total of 118 clusters, of which 11 clusters contained sequences from more than one Cicer species. Further, these clusters were assembled into 19 contigs and 184 putative SNPs were identified in 15 contigs. However, only 73 SNPs involved restriction enzyme sites for development of the CAPS assays as identified through the SNP2CAPs program. Primer pairs were designed for only 8 contigs (CL3a, CL3c, CL3d, CL3e, CL4a, CL10, CL20 and CL99) which had SNPs, resulting in putative recognition sites to commonly used restriction enzymes. Results of the demonstrates the utility of Cicer EST resources and the availability of bioinformatics analysis pipelines for the large-scale identification of SNPs on the HPC (High Performance Computer) at ICRISAT and the development of costeffective CAPS assay for SNP genotyping. It is anticipated that the availability of large number of ESTs from more than one genotype of cultivated chickpea (C. arietinum) in the near future will make it possible to develop larger number of SNPs in cultivated chickpea germplasm for genome analysis and breeding applications