Exciting journey of 10 years from genomes to fields and markets: Some success stories of genomics-assisted breeding in chickpea, pigeonpea and groundnut

Celebrating Professor Rajeev K. Varshney's transformative research odyssey from genomics to the field on his induction as Fellow of the Royal Society

Professor Rajeev K. Varshney's transformative impact on crop genomics, genetics, and agriculture is the result of his passion, dedication, and unyielding commitment to harnessing the potential of genomics to address the most pressing challenges faced by the global agricultural community. Starting from a small town in India and reaching the global stage, Professor Varshney's academic and professional trajectory has inspired many scientists active in research today. His ground-breaking work, especially his effort to list orphan tropical crops to genomic resource-rich entities, has been transformative. Beyond his scientific achievements, Professor Varshney is recognized by his colleagues as an exemplary mentor, fostering the growth of future researchers, building institutional capacity, and strengthening scientific capability. His focus on translational genomics and strengthening seed system in developing countries for the improvement of agriculture has made a tangible impact on farmers' lives. His skills have been best utilized in roles at leading research centres where he has applied his expertise to deliver a new vision for crop improvement. These efforts have now been recognized by the Royal Society with the award of the Fellowship (FRS). As we mark this significant milestone in his career, we not only celebrate Professor Varshney's accomplishments but also his wider contributions that continue to transform the agricultural landscape.

Integrative and inclusive genomics to promote the use of underutilised crops

Underutilised crops or orphan crops are important for diversifying our food systems towards food and nutrition security. Here, the authors discuss how the development of underutilised crop genomic resource should align with their breeding and capacity building strategies, and leverage advances made in major crops.

Natural alleles of Mediator subunit genes modulate plant height in chickpea

Plant height (PH) is an important plant architectural trait targeted during Green Revolution to enhance crop yields. Identification of genes and natural alleles governing plant height without compromising agronomic performance can fill the lacuna of knowledge connecting ideal plant architecture with maximum achievable yield in chickpea. Through coherent strategy involving genome‐wide association study, QTL/fine mapping, map‐based cloning, molecular haplotyping, and downstream functional genomics, the current study identified two Mediator subunit genes namely, CaMED23 and CaMED5b and their derived natural alleles/haplotypes underlying the major QTLs and trans‐acting eQTLs regulating plant height in chickpea. Differential accumulation of haplotype‐specific transcripts of these two Mediator genes in corresponding haplotype‐introgressed near‐isogenic lines (NILs) correlates negatively with the plant height trait. Quantitative as well as qualitative estimation based on histology, scanning electron microscopy, and histochemical assay unraveled the reduced lengths and cell sizes of internodes along with compromised lignin levels in dwarf/semi‐dwarf chickpea NILs introgressed with superior CaMED23 and CaMED5b gene haplotypes. This observation, supported by global transcriptome profiling‐based diminished expression of various phenylpropanoid pathway genes upstream of lignin biosynthesis in dwarf/semi‐dwarf NILs, essentially links plant height with lignin accumulation. The identified molecular signatures in the Mediator subunit genes can be efficiently utilized to develop desirable dwarf/semi‐dwarf‐type chickpea cultivars without affecting their yield per plant via modulating lignin/phenylpropanoid biosynthesis.

Genome-wide association study as a powerful tool for dissecting competitive traits in legumes

Legumes are extremely valuable because of their high protein content and several other nutritional components. The major challenge lies in maintaining the quantity and quality of protein and other nutritional compounds in view of climate change conditions. The global need for plant-based proteins has increased the demand for seeds with a high protein content that includes essential amino acids. Genome-wide association studies (GWAS) have evolved as a standard approach in agricultural genetics for examining such intricate characters. Recent development in machine learning methods shows promising applications for dimensionality reduction, which is a major challenge in GWAS. With the advancement in biotechnology, sequencing, and bioinformatics tools, estimation of linkage disequilibrium (LD) based associations between a genome-wide collection of single-nucleotide polymorphisms (SNPs) and desired phenotypic traits has become accessible. The markers from GWAS could be utilized for genomic selection (GS) to predict superior lines by calculating genomic estimated breeding values (GEBVs). For prediction accuracy, an assortment of statistical models could be utilized, such as ridge regression best linear unbiased prediction (rrBLUP), genomic best linear unbiased predictor (gBLUP), Bayesian, and random forest (RF). Both naturally diverse germplasm panels and family-based breeding populations can be used for association mapping based on the nature of the breeding system (inbred or outbred) in the plant species. MAGIC, MCILs, RIAILs, NAM, and ROAM are being used for association mapping in several crops. Several modifications of NAM, such as doubled haploid NAM (DH-NAM), backcross NAM (BC-NAM), and advanced backcross NAM (AB-NAM), have also been used in crops like rice, wheat, maize, barley mustard, etc. for reliable marker-trait associations (MTAs), phenotyping accuracy is equally important as genotyping. Highthroughput genotyping, phenomics, and computational techniques have advanced during the past few years, making it possible to explore such enormous datasets. Each population has unique virtues and flaws at the genomics and phenomics levels, which will be covered in more detail in this review study. The current investigation includes utilizing elite breeding lines as association mapping population, optimizing the choice of GWAS selection, population size, and hurdles in phenotyping, and statistical methods which will analyze competitive traits in legume breeding.

Breeding and Genomic Approaches towards Development of Fusarium Wilt Resistance in Chickpea

Chickpea is an important leguminous crop with potential to provide dietary proteins to both humans and animals. It also ameliorates soil nitrogen through biological nitrogen fixation. The crop is affected by an array of biotic and abiotic factors. Among different biotic stresses, a major fungal disease called Fusarium wilt, caused by Fusarium oxysporum f. sp. ciceris (FOC), is responsible for low productivity in chickpea. To date, eight pathogenic races of FOC (race 0, 1A, and 1B/C, 2-6) have been reported worldwide. The development of resistant cultivars using different conventional breeding methods is very time consuming and depends upon the environment. Modern technologies can improve conventional methods to solve these major constraints. Understanding the molecular response of chickpea to Fusarium wilt can help to provide effective management strategies. The identification of molecular markers closely linked to genes/QTLs has provided great potential for chickpea improvement programs. Moreover, omics approaches, including transcriptomics, metabolomics, and proteomics give scientists a vast viewpoint of functional genomics. In this review, we will discuss the integration of all available strategies and provide comprehensive knowledge about chickpea plant defense against Fusarium wilt.

Prospects of microgreens as budding living functional food: Breeding and biofortification through OMICS and other approaches for nutritional security

Nutrient deficiency has resulted in impaired growth and development of the population globally. Microgreens are considered immature greens (required light for photosynthesis and growing medium) and developed from the seeds of vegetables, legumes, herbs, and cereals. These are considered "living superfood/functional food" due to the presence of chlorophyll, beta carotene, lutein, and minerals like magnesium (Mg), Potassium (K), Phosphorus (P), and Calcium (Ca). Microgreens are rich at the nutritional level and contain several phytoactive compounds (carotenoids, phenols, glucosinolates, polysterols) that are helpful for human health on Earth and in space due to their anti-microbial, anti-inflammatory, antioxidant, and anti-carcinogenic properties. Microgreens can be used as plant-based nutritive vegetarian foods that will be fruitful as a nourishing constituent in the food industryfor garnish purposes, complement flavor, texture, and color to salads, soups, flat-breads, pizzas, and sandwiches (substitute to lettuce in tacos, sandwich, burger). Good handling practices may enhance microgreens'stability, storage, and shelf-life under appropriate conditions, including light, temperature, nutrients, humidity, and substrate. Moreover, the substrate may be a nutritive liquid solution (hydroponic system) or solid medium (coco peat, coconut fiber, coir dust and husks, sand, vermicompost, sugarcane filter cake, etc.) based on a variety of microgreens. However integrated multiomics approaches alongwith nutriomics and foodomics may be explored and utilized to identify and breed most potential microgreen genotypes, biofortify including increasing the nutritional content (macro-elements:K, Ca and Mg; oligo-elements: Fe and Zn and antioxidant activity) and microgreens related other traits viz., fast growth, good nutritional values, high germination percentage, and appropriate shelf-life through the implementation of integrated approaches includes genomics, transcriptomics, sequencing-based approaches, molecular breeding, machine learning, nanoparticles, and seed priming strategiesetc.

Mining legume germplasm for genetic gains: An Indian perspective

Legumes play a significant role in food and nutritional security and contribute to environmental sustainability. Although legumes are highly beneficial crops, it has not yet been possible to enhance their yield and production to a satisfactory level. Amid a rising population and low yield levels, per capita average legume consumption in India has fallen by 71% over the last 50 years, and this has led to protein-related malnutrition in a large segment of the Indian population, especially women and children. Several factors have hindered attempts to achieve yield enhancement in grain legumes, including biotic and abiotic pressures, a lack of good ideotypes, less amenability to mechanization, poorer responsiveness to fertilizer input, and a poor genetic base. Therefore, there is a need to mine the approximately 0.4 million ex situ collections of legumes that are being conserved in gene banks globally for identification of ideal donors for various traits. The Indian National Gene Bank conserves over 63,000 accessions of legumes belonging to 61 species. Recent initiatives have been undertaken in consortia mode with the aim of unlocking the genetic potential of ex situ collections and conducting large-scale germplasm characterization and evaluation analyses. We assume that large-scale phenotyping integrated with omics-based science will aid the identification of target traits and their use to enhance genetic gains. Additionally, in cases where the genetic base of major legumes is narrow, wild relatives have been evaluated, and these are being exploited through pre-breeding. Thus far, >200 accessions of various legumes have been registered as unique donors for various traits of interest.

Genome-Wide Identification and Characterization of Auxin Response Factor (ARF) Gene Family Involved in Wood Formation and Response to Exogenous Hormone Treatment in Populus trichocarpa

Auxin is a key regulator that virtually controls almost every aspect of plant growth and development throughout its life cycle. As the major components of auxin signaling, auxin response factors (ARFs) play crucial roles in various processes of plant growth and development. In this study, a total of 35 PtrARF genes were identified, and their phylogenetic relationships, chromosomal locations, synteny relationships, exon/intron structures, cis-elements, conserved motifs, and protein characteristics were systemically investigated. We also analyzed the expression patterns of these PtrARF genes and revealed that 16 of them, including PtrARF1, 3, 7, 11, 13-17, 21, 23, 26, 27, 29, 31, and 33, were preferentially expressed in primary stems, while 15 of them, including PtrARF2, 4, 6, 9, 10, 12, 18-20, 22, 24, 25, 28, 32, and 35, participated in different phases of wood formation. In addition, some PtrARF genes, with at least one cis-element related to indole-3-acetic acid (IAA) or abscisic acid (ABA) response, responded differently to exogenous IAA and ABA treatment, respectively. Three PtrARF proteins, namely PtrARF18, PtrARF23, and PtrARF29, selected from three classes, were characterized, and only PtrARF18 was a transcriptional self-activator localized in the nucleus. Moreover, Y2H and bimolecular fluorescence complementation (BiFC) assay demonstrated that PtrARF23 interacted with PtrIAA10 and PtrIAA28 in the nucleus, while PtrARF29 interacted with PtrIAA28 in the nucleus. Our results provided comprehensive information regarding the PtrARF gene family, which will lay some foundation for future research about PtrARF genes in tree development and growth, especially the wood formation, in response to cellular signaling and environmental cues.

Sustaining yield and nutritional quality of peanuts in harsh environments: Physiological and molecular basis of drought and heat stress tolerance

Climate change is significantly impacting agricultural production worldwide. Peanuts provide food and nutritional security to millions of people across the globe because of its high nutritive values. Drought and heat stress alone or in combination cause substantial yield losses to peanut production. The stress, in addition, adversely impact nutritional quality. Peanuts exposed to drought stress at reproductive stage are prone to aflatoxin contamination, which imposes a restriction on use of peanuts as health food and also adversely impact peanut trade. A comprehensive understanding of the impact of drought and heat stress at physiological and molecular levels may accelerate the development of stress tolerant productive peanut cultivars adapted to a given production system. Significant progress has been achieved towards the characterization of germplasm for drought and heat stress tolerance, unlocking the physiological and molecular basis of stress tolerance, identifying significant marker-trait associations as well major QTLs and candidate genes associated with drought tolerance, which after validation may be deployed to initiate marker-assisted breeding for abiotic stress adaptation in peanut. The proof of concept about the use of transgenic technology to add value to peanuts has been demonstrated. Advances in phenomics and artificial intelligence to accelerate the timely and cost-effective collection of phenotyping data in large germplasm/breeding populations have also been discussed. Greater focus is needed to accelerate research on heat stress tolerance in peanut. A suits of technological innovations are now available in the breeders toolbox to enhance productivity and nutritional quality of peanuts in harsh environments. A holistic breeding approach that considers drought and heat-tolerant traits to simultaneously address both stresses could be a successful strategy to produce climate-resilient peanut genotypes with improved nutritional quality.

Molecular Breeding and Drought Tolerance in Chickpea

Cicer arietinum L. is the third greatest widely planted imperative pulse crop worldwide, and it belongs to the Leguminosae family. Drought is the utmost common abiotic factor on plants, distressing their water status and limiting their growth and development. Chickpea genotypes have the natural ability to fight drought stress using certain strategies viz., escape, avoidance and tolerance. Assorted breeding methods, including hybridization, mutation, and marker-aided breeding, genome sequencing along with omics approaches, could be used to improve the chickpea germplasm lines(s) against drought stress. Root features, for instance depth and root biomass, have been recognized as the greatest beneficial morphological factors for managing terminal drought tolerance in the chickpea. Marker-aided selection, for example, is a genomics-assisted breeding (GAB) strategy that can considerably increase crop breeding accuracy and competence. These breeding technologies, notably marker-assisted breeding, omics, and plant physiology knowledge, underlined the importance of chickpea breeding and can be used in future crop improvement programmes to generate drought-tolerant cultivars(s).

Genetic diversity and grouping of pigeonpea [Cajanus cajan Millspaugh] Germplasm using SNP markers and agronomic traits

Knowledge of genetic interrelationships and grouping among pigeonpea germplasm collections is fundamental to selecting breeding parents with unique genetic constitutions. The objectives of this study were to assess the genetic diversity and genetic grouping present among 81 pigeonpea genotypes collected from Malawi, Tanzania and Kenya using 4122 single nucleotide polymorphism (SNP) markers and complementary morphological traits. The SNP markers and phenotypic traits revealed significant genetic variation among the assessed genotypes. The test genotypes were resolved into three distinct clusters based on both marker systems. The mean gene diversity and the polymorphic information content (PIC) were 0.14 and 0.11, suggesting moderate genetic differentiation among the genotypes. The analysis of molecular variance revealed that differences among populations accounted for only 2.7% of the variation, while within the population (among individuals) accounted for 97.3% of the variation. The results based on the DArT SNP genotyping complemented the phenotypic data and led to the selection of unique pigeonpea genotypes for effective breeding programs in Malawi and related agroecologies. This suggested that unique breeding populations could be created by identifying and selecting divergent individuals as parental lines. There is a need to create a new genetic variation or introgress genes from genetically unrelated parents to increase the genetic base of the current pigeonpea breeding populations.

A divide-and-conquer approach for genomic prediction in rubber tree using machine learning

Rubber tree (Hevea brasiliensis) is the main feedstock for commercial rubber; however, its long vegetative cycle has hindered the development of more productive varieties via breeding programs. With the availability of H. brasiliensis genomic data, several linkage maps with associated quantitative trait loci have been constructed and suggested as a tool for marker-assisted selection. Nonetheless, novel genomic strategies are still needed, and genomic selection (GS) may facilitate rubber tree breeding programs aimed at reducing the required cycles for performance assessment. Even though such a methodology has already been shown to be a promising tool for rubber tree breeding, increased model predictive capabilities and practical application are still needed. Here, we developed a novel machine learning-based approach for predicting rubber tree stem circumference based on molecular markers. Through a divide-and-conquer strategy, we propose a neural network prediction system with two stages: (1) subpopulation prediction and (2) phenotype estimation. This approach yielded higher accuracies than traditional statistical models in a single-environment scenario. By delivering large accuracy improvements, our methodology represents a powerful tool for use in Hevea GS strategies. Therefore, the incorporation of machine learning techniques into rubber tree GS represents an opportunity to build more robust models and optimize Hevea breeding programs.

Pea Breeding for Resistance to Rhizospheric Pathogens

Pea (Pisum sativum L.) is a grain legume widely cultivated in temperate climates. It is important in the race for food security owing to its multipurpose low-input requirement and environmental promoting traits. Pea is key in nitrogen fixation, biodiversity preservation, and nutritional functions as food and feed. Unfortunately, like most crops, pea production is constrained by several pests and diseases, of which rhizosphere disease dwellers are the most critical due to their long-term persistence in the soil and difficulty to manage. Understanding the rhizosphere environment can improve host plant root microbial association to increase yield stability and facilitate improved crop performance through breeding. Thus, the use of various germplasm and genomic resources combined with scientific collaborative efforts has contributed to improving pea resistance/cultivation against rhizospheric diseases. This improvement has been achieved through robust phenotyping, genotyping, agronomic practices, and resistance breeding. Nonetheless, resistance to rhizospheric diseases is still limited, while biological and chemical-based control strategies are unrealistic and unfavourable to the environment, respectively. Hence, there is a need to consistently scout for host plant resistance to resolve these bottlenecks. Herein, in view of these challenges, we reflect on pea breeding for resistance to diseases caused by rhizospheric pathogens, including fusarium wilt, root rots, nematode complex, and parasitic broomrape. Here, we will attempt to appraise and harmonise historical and contemporary knowledge that contributes to pea resistance breeding for soilborne disease management and discuss the way forward.

Genetic mapping of QTLs for drought tolerance in chickpea (Cicer arietinum L.)

Chickpea yield is severely affected by drought stress, which is a complex quantitative trait regulated by multiple small-effect genes. Identifying genomic regions associated with drought tolerance component traits may increase our understanding of drought tolerance mechanisms and assist in the development of drought-tolerant varieties. Here, a total of 187 F8 recombinant inbred lines (RILs) developed from an interspecific cross between drought-tolerant genotype GPF 2 (Cicer arietinum) and drought-sensitive accession ILWC 292 (C. reticulatum) were evaluated to identify quantitative trait loci (QTLs) associated with drought tolerance component traits. A total of 21 traits, including 12 morpho-physiological traits and nine root-related traits, were studied under rainfed and irrigated conditions. Composite interval mapping identified 31 QTLs at Ludhiana and 23 QTLs at Faridkot locations for morphological and physiological traits, and seven QTLs were identified for root-related traits. QTL analysis identified eight consensus QTLs for six traits and five QTL clusters containing QTLs for multiple traits on linkage groups CaLG04 and CaLG06. The identified major QTLs and genomic regions associated with drought tolerance component traits can be introgressed into elite cultivars using genomics-assisted breeding to enhance drought tolerance in chickpea.

Exploring Chickpea Germplasm Diversity for Broadening the Genetic Base Utilizing Genomic Resourses

Legume crops provide significant nutrition to humans as a source of protein, omega-3 fatty acids as well as specific macro and micronutrients. Additionally, legumes improve the cropping environment by replenishing the soil nitrogen content. Chickpeas are the second most significant staple legume food crop worldwide behind dry bean which contains 17%–24% protein, 41%–51% carbohydrate, and other important essential minerals, vitamins, dietary fiber, folate, β-carotene, anti-oxidants, micronutrients (phosphorus, calcium, magnesium, iron, and zinc) as well as linoleic and oleic unsaturated fatty acids. Despite these advantages, legumes are far behind cereals in terms of genetic improvement mainly due to far less effort, the bottlenecks of the narrow genetic base, and several biotic and abiotic factors in the scenario of changing climatic conditions. Measures are now called for beyond conventional breeding practices to strategically broadening of narrow genetic base utilizing chickpea wild relatives and improvement of cultivars through advanced breeding approaches with a focus on high yield productivity, biotic and abiotic stresses including climate resilience, and enhanced nutritional values. Desirable donors having such multiple traits have been identified using core and mini core collections from the cultivated gene pool and wild relatives of Chickpea. Several methods have been developed to address cross-species fertilization obstacles and to aid in inter-specific hybridization and introgression of the target gene sequences from wild Cicer species. Additionally, recent advances in “Omics” sciences along with high-throughput and precise phenotyping tools have made it easier to identify genes that regulate traits of interest. Next-generation sequencing technologies, whole-genome sequencing, transcriptomics, and differential genes expression profiling along with a plethora of novel techniques like single nucleotide polymorphism exploiting high-density genotyping by sequencing assays, simple sequence repeat markers, diversity array technology platform, and whole-genome re-sequencing technique led to the identification and development of QTLs and high-density trait mapping of the global chickpea germplasm. These altogether have helped in broadening the narrow genetic base of chickpeas.

Hydrogen Sulfide and Silicon Together Alleviate Chromium (VI) Toxicity by Modulating Morpho-Physiological and Key Antioxidant Defense Systems in Chickpea (Cicer arietinum L.) Varieties

Extensive use of chromium (Cr) in anthropogenic activities leads to Cr toxicity in plants causing serious threat to the environment. Cr toxicity impairs plant growth, development, and metabolism. In the present study, we explored the effect of NaHS [a hydrogen sulfide; (H₂S), donor] and silicon (Si), alone or in combination, on two chickpea (Cicer arietinum) varieties (Pusa 2085 and Pusa Green 112), in pot conditions under Cr stress. Cr stress increased accumulation of Cr reduction of the plasma membrane (PM) H⁺-ATPase activity and decreased in photosynthetic pigments, essential minerals, relative water contents (RWC), and enzymatic and non-enzymatic antioxidants in both the varieties. Exogenous application of NaHS and Si on plants exposed to Cr stress mitigated the effect of Cr and enhanced the physiological and biochemical parameters by reducing Cr accumulation and oxidative stress in roots and leaves. The interactive effects of NaHS and Si showed a highly significant and positive correlation with PM H⁺-ATPase activity, photosynthetic pigments, essential minerals, RWC, proline content, and enzymatic antioxidant activities (catalase, peroxidase, ascorbate peroxidase, dehydroascorbate reductase, superoxide dismutase, and monodehydroascorbate reductase). A similar trend was observed for non-enzymatic antioxidant activities (ascorbic acid, glutathione, oxidized glutathione, and dehydroascorbic acid level) in leaves while oxidative damage in roots and leaves showed a negative correlation. Exogenous application of NaHS + Si could enhance Cr stress tolerance in chickpea and field studies are warranted for assessing crop yield under Cr-affected area.

A joint learning approach for genomic prediction in polyploid grasses

Poaceae, among the most abundant plant families, includes many economically important polyploid species, such as forage grasses and sugarcane (Saccharum spp.). These species have elevated genomic complexities and limited genetic resources, hindering the application of marker-assisted selection strategies. Currently, the most promising approach for increasing genetic gains in plant breeding is genomic selection. However, due to the polyploidy nature of these polyploid species, more accurate models for incorporating genomic selection into breeding schemes are needed. This study aims to develop a machine learning method by using a joint learning approach to predict complex traits from genotypic data. Biparental populations of sugarcane and two species of forage grasses (Urochloa decumbens, Megathyrsus maximus) were genotyped, and several quantitative traits were measured. High-quality markers were used to predict several traits in different cross-validation scenarios. By combining classification and regression strategies, we developed a predictive system with promising results. Compared with traditional genomic prediction methods, the proposed strategy achieved accuracy improvements exceeding 50%. Our results suggest that the developed methodology could be implemented in breeding programs, helping reduce breeding cycles and increase genetic gains.

Genetic Augmentation of Legume Crops Using Genomic Resources and Genotyping Platforms for Nutritional Food Security

Recent advances in next generation sequencing (NGS) technologies have led the surge of genomic resources for the improvement legume crops. Advances in high throughput genotyping (HTG) and high throughput phenotyping (HTP) enable legume breeders to improve legume crops more precisely and efficiently. Now, the legume breeder can reshuffle the natural gene combinations of their choice to enhance the genetic potential of crops. These genomic resources are efficiently deployed through molecular breeding approaches for genetic augmentation of important legume crops, such as chickpea, cowpea, pigeonpea, groundnut, common bean, lentil, pea, as well as other underutilized legume crops. In the future, advances in NGS, HTG, and HTP technologies will help in the identification and assembly of superior haplotypes to tailor the legume crop varieties through haplotype-based breeding. This review article focuses on the recent development of genomic resource databases and their deployment in legume molecular breeding programmes to secure global food security.

Detection of a major QTL and development of KASP markers for seed weight by combining QTL-seq, QTL-mapping and RNA-seq in peanut

Combining QTL-seq, QTL-mapping and RNA-seq identified a major QTL and candidate genes, which contributed to the development of KASP markers and understanding of molecular mechanisms associated with seed weight in peanut. Seed weight, as an important component of seed yield, is a significant target of peanut breeding. However, relatively little is known about the quantitative trait loci (QTLs) and candidate genes associated with seed weight in peanut. In this study, three major QTLs on chromosomes A05, B02, and B06 were determined by applying the QTL-seq approach in a recombinant inbred line (RIL) population. Based on conventional QTL-mapping, these three QTL regions were successfully narrowed down through newly developed single nucleotide polymorphism (SNP) and simple sequence repeat markers. Among these three QTL regions, qSWB06.3 exhibited stable expression, contributing mainly to phenotypic variance across environments. Furthermore, differentially expressed genes (DEGs) were identified at the three seed developmental stages between the two parents of the RIL population. It was found that the DEGs were widely distributed in the ubiquitin-proteasome pathway, the serine/threonine-protein pathway, signal transduction of hormones and transcription factors. Notably, DEGs at the early stage were mostly involved in regulating cell division, whereas DEGs at the middle and late stages were primarily involved in cell expansion during seed development. The expression patterns of candidate genes related to seed weight in qSWB06.3 were investigated using quantitative real-time PCR. In addition, the allelic diversity of qSWB06.3 was investigated in peanut germplasm accessions. The marker Ah011475 has higher efficiency for discriminating accessions with different seed weights, and it would be useful as a diagnostic marker in marker-assisted breeding. This study provided insights into the genetic and molecular mechanisms of seed weight in peanut.

QTL mapping for Fusarium wilt resistance based on the whole-genome resequencing and their association with functional genes in Raphanus sativus

Two major QTL associated with resistance to Fusarium wilt (FW) were identified using whole-genome resequencing. Sequence variations and gene expression level differences suggest that TIR-NBS and LRR-RLK are candidate genes associated with FW-resistance. Fusarium wilt (FW) caused by Fusarium oxysporum f. sp. raphani is an important disease in radish, leading to severe decrease in yield and quality. YR4 as a novel genetic source to resistant to FW was confirmed through screening with five pathogen isolates. We have generated F₂ and F_2:3 populations segregated with FW resistance using YR4 and YR18 inbred lines. The disease symptom was evaluated in F_2:3 population (n = 180) in three independent studies over two years. We identified 4 QTL including the two major QTL (FoRsR7.1^59A and FoRsR9.3^59A). FoRsR7.1^59A and FoRsR9.3^59A were detected in three replicated experiments. FoRsR7.1^59A was delimited to the 2.18-Mb physical interval on chromosome R07, with a high LOD value (5.17-12.84) and explained phenotypic variation (9.34%-27.97%). The FoRsR9.3^59A represented relatively low LOD value (3.38-4.52) and explained phenotypic variation (6.24%-8.82%). On the basis of the re-sequencing data for the parental lines, we identified five putative resistance-related genes and 13 unknown genes with sequence variations at the gene and protein levels. A semi-quantitative RT-PCR analysis revealed that Rs382940 (TIR-NBS) and Rs382200 (RLK) were expressed only in 'YR4' from 0 to 6 days after the inoculation. Moreover, Rs382950 (TIR-NBS-LRR) was more highly expressed in 'YR4' from 3 to 6 days after the inoculation. These three genes might be important for FW-resistance in radish. We identified several markers based on these potential candidate genes. The marker set should be useful for breeding system to introduce the FW resistance loci from 'YR4' to improve tolerance to FW.

Identification of stable heat tolerance QTLs using inter-specific recombinant inbred line population derived from GPF 2 and ILWC 292

Heat stress during reproductive stages has been leading to significant yield losses in chickpea (Cicer arietinum L.). With an aim of identifying the genomic regions or QTLs responsible for heat tolerance, 187 F8 recombinant inbred lines (RILs) derived from the cross GPF 2 (heat tolerant) × ILWC 292 (heat sensitive) were evaluated under late-sown irrigated (January-May) and timely-sown irrigated environments (November-April) at Ludhiana and Faridkot in Punjab, India for 13 heat tolerance related traits. The pooled ANOVA for both locations for the traits namely days to germination (DG), days to flowering initiation (DFI), days to 50% flowering (DFF), days to 100% flowering (DHF), plant height (PH), pods per plant (NPP), biomass (BIO), grain yield (YLD), 100-seed weight (HSW), harvest index (HI), membrane permeability index (MPI), relative leaf water content (RLWC) and pollen viability (PV)) showed a highly significant difference in RILs. The phenotyping data coupled with the genetic map comprising of 1365 ddRAD-Seq based SNP markers were used for identifying the QTLs for heat tolerance. Composite interval mapping provided a total of 28 and 23 QTLs, respectively at Ludhiana and Faridkot locations. Of these, 13 consensus QTLs for DG, DFI, DFF, DHF, PH, YLD, and MPI have been identified at both locations. Four QTL clusters containing QTLs for multiple traits were identified on the same genomic region at both locations. Stable QTLs for days to flowering can be one of the major factors for providing heat tolerance as early flowering has an advantage of more seed setting due to a comparatively longer reproductive period. Identified QTLs can be used in genomics-assisted breeding to develop heat stress-tolerant high yielding chickpea cultivars.

Next-Generation Breeding Strategies for Climate-Ready Crops

Climate change is a threat to global food security due to the reduction of crop productivity around the globe. Food security is a matter of concern for stakeholders and policymakers as the global population is predicted to bypass 10 billion in the coming years. Crop improvement via modern breeding techniques along with efficient agronomic practices innovations in microbiome applications, and exploiting the natural variations in underutilized crops is an excellent way forward to fulfill future food requirements. In this review, we describe the next-generation breeding tools that can be used to increase crop production by developing climate-resilient superior genotypes to cope with the future challenges of global food security. Recent innovations in genomic-assisted breeding (GAB) strategies allow the construction of highly annotated crop pan-genomes to give a snapshot of the full landscape of genetic diversity (GD) and recapture the lost gene repertoire of a species. Pan-genomes provide new platforms to exploit these unique genes or genetic variation for optimizing breeding programs. The advent of next-generation clustered regularly interspaced short palindromic repeat/CRISPR-associated (CRISPR/Cas) systems, such as prime editing, base editing, and de nova domestication, has institutionalized the idea that genome editing is revamped for crop improvement. Also, the availability of versatile Cas orthologs, including Cas9, Cas12, Cas13, and Cas14, improved the editing efficiency. Now, the CRISPR/Cas systems have numerous applications in crop research and successfully edit the major crop to develop resistance against abiotic and biotic stress. By adopting high-throughput phenotyping approaches and big data analytics tools like artificial intelligence (AI) and machine learning (ML), agriculture is heading toward automation or digitalization. The integration of speed breeding with genomic and phenomic tools can allow rapid gene identifications and ultimately accelerate crop improvement programs. In addition, the integration of next-generation multidisciplinary breeding platforms can open exciting avenues to develop climate-ready crops toward global food security.

Construction of a high-density genetic map and QTL analysis for yield, yield components and agronomic traits in chickpea (Cicer arietinum L.)

Unravelling the genetic architecture underlying yield components and agronomic traits is important for enhancing crop productivity. Here, a recombinant inbred line (RIL) population, developed from ICC 4958 and DCP 92–3 cross, was used for constructing linkage map and QTL mapping analysis. The RIL population was genotyped using a high-throughput Axiom^®CicerSNP array, which enabled the development of a high-density genetic map consisting of 3,818 SNP markers and spanning a distance of 1064.14 cM. Analysis of phenotyping data for yield, yield components and agronomic traits measured across three years together with genetic mapping data led to the identification of 10 major-effect QTLs and six minor-effect QTLs explaining up to 59.70% phenotypic variance. The major-effect QTLs identified for 100-seed weight, and plant height possessed key genes, such as C3HC4 RING finger protein, pentatricopeptide repeat (PPR) protein, sugar transporter, leucine zipper protein and NADH dehydrogenase, amongst others. The gene ontology studies highlighted the role of these genes in regulating seed weight and plant height in crop plants. The identified genomic regions for yield, yield components, and agronomic traits, and the closely linked markers will help advance genetics research and breeding programs in chickpea.

Advancing crop genomics from lab to field

Crop genomics remains a key element in ensuring scientific progress to secure global food security. It has been two decades since the sequence of the first plant genome, that of Arabidopsis thaliana, was released, and soon after that the draft sequencing of the rice genome was completed. Since then, the genomes of more than 100 crops have been sequenced, plant genome research has expanded across multiple fronts and the next few years promise to bring further advances spurred by the advent of new technologies and approaches. We are likely to see continued innovations in crop genome sequencing, genetic mapping and the acquisition of multiple levels of biological data. There will be exciting opportunities to integrate genome-scale information across multiple scales of biological organization, leading to advances in our mechanistic understanding of crop biological processes, which will, in turn, provide greater impetus for translation of laboratory results to the field.

Comprehensive analysis and identification of drought-responsive candidate NAC genes in three semi-arid tropics (SAT) legume crops

Background

Chickpea, pigeonpea, and groundnut are the primary legume crops of semi-arid tropics (SAT) and their global productivity is severely affected by drought stress. The plant-specific NAC (NAM - no apical meristem, ATAF - Arabidopsis transcription activation factor, and CUC - cup-shaped cotyledon) transcription factor family is known to be involved in majority of abiotic stresses, especially in the drought stress tolerance mechanism. Despite the knowledge available regarding NAC function, not much information is available on NAC genes in SAT legume crops.

Results

In this study, genome-wide NAC proteins – 72, 96, and 166 have been identified from the genomes of chickpea, pigeonpea, and groundnut, respectively, and later grouped into 10 clusters in chickpea and pigeonpea, while 12 clusters in groundnut. Phylogeny with well-known stress-responsive NACs in Arabidopsis thaliana, Oryza sativa (rice), Medicago truncatula, and Glycine max (soybean) enabled prediction of putative stress-responsive NACs in chickpea (22), pigeonpea (31), and groundnut (33). Transcriptome data revealed putative stress-responsive NACs at various developmental stages that showed differential expression patterns in the different tissues studied. Quantitative real-time PCR (qRT-PCR) was performed to validate the expression patterns of selected stress-responsive, Ca_NAC (Cicer arietinum - 14), Cc_NAC (Cajanus cajan - 15), and Ah_NAC (Arachis hypogaea - 14) genes using drought-stressed and well-watered root tissues from two contrasting drought-responsive genotypes of each of the three legumes. Based on expression analysis, Ca_06899, Ca_18090, Ca_22941, Ca_04337, Ca_04069, Ca_04233, Ca_12660, Ca_16379, Ca_16946, and Ca_21186; Cc_26125, Cc_43030, Cc_43785, Cc_43786, Cc_22429, and Cc_22430; Ah_ann1.G1V3KR.2, Ah_ann1.MI72XM.2, Ah_ann1.V0X4SV.1, Ah_ann1.FU1JML.2, and Ah_ann1.8AKD3R.1 were identified as potential drought stress-responsive candidate genes.

Conclusion

As NAC genes are known to play role in several physiological and biological activities, a more comprehensive study on genome-wide identification and expression analyses of the NAC proteins have been carried out in chickpea, pigeonpea and groundnut. We have identified a total of 21 potential drought-responsive NAC genes in these legumes. These genes displayed correlation between gene expression, transcriptional regulation, and better tolerance against drought. The identified candidate genes, after validation, may serve as a useful resource for molecular breeding for drought tolerance in the SAT legume crops.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07602-5.

Molecular mapping of quantitative trait loci for ascochyta blight and botrytis grey mould resistance in an inter-specific cross in chickpea (Cicer arietinum L.) using genotyping by sequencing

Ascochyta blight (AB) and botrytis grey mould (BGM) are the most devastating fungal diseases of chickpea worldwide. The wild relative of chickpea, C. reticulatum acc. ILWC 292 was found resistant to BGM whereas, GPF2 (Cicer arietinum L.) is resistant to AB. A total of 187 F₈ Recombinant Inbred Lines (RILs) developed from an inter-specific cross of GPF2 × C. reticulatum acc. ILWC 292 were used to identify quantitative trait loci (QTLs) responsible for resistance to AB and BGM. RILs along with parents were evaluated under artificial epiphytotic field/laboratory conditions for two years. Highly significant differences (P < 0.001) were observed for reaction to both pathogens in both years. Parents and RILs were genotyped-by-sequencing to identify genome wide single nucleotide polymorphism (SNPs). A total of 1365 filtered and parental polymorphic SNPs were used for linkage map construction, of which, 673 SNPs were arranged on eight linkage groups. Composite interval mapping revealed three QTLs for AB and four QTLs for BGM resistance. Out of which, two QTLs for AB and three QTLs for BGM were consistent in both years. These QTLs can be targeted for further fine mapping for deployment of resistance to AB and BGM in elite chickpea cultivars using marker-assisted-selection.

Introgression of "QTL-hotspot" region enhances drought tolerance and grain yield in three elite chickpea cultivars

With an aim of enhancing drought tolerance using a marker-assisted backcrossing (MABC) approach, we introgressed the "QTL-hotspot" region from ICC 4958 accession that harbors quantitative trait loci (QTLs) for several drought-tolerance related traits into three elite Indian chickpea (Cicer arietinum L.) cultivars: Pusa 372, Pusa 362, and DCP 92-3. Of eight simple sequence repeat (SSR) markers in the QTL-hotspot region, two to three polymorphic markers were used for foreground selection with respective cross-combinations. A total of 47, 53, and 46 SSRs were used for background selection in case of introgression lines (ILs) developed in genetic backgrounds of Pusa 372, Pusa 362, and DCP 92-3, respectively. In total, 61 ILs (20 BC₃ F₃ in Pusa 372; 20 BC₂ F₃ in Pusa 362, and 21 BC₃ F₃ in DCP 92-3), with >90% recurrent parent genome recovery were developed. Six improved lines in different genetic backgrounds (e.g. BGM 10216 in Pusa 372; BG 3097 and BG 4005 in Pusa 362; IPC(L4-14), IPC(L4-16), and IPC(L19-1) in DCP 92-3) showed better performance than their respective recurrent parents. BGM 10216, with 16% yield gain over Pusa 372, has been released as Pusa Chickpea 10216 by the Central Sub-Committees on Crop Standards, Notification and Release of Varieties of Agricultural Crops, Ministry of Agriculture and Farmers Welfare, Government of India, for commercial cultivation in India. In summary, this study reports introgression of the QTL-hotspot for enhancing yield under rainfed conditions, development of several introgression lines, and release of Pusa Chickpea 10216 developed through molecular breeding in India.

Genomic resources in plant breeding for sustainable agriculture

Climate change during the last 40 years has had a serious impact on agriculture and threatens global food and nutritional security. From over half a million plant species, cereals and legumes are the most important for food and nutritional security. Although systematic plant breeding has a relatively short history, conventional breeding coupled with advances in technology and crop management strategies has increased crop yields by 56 % globally between 1965-85, referred to as the Green Revolution. Nevertheless, increased demand for food, feed, fiber, and fuel necessitates the need to break existing yield barriers in many crop plants. In the first decade of the 21st century we witnessed rapid discovery, transformative technological development and declining costs of genomics technologies. In the second decade, the field turned towards making sense of the vast amount of genomic information and subsequently moved towards accurately predicting gene-to-phenotype associations and tailoring plants for climate resilience and global food security. In this review we focus on genomic resources, genome and germplasm sequencing, sequencing-based trait mapping, and genomics-assisted breeding approaches aimed at developing biotic stress resistant, abiotic stress tolerant and high nutrition varieties in six major cereals (rice, maize, wheat, barley, sorghum and pearl millet), and six major legumes (soybean, groundnut, cowpea, common bean, chickpea and pigeonpea). We further provide a perspective and way forward to use genomic breeding approaches including marker-assisted selection, marker-assisted backcrossing, haplotype based breeding and genomic prediction approaches coupled with machine learning and artificial intelligence, to speed breeding approaches. The overall goal is to accelerate genetic gains and deliver climate resilient and high nutrition crop varieties for sustainable agriculture.

Molecular Mechanisms and Biochemical Pathways for Micronutrient Acquisition and Storage in Legumes to Support Biofortification for Nutritional Security

The world faces a grave situation of nutrient deficiency as a consequence of increased uptake of calorie-rich food that threaten nutritional security. More than half the world's population is affected by different forms of malnutrition. Unhealthy diets associated with poor nutrition carry a significant risk of developing non-communicable diseases, leading to a high mortality rate. Although considerable efforts have been made in agriculture to increase nutrient content in cereals, the successes are insufficient. The number of people affected by different forms of malnutrition has not decreased much in the recent past. While legumes are an integral part of the food system and widely grown in sub-Saharan Africa and South Asia, only limited efforts have been made to increase their nutrient content in these regions. Genetic variation for a majority of nutritional traits that ensure nutritional security in adverse conditions exists in the germplasm pool of legume crops. This diversity can be utilized by selective breeding for increased nutrients in seeds. The targeted identification of precise factors related to nutritional traits and their utilization in a breeding program can help mitigate malnutrition. The principal objective of this review is to present the molecular mechanisms of nutrient acquisition, transport and metabolism to support a biofortification strategy in legume crops to contribute to addressing malnutrition.

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

KEY MESSAGE

Comparative assessment identified naïve interaction model, and naïve and informed interaction GS models suitable for achieving higher prediction accuracy in groundnut keeping in mind the high genotype × environment interaction for complex traits. 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.

A high-density SNP-based linkage map using genotyping-by-sequencing and its utilization for improved genome assembly of chickpea (Cicer arietinum L.)

Genotyping-by-sequencing (GBS) allows rapid identification of markers for use in development of linkage maps, which expedite efficient breeding programs. In the present study, we have utilized GBS approach to identify and genotype single-nucleotide polymorphism (SNP) markers in an inter-specific RIL population of Cicer arietinum L. X C. reticulatum. A total of 141,639 raw SNPs were identified using the TASSEL-GBS pipeline. After stringent filtering, 8208 candidate SNPs were identified of which ~ 37% were localized in the intragenic regions followed by genic regions (~ 30%) and intergenic regions (~ 27%). We then utilized 6920 stringent selected SNPs from present study and 6714 SNPs and microsatellite markers available from previous studies for construction of linkage map. The resulting high-density linkage map comprising of eight linkage groups contained 13,590 markers which spanned 1299.14 cM of map length with an average marker density of 0.095 cM. Further, the derived linkage map was used to improve the available assembly of desi chickpea genome by anchoring 443 previously unplaced scaffolds onto eight linkage groups. The present efforts have refined anchoring of the desi chickpea genome assembly to 55.57% of the ~ 520 Mb of assembled desi genome. To the best of our knowledge, the linkage map generated in the present study represents one of the most dense linkage map developed for the crop till date. It will serve as a valuable resource for fine mapping and positional cloning of important quantitative trait loci (QTLs) associated with agronomical traits and also for anchoring and ordering of future genome sequence assemblies.

The Dawn of the Age of Multi-Parent MAGIC Populations in Plant Breeding: Novel Powerful Next-Generation Resources for Genetic Analysis and Selection of Recombinant Elite Material

The compelling need to increase global agricultural production requires new breeding approaches that facilitate exploiting the diversity available in the plant genetic resources. Multi-parent advanced generation inter-cross (MAGIC) populations are large sets of recombinant inbred lines (RILs) that are a genetic mosaic of multiple founder parents. MAGIC populations display emerging features over experimental bi-parental and germplasm populations in combining significant levels of genetic recombination, a lack of genetic structure, and high genetic and phenotypic diversity. The development of MAGIC populations can be performed using “funnel” or “diallel” cross-designs, which are of great relevance choosing appropriate parents and defining optimal population sizes. Significant advances in specific software development are facilitating the genetic analysis of the complex genetic constitutions of MAGIC populations. Despite the complexity and the resources required in their development, due to their potential and interest for breeding, the number of MAGIC populations available and under development is continuously growing, with 45 MAGIC populations in different crops being reported here. Though cereals are by far the crop group where more MAGIC populations have been developed, MAGIC populations have also started to become available in other crop groups. The results obtained so far demonstrate that MAGIC populations are a very powerful tool for the dissection of complex traits, as well as a resource for the selection of recombinant elite breeding material and cultivars. In addition, some new MAGIC approaches that can make significant contributions to breeding, such as the development of inter-specific MAGIC populations, the development of MAGIC-like populations in crops where pure lines are not available, and the establishment of strategies for the straightforward incorporation of MAGIC materials in breeding pipelines, have barely been explored. The evidence that is already available indicates that MAGIC populations will play a major role in the coming years in allowing for impressive gains in plant breeding for developing new generations of dramatically improved cultivars.

Photosynthesis in a Changing Global Climate: Scaling Up and Scaling Down in Crops

Photosynthesis is the major process leading to primary production in the Biosphere. There is a total of 7000bn tons of CO2 in the atmosphere and photosynthesis fixes more than 100bn tons annually. The CO2 assimilated by the photosynthetic apparatus is the basis of crop production and, therefore, of animal and human food. This has led to a renewed interest in photosynthesis as a target to increase plant production and there is now increasing evidence showing that the strategy of improving photosynthetic traits can increase plant yield. However, photosynthesis and the photosynthetic apparatus are both conditioned by environmental variables such as water availability, temperature, [CO2], salinity, and ozone. The "omics" revolution has allowed a better understanding of the genetic mechanisms regulating stress responses including the identification of genes and proteins involved in the regulation, acclimation, and adaptation of processes that impact photosynthesis. The development of novel non-destructive high-throughput phenotyping techniques has been important to monitor crop photosynthetic responses to changing environmental conditions. This wealth of data is being incorporated into new modeling algorithms to predict plant growth and development under specific environmental constraints. This review gives a multi-perspective description of the impact of changing environmental conditions on photosynthetic performance and consequently plant growth by briefly highlighting how major technological advances including omics, high-throughput photosynthetic measurements, metabolic engineering, and whole plant photosynthetic modeling have helped to improve our understanding of how the photosynthetic machinery can be modified by different abiotic stresses and thus impact crop production.

Identification of QTLs for resistance to leaf spots in cultivated peanut (Arachis hypogaea L.) through GWAS analysis

Two QTLs on ChrB09 significantly associated with both early and late leaf spots were identified by genome-wide association study in the US peanut mini-core collection. Early leaf spot (ELS) and late leaf spot (LLS) are two serious peanut diseases in the USA, causing tens of millions of dollars of annual economic losses. However, the genetic factors underlying resistance to those diseases in peanuts have not been well-studied. We conducted a genome-wide association study for the two peanut diseases using Affymetrix version 2.0 SNP array with 120 genotypes mainly coming from the US peanut mini-core collection. A total of 46 quantitative trait loci (QTLs) were identified with phenotypic variation explained (PVE) from 10.19 to 24.11%, in which eighteen QTLs are for resistance to ELS and 28 QTLs for LLS. Among the 46 QTLs, there were four and two major QTLs with PVE higher than 16.99% for resistance ELS and LLS, respectively. Of the six major QTLs, five were located on the B sub-genome and only one was on the A sub-genome, which suggested that the B sub-genome has more potential resistance genomic regions than the A sub-genome. In addition, two genomic regions on chromosome B09 were found to provide significant resistance to both ELS and LLS. A total of 74 non-redundant genes were identified as resistance genes, among which, twelve candidate genes were in significant genomic regions including two candidate genes for both ELS and LLS, and other ten candidate genes for ELS. The QTLs and candidate genes obtained from this study will be useful to breed peanuts for resistances to the diseases.

Quantitative Trait Locus Mapping of Clubroot Resistance and Plasmodiophora brassicae Pathotype Banglim-Specific Marker Development in Brassica rapa

Clubroot resistance is an economically important trait in Brassicaceae crops. Although many quantitative trait loci (QTLs) for clubroot resistance have been identified in Brassica, disease-related damage continues to occur owing to differences in host variety and constant pathogen variation. Here, we investigated the inheritance of clubroot resistance in a double haploid population developed by crossing clubroot resistant and susceptible lines "09CR500" and "09CR501", respectively. The resistance of "09CR500" to Plasmodiophora brassicae pathotype "Banglim" was controlled as a single dominant gene, with the segregation of resistance and susceptibility being nearly 1:1. PbBrA08^Banglim was identified as having a logarithm of odds value of 7.9-74.8, and a phenotypic variance of 26.0-97.1% with flanking marker "09CR.11390652" in A08. After aligning QTL regions to the B. rapa reference genome, 11 genes were selected as candidates. PbBrA08^Banglim was located near Crr1, CRs, and Rcr9 loci, but differences were validated by marker analysis, gene structural variations, and gene expression levels, as well as phenotypic responses to the pathotype. Genotyping using the "09CR.11390652" marker accurately distinguished the Banglim-resistance phenotypes in the double haploid population. Thus, the developed marker will be useful in Brassica breeding programs, marker-assisted selection, and gene pyramiding to identify and develop resistant cultivars.

Dissection of the genetic basis of oil content in Chinese peanut cultivars through association mapping

Background

Peanut is one of the primary sources for vegetable oil worldwide, and enhancing oil content is the main objective in several peanut breeding programs of the world. Tightly linked markers are required for faster development of high oil content peanut varieties through genomics-assisted breeding (GAB), and association mapping is one of the promising approaches for discovery of such associated markers.

Results

An association mapping panel consisting of 292 peanut varieties extensively distributed in China was phenotyped for oil content and genotyped with 583 polymorphic SSR markers. These markers amplified 3663 alleles with an average of 6.28 alleles per locus. The structure, phylogenetic relationship, and principal component analysis (PCA) indicated two subgroups majorly differentiating based on geographic regions. Genome-wide association analysis identified 12 associated markers including one (AGGS1014_2) highly stable association controlling up to 9.94% phenotypic variance explained (PVE) across multiple environments. Interestingly, the frequency of the favorable alleles for 12 associated markers showed a geographic difference. Two associated markers (AGGS1014_2 and AHGS0798) with 6.90–9.94% PVE were verified to enhance oil content in an independent RIL population and also indicated selection during the breeding program.

Conclusion

This study provided insights into the genetic basis of oil content in peanut and verified highly associated two SSR markers to facilitate marker-assisted selection for developing high-oil content breeding peanut varieties.

An integrated research framework combining genomics, systems biology, physiology, modelling and breeding for legume improvement in response to elevated CO2 under climate change scenario

How unprecedented changes in climatic conditions will impact yield and productivity of some crops and their response to existing stresses, abiotic and biotic interactions is a key global concern. Climate change can also alter natural species' abundance and distribution or favor invasive species, which in turn can modify ecosystem dynamics and the provisioning of ecosystem services. Basic anatomical differences in C3 and C4 plants lead to their varied responses to climate variations. In plants having a C3 pathway of photosynthesis, increased atmospheric carbon dioxide (CO2) positively regulates photosynthetic carbon (C) assimilation and depresses photorespiration. Legumes being C3 plants, they may be in a favorable position to increase biomass and yield through various strategies. This paper comprehensively presents recent progress made in the physiological and molecular attributes in plants with special emphasis on legumes under elevated CO2 conditions in a climate change scenario. A strategic research framework for future action integrating genomics, systems biology, physiology and crop modelling approaches to cope with changing climate is also discussed. Advances in sequencing and phenotyping methodologies make it possible to use vast genetic and genomic resources by deploying high resolution phenotyping coupled with high throughput multi-omics approaches for trait improvement. Integrated crop modelling studies focusing on farming systems design and management, prediction of climate impacts and disease forecasting may also help in planning adaptation. Hence, an integrated research framework combining genomics, plant molecular physiology, crop breeding, systems biology and integrated crop-soil-climate modelling will be very effective to cope with climate change.

Fine mapping and gene cloning in the post-NGS era: advances and prospects

Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.

Integrating genomics for chickpea improvement: achievements and opportunities

Integration of genomic technologies with breeding efforts have been used in recent years for chickpea improvement. Modern breeding along with low cost genotyping platforms have potential to further accelerate chickpea improvement efforts. The implementation of novel breeding technologies is expected to contribute substantial improvements in crop productivity. While conventional breeding methods have led to development of more than 200 improved chickpea varieties in the past, still there is ample scope to increase productivity. It is predicted that integration of modern genomic resources with conventional breeding efforts will help in the delivery of climate-resilient chickpea varieties in comparatively less time. Recent advances in genomics tools and technologies have facilitated the generation of large-scale sequencing and genotyping data sets in chickpea. Combined analysis of high-resolution phenotypic and genetic data is paving the way for identifying genes and biological pathways associated with breeding-related traits. Genomics technologies have been used to develop diagnostic markers for use in marker-assisted backcrossing programmes, which have yielded several molecular breeding products in chickpea. We anticipate that a sequence-based holistic breeding approach, including the integration of functional omics, parental selection, forward breeding and genome-wide selection, will bring a paradigm shift in development of superior chickpea varieties. There is a need to integrate the knowledge generated by modern genomics technologies with molecular breeding efforts to bridge the genome-to-phenome gap. Here, we review recent advances that have led to new possibilities for developing and screening breeding populations, and provide strategies for enhancing the selection efficiency and accelerating the rate of genetic gain in chickpea.

High-resolution mapping of a major and consensus quantitative trait locus for oil content to a ~ 0.8-Mb region on chromosome A08 in peanut (Arachis hypogaea L.)

KEY MESSAGE: ddRAD-seq-based high-density genetic map comprising 2595 loci identified a major and consensus QTL with a linked marker in a 0.8-Mb physical interval for oil content in peanut. Enhancing oil content is an important breeding objective in peanut. High-resolution mapping of quantitative trait loci (QTLs) with linked markers could facilitate marker-assisted selection in breeding for target traits. In the present study, a recombined inbred line population (Xuhua 13 × Zhonghua 6) was used to construct a genetic map based on double-digest restriction-site-associated DNA sequencing (ddRAD-seq). The resulting high-density genetic map contained 2595 loci, and spanned a length of 2465.62 cM, with an average distance of 0.95 cM/locus. Seven QTLs for oil content were identified on five linkage groups, including the major and stable QTL qOCA08.1 on chromosome A08 with 10.14-27.19% phenotypic variation explained. The physical interval of qOCA08.1 was further delimited to a ~ 0.8-Mb genomic region where two genes affecting oil synthesis had been annotated. The marker SNPOCA08 was developed targeting the SNP loci associated with oil content and validated in peanut cultivars with diverse oil contents. The major and stable QTL identified in the present study could be further dissected for gene discovery. Furthermore, the tightly linked marker for oil content would be useful in marker-assisted breeding in peanut.

Legume genomics and transcriptomics: From classic breeding to modern technologies

Legumes are essential and play a significant role in maintaining food standards and augmenting physiochemical soil properties through the biological nitrogen fixation process. Biotic and abiotic factors are the main factors limiting legume production. Classical breeding methodologies have been explored extensively about the problem of truncated yield in legumes but have not succeeded at the desired rate. Conventional breeding improved legume genotypes but with more resources and time. Recently, the invention of next-generation sequencing (NGS) and high-throughput methods for genotyping have opened new avenues for research and developments in legume studies. During the last decade, genome sequencing for many legume crops documented. Sequencing and re-sequencing of important legume species have made structural variation and functional genomics conceivable. NGS and other molecular techniques such as the development of markers; genotyping; high density genetic linkage maps; quantitative trait loci (QTLs) identification, expressed sequence tags (ESTs), single nucleotide polymorphisms (SNPs); and transcription factors incorporated into existing breeding technologies have made possible the accurate and accelerated delivery of information for researchers. The application of genome sequencing, RNA sequencing (transcriptome sequencing), and DNA sequencing (re-sequencing) provide considerable insights for legume development and improvement programs.

Moreover, RNA-Seq helps to characterize genes, including differentially expressed genes, and can be applied for functional genomics studies, especially when there is limited information available for the studied genomes. Genome-based crop development studies and the availability of genomics data as well as decision-making gears look be specific for breeding programs. This review mainly presents an overview of the path from classical breeding to new emerging genomics tools, which will trigger and accelerate genomics-assisted breeding for recognition of novel genes for yield and quality characters for sustainable legume crop production.

Mapping Quantitative Trait Loci for Carotenoid Concentration in Three F2 Populations of Chickpea

Quantitative trait locus (QTL) analyses for carotenoids in chickpea were completed for three F₂ populations. A moderate number of QTLs and candidate genes associated with carotenoid concentration in chickpea seeds were identified. Green cotyledon color is positively associated with provitamin A carotenoids. Three F₂ populations derived from crosses between cultivars with green and yellow cotyledon colors were used to identify quantitative trait loci (QTLs) associated with carotenoid components in chickpea (Cicer arietinum L.) seeds developed by the Crop Development Centre (CDC). Carotenoids including violaxanthin, lutein, zeaxanthin, β-cryptoxanthin, and β-carotene were assessed in the F_2:3 seeds via high-performance liquid chromatography (HPLC). In the 'CDC Jade' × 'CDC Frontier' population, 1068 bin markers derived from the 50K Axiom CicerSNP array were mapped onto eight linkage groups (LGs). Eight QTLs, including two each for β-carotene and zeaxanthin and one each for total carotenoids, β-cryptoxanthin, β-carotene, and violaxanthin were identified in this population. In the 'CDC Cory' × 'CDC Jade' population, 694 bin markers were mapped onto eight LGs and one partial LG. Quantitative trait loci for β-cryptoxanthin, β-carotene, violaxanthin, lutein, and total carotenoids were identified on LG8. A map with eight LGs was developed from 581 bin markers in the third population derived from the 'ICC4475' × 'CDC Jade' cross. One QTL for β-carotene and four QTLs, one each for β-cryptoxanthin, β-carotene, lutein, and total carotenoids, were identified in this population. The highest phenotypic variation explained by the QTLs was for β-carotene, which ranged from 58 to 70% in all three populations. A major gene for cotyledon color was mapped on LG8 in each population. A significant positive correlation between cotyledon color and carotenoid concentration was observed. Potential candidate genes associated with carotenoid components were obtained and their locations on the chickpea genome are presented.

African Orphan Crops Consortium (AOCC): status of developing genomic resources for African orphan crops

The African Orphan Crops Consortium (AOCC) successfully initiated the ambitious genome sequencing project of 101 African orphan crops/trees with 6 genomes sequenced, 6 near completion, and 20 currently in progress. Addressing stunting, malnutrition, and hidden hunger through nutritious, economic, and resilient agri-food system is one of the major agricultural challenges of this century. As sub-Saharan Africa harbors a large portion of the severely malnourished population, the African Orphan Crops Consortium (AOCC) was established in 2011 with an aim to reduce stunting and malnutrition by providing nutritional security through improving locally adapted nutritious, but neglected, under-researched or orphan African food crops. Foods from these indigenous or naturalized crops and trees are rich in minerals, vitamins, and antioxidant, and are an integral part of the dietary portfolio and cultural, social, and economic milieu of African farmers. Through stakeholder consultations supported by the African Union, 101 African orphan and under-researched crop species were prioritized to mainstream into African agri-food systems. The AOCC, through a network of international-regional-public-private partnerships and collaborations, is generating genomic resources of three types, i.e., reference genome sequence, transcriptome sequence, and re-sequencing 100 accessions/species, using next-generation sequencing (NGS) technology. Furthermore, the University of California Davis African Plant Breeding Academy under the AOCC banner is training 150 lead African scientists to breed high yielding, nutritious, and climate-resilient (biotic and abiotic stress tolerant) crop varieties that meet African farmer and consumer needs. To date, one or more forms of sequence data have been produced for 60 crops. Reference genome sequences for six species have already been published, 6 are almost near completion, and 19 are in progress.

Genetics, genomics and breeding of groundnut (Arachis hypogaea L.)

Groundnut is an important food and oil crop in the semiarid tropics, contributing to household food consumption and cash income. In Asia and Africa, yields are low attributed to various production constraints. This review paper highlights advances in genetics, genomics and breeding to improve the productivity of groundnut. Genetic studies concerning inheritance, genetic variability and heritability, combining ability and trait correlations have provided a better understanding of the crop's genetics to develop appropriate breeding strategies for target traits. Several improved lines and sources of variability have been identified or developed for various economically important traits through conventional breeding. Significant advances have also been made in groundnut genomics including genome sequencing, marker development and genetic and trait mapping. These advances have led to a better understanding of the groundnut genome, discovery of genes/variants for traits of interest and integration of marker-assisted breeding for selected traits. The integration of genomic tools into the breeding process accompanied with increased precision of yield trialing and phenotyping will increase the efficiency and enhance the genetic gain for release of improved groundnut varieties.

Resistance to Plant-Parasitic Nematodes in Chickpea: Current Status and Future Perspectives

Plant-parasitic nematodes constrain chickpea (Cicer arietinum) production, with annual yield losses estimated to be 14% of total global production. Nematode species causing significant economic damage in chickpea include root-knot nematodes (Meloidogyne artiella, M. incognita, and M. javanica), cyst nematode (Heterodera ciceri), and root-lesion nematode (Pratylenchus thornei). Reduced functionality of roots from nematode infestation leads to water stress and nutrient deficiency, which in turn lead to poor plant growth and reduced yield. Integration of resistant crops with appropriate agronomic practices is recognized as the safest and most practical, economic and effective control strategy for plant-parasitic nematodes. However, breeding for resistance to plant-parasitic nematodes has numerous challenges that originate from the narrow genetic diversity of the C. arietinum cultigen. While levels of resistance to M. artiella, H. ciceri, and P. thornei have been identified in wild Cicer species that are superior to resistance levels in the C. arietinum cultigen, barriers to interspecific hybridization restrict the use of these crop wild relatives, as sources of nematode resistance. Wild Cicer species of the primary genepool, C. reticulatum and C. echinospermum, are the only species that have been used to introgress resistance genes into the C. arietinum cultigen. The availability of genomic resources, including genome sequence and re-sequence information, the chickpea reference set and mini-core collections, and new wild Cicer collections, provide unprecedented opportunities for chickpea improvement. This review surveys progress in the identification of novel genetic sources of nematode resistance in international germplasm collections and recommends genome-assisted breeding strategies to accelerate introgression of nematode resistance into elite chickpea cultivars.

Genome-wide cis-regulatory signatures for modulation of agronomic traits as exemplified by drought yield index (DYI) in chickpea

Developing functional molecular tags from the cis-regulatory sequence components of genes is vital for their deployment in efficient genetic dissection of complex quantitative traits in crop plants including chickpea. The current study identified 431,194 conserved non-coding SNP (CNSNP) from the cis-regulatory element regions of genes which were annotated on a chickpea genome. These genome-wide CNSNP marker resources are made publicly accessible through a user-friendly web-database ( http://www.cnsnpcicarbase.com ). The CNSNP-based quantitative trait loci (QTL) and expression QTL (eQTL) mapping and genome-wide association study (GWAS) were further integrated with global gene expression landscapes, molecular haplotyping, and DNA-protein interaction study in the association panel and recombinant inbred lines (RIL) mapping population to decode complex genetic architecture of one of the vital seed yield trait under drought stress, drought yield index (DYI), in chickpea. This delineated two constituted natural haplotypes and alleles from a histone H3 protein-coding gene and its transcriptional regulator NAC transcription factor (TF) harboring the major QTLs and trans-acting eQTL governing DYI in chickpea. The effect of CNSNPs in TF-binding cis-element of a histone H3 gene in altering the binding affinity and transcriptional activity of NAC TF based on chromatin immunoprecipitation-quantitative PCR (ChIP-qPCR) assay was evident. The CNSNP-led promising molecular tags scanned will essentially have functional significance to decode transcriptional gene regulatory function and thus can drive translational genomic analysis in chickpea.

Marker-assisted backcrossing to improve seed oleic acid content in four elite and popular peanut (Arachis hypogaea L.) cultivars with high oil content

High oleic acid composition is an important determinant of seed quality in peanut (Arachis hypogaea) in regard to its nutritional benefits for human health and prolonged shelf-life for peanut products. To improve the oleic acid content of popular peanut cultivars in China, four peanut cultivars of different market types were hybridized with high-oleic-acid donors and backcrossed for four generations as recurrent parents using fad2 marker-assisted backcross selection. Seed quality traits in advanced generations derived by selfing were assessed using near-infrared reflectance spectroscopy for detection of oleic acid and Kompetitive allele-specific PCR (KASP) screening of fad2 mutant markers. Twenty-four high-oleic-acid lines of BC₄F₄ and BC₄F₅ populations, with morphological features and agronomic traits similar to those of the recurrent parents, were obtained within 5 years. The genetic backgrounds of BC₄F₅ lines were estimated using the KASP assay, which revealed the genetic background recovery rate was 79.49%-92.31%. The superior lines raised are undergoing a multi-location test for cultivar registration and release. To our knowledge, this is the first application of single nucleotide polymorphism markers based on the high-throughput and cost-effective KASP assay for detection of fad2 mutations and genetic background evaluation in a peanut breeding program.

Legume biofortification is an underexploited strategy for combatting hidden hunger

Legumes are the world's primary source of dietary protein and are particularly important for those in developing economies. However, the biofortification potential of legumes remains underexploited. Legumes offer a diversity of micronutrients and amino acids, exceeding or complementing the profiles of cereals. As such, the enhancement of legume nutritional composition presents an appealing target for addressing the "hidden hunger" of global micronutrient malnutrition. Affecting ~2 billion people, micronutrient malnutrition causes severe health effects ranging from stunted growth to reduced lifespan. An increased availability of micronutrient-enriched legumes, particularly to those in socio-economically deprived areas, would serve the dual functions of ameliorating hidden hunger and increasing the positive health effects associated with legumes. Here, we give an updated overview of breeding approaches for the nutritional improvement of legumes, and crucially, we highlight the importance of considering nutritional improvement in a wider ecological context. Specifically, we review the potential of the legume microbiome for agronomic trait improvement and highlight the need for increased genetic, biochemical, and environmental data resources. Finally, we state that such resources should be complemented by an international and multidisciplinary initiative that will drive crop improvement and, most importantly, ensure that research outcomes benefit those who need them most.

Super Annigeri 1 and improved JG 74: two Fusarium wilt-resistant introgression lines developed using marker-assisted backcrossing approach in chickpea (Cicer arietinum L.)

Annigeri 1 and JG 74 are elite high yielding desi cultivars of chickpea with medium maturity duration and extensively cultivated in Karnataka and Madhya Pradesh, respectively. Both cultivars, in recent years, have become susceptible to race 4 of Fusarium wilt (FW). To improve Annigeri 1 and JG 74, we introgressed a genomic region conferring resistance against FW race 4 (foc4) through marker-assisted backcrossing using WR 315 as the donor parent. For foreground selection, TA59, TA96, TR19 and TA27 markers were used at Agricultural Research Station, Kalaburagi, while GA16 and TA96 markers were used at Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur. Background selection using simple sequence repreats (SSRs) for the cross Annigeri 1 × WR 315 in BC1F1 and BC2F1 lines resulted in 76-87% and 90-95% recurrent parent genome recovery, respectively. On the other hand, 90-97% genome was recovered in BC3F1 lines in the case of cross JG 74 × WR 315. Multilocation evaluation of 10 BC2F5 lines derived from Annigeri 1 provided one superior line referred to as Super Annigeri 1 with 8% increase in yield and enhanced disease resistance over Annigeri 1. JG 74315-14, the superior line in JG 74 background, had a yield advantage of 53.5% and 25.6% over the location trial means in Pantnagar and Durgapura locations, respectively, under Initial Varietal Trial of All India Coordinated Research Project on Chickpea. These lines with enhanced resistance and high yield performance are demonstration of successful deployment of molecular breeding to develop superior lines for FW resistance in chickpea.