Browsing by Author "Varshney, Rajeev K"

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    A chickpea genetic variation map based on the sequencing of 3,366 genomes
    (Springer Nature Publishing AG, 2021) Varshney, Rajeev K; Roorkiwal, Manish; Sun, Shuai; Bajaj, Prasad; Chitikineni, Annapurna; Thudi, Mahendar; Singh, Narendra P; Du, Xiao; Upadhyaya, Hari D; Khan, Aamir W; Wang, Yue; Garg, Vanika; Fan, Guangyi; Cowling, Wallace A; Crossa, José; Gentzbittel, Laurent; Voss-Fels, Kai Peter; Valluri, Vinod Kumar; Sinha, Pallavi; Singh, Vikas K; Ben, Cécile; Rathore, Abhishek; Punna, Ramu; Singh, Muneendra K; Tar'an, Bunyamin; Bharadwaj, Chellapilla; Yasin, Mohammad; Pithia, Motisagar S; Singh, Servejeet; Soren, Khela Ram; Kudapa, Himabindu; Jarquín, Diego; Cubry, Philippe; Hickey, Lee T; Dixit, Girish Prasad; Thuillet, Anne-Céline; Hamwieh, Aladdin; Kumar, Shiv; Deokar, Amit A; Chaturvedi, Sushil K; Francis, Aleena; Howard, Réka; Chattopadhyay, Debasis; Edwards, David; Lyons, Eric; Vigouroux, Yves; Hayes, Ben J; Wettberg, Eric von; Datta, Swapan K; Yang, Huanming; Nguyen, Henry T; Wang, Jian; Siddique, Kadambot H M; Mohapatra, Trilochan; Bennetzen, Jeffrey L; Xu, Xun; Liu, Xin
    Zero hunger and good health could be realized by 2030 through effective conservation, characterization and utilization of germplasm resources1. So far, few chickpea (Cicer arietinum) germplasm accessions have been characterized at the genome sequence level2. Here we present a detailed map of variation in 3,171 cultivated and 195 wild accessions to provide publicly available resources for chickpea genomics research and breeding. We constructed a chickpea pan-genome to describe genomic diversity across cultivated chickpea and its wild progenitor accessions. A divergence tree using genes present in around 80% of individuals in one species allowed us to estimate the divergence of Cicer over the last 21 million years. Our analysis found chromosomal segments and genes that show signatures of selection during domestication, migration and improvement. The chromosomal locations of deleterious mutations responsible for limited genetic diversity and decreased fitness were identified in elite germplasm. We identified superior haplotypes for improvement-related traits in landraces that can be introgressed into elite breeding lines through haplotype-based breeding, and found targets for purging deleterious alleles through genomics-assisted breeding and/or gene editing. Finally, we propose three crop breeding strategies based on genomic prediction to enhance crop productivity for 16 traits while avoiding the erosion of genetic diversity through optimal contribution selection (OCS)-based pre-breeding. The predicted performance for 100-seed weight, an important yield-related trait, increased by up to 23% and 12% with OCS- and haplotype-based genomic approaches, respectively.
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    Millets for a sustainable future
    (Oxford University Press, 2025) Ghatak, Arindam; Pierides, Iro; Singh, Roshan Kumar; Srivastava, Rakesh K; Varshney, Rajeev K; Prasad, Manoj; Chaturvedi, Palak; Weckwerth, Wolfram
    Our current agricultural system faces a perfect storm-climate change, burgeoning population, and unpredictable outbreaks like COVID-19 disrupt food production, particularly for vulnerable populations in developing countries. A paradigm shift in agriculture practices is needed to tackle these issues. One solution is the diversification of crop production. While ~56% of the protein consumed from plants stems from three major cereal crops (rice, wheat and maize), underutilized crops such as millets, legumes and other cereals are highly neglected by farmers and the research community. Millets are one of the most ancient and versatile orphan crops with attributes like fast-growing, high-yielding, withstanding harsh environments, and rich in micronutrients such as iron and zinc, making them appealing to achieve agronomic sustainability. Here, we highlight the contribution of millet to agriculture and pay attention to the latest research on the genetic diversity of millet, genomic resources, and next-generation omics and their applications under various stress conditions. Additionally, integrative omics technologies could identify and develop millets with desirable phenotypes having high agronomic value and mitigating climate change. Here, we emphasize that biotechnological interventions, such as genome-wide association, genomic selection, genome editing, and artificial intelligence/machine learning, can improve and breed millets more effectively.