Cultivated groundnut or peanut (Arachis hypogaea) is an allopolyploid crop with a large complex genome and genetic barrier for exchanging genetic diversity from its wild relatives due to ploidy differences. Optimum genetic and genomic resources are key for accelerating the process for trait mapping and gene discovery and deploying diagnostic markers in genomics-assisted breeding. The better utilization of different aspects of peanut biology such as genetics, genomics, transcriptomics, proteomics, epigenomics, metabolomics, and interactomics can be of great help to groundnut genetic improvement program across the globe. The availability of high-quality reference genome is core to all the “omics” approaches, and hence optimum genomic resources are a must for fully exploiting the potential of modern science into conventional breeding. In this context, groundnut is passing through a very critical and transformational phase by making available the required genetic and genomic resources such as reference genomes of progenitors, resequencing of diverse lines, transcriptome resources, germplasm diversity panel, and multi-parent genetic populations for conducting high-resolution trait mapping, identification of associated markers, and development of diagnostic markers for selected traits. Lastly, the available resources have been deployed in translating genomic information from genome to field by developing improved groundnut lines with enhanced resistance to root-knot nematode, rust, and late leaf spot and high oleic acid. In addition, the International Peanut Genome Initiative (IPGI) have made available the high-quality reference genome for cultivated tetraploid groundnut which will facilitate better utilization of genetic resources in groundnut improvement. In parallel, the development of high-density genotyping platforms, such as Axiom_Arachis array with 58 K SNPs, and constitution of training population will initiate the deployment of the modern breeding approach, genomic selection, for achieving higher genetic gains in less time with more precision.
Journal:
DOI: 10.1007/978-3-319-94746-4_9
Year: 2018