Development and Evaluation of a High Density Genotyping 'Axiom_Arachis' Array with 58 K SNPs for Accelerating Genetics and Breeding in Groundnut (original) (raw)

Single nucleotide polymorphisms (SNPs) are the most abundant DNA sequence variation in the genomes which can be used to associate genotypic variation to the phenotype. Therefore, availability of a high-density SNP array with uniform genome coverage can advance genetic studies and breeding applications. Here we report the development of a high-density SNP array 'Axiom_Arachis' with 58 K SNPs and its utility in groundnut genetic diversity study. In this context, from a total of 163,782 SNPs derived from DNA resequencing and RNA-sequencing of 41 groundnut accessions and wild diploid ancestors, a total of 58,233 unique and informative SNPs were selected for developing the array. In addition to cultivated groundnuts (Arachis hypogaea), fair representation was kept for other diploids (A. duranensis, A. stenosperma, A. cardenasii, A. magna and A. batizocoi). Genotyping of the groundnut 'Reference Set' containing 300 genotypes identified 44,424 polymorphic SNPs and genetic diversity analysis provided in-depth insights into the genetic architecture of this material. The availability of the high-density SNP array 'Axiom_Arachis' with 58 K SNPs will accelerate the process of high resolution trait genetics and molecular breeding in cultivated groundnut. Crop improvement programs in general are focused on enhancing productivity, improving quality and resilience to biotic and abiotic stress by creating and/or harnessing genetic diversity. Genomics-assisted breeding (GAB) has accelerated crop improvement programs for development of improved cultivars in several crops 1. Availability of high density genotyping platform with uniformly distributed genome-wide genetic markers is must have genomic resource in a crop for high resolution genetic dissection of complex traits and tracking the favorable alleles in a breeding population 2. Single nucleotide polymorphisms (SNPs) are the most abundant DNA sequence variations among various types of structural/genetic/sequence variations in the genome. Until recently, it has been a tedious, labor-intensive and expensive task to develop even a limited number of SNPs. In the last decade, next-generation sequencing (NGS) technologies have evolved very rapidly and have become the cheapest and fastest method of identification of genome-wide SNPs 1. The most commonly used NGS approach for identifying and assaying SNPs is genotyping-by-sequencing (GBS) 3. While GBS provides generation of high-density SNP data in less time and less cost, allelic data are not generated for all the SNPs detected among individuals/lines in a given population 4. Furthermore, though the imputation methods are available to infer missing data, these methods rely on prior extensive genotyping data.