Genotyping-by-Sequencing Based Genetic Mapping Identified Major and Consistent Genomic Regions for Productivity and Quality Traits in Peanut

Mangesh P Jadhav; Sunil S Gangurde; Anil A Hake; Arati Yadawad; Supriya S Mahadevaiah; Santosh K Pattanashetti; M V Channabyre Gowda; Kenta Shirasawa; Rajeev K Varshney; Manish K Pandey; Ramesh S Bhat

doi:10.3389/fpls.2021.668020

Genotyping-by-Sequencing Based Genetic Mapping Identified Major and Consistent Genomic Regions for Productivity and Quality Traits in Peanut

Front Plant Sci. 2021 Sep 23:12:668020. doi: 10.3389/fpls.2021.668020. eCollection 2021.

Affiliations

¹ Department of Biotechnology, University of Agricultural Sciences, Dharwad, India.
² Center of Excellence in Genomics & Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India.
³ Department of Genetics and Plant Breeding, University of Agricultural Sciences, Dharwad, India.
⁴ Department of Frontier Research and Development, Kazusa DNA Research Institute, Chiba, Japan.

Abstract

With an objective of identifying the genomic regions for productivity and quality traits in peanut, a recombinant inbred line (RIL) population developed from an elite variety, TMV 2 and its ethyl methane sulfonate (EMS)-derived mutant was phenotyped over six seasons and genotyped with genotyping-by-sequencing (GBS), Arachis hypogaea transposable element (AhTE) and simple sequence repeats (SSR) markers. The genetic map with 700 markers spanning 2,438.1 cM was employed for quantitative trait loci (QTL) analysis which identified a total of 47 main-effect QTLs for the productivity and oil quality traits with the phenotypic variance explained (PVE) of 10-52% over the seasons. A common QTL region (46.7-50.1 cM) on Ah02 was identified for the multiple traits, such as a number of pods per plant (NPPP), pod weight per plant (PWPP), shelling percentage (SP), and test weight (TW). Similarly, a QTL (7.1-18.0 cM) on Ah16 was identified for both SP and protein content (PC). Epistatic QTL (epiQTL) analysis revealed intra- and inter-chromosomal interactions for the main-effect QTLs and other genomic regions governing these productivity traits. The markers identified by a single marker analysis (SMA) mapped to the QTL regions for most of the traits. Among the five potential candidate genes identified for PC, SP and oil quality, two genes (Arahy.7A57YA and Arahy.CH9B83) were affected by AhMITE1 transposition, and three genes (Arahy.J5SZ1I, Arahy.MZJT69, and Arahy.X7PJ8H) involved functional single nucleotide polymorphisms (SNPs). With major and consistent effects, the genomic regions, candidate genes, and the associated markers identified in this study would provide an opportunity for gene cloning and genomics-assisted breeding for increasing the productivity and enhancing the quality of peanut.

Keywords: GBS; QTL validation; SSRs; main and epistatic QTL; peanut; productivity and quality traits; transposable elements.