Genetic Mapping of Tolerance to Iron Deficiency Chlorosis in Peanut (Arachis Hypogaea L.)

Abstract

Iron deficiency chlorosis (IDC) under calcareous and alkaline soils is a significant abiotic stress affecting the growth and yield of peanut. In this study, the genomic regions governing IDC tolerance were mapped using a recombinant inbred line (RIL) population derived from TMV 2 (susceptible to IDC) and TMV 2-NLM (tolerant to IDC), which was phenotyped during the rainy seasons of 2019 and 2020 in the iron-deficient calcareous plots. The best linear unbiased prediction (BLUP) values for IDC tolerance traits like visual chlorotic rating (VCR), and SPAD chlorophyll meter reading (SCMR) were used for QTL analysis along with a genetic map carrying 700 GBS-derived SNP, AhTE and SSR markers. In total, 11 and 12 main-effect QTLs were identified for VCR and SCMR, respectively. Among them three QTLs were major with the phenotypic variance explained (PVE) of 10.3-34.4% for VCR, and two QTL were major for SCMR with PVE of 11.5-11.7%. A region (159.3-178.3 cM) on chromosome Ah13 carrying two QTLs (one each for VCR and SCMR) was consistent with the previous report. A SNP marker, Ah14_138037990 identified from single marker analysis for VCR was located in the intronic region of the gene Arahy.QA0C1, which is important for protein-binding. Overall, this study identified new QTLs and also validated QTL for IDC tolerance. These genomic resources could be useful for genomics-assisted breeding of peanut for IDC tolerance.

Understanding heat tolerance in vegetables: Physiological and molecular insights, and contemporary genomic approaches for enhancing heat stress resilience

“…GS serves as a pre-breeding tool for identifying germplasm with valuable variations, predicting the breeding value of plants within a breeding population. This application efficiently enhances genetic gain for quantitative traits, making GS an integral part of breeding programs, particularly in the private sector where it is widely utilized for developing new varieties in different crops within a short timeframe (Tayade et al, 2022). One notable advantage of GS over MAS and marker-assisted recurrent selection lies in its ability to detect alleles with minor effects, which can be crucial in the selection process.…”