QTL Analysis for Morphological Traits and Capsaicinoids Contents in Capsicum annuum

Abstract

Agriculturally important traits for breeding such as growth habit, yield, and pungency level are controlled by quantitative trait loci (QTLs) in pepper (Capsicum spp.). In this study QTLs were detected which are responsible for morphological traits and capsaicinoids contents. F6-F9 recombinant inbred lines (RILs) derived from a cross between pungent Perennial (C. annuum) and non-pungent Dempsey (C. annuum) were constructed. A total 28 morphological traits and capsaicinoids contents were evaluated for parents and RILs grown in three different environments. An ultra-high density linkage map containing 3,300 single nucleotide polymorphism (SNP) markers defined from whole genome sequencing of two parents and 120 RILs was used for QTL analyses. Using evaluated data and the linkage map, QTL analyses were performed for 27 morphological traits and capsaicinoids contents. Detected QTLs were consolidated to find the major QTLs controlling traits in multiple environments. 402 QTLs were detected for plant architecture, leaf, flower, fruit, and seed related traits. Consolidated 21 QTLs were mapped in chromosome 1, 2, 3, 4, 6, 7, 9, 10, and 11 which were found commonly from two or three environments. Among them, 4 QTL regions were associated with multiple traits. Major QTLs explained 50.9 and 61.4% of phenotypic variation for leaf length and fruit weight respectively. QTL analyses for capsaicin, dihydrocapsaicin and total capsaicinoids were performed and 72 QTLs were detected. Seven consolidated QTLs were distributed to chromosomes 1, 6, 9, and 11. QTLs in chromosome 6 controlling capsaicin and total capsaicinoids and in chromosome 11 controlling dihydrocapsaicin and total capsaicinoids were located in the same region. For major QTLs and the QTLs controlling more than two traits, SNP markers were located less than 1 cM. Therefore genes located in these QTL regions could be identified by SNP markers. Furthermore, SNP markers near the QTLs can be used to predict the values of quantitative trait after validation of the markers.