Quantitative Trait Loci Mapping for Spike Characteristics in Hexaploid Wheat

Abstract

Wheat (Triticum aestivum L.) spike characteristics determine the number of grains produced on each spike and constitute key components of grain yield. Understanding of the genetic basis of spike characteristics in wheat, however, is limited. In this study, genotyping-by-sequencing (GBS) and the iSelect 9K assay were used on a doubled-haploid (DH) soft red winter wheat population that showed a wide range of phenotypic variation for spike traits. A genetic map spanning 2934.1 cM with an average interval length of 3.4 cM was constructed. Quantitative trait loci (QTL) analysis involving additive effects, epistasis (QQ) and QTL  environment (QE), and epistasis  environment (QQE) interactions detected a total of 109 QTL, 13 QE, and 20 QQ interactions in five environments. Spike characteristics were mainly determined by additive effects and were fine-tuned by QQ, QE, and QQE. Major QTL QSl.cz-1A/QFsn.cz-1A explained up to 30.9% of the phenotypic variation for spike length (SL) and fertile spikelet number, QGsp.cz-2B.1 explained up to 15.6% of the phenotypic variation of grain number per spikelet, and QSc.cz-5A.3 explained up to 80.2% of the phenotypic variation for spike compactness. Additionally, QTL for correlated spike characteristics formed QTL clusters on chromosomes 1A, 5A, 2B, 3B, 5B, 1D, and 5D. This study expands the understanding of the genetic basis of spike characteristics in hexaploid wheat. A number of stable QTL detected in this study have potential to be used in marker-assisted selection. Additionally, the genetic map generated in this study could be used to study other traits of economic importance.

Uncovering the Genetic Architecture of Fruiting Efficiency in Bread Wheat: A Viable Alternative to Increase Yield Potential

“…To our knowledge, no markers were previously reported as significant for these traits in similar positions to those found in this research. Few studies have reported genomic regions associated with FE and GFS (Guo et al, 2017; Zhou et al, 2017), primarily involving chromosomes 1D, 2A, 2D, 3B, 3D, 5B, and 7A. In our study, we found four markers associated with FE on 2A, 2D, 4D, and 5A and two markers on 7A linked to GFS.…”

“…In previous studies, stable genomic regions associated with TSS, FSS, and ESS were mainly detected on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 4B, 4D, 5A, 5D, 6A, 6B,7A, 7B, and 7D (Cui et al, 2012; Deng et al, 2017; Guo et al, 2017; Sun et al, 2017; Zhou et al, 2017; Liu et al, 2018; Yu et al, 2018). Here, we found MTAs linked to these traits on chromosomes 2A, 2D, and 7A.…”

Genome-wide association study reveals new loci for yield-related traits in Sichuan wheat germplasm under stripe rust stress

“…In other words, SlPS, TKW and SlC were more stable than FTN and KPSl. Consistent with many other reports, FTN had a low heritability and was strongly influenced by environments [5,9,31] and KPSl also displayed relatively low heritability, whereas SlPS, TKW and SlC had relatively higher heritabilities [3,9,[32][33][34].…”

Several stably expressed QTL for spike density of common wheat (Triticum aestivum) in multiple environments

“…This is not uncommon in numerous studies on QTL identification based on crossing populations. For example, quite a few of previous studies have also identified SD QTL in crossing populations where no significant differences were detected between their parents (Luo et al, ; Zhou et al, ).…”

“…Carver, & Z. W‐C., ; Sourdille et al, , ; Xu et al, ; Zhou et al, ). However, few QTL for SD stably expressed across multiple environments have been identified.…”