Genome-Wide Association Mapping of Yield and Grain Quality Traits in Winter Wheat Genotypes

Abstract

The main goal of this study was to investigate the genetic basis of yield and grain quality traits in winter wheat genotypes using association mapping approach, and identify linked molecular markers for marker assisted selection. A total of 120 elite facultative/winter wheat genotypes were evaluated for yield, quality and other agronomic traits under rain-fed and irrigated conditions for two years (2011–2012) at the Tel Hadya station of ICARDA, Syria. The same genotypes were genotyped using 3,051 Diversity Array Technologies (DArT) markers, of which 1,586 were of known chromosome positions. The grain yield performance of the genotypes was highly significant both in rain-fed and irrigated sites. Average yield of the genotypes ranged from 2295 to 4038 kg/ha and 4268 to 7102 kg/ha under rain-fed and irrigated conditions, respectively. Protein content and alveograph strength (W) ranged from 13.6–16.1% and 217.6–375 Jx10-4, respectively. DArT markers wPt731910 (3B), wPt4680 (4A), wPt3509 (5A), wPt8183 (6B), and wPt0298 (2D) were significantly associated with yield under rain-fed conditions. Under irrigated condition, tPt4125 on chromosome 2B was significantly associated with yield explaining about 13% of the variation. Markers wPt2607 and wPt1482 on 5B were highly associated with protein content and alveograph strength explaining 16 and 14% of the variations, respectively. The elite genotypes have been distributed to many countries using ICARDA’s International system for potential direct release and/or use as parents after local adaptation trials by the NARSs of respective countries. The QTLs identified in this study are recommended to be used for marker assisted selection after through validation using bi-parental populations.

Heat‐Tolerant QTLs Associated with Grain Yield and Its Components in Spring Bread Wheat under Heat‐Stressed Environments of Sudan and Egypt

“…and exploit the high marker coverage and higher resolution of the new genotyping technologies without the time and effort needed to develop biparental mapping populations (Crossa et al, 2007). Breseghello and Sorrells (2006) and Tadesse et al (2015), among many others, identified significantly associated markers with kernel size and milling quality in winter wheat. Breseghello and Sorrells (2006) and Tadesse et al (2015), among many others, identified significantly associated markers with kernel size and milling quality in winter wheat.…”

“…Several MTA studies have been performed in wheat to identify closely linked molecular markers that could be used for marker-assisted selection and thereby increase the efficiency of conventional breeding efforts in pyramiding genes of interest in desired cultivars (Pinto et al, 2010;Edae et al, 2014;Tadesse et al, 2015;Ogbonnaya et al, 2017). However, it is well known that traits controlled mostly by major genes such as plant height and phenology can have a confounding effect over wheat performance-related traits (Olivares-Villegas et al, 2007;Lopes et al, 2012).…”

Population Structure and Genomewide Association Analysis of Resistance to Disease and Insensitivity to Ptr Toxins in Canadian Spring Wheat Using 90K SNP Array

“…Our population size was smaller than several other studies, which may have lowered the power of QTL detection (Yu et al, 2008). However, we used more stringent parameters to minimize false positives, including the use of more stringent threshold p-values (p £ 10 −5 ) for claiming significant marker-trait association than several other studies that only used p £ 10 −3 (Kollers et al, 2013;Gurung et al, 2014;Kollers et al, 2014;Zegeye et al, 2014;Tadesse et al, 2015) and/or the use of more PCs, accounting for ~50% of the variation for population structure as compared with several other studies that used PCs accounting for lower variation (Gurung et al, 2014;Winkler et al, 2016). Results from this study provide additional information to wheat researchers developing disease-resistant and Ptr toxin-insensitive spring wheat cultivars.…”

A MAGIC population-based genome-wide association study reveals functional association of GhRBB1_A07 gene with superior fiber quality in cotton

“…GWAS has several advantages over traditional QTL analysis, such as higher diversity, better utility of the identified QTL across diverse germplasm, and reduced time required for population development [10–12]. GWAS has been successfully employed in many plants, such as Arabidopsis [13], maize [10, 14], barley [15, 16], wheat [17, 18], rice [19], oat [20], sorghum [21] and soybean [11, 22]. In cotton, a few genetic studies using GWAS have been reported [2, 4, 23, 24].…”