Abstract
BackgroundBread wheat (Triticum aestivum L.) is one of the most widely consumed cereal crops, but its complex genome makes it difficult to investigate the genetic effect on important agronomic traits. Genome-wide association (GWA) analysis is a useful method to identify genetic loci controlling complex phenotypic traits. With the RNA-sequencing based gene expression analysis, putative candidate genes governing important agronomic trait can be suggested and also molecular markers can be developed.ResultsWe observed major quantitative agronomic traits of wheat; the winter survival rate (WSR), days to heading (DTH), days to maturity (DTM), stem length (SL), spike length (SPL), awn length (AL), liter weight (LW), thousand kernel weight (TKW), and the number of seeds per spike (SPS), of 287 wheat accessions from diverse country origins. A significant correlation was observed between the observed traits, and the wheat genotypes were divided into three subpopulations according to the population structure analysis. The best linear unbiased prediction (BLUP) values of the genotypic effect for each trait under different environments were predicted, and these were used for GWA analysis based on a mixed linear model (MLM). A total of 254 highly significant marker-trait associations (MTAs) were identified, and 28 candidate genes closely located to the significant markers were predicted by searching the wheat reference genome and RNAseq data. Further, it was shown that the phenotypic traits were significantly affected by the accumulation of favorable or unfavorable alleles.ConclusionsFrom this study, newly identified MTA and putative agronomically useful genes will help to study molecular mechanism of each phenotypic trait. Further, the agronomically favorable alleles found in this study can be used to develop wheats with superior agronomic traits.
Highlights
Bread wheat (Triticum aestivum L.) is one of the most widely consumed cereal crops, but its complex genome makes it difficult to investigate the genetic effect on important agronomic traits
It was observed that winter survival rate (WSR) had the largest variation while days to heading (DTH) and days to maturity (DTM) had the smallest variation among the genotypes based on the coefficient of variation (CV)
DTH was positively correlated with DTM, stem length (SL), spike length (SPL), awn length (AL), and seeds per spike (SPS), and DTM was positively correlated with SPL and SPS
Summary
Bread wheat (Triticum aestivum L.) is one of the most widely consumed cereal crops, but its complex genome makes it difficult to investigate the genetic effect on important agronomic traits. Genome-wide association (GWA) analysis is a useful method to identify genetic loci controlling complex phenotypic traits. With the RNAsequencing based gene expression analysis, putative candidate genes governing important agronomic trait can be suggested and molecular markers can be developed. While conventional breeding is dependent on selecting superior varieties by phenotyping, more recently, with the development of sequencing technology, molecular breeding began to utilize genetic diversity among varieties. A number of molecular markers such as simple sequence repeat (SSR), random amplified polymorphic DNA (RAPD), and restriction fragment length polymorphism (RFLP) have been utilized in plant breeding [5,6,7]. Since the cost of next-generation sequencing (NGS) has begun to decrease, single nucleotide polymorphisms (SNPs) are becoming the most frequently used marker, owing to their abundance throughout all plant species [8]
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