Identifying Candidate Genes for Enhancing Grain Zn Concentration in Wheat

Abstract

Wheat (Triticum aestivum L.) is one of the major staple food crops worldwide. Despite efforts in improving wheat quality, micronutrient levels are still below the optimal range for human nutrition. In particular, zinc (Zn) deficiency is a widespread problem in human nutrition in countries relying mainly on a cereal diet; hence improving Zn accumulation in grains is an imperative need. This study was designed to understand the genetic architecture of Zn grain concentrations in wheat grains. We performed a genome-wide association study (GWAS) for grain Zn concentrations in 369 European wheat genotypes, using field data from 3 years. The complete wheat panel was genotyped by high-density arrays of single nucleotide polymorphic (SNP) markers (90k iSELECT Infinium and 35k Affymetrix arrays) resulting in 15,523 polymorphic markers. Additionally, a subpanel of 183 genotypes was analyzed with a novel 135k Affymetrix marker array resulting in 28,710 polymorphic SNPs for high-resolution mapping of the potential genomic regions. The mean grain Zn concentration of the genotypes ranged from 25.05–52.67 μg g-1 dry weight across years with a moderate heritability value. Notably, 40 marker-trait associations (MTAs) were detected in the complete panel of varieties on chromosomes 2A, 3A, 3B, 4A, 4D, 5A, 5B, 5D, 6D, 7A, 7B, and 7D. The number of MTAs in the subpanel was increased to 161 MTAs whereas the most significant and consistent associations were located on chromosomes 3B (723,504,241–723,611,488 bp) and 5A (462,763,758–466,582,184 bp) having major effects. These genomic regions include newly identified putative candidate genes, which are related to Zn uptake and transport or represent bZIP and mitogen-activated protein kinase genes. These findings provide the basis for understanding the genetic background of Zn concentration in wheat grains that in turn may help breeders to select high Zn-containing genotypes to improve human health and grain quality.

Identification of Novel Genomic Regions and Superior Alleles Associated with Zn Accumulation in Wheat Using a Genome-Wide Association Analysis Method

“…In the present study, after comparing both the GLM, MLM, and FarmCPU models, MLM appeared to be the best choice to perform a GWAS analysis on Zn grain accumulation. These results were in accordance with previous GWAS studies for Zn grain accumulation in wheat [29,30], where the association analysis was performed using the mixed linear model. Slight differences were observed among the Zn concentrations in the grains of the association population planted in different locations, which may be attributed to varying environmental conditions of different locations ( Figure 1A).…”

“…Specifically, in the study conducted by Velu et al [29] were identified major effect QTL on the 2 and 7 group chromosomes using a population of 330 spring common wheat varieties. In the study conducted by Alomari et al [30], markers associated with greater Zn accumulation were identified across the majority of the chromosomes but were concentrated on chromosomes 3B and 5A.…”

Whole-Genome Association Mapping and Genomic Prediction for Iron Concentration in Wheat Grains

“…The QQ plots for SNP results revealed that the distribution of observed association p -values were close to the distribution of expected associations (Figure 4B and Figure 5B); that means the model which we implemented for GWAS was sufficiently stringent to control for false positive associations. In a previous study a total of 8 markers in the whole panel and 31 markers in the subpanel (Tables S3 and S4) had been found significant for grain Zn concentration in the same germplasm [9]. Based on BLUEs, significant markers from the whole and subpanel were selected for a query against IWGSC RefSeq annotation v1.0 to get their annotations.…”

“…A population comprised of 369 elite European wheat varieties including 355 genotypes of winter wheat and 14 genotypes of spring wheat, mainly from Germany and France was used in this study. Field experiments were carried out at IPK, Gatersleben, Germany over three consecutive years (2014/2015, 2015/2016 and 2016/2017) using plot with a size of 2 × 2 m for each genotype with six rows spaced 0.20 m apart and more details were described in a previous study by Alomari et al [9]. The grains were collected randomly from more than 250 plants of each plot to be used in the study.…”

“…Understanding the genetic basis of Fe concentration in wheat grains is imperative for enhancing Fe values in newly developed varieties. Therefore, we performed a genome-wide association study (GWAS) approach which is one of the main approaches for dissecting complex traits including nutritional quality traits that are controlled by many genes and influenced by the environment [8,9]. Several genetic regions controlling mineral concentration traits in wheat have been identified by applying traditional quantitative trait loci (QTL) analysis using bi-parental mapping populations.…”