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Genome-wide association mapping of root system architecture traits in common wheat (Triticum aestivum L.)

Author:
Liu, Peng, Jin, Yirong, Liu, Jindong, Liu, Caiyun, Yao, Hongping, Luo, Fuyi, Guo, Zhihui, Xia, Xianchun, He, Zhonghu
Source:
Euphytica 2019 v.215 no.7 pp. 121
ISSN:
0014-2336
Subject:
Triticum aestivum, alleles, calcium, chromosome mapping, cultivars, genome-wide association study, genotyping, hydroponics, ligases, linear models, loci, phenotype, plant breeding, protein kinases, quantitative trait loci, quantitative traits, regression analysis, river valleys, root systems, root tips, seedlings, single nucleotide polymorphism arrays, wheat, China
Abstract:
Uncovering the genetic basis and optimization of root system architecture (RSA) traits are crucial for modern wheat breeding. Genome-wide association mapping has become a powerful approach to dissect the genetic architecture of complex quantitative traits. In the present study, RSA traits, viz. total root length (TRL), total root area, average root diameter and number of root tips in a diverse panel of 165 elite wheat cultivars from the Yellow and Huai River Valley Facultative Wheat Region of China were evaluated as seedlings in hydroponic culture and in the field to identify loci significantly associated with those traits. The diverse panel was genotyped using the wheat 90 K and 660 K SNP arrays, and a genome-wide association study using a mixed linear model identified 28 and 4 loci significantly associated with RSA traits in hydroponic culture and in the field, explaining 8.8–15.6% and 8.9–12.6% of phenotypic variances, respectively. Seven loci for RSA traits co-located with known genes or quantitative trait loci (QTL), whereas the other 22 were potentially new. Linear regression between favorable alleles and RSA traits suggested that QTL pyramiding should be effective in optimizing root systems. Two candidate genes for RSA traits were identified, including genes encoding calcium dependent protein kinase and E3-Ubiquitin protein ligase. This study provides novel insights into the genetic architecture of RSA traits.
Agid:
6473199