Dissection of complicate genetic architecture and breeding perspective of cottonseed traits by genome-wide association study

Abstract

BackgroundCottonseed is one of the most important raw materials for plant protein, oil and alternative biofuel for diesel engines. Understanding the complex genetic basis of cottonseed traits is requisite for achieving efficient genetic improvement of the traits. However, it is not yet clear about their genetic architecture in genomic level. GWAS has been an effective way to explore genetic basis of quantitative traits in human and many crops. This study aims to dissect genetic mechanism seven cottonseed traits by a GWAS for genetic improvement.ResultsA genome-wide association study (GWAS) based on a full gene model with gene effects as fixed and gene-environment interaction as random, was conducted for protein, oil and 5 fatty acids using 316 accessions and ~ 390 K SNPs. Totally, 124 significant quantitative trait SNPs (QTSs), consisting of 16, 21, 87 for protein, oil and fatty acids (palmitic, linoleic, oleic, myristic, stearic), respectively, were identified and the broad-sense heritability was estimated from 71.62 to 93.43%; no QTS-environment interaction was detected for the protein, the palmitic and the oleic contents; the protein content was predominantly controlled by epistatic effects accounting for 65.18% of the total variation, but the oil content and the fatty acids except the palmitic were mainly determined by gene main effects and no epistasis was detected for the myristic and the stearic. Prediction of superior pure line and hybrid revealed the potential of the QTSs in the improvement of cottonseed traits, and the hybrid could achieve higher or lower genetic values compared with pure lines.ConclusionsThis study revealed complex genetic architecture of seven cottonseed traits at whole genome-wide by mixed linear model approach; the identified genetic variants and estimated genetic component effects of gene, gene-gene and gene-environment interaction provide cotton geneticist or breeders new knowledge on the genetic mechanism of the traits and the potential molecular breeding design strategy.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4837-0) contains supplementary material, which is available to authorized users.

Genome-Wide Association Study Identifies Candidate Genes Related to Seed Oil Composition and Protein Content in Gossypium hirsutum L.

“…For cottonseed oil and protein content, both additive and non-additive (including dominance) effects have been reported (Kohel, 1980 ; Dani and Kohel, 1989 ; Wu et al, 2009 , 2010 ). Recently, significant epistatic effects on the oil and protein content were also detected in the study of Du et al ( 2018 ). They also detected a significant interaction effect between epistasis and environment only for the oil content.…”

“…Stability of QTLs/markers across populations, environments, and genetic backgrounds is essential for MAS in breeding practices. GWAS is an efficient method to identify QTLs and dissect the genetic control of complex quantitative traits (Saeed et al, 2014 ; Islam et al, 2016 ; Cai et al, 2017 ; Huang et al, 2017a ; Du et al, 2018 ). Compared to the agronomic and quality traits of cotton, very few reports in linkage mapping (Song and Zhang, 2007 ; Yu et al, 2012 ; Liu et al, 2015a ), even less in GWAS (Badigannavar and Myers, 2015 ; Liu et al, 2015b ) have been previously reported.…”

Evolutionary and ecological functional genomics, from lab to the wild

“…At present, GWAS are collectively being mobilized to provide population‐based validation for the genotype–phenotype associations of previously identified genes via candidate gene approaches (Todesco et al ., ), and for newly discovered, relevant genes (Nemri et al ., ; Slavov et al ., ; Diepenbrock et al ., ; Hazzouri et al ., ; Rajarammohan et al ., ). Most importantly, population re‐sequencing coupled with QTL or GWAS on traits of interest is being actively adopted in studies on trait plasticity and adaptation in natural environments (Brachi et al ., ; Dell'Acqua et al ., ; van Heerwaarden et al ., ; Lasky et al ., ; Anderson et al ., ; Kerdaffrec et al ., ; Meyer et al ., ; Brunazzi et al ., ; Du et al ., ). GWAS approaches are currently being developed to assess the genetic basis for plant interactions with other members of the species community as well.…”

Genome-Wide Association Study of Micronaire Using a Natural Population of Representative Upland Cotton (Gossypium Hirsutum L.)

“…Through comparison, it was found that eight of the 11 stable QTLs for FM were reported in previous studies and that 3 QTLs were newly detected in this study (Table 2). In this study, we used the method of combining the functional annotation of genes in stable QTLs with the analysis of Arabidopsis homologous genes and the cotton ber transcriptome database to mine candidate genes related to FM (Du et al 2018). The 11 QTLs contained a total of 1,594 genes, which were compared to the upland cotton genome from Zhejiang University using local BLAST (http://ibi.zju.edu.cn/cotton).…”