Detection of Favorable QTL Alleles and Candidate Genes for Lint Percentage by GWAS in Chinese Upland Cotton.

Junji Su,Chi Zhang,Chaoyou Pang,Libei Li,Chengshe Wang,Hantao Wang,Shuqi Zhao,Guangzhi Mao,Hengling Wei,Meizhen Song,Lijiao Gu,Shuxun Yu,Shuli Fan,Caixiang Wang

doi:10.3389/fpls.2016.01576

Junji Su, Chi Zhang + Show 12 more

Open Access

https://doi.org/10.3389/fpls.2016.01576

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Abstract

Improving cotton yield is a major breeding goal for Chinese upland cotton. Lint percentage is an important yield component and a critical economic index for cotton cultivars, and raising the lint percentage has a close relationship to improving cotton lint yield. To investigate the genetic architecture of lint percentage, a diversity panel consisting of 355 upland cotton accessions was grown, and the lint percentage was measured in four different environments. Genotyping was performed with specific-locus amplified fragment sequencing (SLAF-seq). Twelve single-nucleotide polymorphisms (SNPs) associated with lint percentage were detected via a genome-wide association study (GWAS), in which five SNP loci distributed on chromosomes At3 (A02) and At4 (A08) and contained two major-effect QTLs, which were detected in the best linear unbiased predictions (BLUPs) and in more than three environments simultaneously. Furthermore, favorable haplotypes (FHs) of two major-effect QTLs and 47 putative candidate genes in the two linkage disequilibrium (LD) blocks of these associated loci were identified. The expression levels of these putative candidate genes were estimated using RNA-seq data from ten upland cotton tissues. We found that Gh_A02G1268 was very highly expressed during the early fiber development stage, whereas the gene was poorly expressed in the seed. These results implied that Gh_A02G1268 may determine the lint percentage by regulating seed and fiber development. The favorable QTL alleles and candidate genes for lint percentage identified in this study will have high potential for improving lint yield in future Chinese cotton breeding programs.

Highlights

IntroductionQuantitative trait locus (QTL) mapping has been widely used to dissect the genetic changes for cotton complex traits, such as fiber quality and yield component traits (Rong et al, 2007; Said et al, 2013, 2015)
Upland cotton (Gossypium hirsutum L.; AADD, 2n = 4x = 52) is the most important natural textile fiber source worldwide, accounting for approximately 95% of the world’s cotton production (Chen et al, 2007)
genome-wide association study (GWAS) have been widely performed for a large number of single-nucleotide polymorphisms (SNPs) in Arabidopsis (Zhao et al, 2007; Atwell et al, 2010), maize (Kump et al, 2011) and rice (Huang et al, 2010; Zhao et al, 2011), they have seldom been used for large quantities of SNPs in cotton

Summary

Introduction

Quantitative trait locus (QTL) mapping has been widely used to dissect the genetic changes for cotton complex traits, such as fiber quality and yield component traits (Rong et al, 2007; Said et al, 2013, 2015). Association mapping as an alternative for detecting QTLs has been used widely in QTL mapping for important economic traits in cotton, such as fiber quality traits (Abdurakhmonov et al, 2008; Zhang et al, 2013; Nie et al, 2016), yield and its components (Mei et al, 2013; Qin et al, 2015), and resistance traits (Zhao et al, 2014). GWASs have been widely performed for a large number of single-nucleotide polymorphisms (SNPs) in Arabidopsis (Zhao et al, 2007; Atwell et al, 2010), maize (Kump et al, 2011) and rice (Huang et al, 2010; Zhao et al, 2011), they have seldom been used for large quantities of SNPs in cotton

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