Identification of candidate genes controlling fiber quality traits in upland cotton through integration of meta-QTL, significant SNP and transcriptomic data

Abstract

Background Meta-analysis of quantitative trait locus (QTL) is a computational technique to identify consensus QTL and refine QTL positions on the consensus map from multiple mapping studies. The combination of meta-QTL intervals, significant SNPs and transcriptome analysis has been widely used to identify candidate genes in various plants. Results In our study, 884 QTLs associated with cotton fiber quality traits from 12 studies were used for meta-QTL analysis based on reference genome TM-1, as a result, 74 meta-QTLs were identified, including 19 meta-QTLs for fiber length; 18 meta-QTLs for fiber strength; 11 meta-QTLs for fiber uniformity; 11 meta-QTLs for fiber elongation; and 15 meta-QTLs for micronaire. Combined with 8 589 significant single nucleotide polymorphisms associated with fiber quality traits collected from 15 studies, 297 candidate genes were identified in the meta-QTL intervals, 20 of which showed high expression levels specifically in the developing fibers. According to the function annotations, some of the 20 key candidate genes are associated with the fiber development. Conclusions This study provides not only stable QTLs used for marker-assisted selection, but also candidate genes to uncover the molecular mechanisms for cotton fiber development.

Identification of Stable and Multiple Environment Interaction QTLs and Candidate Genes for Fiber Productive Traits Under Irrigated and Water Stress Conditions Using Intraspecific RILs of Gossypium hirsutum var. MCU5 X TCH1218

“…Large array of candidate genes were identified within the QTL reported in this study ( Supplementary Table 2 ), and they were compared and annotated with Xu et al (2020) , where meta-QTL analysis along with transcriptomic approach utilized for the identification of candidate genes related to fiber quality in upland cotton. Though there were genes specific to abiotic stress responses and productive traits, large numbers of genes identified in this study warrant the use of additional markers to fine map these QTL and identify precise genes involved for the target traits.…”

Analysis of the MIR396 gene family and the role of MIR396b in regulating fiber length in cotton

“…In our present study, we analyzed the chromosome location of MIR396 gene family and found eight genes were colocalized with seven meta‐QTLs related to fiber quality (one meta‐QTLs for FS, two meta‐QTLs for MIC, and four meta‐QTLs for FL) (Figure 2A). Among which, GhmiR396b_D13 was colocalized with the meta‐QTLs for FL and expressed differently between Long and Short fibers (Figure 2B) (Ali et al, 2018; Jia et al, 2018; Ma et al, 2018; Xu et al, 2020). This result suggests that GhmiR396b_D13 has a critical role in the development of FL.…”

Quantitative Trait Locus Analysis and Identification of Candidate Genes for Micronaire in an Interspecific Backcross Inbred Line Population of Gossypium hirsutum × Gossypium barbadense

“…To identify new QTLs in this study, QTLs from our results were compared with previously reported QTLs. Previous MIC QTLs were retrieved from CottonGen ( Yu et al, 2014 ) and Cotton QTLdb Release 2.3 (January 24, 2018, see text footnote 1) ( Said J. et al, 2015 ) and from recent reports by Majeed et al (2019) and Xu et al (2020) . In addition, MIC QTL data from previous GWAS reports were also obtained.…”

“…Through a meta-analysis of numerous QTL reports, Said J. et al (2015) compiled a total of 395 QTLs related to MIC in a QTL database for cotton. 1 Xu et al (2020) recently performed a meta-analysis and identified a total of 15 meta-QTLs for MIC. These studies provide references for locations of QTLs for MIC.…”