High-density linkage map construction and QTL analyses for fiber quality, yield and morphological traits using CottonSNP63K array in upland cotton (Gossypium hirsutum L.)

Abstract

BackgroundImproving fiber quality and yield are the primary research objectives in cotton breeding for enhancing the economic viability and sustainability of Upland cotton production. Identifying the quantitative trait loci (QTL) for fiber quality and yield traits using the high-density SNP-based genetic maps allows for bridging genomics with cotton breeding through marker assisted and genomic selection. In this study, a recombinant inbred line (RIL) population, derived from cross between two parental accessions, which represent broad allele diversity in Upland cotton, was used to construct high-density SNP-based linkage maps and to map the QTLs controlling important cotton traits.ResultsMolecular genetic mapping using RIL population produced a genetic map of 3129 SNPs, mapped at a density of 1.41 cM. Genetic maps of the individual chromosomes showed good collinearity with the sequence based physical map. A total of 106 QTLs were identified which included 59 QTLs for six fiber quality traits, 38 QTLs for four yield traits and 9 QTLs for two morphological traits. Sub-genome wide, 57 QTLs were mapped in A sub-genome and 49 were mapped in D sub-genome. More than 75% of the QTLs with favorable alleles were contributed by the parental accession NC05AZ06. Forty-six mapped QTLs each explained more than 10% of the phenotypic variation. Further, we identified 21 QTL clusters where 12 QTL clusters were mapped in the A sub-genome and 9 were mapped in the D sub-genome. Candidate gene analyses of the 11 stable QTL harboring genomic regions identified 19 putative genes which had functional role in cotton fiber development.ConclusionWe constructed a high-density genetic map of SNPs in Upland cotton. Collinearity between genetic and physical maps indicated no major structural changes in the genetic mapping populations. Most traits showed high broad-sense heritability. One hundred and six QTLs were identified for the fiber quality, yield and morphological traits. Majority of the QTLs with favorable alleles were contributed by improved parental accession. More than 70% of the mapped QTLs shared the similar map position with previously reported QTLs which suggest the genetic relatedness of Upland cotton germplasm. Identification of QTL clusters could explain the correlation among some fiber quality traits in cotton. Stable and major QTLs and QTL clusters of traits identified in the current study could be the targets for map-based cloning and marker assisted selection (MAS) in cotton breeding. The genomic region on D12 containing the major stable QTLs for micronaire, fiber strength and lint percentage could be potential targets for MAS and gene cloning of fiber quality traits in cotton.

Genome-Wide Association Analysis Reveals Loci and Candidate Genes Involved in Fiber Quality Traits Under Multiple Field Environments in Cotton (Gossypium hirsutum)

“…In the current study, we observed large phenotypic variations for FL, FS, and Mic in natural populations of 242 genotypes for multiple years. Compared to yield and components (Su et al, 2016 ; Nie et al, 2020 ), fiber quality traits had a higher heritability of more than 80%, consistent with previous reports (Zhang et al, 2019 ; Liu et al, 2020 ). Correlation analysis showed that each trait had high correlations in different environments, indicating the genetic stability of fiber quality traits.…”

QTL mapping for plant height and fruit branch number based on RIL population of upland cotton

“…In the current study, QTL mapping for agronomic traits is based on a high-density genetic map that covers a total genetic distance of 2 477.99 cM, composing 4 729 SNP markers and 122 SSR markers. Comparing the results of this study with previous common QTLs summarized with meta-analysis (Said et al 2013), and QTLs identified in recent years (Jia et al 2016;Su et al 2018;Zhang et al 2019a;Zhang et al 2019b;Ma et al 2019a), QTLs on c04 for PH and those on c01, c07, c12, c20-c21, c24, and c26 for FBN were all newly identified ones. As the existence of significant G × E interactions, QTLs identified in every environment moved around.…”

Prospects for Molecular Breeding in Cotton,Gossypiumspp

“…The Quantitative Trait Loci identification helps in finding the association between a marker and measurable phenotype at the genomic level or understanding the genetics of traits under study. Various types of populations like F2 [104], Recombinant inbred lines (RILs) [105], Backcross inbred lines (BILs) [106] and Multi-parent Advanced Generation Inter Cross (MAGIC) [107] are commonly used in cotton. Bi-parental RIL Mapping is one of the most common methodologies successfully employed for identifying QTLs in cotton for various traits.…”

“…This technique allows detecting association among various markers and traits through assessing Linkage disequilibrium (LD-mapping). In cotton the construction of linkage maps and detection of QTLs for various economic traits has been in progress since 1994 with the first RFLP linkage map [84] being published after which many maps have been constructed [94,96,97,105,108]. Many genome-wide association studies have also been carried out [95,107,109].…”