High‐density linkage map construction and QTL analysis of fiber quality and lint percentage in tetraploid cotton

Abstract

Improving fiber quality and yield are major research objectives for cotton breeders in the United States. Identifying broadly existing and stable quantitative trait loci (QTLs) related to fiber quality is critical to properly utilizing genomic resources in cotton improvement programs. An F6 recombinant inbred line (RIL) population derived from the cross of NC05AZ21 × TX‐2324 was used to develop linkage maps and for QTL analysis of six fiber quality traits and lint percentage. The Illumina 63K single nucleotide polymorphism (SNP) array was used to genotype the RIL population. Analysis of variance of phenotypic trait data showed significant differences among lines and years for all traits tested. The heritability for tested traits ranged from 0.56 to 0.91. Genetic mapping was performed using 3,009 polymorphic SNP markers on the RILs. We constructed a genetic map with a total length of 4,983.73 cM and an average distance of 1.66 cM between markers. The linkage map corresponded well with the Upland cotton (Gossypium hirsutum L.) sequence‐based physical map. Thirty‐two QTLs with additive effects for lint percentage and fiber quality traits were identified on 15 chromosomes, explaining 7.9–22.2% of the phenotypic variance. The majority of these QTLs were mapped in the D subgenome, indicating that functional mutations in the D subgenome are responsible for the major fiber quality improvements in Upland cotton. Furthermore, five QTL clusters were located on four chromosomes (Chr.05, Chr.18, Chr.19, and Chr.26), which may explain the strong correlation between fiber quality traits measured. The QTLs identified in the current study could be targeted for marker‐assisted selection and map‐based cloning of fiber quality traits in Upland cotton.

Identification of quantitative trait loci for fiber quality, yield, and plant height traits in Upland cotton

“…QTL validation resulted in 12 QTL that shared the same genomic location (genetic distance window of 10–20 cM) with previously reported QTL (Jung et al., 2021; Zhang et al., 2019; Zhu et al., 2021), including 10 QTL in D subgenome and 2 in A subgenome. These 12 shared QTL included four QTL for MIC, one for UHML, three for FU, one for FS, two for FEL, and one for SFC (Table 4).…”

“…At present, two SNP arrays are available in cotton, a 63K SNP array and an 80K SNP array (Cai et al., 2017; Hulse‐Kemp et al., 2015b). These SNP arrays have been used to assess genetic diversity (Billings et al., 2021), perform genome‐wide association studies (GWAS) (Cai et al., 2017; Gowda et al., 2022; Song et al., 2021; Sun et al., 2017), construct genetic maps (Hulse‐Kemp et al., 2015b; Zhang et al., 2019; Zhu et al., 2021), and detect QTL for fiber quality traits, yield traits, and morphological traits (Li et al., 2016; Zhang et al., 2019; Zhu et al., 2021). However, only a few studies have reported their use in identifying novel and stable QTL and develop functional markers for fiber quality traits, yield traits, and plant height in intraspecific Upland cotton populations.…”

Identification and genomic characterization of major effect bacterial blight resistance locus (BB-13) in Upland cotton (Gossypium hirsutum L.)

“…Out of 63,058 SNP markers, 40,649 markers had speci c chromosomal positions. Further, grouping data from four Upland cotton linkage maps (Zhang et al 2019;Zhu et al 2021) were used to assign the 1,983 SNP markers that had a homoeologous location on A and D sub genomes to speci c chromosomes. Raw genotypic data of 380 G. hirsutum accessions having 42,518 SNP markers were ltered to remove poor quality SNPs using the following criteria, a) monomorphic markers in the panel were removed; b) minor allele frequency was set to 0.05; c) SNP markers having more than 30% missing data were removed, and d) SNPs markers having more than 30% heterozygosity were removed.…”

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

“…The use of MAS to pyramid several QTLs that affect numerous desired target characteristics enhanced the selection efficiency among breeding populations with varied genetic origins. Recent studies ( Abdelraheem et al, 2021 ; Guo et al, 2021 ; Wang H. et al, 2021 ; Wang N. et al, 2021 ; Zhu et al, 2021 ) demonstrated the necessity of dissecting complicated fiber traits using QTL mapping and the potential of MAS in the cotton breeding program.…”