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Summary Cotton is widely cultivated globally because it provides natural fibre for the textile industry and human use. To identify quantitative trait loci (QTLs)/genes associated with fibre quality and yield, a recombinant inbred line (RIL) population was developed in upland cotton. A consensus map covering the whole genome was constructed with three types of markers (8295 markers, 5197.17 centimorgans (cM)). Six fibre yield and quality traits were evaluated in 17 environments, and 983 QTLs were identified, 198 of which were stable and mainly distributed on chromosomes 4, 6, 7, 13, 21 and 25. Thirty‐seven QTL clusters were identified, in which 92.8% of paired traits with significant medium or high positive correlations had the same QTL additive effect directions, and all of the paired traits with significant medium or high negative correlations had opposite additive effect directions. In total, 1297 genes were discovered in the QTL clusters, 414 of which were expressed in two RNA‐Seq data sets. Many genes were discovered, 23 of which were promising candidates. Six important QTL clusters that included both fibre quality and yield traits were identified with opposite additive effect directions, and those on chromosome 13 (qClu‐chr13‐2) could increase fibre quality but reduce yield; this result was validated in a natural population using three markers. These data could provide information about the genetic basis of cotton fibre quality and yield and help cotton breeders to improve fibre quality and yield simultaneously.

Summary Fine mapping QTLs and identifying candidate genes for cotton fibre‐quality and yield traits would be beneficial to cotton breeding. Here, we constructed a high‐density genetic map by specific‐locus amplified fragment sequencing (SLAF‐seq) to identify QTLs associated with fibre‐quality and yield traits using 239 recombinant inbred lines (RILs), which was developed from LMY22 (a high‐yield Gossypium hirsutumL. cultivar) × LY343 (a superior fibre‐quality germplasm with G. barbadenseL. introgressions). The genetic map spanned 3426.57 cM, including 3556 SLAF‐based SNPs and 199 SSR marker loci. A total of 104 QTLs, including 67 QTLs for fibre quality and 37 QTLs for yield traits, were identified with phenotypic data collected from 7 environments. Among these, 66 QTLs were co‐located in 19 QTL clusters on 12 chromosomes, and 24 QTLs were detected in three or more environments and determined to be stable. We also investigated the genomic components of LY343 and their contributions to fibre‐related traits by deep sequencing the whole genome of LY343, and we found that genomic components from G. hirsutum races (which entered LY343 via its G. barbadense parent) contributed more favourable alleles than those from G. barbadense. We further identified six putative candidate genes for stable QTLs, including Gh_A03G1147 (GhPEL6), Gh_D07G1598 (GhCSLC6) and Gh_D13G1921 (GhTBL5) for fibre‐length QTLs and Gh_D03G0919 (GhCOBL4), Gh_D09G1659 (GhMYB4) and Gh_D09G1690 (GhMYB85) for lint‐percentage QTLs. Our results provide comprehensive insight into the genetic basis of the formation of fibre‐related traits and would be helpful for cloning fibre‐development‐related genes as well as for marker‐assisted genetic improvement in cotton.

Summary Brown fibre cotton is an environmental‐friendly resource that plays a key role in the textile industry. However, the fibre quality and yield of natural brown cotton are poor, and fundamental research on brown cotton is relatively scarce. To understand the genetic basis of brown fibre cotton, we constructed linkage and association populations to systematically examine brown fibre accessions. We fine‐mapped the brown fibre region, Lc1, and dissected it into 2 loci, qBF‐A07‐1 and qBF‐A07‐2. The qBF‐A07‐1 locus mediates the initiation of brown fibre production, whereas the shade of the brown fibre is affected by the interaction between qBF‐A07‐1 and qBF‐A07‐2. Gh_A07G2341 and Gh_A07G0100 were identified as candidate genes for qBF‐A07‐1 and qBF‐A07‐2, respectively. Haploid analysis of the signals significantly associated with these two loci showed that most tetraploid modern brown cotton accessions exhibit the introgression signature of Gossypium barbadense. We identified 10 quantitative trait loci (QTLs) for fibre yield and 19 QTLs for fibre quality through a genome‐wide association study (GWAS) and found that qBF‐A07‐2 negatively affects fibre yield and quality through an epistatic interaction with qBF‐A07‐1. This study sheds light on the genetics of fibre colour and lint‐related traits in brown fibre cotton, which will guide the elite cultivars breeding of brown fibre cotton.

Variation in cotton fiber length impacts processability at the mill and the quality of spun yarns. The High Volume Instrument (HVI) and Advanced Fiber Information System (AFIS) are cotton fiber quality assessment instruments able to quickly assess a myriad of fiber quality characteristics. HVI testing provides the fiber length parameters most widely utilized by the cotton industry, Upper Half Mean Length and Uniformity Index. However, HVI fiber length parameters do not account for the complete within-sample variation in fiber length, such as the shortest fibers in the sample. AFIS testing is able to characterize the complete within-sample distribution of fiber length within a sample of cotton by evaluating individual fibers. Within-sample variation in fiber length is an important cotton fiber quality concern because it impacts processing performance and yarn quality. In this paper, the fiber length for 9127 commercial cotton bales was evaluated on both HVI and AFIS. The AFIS length distributions are used to characterize the complete distribution of fiber length within each bale. A novel statistical technique is introduced and is used to characterize a set of multivariate axes that characterize the total within-bale variation in fiber length among the complete set of commercial bales. These results suggest that less than half of the variation in cotton fiber length captured by the AFIS length distributions is captured by the two length parameters provided by HVI testing. If an experimental factor has no significant impact on an HVI fiber quality parameter, an alternative cotton fiber length measurement such as the AFIS length distribution should be considered.

The study assessed the quality and variability of camel hair fibres in arid regions of Egypt. Raw camel-hair samples were collected from fifteen Sudanese camels divided into seven males (414.60 ± 38.19 kg, BW) and eight females (401.67 ± 26.76 kg BW), and the study investigated the influences of animal sex on both the physical and chemical traits of camel-hair fibers. The relationships among physical properties and both mineral and amino acid content were studied. Camel’s sex had no significant effect on any of the studied traits including fibre diameter (FD), prickle factor (PF), medullated fibre (MF), staple length (SL) and staple strength (SS). In the meantime, no significant differences were found between males and females in fibers’ minerals contents except potassium, where fibres of females had significantly higher potassium content than those of males. For amino acids contents in camel fibres, camel sex had a significant effect only on glutamic acid, since fibres of males showed higher ( P  < 0.05) content than females. Fibre diameter had positive ( P  < 0.01) correlations with prickle factor ( r  = 0.83) and medullated fibres ( r  = 0.73). Zinc content in camel fibres was positively correlated with fibre diameter ( r  = 0.57; P  < 0.05) and medullated fibres ( r  = 0.73; P  < 0.01). Moreover, a significant (negative correlation coefficient P  < 0.05) was found between fibre diameter and both sulfur and proline contents ( r =-0.39 and − 0.56). Ammonia content in fibres was correlated negatively ( P  < 0.05) with prickle factor and elongation ( r =-0.62 and − 0.58, respectively). The variability in the physical properties and chemical composition of Sudanese camel-hair fibers under subtropical desert conditions may shed light on the possibility of improving fiber quality.

Cotton is the most important fiber crop in the world. Asiatic cotton (Gossypium arboreum, genome A2) is a diploid cotton species producing spinnable fibers and important germplasm for cotton breeding and a significant model for fiber biology. However, the genetic map of Asiatic cotton has been lagging behind tetraploid cottons, as well as other stable crops. This study aimed to construct a high-density SNP genetic map and to map QTLs for important yield and fiber quality traits. Using a recombinant inbred line (RIL) population and genome resequencing technology, we constructed a high-density genetic map that covered 1980.17 cM with an average distance of 0.61 cM between adjacent markers. QTL analysis revealed a total of 297 QTLs for 13 yield and fiber quality traits in three environments, explaining 5.0–37.4% of the phenotypic variance, among which 75 were stably detected in two or three environments. Besides, 47 QTL clusters, comprising 131 QTLs for representative traits, were identified. Our works laid solid foundation for fine mapping and cloning of QTL for yield and fiber quality traits in Asiatic cotton.

The genetic base in Upland cotton (Gossypium hirsutum L.) is narrow. Repeated random mating through generations during germplasm development may be an appealing approach to introgress desirable genes from exotic germplasm into Upland cotton. A random mating population, MDRM, was developed to provide a source of germplasm with introgression of novel alleles from other tetraploid species. This population was derived from 48 crosses between four Upland cotton lines/cultivars (MD15, MD52ne, and TAM98D-99ne and FiberMax832) as female parents and twelve exotic germplasm lines as male parents. The male parents include six lines derived from multiple crosses between G. hirsutum and G. barbadense L. and another six lines derived from multiple crosses among five Gossypium tetraploid species. After five generations of random mating followed by six generations of self-pollination, the bulk of RM5F7 population was produced, which further led to the development of recombinant inbred lines (RILs) from seed increase of single plants in the bulk. The bulk of RM5F7 and its 276 RILs were evaluated along with 134 RM0F7 RILs (0 generation of random mating) and 142 RM1F7 RILs (1 generation of random mating) and the parents at College Station, TX, Las Cruces, NM, and Stoneville, MS from 2016 to 2022. The bulk of RM5F7 has superior fiber quality with acceptable yield as compared with parents. Transgressive segregation was observed in RM5F7 RILs for both lint yield and fiber quality. Unfavorable associations between yield and fiber properties of length, strength, and uniformity in RM5F7 were reduced compared with RM0F7 or RM1F7. Therefore, MDRM provides a new breeding stock for cotton breeders to develop germplasm lines with desirable combinations between lint yield and fiber quality and unique combinations of alleles from exotic parents.

Cotton fiber quality traits are controlled by multiple genes of minor effect. Identification of significant and stable quantitative trait loci (QTL) across environments and populations lays foundation for marker-assisted selection for fiber quality improvement and studies of its molecular regulation. Here, a detailed genetic map is constructed and QTL are detected based on an intraspecific recombinant inbred line population derived from a cross between Upland cotton cultivar/line Yumian 1 and 7235. A total of 25,313 SSR primer pairs, including 5,000 developed from G. raimondii BAC-ends sequences, were used to construct the genetic map which finally contained 1,540 loci, spanning 2,842.06 cM, with an average of 1.85 cM between adjacent markers. With 4 year fiber quality traits data, variance analysis revealed that they were significantly affected by genetic and environmental factors. Significant correlations were also detected between them. A total of 62 QTL were identified with combined analysis and single environment analysis. These QTL explain phenotypic variation from 5.0 to 28.1 %. For each trait, favorable alleles were conferred by both parents. Seventeen QTL were detected in more than one environment. The genetic map and stable QTL are valuable for Upland cotton genome research and breeding projects to improve fiber quality.

Summary Sea Island cotton (Gossypium barbadense) is the source of the world’s finest fibre quality cotton, yet relatively little is understood about genetic variations among diverse germplasms, genes underlying important traits and the effects of pedigree selection. Here, we resequenced 336 G. barbadense accessions and identified 16 million SNPs. Phylogenetic and population structure analyses revealed two major gene pools and a third admixed subgroup derived from geographical dissemination and interbreeding. We conducted a genome‐wide association study (GWAS) of 15 traits including fibre quality, yield, disease resistance, maturity and plant architecture. The highest number of associated loci was for fibre quality, followed by disease resistance and yield. Using gene expression analyses and VIGS transgenic experiments, we confirmed the roles of five candidate genes regulating four key traits, that is disease resistance, fibre length, fibre strength and lint percentage. Geographical and temporal considerations demonstrated selection for the superior fibre quality (fibre length and fibre strength), and high lint percentage in improving G. barbadense in China. Pedigree selection breeding increased Fusarium wilt disease resistance and separately improved fibre quality and yield. Our work provides a foundation for understanding genomic variation and selective breeding of Sea Island cotton.

Cotton is a valuable fiber crop which supplies raw material to more than 50 industries and is produced in more than 70 countries worldwide. The superiority of cotton fiber over other crops is primarily dependent on its quality. However, further improvements in fiber length and strength are required for modern processing technology and for cotton to maintain its position in the global market. Association mapping enables identification of QTLs controlling fiber quality-related traits which can be useful in cotton breeding. In the present study, we performed genetic diversity, linkage disequilibrium and association mapping analyses in 157 G. hirsutum multi-parent recombinant inbred lines using a total of 102 SSR markers. The population had depressed genetic variability (14%), a result of inbreeding of modern cotton genotypes. Despite this, we identified 11 significant and stable marker-trait associations for seed cotton yield, lint percentage, fiber length and fiber strength (p < 0.005). We also detected QTL co-localizations with positive and negative marker additive effects. Our results indicate that selection against negative alleles may be as important as selection for positive alleles. Analysis of the effects of allelic combinations at different QTLs revealed significant and stable marker clusters that can be selected for or against to provide maximum quality gains in cotton fiber quality.