Fiber Quality Traits In Cotton Research Articles

Insights into genetic diversity and functional significance of the bHLH genes in cotton fiber development

This study investigated the identification and distribution of single nucleotide polymorphisms (SNPs) within basic Helix-Loop-Helix (bHLH) transcription factors (TFs) across diverse cotton (Gossypium hirsutum) accessions, including wild, landrace, and improved varieties. Comprehensive genomic analyses revealed substantial SNP diversity in wild cotton, distinct from that observed in landraces and improved accessions. Comparative analysis showed notable variations in SNP abundance and impact levels across different accessions, with missense SNPs being prevalent. Nucleotide substitution patterns highlighted the dominance of G>A and A>G substitutions. Population genetic analyses unveiled significant genetic diversity within wild accessions and distinct clustering between wild and improved accessions. Temporal expression profiling of bHLH genes during cotton fiber development demonstrated dynamic expression patterns, emphasizing their roles in fiber initiation, elongation, and cellulose biosynthesis. Moreover, association analysis identified SNPs significantly associated within bHLH genes, particularly GhbHLH149, with fiber quality traits, indicating their potential functional significance. Population genetic analyses further revealed evidence of positive selection on GhbHLH149 during cotton improvement. This study provides a comprehensive understanding of SNP diversity, gene expression dynamics, and genetic selection in bHLH genes, offering valuable insights for future cotton breeding efforts aimed at improving fiber quality traits in cotton.

Bridging molecular genetics and genomics for cotton fiber quality improvement

AbstractUpland cotton (Gossypium hirsutum L.) is the main source of natural fiber for the textile industry. Cotton fibers are unicellular trichomes that emerge from the epidermal cells of the seed. In cultivated cotton species, seed trichomes differentiate into two distinct types, spinnable lint, and short fuzz. The main priority for cotton growers is fiber yield, whereas the textile industry also demands better fiber quality characteristics, such as length, uniformity, strength, maturity, and optimal fineness. However, it is a major challenge for breeders to improve fiber quality while maintaining yield, because of the observed negative correlation between yield and fiber quality traits. Recent technical advances in sequencing and bioinformatics have facilitated the assembly of reference quality genomes of multiple cotton species, bringing a new era for cotton genomics. Available genomic resources will help genetically dissect the agronomic and fiber quality traits of cotton and identify gene variants that can be used for cotton improvement through breeding or biotechnology. Here, we review recent progress in the sequencing of genomes of cotton species and approaches in molecular genetics and genomics for the improvement of cotton fiber quality traits. We discuss progress in the understanding of each stage of cotton fiber development and the remaining challenges.

Interrelationships between cotton fiber quality traits and fluid handling and moisture management properties of nonwoven textiles

Cotton fibers represent a sustainable and environmentally responsible raw material for the production of nonwoven textiles which are currently dominated by synthetic fibers derived from petrochemicals. Natural variation in quality parameters such as fineness, length, and strength present a challenge for cotton fiber conversion to yarns and in weaving and knitting for conventional textiles. The grading process for cotton fibers addresses this issue by allowing converters to select fibers suitable for specific woven textile applications. However, there has been little attempt to correlate cotton fiber quality traits with nonwoven textiles performance. This study examined the relationship of cotton fiber quality and fluid handling and moisture management performance properties of nonwoven textiles for personal hygiene and disposable applications. This includes potential end-use in diapers and incontinence products as well as disposable textiles for use in clinical settings. Ten recombinant inbred lines of cotton with a broad distribution of fiber quality traits were selected from a multiparent advanced generation intercross population. Fibers were harvested, converted into nonwoven textiles, and subjected to a series of standardized testing protocols. The results indicated that inferior quality coarse cotton fibers subjected to discount market pricing can be selectively utilized for nonwoven applications that benefit from improved moisture management and fluid handling performance.

Interrelationships between cotton fiber quality traits and tensile properties of hydroentangled nonwoven fabrics

Cotton fibers can be used to produce nonwovens suitable for numerous single use applications including hygiene, wipes, and medical products among others. Cotton comprises a relatively small amount of total raw materials used in nonwovens production compared to the synthetic fibers of polyester and polypropylene, but the use of cotton fibers in nonwovens continues to increase due to demand for disposable products containing natural, sustainable, and biodegradable materials. However, the relationship between cotton fiber classification measurements and nonwoven fabric physical and functional properties are not well characterized. A better understanding of the effects of cotton fiber properties on nonwovens fabric properties will facilitate fiber selection for specific end-use applications. In this study, cotton fibers with broad distributions of fiber quality measurements from 10 recombinant inbred lines of a multi parent advanced generation intercross multiparent advanced generation intercross population were harvested and processed in their greige state into hydroentangled nonwoven fabrics of two distinct basis weights. Tensile testing of lightweight nonwovens indicated fiber length and tensile strength at break were positively correlated with fabric strength, whereas micronaire (air permeability of a fiber bundle) was negatively correlated indicating finer fibers contributed to increased fabric strength. Increased strength of heavyweight fabrics was mainly correlated with higher fiber uniformity index. These results suggest that cotton fibers could be selectively sourced based on fiber quality for specific nonwoven applications and establishes alternative market opportunities for cotton fibers classified as inferior and subject to discount pricing in the woven textile market.

Genotype selection for fiber quality traits in cotton in the Brazilian Northeast

AbstractThe search for cotton (Gossypium hirsutum L.) genotypes gathering high yield and fiber quality is the main objective of breeding programs. The objectives of this study were: (a) to verify which effects contribute the largest fraction of the total phenotypic variance of cotton fiber quality traits and (b) to recommend the best genotypes for these traits. Eight competition trials of cotton cultivars were carried out between the 2017 and 2019 seasons. Field trials were carried out in Alagoinha (crops seasons 2017, 2018, and 2019) and Barbalha (2017 and 2018) in a randomized block design with three repetitions. Fifteen genotypes developed by the cotton plant breeding program of Embrapa Algodão were evaluated. The following fiber quality traits were evaluated: fiber percentage (FP), average boll weight (BW), upper‐half mean length, fiber uniformity (UNIF), short fiber index (SFI), fiber strength (STR), elongation (ELG), micronaire (MIC), and fiber maturity. Genotypic values (GVs) for the evaluated traits were estimated. The total phenotypic variance of the fiber quality traits evaluated is mostly composed of genotypic effects. Only the traits FP, BW, and ELG showed significant genotypes × sites interaction. The genotype G1 has high GVs for the traits FP, BW, fiber length, and fiber uniformity. The G15 stood out by gathering high values for UNIF, SFI, and STR.

Genetic studies of correlation and path coefficient analysis for yield and fibre quality traits in cotton (Gossypium hirsutum L.)

Sixteen Line × Tester hybrids were studied to better understand yield component relationships. The number of bolls per plant and boll weight had a substantial positive correlation and a high direct influence on seed cotton yield per plant, according to both association and route analysis analyses. Finally, selecting some features, such as number of bolls per plant and boll weight, directly impacts seed cotton yield per plant. Furthermore, number of bolls per plant had a substantially favourable indirect influence on number of sympodial branches per plant, micronaire value, and lint index through number of sympodial branches per plant, micronaire value, and lint index. The lint index had a significant indirect impact on the seed index. Selection based on these qualities indirectly increases seed cotton output per plant by a large margin. As a result, the yield and yield potential have improved. Key words: Path analysis, Cotton, Correlation co-efficient and Gossypium hirsutum L

Identification and validation of SSRS linked to fiber quality traits in cotton using RILs derived from Gossypium hirsutum var. MCU5 and TCH 1218

In order to increase the fiber productivity in cotton, it is imperative to genetically improve the fiber component traits and such effort can be quickened by use of molecular markers. Totally, seventy-four simple sequence repeat (SSR) markers that were previously shown to be linked to fibre strength, boll weight, and fibre elongation were used to differentiate Gossypium hirsutum var. MCU5 and TCH1218 and among them two were found to be polymorphic markers. These two polymorphic markers viz., TMB 0409 and CGR 6889 were used to genotype 220 F13 recombinant inbred lines (RILs) derived from MCU5 and TCH1218 and single marker analysis was used to confirm their linkage with target traits using the phenotypic data collected on cotton fiber yield component traits such as plant height, days to 50 percent flowering data, boll weight, number of monopodial and sympodial branches and bolls. These identified and validated markers across genetic background can be employed to genetically improve cotton through marker assisted selection.

63 K and 50 K SNP array based high-density genetic mapping and QTL analysis for productivity and fiber quality traits in cotton

63 K and 50 K SNP array based high-density genetic mapping and QTL analysis for productivity and fiber quality traits in cotton

Genomic interrogation of a MAGIC population highlights genetic factors controlling fiber quality traits in cotton

Cotton (Gossypium hirsutum L.) fiber is the most important resource of natural and renewable fiber for the textile industry. However, the understanding of genetic components and their genome-wide interactions controlling fiber quality remains fragmentary. Here, we sequenced a multiple-parent advanced-generation inter-cross (MAGIC) population, consisting of 550 individuals created by inter-crossing 11 founders, and established a mosaic genome map through tracing the origin of haplotypes that share identity-by-descent (IBD). We performed two complementary GWAS methods—SNP-based GWAS (sGWAS) and IBD-based haplotype GWAS (hGWAS). A total of 25 sQTLs and 14 hQTLs related to cotton fiber quality were identified, of which 26 were novel QTLs. Two major QTLs detected by both GWAS methods were responsible for fiber strength and length. The gene Ghir_D11G020400 (GhZF14) encoding the MATE efflux family protein was identified as a novel candidate gene for fiber length. Beyond the additive QTLs, we detected prevalent epistatic interactions that contributed to the genetics of fiber quality, pinpointing another layer for trait variance. This study provides new targets for future molecular design breeding of superior fiber quality.

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

BackgroundMeta-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.ResultsIn 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.ConclusionsThis study provides not only stable QTLs used for marker-assisted selection, but also candidate genes to uncover the molecular mechanisms for cotton fiber development.

Decryption of favourable haplotypes and potential candidate genes for five fibre quality properties using a relatively novel genome-wide association study procedure in upland cotton

To understand the genetic basis of crop economic characteristics, identifying whole-genome quantitative trait loci (QTLs) in breeding resources via genome-wide association studies (GWASs) is important, but conventional GWAS procedures have mainly concentrated on identifying regions of major QTLs. In this study, to reveal whole-genome QTLs controlling cotton fibre quality traits, a total of 1,236,418 single-nucleotide polymorphism (SNP) markers were explored in a natural population of 315 upland cotton accessions using the specific-locus amplified fragment sequencing (SLAF-seq) method, and 13,391 high-quality SNPs were organized into 9244 SNP linkage disequilibrium blocks (SNPLDBs) to develop molecular markers with multiple haplotypes/alleles. A relatively novel procedure for restricted two-stage multi-locus multi-allele GWAS (RTM-GWAS) involving two methods was applied, including multiple environments and four single environments. In total, 75, 77, 66, 66, and 60 significant SNPLDBs associated with the upper half mean length (UHML), fibre strength (FS), fibre micronaire (FM), fibre uniformity index (FUI), and fibre elongation (FE), respectively, were identified via the multiple-environment RTM-GWAS method. Based on these results, the haplotype/allele effects of the significant SNPLDB loci were estimated, and QTL-allele matrices were established to provide the abbreviated genetic composition of the population. Most importantly, nine stable SNPLDB loci were simultaneously detected in multiple environments and two or more single test environments with large –lg(P) values and percentages of explained phenotypic variation. Furthermore, favourable haplotypes/alleles of the nine stable SNPLDB loci were identified, and 79 potential candidate genes related to UHML and FS traits were predicted from RNA-seq data. Favourable haplotypes/alleles, potential candidate genes and QTL-allele matrices can offer important insights into the genetic basis of fibre quality traits in upland cotton and may facilitate the breeding of cotton varieties with excellent fibre quality properties.

Fine-mapping and candidate gene analysis of qFS-Chr. D02, a QTL for fibre strength introgressed from a semi-wild cotton into Gossypium hirsutum

Fibre strength (FS) is an important quality attribute in the modern textile industry, which is genetically controlled by quantitative trait loci (QTLs). Fine-mapping stable QTLs for FS to identify candidate genes would be valuable for uncovering the genetic basis of fibre quality traits in cotton. Here, a single segment introgression line, IL-D2−2, from the cross of (TM-1×TX-1046) reported in our previous studies, was found to have significantly improved FS compared with the recurrent parent TM-1. To fine-map the QTLs of the FS, we further crossed IL-D2−2 with its recurrent parent TM-1 to produce F2 and F2:3 populations. QTL analysis and substitution mapping showed qFS-Chr. D02 was anchored into a 550.66 kb-interval between two markers, INTR1027 and JESPR-231. This interval contained 67 genes, among which 27 genes related to cell-wall synthesis were selected to conduct qRT-PCR. The results revealed seven genes were expressed significantly differently during the fibre secondary-wall-thickening stage (10–25 days post-anthesis), three being upregulated and four downregulated in IL-D2−2. Both GH_D02G2269 (UDP-glucosyl transferase 84B1) and GH_D02G2289 (unknown function (DUF869)) with nonsynonymous SNPs in IL-D2−2 had significantly downregulated expression, suggesting they were candidates for qFS-Chr. D02. This research provides information about marker-assisted selection for cotton fibre strength improvement.

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

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.

Genetic analysis of yield and fiber quality traits in upland cotton (Gossypium hirsutum L.) cultivated in different ecological regions of China

BackgroundCotton is an important fiber crop worldwide. The yield potential of current genotypes of cotton can be exploited through hybridization. However, to develop superior hybrids with high yield and fiber quality traits, information of genetic control of traits is prerequisite. Therefore, genetic analysis plays pivotal role in plant breeding.ResultsIn present study, North Carolina II mating design was used to cross 5 female parents with 6 male parents to produce 30 intraspecific F1 cotton hybrids. All plant materials were tested in three different ecological regions of China during the year of 2016–2017. Additive-dominance-environment (ADE) genetic model was used to estimate the genetic effects and genotypic and phenotypic correlation of yield and fiber quality traits. Results showed that yield traits except lint percentage were mainly controlled by genetic and environment interaction effects, whereas lint percentage and fiber quality traits were determined by main genetic effects. Moreover, dominant and additive-environment interaction effects had more influence on yield traits, whereas additive and dominance-environment interaction effects were found to be predominant for fiber traits. Broad-sense and its interaction heritability were significant for all yield and most of fiber quality traits. Narrow-sense and its interaction heritability were non-significant for boll number and seed cotton yield. Correlation analysis indicated that seed cotton yield had significant positive correlation with other yield attributes and non-significant with fiber quality traits. All fiber quality traits had significant positive correlation with each other except micronaire.ConclusionsResults of current study provide important information about genetic control of yield and fiber quality traits. Further, this study identified that parental lines, e.g., SJ48–1, ZB-1, 851–2, and DT-8 can be utilized to improve yield and fiber quality traits in cotton.

Analysis of Testing Locations in Regional High-Quality Tests for Cotton Fiber Quality Traits

Determination of an efficient number of testing locations in multiple-location tests for cotton (Gossypium hirsutum L.) fiber quality can allow removal of unnecessary locations while maintaining the statistical power in detection of genotype (g) by environment (e) interactions. Fiber quality data from Regional High-Quality (RHQ) tests from 2011 to 2016 were used to determine an efficient number of locations in the tests for fiber quality and relationships among locations for their representativeness and ability to discriminate among genotypes. Covariance parameters of g, location (l), and gl in the original RHQ tests were estimated in a random model. The simulating data with varying number of locations omitted from the original tests were created by performing 100 unique simulations. When locations were reduced to five, the standard deviations (std) of gl increased from 18 to 37% compared to the original tests. Further reduction of locations to four or less increased std of gl from 30 to 217% compared to the original tests. Therefore, five locations were determined to be an efficient number of locations in tests for fiber quality. The discriminating ability and representativeness of the eight locations for fiber properties were calculated as their distances to an "ideal environment", which was designed as a center in GGE biplot graphs for representativeness and discriminating ability. The relationships among locations were different across years. However, by averaging the distances across testing years, the locations of Stoneville, MS; Keiser, AR; Lubbock, TX; and College Station, TX were identified as the most representative testing sites for fiber properties.

Whole genome sequencing of a MAGIC population identified genomic loci and candidate genes for major fiber quality traits in upland cotton (Gossypium hirsutum L.).

Significant associations between candidate genes and six major cotton fiber quality traits were identified in a MAGIC population using GWAS and whole genome sequencing. Upland cotton (Gossypium hirsutum L.) is the world's major renewable source of fibers for textiles. To identify causative genetic variants that influence the major agronomic measures of cotton fiber quality, which are used to set discount or premium prices on each bale of cotton in the USA, we measured six fiber phenotypes from twelve environments, across three locations and 7years. Our 550 recombinant inbred lines were derived from a multi-parent advanced generation intercross population and were whole-genome-sequenced at 3× coverage, along with the eleven parental cultivars at 20× coverage. The segregation of 473,517 single nucleotide polymorphisms (SNPs) in this population, including 7506 non-synonymous mutations, was combined with phenotypic data to identify seven highly significant fiber quality loci. At these loci, we found fourteen genes with non-synonymous SNPs. Among these loci, some had simple additive effects, while others were only important in a subset of the population. We observed additive effects for elongation and micronaire, when the three most significant loci for each trait were examined. In an informative subset where the major multi-trait locus on chromosome A07:72-Mb was fixed, we unmasked the identity of another significant fiber strength locus in gene Gh_D13G1792 on chromosome D13. The micronaire phenotype only revealed one highly significant genetic locus at one environmental location, demonstrating a significant genetic by environment component. These loci and candidate causative variant alleles will be useful to cotton breeders for marker-assisted selection with minimal linkage drag and potential biotechnological applications.

Genetic Map Construction and Fiber Quality QTL Mapping Using the CottonSNP80K Array in Upland Cotton.

Cotton fiber quality traits are controlled by multiple quantitative trait loci (QTL), and the improvement of these traits requires extensive germplasm. Herein, an Upland cotton cultivar from America, Acala Maxxa, was crossed with a local high fiber quality cultivar, Yumian 1, and 180 recombinant inbred lines (RILs) were obtained. In order to dissect the genetic basis of fiber quality differences between these parents, a genetic map containing 12116 SNP markers was constructed using the CottonSNP80K assay, which covered 3741.81 cM with an average distance of 0.31 cM between markers. Based on the genetic map and growouts in three environments, we detected a total of 104 QTL controlling fiber quality traits. Among these QTL, 25 were detected in all three environments and 35 in two environments. Meanwhile, 19 QTL clusters were also identified, and nine contained at least one stable QTL (detected in three environments for a given trait). These stable QTL or QTL clusters are priorities for fine mapping, identifying candidate genes, elaborating molecular mechanisms of fiber development, and application in cotton breeding programs by marker-assisted selection (MAS).

Genotype by Environment Interactions on Cotton Fiber Traits and Their Implications on Variety Recommendation

The objective of this study was to evaluate cotton fiber quality traits across diverse environments. This could lead to the selection of the best environment for cotton cultivations and the best adapted commercial cultivars. For this reason four main cotton regions were chosen as different environments: Thessaly, Thrace, Macedonia and Sterea Ellas. Five of the most commercial upland cotton cultivars (DP332, DP377, ST402, CELIA and ELSA) were used for evaluation of their fiber quality traits. Each cultivar was sown in 10 different fields (in order to exploit and evaluate different soil types) in each of the above mentioned regions and (in total) 200 fields were used in total. Four samples from each field were collected in order to analyze fiber quality traits: micronaire, maturity index (%), fiber length as the upper half mean length (mm), fiber strength (gram/tex), uniformity index (%), fiber elongation, short fiber index, yellowness (+b), reflectance index (Rd).Cultivation regions must also be selected in a way that they could promote fiber traits, in order to ensure the highest fiber quality. Cotton fiber quality traits were affected differently from environmental fluctuations, showing that the ranking of cultivars according to environmental fluctuations is important, if proper breeding methods should be applied. Each trait is affected differently by environmental fluctuations and requires precise knowledge of the degree of inheritance i.e., as to how much qualitative or quantitative is the trait, in order to choose and apply the proper breeding method.

GhMYB1 regulates SCW stage-specific expression of the GhGDSL promoter in the fibres of Gossypium hirsutum L.

SummarySecondary cell wall (SCW) biosynthesis is an important stage of the cotton fibre development, and its transcriptional regulation is poorly understood. We selected the Gossypium hirsutum GDSL (GhGDSL) lipase/hydrolase gene (CotAD_74480), which is expressed during SCW biosynthesis (19 through to 25 days postanthesis; DPA), for study. T1‐transgenic cotton lines expressing the β‐glucuronidase (gus) reporter under the control of a 1026‐bp promoter fragment of GhGDSL (PG h GDSL) showed 19 DPA stage‐specific increase in GUS expression. 5′ deletion indicated that the 194‐bp fragment between –788 and –594 relative to the transcription start site was essential for this stage‐specific expression. Site‐directed mutagenesis of eight transcription factor binding sites within PG h GDSL demonstrated that the MYB1AT motif (AAACCA) at –603/–598 was critical for the 19 DPA‐specific reporter gene expressions. Yeast one‐hybrid (Y1H) analysis identified nine proteins, including GhMYB1 (CotAD_64719) that bound to the PG h GDSL promoter. Further, Y1H experiments using the 5′ promoter deletions and individually mutated promoter motifs indicated that GhMYB1 interacted with PG h GDSL at MYB1AT sequence. GhMYB1 was expressed specifically in fibre from 19 DPA, overlapping with the sharp rise in GhGDSL expression, indicating that it could regulate GhGDSL during fibre development. Analysis of genes co‐expressed with GhMYB1 showed that it potentially regulates a number of other 19–25 DPA‐specific genes in networks including those functioning in the cell wall and precursor synthesis, but not the major polysaccharide and protein components of the fibre SCW. GhGDSL and its promoter are therefore potential tools for the improvement of cotton fibre quality traits.

Targeted identification of association between cotton fiber quality traits and microsatellite markers

Primitive and exotic accessions of cotton are potential sources of favorable alleles for genetic improvement, enriching diversity in the genetically constricted gene pool of elite cultivars. Three exotic accessions of cotton (MDN101, MDN063 and MDN257), collected from different parts of Central America and converted to day-neutral flowering; and four elite cultivars (PD94042, DES56, PMHS200 and Acala Maxxa) representing the US cotton gene pool were used as parents to create experimental populations. The corresponding F2 and F2:3 progenies of these populations were grown in two successive years (i.e., some in 2011–2012, some in 2012–2013) and phenotypes were scored in both F2 and F2:3 progenies in all 3 years (2011–2012–2013). These populations were screened with 113 polymorphic microsatellite markers selected from “hotspots” for fiber quality quantitative trait loci in the cotton genome and single marker analyses were performed to identify significant associations of the markers with six fiber quality traits. A total of 134 nominal marker-trait associations were identified, among which 15 were significant after Bonferroni correction for multiple comparisons. In 67 of 134 nominal associations and 4 of 15 significant associations, the exotic parents contributed favorable alleles to multiple backgrounds and for multiple traits, in addition to the traits for which they were selected. These results indicate that utilization of exotic and wild accessions of cotton is useful in introducing favorable alleles into the cultivated cotton gene pool for genetic improvement.