Search

Introduction: The simultaneous improvement of fiber quality and yield for cotton is strongly limited by the narrow genetic backgrounds of Gossypium hirsutum (Gh) and the negative genetic correlations among traits. An effective way to overcome the bottlenecks is to introgress the favorable alleles of Gossypium barbadense (Gb) for fiber quality into Gh with high yield. Objectives: This study was to identify superior loci for the improvement of fiber quality and yield. Methods: Two sets of chromosome segment substitution lines (CSSLs) were generated by crossing Hai1 (Gb, donor-parent) with cultivar CCRI36 (Gh) and CCRI45 (Gh) as genetic backgrounds, and cultivated in 6 and 8 environments, respectively. The kmer genotyping strategy was improved and applied to the population genetic analysis of 743 genomic sequencing data. A progeny segregating population was constructed to validate genetic effects of the candidate loci. Results: A total of 68,912 and 83,352 genome-wide introgressed kmers were identified in the CCRI36 and CCRI45 populations, respectively. Over 90 % introgressions were homologous exchanges and about 21 % were reverse insertions. In total, 291 major introgressed segments were identified with stable genetic effects, of which 66(22.98 %), 64(21.99 %), 35(12.03 %), 31(10.65 %) and 18(6.19 %) were beneficial for the improvement of fiber length (FL), strength (FS), micronaire, lint-percentage (LP) and boll-weight, respectively. Thirty-nine introgression segments were detected with stable favorable additive effects for simultaneous improvement of 2 or more traits in Gh genetic background, including 6 could increase FL/FS and LP. The pyramiding effects of 3 pleiotropic segments (A07:C45Clu-081, D06:C45Clu-218, D02:C45Clu-193) were further validated in the segregating population. Conclusion: The combining of genome-wide introgressions and kmer genotyping strategy showed significant advantages in exploring genetic resources. Through the genome-wide comprehensive mining, a total of 11 clusters (segments) were discovered for the stable simultaneous improvement of FL/FS and LP, which should be paid more attention in the future.

Upland cotton accounts for a high percentage (95%) of the world’s cotton production. Plant height (PH) and branch number (BN) are two important agronomic traits that have an impact on improving the level of cotton mechanical harvesting and cotton yield. In this research, a recombinant inbred line (RIL) population with 250 lines developed from the variety CCRI70 was used for constructing a high-density genetic map and identification of quantitative trait locus (QTL). The results showed that the map harbored 8298 single nucleotide polymorphism (SNP) markers, spanning a total distance of 4876.70 centimorgans (cMs). A total of 69 QTLs for PH (9 stable) and 63 for BN (11 stable) were identified and only one for PH was reported in previous studies. The QTLs for PH and BN harbored 495 and 446 genes, respectively. Combining the annotation information, expression patterns and previous studies of these genes, six genes could be considered as potential candidate genes for PH and BN. The results could be helpful for cotton researchers to better understand the genetic mechanism of PH and BN development, as well as provide valuable genetic resources for cotton breeders to manipulate cotton plant architecture to meet future demands.

Cotton (Gossypium spp. L.) is a major origin of natural fiber, and is projected at 117 million bales worldwide for 2021/22. A variety of biotic and abiotic stresses have considerable negative impacts on cotton. The significantly decreased applications of chemical insecticidal sprays in the agro-ecosystem have greatly affected the biodiversity and dynamics of primary and secondary insects. Various control measures were taken around the globe to increase production costs. Temperature, drought, and salinity, and biotic stresses such as bacteria, viruses, fungi, nematodes, insects, and mites cause substantial losses to cotton crops. Here, we summarize a number of biotic and abiotic stresses upsetting Bt cotton crop with present and future biotechnology solution strategies that include a refuge strategy, multi-gene pyramiding, the release of sterile insects, seed mixing, RNAi, CRISPR/Cas9, biotic signaling, and the use of bioagents. Surveillance of insect resistance, monitoring of grower compliance, and implementation of remedial actions can lead to the sustainable use of cotton across the globe.

Fiber quality traits, especially fiber strength, length, and micronaire (FS, FL, and FM), have been recognized as critical fiber attributes in the textile industry, while the lint percentage (LP) was an important indicator to evaluate the cotton lint yield. So far, the genetic mechanism behind the formation of these traits is still unclear. Quantitative trait loci (QTL) identification and candidate gene validation provide an effective methodology to uncover the genetic and molecular basis of FL, FS, FM, and LP. A previous study identified three important QTL/QTL cluster loci, harboring at least one of the above traits on chromosomes A01, A07, and D12 via a recombinant inbred line (RIL) population derived from a cross of Lumianyan28 (L28) × Xinluzao24 (X24). A secondary segregating population (F2) was developed from a cross between L28 and an RIL, RIL40 (L28 × RIL40). Based on the population, genetic linkage maps of the previous QTL cluster intervals on A01 (6.70–10.15 Mb), A07 (85.48–93.43 Mb), and D12 (0.40–1.43 Mb) were constructed, which span 12.25, 15.90, and 5.56 cM, with 2, 14, and 4 simple sequence repeat (SSR) and insertion/deletion (Indel) markers, respectively. QTLs of FL, FS, FM, and LP on these three intervals were verified by composite interval mapping (CIM) using WinQTL Cartographer 2.5 software via phenotyping of F2 and its derived F2:3 populations. The results validated the previous primary QTL identification of FL, FS, FM, and LP. Analysis of the RNA-seq data of the developing fibers of L28 and RIL40 at 10, 20, and 30 days post anthesis (DPA) identified seven differentially expressed genes (DEGs) as potential candidate genes. qRT-PCR verified that five of them were consistent with the RNA-seq result. These genes may be involved in regulating fiber development, leading to the formation of FL, FS, FM, and LP. This study provides an experimental foundation for further exploration of these functional genes to dissect the genetic mechanism of cotton fiber development.

Upland cotton is an important allotetraploid crop that provides both natural fiber for the textile industry and edible vegetable oil for the food or feed industry. To better understand the genetic mechanism that regulates the biosynthesis of storage oil in cottonseed, we identified the genes harbored in the major quantitative trait loci/nucleotides (QTLs/QTNs) of kernel oil content (KOC) in cottonseed via both multiple linkage analyses and genome-wide association studies (GWAS). In ‘CCRI70′ RILs, six stable QTLs were simultaneously identified by linkage analysis of CHIP and SLAF-seq strategies. In ‘0-153′ RILs, eight stable QTLs were detected by consensus linkage analysis integrating multiple strategies. In the natural panel, thirteen and eight loci were associated across multiple environments with two algorithms of GWAS. Within the confidence interval of a major common QTL on chromosome 3, six genes were identified as participating in the interaction network highly correlated with cottonseed KOC. Further observations of gene differential expression showed that four of the genes, LtnD, PGK, LPLAT1, and PAH2, formed hub genes and two of them, FER and RAV1, formed the key genes in the interaction network. Sequence variations in the coding regions of LtnD, FER, PGK, LPLAT1, and PAH2 genes may support their regulatory effects on oil accumulation in mature cottonseed. Taken together, clustering of the hub genes in the lipid biosynthesis interaction network provides new insights to understanding the mechanism of fatty acid biosynthesis and TAG assembly and to further genetic improvement projects for the KOC in cottonseeds.

Cotton is an important fiber crop. The cotton fiber is an extremely long trichome that develops from the epidermis of an ovule. The trichome is a general and multi-function plant organ, and trichome birefringence-like (TBL) genes are related to trichome development. At the genome-wide scale, we identified TBLs in four cotton species, comprising two cultivated tetraploids (Gossypium hirsutum and G. barbadense) and two ancestral diploids (G. arboreum and G. raimondii). Phylogenetic analysis showed that the TBL genes clustered into six groups. We focused on GH_D02G1759 in group IV because it was located in a lint percentage-related quantitative trait locus. In addition, we used transcriptome profiling to characterize the role of TBLs in group IV in fiber development. The overexpression of GH_D02G1759 in Arabidopsis thaliana resulted in more trichomes on the stems, thereby confirming its function in fiber development. Moreover, the potential interaction network was constructed based on the co-expression network, and it was found that GH_D02G1759 may interact with several genes to regulate fiber development. These findings expand our knowledge of TBL family members and provide new insights for cotton molecular breeding.

Abstract Verticillium wilt is the second serious vascular wilt caused by the phytopathogenic fungus Verticillium dahliae Kleb. It has distributed worldwide, causing serious yield losses and fiber quality reduction in cotton production. The pathogen has developed different mechanisms like the production of cell wall degrading enzymes, activation of virulence genes and protein effectors to succeed in its infection. Cotton plant has also evolved multiple mechanisms in response to the fungus infection, including a strong production of lignin and callose deposition to strengthen the cell wall, burst of reactive oxygen species, accumulation of defene hormones, expression of defense-related genes, and target-directed strategies like cross-kingdom RNAi for specific virulent gene silencing. This review summarizes the recent progress made over the past two decades in understanding the interactions between cotton plant and the pathogen Verticillium dahliae during the infection process. The review also discusses the achievements in the control practices of cotton verticillium wilt in recent years, including cultivation practices, biological control, and molecular breeding strategies. These studies reveal that effective management strategies are needed to control the disease, while cultural practices and biological control approaches show promising results in the future. Furthermore, the biological control approaches developed in recent years, including antagonistic fungi, endophytic bacteria, and host induced gene silencing strategies provide efficient choices for integrated disease management.

Abstract Background Pectin is a key substance involved in cell wall development, and the galacturonosyltransferases (GAUTs) gene family is a critical participant in the pectin synthesis pathway. Systematic and comprehensive research on GAUTs has not been performed in cotton. Analysis of the evolution and expression patterns of the GAUT gene family in different cotton species is needed to increase knowledge of the function of pectin in cotton fiber development. Results In this study, we have identified 131 GAUT genes in the genomes of four Gossypium species (G. raimondii, G. barbadense, G. hirsutum, and G. arboreum), and classified them as GAUT-A, GAUT-B and GAUT-C, which coding probable galacturonosyltransferases. Among them, the GAUT genes encode proteins GAUT1 to GAUT15. All GAUT proteins except for GAUT7 contain a conserved glycosyl transferase family 8 domain (H-DN-A-SVV-S-V-H-T-F). The conserved sequence of GAUT7 is PLN (phospholamban) 02769 domain. According to cis-elemet analysis, GAUT genes transcript levels may be regulated by hormones such as JA, GA, SA, ABA, Me-JA, and IAA. The evolution and transcription patterns of the GAUT gene family in different cotton species and the transcript levels in upland cotton lines with different fiber strength were analyzed. Peak transcript level of GhGAUT genes have been observed before 15 DPA. In the six materials with high fiber strength, the transcription of GhGAUT genes were concentrated from 10 to 15 DPA; while the highest transcript levels in low fiber strength materials were detected between 5 and 10 DPA. These results lays the foundation for future research on gene function during cotton fiber development. Conclusions The GAUT gene family may affect cotton fiber development, including fiber elongation and fiber thickening. In the low strength fiber lines, GAUTs mainly participate in fiber elongation, whereas their major effect on cotton with high strength fiber is related to both elongation and thickening.

Abstract Cotton (Gossypium spp.) contributes significantly to the economy of cotton-producing countries. Pakistan is the fourth-largest producer of cotton after China, the USA and India. The average yield of cotton is about 570.99 kg.hm− 2 in Pakistan. Climate change and different biotic stresses are causing reduction in cotton production. Transgenic approaches have unique advantage to tackle all these problems. However, how to confer permanent resistance in cotton against insects through genetic modification, is still a big challenge to address. Development of transgenic cotton has been proven to be effective. But its effectiveness depends upon several factors, including heterogeneity, seed purity, diffusion of varieties, backcrossing and ethical concerns. Cotton biotechnology was initiated in Pakistan in 1992–1993 with a focus on acquiring cotton leaf curl virus (CLCuV)-resistant insect-resistant, and improving fiber quality. This review summarizes the use of molecular markers, QTLs, GWAS, and gene cloning for cotton germplasm improvement, particularly in Pakistan.

Abstract Background Plant height (PH) and fruit branch number (FBN) are important traits for improving yield and mechanical harvesting of cotton. In order to identify genes of PH and FBN in cotton germplasms to develop superior cultivars, quantitative trait loci (QTLs) for these traits were detected based on the phenotypic evaluation data in nine environments across four locations and 4 years and a previously reported genetic linkage map of an recombinant inbred line (RIL) population of upland cotton. Results In total, 53 QTLs of PH and FBN, were identified on 21 chromosomes of the cotton genome except chromosomes c02, c09-c11, and c22. For PH, 27 QTLs explaining 3.81%–8.54% proportions of phenotypic variance were identified on 18 chromosomes except c02, c08-c12, c15, and c22. For FBN, 26 QTLs explaining 3.23%–11.00% proportions of phenotypic variance were identified on 16 chromosomes except c02-c03, c06, c09-c11, c17, c22-c23, and c25. Eight QTLs were simultaneously identified in at least two environments. Three QTL clusters containing seven QTLs were identified on three chromosomes (c01, c18 and c21). Eleven QTLs were the same as previously reported ones, while the rest were newly identified. Conclusions The QTLs and QTL clusters identified in the current study will be helpful to further understand the genetic mechanism of PH and FBN development of cotton and will enhance the development of excellent cultivars for mechanical managements in cotton production.

Lack of precise information about the candidate genes involved in a complex quantitative trait is a major obstacle in the cotton fiber quality improvement, and thus, overall genetic gain in conventional phenotypic selection is low. Recent molecular interventions and advancements in genome sequencing have led to the development of high-throughput molecular markers, quantitative trait locus (QTL) fine mapping, and single nucleotide polymorphisms (SNPs). These advanced tools have resolved the existing bottlenecks in trait-specific breeding. This review demonstrates the significance of chromosomes 3, 7, 9, 11, and 12 of sub-genomes A and D carrying candidate genes for fiber quality. However, chromosome 7 carrying SNPs for stable and potent QTLs related to fiber quality provides great insights for fiber quality-targeted research. This information can be validated by marker-assisted selection (MAS) and transgene in Arabidopsis and subsequently in cotton.

Upland cotton (Gossypium hirsutum) is widely planted around the world for its natural fiber, and producing high-quality fiber is essential for the textile industry. CCRI70 is a hybrid cotton plant harboring superior yield and fiber quality, whose recombinant inbred line (RIL) population was developed from two upland cotton varieties (sGK156 and 901-001) and were used here to investigate the source of high-quality related alleles. Based on the material of the whole population, a high-density genetic map was constructed using specific locus-amplified fragment sequencing (SLAF-seq). It contained 24,425 single nucleotide polymorphism (SNP) markers, spanning a distance of 4,850.47 centimorgans (cM) over 26 chromosomes with an average marker interval of 0.20 cM. In evaluating three fiber quality traits in nine environments to detect multiple environments stable quantitative trait loci (QTLs), we found 289 QTLs, of which 36 of them were stable QTLs and 18 were novel. Based on the transcriptome analysis for two parents and two RILs, 24,941 unique differentially expressed genes (DEGs) were identified, 473 of which were promising genes. For the fiber strength (FS) QTLs, 320 DEGs were identified, suggesting that pectin synthesis, phenylpropanoid biosynthesis, and plant hormone signaling pathways could influence FS, and several transcription factors may regulate fiber development, such as GAE6, C4H, OMT1, AFR18, EIN3, bZIP44, and GAI. Notably, the marker D13_56413025 in qFS-chr18-4 provides a potential basis for enhancing fiber quality of upland cotton via marker-assisted breeding and gene cloning of important fiber quality traits.

Molecular interventions have helped to explore the genes involved in fiber length, fiber strength, and other quality parameters with improved characteristics, particularly in cotton. The current study is an extension and functional validation of previous findings that Gh_A07G1537 influences fiber length in cotton using a chromosomal segment substitution line MBI7747 through RNA-seq data. The recombinant Gh_A07G1537 derived from the MBI7747 line was over-expressed in CCRI24, a genotype with a low profile of fiber quality parameters. Putative transformants were selected on MS medium containing hygromycin (25mg/ml), acclimatized, and shifted to a greenhouse for further growth and proliferation. Transgene integration was validated through PCR and Southern Blot analysis. Stable integration of the transgene (ΔGh_A07G1537) was validated by tracking its expression in different generations (T0, T1, and T2) of transformed cotton plants. It was found to be 2.97-, 2.86-, and 2.92-folds higher expression in T0, T1, and T2 plants, respectively, of transgenic compared with non-transgenic cotton plants. Fiber quality parameters were also observed to be improved in the engineered cotton line. Genetic modifications of Gh_A07G1537 support the improvement in fiber quality parameters and should be appreciated for the textile industry.

Abstract Background Cotton is a significant economic crop that plays an indispensable role in many domains. Gossypium hirsutum L. is the most important fiber crop worldwide and contributes to more than 95% of global cotton production. Identifying stable quantitative trait locus (QTLs) controlling fiber quality and yield related traits are necessary prerequisites for marker-assisted selection (MAS). Results A genetic linkage map was constructed with 312 simple sequence repeat (SSR) loci and 35 linkage groups using JoinMap 4.0; the map spanned 1 929.9 cM, with an average interval between two markers of 6.19 cM, and covered approximately 43.37% of the cotton genome. A total of 74 QTLs controlling fiber quality and 41 QTLs controlling yield-related traits were identified in 4 segregating generations. These QTLs were distributed across 20 chromosomes and collectively explained 1.01%~27.80% of the observed phenotypic variations. In particular, 35 stable QTLs could be identified in multiple generations, 25 common QTLs were consistent with those in previous studies, and 15 QTL clusters were found in 11 chromosome segments. Conclusion These studies provide a theoretical basis for improving cotton yield and fiber quality for molecular marker-assisted selection.

UDP-glucose dehydrogenase (UGD; EC1.1.1.22) is a NAD+-dependent enzyme that catalyzes the two-fold oxidation of UDP-glucose (UDP-Glc) to produce UDP-glucuronic acid and plays an important role in plant cell wall synthesis. A total of 42 UGD genes from four Gossypium genomes including G. hirsutum, G. arboretum, G. barbadense, and G. raimondii were identified and found that the UGD gene family has conservative evolution patterns in gene structure and protein domain. The growth of fibers can be effectively promoted after adding the UDP-Glc to the medium, and the GhUGD gene expression enhanced. In addition, the transgenic Arabidopsis lines over-expressing GH_D12G1806 had longer root lengths and higher gene expression level than the wild-type plants of Columbia-0. These results indicated that UGD may play important roles in cotton fiber development and has a guiding significance for dissecting fiber development mechanism.

As high-strength cotton fibers are critical components of high quality cotton, developing cotton cultivars with high-strength fibers as well as high yield is a top priority for cotton development. Recently, chromosome segment substitution lines (CSSLs) have been developed from high-yield Upland cotton (Gossypium hirsutum) crossed with high-quality Sea Island cotton (G. barbadense). Here, we constructed a CSSL population by crossing CCRI45, a high-yield Upland cotton cultivar, with Hai1, a Sea Island cotton cultivar with superior fiber quality. We then selected two CSSLs with significantly higher fiber strength than CCRI45 (MBI7747 and MBI7561), and one CSSL with lower fiber strength than CCRI45 (MBI7285), for further analysis. We sequenced all four transcriptomes at four different time points postanthesis, and clustered the 44,678 identified genes by function. We identified 2200 common differentially-expressed genes (DEGs): those that were found in both high quality CSSLs (MBI7747 and MBI7561), but not in the low quality CSSL (MBI7285). Many of these genes were associated with various metabolic pathways that affect fiber strength. Upregulated DEGs were associated with polysaccharide metabolic regulation, single-organism localization, cell wall organization, and biogenesis, while the downregulated DEGs were associated with microtubule regulation, the cellular response to stress, and the cell cycle. Further analyses indicated that three genes, XLOC_036333 [mannosyl-oligosaccharide-α-mannosidase (MNS1)], XLOC_029945 (FLA8), and XLOC_075372 (snakin-1), were potentially important for the regulation of cotton fiber strength. Our results suggest that these genes may be good candidates for future investigation of the molecular mechanisms of fiber strength formation and for the improvement of cotton fiber quality through molecular breeding.

It is of great importance to identify quantitative trait loci (QTL) controlling fiber quality traits and yield components for future marker-assisted selection (MAS) and candidate gene function identifications. In this study, two kinds of traits in 231 F6:8 recombinant inbred lines (RILs), derived from an intraspecific cross between Xinluzao24, a cultivar with elite fiber quality, and Lumianyan28, a cultivar with wide adaptability and high yield potential, were measured in nine environments. This RIL population was genotyped by 122 SSR and 4729 SNP markers, which were also used to construct the genetic map. The map covered 2477.99 cM of hirsutum genome, with an average marker interval of 0.51 cM between adjacent markers. As a result, a total of 134 QTLs for fiber quality traits and 122 QTLs for yield components were detected, with 2.18–24.45 and 1.68–28.27% proportions of the phenotypic variance explained by each QTL, respectively. Among these QTLs, 57 were detected in at least two environments, named stable QTLs. A total of 209 and 139 quantitative trait nucleotides (QTNs) were associated with fiber quality traits and yield components by four multilocus genome-wide association studies methods, respectively. Among these QTNs, 74 were detected by at least two algorithms or in two environments. The candidate genes harbored by 57 stable QTLs were compared with the ones associated with QTN, and 35 common candidate genes were found. Among these common candidate genes, four were possibly “pleiotropic.” This study provided important information for MAS and candidate gene functional studies.

MBI9915 is an introgression cotton line with excellent fiber quality. It was obtained by advanced backcrossing and continuous inbreeding from an interspecific cross between the upland cotton (Gossypium hirsutum) cultivar CCRI36 as the recurrent parent and the sea island cotton (G. barbadense) cultivar Hai1, as the donor parent. To study the genetic effects of the introgressed chromosome segments in G. hirsutum, an F2 secondary segregating population of 1537 individuals was created by crossing MBI9915 and CCRI36, and an F2:3 population was created by randomly selecting 347 individuals from the F2 generation. Quantitative trait locus (QTL) mapping and interaction for fiber length and strength were identified using IciMapping software. The genotype analysis showed that the recovery rate for MBI9915 was 97.9%, with a total 6 heterozygous segments and 13 homozygous segments. A total of 18 QTLs for fiber quality and 6 QTLs for yield related traits were detected using the two segregating generations. These QTLs were distributed across 7 chromosomes and collectively explained 0.81%-9.51% of the observed phenotypic variations. Six QTLs were consistently detected in two generations and 6 QTLs were identified in previous studies. A total of 13 pairs of interaction for fiber length and 13 pairs of interaction for fiber strength were identified in two generations. Among them, 3 pairs of interaction for fiber length and 3 pairs of interaction for fiber strength could be identified in all generations; 4 pairs of interactions affected fiber length and fiber strength simultaneously. The results clearly showed that 5 chromosome segments (Seg-5-1, Seg-7-1, Seg-8-1, Seg-20-2 and Seg-20-3) have important effects on fiber yield and quality. This study provides the useful information for gene cloning and marker-assisted breeding for excellent fiber related quality.

Salinity is a major abiotic stress that affects plant growth and development. In this study, we performed a proteomic analysis of cotton roots and leaf tissue following exposure to saline stress. 611 and 1477 proteins were differentially expressed in the roots and leaves, respectively. In the roots, 259 (42%) proteins were up-regulated and 352 (58%) were down-regulated. In the leaves, 748 (51%) proteins were up-regulated and 729 (49%) were down-regulated. On the basis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, we concluded that the phenylalanine metabolism and starch and sucrose metabolism were active for energy homeostasis to cope with salt stress in cotton roots. Moreover, photosynthesis, pyruvate metabolism, glycolysis / gluconeogenesis, carbon fixation in photosynthetic organisms and phenylalanine metabolism were inhabited to reduce energy consumption. Characterization of the signaling pathways will help elucidate the mechanism activated by cotton in response to salt stress.

Chromosome segment substitution lines MBI9804, MBI9855, MBI9752, and MBI9134, which were obtained by advanced backcrossing and continuously inbreeding from an interspecific cross between CCRI36, a cultivar of upland cotton (Gossypium hirsutum) as the recurrent parent, and Hai1, a cultivar of sea island cotton (G. barbadense) as the donor parent, were used to construct a multiple parent population of (MBI9804×MBI9855)×(MBI9752×MBI9134). The segregating generations of double-crossed F1 and F2 and F2:3 were used to map the quantitative trait locus (QTL) for fiber quality and yield-related traits. The recovery rate of the recurrent parent CCRI36 in the four parental lines was from 94.3%-96.9%. Each of the parental lines harbored 12-20 introgressed segments from Hai1across 21 chromosomes. The number of introgressed segments ranged from 1 to 27 for the individuals in the three generations, mostly from 9 to 18, which represented a genetic length of between 126 cM and 246 cM. A total of 24 QTLs controlling fiber quality and 11 QTLs controlling yield traits were detected using the three segregating generations. These QTLs were distributed across 11 chromosomes and could collectively explain 1.78%-20.27% of the observed phenotypic variations. Sixteen QTLs were consistently detected in two or more generations, four of them were for fiber yield traits and 12 were for fiber quality traits. One introgressed segment could significantly reduce both lint percentage and fiber micronaire. This study provides useful information for gene cloning and marker-assisted breeding for excellent fiber quality.

We hybridized 10 chromosome segment substitution lines (CSSLs) each from two CSSL populations and produced 50 F1 hybrids according to North Carolina Design II. We analyzed the genetic effects and heterosis of yield and yield components in the F1 hybrids and parents in four environments via the additive-dominance genetic model. Yield and yield components of the CSSLs were controlled by combined additive and dominance effects, and lint percentage was mainly controlled by additive effects, but boll weight, boll number, seedcotton yield and lint yield were mainly controlled by dominance effects. We detected significant interaction effects between genetics and the environment for all yields traits. Similar interactions were detected between two CSSL populations (Pop CCRI 36 and Pop CCRI 45). Significant positive mid-parent heterosis was detected for all yield traits in both populations, and significant positive better-parent heterosis was also detected for all yield traits except lint percentage. The differences among parents were relatively small, but significant heterosis was detected for yield and yield components. Therefore, the relationship between heterosis and genetic distance for yield traits is complicated and requires further study. These CSSLs represent useful tools for improving yield and yield components in cotton.

Cotton (Gossypium hirsutum L.) is an important agricultural crop that provides renewable natural fiber resources for the global textile industry. Technological developments in the textile industry and improvements in human living standards have increased the requirement for supplies and better quality cotton. Upland cotton 0-153 is an elite cultivar harboring strong fiber strength genes. To conduct quantitative trait locus (QTL) mapping for fiber quality in 0-153, we developed a population of 196 recombinant inbred lines (RILs) from a cross between 0-153 and sGK9708. The fiber quality traits in 11 environments were measured and a genetic linkage map of chromosome 25 comprising 210 loci was constructed using this RIL population, mainly using simple sequence repeat markers and single nucleotide polymorphism markers. QTLs were identified across diverse environments using the composite interval mapping method. A total of 37 QTLs for fiber quality traits were identified on chromosome 25, of which 17 were stably expressed in at least in two environments. A stable fiber strength QTL, qFS-chr25-4, which was detected in seven environments and was located in the marker interval between CRI-SNP120491 and BNL2572, could explain 6.53%-11.83% of the observed phenotypic variations. Meta-analysis also confirmed the above QTLs with previous reports. Application of these QTLs could contribute to improving fiber quality and provide information for marker-assisted selection.

Introduction: Upland cotton is an important allotetrapolyploid crop providing natural fibers for textile industry. Under the present high-level breeding and production conditions, further simultaneous improvement of fiber quality and yield is facing unprecedented challenges due to their complex negative correlations. Objectives: The study was to adequately identify quantitative trait loci (QTLs) and dissect how they orchestrate the formation of fiber quality and yield. Methods: A high-density genetic map (HDGM) based on an intraspecific recombinant inbred line (RIL) population consisting of 231 individuals was used to identify QTLs and QTL clusters of fiber quality and yield traits. The weighted gene correlation network analysis (WGCNA) package in R software was utilized to identify WGCNA network and hub genes related to fiber development. Gene functions were verified via virus-induced gene silencing (VIGS) and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 strategies. Results: An HDGM consisting of 8045 markers was constructed spanning 4943.01 cM of cotton genome. A total of 295 QTLs were identified based on multi-environmental phenotypes. Among 139 stable QTLs, including 35 newly identified ones, seventy five were of fiber quality and 64 yield traits. A total of 33 QTL clusters harboring 74 QTLs were identified. Eleven candidate hub genes were identified via WGCNA using genes in all stable QTLs and QTL clusters. The relative expression profiles of these hub genes revealed their correlations with fiber development. VIGS and CRISPR/Cas9 edition revealed that the hub gene cellulose synthase 4 (GhCesA4, GH_D07G2262) positively regulate fiber length and fiber strength formation and negatively lint percentage. Conclusion: Multiple analyses demonstrate that the hub genes harbored in the QTLs orchestrate the fiber development. The hub gene GhCesA4 has opposite pleiotropic effects in regulating trait formation of fiber quality and yield. The results facilitate understanding the genetic basis of negative correlation between cotton fiber quality and yield.