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.

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.

BackgroundVerticillium wilt (VW), also known as “cotton cancer,” is one of the most destructive diseases in global cotton production that seriously impacts fiber yield and quality. Despite numerous attempts, little significant progress has been made in improving the VW resistance of upland cotton. The development of chromosome segment substitution lines (CSSLs) from Gossypium hirsutum × G. barbadense has emerged as a means of simultaneously developing new cotton varieties with high-yield, superior fiber, and resistance to VW.ResultsIn this study, VW-resistant investigations were first conducted in an artificial greenhouse, a natural field, and diseased nursery conditions, resulting in the identification of one stably VW-resistant CSSL, MBI8255, and one VW-susceptible G. hirsutum, CCRI36, which were subsequently subjected to biochemical tests and transcriptome sequencing during V991 infection (0, 1, and 2 days after inoculation). Eighteen root samples with three replications were collected to perform multiple comparisons of enzyme activity and biochemical substance contents. The findings indicated that VW resistance was positively correlated with peroxidase and polyphenol oxidase activity, but negatively correlated with malondialdehyde content. Additionally, RNA sequencing was used for the same root samples, resulting in a total of 77,412 genes, of which 23,180 differentially expressed genes were identified from multiple comparisons between samples. After Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis on the expression profiles identified using Short Time-series Expression Miner, we found that the metabolic process in the biological process, as well as the pathways of phenylpropanoid biosynthesis and plant hormone signal transduction, participated significantly in the response to VW. Gene functional annotation and expression quantity analysis indicated the important roles of the phenylpropanoid metabolic pathway and oxidation-reduction process in response to VW, which also provided plenty of candidate genes related to plant resistance.ConclusionsThis study concentrates on the preliminary response to V991 infection by comparing the VW-resistant CSSL and its VW-susceptible recurrent parent. Not only do our findings facilitate the culturing of new resistant varieties with high yield and superior performance, but they also broaden our understanding of the mechanisms of cotton resistance to VW.Electronic supplementary materialThe online version of this article (10.1186/s12870-018-1619-4) contains supplementary material, which is available to authorized users.

Chromosome segment substitution lines (CSSLs) are ideal materials for identifying genetic effects. In this study, CSSL MBI7561 with excellent fiber quality that was selected from BC 4 F 3:5 of CCRI45 (Gossypium hirsutum) × Hai1 (Gossypium barbadense) was used to construct 3 secondary segregating populations with 2 generations (BC 5 F 2 and BC 5 F 2:3). Eighty-one polymorphic markers related to 33 chromosome introgressive segments on 18 chromosomes were finally screened using 2292 SSR markers which covered the whole tetraploid cotton genome. A total of 129 quantitative trait loci (QTL) associated with fiber quality (103) and yield-related traits (26) were detected on 17 chromosomes, explaining 0.85-30.35% of the phenotypic variation; 39 were stable (30.2%), 53 were common (41.1%), 76 were new (58.9%), and 86 had favorable effects on the related traits. More QTL were distributed in the Dt subgenome than in the At subgenome. Twenty-five stable QTL clusters (with stable or common QTL) were detected on 22 chromosome introgressed segments. Finally, the 6 important chromosome introgressed segments (Seg-A02-1, Seg-A06-1, Seg-A07-2, Seg-A07-3, Seg-D07-3, and Seg-D06-2) were identified as candidate chromosome regions for fiber quality, which should be given more attention in future QTL fine mapping, gene cloning, and marker-assisted selection (MAS) breeding.

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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.

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.

Fiber length is an important determinant of fiber quality, and it is a quantitative multi-genic trait. Identifying genes associated with fiber length is of great importance for efforts to improve fiber quality in the context of cotton breeding. Integrating transcriptomic information and details regarding candidate gene regions can aid in candidate gene identification. In the present study, the CCRI45 line and a chromosome segment substitution line (CSSL) with a significantly higher fiber length (MBI7747) were utilized to establish F2 and F2:3 populations. Using a high-density genetic map published previously, six quantitative trait loci (QTLs) associated with fiber length and two QTLs associated with fiber strength were identified on four chromosomes. Within these QTLs, qFL-A07-1, qFL-A12-2, qFL-A12-5, and qFL-D02-1 were identified in two or three environments and confirmed by a meta-analysis. By integrating transcriptomic data from the two parental lines and through qPCR analyses, four genes associated with these QTLs including Cellulose synthase-like protein D3 (CSLD3, GH_A12G2259 for qFL-A12-2), expansin-A1 (EXPA1, GH_A12G1972 for qFL-A12-5), plasmodesmata callose-binding protein 3 (PDCB3, GH_A12G2014 for qFL-A12-5), and Polygalacturonase (At1g48100, GH_D02G0616 for qFL-D02-1) were identified as promising candidate genes associated with fiber length. Overall, these results offer a robust foundation for further studies regarding the molecular basis for fiber length and for efforts to improve cotton fiber quality.