Upland Cotton (Gossypium hirsutum) is one of the most important worldwide crops it provides natural high-quality fiber for the industrial production and everyday use. Next-generation sequencing is a powerful method to identify single nucleotide polymorphism markers on a large scale for the construction of a high-density genetic map for quantitative trait loci mapping. In this research, a recombinant inbred lines population developed from two upland cotton cultivars 0–153 and sGK9708 was used to construct a high-density genetic map through the specific locus amplified fragment sequencing method. The high-density genetic map harbored 5521 single nucleotide polymorphism markers which covered a total distance of 3259.37 cM with an average marker interval of 0.78 cM without gaps larger than 10 cM. In total 18 quantitative trait loci of boll weight were identified as stable quantitative trait loci and were detected in at least three out of 11 environments and explained 4.15–16.70 % of the observed phenotypic variation. In total, 344 candidate genes were identified within the confidence intervals of these stable quantitative trait loci based on the cotton genome sequence. These genes were categorized based on their function through gene ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis and eukaryotic orthologous groups analysis. This research reported the first high-density genetic map for Upland Cotton (Gossypium hirsutum) with a recombinant inbred line population using single nucleotide polymorphism markers developed by specific locus amplified fragment sequencing. We also identified quantitative trait loci of boll weight across 11 environments and identified candidate genes within the quantitative trait loci confidence intervals. The results of this research would provide useful information for the next-step work including fine mapping, gene functional analysis, pyramiding breeding of functional genes as well as marker-assisted selection.

The identification of quantitative trait loci (QTLs) that are stable and consistent across multiple environments and populations plays an essential role in marker-assisted selection (MAS). In the present study, we used 28,861 simple sequence repeat (SSR) markers, which included 12,560 Gossypium raimondii (D genome) sequence-based SSR markers to identify polymorphism between two upland cotton strains 0–153 and sGK9708. A total of 851 polymorphic primers were finally selected and used to genotype 196 recombinant inbred lines (RIL) derived from a cross between 0 and 153 and sGK9708 and used to construct a linkage map. The RIL population was evaluated for fiber quality traits in six locations in China for five years. Stable QTLs identified in this intraspecific cross could be used in future cotton breeding program and with fewer obstacles. The map covered a distance of 4,110 cM, which represents about 93.2 % of the upland cotton genome, and with an average distance of 5.2 cM between adjacent markers. We identified 165 QTLs for fiber quality traits, of which 47 QTLs were determined to be stable across multiple environments. Most of these QTLs aggregated into clusters with two or more traits. A total of 30 QTL clusters were identified which consisted of 103 QTLs. Sixteen clusters in the At sub-genome comprised 44 QTLs, whereas 14 clusters in the Dt sub-genome that included 59 QTLs for fiber quality were identified. Four chromosomes, including chromosome 4 (c4), c7, c14, and c25 were rich in clusters harboring 5, 4, 5, and 6 clusters respectively. A meta-analysis was performed using Biomercator V4.2 to integrate QTLs from 11 environmental datasets on the RIL populations of the above mentioned parents and previous QTL reports. Among the 165 identified QTLs, 90 were identified as common QTLs, whereas the remaining 75 QTLs were determined to be novel QTLs. The broad sense heritability estimates of fiber quality traits were high for fiber length (0.93), fiber strength (0.92), fiber micronaire (0.85), and fiber uniformity (0.80), but low for fiber elongation (0.27). Meta-clusters on c4, c7, c14 and c25 were identified as stable QTL clusters and were considered more valuable in MAS for the improvement of fiber quality of upland cotton. Multiple environmental evaluations of an intraspecific RIL population were conducted to identify stable QTLs. Meta-QTL analyses identified a common chromosomal region that plays an important role in fiber development. Therefore, QTLs identified in the present study are an ideal candidate for MAS in cotton breeding programs to improve fiber quality.

Pectin methylesterase (PME, EC 3.1.1.11) is a hydrolytic enzyme that utilizes pectin as substrates, and plays a significant role in regulating pectin reconstruction thereby regulating plant growth. Pectin is one of the important components of the plant cell wall, which forms the main structural material of cotton fiber. In this research, cotton genome information was used to identify PMEs. We identified 80 (GaPME01-GaPME80) PME genes from diploid G. arboreum (A genome), 78 (GrPME01-GrPME78) PME genes from G. raimondii (D genome), and 135 (GhPME001-GhPME135) PME genes from tetraploid cotton G. hirsutum (AD genome). We further analyzed their gene structure, conserved domain, gene expression, and systematic evolution to lay the foundation for deeper research on the function of PMEs. Phylogenetic data indicated that members from the same species demonstrated relatively high sequence identities and genetic similarities. Analysis of gene structures showed that most of the PMEs genes had 2–3 exons, with a few having a variable number of exons from 4 to 6. There are nearly no differences in the gene structure of PMEs among the three (two diploid and one tetraploid) cotton species. Selective pressure analysis showed that the Ka/Ks value for each of the three cotton species PME families was less than one. Conserved domain analysis showed that PMEs members had a relatively conserved C-terminal pectinesterase domain (PME) while the N-terminus was less conserved. Moreover, some of the family members contained a pectin methylesterase inhibitor (PMEI) domain. The Ka/Ks ratios suggested that the duplicated PMEs underwent purifying selection after the duplication events. This study provided an important basis for further research on the functions of cotton PMEs. Results from qRT-PCR indicated that the expression level of different PMEs at various fiber developmental stages was different. Moreover, some of the PMEs showed fiber predominant expression in secondary wall thickening indicating tissue-specific expression patterns.

Cotton fiber strength is a critical property determining fiber qualities, and determined by the secondary cell wall development. Understanding the mechanism of fiber development will provide a way to improvement of fiber strength. In this study, the introgression lines of upland and sea island cotton, and have experience of four generations of backcross with upland parent, and have significant higher fiber strength than their upland parent, and the transcriptome were analyzed and compared between the introgression lines and their upland parent. There were 2201 differentially expressed genes (DEG) identified by comparing two introgression lines with their recurrent parent CCRI45, in different development stages from 15 days post-anthesis (DPA) to 28 DPA. The up-regulated genes regulated the polysaccharide metabolic process, single-organism localization, cell wall organization or biogenesis and so on. The down-regulated genes involved in the microtubule-based process, cellular response to stress, cell cycle process and so on. Further functional analysis revealed three significant functional genes, XLOC_036333 (mannosyl-oligosaccharide-alpha-mannosidase mns1), XLOC_029945 ( FLA8 ) and XLOC_075372 ( snakin-1 ), playing important roles in the regulation of cotton fiber strength. Our results provide important candidates genes and inspirations for the future investigation of the molecular mechanism of fiber quality formation, and improvement of cotton fiber quality in breeding.