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.

Verticillium 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. In 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. This 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.

Over 6% of agricultural land is affected by salinity. It is becoming obligatory to use saline soils, so growing salt-tolerant plants is a priority. To gain an understanding of the genetic basis of upland cotton tolerance to salinity at seedling stage, an intra-specific cross was developed from CCRI35, tolerant to salinity, as female with Nan Dan (NH), sensitive to salinity, as the male. A genetic map of 5178 SNP markers was developed from 277 F_2:3 populations. The map spanned 4768.098 cM, with an average distance of 0.92 cM. A total of 66 QTLs for 10 traits related to salinity were detected in three environments (0, 110, and 150 mM salt treatment). Only 14 QTLs were consistent, accounting for 2.72% to 9.87% of phenotypic variation. Parental contributions were found to be in the ratio of 3:1, 10 QTLs from the sensitive and four QTLs from the resistant parent. Five QTLs were located in A_t and nine QTLs in the D_t sub-genome. Moreover, eight clusters were identified, in which 12 putative key genes were found to be related to salinity. The GBS-SNPs-based genetic map developed is the first high-density genetic map that has the potential to provide deeper insights into upland cotton salinity tolerance. The 12 key genes found in this study could be used for QTL fine mapping and cloning for further studies.