Plant roots and soil microorganisms interact with each other mainly in the rhizosphere. Changes in the community structure of the rhizosphere microbiome are influenced by many factors. In this study, we determined the community structure of rhizosphere bacteria in cotton, and studied the variation of rhizosphere bacterial community structure in different soil types and developmental stages using TM-1, an upland cotton cultivar (Gossypium hirsutum L.) and Hai 7124, a sea island cotton cultivar (G. barbadense L.) by high-throughput sequencing technology. Six bacterial phyla were found dominantly in cotton rhizosphere bacterial community including Acidobacteria, Actinobacteria, Bacteroidetes, Planctomycetes, Proteobacteria, and Verrucomicrobia. The abundance of Acidobacteria, Cyanobacteria, Firmicutes, Planctomycetes and Proteobacteria were largely influenced by cotton root. Bacterial α-diversity in rhizosphere was lower than that of bulk soil in nutrient-rich soil, but higher in cotton continuous cropping field soil. The β-diversity in nutrient-rich soil was greater than that in continuous cropping field soil. The community structure of the rhizosphere bacteria varied significantly during different developmental stages. Our results provided insights into the dynamics of cotton rhizosphere bacterial community and would facilitate to improve cotton growth and development through adjusting soil bacterial community structure artificially.

SummaryCotton is widely cultivated globally because it provides natural fibre for the textile industry and human use. To identify quantitative trait loci (QTLs)/genes associated with fibre quality and yield, a recombinant inbred line (RIL) population was developed in upland cotton. A consensus map covering the whole genome was constructed with three types of markers (8295 markers, 5197.17 centimorgans (cM)). Six fibre yield and quality traits were evaluated in 17 environments, and 983 QTLs were identified, 198 of which were stable and mainly distributed on chromosomes 4, 6, 7, 13, 21 and 25. Thirty‐seven QTL clusters were identified, in which 92.8% of paired traits with significant medium or high positive correlations had the same QTL additive effect directions, and all of the paired traits with significant medium or high negative correlations had opposite additive effect directions. In total, 1297 genes were discovered in the QTL clusters, 414 of which were expressed in two RNA‐Seq data sets. Many genes were discovered, 23 of which were promising candidates. Six important QTL clusters that included both fibre quality and yield traits were identified with opposite additive effect directions, and those on chromosome 13 (qClu‐chr13‐2) could increase fibre quality but reduce yield; this result was validated in a natural population using three markers. These data could provide information about the genetic basis of cotton fibre quality and yield and help cotton breeders to improve fibre quality and yield simultaneously.

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The germplasm with exotic genomic components especially from Sea Island cotton (Gossypium barbadense L. Gb) is the dominant genetic resources to enhance fiber quality of upland cotton (G. hirsutum L., Gh). Due to low efficiency of phenotypic evaluation and selection on fiber quality, genetic dissection of favorable alleles using molecular markers is essential. Genetic dissection on putative Gb introgressions related to fiber traits were conducted by SSR markers with mapping populations derived from a cross between Luyuan343 (LY343), a superior fiber quality introgression line (IL) with genomic components from Gb, and an elite Upland cotton cv. Lumianyan#22 (LMY22). Among 82 polymorphic loci screened out from 4050 SSRs, 42 were identified as putative introgression alleles. A total of 29 fiber-related QTLs (23 for fiber quality and six for lint percentage) were detected and most of which clustered on the putative Gb introgression chromosomal segments of Chr.2, Chr.16, Chr.23 and Chr.25. As expected, a majority of favorable alleles of fiber quality QTLs (12/17, not considering the QTLs for fiber fineness) came from the IL parent and most of which (11/12) were conferred by the introgression genomic components while three of the six (3/6) favorable alleles for lint percentage came from the Gh parent. Validation of these QTLs using an F 8 breeding population from the same cross made previously indicated that 13 out of 29 QTLs showed considerable stability. The results suggest that fiber quality improvement using the introgression components could be facilitated by marker-assisted selection in cotton breeding program.

Summary Fine mapping QTLs and identifying candidate genes for cotton fibre‐quality and yield traits would be beneficial to cotton breeding. Here, we constructed a high‐density genetic map by specific‐locus amplified fragment sequencing (SLAF‐seq) to identify QTLs associated with fibre‐quality and yield traits using 239 recombinant inbred lines (RILs), which was developed from LMY22 (a high‐yield Gossypium hirsutumL. cultivar) × LY343 (a superior fibre‐quality germplasm with G. barbadenseL. introgressions). The genetic map spanned 3426.57 cM, including 3556 SLAF‐based SNPs and 199 SSR marker loci. A total of 104 QTLs, including 67 QTLs for fibre quality and 37 QTLs for yield traits, were identified with phenotypic data collected from 7 environments. Among these, 66 QTLs were co‐located in 19 QTL clusters on 12 chromosomes, and 24 QTLs were detected in three or more environments and determined to be stable. We also investigated the genomic components of LY343 and their contributions to fibre‐related traits by deep sequencing the whole genome of LY343, and we found that genomic components from G. hirsutum races (which entered LY343 via its G. barbadense parent) contributed more favourable alleles than those from G. barbadense. We further identified six putative candidate genes for stable QTLs, including Gh_A03G1147 (GhPEL6), Gh_D07G1598 (GhCSLC6) and Gh_D13G1921 (GhTBL5) for fibre‐length QTLs and Gh_D03G0919 (GhCOBL4), Gh_D09G1659 (GhMYB4) and Gh_D09G1690 (GhMYB85) for lint‐percentage QTLs. Our results provide comprehensive insight into the genetic basis of the formation of fibre‐related traits and would be helpful for cloning fibre‐development‐related genes as well as for marker‐assisted genetic improvement in cotton.

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A VIGS method by agroinoculation of cotton seeds was developed for gene silencing in young seedlings and roots, and applied in functional analysis of GhBI-1 in response to salt stress. Virus-induced gene silencing (VIGS) has been widely used to investigate the functions of genes expressed in mature leaves, but not yet in young seedlings or roots of cotton (Gossypium hirsutum L.). Here, we developed a simple and effective VIGS method for silencing genes in young cotton seedlings and roots by soaking naked seeds in Agrobacterium cultures carrying tobacco rattle virus (TRV)-VIGS vectors. When the naked seeds were soaked in Agrobacterium cultures with an OD600 of 1.5 for 90 min, it was optimal for silencing genes effectively in young seedlings as clear photo-bleaching phenotype in the newly emerging leaves of pTRV:GhCLA1 seedlings were observed at 12-14 days post inoculation. Silencing of GhPGF (cotton pigment gland formation) by this method resulted in a 90% decrease in transcript abundances of the gene in roots at the early development stage. We further used the tool to investigate function of GhBI-1 (cotton Bax inhibitor-1) gene in response to salt stress and demonstrated that GhBI-1 might play a protective role under salt stress by suppressing stress-induced cell death in cotton. Our results showed that the newly established VIGS method is a powerful tool for elucidating functions of genes in cotton, especially the genes expressed in young seedlings and roots.

The improvement of fiber quality is an essential goal in cotton breeding. In our previous studies, several quantitative trait loci (QTLs) contributing to improved fiber quality were identified in different introgressed chromosomal regions from Sea Island cotton (Gossypium barbadense L.) in a primary introgression population (Pop. A) of upland cotton (G. hirsutum L.). In the present study, to finely map introgressed major QTLs and accurately dissect the genetic contribution of the target introgressed chromosomal segments, we backcrossed two selected recombinant inbred lines (RILs) that presented desirable high fiber quality with their high lint-yielding recurrent parent to ultimately develop two secondary mapping populations (Pop. B and Pop. C). Totals of 20 and 27 QTLs for fiber quality were detected in Pop. B and Pop. C, respectively, including four and five for fiber length, four and eight for fiber micronaire, two and four for fiber uniformity, five and four for fiber elongation, and six and four for fiber strength, respectively. Two QTLs for lint percentage were detected only in Pop. C. In addition, seven stable QTLs were identified, including two for both fiber length and fiber strength and three for fiber elongation. Five QTL clusters for fiber quality were identified in the introgressed chromosomal regions, and negative effects of these chromosomal regions on lint percentage (a major lint yield parameter) were not observed. Candidate genes with a QTL-cluster associated with fiber strength and fiber length in the introgressed region of Chr.7 were further identified. The results may be helpful for revealing the genetic basis of superior fiber quality contributed by introgressed alleles from G. barbadense. Possible strategies involving marker-assisted selection (MAS) for simultaneously improving upland cotton fiber quality and lint yield in breeding programs was also discussed.