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.
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.
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