Cotton is an important economic crop, and many loci for important traits have been identified, but it remains challenging and time-consuming to identify candidate or causal genes/variants and clarify their roles in phenotype formation and regulation. Here, we first collected and integrated the multi-omics datasets including 25 genomes, transcriptomes in 76 tissue samples, epigenome data of five species and metabolome data of 768 metabolites from four tissues, and genetic variation, trait and transcriptome datasets from 4180 cotton accessions. Then, a cotton multi-omics database (CottonMD, http://yanglab.hzau.edu.cn/CottonMD/) was constructed. In CottonMD, multiple statistical methods were applied to identify the associations between variations and phenotypes, and many easy-to-use analysis tools were provided to help researchers quickly acquire the related omics information and perform multi-omics data analysis. Two case studies demonstrated the power of CottonMD for identifying and analyzing the candidate genes, as well as the great potential of integrating multi-omics data for cotton genetic breeding and functional genomics research.

The rapid accumulation of molecular data motivates development of innovative approaches to computationally characterize sequences, structures and functions of biological and chemical molecules in an efficient, accessible and accurate manner. Notwithstanding several computational tools that characterize protein or nucleic acids data, there are no one-stop computational toolkits that comprehensively characterize a wide range of biomolecules. We address this vital need by developing a holistic platform that generates features from sequence and structural data for a diverse collection of molecule types. Our freely available and easy-to-use iFeatureOmega platform generates, analyzes and visualizes 189 representations for biological sequences, structures and ligands. To the best of our knowledge, iFeatureOmega provides the largest scope when directly compared to the current solutions, in terms of the number of feature extraction and analysis approaches and coverage of different molecules. We release three versions of iFeatureOmega including a webserver, command line interface and graphical interface to satisfy needs of experienced bioinformaticians and less computer-savvy biologists and biochemists. With the assistance of iFeatureOmega, users can encode their molecular data into representations that facilitate construction of predictive models and analytical studies. We highlight benefits of iFeatureOmega based on three research applications, demonstrating how it can be used to accelerate and streamline research in bioinformatics, computational biology, and cheminformatics areas. The iFeatureOmega webserver is freely available at http://ifeatureomega.erc.monash.edu and the standalone versions can be downloaded from https://github.com/Superzchen/iFeatureOmega-GUI/ and https://github.com/Superzchen/iFeatureOmega-CLI/.

Brassinosteroid (BR), a growth-promoting phytohormone, regulates many plant growth processes including cell development. However, the mechanism by which BR regulates fiber growth is poorly understood. Cotton (Gossypium hirsutum) fibers are an ideal single-cell model in which to study cell elongation due to their length. Here we report that BR controls cotton fiber elongation by modulating very-long-chain fatty acid (VLCFA) biosynthesis. BR deficiency reduces the expression of 3-ketoacyl-CoA synthases (GhKCSs), the rate-limiting enzymes involved in VLCFA biosynthesis, leading to lower saturated VLCFA contents in pagoda1 (pag1) mutant fibers. In vitro ovule culture experiments show that BR acts upstream of VLCFAs. Silencing of BRI1-EMS-SUPPRESOR 1.4 (GhBES1.4), encoding a master transcription factor of the BR signaling pathway, significantly reduces fiber length, whereas GhBES1.4 overexpression produces longer fibers. GhBES1.4 regulates endogenous VLCFA contents and directly binds to BR RESPONSE ELEMENTS (BRREs) in the GhKCS10_At promoter region, which in turn regulates GhKCS10_At expression to increase endogenous VLCFA contents. GhKCS10_At overexpression promotes cotton fiber elongation, whereas GhKCS10_At silencing inhibits cotton fiber growth, supporting a positive regulatory role for GhKCS10_At in fiber elongation. Overall, these results uncover a mechanism of fiber elongation through crosstalk between BR and VLCFAs at the single-cell level.

Sucrose non-fermenting-1-related protein kinase 2 (SnRK2) is a plant-specific serine/threonine kinase family involved in the abscisic acid (ABA) signaling pathway and responds to osmotic stress. A genome-wide analysis of this protein family has been conducted previously in some plant species, but little is known about SnRK2 genes in upland cotton (Gossypium hirsutum L.). The recent release of the G. hirsutum genome sequence provides an opportunity to identify and characterize the SnRK2 kinase family in upland cotton. We identified 20 putative SnRK2 sequences in the G. hirsutum genome, designated as GhSnRK2.1 to GhSnRK2.20. All of the sequences encoded hydrophilic proteins. Phylogenetic analysis showed that the GhSnRK2 genes were classifiable into three groups. The chromosomal location and phylogenetic analysis of the cotton SnRK2 genes indicated that segmental duplication likely contributed to the diversification and evolution of the genes. The gene structure and motif composition of the cotton SnRK2 genes were analyzed. Nine exons were conserved in length among all members of the GhSnRK2 family. Although the C-terminus was divergent, seven conserved motifs were present. All GhSnRK2s genes showed expression patterns under abiotic stress based on transcriptome data. The expression profiles of five selected genes were verified in various tissues by quantitative real-time RT-PCR (qRT-PCR). Transcript levels of some family members were up-regulated in response to drought, salinity or ABA treatments, consistent with potential roles in response to abiotic stress. This study is the first comprehensive analysis of SnRK2 genes in upland cotton. Our results provide the fundamental information for the functional dissection of GhSnRK2s and vital availability for the improvement of plant stress tolerance using GhSnRK2s.

Previous reports have shown that, when Verticillium dahliae localizes at the root surface, many microRNAs (miRNAs) were identified at the early induction stage. Here, we constructed two groups from two timepoints of small RNA (sRNA) in cotton root responses to V. dahliae at the later induction stage, pathogen localizing in the interior of root tissue. We identified 71 known and 378 novel miRNAs from six libraries of the pathogen-induced and the control sRNAs. Combined with degradome and sRNA sequencing, 178 corresponding miRNA target genes were identified, in which 40 target genes from differentially expressed miRNAs were primarily associated with oxidation-reduction and stress responses. More importantly, we characterized the cotton miR477-CBP60A module in the later response of the plant to V. dahliae infection. A β-glucuronidase fusion reporter and cleavage site analysis showed that ghr-miR477 directly cleaved the messenger RNA of GhCBP60A in the posttranscriptional process. The ghr-miR477-silencing decreased plant resistance to this fungus, while the knockdown of GhCBP60A increased plant resistance, which regulated GhICS1 expression to determine salicylic acid level. Our data documented that numerous later-inducible miRNAs in the plant response to V. dahliae, suggesting that these miRNAs play important roles in plant resistance to vascular disease.