CottonMD: a multi-omics database for cotton biological study

Natural variation in GhROPGEF5 contributes to longer and stronger cotton fibers

Length and strength are key parameters impacting the quality of textiles that can be produced from cotton fibers, and therefore are important considerations in cotton breeding. Through map-based cloning and function analysis, we demonstrated that GhROPGEF5, encoding a ROP guanine nucleotide exchange factor, was the gene controlling fiber length and strength at qFSA10.1. Evolutionary analysis revealed that a base deletion in the third exon of GhROPGEF5 resulting in superior fiber length and strength was a rare mutation occurring in a tiny percentage of Upland cottons, with reduced fiber yield hindering its spread. GhROPGEF5 interacted with and activated GhROP10. Knockout or mutation of GhROPGEF5 resulted a loss of the ability to activate GhROP10. Knockout of GhROPGEF5 or GhROP10 affected the expression of many downstream genes associated with fiber elongation and secondary wall deposition, prolonged fiber elongation and delayed secondary wall deposition, producing denser fiber helices and increasing fiber length and strength. These results revealed new molecular aspects of fiber development and revealed a rare favorable allele for improving fiber quality in cotton breeding.

Systematic Analysis of Cotton RING E3 Ubiquitin Ligase Genes Reveals Their Potential Involvement in Salt Stress Tolerance

The Really Interesting New Gene (RING) E3 ubiquitin ligases represent the largest class of E3 ubiquitin ligases involved in protein degradation and play a pivotal role in plant growth, development, and environmental responses. Despite extensive studies in numerous plant species, the functions of RING E3 ligases in cotton remain largely unknown. In this study, we performed systematic identification, characterization, and expression analysis of RING genes in cotton. A total of 514, 509, and 914 RING genes were identified in Gossypium arboretum, G. raimondii, and G. hirsutum, respectively. Duplication analysis indicates that segmental duplication may be the primary mechanism responsible for the expansion of the cotton RING gene family. Moreover, the Ka/Ks analysis suggests that these duplicated genes have undergone purifying selection throughout the evolutionary history of cotton. Notably, 393 G. hirsutum RING genes exhibited differential expression in response to salt stress. The overexpression of the specific C3H2C3 RING gene, GhZFRG1, in Arabidopsis resulted in enhanced tolerance to salt stress. This study contributes to our understanding of the evolution of cotton RING ligases and paves the way for further functional analysis of the RING E3 ligase genes in cotton.

Genome-wide analysis of the cotton COBRA-like gene family and functional characterization of GhCOBL22 in relation to drought tolerance

BACKGROUND

The COBRA-like (COBL) gene family is a crucial glycosylphosphatidylinositol (GPI)-anchored proteins that participate in various biological processes in plants by regulating the arrangement of cell wall microfibrils. While the functions of COBL genes have been analyzed in several plant species, their roles in cotton's response to abiotic stress remain unexplored.

RESULTS

This study identified and characterized the COBL gene family in Gossypium hirsutum, revealing a total of 39 COBL family members classified into five subgroups. Transcriptome analysis indicated that the transcription levels of several GhCOBL genes were upregulated following PEG treatment, with GhCOBL22 being significantly induced. Further silencing of the GhCOBL22 gene through virus-induced gene silencing (VIGS) technology demonstrated that this gene's silencing reduced cotton's drought stress tolerance. Under drought stress conditions, the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) enzymes, along with proline (PRO) content, were lower in GhCOBL22-silenced plants compared to control plants, while the accumulation of malondialdehyde (MDA) was significantly higher. Moreover, silencing the GhCOBL22 gene also led to reductions in the levels of cellulose, hemicellulose, and lignin content in cotton leaves.

CONCLUSION

A systematic survey of gene structure, motif composition, and evolutionary relationships of the COBL gene family was conducted in Gossypium hirsutum. Subsequent expression and functional studies indicated that GhCOBL22 plays a significant role in cotton's drought tolerance. These findings enhance our understanding of the biological functions of the COBL family and highlight the critical role of the GhCOBL22 gene in cotton's response to drought stress.

A GWAS identified loci and candidate genes associated with fiber quality traits in a new cotton MAGIC population

KEY MESSAGE

GWAS of a new MAGIC population containing alleles from five tetraploid Gossypium species identified novel fiber QTL and confirmed previously identified stable QTL. Identification of loci and underlying genes for fiber quality traits will facilitate genetic improvement in cotton fiber quality. In this research, a genome-wide association study (GWAS) was carried out for fiber quality attributes using a new multi-parent advanced generation inter-cross (MAGIC) population consisting of 372 recombinant inbred lines (RILs). Sixteen parents including 12 exotic germplasm lines derived from five tetraploid Gossypium species and 4 Upland cotton varieties were intercrossed to develop the population. Both RILs and parental lines were evaluated at three locations, College Station, Texas; Las Cruses, New Mexico; and Stoneville, Mississippi, from 2016 through 2023. Fiber length (UHM) had positive correlation with strength (STR) and length uniformity (UNI) and a negative correlation with micronaire (MIC) and elongation (ELO). By combining all the data from all locations, we identified significant SNPs for ELO, UHM, and UNI while STR and MIC were location dependent. These results suggest an important role of genotype by environment interaction in a GWAS of fiber traits. Twenty possible novel fiber QTL were identified: 10 for STR, three for UNI, and seven for MIC. The QTL for ELO (Chr.D04: 53-Mb), UHM (Chr.D11: 24-Mb), and UNI (Chr.D04: 34-Mb) were stable across multiple environments and may be useful for marker-assisted selection to improve fiber quality. For STR, we found candidate genes Gh_A07G1574 and Gh_A07G1581 to be present in the previously identified QTL region (Chr.A07: 77-Mb) on chromosome A07. Identified loci and their corresponding candidate genes will be useful to improve fiber quality via marker-assisted selection in a cotton breeding.

Identification and Analysis of the Plasma Membrane H+-ATPase Gene Family in Cotton and Its Roles in Response to Salt Stress

Plant plasma membrane (PM) H+-ATPase functions as a proton-motive force by exporting cellular protons to establish a transmembrane chemical gradient of H+ ions and an accompanying electrical gradient. These gradients are crucial for plant growth and development and for plant responses to abiotic and biotic stresses. In this study, a comprehensive identification of the PM H+-ATPase gene family was conducted across four cotton species. Specifically, 14 genes were identified in the diploid species Gossypium arboreum and Gossypium raimondii, whereas 39 and 43 genes were identified in the tetraploid species Gossypium hirsutum and Gossypium barbadense, respectively. The characteristics of this gene family were subsequently compared and analyzed using bioinformatics. Chromosomal localization and collinearity analyses elucidated the distribution characteristics of this gene family within the cotton genomes. Gene structure and phylogenetic analyses demonstrated the conservation of this family across cotton species, whereas the examination of cis-acting elements in gene promoters highlighted their involvement in environmental stress and hormone response categories. An expression profile analysis revealed eight genes whose expression was upregulated under salt stress conditions, and quantitative real-time PCR results suggested that the cotton PM H+-ATPase genes may play crucial roles in conferring resistance to salt stress. These findings establish a robust foundation for subsequent investigations into the functions of cotton PM H+-ATPase genes and may offer valuable insights for selecting genes for resistance breeding programs.

TRANSPARENT TESTA 16 collaborates with the MYB-bHLH-WD40 transcriptional complex to produce brown fiber cotton

Naturally colored cotton (NCC; Gossypium spp.) does not require additional chemical dyeing and is an environmentally friendly textile material with great research potential and applications. Our previous study using linkage and association mapping identified TRANSPARENT TESTA 2 (Gh_TT2) as acting on the proanthocyanin synthesis pathway. However, limited information is available about the genetic regulatory network of NCC. Here, we verified the effectiveness of Gh_TT2 and the roles of Gh_TT2 and red foliated mutant gene (Re) in pigment formation and deposition of brown fiber cotton (BFC). Variations in Gh_TT2 derived from interspecific hybridization between Gossypium barbadense acc. Pima 90-53 and Gossypium hirsutum acc. Handan208 resulted in gene expression differences, thereby causing phenotypic variation. Additionally, the MYB-bHLH-WD complex was found to be negatively modulated by TRANSPARENT TESTA 16/ARABIDOPSIS BSISTER (TT16/ABS). RNA-seq suggested that differential expression of homologous genes of key enzymes in the proanthocyanin synthesis pathway strongly contributes to the color rendering of natural dark brown and light brown cotton. Our study proposes a regulatory model in BFC, which will provide theoretical guidance for the genetic improvement of NCC.

New perspectives of post-GWAS analyses: From markers to causal genes for more precise crop breeding

Crop breeding advancement is hindered by the imperfection of methods to reveal genes underlying key traits. Genome-wide Association Study (GWAS) is one such method, identifying genomic regions linked to phenotypes. Post-GWAS analyses predict candidate genes and assist in causative mutation (CM) recognition. Here, we assess post-GWAS approaches, address limitations in omics data integration and stress the importance of evaluating associated variants within a broader context of publicly available datasets. Recent advances in bioinformatics tools and genomic strategies for CM identification and allelic variation exploration are reviewed. We discuss the role of markers and marker panel development for more precise breeding. Finally, we highlight the perspectives and challenges of GWAS-based CM prediction for complex quantitative traits.

The era of panomics-driven gene discovery in plants

Panomics is an approach to integrate multiple 'omics' datasets, generated using different individuals or natural variations. Considering their diverse phenotypic spectrum, the phenome is inherently associated with panomics-based science, which is further combined with genomics, transcriptomics, metabolomics, and other omics techniques, either independently or collectively. Panomics has been accelerated through recent technological advancements in the field of genomics that enable the detection of population-wide structural variations (SVs) and hence offer unprecedented insights into the genetic variations contributing to important agronomic traits. The present review provides the recent trends of panomics-driven gene discovery toward various traits related to plant development, stress tolerance, accumulation of specialized metabolites, and domestication/dedomestication. In addition, the success stories are highlighted in the broader context of enhancing crop productivity.

Evolution and subfunctionalization of CIPK6 homologous genes in regulating cotton drought resistance

The occurrence of whole-genome duplication or polyploidy may promote plant adaptability to harsh environments. Here, we clarify the evolutionary relationship of eight GhCIPK6 homologous genes in upland cotton (Gossypium hirsutum). Gene expression and interaction analyses indicate that GhCIPK6 homologous genes show significant functional changes after polyploidy. Among these, GhCIPK6D1 and GhCIPK6D3 are significantly up-regulated by drought stress. Functional studies reveal that high GhCIPK6D1 expression promotes cotton drought sensitivity, while GhCIPK6D3 expression promotes drought tolerance, indicating clear functional differentiation. Genetic and biochemical analyses confirm the synergistic negative and positive regulation of cotton drought resistance through GhCBL1A1-GhCIPK6D1 and GhCBL2A1-GhCIPK6D3, respectively, to regulate stomatal movement by controlling the directional flow of K+ in guard cells. These results reveal differentiated roles of GhCIPK6 homologous genes in response to drought stress in upland cotton following polyploidy. The work provides a different perspective for exploring the functionalization and subfunctionalization of duplicated genes in response to polyploidization.

Genomic Analysis of Brassinosteroid Biosynthesis Gene Family Reveals Its Roles in Cotton Development across Gossypium Species

Cotton is a globally significant economic crop. Brassinosteroids (BRs) are crucial to cotton development. This study systematically analyzed the BR synthase gene family in four cotton species and identified 60 BR genes: 20 in Gossypium hirsutum (GhBRs), 20 in G. barbadense (GbBRs), 10 in G. arboreum (GaBRs), and 10 in G. raimondii (GrBRs). The analysis was extended to chromosomal localization, evolutionary relationships, domain features, and cis-regulatory elements in the promoter regions of BR synthase genes. The results showed that the BR synthase genes were evenly distributed across different subgenomes and chromosomes. Bioinformatics analyses revealed high conservation of amino acid sequences, secondary structures, and conserved domains among the subfamily members, which is closely linked to their pivotal roles in the BR biosynthesis pathway. Cis-element distribution analysis of the BR synthase genes further underscored the complexity of BR gene expression regulation, which is influenced by multiple factors, including plant hormones, abiotic stress, and transcription factors. Expression profiling of GhBRs genes in various cotton tissues and developmental stages highlighted the key roles of GhROT3-1 and GhDET2-1 in fiber elongation and initiation, respectively. Protein-protein interactions and transcription factor analyses further elucidated the regulatory mechanisms of GhROT3-1 and GhDET2-1 in cotton growth and development. This study lays a theoretical foundation for understanding the role of the BR signaling pathway in cotton development, facilitating molecular breeding.

Identification of the Gossypium hirsutum SDG Gene Family and Functional Study of GhSDG59 in Response to Drought Stress

SET-domain group histone methyltransferases (SDGs) are known to play crucial roles in plant responses to abiotic stress. However, their specific function in cotton's response to drought stress has not been well understood. This study conducted a comprehensive analysis of the SDG gene family in Gossypium hirsutum, identifying a total of 82 SDG genes. An evolutionary analysis revealed that the SDG gene family can be divided into eight subgroups. The expression analysis shows that some GhSDG genes are preferentially expressed in specific tissues, indicating their involvement in cotton growth and development. The transcription level of some GhSDG genes is induced by PEG, with GhSDG59 showing significant upregulation upon polyethylene glycol (PEG) treatment. Quantitative polymerase chain reaction (qPCR) analysis showed that the accumulation of transcripts of the GhSDG59 gene was significantly upregulated under drought stress. Further functional studies using virus-induced gene silencing (VIGS) revealed that silencing GhSDG59 reduced cotton tolerance to drought stress. Under drought conditions, the proline content, superoxide dismutase (SOD) and peroxidase (POD) enzyme activities in the GhSDG59-silenced plants were significantly lower than in the control plants, while the malondialdehyde (MDA) content was significantly higher. Transcriptome sequencing showed that silencing the GhSDG59 gene led to significant changes in the expression levels of 1156 genes. The KEGG enrichment analysis revealed that these differentially expressed genes (DEGs) were mainly enriched in the carbon metabolism and the starch and sucrose metabolism pathways. The functional annotation analysis identified known drought-responsive genes, such as ERF, CIPK, and WRKY, among these DEGs. This indicates that GhSDG59 is involved in the drought-stress response in cotton by affecting the expression of genes related to the carbon metabolism and the starch and sucrose metabolism pathways, as well as known drought-responsive genes. This analysis provides valuable information for the functional genomic study of SDGs and highlights potential beneficial genes for genetic improvement and breeding in cotton.

Anthocyanin gene enrichment in the distal region of cotton chromosome A07: mechanisms of reproductive organ coloration

Introduction

The biosynthesis of secondary metabolites like anthocyanins is often governed by metabolic gene clusters (MGCs) in the plant ancestral genome. However, the existence of gene clusters specifically regulating anthocyanin accumulation in certain organs is not well understood.

Methods and results

In this study, we identify MGCs linked to the coloration of cotton reproductive organs, such as petals, spots, and fibers. Through genetic analysis and map-based cloning, we pinpointed key genes on chromosome A07, such as PCC/GhTT19, which is involved in anthocyanin transport, and GbBM and GhTT2-3A, which are associated with the regulation of anthocyanin and proanthocyanidin biosynthesis. Our results demonstrate the coordinated control of anthocyanin and proanthocyanidin pathways, highlighting the evolutionary significance of MGCs in plant adaptation. The conservation of these clusters in cotton chromosome A07 across species underscores their importance in reproductive development and color variation. Our study sheds light on the complex biosynthesis and transport mechanisms for plant pigments, emphasizing the role of transcription factors and transport proteins in pigment accumulation.

Discussion

This research offers insights into the genetic basis of color variation in cotton reproductive organs and the potential of MGCs to enhance our comprehension of plant secondary metabolism.

Comparative proteomic analysis of seed germination between allotetraploid cotton Gossypium hirsutum and Gossypium barbadense

Seed germination, a key initial event in the plant life cycle, directly affects cotton yield and quality. Gossypium barbadense and Gossypium hirsutum gradually evolved through polyploidization, resulting in different characteristics, and this interspecific variation lacks genetic and molecular explanation. This work aimed to compare the proteomes between G. barbadense and G. hirsutum during seed germination. Here, we identified 2740 proteins for G. barbadense and 3758 for G. hirsutum. In the initial state, proteins in two cotton involved similar bioprocess, such as sugar metabolism, DNA repairing, and ABA signaling pathway. However, in the post-germination stage, G. hirsutum expressed more protein related to redox homeostasis, peroxidase activity, and pathogen interactions. Analyzing the different expression patterns of 915 single-copy orthogroups between the two kinds of cotton indicated that most of the differentially expressed proteins in G. barbadense were related to carbon metabolism. In contrast, most proteins in G. hirsutum were associated with stress response. Besides that, by proteogenomic analysis, we found 349 putative non-canonical peptides, which may be involved in plant development. These results will help to understand the different characteristics of these two kinds of cotton, such as fiber quality, yield, and adaptability. SIGNIFICANCE STATEMENT: Cotton is the predominant natural fiber crop worldwide; Gossypium barbadense and Gossypium hirsutum have evolved through polyploidization to produce differing traits. However, given their specific features, the divergence of mechanisms underlying seed germination between G. hirsutum and G. barbadense has not been discussed. Here, we explore what protein contributes to interspecific differences between G. barbadense and G. hirsutum during the seed germination period. This study helps to elucidate the evolution and domestication history of cotton polyploids and may allow breeders to understand their domestication history better and improve fiber quality and adaptability.

Plant genomic resources at National Genomics Data Center: assisting in data-driven breeding applications

Genomic data serve as an invaluable resource for unraveling the intricacies of the higher plant systems, including the constituent elements within and among species. Through various efforts in genomic data archiving, integrative analysis and value-added curation, the National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), has successfully established and currently maintains a vast amount of database resources. This dedicated initiative of the NGDC facilitates a data-rich ecosystem that greatly strengthens and supports genomic research efforts. Here, we present a comprehensive overview of central repositories dedicated to archiving, presenting, and sharing plant omics data, introduce knowledgebases focused on variants or gene-based functional insights, highlight species-specific multiple omics database resources, and briefly review the online application tools. We intend that this review can be used as a guide map for plant researchers wishing to select effective data resources from the NGDC for their specific areas of study.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42994-023-00134-4.

Isolation and Functional Characterization of a Constitutive Promoter in Upland Cotton (Gossypium hirsutum L.)

Multiple cis-acting elements are present in promoter sequences that play critical regulatory roles in gene transcription and expression. In this study, we isolated the cotton FDH (Fiddlehead) gene promoter (pGhFDH) using a real-time reverse transcription-PCR (qRT-PCR) expression analysis and performed a cis-acting elements prediction analysis. The plant expression vector pGhFDH::GUS was constructed using the Gateway approach and was used for the genetic transformation of Arabidopsis and upland cotton plants to obtain transgenic lines. Histochemical staining and a β-glucuronidase (GUS) activity assay showed that the GUS protein was detected in the roots, stems, leaves, inflorescences, and pods of transgenic Arabidopsis thaliana lines. Notably, high GUS activity was observed in different tissues. In the transgenic lines, high GUS activity was detected in different tissues such as leaves, stalks, buds, petals, androecium, endosperm, and fibers, where the pGhFDH-driven GUS expression levels were 3-10-fold higher compared to those under the CaMV 35S promoter at 10-30 days post-anthesis (DPA) during fiber development. The results indicate that pGhFDH can be used as an endogenous constitutive promoter to drive the expression of target genes in various cotton tissues to facilitate functional genomic studies and accelerate cotton molecular breeding.

SoyMD: a platform combining multi-omics data with various tools for soybean research and breeding

Advanced multi-omics technologies offer much information that can uncover the regulatory mechanisms from genotype to phenotype. In soybean, numerous multi-omics databases have been published. Although they cover multiple omics, there are still limitations when it comes to the types and scales of omics datasets and analysis methods utilized. This study aims to address these limitations by collecting and integrating a comprehensive set of multi-omics datasets. This includes 38 genomes, transcriptomes from 435 tissue samples, 125 phenotypes from 6686 accessions, epigenome data involving histone modification, transcription factor binding, chromosomal accessibility and chromosomal interaction, as well as genetic variation data from 24 501 soybean accessions. Then, common analysis pipelines and statistical methods were applied to mine information from these multi-omics datasets, resulting in the successful establishment of a user-friendly multi-omics database called SoyMD (https://yanglab.hzau.edu.cn/SoyMD/#/). SoyMD provides researchers with efficient query options and analysis tools, allowing them to swiftly access relevant omics information and conduct comprehensive multi-omics data analyses. Another notable feature of SoyMD is its capability to facilitate the analysis of candidate genes, as demonstrated in the case study on seed oil content. This highlights the immense potential of SoyMD in soybean genetic breeding and functional genomics research.

MODMS: a multi-omics database for facilitating biological studies on alfalfa (Medicago sativa L.)

Alfalfa (Medicago sativa L.) is a globally important forage crop. It also serves as a vegetable and medicinal herb because of its excellent nutritional quality and significant economic value. Multi-omics data on alfalfa continue to accumulate owing to recent advances in high-throughput techniques, and integrating this information holds great potential for expediting genetic research and facilitating advances in alfalfa agronomic traits. Therefore, we developed a comprehensive database named MODMS (multi-omics database of M. sativa) that incorporates multiple reference genomes, annotations, comparative genomics, transcriptomes, high-quality genomic variants, proteomics, and metabolomics. This report describes our continuously evolving database, which provides researchers with several convenient tools and extensive omics data resources, facilitating the expansion of alfalfa research. Further details regarding the MODMS database are available at https://modms.lzu.edu.cn/.

A comprehensive overview of cotton genomics, biotechnology and molecular biological studies

Cotton is an irreplaceable economic crop currently domesticated in the human world for its extremely elongated fiber cells specialized in seed epidermis, which makes it of high research and application value. To date, numerous research on cotton has navigated various aspects, from multi-genome assembly, genome editing, mechanism of fiber development, metabolite biosynthesis, and analysis to genetic breeding. Genomic and 3D genomic studies reveal the origin of cotton species and the spatiotemporal asymmetric chromatin structure in fibers. Mature multiple genome editing systems, such as CRISPR/Cas9, Cas12 (Cpf1) and cytidine base editing (CBE), have been widely used in the study of candidate genes affecting fiber development. Based on this, the cotton fiber cell development network has been preliminarily drawn. Among them, the MYB-bHLH-WDR (MBW) transcription factor complex and IAA and BR signaling pathway regulate the initiation; various plant hormones, including ethylene, mediated regulatory network and membrane protein overlap fine-regulate elongation. Multistage transcription factors targeting CesA 4, 7, and 8 specifically dominate the whole process of secondary cell wall thickening. And fluorescently labeled cytoskeletal proteins can observe real-time dynamic changes in fiber development. Furthermore, research on the synthesis of cotton secondary metabolite gossypol, resistance to diseases and insect pests, plant architecture regulation, and seed oil utilization are all conducive to finding more high-quality breeding-related genes and subsequently facilitating the cultivation of better cotton varieties. This review summarizes the paramount research achievements in cotton molecular biology over the last few decades from the above aspects, thereby enabling us to conduct a status review on the current studies of cotton and provide strong theoretical support for the future direction.

Alterations in Growth Habit to Channel End-of-Season Perennial Reserves towards Increased Yield and Reduced Regrowth after Defoliation in Upland Cotton (Gossypium hirsutum L.)

Cotton (Gossypium spp.) is the primary source of natural textile fiber in the U.S. and a major crop in the Southeastern U.S. Despite constant efforts to increase the cotton fiber yield, the yield gain has stagnated. Therefore, we undertook a novel approach to improve the cotton fiber yield by altering its growth habit from perennial to annual. In this effort, we identified genotypes with high-expression alleles of five floral induction and meristem identity genes (FT, SOC1, FUL, LFY, and AP1) from an Upland cotton mini-core collection and crossed them in various combinations to develop cotton lines with annual growth habit, optimal flowering time, and enhanced productivity. To facilitate the characterization of genotypes with the desired combinations of stacked alleles, we identified molecular markers associated with the gene expression traits via genome-wide association analysis using a 63 K SNP Array. Over 14,500 SNPs showed polymorphism and were used for association analysis. A total of 396 markers showed associations with expression traits. Of these 396 markers, 159 were mapped to genes, 50 to untranslated regions, and 187 to random genomic regions. Biased genomic distribution of associated markers was observed where more trait-associated markers mapped to the cotton D sub-genome. Many quantitative trait loci coincided at specific genomic regions. This observation has implications as these traits could be bred together. The analysis also allowed the identification of candidate regulators of the expression patterns of these floral induction and meristem identity genes whose functions will be validated.

Genome-Wide Identification and Expression Analysis of RLCK-VII Subfamily Genes Reveal Their Roles in Stress Responses of Upland Cotton

Receptor-like cytoplasmic kinase VII (RLCK-VII) subfamily members are vital players in plant innate immunity and are also involved in plant development and abiotic stress tolerance. As a widely cultivated textile crop, upland cotton (Gossypium hirsutum) attaches great importance to the cotton industry worldwide. To obtain details of the composition, phylogeny, and putative function of RLCK-VII genes in upland cotton, genome-wide identification, evolutionary event analysis, and expression pattern examination of RLCK-VII subfamily genes in G. hirsutum were performed. There are 129 RLCK-VII members in upland cotton (GhRLCKs) and they were divided into nine groups based on their phylogenetic relationships. The gene structure and sequence features are relatively conserved within each group, which were divided based on their phylogenetic relationships, and consistent with those in Arabidopsis. The phylogenetic analysis results showed that RLCK-VII subfamily genes evolved in plants before the speciation of Arabidopsis and cotton, and segmental duplication was the major factor that caused the expansion of GhRLCKs. The diverse expression patterns of GhRLCKs in response to abiotic stresses (temperature, salt, and drought) and V. dahliae infection were observed. The candidates that may be involved in cotton's response to these stresses are highlighted. GhRLCK7 (GhRLCK7A and D), which is notably induced by V. dahliae infection, was demonstrated to positively regulate cotton defense against V. dahliae by the loss-of-function assay in cotton. These findings shed light on the details of the RLCK-VII subfamily in cotton and provide a scaffold for the further function elucidation and application of GhRLCKs for the germplasm innovation of cotton.

Genome-Wide Identification and Functional Analysis of RF2 Gene Family and the Critical Role of GhRF2-32 in Response to Drought Stress in Cotton

Cotton is an important natural fiber crop. The RF2 gene family is a member of the bZIP transcription factor superfamily, which plays an important role in plant resistance to environmental stresses. In this paper, the RF2 gene family of four cotton species was analyzed genome-wide, and the key gene RF2-32 was cloned for functional verification. A total of 113 RF2 genes were identified in the four cotton species, and the RF2 family was relatively conserved during the evolution of cotton. Chromosome mapping and collinear analysis indicated that fragment replication was the main expansion mode of RF2 gene family during evolution. Cis-element analysis showed that there were many elements related to light response, hormone response and abiotic stress response in the promoters of RF2 genes. The transcriptome and qRT-PCR analysis of RF2 family genes in upland cotton showed that RF2 family genes responded to salt stress and drought stress. GhRF2-32 protein was localized in the cell nucleus. Silencing the GhRF2-32 gene showed less leaf wilting and increased total antioxidant capacity under drought and salt stress, decreased malondialdehyde content and increased drought and salt tolerance. This study revealed the evolutionary and functional diversity of the RF2 gene family, which laid a foundation for the further study of stress-resistant genes in cotton.

Comparative analysis of tissue-specific genes in maize based on machine learning models: CNN performs technically best, LightGBM performs biologically soundest

Introduction: With the advancement of RNA-seq technology and machine learning, training large-scale RNA-seq data from databases with machine learning models can generally identify genes with important regulatory roles that were previously missed by standard linear analytic methodologies. Finding tissue-specific genes could improve our comprehension of the relationship between tissues and genes. However, few machine learning models for transcriptome data have been deployed and compared to identify tissue-specific genes, particularly for plants. Methods: In this study, an expression matrix was processed with linear models (Limma), machine learning models (LightGBM), and deep learning models (CNN) with information gain and the SHAP strategy based on 1,548 maize multi-tissue RNA-seq data obtained from a public database to identify tissue-specific genes. In terms of validation, V-measure values were computed based on k-means clustering of the gene sets to evaluate their technical complementarity. Furthermore, GO analysis and literature retrieval were used to validate the functions and research status of these genes. Results: Based on clustering validation, the convolutional neural network outperformed others with higher V-measure values as 0.647, indicating that its gene set could cover as many specific properties of various tissues as possible, whereas LightGBM discovered key transcription factors. The combination of three gene sets produced 78 core tissue-specific genes that had previously been shown in the literature to be biologically significant. Discussion: Different tissue-specific gene sets were identified due to the distinct interpretation strategy for machine learning models and researchers may use multiple methodologies and strategies for tissue-specific gene sets based on their goals, types of data, and computational resources. This study provided comparative insight for large-scale data mining of transcriptome datasets, shedding light on resolving high dimensions and bias difficulties in bioinformatics data processing.

BnIR: A multi-omics database with various tools for Brassica napus research and breeding

In the post-genome-wide association study era, multi-omics techniques have shown great power and potential for candidate gene mining and functional genomics research. However, due to the lack of effective data integration and multi-omics analysis platforms, such techniques have not still been applied widely in rapeseed, an important oil crop worldwide. Here, we report a rapeseed multi-omics database (BnIR; http://yanglab.hzau.edu.cn/BnIR), which provides datasets of six omics including genomics, transcriptomics, variomics, epigenetics, phenomics, and metabolomics, as well as numerous "variation-gene expression-phenotype" associations by using multiple statistical methods. In addition, a series of multi-omics search and analysis tools are integrated to facilitate the browsing and application of these datasets. BnIR is the most comprehensive multi-omics database for rapeseed so far, and two case studies demonstrated its power to mine candidate genes associated with specific traits and analyze their potential regulatory mechanisms.