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[学术文献 ] Combining suitable brown lint color, fiber quality, and yield in F2 cotton hybrids 进入全文
INDUSTRIAL CROPS AND PRODUCTS
Naturally colored cotton is eco-friendly because its use in textiles does not require dyeing, and textiles made from colored cotton are the best for human health. Despite their many advantages, the low yields and unfavorable quality traits of colored cotton varieties limit extensive production. Therefore, F1 and F2 populations of inter- specific ( Gossypium hirsutum L. x Gossypium barbadense L.) and intraspecific ( Gossypium hirsutum L.) cotton hybrids were examined to develop brown-colored cotton varieties with superior traits. Gelincik and Nazilli Deve T & uuml;y & uuml; (NDT)-15 varieties ( Gossypium hirsutum L.) with brown-colored lint were used as female parents. The male parents included Giza-75, Bahar-82 ( Gossypium barbadense L.), Fiona, May-455, I(center dot)pek-607 and Claudia ( Gossypium hirsutum L.) varieties with white-colored lint. According to the line x tester mating design, 12 hybrid combinations were obtained. F1 populations had higher yield and fiber length values than their parents and F2 populations. F2 populations had more unfavorable color values (L: whiteness, a*: red-green, and b*: yellow-blue) than their colored parents but were superior to F1s. The ratio of general combination ability variance to specific combination ability variance was less than 1, indicating that yield, ginning out-turn, fiber quality, and color parameters were controlled by non-additive genes. In the biplot graph, color and fiber parameters are located in the opposite direction from yield, indicating that it is difficult to develop colored cotton with high yield and fiber quality. Among the 960 F2 single plants evaluated, ten plants were carefully selected according to the optimization of yield, fiber quality, and color values. Based on potential diallel crosses of the ten selected plants, it was decided to begin a recurrent selection with that population. Furthermore, it was determined that F2 seeds of Nazilli DT-15 x I(center dot)pek-607 and Gelincik x Giza-75 combinations may be successfully given to farmers.
[学术文献 ] Spatiotemporal transcriptome and metabolome landscapes of cotton fiber during initiation and early development 进入全文
NATURE COMMUNICATIONS
Cotton fibers are single cells that develop from the epidermal cells in the outer integument of developing seeds. The processes regulating fiber cell development have been extensively studied; however, the spatiotemporal transcriptome and metabolome profiles during the early stages of fiber development remain largely unknown. In this study, we profile the dynamics of transcriptome and metabolome during the early stages of cotton fiber cell development using a combination of spatial transcriptomic, single-cell transcriptomic, and spatial metabolomic analyses. We identify the key genes (e.g., DOX2, KCS19.4, BEE3, and HOS3.7) and metabolites (e.g., linoleic acid, spermine, spermidine, and alpha-linolenic acid) that may regulate the early development of fiber cells. Finally, knockdown and gain-of-function analyses identify the crucial role of GhBEE3/Gh_A09G062900 in cotton fiber initiation. We also construct a publicly accessible website (https://cotton.cricaas.com.cn/ovule/) for visualization of the spatiotemporal gene expression in cotton, providing a reference dataset for further studies on cotton fiber development.
[学术文献 ] Spatiotemporal transcriptome and metabolome landscapes of cotton somatic embryos 进入全文
NATURE COMMUNICATIONS
Somatic embryogenesis (SE) is a developmental process related to the regeneration of tissue-cultured plants, which serves as a useful technique for crop breeding and improvement. However, SE in cotton is difficult and elusive due to the lack of precise cellular level information on the reprogramming of gene expression patterns involved in somatic embryogenesis. Here, we investigate the spatial and single-cell expression profiles of key genes and the metabolic patterns of key metabolites by integrated single-cell RNA-sequencing (scRNA-seq), spatial transcriptomics (ST), and spatial metabolomics (SM). To evaluate the results of these analyses, we functionally characterized the potential roles of two representative marker genes, AATP1 and DOX2, in the regulation of cotton somatic embryo development. A publicly available web-based resource database (https://cotton.cricaas.com.cn/somaticembryo/) in this study provides convenience for future studies of the expression patterns of marker genes at specific developmental stages during the process of SE in cotton.
[学术文献 ] Analysis of the genetic basis of fiber-related traits and flowering time in upland cotton using machine learning 进入全文
THEORETICAL AND APPLIED GENETICS
Cotton is an important crop for fiber production, but the genetic basis underlying key agronomic traits, such as fiber quality and flowering days, remains complex. While machine learning (ML) has shown great potential in uncovering the genetic architecture of complex traits in other crops, its application in cotton has been limited. Here, we applied five machine learning models-AdaBoost, Gradient Boosting Regressor, LightGBM, Random Forest, and XGBoost-to identify loci associated with fiber quality and flowering days in cotton. We compared two SNP dataset down-sampling methods for model training and found that selecting SNPs with an Fscale value greater than 0 outperformed randomly selected SNPs in terms of model accuracy. We further performed machine learning quantitative trait loci (mlQTLs) analysis for 13 traits related to fiber quality and flowering days. These mlQTLs were then compared to those identified through genome-wide association studies (GWAS), revealing that the machine learning approach not only confirmed known loci but also identified novel QTLs. Additionally, we evaluated the effect of population size on model accuracy and found that larger population sizes resulted in better predictive performance. Finally, we proposed candidate genes for the identified mlQTLs, including two argonaute 5 proteins, Gh_A09G104100 and Gh_A09G104400, for the FL3/FS2 locus, as well as GhFLA17 and Syntaxin-121 (Gh_D09G143700) for the FSD09_2/FED09_2 locus. Our findings demonstrate the efficacy of machine learning in enhancing the identification of genetic loci in cotton, providing valuable insights for improving cotton breeding strategies.
[学术文献 ] Genome-Wide Identification and Analysis of the MYC Gene Family in Cotton: Evolution and Expression Profiles During Normal Growth and Stress Response 进入全文
GENES
Background: The gene family of myelomatosis (MYC), serving as a transcription factor in the jasmonate (JA) signaling pathway, displays a significant level of conservation across diverse animal and plant species. Cotton is the most widely used plant for fiber production. Nevertheless, there is a paucity of literature reporting on the members of MYCs and how they respond to biotic stresses in cotton. Methods: Bioinformatics analysis was used to mine the MYC gene family in cotton based on InterPro, cottongen, etc. Results: The gene structure, conserved motifs, and upstream open reading frames of 32 GhMYCs in Gossypium hirsutum were identified. Moreover, it was anticipated that the GT1-motif is the most abundant in GhMYCs, indicating that the GT1-motif plays a significant role in light-responsive GhMYCs. The expression patterns of GhMYCs under biotic stresses including V. dahliae and Aphid gossypii were evaluated, suggesting that GhMYCs in class-1 and -3 GhMYCs, which function as negative regulators, are involved in resistance to verticillium wilt and aphids. The class-3 GhMYCs genes were found to be mostly expressed in female tissues. Interestingly, it was also determined that the homeologous expression bias within GhMYCs in cotton was uncovered, and results showed that the gene expression of class-1A and class-2 GhMYCs in the Dt sub-genome may have a direct impact on gene function. Conclusions: This study provides a research direction for researchers and breeders to enhance cotton traits through manipulating individual or multiple homeologs, which laid a foundation for further study of the molecular characteristics and biological functions of GhMYC gene.
[学术文献 ] Epigenomic and 3D genomic mapping reveals developmental dynamics and subgenomic asymmetry of transcriptional regulatory architecture in allotetraploid cotton 进入全文
NATURE COMMUNICATIONS
Although epigenetic modification has long been recognized as a vital force influencing gene regulation in plants, the dynamics of chromatin structure implicated in the intertwined transcriptional regulation of duplicated genes in polyploids have yet to be understood. Here, we document the dynamic organization of chromatin structure in two subgenomes of allotetraploid cotton (Gossypium hirsutum) by generating 3D genomic, epigenomic and transcriptomic datasets from 12 major tissues/developmental stages covering the life cycle. We systematically identify a subset of genes that are closely associated with specific tissue functions. Interestingly, these genes exhibit not only higher tissue specificity but also a more pronounced homoeologous bias. We comprehensively elucidate the intricate process of subgenomic collaboration and divergence across various tissues. A comparison among subgenomes in the 12 tissues reveals widespread differences in the reorganization of 3D genome structures, with the Dt subgenome exhibiting a higher extent of dynamic chromatin status than the At subgenome. Moreover, we construct a comprehensive atlas of putative functional genome elements and discover that 37 cis-regulatory elements (CREs) have selection signals acquired during domestication and improvement. These data and analyses are publicly available to the research community through a web portal. In summary, this study provides abundant resources and depicts the regulatory architecture of the genome, which thereby facilitates the understanding of biological processes and guides cotton breeding.
