Comparative transcriptome analysis of fiber and nonfiber tissues to identify the genes preferentially expressed in fiber development in Gossypium hirsutum

Abstract

Abstract Cotton is an important natural fiber crop and economic crop worldwide. The quality of cotton fiber directly determines the quality of cotton textiles. Identifying cotton fiber development-related genes and exploring their biological functions will not only help to better understand the elongation and development mechanisms of cotton fibers but also provide a theoretical basis for the cultivation of new cotton varieties with excellent fiber quality. In this study, RNA sequencing technology was used to construct transcriptome databases for different nonfiber tissues (root, leaf, anther and stigma) and fiber developmental stages (7 days post-anthesis (DPA), 14 DPA, and 26 DPA) of upland cotton Coker 312. The sizes of the seven transcriptome databases constructed ranged from 4.43 to 5.20 Gb, corresponding to approximately twice the genome size of Gossypium hirsutum (2.5 Gb). Among the obtained clean reads, 83.32% to 88.22% could be compared to the upland cotton TM-1 reference genome. By analyzing the differential gene expression profiles of the transcriptome libraries of fiber and nonfiber tissues, we obtained 1205, 1135 and 937 genes with significantly upregulated expression at 7 DPA, 14 DPA and 26 DPA, respectively, and 124, 179 and 213 genes with significantly downregulated expression. Subsequently, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway analyses were performed, which revealed that these genes were mainly involved in catalytic activity, carbohydrate metabolism, the cell membrane and organelles, signal transduction and other functions and metabolic pathways. Through gene annotation analysis, many transcription factors and genes related to fiber development were screened. Thirty-six genes were randomly selected from the significantly upregulated genes in fiber, and expression profile analysis was performed using qRT-PCR. The results were highly consistent with the gene expression profile analyzed by RNA-seq, and all of the genes were specifically or predominantly expressed in fiber. Therefore, our RNA sequencing-based comparative transcriptome analysis will lay a foundation for future research to provide new genetic resources for the genetic engineering of improved cotton fiber quality and for cultivating new transgenic cotton germplasms for fiber quality improvement.