Analysis Of Fiber Development-Related Gene Expression In Gossypium Hirsutum L.

Cotton fiber as a single-celled trichome is a biological model system for studying cell differentiation and elongation. However, the complexity of its gene expression and regulatory mechanism allows only marginal progress. Emerging innovative molecular tools such as transcriptome-profiling-based deep-sequencing provide insights into fiber development-related gene activity and regulatory networks. The present study reports the high-throughput tag-sequencing (Tag-seq) analysis using Solexa Genome Analyzer platform on transcriptome of -2～1 (fiber initiation) and 2～8 (fiber elongation) days post anthesis (DPA) cotton (Gossypium hirsutum) ovules (wildtype:WT, Xuzhou 142 and its mutant:fuzzless/lintless or M, in the same background). To this end, we sequenced 3.5 to 3.8 million tags representing 0.7 to 1.0 million unique transcripts for each library (WT1, WT2, M1 and M2). After removal of low quality tags, we obtained a total of 2,973,104, 3,139,306,2,943,654 and 3,392,103 clean sequences that corresponded to 357,852,280,787, 372,952 and 382,503 distinct tags for WT1, WT2, M1 and M2, respectively. All clean tags were aligned to the publicly available cotton gene database (TIGR, http://www.tigr.org). About 15% of the distinct tags were uniquely mapped to the reference genes and 31.4% of existing genes were matched by tags. The tag mapping to reference genes generated 23,854, 24,442,23,497 and 19,957 annotated genes for WT1, WT2, M1 and M2 libraries, respectively. Analyses of differentially expressed genes revealed the substantial changes in gene number and abundance between two libraries. Additionally, we compared the tag-mapped genes to those targeted by microRNAs identified previously, and found that 62 (62%) out of the 99 potential target genes can be matched by tag-mapped sequences. Overall, our deep-sequencing analyses demonstrated the high degree of transcriptional complexity in early ovule initials and developing fibers. It represents a major improvement over the microarrays for analyzing transcriptional changes on a large scale.