Abstract
Cotton fiber development is still an intriguing question to understand fiber commitment and development. At different fiber developmental stages, many genes change their expression pattern and have a pivotal role in fiber quality and yield. Recently, numerous studies have been conducted for transcriptional regulation of fiber, and raw data were deposited to the public repository for comprehensive integrative analysis. Here, we remapped > 380 cotton RNAseq data with uniform mapping strategies that span ∼400 fold coverage to the genome. We identified stage-specific features related to fiber cell commitment, initiation, elongation, and Secondary Cell Wall (SCW) synthesis and their putative cis-regulatory elements for the specific regulation in fiber development. We also mined Exclusively Expressed Transcripts (EETs) that were positively selected during cotton fiber evolution and domestication. Furthermore, the expression of EETs was validated in 100 cotton genotypes through the nCounter assay and correlated with different fiber-related traits. Thus, our data mining study reveals several important features related to cotton fiber development and improvement, which were consolidated in the “CottonExpress-omics” database.
Highlights
A transcriptome is a repertoire for protein-coding and non-coding RNAs of different tissues that are crucial in delineating the molecular basis of any phenotypic plasticity
We considered data only from five tissues as those having the highest number of Sequence Read Archive (SRA) samples (336 runs) (Figure 1B) to represent the fiber and non-fiber tissues
To understand the molecular and biological functions of genes involved in cotton fiber growth and development, the multi-omics approach was taken into consideration (Pang et al, 2009; Rai et al, 2013; Song et al, 2015, 2017; Zou et al, 2016; Kumar et al, 2018; Ayubov et al, 2019; Li et al, 2019)
Summary
A transcriptome is a repertoire for protein-coding and non-coding RNAs of different tissues that are crucial in delineating the molecular basis of any phenotypic plasticity. More than 175 thousand RNAseq data of several plant species have been deposited in Sequence Read Archive (SRA) alone. Making sense of such public archives for reproducibility and reusability of data was highly recommended for providing new biological insights (Rung and Brazma, 2013). The co-expression network analysis of publicly available transcriptome data in Arabidopsis resulted in identifying trait-related modules (Liu et al, 2019) and the nitrate transporter in different tissues (He et al, 2016), whereas the meiosis-related modules were identified in hexaploid wheat (Alabdullah et al, 2019).
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