Cotton Genomics and Genetics 2024, Vol.15, No.2, 112-126 http://cropscipublisher.com/index.php/cgg 116 been successfully applied to assemble complex genomes, overcoming the limitations of each technology when used alone. This approach has been particularly useful in assembling highly repetitive genomes, which are common in many plant species, including cotton (Baptista et al., 2018). The advancements in de novo genome assembly have provided valuable insights into the genetic diversity and evolutionary history of cotton species. 3.2 Transcriptomics and gene expression analysis 3.2.1 RNA-Seq applications RNA sequencing (RNA-Seq) is a powerful application of NGS that has revolutionized transcriptomics and gene expression analysis in cotton. RNA-Seq allows for the comprehensive profiling of gene expression, identification of novel transcripts, and detection of alternative splicing events. The high throughput and sensitivity of RNA-Seq make it an invaluable tool for studying the transcriptome dynamics in cotton under various conditions (Ferros et al., 2022). This technology has been widely used to investigate the molecular mechanisms underlying important traits such as fiber development, stress responses, and disease resistance in cotton (Bansal et al., 2018). Zheng et al. (2021) conducted an in-depth study on the identification and function of long-chain non-coding RNAs (lncRNAs) in upland cotton (Gossypium arboreum). The researchers utilized various high-throughput sequencing technologies, including full-length isoform sequencing, strand-specific RNA sequencing (ssRNA-seq), Cap Analysis Gene Expression sequencing (CAGE-seq), and PolyA sequencing, to systematically analyze lncRNA expression in 21 tissue samples (Figure 2). Figure 2 Full-length annotation of lncRNAs with multi-strategy RNA-seq data in cotton (G. arboreum) (Adopted from Zheng et al., 2021) Image caption: A: The four RNA-seq technologies applied in this study; B: The overview of plant full-length lncRNA (PULL) pipeline; C: Evaluation of CPC and CNCI for lncRNAs and PCGs. Low score indicates weak capability of protein encoding; D: Numbers of lncRNAs with 5ʹ- and/or 3ʹ-end signals; E: Schematic illustration of four types of lncRNAs (left) and their proportions (right); F: The proportion of transcripts with a 5ʹ cap and 3ʹ polyA tail in lncRNAs and PCGs (Adopted from Zheng et al., 2021) Figure 2 illustrates the comprehensive annotation of long-chain non-coding RNAs (lncRNAs) in cotton, integrating multi-strategy RNA sequencing data. By utilizing four sequencing technologies-Iso-seq, ssRNA-seq, CAGE-seq, and PolyA-seq-researchers were able to accurately analyze and identify the precise gene structures of lncRNAs, including transcription start sites (TSS) and transcription termination sites (TTS). The figure also shows
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