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A flexible Transcriptomic Analysis Pipeline (TAP) for quality control and functional assessment of transcriptomes

ABSTRACT: We developed a Transcriptomic Analysis Pipeline (TAP) as a flexible workflow for comprehensive transcriptome analysis from any species with a reference genome. We tested TAP in a case study to compare polyA+ and rRNA-depletion RNA-seq library protocols using Drosophila melanogaster following different thermal stress temperatures. TAP provides a flexible and complete pipeline to enable researchers to extract more biologically relevant interpretations by integrated and interactive transcriptome analysis.

ORGANISM(S): Drosophila melanogaster

PROVIDER: GSE229448 | GEO | 2023/11/09

REPOSITORIES: GEO

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Project description:BackgroundRNA-sequencing (RNA-seq) has revolutionized the exploration of biological mechanisms, shedding light on the roles of non-coding RNAs, including long non-coding RNAs (lncRNAs), across various biological processes, including stress responses. Despite these advancements, there remains a gap in our understanding of the implications of different RNA-seq library protocols on comprehensive lncRNA expression analysis, particularly in non-mammalian organisms.ResultsIn this study, we sought to bridge this knowledge gap by investigating lncRNA expression patterns in Drosophila melanogaster under thermal stress conditions. To achieve this, we conducted a comparative analysis of two RNA-seq library protocols: polyA + RNA capture and rRNA-depletion. Our approach involved the development and application of a Transcriptome Analysis Pipeline (TAP) designed to systematically assess both the technical and functional dimensions of RNA-seq, facilitating a robust comparison of these library protocols. Our findings underscore the efficacy of the polyA + protocol in capturing the majority of expressed lncRNAs within the Drosophila melanogaster transcriptome. In contrast, rRNA-depletion exhibited limited advantages in the context of D. melanogaster studies. Notably, the polyA + protocol demonstrated superior performance in terms of usable read yield and the accurate detection of splice junctions.ConclusionsOur study introduces a versatile transcriptomic analysis pipeline, TAP, designed to uniformly process RNA-seq data from any organism with a reference genome. It also highlights the significance of selecting an appropriate RNA-seq library protocol tailored to the specific research context.BackgroundAdvances in next generation sequencing (NGS) technologies enable the comprehensive analysis of genetic sequences of organisms in a relatively cost-effective manner [1, 2]. Among these technologies, RNA-sequencing (RNA-seq) has emerged as a preeminent method to study fundamental biological mechanisms at the level of cells, tissues, and whole organisms. RNA-seq enables the detection and quantification of various RNA populations, including messenger RNA (mRNA) and various species of non-coding RNA, such as long non-coding RNA (lncRNA), as well as an assessment of features including splice junctions in RNA.

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A flexible Transcriptomic Analysis Pipeline (TAP) for quality control and functional assessment of transcriptomes

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