RNA测序(RNA-seq)是一种高通量技术,可提供有关转录组的深入信息。RNA测序的进步和成本的下降,伴随着更多可用的不同物种的参考基因组,使非模式生物的转录组分析成为可能。当前分析RNA-seq数据的障碍包括缺乏功能注释,这可能会使基因与相应功能的连接过程复杂化。这里,我们提供了一个一站式的RNA-seq分析管道,PipeOne-NM,对于转录组功能注释,非编码RNA鉴定,和非模式生物的转录本选择性剪接分析,用于基于Illumina平台的RNA-seq数据。我们对237个SchmidteamediterraneaRNA-seq运行进行了PipeOne-NM,并组装了一个转录组,该转录组具有来自49,320个基因的84,827个序列,鉴定来自35,485个基因的64,582个mRNA,20,217lncRNA来自17,084个基因,和来自1103个基因的3481个circRNAs。此外,我们对lncRNA和mRNA进行了共表达分析,发现1319lncRNA与至少一种mRNA共表达.对来自地中海链球菌有性和无性菌株的样品的进一步分析揭示了有性生殖在基因表达谱中的作用。来自无性地中海链球菌不同部位的样本显示,不同身体部位的差异表达谱与神经冲动的传导功能相关。总之,PipeOne-NM有潜力在单一平台上为非模型生物提供全面的转录组信息。
RNA sequencing (RNA-seq) is a high-throughput technology that provides in-depth information on transcriptome. The advancement and dropping costs of RNA sequencing, accompanied by more available reference genomes for different species, make transcriptome analysis in non-model organisms possible. Current obstacles in analyzing RNA-seq data include a lack of functional annotation, which may complicate the process of linking genes to corresponding functions. Here, we provide a one-stop RNA-seq analysis pipeline, PipeOne-NM, for transcriptome functional annotation, non-coding RNA identification, and transcripts alternative splicing analysis of non-model organisms, intended for use with Illumina platform-based RNA-seq data. We performed PipeOne-NM on 237 Schmidtea
mediterranea RNA-seq runs and assembled a transcriptome with 84,827 sequences from 49,320 genes, identifying 64,582 mRNA from 35,485 genes, 20,217 lncRNA from 17,084 genes, and 3481 circRNAs from 1103 genes. In addition, we performed a co-expression analysis of lncRNA and mRNA and identified that 1319 lncRNA co-express with at least one mRNA. Further analysis of samples from S.
mediterranea sexual and asexual strains revealed the role of sexual reproduction in gene expression profiles. Samples from different parts of asexual S.
mediterranea revealed that differential expression profiles of different body parts correlated with the function of conduction of nerve impulses. In conclusion, PipeOne-NM has the potential to provide comprehensive transcriptome information for non-model organisms on a single platform.