Reference-Based Identification of Long Noncoding RNAs in Plants with Strand-Specific RNA-Sequencing Data

Methods Mol Biol. 2019:1933:245-255. doi: 10.1007/978-1-4939-9045-0_14.

Abstract

Long noncoding RNAs (lncRNAs) have been shown to play important roles in various organisms, including plant species. Several tools and pipelines have emerged for lncRNA identification, including reference-based transcriptome assembly pipelines and various coding potential calculating tools. In this protocol, we have integrated some of the most updated computational tools and described the procedures step-by-step for identifying lncRNAs from plant strand-specific RNA-sequencing datasets. We will start from clean RNA-sequencing reads, followed by reference-based transcriptome assembly, filtering of known genes, and lncRNA prediction. At the end point, users will obtain a set of predicted lncRNAs for downstream use.

Keywords: Computational identification; Plant long noncoding RNA; Reference-based transcriptome assembly; Software pipeline; Strand-specific RNA-sequencing.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Arabidopsis / genetics*
  • Computational Biology / methods
  • Computational Biology / standards*
  • Gene Expression Regulation, Plant
  • Genome, Plant*
  • High-Throughput Nucleotide Sequencing / methods*
  • RNA, Long Noncoding / genetics*
  • RNA, Plant / genetics*
  • Reference Standards
  • Sequence Analysis, RNA / methods
  • Sequence Analysis, RNA / standards*
  • Transcriptome

Substances

  • RNA, Long Noncoding
  • RNA, Plant