Discovering the RNA Transcription Landscape using Directional Approaches

Autor: Munafo, Daniela B., Liu, Pingfang, Sumner, Christine J., Apone, Lynne M., Langhorst, Bradley W., Yigit, Erbay, Dimalanta, Eileen T., Davis, Theodore B., Stewart, Fiona J.
Jazyk: angličtina
Rok vydání: 2013
Předmět:
Popis: High-throughput complementary DNA sequencing (RNA-Seq) is a powerful technique that allows for sensitive digital quantification of transcript levels. Moreover, RNA-Seq enables the detection of non-canonical transcription start sites and termination sites, alternative splice isoforms and transcript mutation and edition. Standard “next-generation” RNA-sequencing approaches generally require double-stranded cDNA synthesis, which erases RNA strand information. In this approach, the synthesis of randomly primed double-stranded cDNA followed by addition of adaptors for sequencing leads to the loss of information about which strand was present in the original mRNA template. The polarity of the transcript is important for correct annotation of novel genes, identification of antisense transcripts with potential regulatory roles, and for correct determination of gene expression levels in the presence of antisense transcripts. Our objective was to address this need by developing a novel streamlined, low input method for Directional RNA-Sequencing that highly retains strand orientation information while maintaining even coverage of transcript expression. This method is based on second strand labeling and excision after adaptor ligation; allowing differential tagging of the first strand cDNA ends. As a result, we have enabled strand specific mRNA sequencing, as well as whole transcriptome sequencing (Total RNA-Seq) from ribosomal-depleted samples. Total RNA-Seq provides a much broader picture of expression dynamics including discovery of antisense transcripts. This work presents a streamlined, fast solution for complete RNA sequencing, with high quality data that illustrates the complexity and diversity of the RNA transcription landscape.
Databáze: OpenAIRE