Identification and analysis of mouse non-coding RNA using transcriptome data.

Transcripts are expressed spatially and temporally and they are very complicated, precise and specific; however, most studies are focused on protein-coding related genes. Recently, massively parallel cDNA sequencing (RNA-seq) has emerged to be a new and promising tool for transcriptome research, and numbers of non-coding RNAs, especially lincRNAs, have been widely identified and well characterized as important regulators of diverse biological processes. In this study, we used ultra-deep RNA-seq data from 15 mouse tissues to study the diversity and dynamic of non-coding RNAs in mouse.