Science China Life Sciences

, Volume 60, Issue 2, pp 116–125 | Cite as

Characterizing and annotating the genome using RNA-seq data

Open Access
Review

Abstract

Bioinformatics methods for various RNA-seq data analyses are in fast evolution with the improvement of sequencing technologies. However, many challenges still exist in how to efficiently process the RNA-seq data to obtain accurate and comprehensive results. Here we reviewed the strategies for improving diverse transcriptomic studies and the annotation of genetic variants based on RNA-seq data. Mapping RNA-seq reads to the genome and transcriptome represent two distinct methods for quantifying the expression of genes/transcripts. Besides the known genes annotated in current databases, many novel genes/transcripts (especially those long noncoding RNAs) still can be identified on the reference genome using RNA-seq. Moreover, owing to the incompleteness of current reference genomes, some novel genes are missing from them. Genome- guided and de novo transcriptome reconstruction are two effective and complementary strategies for identifying those novel genes/transcripts on or beyond the reference genome. In addition, integrating the genes of distinct databases to conduct transcriptomics and genetics studies can improve the results of corresponding analyses.

Keywords

RNA-seq genome-guided transcriptome reconstruction de novo assembly long noncoding RNA genetic variants 

Notes

Acknowledgements

This work was supported by the National High Technology Research and Development Program of China (2015AA020104), the China Human Proteome Project (2014DFB30010), the National Science Foundation of China (31471239, to Leming Shi), and the 111 Project (B13016).

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Copyright information

© The Author(s) 2016

Authors and Affiliations

  1. 1.Center for Pharmacogenomics, School of Pharmacy and School of Life SciencesFudan UniversityShanghaiChina
  2. 2.The Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
  3. 3.State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, School of Life SciencesFudan UniversityShanghaiChina
  4. 4.Fudan-Zhangjiang Center for Clinical GenomicsShanghaiChina
  5. 5.Zhangjiang Center for Translational MedicineShanghaiChina

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