Premium
Leveraging the complementary nature of RNA‐Seq and shotgun proteomics data
Author(s) -
Wang Xiaojing,
Liu Qi,
Zhang Bing
Publication year - 2014
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201400184
Subject(s) - proteogenomics , shotgun proteomics , proteomics , computational biology , rna seq , biology , proteome , rna , quantitative proteomics , alternative splicing , transcriptome , rna splicing , gene , messenger rna , bioinformatics , gene expression , genetics
RNA sequencing (RNA‐Seq) and MS‐based shotgun proteomics are powerful high‐throughput technologies for identifying and quantifying RNA transcripts and proteins, respectively. With the increasing affordability of these technologies, many projects have started to apply both to the same samples to achieve a more comprehensive understanding of biological systems. A major analytical challenge for such integrative projects is how to effectively leverage the complementary nature of RNA‐Seq and shotgun proteomics data. RNA‐Seq provides comprehensive information on mRNA abundance, alternative splicing, nucleotide variation, and structure alteration. Sample‐specific protein databases derived from RNA‐Seq data can better approximate the real protein pools in cell and tissue samples and thus improve protein identification. Meanwhile, proteomics data provide essential confirmation of the validity and functional relevance of novel findings from RNA‐Seq data. At the quantitative level, mRNA and protein levels are only modestly correlated, suggesting strong involvement of posttranscriptional regulation in controlling gene expression. Here, we review recent studies at the interface of RNA‐Seq and proteomics data. We discuss goals, accomplishments, and challenges in RNA‐Seq‐based proteogenomics. We also examine the current status and future potential of parallel transcriptome and proteome quantification in revealing posttranscriptional regulatory mechanisms.