Format

Send to

Choose Destination
Proteomics. 2016 Oct;16(19):2533-2544. doi: 10.1002/pmic.201600140. Epub 2016 Aug 25.

Integrating transcriptome and proteome profiling: Strategies and applications.

Author information

1
G.N. Ramachandran Knowledge Center for Genome Informatics, CSIR-Institute of Genomics and Integrative Biology, South Campus, Sukhdev Vihar, New Delhi, INDIA.
2
Academy of Scientific & Innovative Research (AcSIR), CSIR-IGIB South Campus, New Delhi, India.
3
G.N. Ramachandran Knowledge Center for Genome Informatics, CSIR-Institute of Genomics and Integrative Biology, South Campus, Sukhdev Vihar, New Delhi, INDIA. ddash@igib.res.in, ddash@igib.in.
4
Academy of Scientific & Innovative Research (AcSIR), CSIR-IGIB South Campus, New Delhi, India. ddash@igib.res.in, ddash@igib.in.

Abstract

Discovering the gene expression signature associated with a cellular state is one of the basic quests in majority of biological studies. For most of the clinical and cellular manifestations, these molecular differences may be exhibited across multiple layers of gene regulation like genomic variations, gene expression, protein translation and post-translational modifications. These system wide variations are dynamic in nature and their crosstalk is overwhelmingly complex, thus analyzing them separately may not be very informative. This necessitates the integrative analysis of such multiple layers of information to understand the interplay of the individual components of the biological system. Recent developments in high throughput RNA sequencing and mass spectrometric (MS) technologies to probe transcripts and proteins made these as preferred methods for understanding global gene regulation. Subsequently, improvements in "big-data" analysis techniques enable novel conclusions to be drawn from integrative transcriptomic-proteomic analysis. The unified analyses of both these data types have been rewarding for several biological objectives like improving genome annotation, predicting RNA-protein quantities, deciphering gene regulations, discovering disease markers and drug targets. There are different ways in which transcriptomics and proteomics data can be integrated; each aiming for different research objectives. Here, we review various studies, approaches and computational tools targeted for integrative analysis of these two high-throughput omics methods.

KEYWORDS:

Bioinformatics; Network biology; Post translational modifications (PTM); Proteogenomics; RNA-seq; Ribosome profiling

PMID:
27343053
DOI:
10.1002/pmic.201600140
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Wiley
Loading ...
Support Center