Integration of Proteomics and Transcriptomics Data Sets for the Analysis of a Lymphoma B-Cell Line in the Context of the Chromosome-Centric Human Proteome Project

详细信息    查看全文

• 作者：Paula D铆ez ; Conrad Droste ; Rosa M. D茅gano ; Mar铆a Gonz谩lez-Mu帽oz ; Nieves Ibarrola ; Mart铆n P茅rez-Andr茅s ; Alba Garin-Muga ; V铆ctor Segura ; Gyorgy Marko-Varga ; Joshua LaBaer ; Alberto Orfao ; Fernando J. Corrales ; Javier De Las Rivas ; Manuel Fuentes
• 刊名：Journal of Proteome Research
• 出版年：2015
• 出版时间：September 4, 2015
• 年：2015
• 卷：14
• 期：9
• 页码：3530-3540
• 全文大小：408K
• ISSN：1535-3907

文摘

A comprehensive study of the molecular active landscape of human cells can be undertaken to integrate two different but complementary perspectives: transcriptomics, and proteomics. After the genome era, proteomics has emerged as a powerful tool to simultaneously identify and characterize the compendium of thousands of different proteins active in a cell. Thus, the Chromosome-centric Human Proteome Project (C-HPP) is promoting a full characterization of the human proteome combining high-throughput proteomics with the data derived from genome-wide expression profiling of protein-coding genes. Here we present a full proteomic profiling of a human lymphoma B-cell line (Ramos) performed using a nanoUPLC-LTQ-Orbitrap Velos proteomic platform, combined to an in-depth transcriptomic profiling of the same cell type. Data are available via ProteomeXchange with identifier PXD001933. Integration of the proteomic and transcriptomic data sets revealed a 94% overlap in the proteins identified by both -omics approaches. Moreover, functional enrichment analysis of the proteomic profiles showed an enrichment of several functions directly related to the biological and morphological characteristics of B-cells. In turn, about 30% of all protein-coding genes present in the whole human genome were identified as being expressed by the Ramos cells (stable average of 30% genes along all the chromosomes), revealing the size of the protein expression-set present in one specific human cell type. Additionally, the identification of missing proteins in our data sets has been reported, highlighting the power of the approach. Also, a comparison between neXtProt and UniProt database searches has been performed. In summary, our transcriptomic and proteomic experimental profiling provided a high coverage report of the expressed proteome from a human lymphoma B-cell type with a clear insight into the biological processes that characterized these cells. In this way, we demonstrated the usefulness of combining -omics for a comprehensive characterization of specific biological systems.