Integration of mass spectrometry and RNA‐Seq data to confirm human ab initio predicted genes and lncRNAs. Issue 23 (December 2014)

• Record Type: Journal Article
• Authors: Sun, Han; Chen, Chen; Shi, Meng; Wang, Dandan; Liu, Mingwei; Li, Daixi; Yang, Pengyuan; Li, Yixue; Xie, Lu; Pandey, Akhilesh; Pevzner, Pavel A.
• Is Part Of: Proteomics. Volume 14:Issue 23/24(2014)
• Page Start: 2760
• Page End: 2768
• Publication Date: 2014-12
• Subjects: Proteins -- Separation -- Periodicals; Bioinformatics -- Periodicals; Proteomics -- Periodicals; Genomes -- Periodicals; Molecular genetics -- Periodicals; 572.605
• DOI: 10.1002/pmic.201400174
• Languages: English
• ISSNs: 1615-9853

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>MS/MS has been used to improve genome annotation in various organisms. The classical approach is to construct comprehensive theoretical peptide database with six frame translation model from the whole ORF of a genome and search against this database with real MS/MS spectra. In this work we took a more focused approach, we constructed a database containing only peptides from the ab initio predicted genes from current human genome annotation, and all theoretical peptides from currently annotated lncRNAs, and searched such a database with MS/MS data from human Hela cell line. The purpose of this design is to find translation evidence for ab initio predicted genes and to rule out possible wrongly defined lncRNAs in a systematic proteogenomics effort. To validate proteogenomics results, we integrated RNA‐Seq data analysis for the same Hela cell line which generated MS/MS data, and performed MRM experiment on self‐cultured Hela cell line samples. Six peptides were found to support ab initio predicted genes with both RNA‐Seq and MRM validations, while none was found to support a translated lncRNA. This workflow could be flexibly applied to other human samples and datasets to help further improve human gene annotation.</p> </abstract>