Dataset Information

ProteomeGenerator analysis of K052

ABSTRACT: To improve identification of canonical and non-canonical protein isoforms, we introduced ProteomeGenerator, a framework for reference-guided and de novo proteogenomic database generation from transcriptomic sequencing dataset. The proteomic databases output by ProteomeGenerator contain only proteins encoded by actively transcribed genes, and includes sample-specific protein isoforms resulting from non-canonical transcription and mRNA editing. We applied this workflow to the proteogenomic analysis of spliceosome-defective K052 SRSF2(P95H) cells, demonstrating high-confidence identification of proteins isoforms arising from intron inclusion and non-canonical splicing, as well as improved overall estimation of false-discovery rate from the focused database assembled by ProteomeGenerator.

INSTRUMENT(S): Orbitrap Fusion ETD

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture

SUBMITTER: Alex Kentsis

LAB HEAD: Alex Kentsis

PROVIDER: PXD008381 | Pride | 2018-10-11

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	160116_K052_OffLRP_RP_f01.raw	Raw
	160116_K052_OffLRP_RP_f02.raw	Raw
	160116_K052_OffLRP_RP_f03.raw	Raw
	160116_K052_OffLRP_RP_f04.raw	Raw
	160116_K052_OffLRP_RP_f05.raw	Raw

Items per page:

1 - 5 of 56

Publications

ProteomeGenerator: A Framework for Comprehensive Proteomics Based on de Novo Transcriptome Assembly and High-Accuracy Peptide Mass Spectral Matching.

Cifani Paolo P Dhabaria Avantika A Chen Zining Z Yoshimi Akihide A Kawaler Emily E Abdel-Wahab Omar O Poirier John T JT Kentsis Alex A

Journal of proteome research 20181019 11

Modern mass spectrometry now permits genome-scale and quantitative measurements of biological proteomes. However, analysis of specific specimens is currently hindered by the incomplete representation of biological variability of protein sequences in canonical reference proteomes and the technical demands for their construction. Here, we report ProteomeGenerator, a framework for de novo and reference-assisted proteogenomic database construction and analysis based on sample-specific transcriptome ...[more]

PMID: 30295032

Similar Datasets

Project description:Human umbilical vein endothelial cells (HUVECs) are a widely-used model system to study many pathological and physiological processes associated with the cardiovascular system. An understanding of genes and proteins that are expressed in any cell type is a fundamental need which facilitates study of molecular changes in disease states and response to various stimuli. In this study, we employed next generation sequencing and mass spectrometry to profile the transcriptome and proteome of primary HUVECs. Analysis of 145 million paired-end reads from next generation sequencing confirmed expression of 12,186 protein-coding genes (FPKM>0.1), 439 novel long non-coding RNAs and revealed 6,089 novel isoforms that were not annotated in GENCODE. A comparison of the transcripts against human gene expression data for 53 tissues catalogued by the Genotype-Tissue Expression (GTEx) project revealed a number of HUVEC-specific genes. Proteomics analysis identified 6,477 proteins including confirmation of N-termini for 1,091 proteins and isoforms for 149 proteins for which transcriptomic evidence was also observed. Alternate translational start sites for seven proteins and alternate splicing in seven proteins were also identified. A database search to specifically identify other post-translational modifications provided evidence for a number of modification sites on 117 proteins which include ubiquitylation, lysine acetylation, mono, di- and tri-methylation. Based on the data from this study and a survey of other databases, we provide evidence for 11 “missing proteins,” which are proteins for which protein level evidence is lacking or insufficient. Proteogenomic analysis identified novel N-termini and exon-exon junctions at both RNA and protein levels by searching against a translated database created from alternate transcript assembly. Peptides supporting the novel events of expressed proteins are further validated by synthesis and spectral comparison. Alternative allelic expression of genes arising from transcription of two alleles of a gene in chromosome pairs is observed. By creating a custom database of proteins incorporated with sample specific single amino acid variations (SAAV) we identified alternative alleles for 207 expressed proteins with 245 peptides with SAAV. Overall, we believe that the integrated approach employed in this study is widely applicable to study any primary cell type for deeper molecular characterization.