Dataset Information

Characterization of Two Unknown Proteins in the Human Testis

ABSTRACT: This project aims at deciphering the human testis proteome and to discover and characterizedunknown proteins in order to better understand the male reproductive physiology.

INSTRUMENT(S): TripleTOF 6600

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Testis

SUBMITTER: E Com

LAB HEAD: Charles Pineau

PROVIDER: PXD009598 | Pride | 2018-08-29

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	OneomicsExportPride.pride.mgf.gz	Mgf
	OneomicsExportPride.pride.mztab.gz	Mztab
	OneomicsExportPride.xml.gz	Xml
	Rennes_HighpH_frac10.wiff	Wiff
	Rennes_HighpH_frac11.wiff	Wiff

Items per page:

1 - 5 of 19

Publications

Deciphering the Dark Proteome: Use of the Testis and Characterization of Two Dark Proteins.

Melaine Nathalie N Com Emmanuelle E Bellaud Pascale P Guillot Laetitia L Lagarrigue Mélanie M Morrice Nick A NA Guével Blandine B Lavigne Régis R Velez de la Calle Juan-Felipe JF Dojahn Jörg J Pineau Charles C

Journal of proteome research 20180831 12

For the C-HPP consortium, dark proteins include not only uPE1, but also missing proteins (MPs, PE2-4), smORFs, proteins from lncRNAs, and products from uncharacterized transcripts. Here, we investigated the expression of dark proteins in the human testis by combining public mRNA and protein expression data for several tissues and performing LC-MS/MS analysis of testis protein extracts. Most uncharacterized proteins are highly expressed in the testis. Thirty could be identified in our data set, o ...[more]

PMID: 30130116

Similar Datasets

Project description:Parkinson disease (PD) is a neurodegenerative disease characterized by the accumulation of alpha-synuclein (SNCA) and other proteins in aggregates termed âLewy Bodiesâ within neurons. PD has both genetic and environmental risk factors, and while processes leading to aberrant protein aggregation are unknown, past work points to abnormal levels of SNCA and other proteins. Although several genome-wide studies have been performed for PD, these have focused on DNA sequence variants by genome-wide association studies (GWAS) and on RNA levels (microarray transcriptomics), while genome-wide proteomics analysis has been lacking. After appropriate filters, proteomics identified 3,558 unique proteins and 283 of these (7.9%) were significantly different between PD and controls (q-value<0.05). RNA-sequencing identified 17,580 protein-coding genes and 1,095 of these (6.2%) were significantly different (FDR p-value<0.05), but only 166 of the FDR significant protein-coding genes (0.94%) were present among the 3,558 proteins characterized. Of these 166, eight genes (4.8%) were significant in both studies, with the same direction of effect. Functional enrichment analysis of the proteomics results strongly supports mitochondrial-related pathways, while comparable analysis of the RNA-sequencing results implicates protein folding pathways and metallothioneins. Ten of the implicated genes or proteins co-localized to GWAS loci. Evidence implicating SNCA was stronger in proteomics than in RNA-sequencing analyses. Notably, differentially expressed protein-coding genes were more likely to not be characterized in the proteomics analysis, which lessens the ability to compare across platforms. Combining multiple genome-wide platforms offers novel insights into the pathological processes responsible for this disease by identifying pathways implicated across methodologies. The study consists of mRNA-Seq (29 PD, 44 neurologically normal controls) and three-stage Mass Spectrometry Tandem Mass Tag Proteomics (12 PD, 12 neurologically normal controls) performed in post-mortem BA9 brain tissue. The proteomics samples are a subset of the RNA-Seq samples.