Dataset Information

Comparative analysis of the human and mouse placental transcriptome and proteome

ABSTRACT: Not available

OTHER RELATED OMICS DATASETS IN: PAe001560PRJNA109739PRJNA109871

INSTRUMENT(S): Fourier Transform Ion Cyclotron Resonance Mass Spectrometer, instrument model

ORGANISM(S): Homo Sapiens (human) Mus Musculus (mouse)

SUBMITTER: Attila Csordas

PROVIDER: PRD000474 | Pride | 2012-07-26

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	PRIDE_Exp_Complete_Ac_17962.pride.mgf.gz	Mgf
	PRIDE_Exp_Complete_Ac_17962.pride.mztab.gz	Mztab
	PRIDE_Exp_Complete_Ac_17962.xml.gz	Xml
	PRIDE_Exp_Complete_Ac_17963.pride.mgf.gz	Mgf
	PRIDE_Exp_Complete_Ac_17963.pride.mztab.gz	Mztab

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Publications

Comparative systems biology of human and mouse as a tool to guide the modeling of human placental pathology.

Cox Brian B Kotlyar Max M Evangelou Andreas I AI Ignatchenko Vladimir V Ignatchenko Alex A Whiteley Kathie K Jurisica Igor I Adamson S Lee SL Rossant Janet J Kislinger Thomas T

Molecular systems biology 20090616

Placental abnormalities are associated with two of the most common and serious complications of human pregnancy, maternal preeclampsia (PE) and fetal intrauterine growth restriction (IUGR), each disorder affecting approximately 5% of all pregnancies. An important question for the use of the mouse as a model for studying human disease is the degree of functional conservation of genetic control pathways from human to mouse. The human and mouse placenta show structural similarities, but there have ...[more]

PMID: 19536202

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Project description:The relationships between the levels of transcripts and the levels of the proteins they encode have not been examined comprehensively in mammals, although previous work in plants and yeast suggest a surprisingly modest correlation. We have examined this issue using a genetic approach in which natural variations were used to perturb both transcript levels and protein levels among inbred strains of mice. We quantified over 5,000 peptides and over 22,000 transcripts in livers of 97 inbred and recombinant inbred strains and focused on the 7,185 most heritable transcripts and 486 most reliable proteins. The transcript levels were quantified by microarray analysis in three replicates and the proteins were quantified by Liquid Chromatography-Mass Spectrometry using O(18)-reference-based isotope labeling approach. We show that the levels of transcripts and proteins correlate significantly for only about half of the genes tested, with an average correlation of 0.27, and the correlations of transcripts and proteins varied depending on the cellular location and biological function of the gene. We examined technical and biological factors that could contribute to the modest correlation. For example, differential splicing clearly affects the analyses for certain genes; but, based on deep sequencing, this does not substantially contribute to the overall estimate of the correlation. We also employed genome-wide association analyses to map loci controlling both transcript and protein levels. Surprisingly, little overlap was observed between the protein- and transcript-mapped loci. We have typed numerous clinically relevant traits among the strains, including adiposity, lipoprotein levels, and tissue parameters. Using correlation analysis, we found that a low number of clinical trait relationships are preserved between the protein and mRNA gene products and that the majority of such relationships are specific to either the protein levels or transcript levels. Surprisingly, transcript levels were more strongly correlated with clinical traits than protein levels. In light of the widespread use of high-throughput technologies in both clinical and basic research, the results presented have practical as well as basic implications.