Abstract
BackgroundNext generation sequencing methods are the gold standard for evaluating expression of the transcriptome. When determining the biological implications of such studies, the assumption is often made that transcript expression levels correspond to protein levels in a meaningful way. However, the strength of the overall correlation between transcript and protein expression is inconsistent, particularly in brain samples.ResultsFollowing high-throughput transcriptomic (RNA-Seq) and proteomic (liquid chromatography coupled with tandem mass spectrometry) analyses of adult human brain samples, we compared the correlation in the expression of transcripts and proteins that support various biological processes, molecular functions, and that are located in different areas of the cell. Although most categories of transcripts have extremely weak predictive value for the expression of their associated proteins (R2 values of < 10%), transcripts coding for protein kinases and membrane-associated proteins, including those that are part of receptors or ion transporters, are among those that are most predictive of downstream protein expression levels.ConclusionsThe predictive value of transcript expression for corresponding proteins is variable in human brain samples, reflecting the complex regulation of protein expression. However, we found that transcriptomic analyses are appropriate for assessing the expression levels of certain classes of proteins, including those that modify proteins, such as kinases and phosphatases, regulate metabolic and synaptic activity, or are associated with a cellular membrane. These findings can be used to guide the interpretation of gene expression results from primate brain samples.
Highlights
Generation sequencing methods are the gold standard for evaluating expression of the transcriptome
A complete ordered list of the transcript and protein expression levels in human anterior cingulate cortex (ACC) and the ordinary least squares (OLS) regression results including the predictive natures (R2) of Gene Ontology (GO) categories can be found in Additional file 1
We report that transcripts coding for protein kinases, phosphatases, and membrane-associated proteins, especially those that participate in metabolic oxidoreductase activity or the transport of ions, are among the transcripts that are most predictive of their downstream protein expression levels
Summary
Generation sequencing methods are the gold standard for evaluating expression of the transcriptome. Generation sequencing, including RNA-Seq, allows researchers to investigate transcript expression using label-free technology, and its relative ease of use has made this method the dominant technology for assessing molecular phenotype. The assumption is frequently made that the expression level of a transcript reflects that of the downstream protein, suggesting the equivalence of these two molecules. Our earlier study [6] explored transcript (RNA-Seq) and protein (liquid chromatography with tandem mass spectrometry [LC/MS/MS]), expression in the anterior cingulate cortex (ACC) and caudate nucleus (CN) of humans and chimpanzees in order to determine if differential expression analyses of these two molecules resulted in different interspecific biological signals. Must overcome additional challenges imposed by longer postmortem intervals (PMIs) and greater cellular heterogeneity than these carefully controlled studies
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