Insights into the regulation of protein abundance from proteomic and transcriptomic analyses
By Christine Vogel, Edward M. Marcotte. Nature reviews genetics, 2012
4,027 citations recorded by the source corpus.
Recent advances in next-generation DNA sequencing and proteomics provide an unprecedented ability to survey mRNA and protein abundances. Such proteome-wide surveys are illuminating the extent to which different aspects of gene expression help to regulate cellular protein abundances. Current data demonstrate a substantial role for regulatory processes occurring after mRNA is made — that is, post-transcriptional, translational and protein degradation regulation — in controlling steady-state protein abundances. Intriguing observations are also emerging in relation to cells following perturbation, single-cell studies and the apparent evolutionary conservation of protein and mRNA abundances. Here, we summarize current understanding of the major factors regulating protein expression.
Subfields: Molecular Biology, Spectroscopy
View Paper: https://www.semanticscholar.org/paper/119839d2861f7293f7a982a421a577799a9dcac6
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In Molecular Biology
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In Spectroscopy
Citations in the corpus
- A survey of best practices for RNA-seq data analysis (2016, background): “Integration of RNA-seq with proteomics is controversial because the two measurements show generally low correlation (~0.40 [158, 159]).”
- Polyploidy, the Nucleotype, and Novelty: The Impact of Genome Doubling on the Biology of the Cell (2019, background): “Protein stability (i.e., rate of protein degradation) is a significant regulator of steady-state protein abundance (Vogel et al. 2010; Vogel and Marcotte 2012).”
- Critical review on biofilm methods (2017, background): “…expression of several genes, and can thus affect the overall physiology of the cell (Brul et al., 2002), investigating the physiological response at transcriptomic levels simply provides information about the pool of the whole transcripts at a steady-state at a given time (Vogel & Marcotte, 2012).”
- High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue (2020, neutral): “28) was low but as expected according to literature (de Sousa Abreu et al., 2009; Vogel and Marcotte, 2012) (Figure S3C).”
- Integrated interactions database: tissue-specific view of the human and model organism interactomes (2015, background): “For example, expression of two genes in a given tissue may not mean that their two proteins will be present as well (36).”