An Abundance of Ubiquitously Expressed Genes Revealed by Tissue Transcriptome Sequence Data

By Daniel Ramsköld, Eric T. Wang, C. Burge, Rickard Sandberg. PLoS Comput. Biol., 2009

883 citations recorded by the source corpus.

The parts of the genome transcribed by a cell or tissue reflect the biological processes and functions it carries out. We characterized the features of mammalian tissue transcriptomes at the gene level through analysis of RNA deep sequencing (RNA-Seq) data across human and mouse tissues and cell lines. We observed that roughly 8,000 protein-coding genes were ubiquitously expressed, contributing to around 75% of all mRNAs by message copy number in most tissues. These mRNAs encoded proteins that were often intracellular, and tended to be involved in metabolism, transcription, RNA processing or translation. In contrast, genes for secreted or plasma membrane proteins were generally expressed in only a subset of tissues. The distribution of expression levels was broad but fairly continuous: no support was found for the concept of distinct expression classes of genes. Expression estimates that included reads mapping to coding exons only correlated better with qRT-PCR data than estimates which also included 3′ untranslated regions (UTRs). Muscle and liver had the least complex transcriptomes, in that they expressed predominantly ubiquitous genes and a large fraction of the transcripts came from a few highly expressed genes, whereas brain, kidney and testis expressed more complex transcriptomes with the vast majority of genes expressed and relatively small contributions from the most expressed genes. mRNAs expressed in brain had unusually long 3′UTRs, and mean 3′UTR length was higher for genes involved in development, morphogenesis and signal transduction, suggesting added complexity of UTR-based regulation for these genes. Our results support a model in which variable exterior components feed into a large, densely connected core composed of ubiquitously expressed intracellular proteins.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/10f8200a3eb5fc9fbe042b1d37fab1d9c10b51f6

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Citations in the corpus

m6A RNA methylation: from mechanisms to therapeutic potential (2021, neutral): “…a nuclease-inactivated Cas13b-YTHDF1 fusion protein promoted translation, while targeting YTHDF2 via an analogous fusion protein led to degradation (Rauch et al , 2018). m 6 A has also been shown to enhance phase separation of YTHDF m 6 A reader proteins and regulate their subcellular localization…”
Human protein interaction networks across tissues and diseases (2015, background): “The application of RNA-sequencing to human tissues revealed that many more transcripts were expressed per tissue than previously acknowledged (Ramsköld et al., 2009).”
Ab initio reconstruction of transcriptomes of pluripotent and lineage committed cells reveals gene structures of thousands of lincRNAs (2010, result): “Overall, we find that the ratio of expressed protein-coding to non-coding genes in these cell types is ~10:1, but that the total number of RNA molecules is more heavily biased toward the protein-coding fraction (~30:1), similar to previous observations 26 .”
Deep proteome and transcriptome mapping of a human cancer cell line (2011, background): “This presumably reflects the often cell typespecific functions of these proteins (Lundberg et al, 2010; Ramskold et al, 2009).”
Modeling gene expression using chromatin features in various cellular contexts (2012, neutral): “Previous studies have shown that CpG-rich promoters are associated with ubiquitously expressed genes while CpG-poor (and often TATA-containing) promoters are associated with cell type-specific genes [27-29] and have different patterns of histone modifications [29].”
An RNA-Sequencing Transcriptome and Splicing Database of Glia, Neurons, and Vascular Cells of the Cerebral Cortex (2014, methodology): “…assess the accuracy and reliability of our RNA-Seq experiments, we applied a widely used procedure to determine the threshold for reliable FPKM estimation based on optimizing the intersection of falsepositive and false-negative rates (Ramskold et al., 2009; Lerch et al., 2012; Chen et al., 2013).”
Tissue-based map of the human proteome (2015, result): “3C) supports earlier suggestions (21, 26) that a larger fraction of tissue-enriched proteins are secreted or membrane-spanning proteins than are intracellular proteins.”
CTCF-promoted RNA polymerase II pausing links DNA methylation to splicing (2011, neutral): “First we computed the expression level of each Refseq transcript as reads per kilobase and million mappable reads using the rpkmforgenes progra”
Single-Cell Transcriptome Profiling of Human Pancreatic Islets in Health and Type 2 Diabetes (2016, methodology): “3.0e) and uniquely aligned reads within RefSeq gene annotations were used to quantify gene expression as reads per kilobase transcript and million mapped reads (RPKMs) using rpkmforgenes (Ramsköld et al., 2009).”
Long Non-coding RNAs in the Cytoplasm (2016, background): “This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).”