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A census of human RNA-binding proteins

Nature Reviews Genetics volume 15, pages 829–845 (2014)Cite this article

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Key Points

  • Recent advances in next-generation sequencing methods and quantitative mass spectrometry have renewed the interest in RNA biology and the genome-wide investigation of post-transcriptional gene regulatory proteins. A global census that systematically lists the number of factors involved in post-transcriptional gene regulation (PTGR) is currently not available. Here, we provide an overall summary of the proteins involved in interactions with all classes of RNAs based on our current knowledge of PTGR; this will guide future systems-wide studies of PTGR.

  • RNA-binding proteins (RBPs) are evolutionarily deeply conserved, and their structural domains diversified early in evolution.

  • RBPs are among the most abundant proteins in the cell and are generally ubiquitously expressed, which mirrors their central and conserved role in gene regulation.

  • Only ~2% of RBPs are tissue-specific, and most of these are mRNA- and non-coding RNA-binding proteins.

  • Diseases involving RBPs show characteristic phenotypes depending on the type of RNA (for example, mRNA, ribosomal RNA and tRNA) predominantly bound by the RBPs.

  • Correlated expression of RBPs across developmental processes can identify factors in shared PTGR pathways.

Abstract

Post-transcriptional gene regulation (PTGR) concerns processes involved in the maturation, transport, stability and translation of coding and non-coding RNAs. RNA-binding proteins (RBPs) and ribonucleoproteins coordinate RNA processing and PTGR. The introduction of large-scale quantitative methods, such as next-generation sequencing and modern protein mass spectrometry, has renewed interest in the investigation of PTGR and the protein factors involved at a systems-biology level. Here, we present a census of 1,542 manually curated RBPs that we have analysed for their interactions with different classes of RNA, their evolutionary conservation, their abundance and their tissue-specific expression. Our analysis is a critical step towards the comprehensive characterization of proteins involved in human RNA metabolism.

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Figure 1: Overview of the main post-transcriptional gene regulation pathways in eukaryotes.
Figure 2: Single or repeated presence of frequent RBDs in human genes.
Figure 3: Transcript abundance of RBPs and TFs across 16 different human tissues.
Figure 4: Target RNA classification and evolutionary conservation of RBP and TF paralogous families.
Figure 5: Tissue specificity of RBPs across 31 human tissues and organs.
Figure 6: Expression of RBPs across nine gestational stages of human fetal ovarian development.
Figure 7: Expression of RBPs across human fetal hippocampus development.

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Acknowledgements

The body map data were kindly provided by the Gene Expression Applications research group at Illumina. The authors thank P. Morozov, M. Carty, M. Brown, R. Kim and S. Lianoglou for discussions on the computational methods, as well as Z. Ozair, A. D. Haase and all laboratory members for comments on the manuscript. S.G. was supported by a Ph.D. fellowship from the Boehringer Ingelheim Fonds. M.H. is supported by the US National Institute of Arthritis and Musculoskeletal and Skin Diseases Intramural Research Program. T.T. is an Investigator of the Howard Hughes Medical Institute.

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Authors and Affiliations

  1. Howard Hughes Medical Institute and Laboratory for RNA Molecular Biology, The Rockefeller University, 1230 York Ave, 10065, New York, USA

    Stefanie Gerstberger & Thomas Tuschl

  2. Laboratory of Muscle Stem Cells and Gene Regulation, National Institute of Arthritis and Musculoskeletal and Skin Disease, National Institutes of Health, Bethesda, 20892, Maryland, USA

    Markus Hafner

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Correspondence to Thomas Tuschl.

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T.T. is a cofounder and scientific advisor to Alnylam Pharmaceuticals and a scientific advisor to Regulus Therapeutics. S.G. and M.H. declare no competing interests.

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Supplementary information

Glossary

Ribonucleoprotein

(RNP). Protein (or proteins) complexed with RNA as an obligate binding partner.

RNA-binding proteins

(RBPs). Proteins involved in the maturation, stability, transport and degradation of cellular RNAs. RBPs directly bind to RNA or are integral parts of macromolecular protein complexes that bind to RNA.

Non-coding RNA

(ncRNA). An RNA that does not encode a protein. In this Analysis, ncRNA is also used to specifically group together all remaining ncRNAs that are not ribosomal RNAs, tRNAs, small nuclear RNAs, small nucleolar RNAs or small Cajal body-specific RNAs.

RNA recognition elements

Short (rarely more than 4–6-nucleotide-long) sequence elements within RNA targets that are recognized and bound by RNA-binding proteins.

Crosslinking and immunoprecipitation followed by sequencing

(CLIP–seq). An experimental method to map the binding sites of RNA-binding proteins (RBPs) on RNA targets transcriptome-wide. RBPs are ultraviolet-crosslinked to RNA in vivo, followed by partial RNase treatment of cell lysates, immunoprecipitation of RBPs, recovery of covalently bound RNA, and small RNA cDNA library preparation for deep sequencing of crosslinked RNA segments.

RNA immunoprecipitation and sequencing

(RIP-seq). An experimental method to identify enrichment and targets of RNA-binding proteins (RBPs). RBPs are immunoprecipitated, and bound RNAs are library-prepared for deep sequencing.

Small Cajal body-specific RNAs

(scaRNAs). Small RNAs that have a similar structure and sequence to small nucleolar RNAs (snoRNAs), localize to the Cajal body and are involved in the methylation and pseudouridylation of snoRNAs.

RNA-binding domains

(RBDs). Structural protein domains that directly bind to RNA. In this Analysis, RBD is also used to include structural domains found exclusively in RNA-binding proteins that are able to transiently contact RNA during ribonucleoprotein assembly or disassembly.

Hidden Markov models

Statistical probability models that assume a Markov chain with unobserved (hidden) states. In protein domain predictions, HMMs are calculated from protein sequence alignments and compute the probability of a specific protein sequence.

Transcription factors

(TFs). Proteins that bind to specific DNA sequences at gene promoters, upstream and downstream elements, or within the gene body; they influence gene expression by enhancing or blocking transcription.

RPKM

(Reads per kilobase per million mapped reads). A measure for quantifying single-end read RNA-sequencing data per transcript or gene exon model; it normalizes the total number of mapped reads per transcript or gene exon model by the length of the transcript or gene exon model (in kilobases) and the library size (total number of reads mapped to the genome or transcriptome in million reads).

Small nuclear RNA

(snRNA). A type of short (~70–200-nucleotide) RNA found in the nucleus of eukaryotic cells. snRNAs associate with proteins of the spliceosome to form the spliceosomal core complexes.

Small nucleolar RNA

(snoRNA). A type of short (~50–200-nucleotide) RNA that is localized to the nucleolus and that guides methylation or pseudouridylation of ribosomal RNAs and small nuclear RNAs.

MicroRNA

(miRNA). A type of small (~21-nucleotide) non-coding RNA involved in post-transcriptional gene silencing. miRNAs form ribonucleoprotein complexes with Argonaute proteins to repress mRNA stability and protein expression by recruiting RNA deadenylation and degradation complexes to their RNA targets.

PIWI-interacting RNAs

(piRNAs). Small (~28-nucleotide) non-coding RNAs involved in post-transcriptional gene silencing that are expressed in the germ line; they form ribonucleoprotein complexes with PIWI proteins, and protect the genome from genomic instability by transcriptional and post-transcriptional repression of transposons.

Long ncRNAs

(lncRNAs). RNAs that do not encode proteins and are > 200 nucleotides long; they are found as structural components in nuclear and cytoplasmic ribonucleoprotein complexes and are transcribed by RNA polymerase II, similarly to mRNAs. Less abundant lncRNAs may influence the gene expression of neighbouring genes (in cis) at the transcriptional, post-transcriptional and translational levels.

Post-conception week

(PCW). A time measurement used to describe stages of human development in prenatal weeks. PCW records the time elapsed since the day of conception. Also commonly used is gestation week, which counts from the day of the last menstrual period. Assuming a normal 28-day menstrual cycle, PCW is 2 weeks less than gestation week.

3′ untranslated regions

(3′UTRs). 3′ ends of mRNAs, specifically the region between the stop codon and the poly(A) tail. 3′UTRs are targets of post-transcriptional regulation by many ribonucleoprotein and RNA-binding protein complexes, which determine their stability, translation and turnover.

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Gerstberger, S., Hafner, M. & Tuschl, T. A census of human RNA-binding proteins. Nat Rev Genet 15, 829–845 (2014). https://doi.org/10.1038/nrg3813

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