Luiz O. F. Penalva

A compendium of RNA-binding motifs for decoding gene regulation

RNA-binding proteins are key regulators of gene expression, yet only a small fraction have been functionally characterized. Here we report a systematic analysis of the RNA motifs recognized by RNA-binding proteins, encompassing 205 distinct genes from 24 diverse eukaryotes. The sequence specificities of RNA-binding proteins display deep evolutionary conservation, and the recognition preferences for a large fraction of metazoan RNA-binding proteins can thus be inferred from their RNA-binding domain sequence. The motifs that we identify in vitro correlate well with in vivo RNA-binding data. Moreover, we can associate them with distinct functional roles in diverse types of post-transcriptional regulation, enabling new insights into the functions of RNA-binding proteins both in normal physiology and in human disease. These data provide an unprecedented overview of RNA-binding proteins and their targets, and constitute an invaluable resource for determining post-transcriptional regulatory mechanisms in eukaryotes.

Global signatures of protein and mRNA expression levels

Cellular states are determined by differential expression of the cells proteins. The relationship between protein and mRNA expression levels informs about the combined outcomes of translation and protein degradation which are, in addition to transcription and mRNA stability, essential contributors to gene expression regulation. This review summarizes the state of knowledge about large-scale measurements of absolute protein and mRNA expression levels, and the degree of correlation between the two parameters. We summarize the information that can be derived from comparison of protein and mRNA expression levels and discuss how corresponding sequence characteristics suggest modes of regulation.

miR-33a/b contribute to the regulation of fatty acid metabolism and insulin signaling

Cellular imbalances of cholesterol and fatty acid metabolism result in pathological processes, including atherosclerosis and metabolic syndrome. Recent work from our group and others has shown that the intronic microRNAs hsa-miR-33a and hsa-miR-33b are located within the sterol regulatory element-binding protein-2 and -1 genes, respectively, and regulate cholesterol homeostasis in concert with their host genes. Here, we show that miR-33a and -b also regulate genes involved in fatty acid metabolism and insulin signaling. miR-33a and -b target key enzymes involved in the regulation of fatty acid oxidation, including carnitine O-octaniltransferase, carnitine palmitoyltransferase 1A, hydroxyacyl-CoA-dehydrogenase, Sirtuin 6 (SIRT6), and AMP kinase subunit-α. Moreover, miR-33a and -b also target the insulin receptor substrate 2, an essential component of the insulin-signaling pathway in the liver. Overexpression of miR-33a and -b reduces both fatty acid oxidation and insulin signaling in hepatic cell lines, whereas inhibition of endogenous miR-33a and -b increases these two metabolic pathways. Together, these data establish that miR-33a and -b regulate pathways controlling three of the risk factors of metabolic syndrome, namely levels of HDL, triglycerides, and insulin signaling, and suggest that inhibitors of miR-33a and -b may be useful in the treatment of this growing health concern.

Sequence signatures and mRNA concentration can explain two-thirds of protein abundance variation in a human cell line

Transcription, mRNA decay, translation and protein degradation are essential processes during eukaryotic gene expression, but their relative global contributions to steady‐state protein concentrations in multi‐cellular eukaryotes are largely unknown. Using measurements of absolute protein and mRNA abundances in cellular lysate from the human Daoy medulloblastoma cell line, we quantitatively evaluate the impact of mRNA concentration and sequence features implicated in translation and protein degradation on protein expression. Sequence features related to translation and protein degradation have an impact similar to that of mRNA abundance, and their combined contribution explains two‐thirds of protein abundance variation. mRNA sequence lengths, amino‐acid properties, upstream open reading frames and secondary structures in the 5′ untranslated region (UTR) were the strongest individual correlates of protein concentrations. In a combined model, characteristics of the coding region and the 3′UTR explained a larger proportion of protein abundance variation than characteristics of the 5′UTR. The absolute protein and mRNA concentration measurements for >1000 human genes described here represent one of the largest datasets currently available, and reveal both general trends and specific examples of post‐transcriptional regulation.

MicroRNA-16 and MicroRNA-424 Regulate Cell-Autonomous Angiogenic Functions in Endothelial Cells via Targeting Vascular Endothelial Growth Factor Receptor-2 and Fibroblast Growth Factor Receptor-1

Objective—MicroRNAs play key roles in modulating a variety of cellular processes by posttranscriptional regulation of their target genes. Vascular endothelial growth factor (VEGF), VEGF receptor-2 (VEGFR2), and fibroblast growth factor receptor-1 (FGFR1) were identified by bioinformatic approaches and subsequently validated as targets of microRNA (miR)-16 and miR-424 in endothelial cells (ECs). Methods and Results—Mimetics of these microRNAs reduced VEGF, VEGFR2, and FGFR1 expression, whereas specific antagonists enhanced their expression. Expression of mature miR-16 and miR-424 was upregulated on VEGF or basic fibroblast growth factor (bFGF) treatment. This upregulation was accompanied by a parallel increase in primary transcript (pri-miR)-16-1 and pri-miR-16-2 but not in pri-miR-424 levels, indicating a VEGF/bFGF-dependent transcriptional and posttranscriptional regulation of miR-16 and miR-424, respectively. Reduced expression of VEGFR2 and FGFR1 by miR-16 or miR-424 overexpression regulated VEGF and bFGF signaling through these receptors, thereby affecting the activity of downstream components of the pathways. Functionally, miR-16 or miR-424 overexpression reduced proliferation, migration, and cord formation of ECs in vitro, and lentiviral overexpression of miR-16 reduced the ability of ECs to form blood vessels in vivo. Conclusion—We conclude that these miRNAs fine-tune the expression of selected endothelial angiogenic mediators in response to these growth factors. Altogether, these findings suggest that miR-16 and miR-424 play important roles in regulating cell-intrinsic angiogenic activity of ECs.

RNA Binding Protein Sex-Lethal (Sxl) and Control of Drosophila Sex Determination and Dosage Compensation

SUMMARY In the past two decades, scientists have elucidated the molecular mechanisms behind Drosophila sex determination and dosage compensation. These two processes are controlled essentially by two different sets of genes, which have in common a master regulatory gene, Sex-lethal (Sxl). Sxl encodes one of the best-characterized members of the family of RNA binding proteins. The analysis of different mechanisms involved in the regulation of the three identified Sxl target genes (Sex-lethal itself, transformer, and male specific lethal-2) has contributed to a better understanding of translation repression, as well as constitutive and alternative splicing. Studies using the Drosophila system have identified the features of the protein that contribute to its target specificity and regulatory functions. In this article, we review the existing data concerning Sxl protein, its biological functions, and the regulation of its target genes.

Site identification in high-throughput RNA–protein interaction data

MOTIVATION Post-transcriptional and co-transcriptional regulation is a crucial link between genotype and phenotype. The central players are the RNA-binding proteins, and experimental technologies [such as cross-linking with immunoprecipitation- (CLIP-) and RIP-seq] for probing their activities have advanced rapidly over the course of the past decade. Statistically robust, flexible computational methods for binding site identification from high-throughput immunoprecipitation assays are largely lacking however. RESULTS We introduce a method for site identification which provides four key advantages over previous methods: (i) it can be applied on all variations of CLIP and RIP-seq technologies, (ii) it accurately models the underlying read-count distributions, (iii) it allows external covariates, such as transcript abundance (which we demonstrate is highly correlated with read count) to inform the site identification process and (iv) it allows for direct comparison of site usage across cell types or conditions. AVAILABILITY AND IMPLEMENTATION We have implemented our method in a software tool called Piranha. Source code and binaries, licensed under the GNU General Public License (version 3) are freely available for download from http://smithlab.usc.edu. CONTACT andrewds@usc.edu SUPPLEMENTARY INFORMATION Supplementary data available at Bioinformatics online.

Before It Gets Started: Regulating Translation at the 5′ UTR

Translation regulation plays important roles in both normal physiological conditions and diseases states. This regulation requires cis-regulatory elements located mostly in 5′ and 3′ UTRs and trans-regulatory factors (e.g., RNA binding proteins (RBPs)) which recognize specific RNA features and interact with the translation machinery to modulate its activity. In this paper, we discuss important aspects of 5′ UTR-mediated regulation by providing an overview of the characteristics and the function of the main elements present in this region, like uORF (upstream open reading frame), secondary structures, and RBPs binding motifs and different mechanisms of translation regulation and the impact they have on gene expression and human health when deregulated.

Genomic Analyses of Musashi1 Downstream Targets Show a Strong Association with Cancer-related Processes

Musashi1 (Msi1) is a highly conserved RNA-binding protein with pivotal functions in stem cell maintenance, nervous system development, and tumorigenesis. Despite its importance, only three direct mRNA targets have been characterized so far: m-numb, CDKN1A, and c-mos. Msi1 has been shown to affect their translation by binding to short elements located in the 3′-untranslated region. To better understand Msi1 functions, we initially performed an RIP-Chip analysis in HEK293T cells; this method consists of isolation of specific RNA-protein complexes followed by identification of the RNA component via microarrays. A group of 64 mRNAs was found to be enriched in the Msi1-associated population compared with controls. These genes belong to two main functional categories pertinent to tumorigenesis: 1) cell cycle, cell proliferation, cell differentiation, and apoptosis and 2) protein modification (including ubiquitination and ubiquitin cycle). To corroborate our findings, we examined the impact of Msi1 expression on both mRNA (transcriptomic) and protein (proteomic) expression levels. Genes whose mRNA levels were affected by Msi1 expression have a Gene Ontology distribution similar to RIP-Chip results, reinforcing Msi1 participation in cancer-related processes. The proteomics study revealed that Msi1 can have either positive or negative effects on gene expression of its direct targets. In summary, our results indicate that Msi1 affects a network of genes and could function as a master regulator during development and tumor formation.

Integrating shotgun proteomics and mRNA expression data to improve protein identification

Motivation: Tandem mass spectrometry (MS/MS) offers fast and reliable characterization of complex protein mixtures, but suffers from low sensitivity in protein identification. In a typical shotgun proteomics experiment, it is assumed that all proteins are equally likely to be present. However, there is often other information available, e.g. the probability of a proteins presence is likely to correlate with its mRNA concentration. Results: We develop a Bayesian score that estimates the posterior probability of a proteins presence in the sample given its identification in an MS/MS experiment and its mRNA concentration measured under similar experimental conditions. Our method, MSpresso, substantially increases the number of proteins identified in an MS/MS experiment at the same error rate, e.g. in yeast, MSpresso increases the number of proteins identified by ∼40%. We apply MSpresso to data from different MS/MS instruments, experimental conditions and organisms (Escherichia coli, human), and predict 19–63% more proteins across the different datasets. MSpresso demonstrates that incorporating prior knowledge of protein presence into shotgun proteomics experiments can substantially improve protein identification scores. Availability and Implementation: Software is available upon request from the authors. Mass spectrometry datasets and supplementary information are available from http://www.marcottelab.org/MSpresso/. Contact: marcotte@icmb.utexas.edu; miranker@cs.utexas.edu Supplementary Information: Supplementary data website: http://www.marcottelab.org/MSpresso/.