Systematic Discovery of Structural Elements Governing Mammalian mRNA Stability

Decoding post-transcriptional regulatory programs in RNA is a critical step towards the larger goal of developing predictive dynamical models of cellular behaviour. Despite recent efforts, the vast landscape of RNA regulatory elements remains largely uncharacterized. A long-standing obstacle is the contribution of local RNA secondary structure to the definition of interaction partners in a variety of regulatory contexts, including—but not limited to—transcript stability, alternative splicing and localization. There are many documented instances where the presence of a structural regulatory element dictates alternative splicing patterns (for example, human cardiac troponin T) or affects other aspects of RNA biology. Thus, a full characterization of post-transcriptional regulatory programs requires capturing information provided by both local secondary structures and the underlying sequence. Here we present a computational framework based on context-free grammars and mutual information that systematically explores the immense space of small structural elements and reveals motifs that are significantly informative of genome-wide measurements of RNA behaviour. By applying this framework to genome-wide human mRNA stability data, we reveal eight highly significant elements with substantial structural information, for the strongest of which we show a major role in global mRNA regulation. Through biochemistry, mass spectrometry and in vivo binding studies, we identified human HNRPA2B1 (heterogeneous nuclear ribonucleoprotein A2/B1, also known as HNRNPA2B1) as the key regulator that binds this element and stabilizes a large number of its target genes. We created a global post-transcriptional regulatory map based on the identity of the discovered linear and structural cis-regulatory elements, their regulatory interactions and their target pathways. This approach could also be used to reveal the structural elements that modulate other aspects of RNA behaviour.

[1]  Yongfeng Jin,et al.  RNA secondary structure in mutually exclusive splicing , 2011, Nature Structural &Molecular Biology.

[2]  Tyson A. Clark,et al.  HITS-CLIP yields genome-wide insights into brain alternative RNA processing , 2008, Nature.

[3]  P. Stadler,et al.  Secondary structure prediction for aligned RNA sequences. , 2002, Journal of molecular biology.

[4]  Jordan M. Komisarow,et al.  RIP-Chip: the isolation and identification of mRNAs, microRNAs and protein components of ribonucleoprotein complexes from cell extracts , 2006, Nature Protocols.

[5]  D. Searls,et al.  Robots in invertebrate neuroscience , 2002, Nature.

[6]  Michael A. Beer,et al.  Predicting Gene Expression from Sequence , 2004, Cell.

[7]  N. Slonim,et al.  A universal framework for regulatory element discovery across all genomes and data types. , 2007, Molecular cell.

[8]  Graziano Pesole,et al.  An algorithm for finding conserved secondary structure motifs in unaligned RNA sequences , 2008, Journal of Computer Science and Technology.

[9]  A. Mele,et al.  Ago HITS-CLIP decodes miRNA-mRNA interaction maps , 2009, Nature.

[10]  Brendan J. Frey,et al.  Deciphering the splicing code , 2010, Nature.

[11]  Robert B Darnell,et al.  CLIP: crosslinking and immunoprecipitation of in vivo RNA targets of RNA-binding proteins. , 2008, Methods in molecular biology.

[12]  S. Peltz,et al.  The cap-to-tail guide to mRNA turnover , 2001, Nature Reviews Molecular Cell Biology.

[13]  M. Mann,et al.  Universal sample preparation method for proteome analysis , 2009, Nature Methods.

[14]  N. Windbichler,et al.  Isolation of specific RNA-binding proteins using the streptomycin-binding RNA aptamer , 2006, Nature Protocols.

[15]  K. Cutroneo,et al.  Silencing or knocking out eukaryotic gene expression by oligodeoxynucleotide decoys. , 2006, Critical reviews in eukaryotic gene expression.

[16]  O. Elemento,et al.  Revealing global regulatory perturbations across human cancers. , 2009, Molecular cell.

[17]  M. Selbach,et al.  Global quantification of mammalian gene expression control , 2011, Nature.

[18]  Eran Segal,et al.  Computational prediction of RNA structural motifs involved in posttranscriptional regulatory processes , 2008, Proceedings of the National Academy of Sciences.

[19]  Olivier Elemento,et al.  An integrated ChIP-seq analysis platform with customizable workflows , 2011, BMC Bioinformatics.

[20]  R. Zimmer,et al.  High-resolution gene expression profiling for simultaneous kinetic parameter analysis of RNA synthesis and decay. , 2008, RNA.

[21]  Howard Y. Chang,et al.  Genome-wide measurement of RNA secondary structure in yeast , 2010, Nature.

[22]  Christian A. Rees,et al.  Systematic variation in gene expression patterns in human cancer cell lines , 2000, Nature Genetics.

[23]  G. Mauri,et al.  An algorithm for finding conserved secondary structure motifs in unaligned RNA sequences , 2008, Journal of Computer Science and Technology.

[24]  S. Riva,et al.  Two homologous genes, originated by duplication, encode the human hnRNP proteins A2 and A1. , 1994, Nucleic acids research.

[25]  Howard Y. Chang,et al.  Understanding the transcriptome through RNA structure , 2011, Nature Reviews Genetics.

[26]  J. Cáceres,et al.  Antagonistic role of hnRNP A1 and KSRP in the regulation of Let-7a biogenesis , 2010, Nature Structural &Molecular Biology.

[27]  Amanda J. Guise,et al.  Nuclear Import of Histone Deacetylase 5 by Requisite Nuclear Localization Signal Phosphorylation* , 2010, Molecular & Cellular Proteomics.