RNA binding proteins (RBPs) orchestrate the production, processing, and function of mRNAs. Here, we present the affinity landscapes of 78 human RBPs using an unbiased assay that determines the sequence, structure, and context preferences of these proteins in vitro by deep sequencing of bound RNAs. These data enable construction of "RNA maps" of RBP activity without requiring crosslinking-based assays. We found an unexpectedly low diversity of RNA motifs, implying frequent convergence of binding specificity toward a relatively small set of RNA motifs, many with low compositional complexity. Offsetting this trend, however, we observed extensive preferences for contextual features distinct from short linear RNA motifs, including spaced "bipartite" motifs, biased flanking nucleotide composition, and bias away from or toward RNA structure. Our results emphasize the importance of contextual features in RNA recognition, which likely enable targeting of distinct subsets of transcripts by different RBPs that recognize the same linear motif.

Production of functional cellular RNAs involves multiple processing and regulatory steps principally mediated by RNA binding proteins (RBPs). Here we present the affinity landscapes of 78 human RBPs using an unbiased assay that determines the sequence, structure, and context preferences of an RBP in vitro from deep sequencing of bound RNAs. Analyses of these data revealed several interesting patterns, including unexpectedly low diversity of RNA motifs, implying frequent convergent evolution of binding specificity toward a relatively small set of RNA motifs, many with low compositional complexity. Offsetting this trend, we observed extensive preferences for contextual features outside of core RNA motifs, including spaced "bipartite" motifs, biased flanking nucleotide context, and bias away from or towards RNA structure.These contextual features are likely to enable targeting of distinct subsets of transcripts by different RBPs that recognize the same core motif. Our results enable construction of "RNA maps" of RBP activity without requiring crosslinking-based assays, and provide unprecedented depth of information on the interaction of RBPs with RNA..

The order of genes in eukaryotic genomes has generally been assumed to be neutral, since gene order is largely scrambled over evolutionary time. Only a handful of exceptional examples are known, typically involving deeply conserved clusters of tandemly duplicated genes (e.g., Hox genes and histones). Here we report the first systematic survey of microsynteny conservation across metazoans, utilizing 17 genome sequences. We identified nearly 600 pairs of unrelated genes that have remained tightly physically linked in diverse lineages across over 600 million years of evolution. Integrating sequence conservation, gene expression data, gene function, epigenetic marks, and other genomic features, we provide extensive evidence that many conserved ancient linkages involve (1) the coordinated transcription of neighboring genes, or (2) genomic regulatory blocks (GRBs) in which transcriptional enhancers controlling developmental genes are contained within nearby bystander genes. In addition, we generated ChIP-seq data for key histone modifications in zebrafish embryos, which provided further evidence of putative GRBs in embryonic development. Finally, using chromosome conformation capture (3C) assays and stable transgenic experiments, we demonstrate that enhancers within bystander genes drive the expression of genes such as Otx and Islet, critical regulators of central nervous system development across bilaterians. These results suggest that ancient genomic functional associations are far more common than previously thought-involving~12% of the ancestral bilaterian genome-and that cis-regulatory constraints are crucial in determining metazoan genome architecture.

Acidosis is a fundamental feature of the tumor microenvironment, which directly regulates tumor cell invasion by affecting immune cell function, clonal cell evolution, and drug resistance. Despite the important association of tumor microenvironment acidosis with tumor cell invasion, relatively little is known regarding which areas within a tumor are acidic and how acidosis influences gene expression to promote invasion. Here, we injected a labeled pH-responsive peptide to mark acidic regions within tumors. Surprisingly, acidic regions were not restricted to hypoxic areas and overlapped with highly proliferative, invasive regions at the tumor-stroma interface, which were marked by increased expression of matrix metalloproteinases and degradation of the basement membrane. RNA-seq analysis of cells exposed to low pH conditions revealed a general rewiring of the transcriptome that involved RNA splicing and enriched for targets of RNA binding proteins with specificity for AU-rich motifs. Alternative splicing of Mena and CD44, which play important isoform-specific roles in metastasis and drug resistance, respectively, was sensitive to histone acetylation status. Strikingly, this program of alternative splicing was reversed in vitro and in vivo through neutralization experiments that mitigated acidic conditions. These findings highlight a previously underappreciated role for localized acidification of tumor microenvironment in the expression of an alternative splicingdependent tumor invasion program.Significance: This study expands our understanding of acidosis within the tumor microenvironment and indicates that acidosis induces potentially therapeutically actionable changes to alternative splicing.

BackgroundDifferences in gene expression drive phenotypic differences between species, yet major organs and tissues generally have conserved gene expression programs. Several comparative transcriptomic studies have observed greater similarity in gene expression between homologous tissues from different vertebrate species than between diverse tissues of the same species. However, a recent study by Lin and colleagues reached the opposite conclusion. These studies differed in the species and tissues analyzed, and in technical details of library preparation, sequencing, read mapping, normalization, gene sets, and clustering methods.ResultsTo better understand gene expression evolution we reanalyzed data from four studies, including that of Lin, encompassing 6–13 tissues each from 11 vertebrate species using standardized mapping, normalization, and clustering methods. An analysis of independent data showed that the set of tissues chosen by Lin et al. were more similar to each other than those analyzed by previous studies. Comparing expression in five common tissues from the four studies, we observed that samples clustered exclusively by tissue rather than by species or study, supporting conservation of organ physiology in mammals. Furthermore, inter-study distances between homologous tissues were generally less than intra-study distances among different tissues, enabling informative meta-analyses. Notably, when comparing expression divergence of tissues over time to expression variation across 51 human GTEx tissues, we could accurately predict the clustering of expression for arbitrary pairs of tissues and species.ConclusionsThese results provide a framework for the design of future evolutionary studies of gene expression and demonstrate the utility of comparing RNA-seq data across studies.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0853-4) contains supplementary material, which is available to authorized users.