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.

The vast majority of genome-wide association study (GWAS) risk loci fall in non-coding regions of the genome. One possible hypothesis is that these GWAS risk loci alter the individual's disease risk through their effect on gene expression in different tissues. In order to understand the mechanisms driving a GWAS risk locus, it is helpful to determine which gene is affected in specific tissue types. For example, the relevant gene and tissue could play a role in the disease mechanism if the same variant responsible for a GWAS locus also affects gene expression. Identifying whether or not the same variant is causal in both GWASs and expression quantitative trail locus (eQTL) studies is challenging because of the uncertainty induced by linkage disequilibrium and the fact that some loci harbor multiple causal variants. However, current methods that address this problem assume that each locus contains a single causal variant. In this paper, we present eCAVIAR, a probabilistic method that has several key advantages over existing methods. First, our method can account for more than one causal variant in any given locus. Second, it can leverage summary statistics without accessing the individual genotype data. We use both simulated and real datasets to demonstrate the utility of our method. Using publicly available eQTL data on 45 different tissues, we demonstrate that eCAVIAR can prioritize likely relevant tissues and target genes for a set of glucose- and insulin-related trait loci.

Heterochromatin mainly comprises repeated DNA sequences that are prone to ectopic recombination. In Drosophila cells, 'safe' repair of heterochromatic double-strand breaks by homologous recombination relies on the relocalization of repair sites to the nuclear periphery before strand invasion. The mechanisms responsible for this movement were unknown. Here we show that relocalization occurs by directed motion along nuclear actin filaments assembled at repair sites by the Arp2/3 complex. Relocalization requires nuclear myosins associated with the heterochromatin repair complex Smc5/6 and the myosin activator Unc45, which is recruited to repair sites by Smc5/6. ARP2/3, actin nucleation and myosins also relocalize heterochromatic double-strand breaks in mouse cells. Defects in this pathway result in impaired heterochromatin repair and chromosome rearrangements. These findings identify de novo nuclear actin filaments and myosins as effectors of chromatin dynamics for heterochromatin repair and stability in multicellular eukaryotes.

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