CPSF30 and Wdr33 directly bind to AAUAAA in mammalian mRNA 3' processing.

AAUAAA is the most highly conserved motif in eukaryotic mRNA polyadenylation sites and, in mammals, is specifically recognized by the multisubunit CPSF (cleavage and polyadenylation specificity factor) complex. Despite its critical functions in mRNA 3' end formation, the molecular basis for CPSF-AAUAAA interaction remains poorly defined. The CPSF subunit CPSF160 has been implicated in AAUAAA recognition, but direct evidence has been lacking. Using in vitro and in vivo assays, we unexpectedly found that CPSF subunits CPSF30 and Wdr33 directly contact AAUAAA. Importantly, the CPSF30-RNA interaction is essential for mRNA 3' processing and is primarily mediated by its zinc fingers 2 and 3, which are specifically targeted by the influenza protein NS1A to suppress host mRNA 3' processing. Our data suggest that AAUAAA recognition in mammalian mRNA 3' processing is more complex than previously thought and involves multiple protein-RNA interactions.

Fip1 regulates mRNA alternative polyadenylation to promote stem cell self-renewal.

mRNA alternative polyadenylation (APA) plays a critical role in post-transcriptional gene control and is highly regulated during development and disease. However, the regulatory mechanisms and functional consequences of APA remain poorly understood. Here, we show that an mRNA 3' processing factor, Fip1, is essential for embryonic stem cell (ESC) self-renewal and somatic cell reprogramming. Fip1 promotes stem cell maintenance, in part, by activating the ESC-specific APA profiles to ensure the optimal expression of a specific set of genes, including critical self-renewal factors. Fip1 expression and the Fip1-dependent APA program change during ESC differentiation and are restored to an ESC-like state during somatic reprogramming. Mechanistically, we provide evidence that the specificity of Fip1-mediated APA regulation depends on multiple factors, including Fip1-RNA interactions and the distance between APA sites. Together, our data highlight the role for post-transcriptional control in stem cell self-renewal, provide mechanistic insight on APA regulation in development, and establish an important function for APA in cell fate specification.

Poly(A) code analyses reveal key determinants for tissue-specific mRNA alternative polyadenylation.

mRNA alternative polyadenylation (APA) is a critical mechanism for post-transcriptional gene regulation and is often regulated in a tissue- and/or developmental stage-specific manner. An ultimate goal for the APA field has been to be able to computationally predict APA profiles under different physiological or pathological conditions. As a first step toward this goal, we have assembled a poly(A) code for predicting tissue-specific poly(A) sites (PASs). Based on a compendium of over 600 features that have known or potential roles in PAS selection, we have generated and refined a machine-learning algorithm using multiple high-throughput sequencing-based data sets of tissue-specific and constitutive PASs. This code can predict tissue-specific PASs with >85% accuracy. Importantly, by analyzing the prediction performance based on different RNA features, we found that PAS context, including the distance between alternative PASs and the relative position of a PAS within the gene, is a key feature for determining the susceptibility of a PAS to tissue-specific regulation. Our poly(A) code provides a useful tool for not only predicting tissue-specific APA regulation, but also for studying its underlying molecular mechanisms.

Overlapping and distinct functions of CstF64 and CstF64τ in mammalian mRNA 3' processing.

mRNA 3' processing is dynamically regulated spatially and temporally. However, the underlying mechanisms remain poorly understood. CstF64τ is a paralog of the general mRNA 3' processing factor, CstF64, and has been implicated in mediating testis-specific mRNA alternative polyadenylation (APA). However, the functions of CstF64τ in mRNA 3' processing have not been systematically investigated. We carried out a comprehensive characterization of CstF64τ and compared its properties to those of CstF64. In contrast to previous reports, we found that both CstF64 and CstF64τ are widely expressed in mammalian tissues, and their protein levels display tissue-specific variations. We further demonstrated that CstF64 and CstF64τ have highly similar RNA-binding specificities both in vitro and in vivo. CstF64 and CstF64τ modulate one another's expression and play overlapping as well as distinct roles in regulating global APA profiles. Interestingly, protein interactome analyses revealed key differences between CstF64 and CstF64τ, including their interactions with another mRNA 3' processing factor, symplekin. Together, our study of CstF64 and CstF64τ revealed both functional overlap and specificity of these two important mRNA 3' processing factors and provided new insights into the regulatory mechanisms of mRNA 3' processing.

Transcriptome-wide analyses of CstF64-RNA interactions in global regulation of mRNA alternative polyadenylation.

Cleavage stimulation factor 64 kDa (CstF64) is an essential pre-mRNA 3' processing factor and an important regulator of alternative polyadenylation (APA). Here we characterized CstF64-RNA interactions in vivo at the transcriptome level and investigated the role of CstF64 in global APA regulation through individual nucleotide resolution UV crosslinking and immunoprecipitation sequencing and direct RNA sequencing analyses. We observed highly specific CstF64-RNA interactions at poly(A) sites (PASs), and we provide evidence that such interactions are widely variable in affinity and may be differentially required for PAS recognition. Depletion of CstF64 by RNAi has a relatively small effect on the global APA profile, but codepletion of the CstF64 paralog CstF64τ leads to greater APA changes, most of which are characterized by the increased relative use of distal PASs. Finally, we found that CstF64 binds to thousands of dormant intronic PASs that are suppressed, at least in part, by U1 small nuclear ribonucleoproteins. Taken together, our findings provide insight into the mechanisms of PAS recognition and identify CstF64 as an important global regulator of APA.

Hobbes: optimized gram-based methods for efficient read alignment.

Recent advances in sequencing technology have enabled the rapid generation of billions of bases at relatively low cost. A crucial first step in many sequencing applications is to map those reads to a reference genome. However, when the reference genome is large, finding accurate mappings poses a significant computational challenge due to the sheer amount of reads, and because many reads map to the reference sequence approximately but not exactly. We introduce Hobbes, a new gram-based program for aligning short reads, supporting Hamming and edit distance. Hobbes implements two novel techniques, which yield substantial performance improvements: an optimized gram-selection procedure for reads, and a cache-efficient filter for pruning candidate mappings. We systematically tested the performance of Hobbes on both real and simulated data with read lengths varying from 35 to 100 bp, and compared its performance with several state-of-the-art read-mapping programs, including Bowtie, BWA, mrsFast and RazerS. Hobbes is faster than all other read mapping programs we have tested while maintaining high mapping quality. Hobbes is about five times faster than Bowtie and about 2-10 times faster than BWA, depending on read length and error rate, when asked to find all mapping locations of a read in the human genome within a given Hamming or edit distance, respectively. Hobbes supports the SAM output format and is publicly available at http://hobbes.ics.uci.edu.

SNP-based pathway enrichment analysis for genome-wide association studies.

BACKGROUND: Recently we have witnessed a surge of interest in using genome-wide association studies (GWAS) to discover the genetic basis of complex diseases. Many genetic variations, mostly in the form of single nucleotide polymorphisms (SNPs), have been identified in a wide spectrum of diseases, including diabetes, cancer, and psychiatric diseases. A common theme arising from these studies is that the genetic variations discovered by GWAS can only explain a small fraction of the genetic risks associated with the complex diseases. New strategies and statistical approaches are needed to address this lack of explanation. One such approach is the pathway analysis, which considers the genetic variations underlying a biological pathway, rather than separately as in the traditional GWAS studies. A critical challenge in the pathway analysis is how to combine evidences of association over multiple SNPs within a gene and multiple genes within a pathway. Most current methods choose the most significant SNP from each gene as a representative, ignoring the joint action of multiple SNPs within a gene. This approach leads to preferential identification of genes with a greater number of SNPs. RESULTS: We describe a SNP-based pathway enrichment method for GWAS studies. The method consists of the following two main steps: 1) for a given pathway, using an adaptive truncated product statistic to identify all representative (potentially more than one) SNPs of each gene, calculating the average number of representative SNPs for the genes, then re-selecting the representative SNPs of genes in the pathway based on this number; and 2) ranking all selected SNPs by the significance of their statistical association with a trait of interest, and testing if the set of SNPs from a particular pathway is significantly enriched with high ranks using a weighted Kolmogorov-Smirnov test. We applied our method to two large genetically distinct GWAS data sets of schizophrenia, one from European-American (EA) and the other from African-American (AA). In the EA data set, we found 22 pathways with nominal P-value less than or equal to 0.001 and corresponding false discovery rate (FDR) less than 5%. In the AA data set, we found 11 pathways by controlling the same nominal P-value and FDR threshold. Interestingly, 8 of these pathways overlap with those found in the EA sample. We have implemented our method in a JAVA software package, called SNP Set Enrichment Analysis (SSEA), which contains a user-friendly interface and is freely available at http://cbcl.ics.uci.edu/SSEA. CONCLUSIONS: The SNP-based pathway enrichment method described here offers a new alternative approach for analysing GWAS data. By applying it to schizophrenia GWAS studies, we show that our method is able to identify statistically significant pathways, and importantly, pathways that can be replicated in large genetically distinct samples.

Global protein-RNA interaction mapping at single nucleotide resolution by iCLIP-seq.

Eukaryotic genomes encode a large number of RNA-binding proteins, which play critical roles in many aspects of gene regulation. To functionally characterize these proteins, a key step is to map their interactions with target RNAs. UV crosslinking and immunoprecipitation coupled with high-throughput sequencing has become the standard method for this purpose. Here we describe the detailed procedure that we have used to characterize the protein-RNA interactions of the mRNA 3' processing factors.