Regulation of alternative splicing by p300-mediated acetylation of splicing factors.

Splicing of precursor mRNA (pre-mRNA) is an important regulatory step in gene expression. Recent evidence points to a regulatory role of chromatin-related proteins in alternative splicing regulation. Using an unbiased approach, we have identified the acetyltransferase p300 as a key chromatin-related regulator of alternative splicing. p300 promotes genome-wide exon inclusion in both a transcription-dependent and -independent manner. Using CD44 as a paradigm, we found that p300 regulates alternative splicing by modulating the binding of splicing factors to pre-mRNA. Using a tethering strategy, we found that binding of p300 to the CD44 promoter region promotes CD44v exon inclusion independently of RNAPII transcriptional elongation rate. Promoter-bound p300 regulates alternative splicing by acetylating splicing factors, leading to exclusion of hnRNP M from CD44 pre-mRNA and activation of Sam68. p300-mediated CD44 alternative splicing reduces cell motility and promotes epithelial features. Our findings reveal a chromatin-related mechanism of alternative splicing regulation and demonstrate its impact on cellular function.

Evaluation of COVID-19 RT-qPCR Test in Multi sample Pools.

BACKGROUND: The recent emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to a current pandemic of unprecedented scale. Although diagnostic tests are fundamental to the ability to detect and respond, overwhelmed healthcare systems are already experiencing shortages of reagents associated with this test, calling for a lean immediately applicable protocol. METHODS: RNA extracts of positive samples were tested for the presence of SARS-CoV-2 using reverse transcription quantitative polymerase chain reaction, alone or in pools of different sizes (2-, 4-, 8-, 16-, 32-, and 64-sample pools) with negative samples. Transport media of additional 3 positive samples were also tested when mixed with transport media of negative samples in pools of 8. RESULTS: A single positive sample can be detected in pools of up to 32 samples, using the standard kits and protocols, with an estimated false negative rate of 10%. Detection of positive samples diluted in even up to 64 samples may also be attainable, although this may require additional amplification cycles. Single positive samples can be detected when pooling either after or prior to RNA extraction. CONCLUSIONS: As it uses the standard protocols, reagents, and equipment, this pooling method can be applied immediately in current clinical testing laboratories. We hope that such implementation of a pool test for coronavirus disease 2019 would allow expanding current screening capacities, thereby enabling the expansion of detection in the community, as well as in close organic groups, such as hospital departments, army units, or factory shifts.

SMARTIV: combined sequence and structure de-novo motif discovery for in-vivo RNA binding data.

Gene expression regulation is highly dependent on binding of RNA-binding proteins (RBPs) to their RNA targets. Growing evidence supports the notion that both RNA primary sequence and its local secondary structure play a role in specific Protein-RNA recognition and binding. Despite the great advance in high-throughput experimental methods for identifying sequence targets of RBPs, predicting the specific sequence and structure binding preferences of RBPs remains a major challenge. We present a novel webserver, SMARTIV, designed for discovering and visualizing combined RNA sequence and structure motifs from high-throughput RNA-binding data, generated from in-vivo experiments. The uniqueness of SMARTIV is that it predicts motifs from enriched k-mers that combine information from ranked RNA sequences and their predicted secondary structure, obtained using various folding methods. Consequently, SMARTIV generates Position Weight Matrices (PWMs) in a combined sequence and structure alphabet with assigned P-values. SMARTIV concisely represents the sequence and structure motif content as a single graphical logo, which is informative and easy for visual perception. SMARTIV was examined extensively on a variety of high-throughput binding experiments for RBPs from different families, generated from different technologies, showing consistent and accurate results. Finally, SMARTIV is a user-friendly webserver, highly efficient in run-time and freely accessible via http://smartiv.technion.ac.il/.

A widespread role of the motif environment in transcription factor binding across diverse protein families.

Transcriptional regulation requires the binding of transcription factors (TFs) to short sequence-specific DNA motifs, usually located at the gene regulatory regions. Interestingly, based on a vast amount of data accumulated from genomic assays, it has been shown that only a small fraction of all potential binding sites containing the consensus motif of a given TF actually bind the protein. Recent in vitro binding assays, which exclude the effects of the cellular environment, also demonstrate selective TF binding. An intriguing conjecture is that the surroundings of cognate binding sites have unique characteristics that distinguish them from other sequences containing a similar motif that are not bound by the TF. To test this hypothesis, we conducted a comprehensive analysis of the sequence and DNA shape features surrounding the core-binding sites of 239 and 56 TFs extracted from in vitro HT-SELEX binding assays and in vivo ChIP-seq data, respectively. Comparing the nucleotide content of the regions around the TF-bound sites to the counterpart unbound regions containing the same consensus motifs revealed significant differences that extend far beyond the core-binding site. Specifically, the environment of the bound motifs demonstrated unique sequence compositions, DNA shape features, and overall high similarity to the core-binding motif. Notably, the regions around the binding sites of TFs that belong to the same TF families exhibited similar features, with high agreement between the in vitro and in vivo data sets. We propose that these unique features assist in guiding TFs to their cognate binding sites.

A combined sequence and structure based method for discovering enriched motifs in RNA from in vivo binding data.

RNA binding proteins (RBPs) play an important role in regulating many processes in the cell. RBPs often recognize their RNA targets in a specific manner. In addition to the RNA primary sequence, the structure of the RNA has been shown to play a central role in RNA recognition by RBPs. In recent years, many experimental approaches, both in vitro and in vivo, were developed and employed to identify and characterize RBP targets and extract their binding specificities. In vivo binding techniques, such as CrossLinking and ImmunoPrecipitation (CLIP)-based methods, enable the characterization of protein binding sites on RNA targets. However, these methods do not provide information regarding the structural preferences of the protein. While methods to obtain the structure of RNA are available, inferring both the sequence and the structure preferences of RBPs remains a challenge. Here we present SMARTIV, a novel computational tool for discovering combined sequence and structure binding motifs from in vivo RNA binding data relying on the sequences of the target sites, the ranking of their binding scores and their predicted secondary structure. The combined motifs are provided in a unified representation that is informative and easy for visual perception. We tested the method on CLIP-seq data from different platforms for a variety of RBPs. Overall, we show that our results are highly consistent with known binding motifs of RBPs, offering additional information on their structural preferences.

How motif environment influences transcription factor search dynamics: Finding a needle in a haystack.

Transcription factors (TFs) have to find their binding sites, which are distributed throughout the genome. Facilitated diffusion is currently the most widely accepted model for this search process. Based on this model the TF alternates between one-dimensional sliding along the DNA, and three-dimensional bulk diffusion. In this view, the non-specific associations between the proteins and the DNA play a major role in the search dynamics. However, little is known about how the DNA properties around the motif contribute to the search. Accumulating evidence showing that TF binding sites are embedded within a unique environment, specific to each TF, leads to the hypothesis that the search process is facilitated by favorable DNA features that help to improve the search efficiency. Here, we review the field and present the hypothesis that TF-DNA recognition is dictated not only by the motif, but is also influenced by the environment in which the motif resides.

BindUP: a web server for non-homology-based prediction of DNA and RNA binding proteins.

Gene expression is a multi-step process involving many layers of regulation. The main regulators of the pathway are DNA and RNA binding proteins. While over the years, a large number of DNA and RNA binding proteins have been identified and extensively studied, it is still expected that many other proteins, some with yet another known function, are awaiting to be discovered. Here we present a new web server, BindUP, freely accessible through the website http://bindup.technion.ac.il/, for predicting DNA and RNA binding proteins using a non-homology-based approach. Our method is based on the electrostatic features of the protein surface and other general properties of the protein. BindUP predicts nucleic acid binding function given the proteins three-dimensional structure or a structural model. Additionally, BindUP provides information on the largest electrostatic surface patches, visualized on the server. The server was tested on several datasets of DNA and RNA binding proteins, including proteins which do not possess DNA or RNA binding domains and have no similarity to known nucleic acid binding proteins, achieving very high accuracy. BindUP is applicable in either single or batch modes and can be applied for testing hundreds of proteins simultaneously in a highly efficient manner.

Mutual enrichment in aggregated ranked lists with applications to gene expression regulation.

MOTIVATION: It is often the case in biological measurement data that results are given as a ranked list of quantities-for example, differential expression (DE) of genes as inferred from microarrays or RNA-seq. Recent years brought considerable progress in statistical tools for enrichment analysis in ranked lists. Several tools are now available that allow users to break the fixed set paradigm in assessing statistical enrichment of sets of genes. Continuing with the example, these tools identify factors that may be associated with measured differential expression. A drawback of existing tools is their focus on identifying single factors associated with the observed or measured ranks, failing to address relationships between these factors. For example, a scenario in which genes targeted by multiple miRNAs play a central role in the DE signal but the effect of each single miRNA is too subtle to be detected, as shown in our results. RESULTS: We propose statistical and algorithmic approaches for selecting a sub-collection of factors that can be aggregated into one ranked list that is heuristically most associated with an input ranked list (pivot). We examine performance on simulated data and apply our approach to cancer datasets. We find small sub-collections of miRNA that are statistically associated with gene DE in several types of cancer, suggesting miRNA cooperativity in driving disease related processes. Many of our findings are consistent with known roles of miRNAs in cancer, while others suggest previously unknown roles for certain miRNAs. AVAILABILITY AND IMPLEMENTATION: Code and instructions for our algorithmic framework, MULSEA, are in: https://github.com/YakhiniGroup/MULSEAContact:dalia.cohn@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A diverse epigenetic landscape at human exons with implication for expression.

DNA methylation is an important epigenetic marker associated with gene expression regulation in eukaryotes. While promoter methylation is relatively well characterized, the role of intragenic DNA methylation remains unclear. Here, we investigated the relationship of DNA methylation at exons and flanking introns with gene expression and histone modifications generated from a human fibroblast cell-line and primary B cells. Consistent with previous work we found that intragenic methylation is positively correlated with gene expression and that exons are more highly methylated than their neighboring intronic environment. Intriguingly, in this study we identified a unique subset of hypomethylated exons that demonstrate significantly lower methylation levels than their surrounding introns. Furthermore, we observed a negative correlation between exon methylation and the density of the majority of histone modifications. Specifically, we demonstrate that hypo-methylated exons at highly expressed genes are associated with open chromatin and have a characteristic histone code comprised of significantly high levels of histone markings. Overall, our comprehensive analysis of the human exome supports the presence of regulatory hypomethylated exons in protein coding genes. In particular our results reveal a previously unrecognized diverse and complex role of the epigenetic landscape within the gene body.

PfSR1 controls alternative splicing and steady-state RNA levels in Plasmodium falciparum through preferential recognition of specific RNA motifs.

Plasmodium species have evolved complex biology to adapt to different hosts and changing environments throughout their life cycle. Remarkably, these adaptations are achieved by a relatively small genome. One way by which the parasite expands its proteome is through alternative splicing (AS). We recently identified PfSR1 as a bona fide Ser/Arg-rich (SR) protein that shuttles between the nucleus and cytoplasm and regulates AS in Plasmodium falciparum. Here we show that PfSR1 is localized adjacent to the Nuclear Pore Complex (NPC) clusters in the nucleus of early stage parasites. To identify the endogenous RNA targets of PfSR1, we adapted an inducible overexpression system for tagged PfSR1 and performed RNA immunoprecipitation followed by microarray analysis (RIP-chip) to recover and identify the endogenous RNA targets that bind PfSR1. Bioinformatic analysis of these RNAs revealed common sequence motifs potentially recognized by PfSR1. RNA-EMSAs show that PfSR1 preferentially binds RNA molecules containing these motifs. Interestingly, we find that PfSR1 not only regulates AS but also the steady-state levels of mRNAs containing these motifs in vivo.

A complex immunodeficiency is based on U1 snRNP-mediated poly(A) site suppression.

Biallelic mutations in the untranslated regions (UTRs) of mRNAs are rare causes for monogenetic diseases whose mechanisms remain poorly understood. We investigated a 3'UTR mutation resulting in a complex immunodeficiency syndrome caused by decreased mRNA levels of p14/robld3 by a previously unknown mechanism. Here, we show that the mutation creates a functional 5' splice site (SS) and that its recognition by the spliceosomal component U1 snRNP causes p14 mRNA suppression in the absence of splicing. Histone processing signals are able to rescue p14 expression. Therefore, the mutation interferes only with canonical poly(A)-site 3' end processing. Our data suggest that U1 snRNP inhibits cleavage or poly(A) site recognition. This is the first description of a 3'UTR mutation that creates a functional 5'SS causative of a monogenetic disease. Moreover, our data endorse the recently described role of U1 snRNP in suppression of intronic poly(A) sites, which is here deleterious for p14 mRNA biogenesis.

ORF57 overcomes the detrimental sequence bias of Kaposi's sarcoma-associated herpesvirus lytic genes.

UNLABELLED: Kaposi's sarcoma-associated herpesvirus (KSHV) encodes ORF57, which enhances the expression of intronless KSHV genes on multiple posttranscriptional levels. However, it remains elusive how ORF57 recognizes viral RNAs. Here, we demonstrate that ORF57 also increases the expression of the multiple intron-containing K15 gene. The nucleotide bias of the K15 cDNA revealed an unusual high AT content. Thus, we optimized the K15 cDNA by raising the frequency of GC nucleotides, yielding an ORF57-independent version. To further prove the importance of the sequence bias of ORF57-dependent RNAs, we grouped KSHV mRNAs according to their AT content and found a correlation between AT-richness and ORF57 dependency. More importantly, latent genes, which have to be expressed in the absence of ORF57, have a low AT content and are indeed ORF57 independent. The nucleotide composition of K15 resembles that of HIV gag, which cannot be expressed unless RNA export is facilitated by the HIV Rev protein. Interestingly, ORF57 can partially rescue HIV Gag expression. Thus, the KSHV target RNAs of ORF57 and HIV gag RNA may share certain motifs based on the nucleotide bias. A bioinformatic comparison between wild-type and sequence-optimized K15 revealed a higher density for hnRNP-binding motifs in the former. We speculate that binding of particular hnRNPs to KSHV lytic transcripts is the prerequisite for ORF57 to enhance their expression. IMPORTANCE: The mostly intronless genes of KSHV are only expressed in the presence of the viral regulator protein ORF57, but how ORF57 recognizes viral RNAs remains elusive. We focused on the multiple intron-containing KSHV gene K15 and revealed that its expression is also increased by ORF57. Moreover, sequences in the K15 cDNA mediate this enhancement. The quest for a target sequence or a response element for ORF57 in the lytic genes was not successful. Instead, we found the nucleotide bias to be the critical determinant of ORF57 dependency. Based on the fact that ORF57 has only a weak affinity for nucleic acids, we speculate that a cellular RNA-binding protein provides the sequence preference for ORF57. This study provides evidence that herpesviral RNA regulator proteins use the sequence bias of lytic genes and the resulting composition of the viral mRNP to distinguish between viral and cellular mRNAs.

Covariation between homeodomain transcription factors and the shape of their DNA binding sites.

Protein-DNA recognition is a critical component of gene regulatory processes but the underlying molecular mechanisms are not yet completely understood. Whereas the DNA binding preferences of transcription factors (TFs) are commonly described using nucleotide sequences, the 3D DNA structure is recognized by proteins and is crucial for achieving binding specificity. However, the ability to analyze DNA shape in a high-throughput manner made it only recently feasible to integrate structural information into studies of protein-DNA binding. Here we focused on the homeodomain family of TFs and analyzed the DNA shape of thousands of their DNA binding sites, investigating the covariation between the protein sequence and the sequence and shape of their DNA targets. We found distinct homeodomain regions that were more correlated with either the nucleotide sequence or the DNA shape of their preferred binding sites, demonstrating different readout mechanisms through which homeodomains attain DNA binding specificity. We identified specific homeodomain residues that likely play key roles in DNA recognition via shape readout. Finally, we showed that adding DNA shape information when characterizing binding sites improved the prediction accuracy of homeodomain binding specificities. Taken together, our findings indicate that DNA shape information can generally provide new mechanistic insights into TF binding.

RBPmap: a web server for mapping binding sites of RNA-binding proteins.

Regulation of gene expression is executed in many cases by RNA-binding proteins (RBPs) that bind to mRNAs as well as to non-coding RNAs. RBPs recognize their RNA target via specific binding sites on the RNA. Predicting the binding sites of RBPs is known to be a major challenge. We present a new webserver, RBPmap, freely accessible through the website http://rbpmap.technion.ac.il/ for accurate prediction and mapping of RBP binding sites. RBPmap has been developed specifically for mapping RBPs in human, mouse and Drosophila melanogaster genomes, though it supports other organisms too. RBPmap enables the users to select motifs from a large database of experimentally defined motifs. In addition, users can provide any motif of interest, given as either a consensus or a PSSM. The algorithm for mapping the motifs is based on a Weighted-Rank approach, which considers the clustering propensity of the binding sites and the overall tendency of regulatory regions to be conserved. In addition, RBPmap incorporates a position-specific background model, designed uniquely for different genomic regions, such as splice sites, 5' and 3' UTRs, non-coding RNA and intergenic regions. RBPmap was tested on high-throughput RNA-binding experiments and was proved to be highly accurate.

RNA-dependent chromatin localization of KDM4D lysine demethylase promotes H3K9me3 demethylation.

The JmjC-containing lysine demethylase, KDM4D, demethylates di-and tri-methylation of histone H3 on lysine 9 (H3K9me3). How KDM4D is recruited to chromatin and recognizes its histone substrates remains unknown. Here, we show that KDM4D binds RNA independently of its demethylase activity. We mapped two non-canonical RNA binding domains: the first is within the N-terminal spanning amino acids 115 to 236, and the second is within the C-terminal spanning amino acids 348 to 523 of KDM4D. We also demonstrate that RNA interactions with KDM4D N-terminal region are critical for its association with chromatin and subsequently for demethylating H3K9me3 in cells. This study implicates, for the first time, RNA molecules in regulating the levels of H3K9 methylation by affecting KDM4D association with chromatin.

The role of RNA conformation in RNA-protein recognition.

Interactions between protein and RNA play a key role in many biological processes in the gene expression pathway. Those interactions are mediated through a variety of RNA-binding protein domains, among them the highly abundant RNA recognition motif (RRM). Here we studied protein-RNA complexes from different RNA binding domain families solved by NMR and x-ray crystallography. Characterizing the structural properties of the RNA at the binding interfaces revealed an unexpected number of nucleotides with unusual RNA conformations, specifically found in RNA-RRM complexes. Moreover, we observed that the RNA nucleotides that are directly involved in interactions with the RRM domains, via hydrogen bonds and hydrophobic contacts, are significantly enriched with unique RNA conformations. Further examination of the sequences binding the RRM domain showed a preference for G nucleotides in syn conformation to precede or to follow U nucleotides in the anti-conformation, and U nucleotides in C2' endo conformation to precede U and G nucleotides possessing the more common C3' endo conformation. These findings imply a possible mode of RNA recognition by the RRM domains which enables the recognition of a wide variety of different RNA sequences and shapes. Overall, this study suggests an additional way by which the RRM domain recognizes its RNA target, involving a conformational readout.

DRIMust: a web server for discovering rank imbalanced motifs using suffix trees.

Cellular regulation mechanisms that involve proteins and other active molecules interacting with specific targets often involve the recognition of sequence patterns. Short sequence elements on DNA, RNA and proteins play a central role in mediating such molecular recognition events. Studies that focus on measuring and investigating sequence-based recognition processes make use of statistical and computational tools that support the identification and understanding of sequence motifs. We present a new web application, named DRIMust, freely accessible through the website http://drimust.technion.ac.il for de novo motif discovery services. The DRIMust algorithm is based on the minimum hypergeometric statistical framework and uses suffix trees for an efficient enumeration of motif candidates. DRIMust takes as input ranked lists of sequences in FASTA format and returns motifs that are over-represented at the top of the list, where the determination of the threshold that defines top is data driven. The resulting motifs are presented individually with an accurate P-value indication and as a Position Specific Scoring Matrix. Comparing DRIMust with other state-of-the-art tools demonstrated significant advantage to DRIMust, both in result accuracy and in short running times. Overall, DRIMust is unique in combining efficient search on large ranked lists with rigorous P-value assessment for the detected motifs.

The hnRNP F/H homologue of Trypanosoma brucei is differentially expressed in the two life cycle stages of the parasite and regulates splicing and mRNA stability.

Trypanosomes are protozoan parasites that cycle between a mammalian host (bloodstream form) and an insect host, the Tsetse fly (procyclic stage). In trypanosomes, all mRNAs are trans-spliced as part of their maturation. Genome-wide analysis of trans-splicing indicates the existence of alternative trans-splicing, but little is known regarding RNA-binding proteins that participate in such regulation. In this study, we performed functional analysis of the Trypanosoma brucei heterogeneous nuclear ribonucleoproteins (hnRNP) F/H homologue, a protein known to regulate alternative splicing in metazoa. The hnRNP F/H is highly expressed in the bloodstream form of the parasite, but is also functional in the procyclic form. Transcriptome analyses of RNAi-silenced cells were used to deduce the RNA motif recognized by this protein. A purine rich motif, AAGAA, was enriched in both the regulatory regions flanking the 3' splice site and poly (A) sites of the regulated genes. The motif was further validated using mini-genes carrying wild-type and mutated sequences in the 3' and 5' UTRs, demonstrating the role of hnRNP F/H in mRNA stability and splicing. Biochemical studies confirmed the binding of the protein to this proposed site. The differential expression of the protein and its inverse effects on mRNA level in the two lifecycle stages demonstrate the role of hnRNP F/H in developmental regulation.

A novel Plasmodium falciparum SR protein is an alternative splicing factor required for the parasites' proliferation in human erythrocytes.

Malaria parasites have a complex life cycle, during which they undergo significant biological changes to adapt to different hosts and changing environments. Plasmodium falciparum, the species responsible for the deadliest form of human malaria, maintains this complex life cycle with a relatively small number of genes. Alternative splicing (AS) is an important post-transcriptional mechanisms that enables eukaryotic organisms to expand their protein repertoire out of relatively small number of genes. SR proteins are major regulators of AS in higher eukaryotes. Nevertheless, the regulation of splicing as well as the AS machinery in Plasmodium spp. are still elusive. Here, we show that PfSR1, a putative P. falciparum SR protein, can mediate RNA splicing in vitro. In addition, we show that PfSR1 functions as an AS factor in mini-gene in vivo systems similar to the mammalian SR protein SRSF1. Expression of PfSR1-myc in P. falciparum shows distinct patterns of cellular localization during intra erythrocytic development. Furthermore, we determine that the predicted RS domain of PfSR1 is essential for its localization to the nucleus. Finally, we demonstrate that proper regulation of pfsr1 is required for parasite proliferation in human RBCs and over-expression of pfsr1 influences AS activity of P. falciparum genes in vivo.

Proteasome gene expression is controlled by coordinated functions of multiple transcription factors.

Proteasome activity is crucial for cellular integrity, but how tissues adjust proteasome content in response to catabolic stimuli is uncertain. Here, we demonstrate that transcriptional coordination by multiple transcription factors is required to increase proteasome content and activate proteolysis in catabolic states. Using denervated mouse muscle as a model system for accelerated proteolysis in vivo, we reveal that a two-phase transcriptional program activates genes encoding proteasome subunits and assembly chaperones to boost an increase in proteasome content. Initially, gene induction is necessary to maintain basal proteasome levels, and in a more delayed phase (7-10 days after denervation), it stimulates proteasome assembly to meet cellular demand for excessive proteolysis. Intriguingly, the transcription factors PAX4 and α-PALNRF-1 control the expression of proteasome among other genes in a combinatorial manner, driving cellular adaptation to muscle denervation. Consequently, PAX4 and α-PALNRF-1 represent new therapeutic targets to inhibit proteolysis in catabolic diseases (e.g., type-2 diabetes, cancer).