Psi promotes Drosophila wing growth via direct transcriptional activation of cell cycle targets and repression of growth inhibitors.

The first characterised FUSE Binding Protein family member, FUBP1, binds single-stranded DNA to activate MYC transcription. Psi, the sole FUBP protein in Drosophila, binds RNA to regulate P-element and mRNA splicing. Our previous work revealed pro-growth functions for Psi, which depend, in part, on transcriptional activation of Myc. Genome-wide functions for FUBP family proteins in transcriptional control remain obscure. Here, through the first genome-wide binding and expression profiles obtained for a FUBP family protein, we demonstrate that, in addition to being required to activate Myc to promote cell growth, Psi also directly binds and activates stg to couple growth and cell division. Thus, Psi knockdown results in reduced cell division in the wing imaginal disc. In addition to activating these pro-proliferative targets, Psi directly represses transcription of the growth inhibitor tolkin (tok, a metallopeptidase implicated in TGFß signalling). We further demonstrate tok overexpression inhibits proliferation, while tok loss of function increases mitosis alone and suppresses impaired cell division caused by Psi knockdown. Thus, Psi orchestrates growth through concurrent transcriptional activation of the pro-proliferative genes Myc and stg, in combination with repression of the growth inhibitor tok.

Comprehensive translational profiling and STE AI uncover rapid control of protein biosynthesis during cell stress.

Translational control is important in all life, but it remains a challenge to accurately quantify. When ribosomes translate messenger (m)RNA into proteins, they attach to the mRNA in series, forming poly(ribo)somes, and can co-localize. Here, we computationally model new types of co-localized ribosomal complexes on mRNA and identify them using enhanced translation complex profile sequencing (eTCP-seq) based on rapid in vivo crosslinking. We detect long disome footprints outside regions of non-random elongation stalls and show these are linked to translation initiation and protein biosynthesis rates. We subject footprints of disomes and other translation complexes to artificial intelligence (AI) analysis and construct a new, accurate and self-normalized measure of translation, termed stochastic translation efficiency (STE). We then apply STE to investigate rapid changes to mRNA translation in yeast undergoing glucose depletion. Importantly, we show that, well beyond tagging elongation stalls, footprints of co-localized ribosomes provide rich insight into translational mechanisms, polysome dynamics and topology. STE AI ranks cellular mRNAs by absolute translation rates under given conditions, can assist in identifying its control elements and will facilitate the development of next-generation synthetic biology designs and mRNA-based therapeutics.

Concepts and methods for transcriptome-wide prediction of chemical messenger RNA modifications with machine learning.

The expanding field of epitranscriptomics might rival the epigenome in the diversity of biological processes impacted. In recent years, the development of new high-throughput experimental and computational techniques has been a key driving force in discovering the properties of RNA modifications. Machine learning applications, such as for classification, clustering or de novo identification, have been critical in these advances. Nonetheless, various challenges remain before the full potential of machine learning for epitranscriptomics can be leveraged. In this review, we provide a comprehensive survey of machine learning methods to detect RNA modifications using diverse input data sources. We describe strategies to train and test machine learning methods and to encode and interpret features that are relevant for epitranscriptomics. Finally, we identify some of the current challenges and open questions about RNA modification analysis, including the ambiguity in predicting RNA modifications in transcript isoforms or in single nucleotides, or the lack of complete ground truth sets to test RNA modifications. We believe this review will inspire and benefit the rapidly developing field of epitranscriptomics in addressing the current limitations through the effective use of machine learning.

Formation of an invasion-permissive matrix requires TGFß/SNAIL1-regulated alternative splicing of fibronectin.

BACKGROUND: As in most solid cancers, the emergence of cells with oncogenic mutations in the mammary epithelium alters the tissue homeostasis. Some soluble factors, such as TGFß, potently modify the behavior of healthy stromal cells. A subpopulation of cancer-associated fibroblasts expressing a TGFß target, the SNAIL1 transcription factor, display myofibroblastic abilities that rearrange the stromal architecture. Breast tumors with the presence of SNAIL1 in the stromal compartment, and with aligned extracellular fiber, are associated with poor survival prognoses. METHODS: We used deep RNA sequencing and biochemical techniques to study alternative splicing and human tumor databases to test for associations (correlation t-test) between SNAIL1 and fibronectin isoforms. Three-dimensional extracellular matrices generated from fibroblasts were used to study the mechanical properties and actions of the extracellular matrices on tumor cell and fibroblast behaviors. A metastatic mouse model of breast cancer was used to test the action of fibronectin isoforms on lung metastasis. RESULTS: In silico studies showed that SNAIL1 correlates with the expression of the extra domain A (EDA)-containing (EDA+) fibronectin in advanced human breast cancer and other types of epithelial cancers. In TGFß-activated fibroblasts, alternative splicing of fibronectin as well as of 500 other genes was modified by eliminating SNAIL1. Biochemical analyses demonstrated that SNAIL1 favors the inclusion of the EDA exon by modulating the activity of the SRSF1 splicing factor. Similar to Snai1 knockout fibroblasts, EDA- fibronectin fibroblasts produce an extracellular matrix  that does not sustain TGFß-induced fiber organization, rigidity, fibroblast activation, or tumor cell invasion. The presence of EDA+ fibronectin changes the action of metalloproteinases on fibronectin fibers. Critically, in an mouse orthotopic breast cancer model, the absence of the fibronectin EDA domain completely prevents lung metastasis. CONCLUSIONS: Our results support the requirement of EDA+ fibronectin in the generation of a metastasis permissive stromal architecture in breast cancers and its molecular control by SNAIL1. From a pharmacological point of view, specifically blocking EDA+ fibronectin deposition could be included in studies to reduce the formation of a pro-metastatic environment.

mRNA spindle localization and mitotic translational regulation by CPEB1 and CPEB4.

Transition through cell cycle phases requires temporal and spatial regulation of gene expression to ensure accurate chromosome duplication and segregation. This regulation involves dynamic reprogramming of gene expression at multiple transcriptional and posttranscriptional levels. In transcriptionally silent oocytes, the CPEB-family of RNAbinding proteins coordinates temporal and spatial translation regulation of stored maternal mRNAs to drive meiotic progression. CPEB1 mediates mRNA localization to the meiotic spindle, which is required to ensure proper chromosome segregation. Temporal translational regulation also takes place in mitosis, where a large repertoire of transcripts are activated or repressed in specific cell cycle phases. However, whether control of localized translation at the spindle is required for mitosis is unclear, as mitotic and acentriolar-meiotic spindles are functionally and structurally different. Furthermore, the large differences in scale-ratio between cell volume and spindle size in oocytes compared to somatic mitotic cells may generate distinct requirements for gene expression compartmentalization in meiosis and mitosis. Here we show that mitotic spindles contain CPE-localized mRNAs and translating ribosomes. Moreover, CPEB1 and CPEB4 localize in the spindles and they may function sequentially in promoting mitotic stage transitions and correct chromosome segregation. Thus, CPEB1 and CPEB4 bind to specific spindle-associated transcripts controlling the expression and/or localization of their encoded factors that, respectively, drive metaphase and anaphase/cytokinesis.

ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer.

Immunotherapies provide effective treatments for previously untreatable tumors and identifying tumor-specific epitopes can help elucidate the molecular determinants of therapy response. Here, we describe a pipeline, ISOTOPE (ISOform-guided prediction of epiTOPEs In Cancer), for the comprehensive identification of tumor-specific splicing-derived epitopes. Using RNA sequencing and mass spectrometry for MHC-I associated proteins, ISOTOPE identified neoepitopes from tumor-specific splicing events that are potentially presented by MHC-I complexes. Analysis of multiple samples indicates that splicing alterations may affect the production of self-epitopes and generate more candidate neoepitopes than somatic mutations. Although there was no difference in the number of splicing-derived neoepitopes between responders and non-responders to immune therapy, higher MHC-I binding affinity was associated with a positive response. Our analyses highlight the diversity of the immunogenic impacts of tumor-specific splicing alterations and the importance of studying splicing alterations to fully characterize tumors in the context of immunotherapies. ISOTOPE is available at https://github.com/comprna/ISOTOPE.

A global regulatory mechanism for activating an exon network required for neurogenesis.

The vertebrate and neural-specific Ser/Arg (SR)-related protein nSR100/SRRM4 regulates an extensive program of alternative splicing with critical roles in nervous system development. However, the mechanism by which nSR100 controls its target exons is poorly understood. We demonstrate that nSR100-dependent neural exons are associated with a unique configuration of intronic cis-elements that promote rapid switch-like regulation during neurogenesis. A key feature of this configuration is the insertion of specialized intronic enhancers between polypyrimidine tracts and acceptor sites that bind nSR100 to potently activate exon inclusion in neural cells while weakening 3' splice site recognition and contributing to exon skipping in nonneural cells. nSR100 further operates by forming multiple interactions with early spliceosome components bound proximal to 3' splice sites. These multifaceted interactions achieve dominance over neural exon silencing mediated by the splicing regulator PTBP1. The results thus illuminate a widespread mechanism by which a critical neural exon network is activated during neurogenesis.

Altered regulation of BRCA1 exon 11 splicing is associated with breast cancer risk in carriers of BRCA1 pathogenic variants.

Germline pathogenic variants in BRCA1 confer a high risk of developing breast and ovarian cancer. The BRCA1 exon 11 (formally exon 10) is one of the largest exons and codes for the nuclear localization signals of the corresponding gene product. This exon can be partially or entirely skipped during pre-mRNA splicing, leading to three major in-frame isoforms that are detectable in most cell types and tissue, and in normal and cancer settings. However, it is unclear whether the splicing imbalance of this exon is associated with cancer risk. Here we identify a common genetic variant in intron 10, rs5820483 (NC_000017.11:g.43095106_43095108dup), which is associated with exon 11 isoform expression and alternative splicing, and with the risk of breast cancer, but not ovarian cancer, in BRCA1 pathogenic variant carriers. The identification of this genetic effect was confirmed by analogous observations in mouse cells and tissue in which a loxP sequence was inserted in the syntenic intronic region. The prediction that the rs5820483 minor allele variant would create a binding site for the splicing silencer hnRNP A1 was confirmed by pull-down assays. Our data suggest that perturbation of BRCA1 exon 11 splicing modifies the breast cancer risk conferred by pathogenic variants of this gene.

RBM5, 6, and 10 differentially regulate NUMB alternative splicing to control cancer cell proliferation.

RBM5, a regulator of alternative splicing of apoptotic genes, and its highly homologous RBM6 and RBM10 are RNA-binding proteins frequently deleted or mutated in lung cancer. We report that RBM5/6 and RBM10 antagonistically regulate the proliferative capacity of cancer cells and display distinct positional effects in alternative splicing regulation. We identify the Notch pathway regulator NUMB as a key target of these factors in the control of cell proliferation. NUMB alternative splicing, which is frequently altered in lung cancer, can regulate colony and xenograft tumor formation, and its modulation recapitulates or antagonizes the effects of RBM5, 6, and 10 in cell colony formation. RBM10 mutations identified in lung cancer cells disrupt NUMB splicing regulation to promote cell growth. Our results reveal a key genetic circuit in the control of cancer cell proliferation.

Nucleosome-driven transcription factor binding and gene regulation.

Elucidating the global function of a transcription factor implies the identification of its target genes and genomic binding sites. The role of chromatin in this context is unclear, but the dominant view is that factors bind preferentially to nucleosome-depleted regions identified as DNaseI-hypersensitive sites (DHS). Here we show by ChIP, MNase, and DNaseI assays followed by deep sequencing that the progesterone receptor (PR) requires nucleosomes for optimal binding and function. In breast cancer cells treated with progestins, we identified 25,000 PR binding sites (PRbs). The majority of these sites encompassed several copies of the hexanucleotide TGTYCY, which is highly abundant in the genome. We found that functional PRbs accumulate around progesterone-induced genes, mainly in enhancers. Most of these sites overlap with DHS but exhibit high nucleosome occupancy. Progestin stimulation results in remodeling of these nucleosomes with displacement of histones H1 and H2A/H2B dimers. Our results strongly suggest that nucleosomes are crucial for PR binding and hormonal gene regulation.

The discovery potential of RNA processing profiles.

Small non-coding RNAs (sncRNAs) are highly abundant molecules that regulate essential cellular processes and are classified according to sequence and structure. Here we argue that read profiles from size-selected RNA sequencing capture the post-transcriptional processing specific to each RNA family, thereby providing functional information independently of sequence and structure. We developed SeRPeNT, a new computational method that exploits reproducibility across replicates and uses dynamic time-warping and density-based clustering algorithms to identify, characterize and compare sncRNAs by harnessing the power of read profiles. We applied SeRPeNT to: (i) generate an extended human annotation with 671 new sncRNAs from known classes and 131 from new potential classes, (ii) show pervasive differential processing of sncRNAs between cell compartments and (iii) predict new molecules with miRNA-like behaviour from snoRNA, tRNA and long non-coding RNA precursors, potentially dependent on the miRNA biogenesis pathway. Furthermore, we validated experimentally four predicted novel non-coding RNAs: a miRNA, a snoRNA-derived miRNA, a processed tRNA and a new uncharacterized sncRNA. SeRPeNT facilitates fast and accurate discovery and characterization of sncRNAs at an unprecedented scale. SeRPeNT code is available under the MIT license at https://github.com/comprna/SeRPeNT.

Nuclear matrix protein Matrin3 regulates alternative splicing and forms overlapping regulatory networks with PTB.

Matrin3 is an RNA- and DNA-binding nuclear matrix protein found to be associated with neural and muscular degenerative diseases. A number of possible functions of Matrin3 have been suggested, but no widespread role in RNA metabolism has yet been clearly demonstrated. We identified Matrin3 by its interaction with the second RRM domain of the splicing regulator PTB. Using a combination of RNAi knockdown, transcriptome profiling and iCLIP, we find that Matrin3 is a regulator of hundreds of alternative splicing events, principally acting as a splicing repressor with only a small proportion of targeted events being co-regulated by PTB. In contrast to other splicing regulators, Matrin3 binds to an extended region within repressed exons and flanking introns with no sharply defined peaks. The identification of this clear molecular function of Matrin3 should help to clarify the molecular pathology of ALS and other diseases caused by mutations of Matrin3.

Large-scale analysis of genome and transcriptome alterations in multiple tumors unveils novel cancer-relevant splicing networks.

Alternative splicing is regulated by multiple RNA-binding proteins and influences the expression of most eukaryotic genes. However, the role of this process in human disease, and particularly in cancer, is only starting to be unveiled. We systematically analyzed mutation, copy number, and gene expression patterns of 1348 RNA-binding protein (RBP) genes in 11 solid tumor types, together with alternative splicing changes in these tumors and the enrichment of binding motifs in the alternatively spliced sequences. Our comprehensive study reveals widespread alterations in the expression of RBP genes, as well as novel mutations and copy number variations in association with multiple alternative splicing changes in cancer drivers and oncogenic pathways. Remarkably, the altered splicing patterns in several tumor types recapitulate those of undifferentiated cells. These patterns are predicted to be mainly controlled by MBNL1 and involve multiple cancer drivers, including the mitotic gene NUMA1 We show that NUMA1 alternative splicing induces enhanced cell proliferation and centrosome amplification in nontumorigenic mammary epithelial cells. Our study uncovers novel splicing networks that potentially contribute to cancer development and progression.

SARNAclust: Semi-automatic detection of RNA protein binding motifs from immunoprecipitation data.

RNA-protein binding is critical to gene regulation, controlling fundamental processes including splicing, translation, localization and stability, and aberrant RNA-protein interactions are known to play a role in a wide variety of diseases. However, molecular understanding of RNA-protein interactions remains limited; in particular, identification of RNA motifs that bind proteins has long been challenging, especially when such motifs depend on both sequence and structure. Moreover, although RNA binding proteins (RBPs) often contain more than one binding domain, algorithms capable of identifying more than one binding motif simultaneously have not been developed. In this paper we present a novel pipeline to determine binding peaks in crosslinking immunoprecipitation (CLIP) data, to discover multiple possible RNA sequence/structure motifs among them, and to experimentally validate such motifs. At the core is a new semi-automatic algorithm SARNAclust, the first unsupervised method to identify and deconvolve multiple sequence/structure motifs simultaneously. SARNAclust computes similarity between sequence/structure objects using a graph kernel, providing the ability to isolate the impact of specific features through the bulge graph formalism. Application of SARNAclust to synthetic data shows its capability of clustering 5 motifs at once with a V-measure value of over 0.95, while GraphClust achieves only a V-measure of 0.083 and RNAcontext cannot detect any of the motifs. When applied to existing eCLIP sets, SARNAclust finds known motifs for SLBP and HNRNPC and novel motifs for several other RBPs such as AGGF1, AKAP8L and ILF3. We demonstrate an experimental validation protocol, a targeted Bind-n-Seq-like high-throughput sequencing approach that relies on RNA inverse folding for oligo pool design, that can validate the components within the SLBP motif. Finally, we use this protocol to experimentally interrogate the SARNAclust motif predictions for protein ILF3. Our results support a newly identified partially double-stranded UUUUUGAGA motif similar to that known for the splicing factor HNRNPC.

Deciphering 3'ss selection in the yeast genome reveals an RNA thermosensor that mediates alternative splicing.

Poor understanding of the spliceosomal mechanisms to select intronic 3' ends (3'ss) is a major obstacle to deciphering eukaryotic genomes. Here, we discern the rules for global 3'ss selection in yeast. We show that, in contrast to the uniformity of yeast splicing, the spliceosome uses all available 3'ss within a distance window from the intronic branch site (BS), and that in ∼70% of all possible 3'ss this is likely to be mediated by pre-mRNA structures. Our results reveal that one of these RNA folds acts as an RNA thermosensor, modulating alternative splicing in response to heat shock by controlling alternate 3'ss availability. Thus, our data point to a deeper role for the pre-mRNA in the control of its own fate, and to a simple mechanism for some alternative splicing.

Dual function of C/D box small nucleolar RNAs in rRNA modification and alternative pre-mRNA splicing.

C/D box small nucleolar RNAs (SNORDs) are small noncoding RNAs, and their best-understood function is to target the methyltransferase fibrillarin to rRNA (for example, SNORD27 performs 2'-O-methylation of A27 in 18S rRNA). Unexpectedly, we found a subset of SNORDs, including SNORD27, in soluble nuclear extract made under native conditions, where fibrillarin was not detected, indicating that a fraction of the SNORD27 RNA likely forms a protein complex different from canonical snoRNAs found in the insoluble nuclear fraction. As part of this previously unidentified complex,SNORD27 regulates the alternative splicing of the transcription factor E2F7p re-mRNA through direct RNA-RNA interaction without methylating the RNA, likely by competing with U1 small nuclear ribonucleoprotein (snRNP). Furthermore, knockdown of SNORD27 activates previously "silent" exons in several other genes through base complementarity across the entire SNORD27 sequence, not just the antisense boxes. Thus, some SNORDs likely function in both rRNA and pre-mRNA processing, which increases the repertoire of splicing regulators and links both processes.

The RNA-binding profile of Acinus, a peripheral component of the exon junction complex, reveals its role in splicing regulation.

Acinus (apoptotic chromatin condensation inducer in the nucleus) is an RNA-binding protein (RBP) originally identified for its role in apoptosis. It was later found to be an auxiliary component of the exon junction complex (EJC), which is deposited at exon junctions as a consequence of pre-mRNA splicing. To uncover the cellular functions of Acinus and investigate its role in splicing, we mapped its endogenous RNA targets using the cross-linking immunoprecipitation protocol (iCLIP). We observed that Acinus binds to pre-mRNAs, associating specifically to a subset of suboptimal introns, but also to spliced mRNAs. We also confirmed the presence of Acinus as a peripheral factor of the EJC. RNA-seq was used to investigate changes in gene expression and alternative splicing following siRNA-mediated depletion of Acinus in HeLa cells. This analysis revealed that Acinus is preferentially required for the inclusion of specific alternative cassette exons and also controls the faithful splicing of a subset of introns. Moreover, a large number of splicing changes can be related to Acinus binding, suggesting a direct role of Acinus in exon and intron definition. In particular, Acinus regulates the splicing of DFFA/ICAD transcript, a major regulator of DNA fragmentation. Globally, the genome-wide identification of RNA targets of Acinus revealed its role in splicing regulation as well as its involvement in other cellular pathways, including cell cycle progression. Altogether, this study uncovers new cellular functions of an RBP transiently associated with the EJC.

The alternative splicing program of differentiated smooth muscle cells involves concerted non-productive splicing of post-transcriptional regulators.

Alternative splicing (AS) is a key component of gene expression programs that drive cellular differentiation. Smooth muscle cells (SMCs) are important in the function of a number of physiological systems; however, investigation of SMC AS has been restricted to a handful of events. We profiled transcriptome changes in mouse de-differentiating SMCs and observed changes in hundreds of AS events. Exons included in differentiated cells were characterized by particularly weak splice sites and by upstream binding sites for Polypyrimidine Tract Binding protein (PTBP1). Consistent with this, knockdown experiments showed that that PTBP1 represses many smooth muscle specific exons. We also observed coordinated splicing changes predicted to downregulate the expression of core components of U1 and U2 snRNPs, splicing regulators and other post-transcriptional factors in differentiated cells. The levels of cognate proteins were lower or similar in differentiated compared to undifferentiated cells. However, levels of snRNAs did not follow the expression of splicing proteins, and in the case of U1 snRNP we saw reciprocal changes in the levels of U1 snRNA and U1 snRNP proteins. Our results suggest that the AS program in differentiated SMCs is orchestrated by the combined influence of auxiliary RNA binding proteins, such as PTBP1, along with altered activity and stoichiometry of the core splicing machinery.

Leveraging transcript quantification for fast computation of alternative splicing profiles.

Alternative splicing plays an essential role in many cellular processes and bears major relevance in the understanding of multiple diseases, including cancer. High-throughput RNA sequencing allows genome-wide analyses of splicing across multiple conditions. However, the increasing number of available data sets represents a major challenge in terms of computation time and storage requirements. We describe SUPPA, a computational tool to calculate relative inclusion values of alternative splicing events, exploiting fast transcript quantification. SUPPA accuracy is comparable and sometimes superior to standard methods using simulated as well as real RNA-sequencing data compared with experimentally validated events. We assess the variability in terms of the choice of annotation and provide evidence that using complete transcripts rather than more transcripts per gene provides better estimates. Moreover, SUPPA coupled with de novo transcript reconstruction methods does not achieve accuracies as high as using quantification of known transcripts, but remains comparable to existing methods. Finally, we show that SUPPA is more than 1000 times faster than standard methods. Coupled with fast transcript quantification, SUPPA provides inclusion values at a much higher speed than existing methods without compromising accuracy, thereby facilitating the systematic splicing analysis of large data sets with limited computational resources. The software is implemented in Python 2.7 and is available under the MIT license at https://bitbucket.org/regulatorygenomicsupf/suppa.