Tissue-specific alternative splicing remodels protein-protein interaction networks

Revealing the Determinants of Widespread Alternative Splicing Perturbation in Cancer

It is increasingly appreciated that alternative splicing plays a key role in generating functional specificity and diversity in cancer. However, the mechanisms by which cancer mutations perturb splicing remain unknown. Here, we developed a network-based strategy, DrAS-Net, to investigate more than 2.5 million variants across cancer types and link somatic mutations with cancer-specific splicing events. We identified more than 40,000 driver variant candidates and their 80,000 putative splicing targets deregulated in 33 cancer types and inferred their functional impact. Strikingly, tumors with splicing perturbations show reduced expression of immune system-related genes and increased expression of cell proliferation markers. Tumors harboring different mutations in the same gene often exhibit distinct splicing perturbations. Further stratification of 10,000 patients based on their mutation-splicing relationships identifies subtypes with distinct clinical features, including survival rates. Our work reveals how single-nucleotide changes can alter the repertoires of splicing isoforms, providing insights into oncogenic mechanisms for precision medicine.

ChiPPI: a novel method for mapping chimeric protein-protein interactions uncovers selection principles of protein fusion events in cancer

Fusion proteins, comprising peptides deriving from the translation of two parental genes, are produced in cancer by chromosomal aberrations. The expressed fusion protein incorporates domains of both parental proteins. Using a methodology that treats discrete protein domains as binding sites for specific domains of interacting proteins, we have cataloged the protein interaction networks for 11 528 cancer fusions (ChiTaRS-3.1). Here, we present our novel method, chimeric protein–protein interactions (ChiPPI) that uses the domain–domain co-occurrence scores in order to identify preserved interactors of chimeric proteins. Mapping the influence of fusion proteins on cell metabolism and pathways reveals that ChiPPI networks often lose tumor suppressor proteins and gain oncoproteins. Furthermore, fusions often induce novel connections between non-interactors skewing interaction networks and signaling pathways. We compared fusion protein PPI networks in leukemia/lymphoma, sarcoma and solid tumors finding distinct enrichment patterns for each disease type. While certain pathways are enriched in all three diseases (Wnt, Notch and TGF β), there are distinct patterns for leukemia (EGFR signaling, DNA replication and CCKR signaling), for sarcoma (p53 pathway and CCKR signaling) and solid tumors (FGFR and EGFR signaling). Thus, the ChiPPI method represents a comprehensive tool for studying the anomaly of skewed cellular networks produced by fusion proteins in cancer.

Dynamical differential networks and modules inferring disrupted genes associated with the progression of Alzheimer's disease

In order to understand the pathogenic factors that initiate the processes of Alzheimer's disease (AD), a method of inference of multiple differential modules (iMDM) to conduct analysis was performed on the gene expression profile of AD. A total of 11,089 genes and 588,391 interactions were gained based on the gene expression profile and protein-protein interaction network. Subsequently, three differential co-expression networks (DCNs) were constructed with the same nodes but different interactions, and eight multiple differential modules (M-DMs) were identified. Furthermore, by performing Module Connectivity Dynamic Score to quantify the change in the connectivity of component modules, two M-DMs were identified: Module 1 (P=0.0419) and 2 (P=0.0419; adjusted, P≤0.05). Finally, hub genes of MDH1, NDUFAB1, NDUFB5, DDX1 and MRPS35 were gained via topological analysis conducted on the 2 M-DMs. In conclusion, the method of iMDM was suitable for conducting analysis on AD. By applying iMDM, 2 M-DMs were successfully identified and the MDH1, NDUFAB1, NDUFB5, DDX1 and MRPS35 genes were predicted to be important during the occurrence and development of AD.

Alternative Splicing in Genetic Diseases: Improved Diagnosis and Novel Treatment Options

Alternative splicing is an important mechanism to regulate gene expression and to expand the repertoire of gene products in order to accommodate an increase in complexity of multicellular organisms. It needs to be precisely regulated, which is achieved via RNA structure, splicing factors, transcriptional regulation, and chromatin. Changes in any of these factors can lead to disease. These may include the core spliceosome, splicing enhancer/repressor sequences and their interacting proteins, the speed of transcription by RNA polymerase II, and histone modifications. While the basic principle of splicing is well understood, it is still very difficult to predict splicing outcome, due to the multiple levels of regulation. Current molecular diagnostics mainly uses Sanger sequencing of exons, or next-generation sequencing of gene panels or the whole exome. Functional analysis of potential splicing variants is scarce, and intronic variants are often not considered. This likely results in underestimation of the percentage of splicing variants. Understanding how sequence variants may affect splicing is not only crucial for confirmation of diagnosis and for genetic counseling, but also for the development of novel treatment options. These include small molecules, transsplicing, antisense oligonucleotides, and gene therapy. Here we review the current state of molecular mechanisms of splicing regulation and how deregulation can lead to human disease, diagnostics to detect splicing variants, and novel treatment options based on splicing correction.

The developmental transcriptome landscape of receptive endometrium during embryo implantation in dairy goats

Under natural conditions, some embryos cannot implant successfully because of the dysfunction of receptive endometrium (RE). Thus, it is imperative for us to study the molecular mechanisms involved in the formation of the RE from pre-receptive endometrium (PE). In this study, the endometrium from gestational day 5 (D5, PE) and gestational day 15 (D15, RE) dairy goats were selected to systematically analyze the transcriptome using strand-specific Ribo-Zero RNA-Seq, >120 million high-quality paired-end reads were generated and 47,616 transcripts were identified in the endometrium of dairy goats. A total of 810 mRNAs were differentially expressed genes (DEGs) between the RE and PE meeting the criteria of P-values<0.05. Bioinformatics analysis of the DEGs revealed that a number of biological processes and pathways were potentially involved in the establishment of the RE, notably energy metabolism and amino acid metabolism. Furthermore, we speculated that CXCL14, IGFBP3, and LGALS15 potentially participated in the development of endometrium. What's more, putative SNPs, InDels and AS events were identified and analyzed in the endometrium. In a word, this resulting view of the transcriptome greatly enhances the comprehensive transcript catalog and uncovers the global trends in gene expression during the formation of receptive endometrium in dairy goats.

An atlas of alternative splicing profiles and functional associations reveals new regulatory programs and genes that simultaneously express multiple major isoforms

Alternative splicing (AS) generates remarkable regulatory and proteomic complexity in metazoans. However, the functions of most AS events are not known, and programs of regulated splicing remain to be identified. To address these challenges, we describe the Vertebrate Alternative Splicing and Transcription Database (VastDB), the largest resource of genome-wide, quantitative profiles of AS events assembled to date. VastDB provides readily accessible quantitative information on the inclusion levels and functional associations of AS events detected in RNA-seq data from diverse vertebrate cell and tissue types, as well as developmental stages. The VastDB profiles reveal extensive new intergenic and intragenic regulatory relationships among different classes of AS and previously unknown and conserved landscapes of tissue-regulated exons. Contrary to recent reports concluding that nearly all human genes express a single major isoform, VastDB provides evidence that at least 48% of multiexonic protein-coding genes express multiple splice variants that are highly regulated in a cell/tissue-specific manner, and that >18% of genes simultaneously express multiple major isoforms across diverse cell and tissue types. Isoforms encoded by the latter set of genes are generally coexpressed in the same cells and are often engaged by translating ribosomes. Moreover, they are encoded by genes that are significantly enriched in functions associated with transcriptional control, implying they may have an important and wide-ranging role in controlling cellular activities. VastDB thus provides an unprecedented resource for investigations of AS function and regulation.

Regulation of the interaction between the neuronal BIN1 isoform 1 and Tau proteins - role of the SH3 domain

Bridging integrator 1 (bin1) gene is a genetic determinant of Alzheimer's disease (AD) and has been reported to modulate Alzheimer's pathogenesis through pathway(s) involving Tau. The functional impact of Tau/BIN1 interaction as well as the molecular details of this interaction are still not fully resolved. As a consequence, how BIN1 through its interaction with Tau affects AD risk is also still not determined. To progress in this understanding, interaction of Tau with two BIN1 isoforms was investigated using Nuclear Magnetic Resonance spectroscopy. ¹ H, ¹⁵ N spectra showed that the C-terminal SH3 domain of BIN1 isoform 1 (BIN1Iso1) is not mobile in solution but locked with the core of the protein. In contrast, the SH3 domain of BIN1 isoform 9 (BIN1Iso9) behaves as an independent mobile domain. This reveals an equilibrium between close and open conformations for the SH3 domain. Interestingly, a 334-376 peptide from the clathrin and AP-2-binding domain (CLAP) domain of BIN1Iso1, which contains a SH3-binding site, is able to compete with BIN1-SH3 intramolecular interaction. For both BIN1 isoforms, the SH3 domain can interact with Tau(210-240) sequence. Tau(210-240) peptide can indeed displace the intramolecular interaction of the BIN1-SH3 of BIN1Iso1 and form a complex with the released domain. The measured K_d were in agreement with a stronger affinity of Tau peptide. Both CLAP and Tau peptides occupied the same surface on the BIN1-SH3 domain, showing that their interaction is mutually exclusive. These results emphasize an additional level of complexity in the regulation of the interaction between BIN1 and Tau dependent of the BIN1 isoforms.

Domain-based prediction of the human isoform interactome provides insights into the functional impact of alternative splicing

Alternative splicing is known to remodel protein-protein interaction networks (“interactomes”), yet large-scale determination of isoform-specific interactions remains challenging. We present a domain-based method to predict the isoform interactome from the reference interactome. First, we construct the domain-resolved reference interactome by mapping known domain-domain interactions onto experimentally-determined interactions between reference proteins. Then, we construct the isoform interactome by predicting that an isoform loses an interaction if it loses the domain mediating the interaction. Our prediction framework is of high-quality when assessed by experimental data. The predicted human isoform interactome reveals extensive network remodeling by alternative splicing. Protein pairs interacting with different isoforms of the same gene tend to be more divergent in biological function, tissue expression, and disease phenotype than protein pairs interacting with the same isoforms. Our prediction method complements experimental efforts, and demonstrates that integrating structural domain information with interactomes provides insights into the functional impact of alternative splicing.

Protein-protein interaction networks have been extensively used in systems biology to study the role of proteins in cell function and disease. However, current network biology studies typically assume that one gene encodes one protein isoform, ignoring the effect of alternative splicing. Alternative splicing allows a gene to produce multiple protein isoforms, by alternatively selecting distinct regions in the gene to be translated to protein products. Here, we present a computational method to predict and analyze the large-scale effect of alternative splicing on protein-protein interaction networks. Starting with a reference protein-protein interaction network determined by experiments, our method annotates protein-protein interactions with domain-domain interactions, and predicts that a protein isoform loses an interaction if it loses the domain mediating the interaction as a result of alternative splicing. Our predictions reveal the central role of alternative splicing in extensively remodeling the human protein-protein interaction network, and in increasing the functional complexity of the human cell. Our prediction method complements ongoing experimental efforts by predicting isoform-specific interactions for genes not tested yet by experiments and providing insights into the functional impact of alternative splicing.

Extensive alternative splicing transitions during postnatal skeletal muscle development are required for calcium handling functions

Postnatal development of skeletal muscle is a highly dynamic period of tissue remodeling. Here, we used RNA-seq to identify transcriptome changes from late embryonic to adult mouse muscle and demonstrate that alternative splicing developmental transitions impact muscle physiology. The first 2 weeks after birth are particularly dynamic for differential gene expression and alternative splicing transitions, and calcium-handling functions are significantly enriched among genes that undergo alternative splicing. We focused on the postnatal splicing transitions of the three calcineurin A genes, calcium-dependent phosphatases that regulate multiple aspects of muscle biology. Redirected splicing of calcineurin A to the fetal isoforms in adult muscle and in differentiated C2C12 slows the timing of muscle relaxation, promotes nuclear localization of calcineurin target Nfatc3, and/or affects expression of Nfatc transcription targets. The results demonstrate a previously unknown specificity of calcineurin isoforms as well as the broader impact of alternative splicing during muscle postnatal development.

Proteogenomic analysis reveals alternative splicing and translation as part of the abscisic acid response in Arabidopsis seedlings

In eukaryotes, mechanisms such as alternative splicing (AS) and alternative translation initiation (ATI) contribute to organismal protein diversity. Specifically, splicing factors play crucial roles in responses to environment and development cues; however, the underlying mechanisms are not well investigated in plants. Here, we report the parallel employment of short-read RNA sequencing, single molecule long-read sequencing and proteomic identification to unravel AS isoforms and previously unannotated proteins in response to abscisic acid (ABA) treatment. Combining the data from the two sequencing methods, approximately 83.4% of intron-containing genes were alternatively spliced. Two AS types, which are referred to as alternative first exon (AFE) and alternative last exon (ALE), were more abundant than intron retention (IR); however, by contrast to AS events detected under normal conditions, differentially expressed AS isoforms were more likely to be translated. ABA extensively affects the AS pattern, indicated by the increasing number of non-conventional splicing sites. This work also identified thousands of unannotated peptides and proteins by ATI based on mass spectrometry and a virtual peptide library deduced from both strands of coding regions within the Arabidopsis genome. The results enhance our understanding of AS and alternative translation mechanisms under normal conditions, and in response to ABA treatment.

A convex optimization approach for identification of human tissue-specific interactomes

Motivation: Analysis of organism-specific interactomes has yielded novel insights into cellular function and coordination, understanding of pathology, and identification of markers and drug targets. Genes, however, can exhibit varying levels of cell type specificity in their expression, and their coordinated expression manifests in tissue-specific function and pathology. Tissue-specific/tissue-selective interaction mechanisms have significant applications in drug discovery, as they are more likely to reveal drug targets. Furthermore, tissue-specific transcription factors (tsTFs) are significantly implicated in human disease, including cancers. Finally, disease genes and protein complexes have the tendency to be differentially expressed in tissues in which defects cause pathology. These observations motivate the construction of refined tissue-specific interactomes from organism-specific interactomes.

Results: We present a novel technique for constructing human tissue-specific interactomes. Using a variety of validation tests (Edge Set Enrichment Analysis, Gene Ontology Enrichment, Disease-Gene Subnetwork Compactness), we show that our proposed approach significantly outperforms state-of-the-art techniques. Finally, using case studies of Alzheimer’s and Parkinson’s diseases, we show that tissue-specific interactomes derived from our study can be used to construct pathways implicated in pathology and demonstrate the use of these pathways in identifying novel targets.

Availability and implementation:http://www.cs.purdue.edu/homes/mohammas/projects/ActPro.html

Contact:mohammadi@purdue.edu

Use of Microarray Datasets to generate Caco-2-dedicated Networks and to identify Reporter Genes of Specific Pathway Activity

Intestinal epithelial cells, like Caco-2, are commonly used to study the interaction between food, other luminal factors and the host, often supported by microarray analysis to study the changes in gene expression as a result of the exposure. However, no compiled dataset for Caco-2 has ever been initiated and Caco-2-dedicated gene expression networks are barely available. Here, 341 Caco-2-specific microarray samples were collected from public databases and from in-house experiments pertaining to Caco-2 cells exposed to pathogens, probiotics and several food compounds. Using these datasets, a gene functional association network specific for Caco-2 was generated containing 8937 nodes 129711 edges. Two in silico methods, a modified version of biclustering and the new Differential Expression Correlation Analysis, were developed to identify Caco-2-specific gene targets within a pathway of interest. These methods were subsequently applied to the AhR and Nrf2 signalling pathways and altered expression of the predicted target genes was validated by qPCR in Caco-2 cells exposed to coffee extracts, known to activate both AhR and Nrf2 pathways. The datasets and in silico method(s) to identify and predict responsive target genes can be used to more efficiently design experiments to study Caco-2/intestinal epithelial-relevant biological processes.

The contribution of intrinsically disordered regions to protein function, cellular complexity, and human disease

In the 1960s, Christian Anfinsen postulated that the unique three-dimensional structure of a protein is determined by its amino acid sequence. This work laid the foundation for the sequence–structure–function paradigm, which states that the sequence of a protein determines its structure, and structure determines function. However, a class of polypeptide segments called intrinsically disordered regions does not conform to this postulate. In this review, I will first describe established and emerging ideas about how disordered regions contribute to protein function. I will then discuss molecular principles by which regulatory mechanisms, such as alternative splicing and asymmetric localization of transcripts that encode disordered regions, can increase the functional versatility of proteins. Finally, I will discuss how disordered regions contribute to human disease and the emergence of cellular complexity during organismal evolution.

Rare Splice Variants in Long Non-Coding RNAs

Long non-coding RNAs (lncRNAs) form a substantial component of the transcriptome and are involved in a wide variety of regulatory mechanisms. Compared to protein-coding genes, they are often expressed at low levels and are restricted to a narrow range of cell types or developmental stages. As a consequence, the diversity of their isoforms is still far from being recorded and catalogued in its entirety, and the debate is ongoing about what fraction of non-coding RNAs truly conveys biological function rather than being "junk". Here, using a collection of more than 100 transcriptomes from related B cell lymphoma, we show that lncRNA loci produce a very defined set of splice variants. While some of them are so rare that they become recognizable only in the superposition of dozens or hundreds of transcriptome datasets and not infrequently include introns or exons that have not been included in available genome annotation data, there is still a very limited number of processing products for any given locus. The combined depth of our sequencing data is large enough to effectively exhaust the isoform diversity: the overwhelming majority of splice junctions that are observed at all are represented by multiple junction-spanning reads. We conclude that the human transcriptome produces virtually no background of RNAs that are processed at effectively random positions, but is-under normal circumstances-confined to a well defined set of splice variants.

Modeling osteosarcoma progression by measuring the connectivity dynamics using an inference of multiple differential modules algorithm

Understanding the dynamic changes in connectivity of molecular pathways is important for determining disease prognosis. Thus, the current study used an inference of multiple differential modules (iMDM) algorithm to identify the connectivity changes of sub-network to predict the progression of osteosarcoma (OS) based on the microarray data of OS at four Huvos grades. Initially, multiple differential co-expression networks (M-DCNs) were constructed, and weight values were assigned for each edge, followed by detection of seed genes in M-DCNs according to the topological properties. Using these seed gene as a start, an iMDM algorithm was utilized to identify the multiple candidate modules. The statistical significance was determined to select multiple differential modules (M-DMs) based on the null score distribution of candidate modules generated using randomized networks. Additionally, the significance of Module Connectivity Dynamic Score (MCDS) to quantify the dynamic change of M-DMs connectivity. Further, DAVID was employed for KEGG pathway enrichment analysis of genes in dynamic modules. In addition to the basal condition, four conditions, OS grade 1–4, were also included (M=4). In total, 4 DCNs were constructed, and each of them included 2,138 edges and 272 nodes. A total of 13 genes were identified and termed ‘seed genes’ based on the z-score distribution of 272 nodes in DCNs. Following the module search, module refinement and statistical significance analysis, a total of four 4-DMs (modules 1, 2, 3 and 4) were identified. Only one significant 4-DM (module 3 in the DCNs of grade 1, 2, 3 and 4 OS) with dynamic changes was detected when the MCDS of real 4-DMs were compared to a null distribution of MCDS of random 4-DMs. Notably, the genes of the dynamic module (module 3) were enriched in two significant pathway terms, ubiquitin-mediated proteolysis and ribosome. The seed genes with the highest degrees included protein phosphatase 1 regulatory subunit 12A (PPP1R12A), UTP3, small subunit processome component homolog (UTP3), prostaglandin E synthase 3 (PTGES3). Thus, pathway functions (ubiquitin-mediated proteolysis and ribosome) and several seed genes (PPP1R12A, UTP3, and PTGES3) in the dynamic module 3 may be associated with the progression of OS and may serve as potential therapeutic targets in OS.

Neuronal activity-regulated alternative mRNA splicing

Activity-regulated gene transcription underlies plasticity-dependent changes in the molecular composition and structure of neurons. Numerous genes whose expression is induced by different neuronal plasticity inducing pathways have been identified, but the alteration of gene expression levels represents only part of the complexity of the activity-regulated transcriptional program. Alternative splicing of precursor mRNA is an additional mechanism that modulates the activity-dependent transcriptional signature. Recently developed splicing sensitive transcriptome wide analyses improve our understanding of the underlying mechanisms and demonstrate to what extend the activity regulated transcriptome is alternatively spliced. So far, only for a small group of differentially spliced mRNAs of synaptic proteins, the functional implications have been studied in detail. These include examples in which differential exon usage can result in the expression of alternative proteins which interfere with or alter the function of preexisting proteins and cause a dominant negative functional block of constitutively expressed variants. Such altered proteins contribute to the structural and functional reorganization of pre- and postsynaptic terminals and to the maintenance and formation of synapses. In addition, activity-induced alternative splicing can affect the untranslated regions (UTRs) and generates mRNAs harboring different cis-regulatory elements. Such differential UTRs can influence mRNA stability, translation, and can change the targeting of mRNAs to subcellular compartments. Here, we summarize different categories of alternative splicing which are thought to contribute to synaptic remodeling, give an overview of activity-regulated alternatively spliced mRNAs of synaptic proteins that impact synaptic functions, and discuss splicing factors and epigenetic modifications as regulatory determinants.

Alternative splicing shapes transcriptome but not proteome diversity in Physcomitrella patens

Alternative splicing (AS) can significantly impact the transcriptome and proteome of a eukaryotic cell. Here, using transcriptome and proteome profiling data, we analyzed AS in two life forms of the model moss Physcomitrella patens, namely protonemata and gametophores, as well as in protoplasts. We identified 12 043 genes subject to alternative splicing and analyzed the extent to which AS contributes to proteome diversity. We could distinguish a few examples that unambiguously indicated the presence of two or more splice isoforms from the same locus at the proteomic level. Our results indicate that alternative isoforms have a small effect on proteome diversity. We also revealed that mRNAs and pre-mRNAs have thousands of complementary binding sites for long non-coding RNAs (lncRNAs) that may lead to potential interactions in transcriptome. This finding points to an additional level of gene expression and AS regulation by non-coding transcripts in Physcomitrella patens. Among the differentially expressed and spliced genes we found serine/arginine-rich (SR) genes, which are known to regulate AS in cells. We found that treatment with abscisic (ABA) and methyl jasmonic acids (MeJA) led to an isoform-specific response and suggested that ABA in gametophores and MeJA in protoplasts regulate AS and the transcription of SR genes.

Mapping, modeling, and characterization of protein-protein interactions on a proteomic scale

Proteins effect a number of biological functions, from cellular signaling, organization, mobility, and transport to catalyzing biochemical reactions and coordinating an immune response. These varied functions are often dependent upon macromolecular interactions, particularly with other proteins. Small-scale studies in the scientific literature report protein-protein interactions (PPIs), but slowly and with bias towards well-studied proteins. In an era where genomic sequence is readily available, deducing genotype-phenotype relationships requires an understanding of protein connectivity at proteome-scale. A proteome-scale map of the protein-protein interaction network provides a global view of cellular organization and function. Here, we discuss a summary of methods for building proteome-scale interactome maps and the current status and implications of mapping achievements. Not only do interactome maps serve as a reference, detailing global cellular function and organization patterns, but they can also reveal the mechanisms altered by disease alleles, highlight the patterns of interaction rewiring across evolution, and help pinpoint biologically and therapeutically relevant proteins. Despite the considerable strides made in proteome-wide mapping, several technical challenges persist. Therefore, future considerations that impact current mapping efforts are also discussed.

Alternative splicing as a regulator of development and tissue identity

Alternative splicing of eukaryotic transcripts is a mechanism that enables cells to generate vast protein diversity from a limited number of genes. The mechanisms and outcomes of alternative splicing of individual transcripts are relatively well understood, and recent efforts have been directed towards studying splicing networks. It has become apparent that coordinated splicing networks regulate tissue and organ development, and that alternative splicing has important physiological functions in different developmental processes in humans.

Identification of alternatively spliced transcripts of rice phytochelatin synthase 2 gene OsPCS2 involved in mitigation of cadmium and arsenic stresses

The OsPCS2 exhibits root- and shoot-specific differential ratios of alternatively spliced transcripts in indica rice under Cd stress, and plays role in Cd and As stress tolerance and accumulation. Enzymatic activity of phytochelatin synthase (PCS) in plant produces phytochelatins, which help in sequestration of heavy metal(loid)s inside the cell vacuole to alleviate toxicity. Here we report that among the two PCS genes-OsPCS1 and OsPCS2 in indica rice (Oryza sativa) cultivar, the OsPCS2 produces an alternatively spliced OsPCS2b transcript that bears the unusual premature termination codon besides the canonically spliced OsPCS2a transcript. Root- and shoot-specific differential ratios of alternatively spliced OsPCS2a and OsPCS2b transcript expressions were observed under cadmium stress. Saccharomyces cerevisiae cells transformed with OsPCS2a exhibited increased cadmium (Cd) and arsenic (As) tolerance and accumulation, unlike the OsPCS2b transformed yeast cells. An intron-containing hairpin RNA-mediated gene silencing was carried out in endosperm-specific manner for efficient down-regulation of OsPCS genes in rice grains. Analysis of the transgenic rice lines grown under metal(loid) stress revealed almost complete absence of both OsPCS1 and OsPCS2 transcripts in the developing seeds coupled with the significant reduction in the content of Cd (~51%) and As (~35%) in grains compared with the non-transgenic plant. Taken together, the findings indicate towards a crucial role played by the tissue-specific alternative splicing and relative abundance of the OsPCS2 gene during heavy metal(loid) stress mitigation in rice plant.

Identification of protein features encoded by alternative exons using Exon Ontology

Transcriptomic genome-wide analyses demonstrate massive variation of alternative splicing in many physiological and pathological situations. One major challenge is now to establish the biological contribution of alternative splicing variation in physiological- or pathological-associated cellular phenotypes. Toward this end, we developed a computational approach, named “Exon Ontology,” based on terms corresponding to well-characterized protein features organized in an ontology tree. Exon Ontology is conceptually similar to Gene Ontology-based approaches but focuses on exon-encoded protein features instead of gene level functional annotations. Exon Ontology describes the protein features encoded by a selected list of exons and looks for potential Exon Ontology term enrichment. By applying this strategy to exons that are differentially spliced between epithelial and mesenchymal cells and after extensive experimental validation, we demonstrate that Exon Ontology provides support to discover specific protein features regulated by alternative splicing. We also show that Exon Ontology helps to unravel biological processes that depend on suites of coregulated alternative exons, as we uncovered a role of epithelial cell-enriched splicing factors in the AKT signaling pathway and of mesenchymal cell-enriched splicing factors in driving splicing events impacting on autophagy. Freely available on the web, Exon Ontology is the first computational resource that allows getting a quick insight into the protein features encoded by alternative exons and investigating whether coregulated exons contain the same biological information.

Intron retention as a component of regulated gene expression programs

Intron retention has long been an exemplar of regulated splicing with case studies of individual events serving as models that provided key mechanistic insights into the process of splicing control. In organisms such as plants and budding yeast, intron retention is well understood as a major mechanism of gene expression regulation. In contrast, in mammalian systems, the extent and functional significance of intron retention have, until recently, remained greatly underappreciated. Technical challenges to the global detection and quantitation of transcripts with retained introns have often led to intron retention being overlooked or dismissed as “noise”. Now, however, with the wealth of information available from high-throughput deep sequencing, combined with focused computational and statistical analyses, we are able to distinguish clear intron retention patterns in various physiological and pathological contexts. Several recent studies have demonstrated intron retention as a central component of gene expression programs during normal development as well as in response to stress and disease. Furthermore, these studies revealed various ways in which intron retention regulates protein isoform production, RNA stability and translation efficiency, and rapid induction of expression via post-transcriptional splicing of retained introns. In this review, we highlight critical findings from these transcriptomic studies and discuss commonalties in the patterns prevalent in intron retention networks at the functional and regulatory levels.

Rewiring of the inferred protein interactome during blood development studied with the tool PPICompare

BACKGROUND

Differential analysis of cellular conditions is a key approach towards understanding the consequences and driving causes behind biological processes such as developmental transitions or diseases. The progress of whole-genome expression profiling enabled to conveniently capture the state of a cell's transcriptome and to detect the characteristic features that distinguish cells in specific conditions. In contrast, mapping the physical protein interactome for many samples is experimentally infeasible at the moment. For the understanding of the whole system, however, it is equally important how the interactions of proteins are rewired between cellular states. To overcome this deficiency, we recently showed how condition-specific protein interaction networks that even consider alternative splicing can be inferred from transcript expression data. Here, we present the differential network analysis tool PPICompare that was specifically designed for isoform-sensitive protein interaction networks.

RESULTS

Besides detecting significant rewiring events between the interactomes of grouped samples, PPICompare infers which alterations to the transcriptome caused each rewiring event and what is the minimal set of alterations necessary to explain all between-group changes. When applied to the development of blood cells, we verified that a reasonable amount of rewiring events were reported by the tool and found that differential gene expression was the major determinant of cellular adjustments to the interactome. Alternative splicing events were consistently necessary in each developmental step to explain all significant alterations and were especially important for rewiring in the context of transcriptional control.

CONCLUSIONS

Applying PPICompare enabled us to investigate the dynamics of the human protein interactome during developmental transitions. A platform-independent implementation of the tool PPICompare is available at https://sourceforge.net/projects/ppicompare/ .

C-terminal splice variants of P/Q-type Ca2+ channel CaV2.1 α1 subunits are differentially regulated by Rab3-interacting molecule proteins

Voltage-dependent Ca²⁺ channels (VDCCs) mediate neurotransmitter release controlled by presynaptic proteins such as the scaffolding proteins Rab3-interacting molecules (RIMs). RIMs confer sustained activity and anchoring of synaptic vesicles to the VDCCs. Multiple sites on the VDCC α₁ and β subunits have been reported to mediate the RIMs-VDCC interaction, but their significance is unclear. Because alternative splicing of exons 44 and 47 in the P/Q-type VDCC α₁ subunit Ca_V2.1 gene generates major variants of the Ca_V2.1 C-terminal region, known for associating with presynaptic proteins, we focused here on the protein regions encoded by these two exons. Co-immunoprecipitation experiments indicated that the C-terminal domain (CTD) encoded by Ca_V2.1 exons 40-47 interacts with the α-RIMs, RIM1α and RIM2α, and this interaction was abolished by alternative splicing that deletes the protein regions encoded by exons 44 and 47. Electrophysiological characterization of VDCC currents revealed that the suppressive effect of RIM2α on voltage-dependent inactivation (VDI) was stronger than that of RIM1α for the Ca_V2.1 variant containing the region encoded by exons 44 and 47. Importantly, in the Ca_V2.1 variant in which exons 44 and 47 were deleted, strong RIM2α-mediated VDI suppression was attenuated to a level comparable with that of RIM1α-mediated VDI suppression, which was unaffected by the exclusion of exons 44 and 47. Studies of deletion mutants of the exon 47 region identified 17 amino acid residues on the C-terminal side of a polyglutamine stretch as being essential for the potentiated VDI suppression characteristic of RIM2α. These results suggest that the interactions of the Ca_V2.1 CTD with RIMs enable Ca_V2.1 proteins to distinguish α-RIM isoforms in VDI suppression of P/Q-type VDCC currents.

Prostate-associated gene 4 (PAGE4), an intrinsically disordered cancer/testis antigen, is a novel therapeutic target for prostate cancer

Prostate-associated gene 4 (PAGE4) is a remarkably prostate-specific Cancer/Testis Antigen that is highly upregulated in the human fetal prostate and its diseased states but not in the adult normal gland. PAGE4 is an intrinsically disordered protein (IDP) that functions as a stress-response protein to suppress reactive oxygen species as well as prevent DNA damage. In addition, PAGE4 is also a transcriptional regulator that potentiates transactivation by the oncogene c-Jun. c-Jun forms the AP-1 complex by heterodimerizing with members of the Fos family and plays an important role in the development and pathology of the prostate gland, underscoring the importance of the PAGE4/c-Jun interaction. HIPK1, also a component of the stress-response pathway, phosphorylates PAGE4 at T51 which is critical for its transcriptional activity. Phosphorylation induces conformational and dynamic switching in the PAGE4 ensemble leading to a new cellular function. Finally, bioinformatics evidence suggests that the PAGE4 mRNA could be alternatively spliced resulting in four potential isoforms of the polypeptide alluding to the possibility of a range of conformational ensembles with latent functions. Considered together, the data suggest that PAGE4 may represent the first molecular link between stress and prostate cancer (PCa). Thus, pharmacologically targeting PAGE4 may be a novel opportunity for treating and managing patients with PCa, especially patients with low-risk disease.

Proteome-Scale Human Interactomics

Cellular functions are mediated by complex interactome networks of physical, biochemical, and functional interactions between DNA sequences, RNA molecules, proteins, lipids, and small metabolites. A thorough understanding of cellular organization requires accurate and relatively complete models of interactome networks at proteome scale. The recent publication of four human protein-protein interaction (PPI) maps represents a technological breakthrough and an unprecedented resource for the scientific community, heralding a new era of proteome-scale human interactomics. Our knowledge gained from these and complementary studies provides fresh insights into the opportunities and challenges when analyzing systematically generated interactome data, defines a clear roadmap towards the generation of a first reference interactome, and reveals new perspectives on the organization of cellular life.

SRRM4-dependent neuron-specific alternative splicing of protrudin transcripts regulates neurite outgrowth

Alternative splicing gives rise to diversity of the proteome, and it is especially prevalent in the mammalian nervous system. Indeed, many factors that control the splicing process govern nervous system development. Among such factors, SRRM4 is an important regulator of aspects of neural differentiation including neurite outgrowth. The mechanism by which SRRM4 regulates neurite outgrowth has remained poorly understood, however. We now show that SRRM4 regulates the splicing of protrudin gene (Zfyve27) transcripts in neuronal cells. SRRM4 was found to promote splicing of protrudin pre-mRNA so as to include a microexon (exon L) encoding seven amino acids in a neuron-specific manner. The resulting protein (protrudin-L) promotes neurite outgrowth during neurogenesis. Depletion of SRRM4 in Neuro2A cells impaired inclusion of exon L in protrudin mRNA, resulting in the generation of a shorter protein isoform (protrudin-S) that is less effective at promoting neurite extension. SRRM4 was found to recognize a UGC motif that is located immediately upstream of exon L and is necessary for inclusion of exon L in the mature transcript. Deletion of exon L in Neuro2A or embryonic stem cells inhibited neurite outgrowth. Our results suggest that SRRM4 controls neurite outgrowth through regulation of alternative splicing of protrudin transcripts.

Targeted RNA-Seq profiling of splicing pattern in the DMD gene: exons are mostly constitutively spliced in human skeletal muscle

We have analysed the splicing pattern of the human Duchenne Muscular Dystrophy (DMD) NB transcript in normal skeletal muscle. To achieve depth of coverage required for the analysis of this lowly expressed gene in muscle, we designed a targeted RNA-Seq procedure that combines amplification of the full-length 11.3 kb DMD cDNA sequence and 454 sequencing technology. A high and uniform coverage of the cDNA sequence was obtained that allowed to draw up a reliable inventory of the physiological alternative splicing events in the muscular DMD transcript. In contrast to previous assumptions, we evidenced that most of the 79 DMD exons are constitutively spliced in skeletal muscle. Only a limited number of 12 alternative splicing events were identified, all present at a very low level. These include previously known exon skipping events but also newly described pseudoexon inclusions and alternative 3′ splice sites, of which one is the first functional NAGNAG splice site reported in the DMD gene. This study provides the first RNA-Seq-based reference of DMD splicing pattern in skeletal muscle and reports on an experimental procedure well suited to detect condition-specific differences in this low abundance transcript that may prove useful for diagnostic, research or RNA-based therapeutic applications.

LUMIER: A Discovery Tool for Mammalian Protein Interaction Networks

Protein-protein interactions (PPIs) play an essential role in all biological processes. In vivo, PPIs occur dynamically and depend on extracellular cues. To discover novel protein-protein interactions in mammalian cells, we developed a high-throughput automated technology called LUMIER (LUminescence-based Mammalian IntERactome). In this approach, we co-express a Luciferase (LUC)-tagged fusion protein along with a Flag-tagged protein in an efficiently transfectable cell line such as HEK-293T cells. The interaction between the two proteins is determined by co-immunoprecipitation using an anti-Flag antibody, and the presence of the LUC-tagged interactor in the complex is subsequently detected via its luciferase activity. LUMIER can easily detect transmembrane protein partners, interactions that are signaling- or splice isoform-dependent, as well as those that may occur only in the presence of posttranslational modifications. Using various collections of Flag-tagged proteins, we have generated protein interaction networks for several TGF-β family receptors, Wnt pathway members, and have systematically analyzed the effect of neural-specific alternative splicing on protein interaction networks. The results have provided important insights into the physiological and functional relevance of some of the novel interactions found. LUMIER is highly scalable and can be used for both low- and high-throughput strategies. LUMIER is thus a valuable tool for the identification and characterization of dynamically regulated PPIs in mammalian systems. Here, we describe a manual version of LUMIER in a 96-well format that can be easily implemented in any laboratory.

Strategic Integration of Multiple Bioinformatics Resources for System Level Analysis of Biological Networks

Recent technological advances in genomics allow the production of biological data at unprecedented tera- and petabyte scales. Efficient mining of these vast and complex datasets for the needs of biomedical research critically depends on a seamless integration of the clinical, genomic, and experimental information with prior knowledge about genotype-phenotype relationships. Such experimental data accumulated in publicly available databases should be accessible to a variety of algorithms and analytical pipelines that drive computational analysis and data mining.We present an integrated computational platform Lynx (Sulakhe et al., Nucleic Acids Res 44:D882-D887, 2016) ( http://lynx.cri.uchicago.edu ), a web-based database and knowledge extraction engine. It provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization. It gives public access to the Lynx integrated knowledge base (LynxKB) and its analytical tools via user-friendly web services and interfaces. The Lynx service-oriented architecture supports annotation and analysis of high-throughput experimental data. Lynx tools assist the user in extracting meaningful knowledge from LynxKB and experimental data, and in the generation of weighted hypotheses regarding the genes and molecular mechanisms contributing to human phenotypes or conditions of interest. The goal of this integrated platform is to support the end-to-end analytical needs of various translational projects.

The role of alternative splicing in cancer

The functional capacity of cells is defined by the transcriptome. Many recent studies have identified variations in the transcriptome of tumors due to alternative splicing changes, as well as mutations in splicing factors and regulatory signals in most tumor types. Some of these alterations have been linked to tumor progression, metastasis, therapy resistance, and other oncogenic processes. Here, we describe the different mechanisms that drive splicing changes in tumors and their impact in cancer. Motivated by the current evidence, we propose a model whereby a subset of the splicing patterns contributes to the definition of specific tumor phenotypes, and may hold potential for the development of novel clinical biomarkers and therapeutic approaches.

Identification and Characterization of a New Protein Isoform of Human 5-Lipoxygenase

Leukotrienes (LTs) are inflammatory mediators that play a pivotal role in many diseases like asthma bronchiale, atherosclerosis and in various types of cancer. The key enzyme for generation of LTs is the 5-lipoxygenase (5-LO). Here, we present a novel putative protein isoform of human 5-LO that lacks exon 4, termed 5-LOΔ4, identified in cells of lymphoid origin, namely the Burkitt lymphoma cell lines Raji and BL41 as well as primary B and T cells. Deletion of exon 4 does not shift the reading frame and therefore the mRNA is not subjected to non-mediated mRNA decay (NMD). By eliminating exon 4, the amino acids Trp144 until Ala184 are omitted in the corresponding protein. Transfection of HEK293T cells with a 5-LOΔ4 expression plasmid led to expression of the corresponding protein which suggests that the 5-LOΔ4 isoform is a stable protein in eukaryotic cells. We were also able to obtain soluble protein after expression in E. coli and purification. The isoform itself lacks canonical enzymatic activity as it misses the non-heme iron but it still retains ATP-binding affinity. Differential scanning fluorimetric analysis shows two transitions, corresponding to the two domains of 5-LO. Whilst the catalytic domain of 5-LO WT is destabilized by calcium, addition of calcium has no influence on the catalytic domain of 5-LOΔ4. Furthermore, we investigated the influence of 5-LOΔ4 on the activity of 5-LO WT and proved that it stimulates 5-LO product formation at low protein concentrations. Therefore regulation of 5-LO by its isoform 5-LOΔ4 might represent a novel mechanism of controlling the biosynthesis of lipid mediators.

Towards improved genome-scale metabolic network reconstructions: unification, transcript specificity and beyond

Genome-scale metabolic network reconstructions provide a basis for the investigation of the metabolic properties of an organism. There are reconstructions available for multiple organisms, from prokaryotes to higher organisms and methods for the analysis of a reconstruction. One example is the use of flux balance analysis to improve the yields of a target chemical, which has been applied successfully. However, comparison of results between existing reconstructions and models presents a challenge because of the heterogeneity of the available reconstructions, for example, of standards for presenting gene-protein-reaction associations, nomenclature of metabolites and reactions or selection of protonation states. The lack of comparability for gene identifiers or model-specific reactions without annotated evidence often leads to the creation of a new model from scratch, as data cannot be properly matched otherwise. In this contribution, we propose to improve the predictive power of metabolic models by switching from gene-protein-reaction associations to transcript-isoform-reaction associations, thus taking advantage of the improvement of precision in gene expression measurements. To achieve this precision, we discuss available databases that can be used to retrieve this type of information and point at issues that can arise from their neglect. Further, we stress issues that arise from non-standardized building pipelines, like inconsistencies in protonation states. In addition, problems arising from the use of non-specific cofactors, e.g. artificial futile cycles, are discussed, and finally efforts of the metabolic modelling community to unify model reconstructions are highlighted.

Alternative Splicing May Not Be the Key to Proteome Complexity

Alternative splicing is commonly believed to be a major source of cellular protein diversity. However, although many thousands of alternatively spliced transcripts are routinely detected in RNA-seq studies, reliable large-scale mass spectrometry-based proteomics analyses identify only a small fraction of annotated alternative isoforms. The clearest finding from proteomics experiments is that most human genes have a single main protein isoform, while those alternative isoforms that are identified tend to be the most biologically plausible: those with the most cross-species conservation and those that do not compromise functional domains. Indeed, most alternative exons do not seem to be under selective pressure, suggesting that a large majority of predicted alternative transcripts may not even be translated into proteins.

ExonImpact: Prioritizing Pathogenic Alternative Splicing Events

Alternative splicing (AS) is a closely regulated process that allows a single gene to encode multiple protein isoforms, thereby contributing to the diversity of the proteome. Dysregulation of the splicing process has been found to be associated with many inherited diseases. However, among the pathogenic AS events, there are numerous "passenger" events whose inclusion or exclusion does not lead to significant changes with respect to protein function. In this study, we evaluate the secondary and tertiary structural features of proteins associated with disease-causing and neutral AS events, and show that several structural features are strongly associated with the pathological impact of exon inclusion. We further develop a machine-learning-based computational model, ExonImpact, for prioritizing and evaluating the functional consequences of hitherto uncharacterized AS events. We evaluated our model using several strategies including cross-validation, and data from the Gene-Tissue Expression (GTEx) and ClinVar databases. ExonImpact is freely available at http://watson.compbio.iupui.edu/ExonImpact.

Fluorescence ImmunoPrecipitation (FLIP): a Novel Assay for High-Throughput IP

Background

The immunoprecipitation (IP) assay is a valuable molecular biology tool applied across a breadth of fields. The standard assay couples IP to immunoblotting (IP/IB), a procedure severely limited as it is not easily scaled for high-throughput analysis.

Results

Here we describe and characterize a new methodology for fast and reliable evaluation of an immunoprecipitation reaction. FLIP (FLuorescence IP) relies on the expression of the target protein as a chromophore-tagged protein and couples IP with the measurement of fluorescent signal coating agarose beads. We show here that FLIP displays similar sensitivity to the standard IP/IB procedure but is amenable to high-throughput analysis. We applied FLIP to the screening of mouse monoclonal antibodies of unknown behavior in IP procedures. The parallel analysis of the considered antibodies using FLIP and IP/western shows good correlation between the two procedures. We also show application of FLIP using unpurified antibodies (hybridoma supernatant) and we developed a publicly available tool for the easy analysis and quantification of FLIP signals.

Conclusions

Altogether, our characterizations of this new methodology show that FLIP is an appealing and reliable tool for any application of high-throughput IP.

Electronic supplementary material

The online version of this article (doi:10.1186/s12575-016-0046-x) contains supplementary material, which is available to authorized users.

Conserved functional antagonism of CELF and MBNL proteins controls stem cell-specific alternative splicing in planarians

In contrast to transcriptional regulation, the function of alternative splicing (AS) in stem cells is poorly understood. In mammals, MBNL proteins negatively regulate an exon program specific of embryonic stem cells; however, little is known about the in vivo significance of this regulation. We studied AS in a powerful in vivo model for stem cell biology, the planarian Schmidtea mediterranea. We discover a conserved AS program comprising hundreds of alternative exons, microexons and introns that is differentially regulated in planarian stem cells, and comprehensively identify its regulators. We show that functional antagonism between CELF and MBNL factors directly controls stem cell-specific AS in planarians, placing the origin of this regulatory mechanism at the base of Bilaterians. Knockdown of CELF or MBNL factors lead to abnormal regenerative capacities by affecting self-renewal and differentiation sets of genes, respectively. These results highlight the importance of AS interactions in stem cell regulation across metazoans.

DOI:http://dx.doi.org/10.7554/eLife.16797.001

Stem cells are specialized cells found in all animals that can develop into several different types of mature cells. Stem cells are therefore well suited for maintaining organs that are in heavy use, such as the intestine, and for regenerating tissues that are prone to injury, like the skin.

One reason why stem cells differ from mature cell types is because they activate, or “express”, different sets of genes. In addition, many genes can be expressed as one of several versions. These variants, also known as isoforms, are generated by a process called alternative splicing. In mature cells in mammals, a group of proteins called the MBNL proteins help to prevent the expression of gene isoforms that are characteristic to stem cells.

The adult flatworm Schmidtea mediterranea contains stem cells that can regenerate any part of the body. Solana, Irimia et al. have now investigated whether alternative splicing is important for controlling how the worm’s stem cells behave. After establishing which gene isoforms are expressed in the stem cells and the mature cells, the levels of different sets of proteins that control alternative splicing were experimentally reduced.

The results indicate that just as seen in mammals, the MBNL proteins reduce the expression of stem cell-related gene isoforms in the flatworms. Furthermore, Solana, Irimia et al. found that another protein called CELF counteracts MBNL proteins by helping to express gene isoforms that are active in stem cells.

The interplay between the MBNL and CELF proteins has also been observed in human cells. Thus, it appears that this way of controlling alternative splicing is common to flatworms and mammals and is therefore evolutionarily ancient. This suggests that other similar ways of controlling stem cells by interactions between regulatory proteins might be working in all animal stem cells. Further studies are now needed to investigate these control proteins.

DOI:http://dx.doi.org/10.7554/eLife.16797.002

Network biology concepts in complex disease comorbidities

The co-occurrence of diseases can inform the underlying network biology of shared and multifunctional genes and pathways. In addition, comorbidities help to elucidate the effects of external exposures, such as diet, lifestyle and patient care. With worldwide health transaction data now often being collected electronically, disease co-occurrences are starting to be quantitatively characterized. Linking network dynamics to the real-life, non-ideal patient in whom diseases co-occur and interact provides a valuable basis for generating hypotheses on molecular disease mechanisms, and provides knowledge that can facilitate drug repurposing and the development of targeted therapeutic strategies.

Predominant expression of Alzheimer's disease-associated BIN1 in mature oligodendrocytes and localization to white matter tracts

BACKGROUND

Genome-wide association studies have identified BIN1 within the second most significant susceptibility locus in late-onset Alzheimer's disease (AD). BIN1 undergoes complex alternative splicing to generate multiple isoforms with diverse functions in multiple cellular processes including endocytosis and membrane remodeling. An increase in BIN1 expression in AD and an interaction between BIN1 and Tau have been reported. However, disparate descriptions of BIN1 expression and localization in the brain previously reported in the literature and the lack of clarity on brain BIN1 isoforms present formidable challenges to our understanding of how genetic variants in BIN1 increase the risk for AD.

METHODS

In this study, we analyzed BIN1 mRNA and protein levels in human brain samples from individuals with or without AD. In addition, we characterized the BIN1 expression and isoform diversity in human and rodent tissue by immunohistochemistry and immunoblotting using a panel of BIN1 antibodies.

RESULTS

Here, we report on BIN1 isoform diversity in the human brain and document alterations in the levels of select BIN1 isoforms in individuals with AD. In addition, we report striking BIN1 localization to white matter tracts in rodent and the human brain, and document that the large majority of BIN1 is expressed in mature oligodendrocytes whereas neuronal BIN1 represents a minor fraction. This predominant non-neuronal BIN1 localization contrasts with the strict neuronal expression and presynaptic localization of the BIN1 paralog, Amphiphysin 1. We also observe upregulation of BIN1 at the onset of postnatal myelination in the brain and during differentiation of cultured oligodendrocytes. Finally, we document that the loss of BIN1 significantly correlates with the extent of demyelination in multiple sclerosis lesions.

CONCLUSION

Our study provides new insights into the brain distribution and cellular expression of an important risk factor associated with late-onset AD. We propose that efforts to define how genetic variants in BIN1 elevate the risk for AD would behoove to consider BIN1 function in the context of its main expression in mature oligodendrocytes and the potential for a role of BIN1 in the membrane remodeling that accompanies the process of myelination.

Inside out: the role of nucleocytoplasmic transport in ALS and FTLD

Neurodegenerative diseases are characterized by the presence of protein inclusions with a different protein content depending on the type of disease. Amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) are no exceptions to this common theme. In most ALS and FTLD cases, the predominant pathological species are RNA-binding proteins. Interestingly, these proteins are both depleted from their normal nuclear localization and aggregated in the cytoplasm. This key pathological feature has suggested a potential dual mechanism with both nuclear loss of function and cytoplasmic gain of function being at play. Yet, why and how this pathological cascade is initiated in most patients, and especially sporadic cases, is currently unresolved. Recent breakthroughs in C9orf72 ALS/FTLD disease models point at a pivotal role for the nuclear transport system in toxicity. To address whether defects in nuclear transport are indeed implicated in the disease, we reviewed two decades of ALS/FTLD literature and combined this with bioinformatic analyses. We find that both RNA-binding proteins and nuclear transport factors are key players in ALS/FTLD pathology. Moreover, our analyses suggest that disturbances in nucleocytoplasmic transport play a crucial initiating role in the disease, by bridging both nuclear loss and cytoplasmic gain of functions. These findings highlight this process as a novel and promising therapeutic target for ALS and FTLD.

Contextual fear conditioning induces differential alternative splicing

The process of memory consolidation requires transcription and translation to form long-term memories. Significant effort has been dedicated to understanding changes in hippocampal gene expression after contextual fear conditioning. However, alternative splicing by differential transcript regulation during this time period has received less attention. Here, we use RNA-seq to determine exon-level changes in expression after contextual fear conditioning and retrieval. Our work reveals that a short variant of Homer1, Ania-3, is regulated by contextual fear conditioning. The ribosome biogenesis regulator Las1l, small nucleolar RNA Snord14e, and the RNA-binding protein Rbm3 also change specific transcript usage after fear conditioning. The changes in Ania-3 and Las1l are specific to either the new context or the context-shock association, while the changes in Rbm3 occur after context or shock only. Our analysis revealed novel transcript regulation of previously undetected changes after learning, revealing the importance of high throughput sequencing approaches in the study of gene expression changes after learning.

Transcriptome-Wide Analysis Reveals Modulation of Human Macrophage Inflammatory Phenotype Through Alternative Splicing

OBJECTIVE

Human macrophages can shift phenotype across the inflammatory M1 and reparative M2 spectrum in response to environmental challenges, but the mechanisms promoting inflammatory and cardiometabolic disease-associated M1 phenotypes remain incompletely understood. Alternative splicing (AS) is emerging as an important regulator of cellular function, yet its role in macrophage activation is largely unknown. We investigated the extent to which AS occurs in M1 activation within the cardiometabolic disease context and validated a functional genomic cell model for studying human macrophage-related AS events.

APPROACH AND RESULTS

From deep RNA-sequencing of resting, M1, and M2 primary human monocyte-derived macrophages, we found 3860 differentially expressed genes in M1 activation and detected 233 M1-induced AS events; the majority of AS events were cell- and M1-specific with enrichment for pathways relevant to macrophage inflammation. Using genetic variant data for 10 cardiometabolic traits, we identified 28 trait-associated variants within the genomic loci of 21 alternatively spliced genes and 15 variants within 7 differentially expressed regulatory splicing factors in M1 activation. Knockdown of 1 such splicing factor, CELF1, in primary human macrophages led to increased inflammatory response to M1 stimulation, demonstrating CELF1's potential modulation of the M1 phenotype. Finally, we demonstrated that an induced pluripotent stem cell-derived macrophage system recapitulates M1-associated AS events and provides a high-fidelity macrophage AS model.

CONCLUSIONS

AS plays a role in defining macrophage phenotype in a cell- and stimulus-specific fashion. Alternatively spliced genes and splicing factors with trait-associated variants may reveal novel pathways and targets in cardiometabolic diseases.

A Network of Splice Isoforms for the Mouse

The laboratory mouse is the primary mammalian species used for studying alternative splicing events. Recent studies have generated computational models to predict functions for splice isoforms in the mouse. However, the functional relationship network, describing the probability of splice isoforms participating in the same biological process or pathway, has not yet been studied in the mouse. Here we describe a rich genome-wide resource of mouse networks at the isoform level, which was generated using a unique framework that was originally developed to infer isoform functions. This network was built through integrating heterogeneous genomic and protein data, including RNA-seq, exon array, protein docking and pseudo-amino acid composition. Through simulation and cross-validation studies, we demonstrated the accuracy of the algorithm in predicting isoform-level functional relationships. We showed that this network enables the users to reveal functional differences of the isoforms of the same gene, as illustrated by literature evidence with Anxa6 (annexin a6) as an example. We expect this work will become a useful resource for the mouse genetics community to understand gene functions. The network is publicly available at: http://guanlab.ccmb.med.umich.edu/isoformnetwork.

Alternative Splicing of G9a Regulates Neuronal Differentiation

Chromatin modifications are critical for the establishment and maintenance of differentiation programs. G9a, the enzyme responsible for histone H3 lysine 9 dimethylation in mammalian euchromatin, exists as two isoforms with differential inclusion of exon 10 (E10) through alternative splicing. We find that the G9a methyltransferase is required for differentiation of the mouse neuronal cell line N2a and that E10 inclusion increases during neuronal differentiation of cultured cells, as well as in the developing mouse brain. Although E10 inclusion greatly stimulates overall H3K9me2 levels, it does not affect G9a catalytic activity. Instead, E10 increases G9a nuclear localization. We show that the G9a E10(+) isoform is necessary for neuron differentiation and regulates the alternative splicing pattern of its own pre-mRNA, enhancing E10 inclusion. Overall, our findings indicate that by regulating its own alternative splicing, G9a promotes neuron differentiation and creates a positive feedback loop that reinforces cellular commitment to differentiation.

Analysis of weighted co-regulatory networks in maize provides insights into new genes and regulatory mechanisms related to inositol phosphate metabolism

BACKGROUND

D-myo-inositol phosphates (IPs) are a series of phosphate esters. Myo-inositol hexakisphosphate (phytic acid, IP6) is the most abundant IP and has negative effects on animal and human nutrition. IPs play important roles in plant development, stress responses, and signal transduction. However, the metabolic pathways and possible regulatory mechanisms of IPs in maize are unclear. In this study, the B73 (high in phytic acid) and Qi319 (low in phytic acid) lines were selected for RNA-Seq analysis from 427 inbred lines based on a screening of IP levels. By integrating the metabolite data with the RNA-Seq data at three different kernel developmental stages (12, 21 and 30 days after pollination), co-regulatory networks were constructed to explore IP metabolism and its interactions with other pathways.

RESULTS

Differentially expressed gene analyses showed that the expression of MIPS and ITPK was related to differences in IP metabolism in Qi319 and B73. Moreover, WRKY and ethylene-responsive transcription factors (TFs) were common among the differentially expressed TFs, and are likely to be involved in the regulation of IP metabolism. Six co-regulatory networks were constructed, and three were chosen for further analysis. Based on network analyses, we proposed that the GA pathway interacts with the IP pathway through the ubiquitination pathway, and that Ca(2+) signaling functions as a bridge between IPs and other pathways. IP pools were found to be transported by specific ATP-binding cassette (ABC) transporters. Finally, three candidate genes (Mf3, DH2 and CB5) were identified and validated using Arabidopsis lines with mutations in orthologous genes or RNA interference (RNAi)-transgenic maize lines. Some mutant or RNAi lines exhibited seeds with a low-phytic-acid phenotype, indicating perturbation of IP metabolism. Mf3 likely encodes an enzyme involved in IP synthesis, DH2 encodes a transporter responsible for IP transport across organs and CB5 encodes a transporter involved in IP co-transport into vesicles.

CONCLUSIONS

This study provides new insights into IP metabolism and regulation, and facilitates our development of a better understanding of the functions of IPs and how they interact with other pathways involved in plant development and stress responses. Three new genes were discovered and preliminarily validated, thereby increasing our knowledge of IP metabolism.