Alternative splicing links histone modifications to stem cell fate decision

Drought-induced circular RNAs in maize roots: Separating signal from noise

Circular RNAs (circRNAs) play an important role in diverse biological processes; however, their origin and functions, especially in plants, remain largely unclear. Here, we used 2 maize (Zea mays) inbred lines, as well as 14 of their derivative recombination inbred lines with different drought sensitivity, to systematically characterize 8,790 circRNAs in maize roots under well-watered (WW) and water-stress (WS) conditions. We found that a diverse set of circRNAs expressed at significantly higher levels under WS. Enhanced expression of circRNAs was associated with longer flanking introns and an enrichment of long interspersed nuclear element retrotransposable elements. The epigenetic marks found at the back-splicing junctions of circRNA-producing genes were markedly different from canonical splicing, characterized by increased levels of H3K36me3/H3K4me1, as well as decreased levels of H3K9Ac/H3K27Ac. We found that genes expressing circRNAs are subject to relaxed selection. The significant enrichment of trait-associated sites along their genic regions suggested that genes giving rise to circRNAs were associated with plant survival rate under drought stress, implying that circRNAs play roles in plant drought responses. Furthermore, we found that overexpression of circMED16, one of the drought-responsive circRNAs, enhances drought tolerance in Arabidopsis (Arabidopsis thaliana). Our results provide a framework for understanding the intricate interplay of epigenetic modifications and how they contribute to the fine-tuning of circRNA expression under drought stress.

Age-dependent regulation of ELP1 exon 20 splicing in Familial Dysautonomia by RNA Polymerase II kinetics and chromatin structure

Familial Dysautonomia (FD) is a rare disease caused by ELP1 exon 20 skipping. Here we clarify the role of RNA Polymerase II (RNAPII) and chromatin on this splicing event. A slow RNAPII mutant and chromatin-modifying chemicals that reduce the rate of RNAPII elongation induce exon skipping whereas chemicals that create a more relaxed chromatin exon inclusion. In the brain of a mouse transgenic for the human FD-ELP1 we observed on this gene an age-dependent decrease in the RNAPII density profile that was most pronounced on the alternative exon, a robust increase in the repressive marks H3K27me3 and H3K9me3 and a decrease of H3K27Ac, together with a progressive reduction in ELP1 exon 20 inclusion level. In HEK 293T cells, selective drug-induced demethylation of H3K27 increased RNAPII elongation on ELP1 and SMN2, promoted the inclusion of the corresponding alternative exons, and, by RNA-sequencing analysis, induced changes in several alternative splicing events. These data suggest a co-transcriptional model of splicing regulation in which age-dependent changes in H3K27me3/Ac modify the rate of RNAPII elongation and affect processing of ELP1 alternative exon 20.

The Many Roads from Alternative Splicing to Cancer: Molecular Mechanisms Involving Driver Genes

Cancer driver genes are either oncogenes or tumour suppressor genes that are classically activated or inactivated, respectively, by driver mutations. Alternative splicing-which produces various mature mRNAs and, eventually, protein variants from a single gene-may also result in driving neoplastic transformation because of the different and often opposed functions of the variants of driver genes. The present review analyses the different alternative splicing events that result in driving neoplastic transformation, with an emphasis on their molecular mechanisms. To do this, we collected a list of 568 gene drivers of cancer and revised the literature to select those involved in the alternative splicing of other genes as well as those in which its pre-mRNA is subject to alternative splicing, with the result, in both cases, of producing an oncogenic isoform. Thirty-one genes fall into the first category, which includes splicing factors and components of the spliceosome and splicing regulators. In the second category, namely that comprising driver genes in which alternative splicing produces the oncogenic isoform, 168 genes were found. Then, we grouped them according to the molecular mechanisms responsible for alternative splicing yielding oncogenic isoforms, namely, mutations in cis splicing-determining elements, other causes involving non-mutated cis elements, changes in splicing factors, and epigenetic and chromatin-related changes. The data given in the present review substantiate the idea that aberrant splicing may regulate the activation of proto-oncogenes or inactivation of tumour suppressor genes and details on the mechanisms involved are given for more than 40 driver genes.

Alternative pre-mRNA splicing in stem cell function and therapeutic potential: A critical review of current evidence

Alternative splicing is a crucial regulator in stem cell biology, intricately influencing the functions of various biological macromolecules, particularly pre-mRNAs and the resultant protein isoforms. This regulatory mechanism is vital in determining stem cell pluripotency, differentiation, and proliferation. Alternative splicing's role in allowing single genes to produce multiple protein isoforms facilitates the proteomic diversity that is essential for stem cells' functional complexity. This review delves into the critical impact of alternative splicing on cellular functions, focusing on its interaction with key macromolecules and how this affects cellular behavior. We critically examine how alternative splicing modulates the function and stability of pre-mRNAs, leading to diverse protein expressions that govern stem cell characteristics, including pluripotency, self-renewal, survival, proliferation, differentiation, aging, migration, somatic reprogramming, and genomic stability. Furthermore, the review discusses the therapeutic potential of targeting alternative splicing-related pathways in disease treatment, particularly focusing on the modulation of RNA and protein interactions. We address the challenges and future prospects in this field, underscoring the need for further exploration to unravel the complex interplay between alternative splicing, RNA, proteins, and stem cell behaviors, which is crucial for advancing our understanding and therapeutic approaches in regenerative medicine and disease treatment.

Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms

Most human Transcription factors (TFs) genes encode multiple protein isoforms differing in DNA binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators", both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.

Single-cell analysis of isoform switching and transposable element expression during preimplantation embryonic development

Alternative splicing is an essential regulatory mechanism for development and pathogenesis. Through alternative splicing one gene can encode multiple isoforms and be translated into proteins with different functions. Therefore, this diversity is an important dimension to understand the molecular mechanism governing embryo development. Isoform expression in preimplantation embryos has been extensively investigated, leading to the discovery of new isoforms. However, the dynamics of isoform switching of different types of transcripts throughout the development remains unexplored. Here, using single-cell direct isoform sequencing in over 100 single blastomeres from the mouse oocyte to blastocyst stage, we quantified isoform expression and found that 3-prime partial transcripts lacking stop codons are highly accumulated in oocytes and zygotes. These transcripts are not transcription by-products and might play a role in maternal to zygote transition (MZT) process. Long-read sequencing also enabled us to determine the expression of transposable elements (TEs) at specific loci. In this way, we identified 3,894 TE loci that exhibited dynamic changes along the preimplantation development, likely regulating the expression of adjacent genes. Our work provides novel insights into the transcriptional regulation of early embryo development.

TOBF1 modulates mouse embryonic stem cell fate through regulating alternative splicing of pluripotency genes

Embryonic stem cells (ESCs) can undergo lineage-specific differentiation, giving rise to different cell types that constitute an organism. Although roles of transcription factors and chromatin modifiers in these cells have been described, how the alternative splicing (AS) machinery regulates their expression has not been sufficiently explored. Here, we show that the long non-coding RNA (lncRNA)-associated protein TOBF1 modulates the AS of transcripts necessary for maintaining stem cell identity in mouse ESCs. Among the genes affected is serine/arginine splicing factor 1 (SRSF1), whose AS leads to global changes in splicing and expression of a large number of downstream genes involved in the maintenance of ESC pluripotency. By overlaying information derived from TOBF1 chromatin occupancy, the distribution of its pluripotency-associated OCT-SOX binding motifs, and transcripts undergoing differential expression and AS upon its knockout, we describe local nuclear territories where these distinct events converge. Collectively, these contribute to the maintenance of mouse ESC identity.

Molecular Mechanisms of Lupus Susceptibility Allele PBX1D

Pre-B cell leukemia homeobox 1 (PBX1) controls chromatin accessibility to a large number of genes in various cell types. Its dominant negative splice isoform, PBX1D, which lacks the DNA and Hox-binding domains, is expressed more frequently in the CD4+ T cells from lupus-prone mice and patients with systemic lupus erythematosus than healthy control subjects. PBX1D overexpression in CD4+ T cells impaired regulatory T cell homeostasis and expanded inflammatory CD4+ T cells. In this study, we showed that PBX1 message expression is downregulated by activation in CD4+ T cells as well as in B cells. PBX1D protein was less stable than the normal isoform, PBX1B, and it is degraded through the ubiquitin-proteasome-dependent pathway. The DNA binding domain lacking in PBX1D has two putative ubiquitin binding sites, K292 and K293, that are predicted to be in direct contact with DNA. Mutation of K292-293 reduced PBX1B stability to a level similar to PBX1D and abrogated DNA binding. In addition, contrary to PBX1B, PBX1D is retained in the cytoplasm without the help of the cofactors MEIS or PREP1, indicating a different requirement for nuclear translocation. Overall, these findings suggest that multiple post-transcriptional mechanisms are responsible for PBX1D loss of function and induction of CD4+ T cell inflammatory phenotypes in systemic lupus erythematosus.

Single-cell and long-read sequencing to enhance modelling of splicing and cell-fate determination

Single-cell sequencing technologies have revolutionised the life sciences and biomedical research. Single-cell sequencing provides high-resolution data on cell heterogeneity, allowing high-fidelity cell type identification, and lineage tracking. Computational algorithms and mathematical models have been developed to make sense of the data, compensate for errors and simulate the biological processes, which has led to breakthroughs in our understanding of cell differentiation, cell-fate determination and tissue cell composition. The development of long-read (a.k.a. third-generation) sequencing technologies has produced powerful tools for investigating alternative splicing, isoform expression (at the RNA level), genome assembly and the detection of complex structural variants (at the DNA level). In this review, we provide an overview of the recent advancements in single-cell and long-read sequencing technologies, with a particular focus on the computational algorithms that help in correcting, analysing, and interpreting the resulting data. Additionally, we review some mathematical models that use single-cell and long-read sequencing data to study cell-fate determination and alternative splicing, respectively. Moreover, we highlight the emerging opportunities in modelling cell-fate determination that result from the combination of single-cell and long-read sequencing technologies.

Epigenetic Regulations in Autoimmunity and Cancer: from Basic Science to Translational Medicine

Epigenetics, as a discipline that aims to explain the differential expression of phenotypes arising from the same gene sequence and the heritability of epigenetic expression, has received much attention in medicine. Epigenetic mechanisms are constantly being discovered, including DNA methylation, histone modifications, noncoding RNAs and m6A. The immune system mainly achieves an immune response through the differentiation and functional expression of immune cells, in which epigenetic modification will have an important impact. Because of immune infiltration in the tumor microenvironment, immunotherapy has become a research hotspot in tumor therapy. Epigenetics plays an important role in autoimmune diseases and cancers through immunology. An increasing number of drugs targeting epigenetic mechanisms, such as DNA methyltransferase inhibitors, histone deacetylase inhibitors, and drug combinations, are being evaluated in clinical trials for the treatment of various cancers (including leukemia and osteosarcoma) and autoimmune diseases (systemic lupus erythematosus, rheumatoid arthritis, systemic sclerosis). This review summarizes the progress of epigenetic regulation for cancers and autoimmune diseases to date, shedding light on potential therapeutic strategies.

Research progress of PBX1 in developmental and regenerative medicine

Pre-B-cell leukemia transcription factor 1 (PBX1) proteins are a subfamily of evolutionarily conserved atypical homeodomain transcription factors belonging to the superfamily of triple amino acid loop extension homeodomain proteins. PBX family members play crucial roles in the regulation of various pathophysiological processes. This article reviews the research progress on PBX1 in terms of structure, developmental function, and regenerative medicine. The potential mechanisms of development and research targets in regenerative medicine are also summarized. It also suggests a possible link between PBX1 in the two domains, which is expected to open up a new field for future exploration of cell homeostasis, as well as the regulation of endogenous danger signals. This would provide a new target for the study of diseases in various systems.

Locus-Specific Isolation of the Nanog Chromatin Identifies Regulators Relevant to Pluripotency of Mouse Embryonic Stem Cells and Reprogramming of Somatic Cells

Pluripotency is a crucial feature of pluripotent stem cells, which are regulated by the core pluripotency network consisting of key transcription factors and signaling molecules. However, relatively less is known about the molecular mechanisms that modify the core pluripotency network. Here we used the CAPTURE (CRISPR Affinity Purification in situ of Regulatory Elements) to unbiasedly isolate proteins assembled on the Nanog promoter in mouse embryonic stem cells (mESCs), and then tested their functional relevance to the maintenance of mESCs and reprogramming of somatic cells. Gene ontology analysis revealed that the identified proteins, including many RNA-binding proteins (RBPs), are enriched in RNA-related functions and gene expression. ChIP-qPCR experiments confirmed that BCLAF1, FUBP1, MSH6, PARK7, PSIP1, and THRAP3 occupy the Nanog promoter region in mESCs. Knockdown experiments of these factors show that they play varying roles in self-renewal, pluripotency gene expression, and differentiation of mESCs as well as in the reprogramming of somatic cells. Our results show the utility of unbiased identification of chromatin-associated proteins on a pluripotency gene in mESCs and reveal the functional relevance of RBPs in ESC differentiation and somatic cell reprogramming.

The emerging significance of splicing in vertebrate development

Splicing is a crucial regulatory node of gene expression that has been leveraged to expand the proteome from a limited number of genes. Indeed, the vast increase in intron number that accompanied vertebrate emergence might have aided the evolution of developmental and organismal complexity. Here, we review how animal models for core spliceosome components have provided insights into the role of splicing in vertebrate development, with a specific focus on neuronal, neural crest and skeletal development. To this end, we also discuss relevant spliceosomopathies, which are developmental disorders linked to mutations in spliceosome subunits. Finally, we discuss potential mechanisms that could underlie the tissue-specific phenotypes often observed upon spliceosome inhibition and identify gaps in our knowledge that, we hope, will inspire further research.

Histone Marks-Dependent Effect on Alternative Splicing: New Perspectives for Targeted Splicing Modulation in Cancer?

Alternative splicing (AS) is a tightly regulated mechanism that generates the complex human proteome from a small number of genes. Cis-regulatory RNA motifs in exons and introns control AS, recruiting positive and negative trans-acting splicing regulators. At a higher level, chromatin affects splicing events. Growing evidence indicates that the popular histone code hypothesis can be extended to RNA-level processes, such as AS. In addition to nucleosome positioning, which can generate transcriptional barriers to shape the final splicing outcome, histone post-translational modifications can contribute to the detailed regulation of single exon inclusion/exclusion. A histone-based system can identify alternatively spliced chromatin stretches, affecting RNAPII elongation locally or recruiting splicing components via adaptor complexes. In tumor cells, several mechanisms trigger misregulated AS events and produce cancer-associated transcripts. On a genome-wide level, aberrant AS can be the consequence of dysfunctional epigenetic splicing code, including altered enrichment in histone post-translational modifications. This review describes the main findings related to the effect of histone modifications and variants on splicing outcome and how a dysfunctional epigenetic splicing code triggers aberrant AS in cancer. In addition, it highlights recent advances in programmable DNA-targeting technologies and their possible application for AS targeted epigenetic modulation.

SRSF1 governs progenitor-specific alternative splicing to maintain adult epithelial tissue homeostasis and renewal

Alternative splicing generates distinct mRNA variants and is essential for development, homeostasis, and renewal. Proteins of the serine/arginine (SR)-rich splicing factor family are major splicing regulators that are broadly required for organ development as well as cell and organism viability. However, how these proteins support adult organ function remains largely unknown. Here, we used the continuously growing mouse incisor as a model to dissect the functions of the prototypical SR family protein SRSF1 during tissue homeostasis and renewal. We identified an SRSF1-governed alternative splicing network that is specifically required for dental proliferation and survival of progenitors but dispensable for the viability of differentiated cells. We also observed a similar progenitor-specific role of SRSF1 in the small intestinal epithelium, indicating a conserved function of SRSF1 across adult epithelial tissues. Thus, our findings define a regulatory mechanism by which SRSF1 specifically controls progenitor-specific alternative splicing events to support adult tissue homeostasis and renewal.

Histone marks regulate the epithelial-to-mesenchymal transition via alternative splicing

Histone modifications impact final splicing decisions. However, there is little evidence of the driving role of these marks in inducing cell-specific splicing changes. Using CRISPR epigenome editing tools, we show in an epithelial-to-mesenchymal cell reprogramming system (epithelial-to-mesenchymal transition [EMT]) that a single change in H3K27ac or H3K27me3 levels right at the alternatively spliced exon is necessary and sufficient to induce a splicing change capable of recapitulating important aspects of EMT, such as cell motility and invasiveness. This histone-mark-dependent splicing effect is highly dynamic and mediated by direct recruitment of the splicing regulator PTB to its RNA binding sites. These results support a role for H3K27 marks in inducing a change in the cell's phenotype via regulation of alternative splicing. We propose the dynamic nature of chromatin as a rapid and reversible mechanism to coordinate the splicing response to cell-extrinsic cues, such as induction of EMT.

Using Chou's 5-steps rule to identify N6-methyladenine sites by ensemble learning combined with multiple feature extraction methods

N⁶-methyladenine (m6A), a type of modification mostly affecting the downstream biological functions and determining the levels of gene expression, is mediated by the methylation of adenine in nucleic acids. It is also a key factor for influencing biological processes and has attracted attention as a target for treating diseases. Here, an ensemble predictor named as TL-Methy, was developed to identify m6A sites across the genome. TL-Methy is a 2-level machine learning method developed by combining the support vector machine model and multiple features extraction methods, including nucleic acid composition, di-nucleotide composition, tri-nucleotide composition, position-specific trinucleotide propensity, Bi-profile Bayes, binary encoding, and accumulated nucleotide frequency. For Homo sapiens, TL-Methy method reached the accuracy of 91.68% on jackknife test and of 92.23% on 10-fold cross validation test; For Mus musculus, TL-Methy method achieved the accuracy of 93.66% on jackknife test and of 97.07% on 10-fold cross validation test; For Saccharomyces cerevisiae, TL-Methy method obtained the accuracy of 81.57% on jackknife test and of 82.54% on 10-fold cross validation test; For rice genome, TL-Methy method achieved the accuracy of 91.87% on jackknife test and of 93.04% on 10-fold cross validation test. The results via these two test approaches demonstrated the robustness and practicality of our TL-Methy model. The TL-Methy model may be as a potential method for m6A site identification.Communicated by Ramaswamy H. Sarma.

YBX1 Promotes the Inclusion of RUNX2 Alternative Exon 5 in Dental Pulp Stem Cells

Background and Objectives

RUNX2 plays an essential role during the odontoblast differentiation of dental pulp stem cells (DPSCs). RUNX2 Exon 5 is an alternative exon and essential for RUNX2 transcriptional activity. This study aimed to investigate the regulatory mechanisms of RUNX2 exon 5 alternative splicing in human DPSCs.

Methods and Results

The regulatory motifs of RUNX2 exon 5 were analyzed using the online SpliceAid program. The alternative splicing of RUNX2 exon 5 in DPSCs during mineralization-induced differentiation was analyzed by RT-PCR. To explore the effect of splicing factor YBX1 on exon 5 alternative splicing, gaining or losing function of YBX1 was performed by transfection of YBX1 overexpression plasmid or anti-YBX1 siRNA in DPSCs. Human RUNX2 exon 5 is evolutionarily conserved and alternatively spliced in DPSCs. There are three potential YBX1 binding motifs in RUNX2 exon 5. The inclusion of RUNX2 exon 5 and YBX1 expression level increased significantly during mineralization- induced differentiation in DPSCs. Overexpression of YBX1 significantly increased the inclusion of RUNX2 exon 5 in DPSCs. In contrast, silence of YBX1 significantly reduced the inclusion of exon 5 and the corresponding RUNX2 protein expression level. Knockdown of YBX1 reduced the expression of alkaline phosphatase (ALP) and osteocalcin (OC) and the mineralization ability of DPSCs, while overexpression of YBX1 increased the expression of ALP and OC and the mineralization ability of DPSCs.

Conclusions

Human RUNX2 exon 5 is conserved evolutionarily and alternatively spliced in DPSCs. Splicing factor YBX1 promotes the inclusion of RUNX2 exon 5 and improves the mineralization ability of DPSCs.

Comparison of promoter, DNA vector, and cationic carrier for efficient transfection of hMSCs from multiple donors and tissue sources

Human mesenchymal stem cells (hMSCs) are primary cells with high clinical relevance that could be enhanced through genetic modification. However, gene delivery, particularly through nonviral routes, is inefficient. To address the shortcomings of nonviral gene delivery to hMSCs, our lab has previously demonstrated that pharmacological "priming" of hMSCs with clinically approved drugs can increase transfection in hMSCs by modulating transfection-induced cytotoxicity. However, even with priming, hMSC transfection remains inefficient for clinical applications. This work takes a complementary approach to addressing the challenges of transfecting hMSCs by systematically investigating key transfection parameters for their effect on transgene expression. Specifically, we investigated two promoters (cytomegalovirus [CMV] and elongation factor 1 alpha), four DNA vectors (plasmid, plasmid with no F1 origin, minicircle, and mini-intronic plasmid), two cationic carriers (Lipofectamine 3000 and Turbofect), and four donors of hMSCs from two tissues (adipose and bone marrow) for efficient hMSC transfection. Following systematic comparison of each variable, we identified adipose-derived hMSCs transfected with mini-intronic plasmids containing the CMV promoter delivered using Lipofectamine 3000 as the parameters that produced the highest transfection levels. The data presented in this work can guide the development of other hMSC transfection systems with the goal of producing clinically relevant, genetically modified hMSCs.

Genomic Mapping of Splicing-Related Genes Identify Amplifications in LSM1, CLNS1A, and ILF2 in Luminal Breast Cancer

Simple Summary

The alternative splicing (AS) process is highly relevant, affecting most of the hallmarks of cancer, such as proliferation, angiogenesis, and metastasis. Our study evaluated alterations in 304 splicing-related genes and their prognosis value in breast cancer patients. Amplifications in CLNS1A, LSM1, and ILF2 genes in luminal patients were significantly associated with poor outcome. Downregulation of these genes in luminal cell lines showed an antiproliferative effect. Pharmacological modulation of transcription and RNA regulation is key for the optimal development of therapeutic strategies against key proteins. Administration of a BET inhibitor and BET-PROTAC reduced the expression of these identified genes and displayed a significant antiproliferative effect on these cell models. In conclusion, we describe novel splicing genes amplified in luminal breast tumors that are associated with detrimental prognosis and can be modulated pharmacologically. It opens the door for further studies confirming the effect of these genes in patients treated with BET inhibitors.

Abstract

Alternative splicing is an essential biological process, which increases the diversity and complexity of the human transcriptome. In our study, 304 splicing pathway-related genes were evaluated in tumors from breast cancer patients (TCGA dataset). A high number of alterations were detected, including mutations and copy number alterations (CNAs), although mutations were less frequently present compared with CNAs. In the four molecular subtypes, 14 common splice genes showed high level amplification in >5% of patients. Certain genes were only amplified in specific breast cancer subtypes. Most altered genes in each molecular subtype clustered to a few chromosomal regions. In the Luminal subtype, amplifications of LSM1, CLNS1A, and ILF2 showed a strong significant association with prognosis. An even more robust association with OS and RFS was observed when expression of these three genes was combined. Inhibition of LSM1, CLNS1A, and ILF2, using siRNA in MCF7 and T47D cells, showed a decrease in cell proliferation. The mRNA expression of these genes was reduced by treatment with BET inhibitors, a family of epigenetic modulators. We map the presence of splicing-related genes in breast cancer, describing three novel genes, LSM1, CLNS1A, and ILF2, that have an oncogenic role and can be modulated with BET inhibitors.

Maturation State-Specific Alternative Splicing in FLT3-ITD and NPM1 Mutated AML

Simple Summary

In hematological malignancies, genome-wide sequencing studies found the process of splicing to be surprisingly frequently disrupted. While recent studies characterized altered splicing in relation to splicing factor mutations in AML, this study explored differential splicing profiles associated with two most common aberrations in AML: FLT3-ITD and NPM1 mutations. We identified the differential splicing of FAB-type specific gene sets in FLT3-ITD+/NPM1+ specimens as compared to FLT3-ITD−/NPM1− samples. The primary functions perturbed by differential splicing in all three FAB types included cell cycle control and DNA damage response. Interestingly, differential expression mainly affected genes involved in hematopoietic differentiation. Our findings increase our understanding of how genetic mutations translate to phenotypic features of AML cells to further improve response predictions and to find innovative therapeutic approaches. Altogether, to the best of our knowledge, this is the first study to report differential splicing profiles associated with FLT3-ITD with a concomitant NPM1 mutation in AML.

Abstract

Despite substantial progress achieved in unraveling the genetics of AML in the past decade, its treatment outcome has not substantially improved. Therefore, it is important to better understand how genetic mutations translate to phenotypic features of AML cells to further improve response predictions and to find innovative therapeutic approaches. In this respect, aberrant splicing is a crucial contributor to the pathogenesis of hematological malignancies. Thus far, altered splicing is well characterized in relation to splicing factor mutations in AML. However, splicing profiles associated with mutations in other genes remain largely unexplored. In this study, we explored differential splicing profiles associated with two of the most common aberrations in AML: FLT3-ITD and NPM1 mutations. Using RNA-sequencing data of a total of 382 primary AML samples, we found that the co-occurrence of FLT3-ITD and mutated NPM1 is associated with differential splicing of FAB-type specific gene sets. Despite the FAB-type specificity of particular gene sets, the primary functions perturbed by differential splicing in all three FAB types include cell cycle control and DNA damage response. Interestingly, we observed functional divergence between alternatively spliced and differentially expressed genes in FLT3-ITD+/NPM1+ samples in all analyzed FAB types, with differential expression affecting genes involved in hematopoietic differentiation. Altogether, these observations indicate that concomitant FLT3-ITD and mutated NPM1 are associated with the maturation state-specific differential splicing of genes with potential oncogenic relevance.

Comprehensive analysis of epigenetic signatures of human transcription control

Advances in sequencing technologies have enabled exploration of epigenetic and transcriptional profiles at a genome-wide level. The epigenetic and transcriptional landscapes are now available in hundreds of mammalian cell and tissue contexts. Many studies have performed multi-omics analyses using these datasets to enhance our understanding of relationships between epigenetic modifications and transcription regulation. Nevertheless, most studies so far have focused on the promoters/enhancers and transcription start sites, and other features of transcription control including exons, introns and transcription termination remain underexplored. We investigated the interplay between epigenetic modifications and diverse transcription features using the data generated by the Roadmap Epigenomics project. A comprehensive analysis of histone modifications, DNA methylation, and RNA-seq data of thirty-three human cell lines and tissue types allowed us to confirm the generality of previously described relationships, as well as to generate new hypotheses about the interplay between epigenetic modifications and transcription features. Importantly, our analysis included previously under-explored features of transcription control, namely, transcription termination sites, exon-intron boundaries, and the exon inclusion ratio. We have made the analyses freely available to the scientific community at joshiapps.cbu.uib.no/perepigenomics_app/ for easy exploration, validation and hypothesis generation.

PBX1 expression in uterine natural killer cells drives fetal growth

Abundant decidual natural killer (dNK) cells at the maternal-fetal interface are important during early pregnancy. However, functional subsets of dNK cells remain poorly understood. We describe a CD49a⁺PBX homeobox 1 (PBX1)⁺ dNK cell subset that promotes fetal development in humans and mice. The expression of PBX1 in dNK cells is up-regulated via the activated AKT1 pathway through the interaction of major histocompatibility complex G with the immunoglobulin-like transcript 2 receptor. PBX1 drives pleiotrophin and osteoglycin transcription in dNK cells, further promoting fetal development. Decreased PBX1 expression or the PBX1^G21S mutant correlated with fetal growth restriction and pregnancy failure in patients with unexplained recurrent spontaneous abortion (URSA). Inactivation of Pbx1 in mouse dNK cells impairs fetal development by decreasing growth-promoting factors from CD49a⁺PBX1⁺ dNK cells. Impairment of PBX1 in dNK cells has positive correlation with URSA pathogenesis and may provide a potential marker for this condition.

Alternate Roles of Sox Transcription Factors beyond Transcription Initiation

Sox proteins are known as crucial transcription factors for many developmental processes and for a wide range of common diseases. They were believed to specifically bind and bend DNA with other transcription factors and elicit transcriptional activation or repression activities in the early stage of transcription. However, their functions are not limited to transcription initiation. It has been showed that Sox proteins are involved in the regulation of alternative splicing regulatory networks and translational control. In this review, we discuss the current knowledge on how Sox transcription factors such as Sox2, Sry, Sox6, and Sox9 allow the coordination of co-transcriptional splicing and also the mechanism of SOX4-mediated translational control in the context of RNA polymerase III.

Characterization of Alternative Splicing (AS) Events during Chicken (Gallus gallus) Male Germ-Line Stem Cell Differentiation with Single-Cell RNA-seq

Simple Summary

Studies have shown that alternative splicing (AS) has been utilized in a wide variety of life processes. However, there are very few studies on AS during germ cell development. In this study, we preliminarily investigated the variation of variable shear events during the formation of chicken germ cells through the RNA-seq data analysis of embryonic stem cells (ESCs), gonad PGCs (gPGCs), and spermatogonia stem cells (SSCs), and the critical AS mode for several crucial stage-specific genes, which were identified during germ cell development. The results of this study lay a theoretical foundation for further analysis of the regulation mechanism of key genes involved in germ cell formation.

Abstract

Alternative splicing (AS) is a ubiquitous, co-transcriptional, and post-transcriptional regulation mechanism during certain developmental processes, such as germ cell differentiation. A thorough understanding of germ cell differentiation will help us to open new avenues for avian reproduction, stem cell biology, and advances in medicines for human consumption. Here, based on single-cell RNA-seq, we characterized genome-wide AS events in manifold chicken male germ cells: embryonic stem cells (ESCs), gonad primordial germ cells (gPGCs), and spermatogonia stem cells (SSCs). A total of 38,494 AS events from 15,338 genes were detected in ESCs, with a total of 48,955 events from 14,783 genes and 49,900 events from 15,089 genes observed in gPGCs and SSCs, respectively. Moreover, this distribution of AS events suggests the diverse splicing feature of ESCs, gPGCs, and SSCs. Finally, several crucial stage-specific genes, such as NANOG, POU5F3, LIN28B, BMP4, STRA8, and LHX9, were identified in AS events that were transmitted in ESCs, gPGCs, and SSCs. The gene expression results of the RNA-seq data were validated by qRT-PCR. In summary, we provided a comprehensive atlas of the genome-wide scale of the AS event landscape in male chicken germ-line cells and presented its distribution for the first time. This research may someday improve treatment options for men suffering from male infertility.

Natural Antisense Transcript PEBP1P3 Regulates the RNA Expression, DNA Methylation and Histone Modification of CD45 Gene

The leukocyte common antigen CD45 is a transmembrane phosphatase expressed on all nucleated hemopoietic cells, and the expression levels of its splicing isoforms are closely related to the development and function of lymphocytes. PEBP1P3 is a natural antisense transcript from the opposite strand of CD45 intron 2 and is predicted to be a noncoding RNA. The genotype-tissue expression and quantitative PCR data suggested that PEBP1P3 might be involved in the regulation of expression of CD45 splicing isoforms. To explore the regulatory mechanism of PEBP1P3 in CD45 expression, DNA methylation and histone modification were detected by bisulfate sequencing PCR and chromatin immunoprecipitation assays, respectively. The results showed that after the antisense RNA PEBP1P3 was knocked down by RNA interference, the DNA methylation of CD45 intron 2 was decreased and histone H3K9 and H3K36 trimethylation at the alternative splicing exons of CD45 DNA was increased. Knockdown of PEBP1P3 also increased the binding levels of chromatin conformation organizer CTCF at intron 2 and the alternative splicing exons of CD45. The present results indicate that the natural antisense RNA PEBP1P3 regulated the alternative splicing of CD45 RNA, and that might be correlated with the regulation of histone modification and DNA methylation.

Changes in the phosphorylation of nucleotide metabolism‑associated proteins by leukemia inhibitory factor in mouse embryonic stem cells

Leukemia inhibitory factor (LIF) is a stem cell growth factor that maintains self‑renewal of mouse embryonic stem cells (mESCs). LIF is a cytokine in the interleukin‑6 family and signals via the common receptor subunit gp130 and ligand‑specific LIF receptor. LIF causes heterodimerization of the LIF receptor and gp130, activating the Janus kinase/STAT and MAPK pathways, resulting in changes in protein phosphorylation. The present study profiled LIF‑mediated protein phosphorylation changes in mESCs via proteomic analysis. mESCs treated in the presence or absence of LIF were analyzed via two‑dimensional differential in‑gel electrophoresis and protein and phosphoprotein staining. Protein identification was performed by matrix‑assisted laser desorption/ionization‑time of flight mass spectrophotometry. Increased phosphorylation of 16 proteins and decreased phosphorylation of 34 proteins in response to LIF treatment was detected. Gene Ontology terms enriched in these proteins included 'organonitrogen compound metabolic process', 'regulation of mRNA splicing via spliceosome' and 'nucleotide metabolic process'. The present results revealed that LIF modulated phosphorylation levels of nucleotide metabolism‑associated proteins, thus providing insight into the mechanism underlying LIF action in mESCs.

The multifaceted role of PARP1 in RNA biogenesis

Poly(ADP-ribose) polymerases (PARPs) are abundant nuclear proteins that synthesize ADP ribose polymers (pADPr) and catalyze the addition of (p)ADPr to target biomolecules. PARP1, the most abundant and well-studied PARP, is a multifunctional enzyme that participates in numerous critical cellular processes. A considerable amount of PARP research has focused on PARP1's role in DNA damage. However, an increasing body of evidence outlines more routine roles for PARP and PARylation in nearly every step of RNA biogenesis and metabolism. PARP1's involvement in these RNA processes is pleiotropic and has been ascribed to PARP1's unique flexible domain structures. PARP1 domains are modular self-arranged enabling it to recognize structurally diverse substrates and to act simultaneously through multiple discrete mechanisms. These mechanisms include direct PARP1-protein binding, PARP1-nucleic acid binding, covalent PARylation of target molecules, covalent autoPARylation, and induction of noncovalent interactions with PAR molecules. A combination of these mechanisms has been implicated in PARP1's context-specific regulation of RNA biogenesis and metabolism. We examine the mechanisms of PARP1 regulation in transcription initiation, elongation and termination, co-transcriptional splicing, RNA export, and post-transcriptional RNA processing. Finally, we consider promising new investigative avenues for PARP1 involvement in these processes with an emphasis on PARP1 regulation of subcellular condensates. This article is categorized under: RNA Processing > Splicing Regulation/Alternative Splicing.

hnRNPLL controls pluripotency exit of embryonic stem cells by modulating alternative splicing of Tbx3 and Bptf

The regulatory circuitry underlying embryonic stem (ES) cell self-renewal is well defined, but how this circuitry is disintegrated to enable lineage specification is unclear. RNA-binding proteins (RBPs) have essential roles in RNA-mediated gene regulation, and preliminary data suggest that they might regulate ES cell fate. By combining bioinformatic analyses with functional screening, we identified seven RBPs played important roles for the exit from pluripotency of ES cells. We characterized hnRNPLL, which mainly functions as a global regulator of alternative splicing in ES cells. Specifically, hnRNPLL promotes multiple ES cell-preferred exon skipping events during the onset of ES cell differentiation. hnRNPLL depletion thus leads to sustained expression of ES cell-preferred isoforms, resulting in a differentiation deficiency that causes developmental defects and growth impairment in hnRNPLL-KO mice. In particular, hnRNPLL-mediated alternative splicing of two transcription factors, Bptf and Tbx3, is important for pluripotency exit. These data uncover the critical role of RBPs in pluripotency exit and suggest the application of targeting RBPs in controlling ES cell fate.

Splicing-associated chromatin signatures: a combinatorial and position-dependent role for histone marks in splicing definition

Alternative splicing relies on the combinatorial recruitment of splicing regulators to specific RNA binding sites. Chromatin has been shown to impact this recruitment. However, a limited number of histone marks have been studied at a global level. In this work, a machine learning approach, applied to extensive epigenomics datasets in human H1 embryonic stem cells and IMR90 foetal fibroblasts, has identified eleven chromatin modifications that differentially mark alternatively spliced exons depending on the level of exon inclusion. These marks act in a combinatorial and position-dependent way, creating characteristic splicing-associated chromatin signatures (SACS). In support of a functional role for SACS in coordinating splicing regulation, changes in the alternative splicing of SACS-marked exons between ten different cell lines correlate with changes in SACS enrichment levels and recruitment of the splicing regulators predicted by RNA motif search analysis. We propose the dynamic nature of chromatin modifications as a mechanism to rapidly fine-tune alternative splicing when necessary.

Chromatin is known to regulate splicing by modulating recruitment of splicing factors. Using machine learning approaches, the authors have underlined a chromatin code for alternative splicing regulation that is conserved amongst cell lines.

SubLocEP: a novel ensemble predictor of subcellular localization of eukaryotic mRNA based on machine learning

MOTIVATION

mRNA location corresponds to the location of protein translation and contributes to precise spatial and temporal management of the protein function. However, current assignment of subcellular localization of eukaryotic mRNA reveals important limitations: (1) turning multiple classifications into multiple dichotomies makes the training process tedious; (2) the majority of the models trained by classical algorithm are based on the extraction of single sequence information; (3) the existing state-of-the-art models have not reached an ideal level in terms of prediction and generalization ability. To achieve better assignment of subcellular localization of eukaryotic mRNA, a better and more comprehensive model must be developed.

RESULTS

In this paper, SubLocEP is proposed as a two-layer integrated prediction model for accurate prediction of the location of sequence samples. Unlike the existing models based on limited features, SubLocEP comprehensively considers additional feature attributes and is combined with LightGBM to generated single feature classifiers. The initial integration model (single-layer model) is generated according to the categories of a feature. Subsequently, two single-layer integration models are weighted (sequence-based: physicochemical properties = 3:2) to produce the final two-layer model. The performance of SubLocEP on independent datasets is sufficient to indicate that SubLocEP is an accurate and stable prediction model with strong generalization ability. Additionally, an online tool has been developed that contains experimental data and can maximize the user convenience for estimation of subcellular localization of eukaryotic mRNA.

A Method for Identifying Vesicle Transport Proteins Based on LibSVM and MRMD

With the development of computer technology, many machine learning algorithms have been applied to the field of biology, forming the discipline of bioinformatics. Protein function prediction is a classic research topic in this subject area. Though many scholars have made achievements in identifying protein by different algorithms, they often extract a large number of feature types and use very complex classification methods to obtain little improvement in the classification effect, and this process is very time-consuming. In this research, we attempt to utilize as few features as possible to classify vesicular transportation proteins and to simultaneously obtain a comparative satisfactory classification result. We adopt CTDC which is a submethod of the method of composition, transition, and distribution (CTD) to extract only 39 features from each sequence, and LibSVM is used as the classification method. We use the SMOTE method to deal with the problem of dataset imbalance. There are 11619 protein sequences in our dataset. We selected 4428 sequences to train our classification model and selected other 1832 sequences from our dataset to test the classification effect and finally achieved an accuracy of 71.77%. After dimension reduction by MRMD, the accuracy is 72.16%.

Splicing to Keep Cycling: The Importance of Pre-mRNA Splicing during the Cell Cycle

Pre-mRNA splicing is a fundamental process in mammalian gene expression, and alternative splicing plays an extensive role in generating protein diversity. Because the majority of genes undergo pre-mRNA splicing, most cellular processes depend on proper spliceosome function. We focus on the cell cycle and describe its dependence on pre-mRNA splicing and accurate alternative splicing. We outline the key cell-cycle factors and their known alternative splicing isoforms. We discuss different levels of pre-mRNA splicing regulation such as post-translational modifications and changes in the expression of splicing factors. We describe the effect of chromatin dynamics on pre-mRNA splicing during the cell cycle. In addition, we focus on spliceosome component SF3B1, which is mutated in many types of cancer, and describe the link between SF3B1 and its inhibitors and the cell cycle.

Identification of Candidate Biomarkers for Salt Sensitivity of Blood Pressure by Integrated Bioinformatics Analysis

In the current study, we aimed to identify potential biomarkers for salt sensitivity of blood pressure (SSBP), which may provide a novel insight into the pathogenic mechanisms of salt-sensitive hypertension. Firstly, we conducted weighted gene coexpression network analysis (WGCNA) and selected a gene module and 60 hub genes significantly correlated to SSBP. Then, GO function and KEGG signaling pathway enrichment analysis and protein-protein interaction (PPI) network analysis were performed. Furthermore, we identified a five-gene signature with high connectivity degree in the PPI network and high AUC of ROC curves, which may have high diagnosis value for SSBP. Moreover, through combining two gene screening methods, we identified 23 differentially expressed circRNAs and selected the top 5% circRNAs (1 circRNA) with the highest connectivity degree in the coexpression network as hub circRNA highly associated with SSBP. Finally, we carried out RT-qPCR to validate the expression of five hub genes, and our results showed that the expression of HECTD1 (P = 0.017), SRSF5 (P = 0.003), SRSF1 (P = 0.006), HERC2 (P = 0.004), and TNPO1 (P = 0.002) was significantly upregulated in the renal tissue in salt-sensitive rats compared to salt-resistant rats, indicating that these five hub genes can serve as potential biomarkers for SSBP.

Prediction of Anticancer Peptides Using a Low-Dimensional Feature Model

Cancer is still a severe health problem globally. The therapy of cancer traditionally involves the use of radiotherapy or anticancer drugs to kill cancer cells, but these methods are quite expensive and have side effects, which will cause great harm to patients. With the find of anticancer peptides (ACPs), significant progress has been achieved in the therapy of tumors. Therefore, it is invaluable to accurately identify anticancer peptides. Although biochemical experiments can solve this work, this method is expensive and time-consuming. To promote the application of anticancer peptides in cancer therapy, machine learning can be used to recognize anticancer peptides by extracting the feature vectors of anticancer peptides. Nevertheless, poor performance usually be found in training the machine learning model to utilizing high-dimensional features in practice. In order to solve the above job, this paper put forward a 19-dimensional feature model based on anticancer peptide sequences, which has lower dimensionality and better performance than some existing methods. In addition, this paper also separated a model with a low number of dimensions and acceptable performance. The few features identified in this study may represent the important features of anticancer peptides.

ICGEC: a comparative method for measuring epigenetic conservation of genes via the integrated signal from multiple histone modifications between cell types

Background

Histone post-translational modifications play crucial roles in epigenetic regulation of gene expression and are known to be associated with the phenotypic differences of different cell types. Therefore, it is of fundamental importance to dissect the genes and pathways involved in such a phenotypic variation at the level of epigenetics. However, the existing comparative approaches are largely based on the differences, especially the absolute difference in the levels of individual histone modifications of genes under contrasting conditions. Thus, a method for measuring the overall change in the epigenetic circumstance of each gene underpinned by multiple types of histone modifications between cell types is lacking.

Results

To address this challenge, we developed ICGEC, a new method for estimating the degree of epigenetic conservation of genes between two cell lines. Different from existing comparative methods, ICGEC provides a reliable score for measuring the relative change in the epigenetic context of corresponding gene between two conditions and simultaneously produces a score for each histone mark. The application of ICGEC to the human embryonic stem cell line H1 and four H1-derived cell lines with available epigenomic data for the same 16 types of histone modifications indicated high robustness and reliability of ICGEC. Furthermore, the analysis of the epigenetically dynamic and conserved genes which were defined based on the ICGEC output results demonstrated that ICGEC can deepen our understanding of the biological processes of cell differentiation to overcome the limitations of traditional expression analysis. Specifically, the ICGEC-derived differentiation-direction-specific genes were shown to have putative functions that are well-matched with cell identity. Additionally, H3K79me1 and H3K27ac were found to be the main histone marks accounting for whether an epigenetically dynamic gene was differentially expressed between two cell lines.

Conclusions

The use of ICGEC creates a convenient and robust way to measure the overall epigenetic conservation of individual genes and marks between two conditions. Thus, it provides a basis for exploring the epigenotype-phenotype relationship. ICGEC can be deemed a state-of-the-art method tailored for comparative epigenomic analysis of changes in cell dynamics.

Histone methyltransferase SETD2: a potential tumor suppressor in solid cancers

Epigenetic regulation plays an important role in the occurrence, development and treatment of malignant tumors; and a great deal of attention has been paid to the histone methylation level in recent years. As a 230-kD epigenetic regulator, the histone H3 lysine 36 histone (H3K36) methyltransferase SETD2 is a key enzyme of the nuclear receptor SET domain-containing (NSD) family, which is associated with a specific hyperphosphorylated domain, a large subunit of RNA polymerase II (RNAPII), named RNAPII subunit B1 (RPB1), and SETD2 which methylates the ly-36 position of dimethylated histone H3 (H3K36me2) to generate trimethylated H3K36 (H3K36me3). SETD2 is involved in various cellular processes, including transcriptional regulation, DNA damage repair, non-histone protein-related functions and some other processes. Great efforts of high-throughput sequencing have revealed that SETD2 is mutated or its function is lost in a range of solid cancers, including renal cancer, gastrointestinal cancer, lung cancer, pancreatic cancer, osteosarcoma, and so on. Mutation, or functional loss, of the SETD2 gene produces dysfunction in corresponding tumor tissue proteins, leading to tumorigenesis, progression, chemotherapy resistance, and unfavorable prognosis, suggesting that SETD2 possibly acts as a tumor suppressor. However, its underlying mechanism remains largely unexplored. In the present study, we summarized the latest advances of effects of SETD2 expression at the mRNA and protein levels in solid cancers, and its potential molecular and cellular functions as well as clinical applications were also reviewed.

6mA-RicePred: A Method for Identifying DNA N 6-Methyladenine Sites in the Rice Genome Based on Feature Fusion

MOTIVATION

The biological function of N 6-methyladenine DNA (6mA) in plants is largely unknown. Rice is one of the most important crops worldwide and is a model species for molecular and genetic studies. There are few methods for 6mA site recognition in the rice genome, and an effective computational method is needed.

RESULTS

In this paper, we propose a new computational method called 6mA-Pred to identify 6mA sites in the rice genome. 6mA-Pred employs a feature fusion method to combine advantageous features from other methods and thus obtain a new feature to identify 6mA sites. This method achieved an accuracy of 87.27% in the identification of 6mA sites with 10-fold cross-validation and achieved an accuracy of 85.6% in independent test sets.

PRP8A and PRP8B spliceosome subunits act co-ordinately to control pollen tube attraction in Arabidopsis

Precise guided pollen tube growth by the female gametophyte is a pre-requisite for successful sexual reproduction in flowering plants. Cysteine-rich proteins (CRPs) secreted from the embryo sac are known pollen tube attractants perceived by pollen tube receptor-like kinases (RLK's). How pre-mRNA splicing facilitates this cell-to-cell communication is not understood. Here, we report novel function of Pre-mRNA PROCESSING factor 8 paralogs, PRP8A and PRP8B, as regulators of pollen tube attraction. Double mutant prp8a prp8b ovules cannot attract pollen tubes, and prp8a prp8b pollen tubes fail in sensing ovules attraction signals. Only 3% of ovule-expressed genes were misregulated in prp8a prp8b. Combination of RNA-seq and MYB98/LURE1.2-YFP reporter revealed the expression of MYB98, LUREs and 49 other CRPs were downregulated suggesting loss of synergid cell fate. Differential Exon usage (DEU) and Intron-retention (IR) analysis revealed autoregulation of PPR8A/PRP8B splicing. In vivo, PRP8A coimmunoprecipitates with splicing enhancer AtSF3A1, suggesting involvement of PRP8A in 3′-splice site selection. Our data hint that PRP8A/PRP8B module exhibit spliceosome-autoregulation to facilitate pollen tube attraction via transcriptional regulation of MYB98, CRPs and LURE pollen tube attractants.

Machine learning and its applications in plant molecular studies

The advent of high-throughput genomic technologies has resulted in the accumulation of massive amounts of genomic information. However, biologists are challenged with how to effectively analyze these data. Machine learning can provide tools for better and more efficient data analysis. Unfortunately, because many plant biologists are unfamiliar with machine learning, its application in plant molecular studies has been restricted to a few species and a limited set of algorithms. Thus, in this study, we provide the basic steps for developing machine learning frameworks and present a comprehensive overview of machine learning algorithms and various evaluation metrics. Furthermore, we introduce sources of important curated plant genomic data and R packages to enable plant biologists to easily and quickly apply appropriate machine learning algorithms in their research. Finally, we discuss current applications of machine learning algorithms for identifying various genes related to resistance to biotic and abiotic stress. Broad application of machine learning and the accumulation of plant sequencing data will advance plant molecular studies.

An Intricate Connection between Alternative Splicing and Phenotypic Plasticity in Development and Cancer

During tumor progression, hypoxia, nutrient deprivation or changes in the extracellular environment (i.e., induced by anti-cancer drugs) elicit adaptive responses in cancer cells. Cellular plasticity increases the chance that tumor cells may survive in a challenging microenvironment, acquire new mechanisms of resistance to conventional drugs, and spread to distant sites. Re-activation of stem pathways appears as a significant cause of cellular plasticity because it promotes the acquisition of stem-like properties through a profound phenotypic reprogramming of cancer cells. In addition, it is a major contributor to tumor heterogeneity, depending on the coexistence of phenotypically distinct subpopulations in the same tumor bulk. Several cellular mechanisms may drive this fundamental change, in particular, high-throughput sequencing technologies revealed a key role for alternative splicing (AS). Effectively, AS is one of the most important pre-mRNA processes that increases the diversity of transcriptome and proteome in a tissue- and development-dependent manner. Moreover, defective AS has been associated with several human diseases. However, its role in cancer cell plasticity and tumor heterogeneity remains unclear. Therefore, unravelling the intricate relationship between AS and the maintenance of a stem-like phenotype may explain molecular mechanisms underlying cancer cell plasticity and improve cancer diagnosis and treatment.

The elongation factor Elof1 is required for mammalian gastrulation

Despite having been sequenced over a decade ago, the functional significance of much of the mammalian genome remains unknown. The mouse has become the preeminent mammalian model for identifying endogenous gene function in vivo. Here we characterize the phenotype of a loss-of function allele for the evolutionarily conserved transcription factor, Elongation Factor Homolog 1 (Elof1). Recent work utilizing the yeast homolog, Elf1, has demonstrated that Elf1 associates with the RNA polymerase II complex to promote elongation by relieving the association of the template DNA strand with bound histones. Loss of Elof1 results in developmental delay and morphological defects during early mouse development resulting in peri-gastrulation lethality. Although Elof1 is highly conserved we observe tissue specific expression during gastrulation and in adult murine tissues, suggesting there may be other genes with similar function in diverse tissues or that mElof1 has adopted lineage specific functions. To better understand its function in mammalian transcription, we examined splice variants and find that Elof1 regulates mutually exclusive exon use in vivo. Distinct from what has been demonstrated in yeast, we demonstrate that Elof1 is essential for viability during mammalian gastrulation which may be due to a role mediating tissue specific exclusive exon use, a regulatory function unique to higher eukaryotes.

More than a messenger: Alternative splicing as a therapeutic target

Alternative splicing of pre-mRNA is an essential post- and co-transcriptional mechanism of gene expression regulation that produces multiple mature mRNA transcripts from a single gene. Genetic mutations that affect splicing underlie numerous devastating diseases. The complexity of splicing regulation allows for multiple therapeutic approaches to correct disease-associated mis-splicing events. In this review, we first highlight recent findings from therapeutic strategies that have used splice switching antisense oligonucleotides and small molecules that bind directly to RNA. Second, we summarize different genetic and chemical approaches to target components of the spliceosome to correct splicing defects in pathological conditions. Finally, we present an overview of compounds that target kinases and accessory pathways that intersect with the splicing machinery. Advancements in the understanding of disease-specific defects caused by mis-regulation of alternative splicing will certainly increase the development of therapeutic options for the clinic. This article is part of a Special Issue entitled: RNA structure and splicing regulation edited by Francisco Baralle, Ravindra Singh and Stefan Stamm.

Predicting Ion Channels Genes and Their Types With Machine Learning Techniques

Motivation: The number of ion channels is increasing rapidly. As many of them are associated with diseases, they are the targets of more than 700 drugs. The discovery of new ion channels is facilitated by computational methods that predict ion channels and their types from protein sequences. Methods: We used the SVMProt and the k-skip-n-gram methods to extract the feature vectors of ion channels, and obtained 188- and 400-dimensional features, respectively. The 188- and 400-dimensional features were combined to obtain 588-dimensional features. We then employed the maximum-relevance-maximum-distance method to reduce the dimensions of the 588-dimensional features. Finally, the support vector machine and random forest methods were used to build the prediction models to evaluate the classification effect. Results: Different methods were employed to extract various feature vectors, and after effective dimensionality reduction, different classifiers were used to classify the ion channels. We extracted the ion channel data from the Universal Protein Resource (UniProt, http://www.uniprot.org/) and Ligand-Gated Ion Channel databases (http://www.ebi.ac.uk/compneur-srv/LGICdb/LGICdb.php), and then verified the performance of the classifiers after screening. The findings of this study could inform the research and development of drugs.

Gene2vec: gene subsequence embedding for prediction of mammalian N6-methyladenosine sites from mRNA

N⁶-Methyladenosine (m⁶A) refers to methylation modification of the adenosine nucleotide acid at the nitrogen-6 position. Many conventional computational methods for identifying N⁶-methyladenosine sites are limited by the small amount of data available. Taking advantage of the thousands of m⁶A sites detected by high-throughput sequencing, it is now possible to discover the characteristics of m⁶A sequences using deep learning techniques. To the best of our knowledge, our work is the first attempt to use word embedding and deep neural networks for m⁶A prediction from mRNA sequences. Using four deep neural networks, we developed a model inferred from a larger sequence shifting window that can predict m⁶A accurately and robustly. Four prediction schemes were built with various RNA sequence representations and optimized convolutional neural networks. The soft voting results from the four deep networks were shown to outperform all of the state-of-the-art methods. We evaluated these predictors mentioned above on a rigorous independent test data set and proved that our proposed method outperforms the state-of-the-art predictors. The training, independent, and cross-species testing data sets are much larger than in previous studies, which could help to avoid the problem of overfitting. Furthermore, an online prediction web server implementing the four proposed predictors has been built and is available at http://server.malab.cn/Gene2vec/.

Alternative splicing of neuronal genes: new mechanisms and new therapies

Dynamic changes in alternative splicing during the life cycle of neurons support development and plasticity, and are implicated in disease pathology. Cell-specific alternative splicing programs coordinate exon selection across networks of functionally connected genes. In this opinion piece, we highlight recent publications that identify some of the molecular mechanisms-RNA and DNA binding proteins and epigenetic modifications-which direct cell-specific exon selection during pre-mRNA splicing. Aberrant splicing patterns are signature features of a growing number of diseases of the nervous system. Recent publications demonstrate the value of delineating basic mechanisms that dictate exon choice to inform the development of new therapeutic strategies that correct or compensate for damaging deficits in alternative splicing.

Gene-Based Nonparametric Testing of Interactions Using Distance Correlation Coefficient in Case-Control Association Studies

Among the various statistical methods for identifying gene⁻gene interactions in qualitative genome-wide association studies (GWAS), gene-based methods have recently grown in popularity because they confer advantages in both statistical power and biological interpretability. However, most of these methods make strong assumptions about the form of the relationship between traits and single-nucleotide polymorphisms, which result in limited statistical power. In this paper, we propose a gene-based method based on the distance correlation coefficient called gene-based gene-gene interaction via distance correlation coefficient (GBDcor). The distance correlation (dCor) is a measurement of the dependency between two random vectors with arbitrary, and not necessarily equal, dimensions. We used the difference in dCor in case and control datasets as an indicator of gene⁻gene interaction, which was based on the assumption that the joint distribution of two genes in case subjects and in control subjects should not be significantly different if the two genes do not interact. We designed a permutation-based statistical test to evaluate the difference between dCor in cases and controls for a pair of genes, and we provided the p-value for the statistic to represent the significance of the interaction between the two genes. In experiments with both simulated and real-world data, our method outperformed previous approaches in detecting interactions accurately.

Comparative analysis and prediction of quorum-sensing peptides using feature representation learning and machine learning algorithms

Quorum-sensing peptides (QSPs) are the signal molecules that are closely associated with diverse cellular processes, such as cell-cell communication, and gene expression regulation in Gram-positive bacteria. It is therefore of great importance to identify QSPs for better understanding and in-depth revealing of their functional mechanisms in physiological processes. Machine learning algorithms have been developed for this purpose, showing the great potential for the reliable prediction of QSPs. In this study, several sequence-based feature descriptors for peptide representation and machine learning algorithms are comprehensively reviewed, evaluated and compared. To effectively use existing feature descriptors, we used a feature representation learning strategy that automatically learns the most discriminative features from existing feature descriptors in a supervised way. Our results demonstrate that this strategy is capable of effectively capturing the sequence determinants to represent the characteristics of QSPs, thereby contributing to the improved predictive performance. Furthermore, wrapping this feature representation learning strategy, we developed a powerful predictor named QSPred-FL for the detection of QSPs in large-scale proteomic data. Benchmarking results with 10-fold cross validation showed that QSPred-FL is able to achieve better performance as compared to the state-of-the-art predictors. In addition, we have established a user-friendly webserver that implements QSPred-FL, which is currently available at http://server.malab.cn/QSPred-FL. We expect that this tool will be useful for the high-throughput prediction of QSPs and the discovery of important functional mechanisms of QSPs.