Long range chromatin organization: a new layer in splicing regulation?

SEAMoD: A fully interpretable neural network for cis-regulatory analysis of differentially expressed genes

A common way to investigate gene regulatory mechanisms is to identify differentially expressed genes using transcriptomics, find their candidate enhancers using epigenomics, and search for over-represented transcription factor (TF) motifs in these enhancers using bioinformatics tools. A related follow-up task is to model gene expression as a function of enhancer sequences and rank TF motifs by their contribution to such models, thus prioritizing among regulators. We present a new computational tool called SEAMoD that performs the above tasks of motif finding and sequence-to-expression modeling simultaneously. It trains a convolutional neural network model to relate enhancer sequences to differential expression in one or more biological conditions. The model uses TF motifs to interpret the sequences, learning these motifs and their relative importance to each biological condition from data. It also utilizes epigenomic information in the form of activity scores of putative enhancers and automatically searches for the most promising enhancer for each gene. Compared to existing neural network models of non-coding sequences, SEAMoD uses far fewer parameters, requires far less training data, and emphasizes biological interpretability. We used SEAMoD to understand regulatory mechanisms underlying the differentiation of neural stem cell (NSC) derived from mouse forebrain. We profiled gene expression and histone modifications in NSC and three differentiated cell types and used SEAMoD to model differential expression of nearly 12,000 genes with an accuracy of 81%, in the process identifying the Olig2, E2f family TFs, Foxo3, and Tcf4 as key transcriptional regulators of the differentiation process.

Role of promoters in regulating alternative splicing

Alternative splicing (AS) plays a critical role in enhancing proteome complexity in higher eukaryotes. Almost all the multi intron-containing genes undergo AS in humans. Splicing mainly occurs co-transcriptionally, where RNA polymerase II (RNA pol II) plays a crucial role in coordinating transcription and pre-mRNA splicing. Aberrant AS leads to non-functional proteins causative in various pathophysiological conditions such as cancers, neurodegenerative diseases, and muscular dystrophies. Transcription and pre-mRNA splicing are deeply interconnected and can influence each other's functions. Several studies evinced that specific promoters employed by RNA pol II dictate the RNA processing decisions. Promoter-specific recruitment of certain transcriptional factors or transcriptional coactivators influences splicing, and the extent to which these factors affect splicing has not been discussed in detail. Here, in this review, various DNA-binding proteins and their influence on promoter-specific AS are extensively discussed. Besides, this review highlights how the promoter-specific epigenetic changes might regulate AS.

Ultrasound May Suppress Tumor Growth, Inhibit Inflammation, and Establish Tolerogenesis by Remodeling Innatome via Pathways of ROS, Immune Checkpoints, Cytokines, and Trained Immunity/Tolerance

BACKGROUND

The immune mechanisms underlying low-intensity ultrasound- (LIUS-) mediated suppression of inflammation and tumorigenesis remain poorly determined.

METHODS

We used microarray datasets from the NCBI GEO DataSet repository and conducted comprehensive data-mining analyses, where we examined the gene expression of 1376 innate immune regulators (innatome genes (IGs) in cells treated with LIUS.

RESULTS

We made the following findings: (1) LIUS upregulates proinflammatory IGs and downregulates metastasis genes in cancer cells, and LIUS upregulates adaptive immunity pathways but inhibits danger-sensing and inflammation pathways and promote tolerogenic differentiation in bone marrow (BM) cells. (2) LIUS upregulates IGs encoded for proteins localized in the cytoplasm, extracellular space, and others, but downregulates IG proteins localized in nuclear and plasma membranes, and LIUS downregulates phosphatases. (3) LIUS-modulated IGs act partially via several important pathways of reactive oxygen species (ROS), reverse signaling of immune checkpoint receptors B7-H4 and BTNL2, inflammatory cytokines, and static or oscillatory shear stress and heat generation, among which ROS is a dominant mechanism. (4) LIUS upregulates trained immunity enzymes in lymphoma cells and downregulates trained immunity enzymes and presumably establishes trained tolerance in BM cells. (5) LIUS modulates chromatin long-range interactions to differentially regulate IGs expression in cancer cells and noncancer cells.

CONCLUSIONS

Our analysis suggests novel molecular mechanisms that are utilized by LIUS to induce tumor suppression and inflammation inhibition. Our findings may lead to development of new treatment protocols for cancers and chronic inflammation.

Experimental Data-Mining Analyses Reveal New Roles of Low-Intensity Ultrasound in Differentiating Cell Death Regulatome in Cancer and Non-cancer Cells via Potential Modulation of Chromatin Long-Range Interactions

Background: The mechanisms underlying low intensity ultrasound (LIUS) mediated suppression of inflammation and tumorigenesis remain poorly determined. Methods: We used microarray datasets from NCBI GEO Dataset databases and conducted a comprehensive data mining analyses, where we studied the gene expression of 299 cell death regulators that regulate 13 different cell death types (cell death regulatome) in cells treated with LIUS. Results: We made the following findings: (1) LIUS exerts a profound effect on the expression of cell death regulatome in cancer cells and non-cancer cells. Of note, LIUS has the tendency to downregulate the gene expression of cell death regulators in non-cancer cells. Most of the cell death regulator genes downregulated by LIUS in non-cancer cells are responsible for mediating inflammatory signaling pathways; (2) LIUS activates different cell death transcription factors in cancer and non-cancer cells. Transcription factors TP-53 and SRF- were induced by LIUS exposure in cancer cells and non-cancer cells, respectively; (3) As two well-accepted mechanisms of LIUS, mild hyperthermia and oscillatory shear stress induce changes in the expression of cell death regulators, therefore, may be responsible for inducing LIUS mediated changes in gene expression patterns of cell death regulators in cells; (4) LIUS exposure may change the redox status of the cells. LIUS may induce more of antioxidant effects in non-cancer cells compared to cancer cells; and (5) The genes modulated by LIUS in cancer cells have distinct chromatin long range interaction (CLRI) patterns to that of non-cancer cells. Conclusions: Our analysis suggests novel molecular mechanisms that may be utilized by LIUS to induce tumor suppression and inflammation inhibition. Our findings may lead to development of new treatment protocols for cancers and chronic inflammation.

Increased acetylation of H3K14 in the genomic regions that encode trained immunity enzymes in lysophosphatidylcholine-activated human aortic endothelial cells - Novel qualification markers for chronic disease risk factors and conditional DAMPs

To test our hypothesis that proatherogenic lysophosphatidylcholine (LPC) upregulates trained immunity pathways (TIPs) in human aortic endothelial cells (HAECs), we conducted an intensive analyses on our RNA-Seq data and histone 3 lysine 14 acetylation (H3K14ac)-CHIP-Seq data, both performed on HAEC treated with LPC. Our analysis revealed that: 1) LPC induces upregulation of three TIPs including glycolysis enzymes (GE), mevalonate enzymes (ME), and acetyl-CoA generating enzymes (ACE); 2) LPC induces upregulation of 29% of 31 histone acetyltransferases, three of which acetylate H3K14; 3) LPC induces H3K14 acetylation (H3K14ac) in the genomic DNA that encodes LPC-induced TIP genes (79%) in comparison to that of in LPC-induced effector genes (43%) including ICAM-1; 4) TIP pathways are significantly different from that of EC activation effectors including adhesion molecule ICAM-1; 5) reactive oxygen species generating enzyme NOX2 deficiency decreases, but antioxidant transcription factor Nrf2 deficiency increases, the expressions of a few TIP genes and EC activation effector genes; and 6) LPC induced TIP genes(81%) favor inter-chromosomal long-range interactions (CLRI, trans-chromatin interaction) while LPC induced effector genes (65%) favor intra-chromosomal CLRIs (cis-chromatin interaction). Our findings demonstrated that proatherogenic lipids upregulate TIPs in HAECs, which are a new category of qualification markers for chronic disease risk factors and conditional DAMPs and potential mechanisms for acute inflammation transition to chronic ones. These novel insights may lead to identifications of new cardiovascular risk factors in upregulating TIPs in cardiovascular cells and novel therapeutic targets for the treatment of metabolic cardiovascular diseases, inflammation, and cancers. (total words: 245).

Increasing Upstream Chromatin Long-Range Interactions May Favor Induction of Circular RNAs in LysoPC-Activated Human Aortic Endothelial Cells

Circular RNAs (circRNAs) are non-coding RNAs that form covalently closed continuous loops, and act as gene regulators in physiological and disease conditions. To test our hypothesis that proatherogenic lipid lysophosphatidylcholine (LPC) induce a set of circRNAs in human aortic endothelial cell (HAEC) activation, we performed circRNA analysis by searching our RNA-Seq data from LPC-activated HAECs, and found: (1) LPC induces significant modulation of 77 newly characterized cirRNAs, among which 47 circRNAs (61%) are upregulated; (2) 34 (72%) out of 47 upregulated circRNAs are upregulated when the corresponding mRNAs are downregulated, suggesting that the majority of circRNAs are upregulated presumably via LPC-induced “abnormal splicing” when the canonical splicing for generation of corresponding mRNAs is suppressed; (3) Upregulation of 47 circRNAs is temporally associated with mRNAs-mediated LPC-upregulated cholesterol synthesis-SREBP2 pathway and LPC-downregulated TGF-β pathway; (4) Increase in upstream chromatin long-range interaction sites to circRNA related genes is associated with preferred circRNA generation over canonical splicing for mRNAs, suggesting that shifting chromatin long-range interaction sites from downstream to upstream may promote induction of a list of circRNAs in lysoPC-activated HAECs; (5) Six significantly changed circRNAs may have sponge functions for miRNAs; and (6) 74% significantly changed circRNAs contain open reading frames, suggesting that putative short proteins may interfere with the protein interaction-based signaling. Our findings have demonstrated for the first time that a new set of LPC-induced circRNAs may contribute to homeostasis in LPC-induced HAEC activation. These novel insights may lead to identifications of new therapeutic targets for treating metabolic cardiovascular diseases, inflammations, and cancers.

Mechanism of Splicing Regulation of Spinal Muscular Atrophy Genes

Spinal muscular atrophy (SMA) is one of the major genetic disorders associated with infant mortality. More than 90% cases of SMA result from deletions or mutations of Survival Motor Neuron 1 (SMN1) gene. SMN2, a nearly identical copy of SMN1, does not compensate for the loss of SMN1 due to predominant skipping of exon 7. However, correction of SMN2 exon 7 splicing has proven to confer therapeutic benefits in SMA patients. The only approved drug for SMA is an antisense oligonucleotide (Spinraza™/Nusinersen), which corrects SMN2 exon 7 splicing by blocking intronic splicing silencer N1 (ISS-N1) located immediately downstream of exon 7. ISS-N1 is a complex regulatory element encompassing overlapping negative motifs and sequestering a cryptic splice site. More than 40 protein factors have been implicated in the regulation of SMN exon 7 splicing. There is evidence to support that multiple exons of SMN are alternatively spliced during oxidative stress, which is associated with a growing number of pathological conditions. Here, we provide the most up to date account of the mechanism of splicing regulation of the SMN genes.

Beyond Transcription: Roles of Transcription Factors in Pre-mRNA Splicing

Whereas individual steps of protein-coding gene expression in eukaryotes can be studied in isolation in vitro, it has become clear that these steps are intimately connected within cells. Connections not only ensure quality control but also fine-tune the gene expression process, which must adapt to environmental changes while remaining robust. In this review, we systematically present proven and potential mechanisms by which sequence-specific DNA-binding transcription factors can alter gene expression beyond transcription initiation and regulate pre-mRNA splicing, and thereby mRNA isoform production, by (i) influencing transcription elongation rates, (ii) binding to pre-mRNA to recruit splicing factors, and/or (iii) blocking the association of splicing factors with pre-mRNA. We propose various mechanistic models throughout the review, in some cases without explicit supportive evidence, in hopes of providing fertile ground for future studies.

An intronic RNA structure modulates expression of the mRNA biogenesis factor Sus1

Sus1 is a conserved protein involved in chromatin remodeling and mRNA biogenesis. Unlike most yeast genes, the SUS1 pre-mRNA of Saccharomyces cerevisiae contains two introns and is alternatively spliced, retaining one or both introns in response to changes in environmental conditions. SUS1 splicing may allow the cell to control Sus1 expression, but the mechanisms that regulate this process remain unknown. Using in silico analyses together with NMR spectroscopy, gel electrophoresis, and UV thermal denaturation experiments, we show that the downstream intron (I2) of SUS1 forms a weakly stable, 37-nucleotide stem-loop structure containing the branch site near its apical loop and the 3' splice site after the stem terminus. A cellular assay revealed that two of four mutants containing altered I2 structures had significantly impaired SUS1 expression. Semiquantitative RT-PCR experiments indicated that all mutants accumulated unspliced SUS1 pre-mRNA and/or induced distorted levels of fully spliced mRNA relative to wild type. Concomitantly, Sus1 cellular functions in histone H2B deubiquitination and mRNA export were affected in I2 hairpin mutants that inhibited splicing. This work demonstrates that I2 structure is relevant for SUS1 expression, and that this effect is likely exerted through modulation of splicing.

Let there be light: regulation of gene expression in plants

Gene expression regulation relies on a variety of molecular mechanisms affecting different steps of a messenger RNA (mRNA) life: transcription, processing, splicing, alternative splicing, transport, translation, storage and decay. Light induces massive reprogramming of gene expression in plants. Differences in alternative splicing patterns in response to environmental stimuli suggest that alternative splicing plays an important role in plant adaptation to changing life conditions. In a recent publication, our laboratories showed that light regulates alternative splicing of a subset of Arabidopsis genes encoding proteins involved in RNA processing by chloroplast retrograde signals. The light effect on alternative splicing is also observed in roots when the communication with the photosynthetic tissues is not interrupted, suggesting that a signaling molecule travels through the plant. These results point at alternative splicing regulation by retrograde signals as an important mechanism for plant adaptation to their environment.

A Quantitative Profiling Tool for Diverse Genomic Data Types Reveals Potential Associations between Chromatin and Pre-mRNA Processing

High-throughput sequencing, and genome-based datasets in general, are often represented as profiles centered at reference points to study the association of protein binding and other signals to particular regulatory mechanisms. Although these profiles often provide compelling evidence of these associations, they do not provide a quantitative assessment of the enrichment, which makes the comparison between signals and conditions difficult. In addition, a number of biases can confound profiles, but are rarely accounted for in the tools currently available. We present a novel computational method, ProfileSeq, for the quantitative assessment of biological profiles to provide an exact, nonparametric test that specific regions of the test profile have higher or lower signal densities than a control set. The method is applicable to high-throughput sequencing data (ChIP-Seq, GRO-Seq, CLIP-Seq, etc.) and to genome-based datasets (motifs, etc.). We validate ProfileSeq by recovering and providing a quantitative assessment of several results reported before in the literature using independent datasets. We show that input signal and mappability have confounding effects on the profile results, but that normalizing the signal by input reads can eliminate these biases while preserving the biological signal. Moreover, we apply ProfileSeq to ChIP-Seq data for transcription factors, as well as for motif and CLIP-Seq data for splicing factors. In all examples considered, the profiles were robust to biases in mappability of sequencing reads. Furthermore, analyses performed with ProfileSeq reveal a number of putative relationships between transcription factor binding to DNA and splicing factor binding to pre-mRNA, adding to the growing body of evidence relating chromatin and pre-mRNA processing. ProfileSeq provides a robust way to quantify genome-wide coordinate-based signal. Software and documentation are freely available for academic use at https://bitbucket.org/regulatorygenomicsupf/profileseq/.