MAGIC: A tool for predicting transcription factors and cofactors driving gene sets using ENCODE data

Ki-67 is necessary during DNA replication for fork protection and genome stability

BACKGROUND

The proliferation antigen Ki-67 has been widely used in clinical settings for cancer staging for many years, but investigations on its biological functions have lagged. Recently, Ki-67 has been shown to regulate both the composition of the chromosome periphery and chromosome behaviour in mitosis as well as to play a role in heterochromatin organisation and gene transcription. However, how the different roles for Ki-67 across the cell cycle are regulated and coordinated remain poorly understood. The progress towards understanding Ki-67 function have been limited by the tools available to deplete the protein, coupled to its abundance and fluctuation during the cell cycle.

RESULTS

Here, we use a doxycycline-inducible E3 ligase together with an auxin-inducible degron tag to achieve a rapid, acute and homogeneous degradation of Ki-67 in HCT116 cells. This system, coupled with APEX2 proteomics and phospho-proteomics approaches, allows us to show that Ki-67 plays a role during DNA replication. In its absence, DNA replication is severely delayed, the replication machinery is unloaded, causing DNA damage that is not sensed by the canonical pathways and dependent on HUWE1 ligase. This leads to defects in replication and sister chromatids cohesion, but it also triggers an interferon response mediated by the cGAS/STING pathway in all the cell lines tested.

CONCLUSIONS

We unveil a new function of Ki-67 in DNA replication and genome maintenance that is independent of its previously known role in mitosis and gene regulation.

Silencing Apoe with divalent-siRNAs improves amyloid burden and activates immune response pathways in Alzheimer's disease

INTRODUCTION

The most significant genetic risk factor for late-onset Alzheimer's disease (AD) is APOE4, with evidence for gain- and loss-of-function mechanisms. A clinical need remains for therapeutically relevant tools that potently modulate APOE expression.

METHODS

We optimized small interfering RNAs (di-siRNA, GalNAc) to potently silence brain or liver Apoe and evaluated the impact of each pool of Apoe on pathology.

RESULTS

In adult 5xFAD mice, siRNAs targeting CNS Apoe efficiently silenced Apoe expression and reduced amyloid burden without affecting systemic cholesterol, confirming that potent silencing of brain Apoe is sufficient to slow disease progression. Mechanistically, silencing Apoe reduced APOE-rich amyloid cores and activated immune system responses.

DISCUSSION

These results establish siRNA-based modulation of Apoe as a viable therapeutic approach, highlight immune activation as a key pathway affected by Apoe modulation, and provide the technology to further evaluate the impact of APOE silencing on neurodegeneration.

Assessing NGS-based computational methods for predicting transcriptional regulators with query gene sets

This article provides an in-depth review of computational methods for predicting transcriptional regulators with query gene sets. Identification of transcriptional regulators is of utmost importance in many biological applications, including but not limited to elucidating biological development mechanisms, identifying key disease genes, and predicting therapeutic targets. Various computational methods based on next-generation sequencing (NGS) data have been developed in the past decade, yet no systematic evaluation of NGS-based methods has been offered. We classified these methods into two categories based on shared characteristics, namely library-based and region-based methods. We further conducted benchmark studies to evaluate the accuracy, sensitivity, coverage, and usability of NGS-based methods with molecular experimental datasets. Results show that BART, ChIP-Atlas, and Lisa have relatively better performance. Besides, we point out the limitations of NGS-based methods and explore potential directions for further improvement.

Key points

An introduction to available computational methods for predicting functional TRs from a query gene set.A detailed walk-through along with practical concerns and limitations.A systematic benchmark of NGS-based methods in terms of accuracy, sensitivity, coverage, and usability, using 570 TR perturbation-derived gene sets.NGS-based methods outperform motif-based methods. Among NGS methods, those utilizing larger databases and adopting region-centric approaches demonstrate favorable performance. BART, ChIP-Atlas, and Lisa are recommended as these methods have overall better performance in evaluated scenarios.

Profound seizure suppression and disease modification by targeting JAK1, a key driver of a pro-epileptogenic gene network

Epilepsy is the 4th most prevalent neurological disorder with over 50 million cases worldwide. While a number of drugs exist to suppress seizures, approximately 1/3 of patients remain drug resistant, and no current treatments are disease modifying. Using network and systems-based approaches, we find that the histone methylase EZH2 suppresses epileptogenesis and slows disease progression, via repression of JAK1 and STAT3 signaling in hippocampal neurons. Pharmacological inhibition of JAK1 with the orally available, FDA-approved drug CP690550 (Tofacitinib) profoundly suppresses behavioral and electrographic seizures after the onset of epilepsy across preclinical rodent models of acquired epilepsy. This seizure suppression persists for weeks after drug withdrawal. Identification of an endogenous protective response to status epilepticus in the form of EZH2 induction has highlighted a critical role for the JAK1 kinase and STAT3 in both the initiation and propagation of epilepsy across preclinical rodent models and human disease. Overall, we find that STAT3 is transiently activated after insult, reactivates with spontaneous seizures, and remains targetable for disease modification in chronic epilepsy.

The calcium channel TRPC6 promotes chemotherapy-induced persistence by regulating integrin α6 mRNA splicing

Understanding the cell biological mechanisms that enable tumor cells to persist after therapy is necessary to improve the treatment of recurrent disease. Here, we demonstrate that transient receptor potential channel 6 (TRPC6), a channel that mediates calcium entry, contributes to the properties of breast cancer stem cells, including resistance to chemotherapy, and that tumor cells that persist after therapy are dependent on TRPC6. The mechanism involves the ability of TRPC6 to regulate integrin α6 mRNA splicing. Specifically, TRPC6-mediated calcium entry represses the epithelial splicing factor ESRP1 (epithelial splicing regulatory protein 1), which enables expression of the integrin α6B splice variant. TRPC6 and α6B function in tandem to facilitate stemness and persistence by activating TAZ and, consequently, repressing Myc. Therapeutic inhibition of TRPC6 sensitizes triple-negative breast cancer (TNBC) cells and tumors to chemotherapy by targeting the splicing of α6 integrin mRNA and inducing Myc. These data reveal a Ca2+-dependent mechanism of chemotherapy-induced persistence, which is amenable to therapy, that involves integrin mRNA splicing.

HAPLN1 matrikine: a bone marrow homing factor linked to poor outcomes in patients with MM

The bone marrow (BM) microenvironment is critical for dissemination, growth, and survival of multiple myeloma (MM) cells. Homing of myeloma cells to the BM niche is a crucial step in MM dissemination, but the mechanisms involved are incompletely understood. In particular, any role of matrikines, neofunctional peptides derived from extracellular matrix proteins, remains unknown. Here, we report that a matrikine derived from hyaluronan and proteoglycan link protein 1 (HAPLN1) induces MM cell adhesion to the BM stromal components, such as fibronectin, endothelial cells, and stromal cells and, furthermore, induces their chemotactic and chemokinetic migration. In a mouse xenograft model, we show that MM cells preferentially home to HAPLN1 matrikine-conditioned BM. The transcription factor STAT1 is activated by HAPLN1 matrikine and is necessary to induce MM cell adhesion, migration, migration-related genes, and BM homing. STAT1 activation is mediated by interferon beta (IFN-β), which is induced by NF-κB after stimulation by HAPLN1 matrikine. Finally, we also provide evidence that higher levels of HAPLN1 in BM samples correlate with poorer progression-free survival of patients with newly diagnosed MM. These data reveal that a matrikine present in the BM microenvironment acts as a chemoattractant, plays an important role in BM homing of MM cells via NF-κB-IFN-β-STAT1 signaling, and may help identify patients with poor outcomes. This study also provides a mechanistic rationale for targeting HAPLN1 matrikine in MM therapy.

The YAP-TEAD complex promotes senescent cell survival by lowering endoplasmic reticulum stress

Sublethal cell damage can trigger senescence, a complex adaptive program characterized by growth arrest, resistance to apoptosis and a senescence-associated secretory phenotype (SASP). Here, a whole-genome CRISPR knockout screen revealed that proteins in the YAP-TEAD pathway influenced senescent cell viability. Accordingly, treating senescent cells with a drug that inhibited this pathway, verteporfin (VPF), selectively triggered apoptotic cell death largely by derepressing DDIT4, which in turn inhibited mTOR. Reducing mTOR function in senescent cells diminished endoplasmic reticulum (ER) biogenesis, triggering ER stress and apoptosis due to high demands on ER function by the SASP. Importantly, VPF treatment decreased the numbers of senescent cells in the organs of old mice and mice exhibiting doxorubicin-induced senescence. Moreover, VPF treatment reduced immune cell infiltration and pro-fibrotic transforming growth factor-β signaling in aging mouse lungs, improving tissue homeostasis. We present an alternative senolytic strategy that eliminates senescent cells by hindering ER activity required for SASP production.

Patterns of transcription factor binding and epigenome at promoters allow interpretable predictability of multiple functions of non-coding and coding genes

Understanding the biological roles of all genes only through experimental methods is challenging. A computational approach with reliable interpretability is needed to infer the function of genes, particularly for non-coding RNAs. We have analyzed genomic features that are present across both coding and non-coding genes like transcription factor (TF) and cofactor ChIP-seq (823), histone modifications ChIP-seq (n = 621), cap analysis gene expression (CAGE) tags (n = 255), and DNase hypersensitivity profiles (n = 255) to predict ontology-based functions of genes. Our approach for gene function prediction was reliable (>90% balanced accuracy) for 486 gene-sets. PubMed abstract mining and CRISPR screens supported the inferred association of genes with biological functions, for which our method had high accuracy. Further analysis revealed that TF-binding patterns at promoters have high predictive strength for multiple functions. TF-binding patterns at the promoter add an unexplored dimension of explainable regulatory aspects of genes and their functions. Therefore, we performed a comprehensive analysis for the functional-specificity of TF-binding patterns at promoters and used them for clustering functions to reveal many latent groups of gene-sets involved in common major cellular processes. We also showed how our approach could be used to infer the functions of non-coding genes using the CRISPR screens of coding genes, which were validated using a long non-coding RNA CRISPR screen. Thus our results demonstrated the generality of our approach by using gene-sets from CRISPR screens. Overall, our approach opens an avenue for predicting the involvement of non-coding genes in various functions.

In silico enhancer mining reveals SNS-032 and EHMT2 inhibitors as therapeutic candidates in high-grade serous ovarian cancer

BACKGROUND

Epigenomic dysregulation has been linked to solid tumour malignancies, including ovarian cancers. Profiling of re-programmed enhancer locations associated with disease has the potential to improve stratification and thus therapeutic choices. Ovarian cancers are subdivided into histological subtypes that have significant molecular and clinical differences, with high-grade serous carcinoma representing the most common and aggressive subtype.

METHODS

We interrogated the enhancer landscape(s) of normal ovary and subtype-specific ovarian cancer states using publicly available data. With an initial focus on H3K27ac histone mark, we developed a computational pipeline to predict drug compound activity based on epigenomic stratification. Lastly, we substantiated our predictions in vitro using patient-derived clinical samples and cell lines.

RESULTS

Using our in silico approach, we highlighted recurrent and privative enhancer landscapes and identified the differential enrichment of a total of 164 transcription factors involved in 201 protein complexes across the subtypes. We pinpointed SNS-032 and EHMT2 inhibitors BIX-01294 and UNC0646 as therapeutic candidates in high-grade serous carcinoma, as well as probed the efficacy of specific inhibitors in vitro.

CONCLUSION

Here, we report the first attempt to exploit ovarian cancer epigenomic landscapes for drug discovery. This computational pipeline holds enormous potential for translating epigenomic profiling into therapeutic leads.

TF-Prioritizer: a Java pipeline to prioritize condition-specific transcription factors

BACKGROUND

Eukaryotic gene expression is controlled by cis-regulatory elements (CREs), including promoters and enhancers, which are bound by transcription factors (TFs). Differential expression of TFs and their binding affinity at putative CREs determine tissue- and developmental-specific transcriptional activity. Consolidating genomic datasets can offer further insights into the accessibility of CREs, TF activity, and, thus, gene regulation. However, the integration and analysis of multimodal datasets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined chromatin state data (e.g., chromatin immunoprecipitation [ChIP], ATAC, or DNase sequencing) and RNA sequencing data exist, they do not offer convenient usability, have limited support for large-scale data processing, and provide only minimal functionality for visually interpreting results.

RESULTS

We developed TF-Prioritizer, an automated pipeline that prioritizes condition-specific TFs from multimodal data and generates an interactive web report. We demonstrated its potential by identifying known TFs along with their target genes, as well as previously unreported TFs active in lactating mouse mammary glands. Additionally, we studied a variety of ENCODE datasets for cell lines K562 and MCF-7, including 12 histone modification ChIP sequencing as well as ATAC and DNase sequencing datasets, where we observe and discuss assay-specific differences.

CONCLUSION

TF-Prioritizer accepts ATAC, DNase, or ChIP sequencing and RNA sequencing data as input and identifies TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.

Human CYP2B6 produces oxylipins from polyunsaturated fatty acids and reduces diet-induced obesity

Multiple factors in addition to over consumption lead to obesity and non-alcoholic fatty liver disease (NAFLD) in the United States and worldwide. CYP2B6 is the only human detoxification CYP whose loss is associated with obesity, and Cyp2b-null mice show greater diet-induced obesity with increased steatosis than wildtype mice. However, a putative mechanism has not been determined. LC-MS/MS revealed that CYP2B6 metabolizes PUFAs, with a preference for metabolism of ALA to 9-HOTrE and to a lesser extent 13-HOTrE with a preference for metabolism of PUFAs at the 9- and 13-positions. To further study the role of CYP2B6 in vivo, humanized-CYP2B6-transgenic (hCYP2B6-Tg) and Cyp2b-null mice were fed a 60% high-fat diet for 16 weeks. Compared to Cyp2b-null mice, hCYP2B6-Tg mice showed reduced weight gain and metabolic disease as measured by glucose tolerance tests, however hCYP2B6-Tg male mice showed increased liver triglycerides. Serum and liver oxylipin metabolite concentrations increased in male hCYP2B6-Tg mice, while only serum oxylipins increased in female hCYP2B6-Tg mice with the greatest increases in LA oxylipins metabolized at the 9 and 13-positions. Several of these oxylipins, specifically 9-HODE, 9-HOTrE, and 13-oxoODE, are PPAR agonists. RNA-seq data also demonstrated sexually dimorphic changes in gene expression related to nuclear receptor signaling, especially CAR > PPAR with qPCR suggesting PPARγ signaling is more likely than PPARα signaling in male mice. Overall, our data indicates that CYP2B6 is an anti-obesity enzyme, but probably to a lesser extent than murine Cyp2b's. Therefore, the inhibition of CYP2B6 by xenobiotics or dietary fats can exacerbate obesity and metabolic disease potentially through disrupted PUFA metabolism and the production of key lipid metabolites.

Single cell atlas of spinal cord injury in mice reveals a pro-regenerative signature in spinocerebellar neurons

After spinal cord injury, tissue distal to the lesion contains undamaged cells that could support or augment recovery. Targeting these cells requires a clearer understanding of their injury responses and capacity for repair. Here, we use single nucleus RNA sequencing to profile how each cell type in the lumbar spinal cord changes after a thoracic injury in mice. We present an atlas of these dynamic responses across dozens of cell types in the acute, subacute, and chronically injured spinal cord. Using this resource, we find rare spinal neurons that express a signature of regeneration in response to injury, including a major population that represent spinocerebellar projection neurons. We characterize these cells anatomically and observed axonal sparing, outgrowth, and remodeling in the spinal cord and cerebellum. Together, this work provides a key resource for studying cellular responses to injury and uncovers the spontaneous plasticity of spinocerebellar neurons, uncovering a potential candidate for targeted therapy.

Matson et al. performed single nucleus sequencing of the “spared” spinal cord tissue distal to an injury in mice. They found that spinocerebellar neurons expressed a pro-regenerative gene signature and showed axon outgrowth after injury.

Small-molecule screening identifies Syk kinase inhibition and rutaecarpine as modulators of macrophage training and SARS-CoV-2 infection

Biologically active small molecules can impart modulatory effects, in some cases providing extended long-term memory. In a screen of biologically active small molecules for regulators of tumor necrosis factor (TNF) induction, we identify several compounds with the ability to induce training effects on human macrophages. Rutaecarpine shows acute and long-term modulation, enhancing lipopolysaccharide (LPS)-induced pro-inflammatory cytokine secretion and relieving LPS tolerance in human macrophages. Rutaecarpine inhibits β-glucan-induced H3K4Me3 marks at the promoters of several pro-inflammatory cytokines, highlighting the potential of this molecule to modulate chromosomal topology. Syk kinase inhibitor (SYKi IV), another screen hit, promotes an enhanced response to LPS similar to that previously reported for β-glucan-induced training. Macrophages trained with SYKi IV show a high degree of resistance to influenza A, multiple variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and OC43 coronavirus infection, highlighting a potential application of this molecule and other SYKis as prophylactic treatments for viral susceptibility.

Altered gene expression profiles impair the nervous system development in individuals with 15q13.3 microdeletion

The 15q13.3 microdeletion has pleiotropic effects ranging from apparently healthy to severely affected individuals. The underlying basis of the variable phenotype remains elusive. We analyzed gene expression using blood from three individuals with 15q13.3 microdeletion and brain cortex tissue from ten mice Df[h15q13]/+. We assessed differentially expressed genes (DEGs), protein–protein interaction (PPI) functional modules, and gene expression in brain developmental stages. The deleted genes’ haploinsufficiency was not transcriptionally compensated, suggesting a dosage effect may contribute to the pathomechanism. DEGs shared between tested individuals and a corresponding mouse model show a significant overlap including genes involved in monogenic neurodevelopmental disorders. Yet, network-wide dysregulatory effects suggest the phenotype is not caused by a single critical gene. A significant proportion of blood DEGs, silenced in adult brain, have maximum expression during the prenatal brain development. Based on DEGs and their PPI partners we identified altered functional modules related to developmental processes, including nervous system development. We show that the 15q13.3 microdeletion has a ubiquitous impact on the transcriptome pattern, especially dysregulation of genes involved in brain development. The high phenotypic variability seen in 15q13.3 microdeletion could stem from an increased vulnerability during brain development, instead of a specific pathomechanism.

Specific dopaminergic genetic variants influence impulsivity, cognitive deficit, and disease severity of Indian ADHD probands

BACKGROUND

Impulsivity (Imp), being one of the cardinal symptoms of Attention Deficit Hyperactivity Disorder (ADHD), often leads to inappropriate responses to stimuli. Since the dopaminergic system is the primary target for pharmaceutical intervention in ADHD, we investigated the association between ADHD-related Imp and functional gene variants of the dopamine transporter (SLC6A3) and catechol-O-methyltransferase involved in dopamine clearance.

METHODS AND RESULTS

Indo-Caucasoid families with ADHD probands (N = 217) were recruited based on the Diagnostic and Statistical Manual of Mental Disorders (DSM). Imp of the probands was assessed using the Domain Specific Imp Scale for Children and DSM. Peripheral blood was collected after obtaining informed written consent for participation, genomic DNA was isolated, and target sites were genotyped by DNA sequencing. The association of genetic variants with Imp was examined by the Quantitative trait analysis (QTA) and Analysis of variance (ANOVA). Post-Hoc analysis following QTA and ANOVA showed significant associations of rs2254408, rs2981359, and rs2239393 with different domains of Imp (P < 0.05). Various haplotypic combinations also showed statistically significant associations with Imp (P < 0.05). Multifactor dimensionality reduction models revealed strong effects of the variants on Imp. ADHD probands harboring the risk alleles exhibited a deficit in performance during cognitive assessment. Longitudinal follow-up revealed a significant association of rs2254408 with trait persistence.

CONCLUSION

The present study indicates the influence of the studied genetic variants on ADHD-associated imp, executive deficit, and disease persistence. Thus, these variants may be helpful as predictors for the success of individual therapeutic sessions during cognitive training.

A deep learning approach to predict inter-omics interactions in multi-layer networks

Background

Despite enormous achievements in the production of high-throughput datasets, constructing comprehensive maps of interactions remains a major challenge. Lack of sufficient experimental evidence on interactions is more significant for heterogeneous molecular types. Hence, developing strategies to predict inter-omics connections is essential to construct holistic maps of disease.

Results

Here, as a novel nonlinear deep learning method, Data Integration with Deep Learning (DIDL) was proposed to predict inter-omics interactions. It consisted of an encoder that performs automatic feature extraction for biomolecules according to existing interactions coupled with a predictor that predicts unforeseen interactions. Applicability of DIDL was assessed on different networks, namely drug–target protein, transcription factor-DNA element, and miRNA–mRNA. Also, validity of the novel predictions was evaluated by literature surveys. According to the results, the DIDL outperformed state-of-the-art methods. For all three networks, the areas under the curve and the precision–recall curve exceeded 0.85 and 0.83, respectively.

Conclusions

DIDL offers several advantages like automatic feature extraction from raw data, end-to-end training, and robustness to network sparsity. In addition, reliance solely on existing inter-layer interactions and independence of biochemical features of interacting molecules make this algorithm applicable for a wide variety of networks. DIDL paves the way to understand the underlying mechanisms of complex disorders through constructing integrative networks.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04569-2.

JASPAR 2022: the 9th release of the open-access database of transcription factor binding profiles

JASPAR (http://jaspar.genereg.net/) is an open-access database containing manually curated, non-redundant transcription factor (TF) binding profiles for TFs across six taxonomic groups. In this 9th release, we expanded the CORE collection with 341 new profiles (148 for plants, 101 for vertebrates, 85 for urochordates, and 7 for insects), which corresponds to a 19% expansion over the previous release. We added 298 new profiles to the Unvalidated collection when no orthogonal evidence was found in the literature. All the profiles were clustered to provide familial binding profiles for each taxonomic group. Moreover, we revised the structural classification of DNA binding domains to consider plant-specific TFs. This release introduces word clouds to represent the scientific knowledge associated with each TF. We updated the genome tracks of TFBSs predicted with JASPAR profiles in eight organisms; the human and mouse TFBS predictions can be visualized as native tracks in the UCSC Genome Browser. Finally, we provide a new tool to perform JASPAR TFBS enrichment analysis in user-provided genomic regions. All the data is accessible through the JASPAR website, its associated RESTful API, the R/Bioconductor data package, and a new Python package, pyJASPAR, that facilitates serverless access to the data.

A deep learning model to identify gene expression level using cobinding transcription factor signals

Gene expression is directly controlled by transcription factors (TFs) in a complex combination manner. It remains a challenging task to systematically infer how the cooperative binding of TFs drives gene activity. Here, we quantitatively analyzed the correlation between TFs and surveyed the TF interaction networks associated with gene expression in GM12878 and K562 cell lines. We identified six TF modules associated with gene expression in each cell line. Furthermore, according to the enrichment characteristics of TFs in these TF modules around a target gene, a convolutional neural network model, called TFCNN, was constructed to identify gene expression level. Results showed that the TFCNN model achieved a good prediction performance for gene expression. The average of the area under receiver operating characteristics curve (AUC) can reach up to 0.975 and 0.976, respectively in GM12878 and K562 cell lines. By comparison, we found that the TFCNN model outperformed the prediction models based on SVM and LDA. This is due to the TFCNN model could better extract the combinatorial interaction among TFs. Further analysis indicated that the abundant binding of regulatory TFs dominates expression of target genes, while the cooperative interaction between TFs has a subtle regulatory effects. And gene expression could be regulated by different TF combinations in a nonlinear way. These results are helpful for deciphering the mechanism of TF combination regulating gene expression.

Deficiency of PARP-1 and PARP-2 in the mouse uterus results in decidualization failure and pregnancy loss

Miscarriage is a common complication of pregnancy for which there are few clinical interventions. Deficiency in endometrial stromal cell decidualization is considered a major contributing factor to pregnancy loss; however, our understanding of the underlying mechanisms of decidual deficiency are incomplete. ADP ribosylation by PARP-1 and PARP-2 has been linked to physiological processes essential to successful pregnancy outcomes. Here, we report that the catalytic inhibition or genetic ablation of PARP-1 and PARP-2 in the uterus lead to pregnancy loss in mice. Notably, the absence of PARP-1 and PARP-2 resulted in increased p53 signaling and an increased population of senescent decidual cells. Molecular and histological analysis revealed that embryo attachment and the removal of the luminal epithelium are not altered in uterine Parp1, Parp2 knockout mice, but subsequent decidualization failure results in pregnancy loss. These findings provide evidence for a previously unknown function of PARP-1 and PARP-2 in mediating decidualization for successful pregnancy establishment.

MyoData: An expression knowledgebase at single cell/nucleus level for the discovery of coding-noncoding RNA functional interactions in skeletal muscle

•

Regulation of gene expression through non-coding RNAs at single myofiber and nucleus resolution.

•

Reinterpretation of KEGG pathways with microRNA and long non-coding RNA activities.

•

miR-149, -214, and let-7e alter mitochondrial shape.

•

The long non-coding RNA Pvt1 is a sponge for miR-27a.

•

miR-208b regulates Sox6; miR-214 regulates both Sox6 and Slc16a3.

Non-coding RNAs represent the largest part of transcribed mammalian genomes and prevalently exert regulatory functions. Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) can modulate the activity of each other. Skeletal muscle is the most abundant tissue in mammals. It is composed of different cell types with myofibers that represent the smallest complete contractile system. Considering that lncRNAs and miRNAs are more cell type-specific than coding RNAs, to understand their function it is imperative to evaluate their expression and action within single myofibers. In this database, we collected gene expression data for coding and non-coding genes in single myofibers and used them to produce interaction networks based on expression correlations. Since biological pathways are more informative than networks based on gene expression correlation, to understand how altered genes participate in the studied phenotype, we integrated KEGG pathways with miRNAs and lncRNAs. The database also integrates single nucleus gene expression data on skeletal muscle in different patho-physiological conditions. We demonstrated that these networks can serve as a framework from which to dissect new miRNA and lncRNA functions to experimentally validate. Some interactions included in the database have been previously experimentally validated using high throughput methods. These can be the basis for further functional studies. Using database information, we demonstrate the involvement of miR-149, -214 and let-7e in mitochondria shaping; the ability of the lncRNA Pvt1 to mitigate the action of miR-27a via sponging; and the regulatory activity of miR-214 on Sox6 and Slc16a3. The MyoData is available at https://myodata.bio.unipd.it.

TCF19 Impacts a Network of Inflammatory and DNA Damage Response Genes in the Pancreatic β-Cell

Transcription factor 19 (TCF19) is a gene associated with type 1 diabetes (T1DM) and type 2 diabetes (T2DM) in genome-wide association studies. Prior studies have demonstrated that Tcf19 knockdown impairs β-cell proliferation and increases apoptosis. However, little is known about its role in diabetes pathogenesis or the effects of TCF19 gain-of-function. The aim of this study was to examine the impact of TCF19 overexpression in INS-1 β-cells and human islets on proliferation and gene expression. With TCF19 overexpression, there was an increase in nucleotide incorporation without any change in cell cycle gene expression, alluding to an alternate process of nucleotide incorporation. Analysis of RNA-seq of TCF19 overexpressing cells revealed increased expression of several DNA damage response (DDR) genes, as well as a tightly linked set of genes involved in viral responses, immune system processes, and inflammation. This connectivity between DNA damage and inflammatory gene expression has not been well studied in the β-cell and suggests a novel role for TCF19 in regulating these pathways. Future studies determining how TCF19 may modulate these pathways can provide potential targets for improving β-cell survival.

Understanding the Molecular Drivers of Disease Heterogeneity in Crohn's Disease Using Multi-omic Data Integration and Network Analysis

Crohn's disease (CD), a form of inflammatory bowel disease (IBD), is characterized by heterogeneity along multiple clinical axes, which in turn impacts disease progression and treatment modalities. Using advanced data integration approaches and systems biology tools, we studied the contribution of CD susceptibility variants and gene expression in distinct peripheral immune cell subsets (CD14+ monocytes and CD4+ T cells) to relevant clinical traits. Our analyses revealed that most clinical traits capturing CD heterogeneity could be associated with CD14+ and CD4+ gene expression rather than disease susceptibility variants. By disentangling the sources of variation, we identified molecular features that could potentially be driving the heterogeneity of various clinical traits of CD patients. Further downstream analyses identified contextual hub proteins such as genes encoding barrier functions, antimicrobial peptides, chemokines, and their receptors, which are either targeted by drugs used in CD or other inflammatory diseases or are relevant to the biological functions implicated in disease pathology. These hubs could be used as cell type-specific targets to treat specific subtypes of CD patients in a more individualized approach based on the underlying biology driving their disease subtypes. Our study highlights the importance of data integration and systems approaches to investigate complex and heterogeneous diseases such as IBD.

Mutations in cis that affect mRNA synthesis, processing and translation

Genetic mutations that cause hereditary diseases usually affect the composition of the transcribed mRNA and its encoded protein, leading to instability of the mRNA and/or the protein. Sometimes, however, such mutations affect the synthesis, the processing or the translation of the mRNA, with similar disastrous effects. We here present an overview of mRNA synthesis, its posttranscriptional modification and its translation into protein. We then indicate which elements in these processes are known to be affected by pathogenic mutations, but we restrict our review to mutations in cis, in the DNA of the gene that encodes the affected protein. These mutations can be in enhancer or promoter regions of the gene, which act as binding sites for transcription factors involved in pre-mRNA synthesis. We also describe mutations in polyadenylation sequences and in splice site regions, exonic and intronic, involved in intron removal. Finally, we include mutations in the Kozak sequence in mRNA, which is involved in protein synthesis. We provide examples of genetic diseases caused by mutations in these DNA regions and refer to databases to help identify these regions. The over-all knowledge of mRNA synthesis, processing and translation is essential for improvement of the diagnosis of patients with genetic diseases.

The adverse metabolic effects of branched-chain amino acids are mediated by isoleucine and valine

Low-protein diets promote metabolic health in rodents and humans, and the benefits of low-protein diets are recapitulated by specifically reducing dietary levels of the three branched-chain amino acids (BCAAs), leucine, isoleucine, and valine. Here, we demonstrate that each BCAA has distinct metabolic effects. A low isoleucine diet reprograms liver and adipose metabolism, increasing hepatic insulin sensitivity and ketogenesis and increasing energy expenditure, activating the FGF21-UCP1 axis. Reducing valine induces similar but more modest metabolic effects, whereas these effects are absent with low leucine. Reducing isoleucine or valine rapidly restores metabolic health to diet-induced obese mice. Finally, we demonstrate that variation in dietary isoleucine levels helps explain body mass index differences in humans. Our results reveal isoleucine as a key regulator of metabolic health and the adverse metabolic response to dietary BCAAs and suggest reducing dietary isoleucine as a new approach to treating and preventing obesity and diabetes.

Ouabain-Induced Gene Expression Changes in Human iPSC-Derived Neuron Culture Expressing Dopamine and cAMP-Regulated Phosphoprotein 32 and GABA Receptors

Cardiotonic steroids (CTS) are specific inhibitors and endogenous ligands of a key enzyme in the CNS-the Na⁺, K⁺-ATPase, which maintains and creates an ion gradient on the plasma membrane of neurons. CTS cause the activation of various signaling cascades and changes in gene expression in neurons and other cell types. It is known that intracerebroventricular injection of cardiotonic steroid ouabain causes mania-like behavior in rodents, in part due to activation of dopamine-related signaling cascades in the dopamine and cAMP-regulated phosphoprotein 32 (DARPP-32) expressing medium spiny neurons in the striatum. Dopaminergic projections in the striatum innervate these GABAergic medium spiny neurons. The objective of this study was to assess changes in the expression of all genes in human iPSC-derived expressing DARPP-32 and GABA receptors neurons under the influence of ouabain. We noted a large number of statistically significant upregulated and downregulated genes after a 16-h incubation with non-toxic concentration (30 nM) of ouabain. These changes in the transcriptional activity were accomplished with activation of MAP-kinase ERK1/2 and transcriptional factor cAMP response element-binding protein (CREB). Thus, it can be concluded that 30 nM ouabain incubated for 16 h with human iPSC-derived expressing DARPP-32 and GABA receptors neurons activates genes associated with neuronal maturation and synapse formation, by increasing the expression of genes associated with translation, vesicular transport, and increased electron transport chain function. At the same time, the expression of genes associated with proliferation, migration, and early development of neurons decreases. These data indicate that non-toxic concentrations of ouabain may induce neuronal maturation, neurite growth, and increased synaptogenesis in dopamine-receptive GABAergic neurons, suggesting formation of plasticity and the establishment of new neuronal junctions.