JASPAR, the open access database of transcription factor-binding profiles: new content and tools in the 2008 update

Exploring molecular targets: herbal isolates in cervical cancer therapy

OBJECTIVE

Cervical cancer (CxCa) stands as a significant global health challenge, ranking fourth in cancer-related mortality among the female population. While chemotherapy regimens have demonstrated incremental progress in extending overall survival, the outlook for recurrent CxCa patients remains disheartening. An imperative necessity arises to delve into innovative therapeutic avenues, with molecular targeted therapy emerging as a promising candidate. Previous investigations have shed light on the therapeutic effectiveness of five distinct herbal compounds, epicatechin, curcumin, myricetin, jatrorrhizine, and arborinine, within the context of CxCa.

METHODS

A systems biology approach was employed to discern differentially expressed genes (DEGs) in CxCa tissues relative to healthy cervical epithelial tissues. A protein-protein interaction network (PPIN) was constructed, anchored in the genes related to CxCa. The central genes were discerned within the PPIN, and Kaplan-Meier survival curves explored their prognostic significance. An assessment of the binding affinity of the selected herbal compounds to the master regulator of prognostic markers in CxCa was conducted.

RESULTS

A significant correlation between the overexpression of MYC, IL6, JUN, RRM2, and VEGFA and an adverse prognosis in CxCa was indicated. The regulation of these markers is notably influenced by the transcription factor CEBPD. Molecular docking analysis indicated that the binding affinity between myricetin and the CEBPD DNA binding site was robust.

CONCLUSION

The findings presented herein have unveiled pivotal genes and pathways that play a central role in the malignant transformation of CxCa. CEBPD has emerged as a potential target for harnessing the therapeutic potential of myricetin in this context.

Stroke Causes DNA Methylation at Ncx1 Heart Promoter in the Brain Via DNMT1/MeCP2/REST Epigenetic Complex

BACKGROUND

REST (Repressor-Element 1 [RE1]-silencing transcription factor) inhibits Na+/Ca2+exchanger-1 (Ncx1) transcription in neurons through the binding of RE1 site on brain promoter (Br) after stroke. We identified a new putative RE1 site in Ncx1 heart promoter (Ht) sequence (Ht-RE1) that participates in neuronal Ncx1 transcription. Because REST recruits DNA-methyltransferase-1 (DNMT1) and MeCP2 (methyl-CpG binding protein 2) on different neuronal genes, we investigated the role of this complex in Ncx1 transcriptional regulation after stroke.

METHODS AND RESULTS

Luciferase experiments performed in SH-SY5Y cells demonstrated that Br activity was selectively decreased by REST, whereas Ht activity was reduced by DNMT1, MeCP2, and REST. Notably, site-direct mutagenesis of Ht-RE1 prevented REST-dependent downregulation of Ncx1. Furthermore, in temporoparietal cortex of 8-week-old male wild-type mice (C57BL/6) subjected to transient middle cerebral artery occlusion, DNMT1, MeCP2, and REST binding to Ht promoter was increased, with a consequent DNA promoter hypermethylation. Intracerebroventricular injection of siREST prevented DNMT1/MeCP2 binding to Ht and Ncx1 downregulation, thus causing a reduction in stroke-induced damage. Consistently, in cortical neurons subjected to oxygen and glucose deprivation plus reoxygenation Ncx1 knockdown counteracted neuronal protection induced by the demethylating agent 5-azacytidine. For comparisons between 2 experimental groups, Student's t test was used, whereas for more than 2 experimental groups, 1-way ANOVA was used, followed by Tukey or Newman Keuls. Statistical significance was set at P<0.05.

CONCLUSIONS

If the results of this study are confirmed in humans, it could be asserted that DNMT1/MeCP2/REST complex disruption could be a new pharmacological strategy to reduce DNA methylation of Ht in the brain, ameliorating stroke damage.

Differential sensitivity to longitudinal and transverse stretch mediates transcriptional responses in mouse neonatal ventricular myocytes

To identify how cardiomyocyte mechanosensitive signaling pathways are regulated by anisotropic stretch, micropatterned mouse neonatal cardiomyocytes were stretched primarily longitudinally or transversely to the myofiber axis. Four hours of static, longitudinal stretch induced differential expression of 557 genes, compared with 30 induced by transverse stretch, measured using RNA-seq. A logic-based ordinary differential equation model of the cardiac myocyte mechanosignaling network, extended to include the transcriptional regulation and expression of 784 genes, correctly predicted measured expression changes due to anisotropic stretch with 69% accuracy. The model also predicted published transcriptional responses to mechanical load in vitro or in vivo with 63-91% accuracy. The observed differences between transverse and longitudinal stretch responses were not explained by differential activation of specific pathways but rather by an approximately twofold greater sensitivity to longitudinal stretch than transverse stretch. In vitro experiments confirmed model predictions that stretch-induced gene expression is more sensitive to angiotensin II and endothelin-1, via RhoA and MAP kinases, than to the three membrane ion channels upstream of calcium signaling in the network. Quantitative cardiomyocyte gene expression differs substantially with the axis of maximum principal stretch relative to the myofilament axis, but this difference is due primarily to differences in stretch sensitivity rather than to selective activation of mechanosignaling pathways.NEW & NOTEWORTHY Anisotropic stretch applied to micropatterned neonatal mouse ventricular myocytes induced markedly greater acute transcriptional responses when the major axis of stretch was parallel to the myofilament axis than when it was transverse. Analysis with a novel quantitative network model of mechanoregulated cardiomyocyte gene expression suggests that this difference is explained by higher cell sensitivity to longitudinal loading than transverse loading than by the activation of differential signaling pathways.

Deep molecular learning of transcriptional control of a synthetic CRE enhancer and its variants

Massively parallel reporter assay measures transcriptional activities of various cis-regulatory modules (CRMs) in a single experiment. We developed a thermodynamic computational model framework that calculates quantitative levels of gene expression directly from regulatory DNA sequences. Using the framework, we investigated the molecular mechanisms of cis-regulatory mutations of a synthetic enhancer that cause abnormal gene expression. We found that, in a human cell line, competitive binding between family transcription factors (TFs) with slightly different binding preferences significantly increases the accuracy of recapitulating the transcriptional effects of thousands of single- or multi-mutations. We also discovered that even if various harmful mutations occurred in an activator binding site, CRM could stably maintain or even increase gene expression through a certain form of competitive binding between family TFs. These findings enhance understanding the effect of SNPs and indels on CRMs and would help building robust custom-designed CRMs for biologics production and gene therapy.

The C2H2 zinc finger transcription factor CF2-II regulates multi-insecticide resistance-related gut-predominant ABC transporters in Aphis gossypii Glover

Clarifying the molecular mechanisms of cotton aphid resistance to various insecticides is crucial for the long-term safe application of insecticides in chemical control. ATP-binding cassette (ABC) transporters mediate the membrane transport of various substrates (including exogenous substances). Experiments confirmed that ABCB5, ABCF2, and MRP12 contributed to high levels of resistance to spirotetramat, cyantraniliprole, thiamethoxam or imidacloprid. Binding sites of the C2H2 zinc finger transcription factor CF2-II was predicted to be located in the promoters of ABCB5, ABCF2, and MRP12. The expression levels of ABCB5, ABCF2, and MRP12 were significantly upregulated after silencing CF2-II. The results of dual-luciferase reporter assays demonstrated a negative regulatory relationship between CF2-II and ABC transporter promoters. Furthermore, yeast one-hybrid (Y1H) and electrophoresis mobility shift assays (EMSAs) revealed that CF2-II inhibited the expression of ABC transporter genes through interaction with binding sites [ABCF2.p (-1149/-1140) or MRP12.p (-1189/-1181)]. The above results indicated that ABCB5, ABCF2, and MRP12 were negatively regulated by the transcription factor CF2-II, which will help us further understand the mechanism of transcriptional adaption of multi-insecticides resistant related ABC transporters in response to xenobiotics.

Molecular Footprints on Osmoregulation-Related Genes Associated with Freshwater Colonization by Cetaceans and Sirenians

The genetic basis underlying adaptive physiological mechanisms has been extensively explored in mammals after colonizing the seas. However, independent lineages of aquatic mammals exhibit complex patterns of secondary colonization in freshwater environments. This change in habitat represents new osmotic challenges, and additional changes in key systems, such as the osmoregulatory system, are expected. Here, we studied the selective regime on coding and regulatory regions of 20 genes related to the osmoregulation system in strict aquatic mammals from independent evolutionary lineages, cetaceans, and sirenians, with representatives in marine and freshwater aquatic environments. We identified positive selection signals in genes encoding the protein vasopressin (AVP) in mammalian lineages with secondary colonization in the fluvial environment and in aquaporins for lineages inhabiting the marine and fluvial environments. A greater number of sites with positive selection signals were found for the dolphin species compared to the Amazonian manatee. Only the AQP5 and AVP genes showed selection signals in more than one independent lineage of these mammals. Furthermore, the vasopressin gene tree indicates greater similarity in river dolphin sequences despite the independence of their lineages based on the species tree. Patterns of distribution and enrichment of Transcription Factors in the promoter regions of target genes were analyzed and appear to be phylogenetically conserved among sister species. We found accelerated evolution signs in genes ACE, AQP1, AQP5, AQP7, AVP, NPP4, and NPR1 for the fluvial mammals. Together, these results allow a greater understanding of the molecular bases of the evolution of genes responsible for osmotic control in aquatic mammals.

Multi-omics approach reveals dysregulated genes during hESCs neuronal differentiation exposure to paracetamol

Prenatal paracetamol exposure has been associated with neurodevelopmental outcomes in childhood. Pharmacoepigenetic studies show differences in cord blood DNA methylation between unexposed and paracetamol-exposed neonates, however, causality and impact of long-term prenatal paracetamol exposure on brain development remain unclear. Using a multi-omics approach, we investigated the effects of paracetamol on an in vitro model of early human neurodevelopment. We exposed human embryonic stem cells undergoing neuronal differentiation with paracetamol concentrations corresponding to maternal therapeutic doses. Single-cell RNA-seq and ATAC-seq integration identified paracetamol-induced chromatin opening changes linked to gene expression. Differentially methylated and/or expressed genes were involved in neurotransmission and cell fate determination trajectories. Some genes involved in neuronal injury and development-specific pathways, such as KCNE3, overlapped with differentially methylated genes previously identified in cord blood associated with prenatal paracetamol exposure. Our data suggest that paracetamol may play a causal role in impaired neurodevelopment.

Resveratrol and 3,3'-Diindolylmethane Differentially Regulate Aryl Hydrocarbon Receptor and Estrogen Receptor Alpha Activity through Multiple Transcriptomic Targets in MCF-7 Human Breast Cancer Cells

Inhibitory crosstalk between estrogen receptor alpha (ERα) and aryl hydrocarbon receptor (AHR) regulates 17β-estradiol (E2)-dependent breast cancer cell signaling. ERα and AHR are transcription factors activated by E2 and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), respectively. Dietary ligands resveratrol (RES) and 3,3'diindolylmethane (DIM) also activate ERα while only DIM activates AHR and RES represses it. DIM and RES are reported to have anti-cancer and anti-inflammatory properties. Studies with genome-wide targets and AHR- and ERα-regulated genes after DIM and RES are unknown. We used chromatin immunoprecipitation with high-throughput sequencing and transcriptomics to study ERα as well as AHR coregulation in MCF-7 human breast cancer cells treated with DIM, RES, E2, or TCDD alone or E2+TCDD for 1 and 6 h, respectively. ERα bound sites after being DIM enriched for the AHR motif but not after E2 or RES while AHR bound sites after being DIM and E2+TCDD enriched for the ERE motif but not after TCDD. More than 90% of the differentially expressed genes closest to an AHR binding site after DIM or E2+TCDD also had an ERα site, and 60% of the coregulated genes between DIM and E2+TCDD were common. Collectively, our data show that RES and DIM differentially regulate multiple transcriptomic targets via ERα and ERα/AHR coactivity, respectively, which need to be considered to properly interpret their cellular and biological responses. These novel data also suggest that, when both receptors are activated, ERα dominates with preferential recruitment of AHR to ERα target genes.

Identifying functional regulatory mutation blocks by integrating genome sequencing and transcriptome data

Millions of single nucleotide variants (SNVs) exist in the human genome; however, it remains challenging to identify functional SNVs associated with diseases. We propose a non-encoding SNVs analysis tool bpb3, BayesPI-BAR version 3, aiming to identify the functional mutation blocks (FMBs) by integrating genome sequencing and transcriptome data. The identified FMBs display high frequency SNVs, significant changes in transcription factors (TFs) binding affinity and are nearby the regulatory regions of differentially expressed genes. A two-level Bayesian approach with a biophysical model for protein-DNA interactions is implemented, to compute TF-DNA binding affinity changes based on clustered position weight matrices (PWMs) from over 1700 TF-motifs. The epigenetic data, such as the DNA methylome can also be integrated to scan FMBs. By testing the datasets from follicular lymphoma and melanoma, bpb3 automatically and robustly identifies FMBs, demonstrating that bpb3 can provide insight into patho-mechanisms, and therapeutic targets from transcriptomic and genomic data.

Corneal gene therapy: Structural and mechanistic understanding

Cornea, a dome-shaped and transparent front part of the eye, affords 2/3rd refraction and barrier functions. Globally, corneal diseases are the leading cause of vision impairment. Loss of corneal function including opacification involve the complex crosstalk and perturbation between a variety of cytokines, chemokines and growth factors generated by corneal keratocytes, epithelial cells, lacrimal tissues, nerves, and immune cells. Conventional small-molecule drugs can treat mild-to-moderate traumatic corneal pathology but requires frequent application and often fails to treat severe pathologies. The corneal transplant surgery is a standard of care to restore vision in patients. However, declining availability and rising demand of donor corneas are major concerns to maintain ophthalmic care. Thus, the development of efficient and safe nonsurgical methods to cure corneal disorders and restore vision in vivo is highly desired. Gene-based therapy has huge potential to cure corneal blindness. To achieve a nonimmunogenic, safe and sustained therapeutic response, the selection of a relevant genes, gene editing methods and suitable delivery vectors are vital. This article describes corneal structural and functional features, mechanistic understanding of gene therapy vectors, gene editing methods, gene delivery tools, and status of gene therapy for treating corneal disorders, diseases, and genetic dystrophies.

Systematic assessment of prognostic molecular features across cancers

Precision oncology promises accurate prediction of disease trajectories by utilizing molecular features of tumors. We present a systematic analysis of the prognostic potential of diverse molecular features across large cancer cohorts. We find that the mRNA expression of biologically coherent sets of genes (modules) is substantially more predictive of patient survival than single-locus genomic and transcriptomic aberrations. Extending our analysis beyond existing curated gene modules, we find a large novel class of highly prognostic DNA/RNA cis-regulatory modules associated with dynamic gene expression within cancers. Remarkably, in more than 82% of cancers, modules substantially improve survival stratification compared with conventional clinical factors and prominent genomic aberrations. The prognostic potential of cancer modules generalizes to external cohorts better than conventionally used single-gene features. Finally, a machine-learning framework demonstrates the combined predictive power of multiple modules, yielding prognostic models that perform substantially better than existing histopathological and clinical factors in common use.

Genetic Diversity of the LTR Region of Polish SRLVs and Its Impact on the Transcriptional Activity of Viral Promoters

A long terminal repeat (LTR) plays an indispensable role in small ruminant lentivirus (SRLV) gene expression. In this study, we present the LTR sequence of Polish SRLVs representing different subtypes, and analyzed their impact on SRLV promoter activity, as measured in transient transfection assays. Although certain nucleotide motifs (AML(vis), TATA box and the polyadenylation site (AATAAA)) were conserved across sequences, numerous mutations within the LTR sequences have been identified. Single nucleotide polymorphisms (SNPs) were detected in both regulatory (AP-1, AP-4, Stat and Gas) and non-regulatory sequences, and subtype-specific genetic diversity in the LTR region of Polish SRLVs was observed. In vitro assays demonstrated subtype-specific functional differences between the LTR regions of distinct SRLV subtypes. Our results revealed that the promoter activity of Polish strains was lower (1.64-10.8-fold) than that noted for the K1514 reference strain; however, the differences in most cases were not statistically significant. The lowest promoter activity was observed for strains representing subtype A5 (mean 69.067) while the highest promoter activity was observed for strain K1514 representing subtype A1 (mean 373.48). The mean LTR activities of strains representing subtypes A12, A17, A23, A18 and A24 were 91.22, 137.21, 178.41, 187.05 and 236.836, respectively. The results of the inter-subtype difference analysis showed that the promoter activity of strains belonging to subtype A5 was significantly lower than that for subtype A12 strains (1.32-fold; p < 0.00). The promoter activities of the A5 strain were 1.98-fold and 2.58-fold less active than that of the A17 and A23 strains, and the promoter activities of A12 strains were 1.955 and 1.5 times lower than the promoter activity of A23 and A17 strains, respectively. Furthermore, the promoter activity of A17 strains was 1.3 lower than the promoter activity of A23 strains. Our findings suggest that subtype-specific genetic diversity, mainly in the transcription factor's binding sites, has an impact on their transcriptional activity, producing a distinct activity pattern for the subtypes. This study provides new information that is important for better understanding the function of the SRLV LTR. However, further research including more strains and subtypes as well as other cell lines is needed to confirm these findings.

PU.1-CD23 signaling mediates pulmonary innate immunity against Aspergillus fumigatus infection by driving inflammatory response

BACKGROUND

Aspergillosis is a common cause of morbidity and mortality in immunocompromised populations. PU.1 is critical for innate immunity against Aspergillus fumigatus (AF) in macrophages. However, the molecular mechanism underlying PU.1 mediating immunity against AF infection in human alveolar macrophages (AMs) is still unclear.

METHODS

In this study, we detected the expressions of PU.1, CD23, p-ERK, CCL20 and IL-8 and key inflammatory markers IL-1β, IL-6, TNF-α and IL-12 in human THP-1-derived macrophages (HTMs) or PU.1/CD23-overexpressed immunodeficient mice with AF infection. Moreover, we examined these expressions in PU.1-overexpressed/interfered HTMs. Additionally, we detected the phagocytosis of macrophages against AF infection with altered PU.1 expression. Dual luciferase, ChIP and EMSAs were performed to detect the interaction of PU.1 and CD23. And we invested the histological changes in mouse lung tissues transfected with PU.1/CD23-expressing adenoviruses in AF infection.

RESULTS

The results showed that the expressions of PU.1, CD23, p-ERK, CCL20, IL-8, IL-1β, IL-6, TNF-α and IL-12 increased significantly with AF infection, and PU.1 regulated the later 8 gene expressions in HTMs. Moreover, CD23 was directly activated by PU.1, and overexpression of CD23 in PU.1-interfered HTMs upregulated IL-1β, IL-6, TNF-α and IL-12 levels which were downregulated by PU.1 interference. PU.1 overexpression strengthened the phagocytosis of the HTMs against AF. And injection of PU.1/CD23-expressing adenoviruses attenuated pathological defects in immunodeficient mouse lung tissues with AF infection. Adenovirus (Ad)-PU.1 increased the CD23, p-ERK, CCL20, IL-8 levels.

CONCLUSIONS

Our study concluded that PU.1-CD23 signaling mediates innate immunity against AF in lungs through regulating inflammatory response. Therefore, PU.1-CD23 may be a new anti-aspergillosis therapeutic for the treatment of invasive aspergillosis with the deepening of gene therapy and its wide application in the clinic.

miR-328-3p Affects Axial Length Via Multiple Routes and Anti-miR-328-3p Possesses a Potential to Control Myopia Progression

Purpose

We previously reported miR-328-3p as a novel risk factor for myopia through a genetic association study of the PAX6 gene. In the present study, we first explored the effects of miR-328-3p on other myopia-related genes, and then tested whether anti-miR-328-3p may be used for myopia control.

Methods

The luciferase report assay and transient transfection were used to confirm miR-328-3p target genes. The chromatin immunoprecipitation (ChIP) assay was used to investigate retinoic acid receptor on the miR-328-3p promoter. Mice and pigmented rabbits were induced to have myopia by the form deprivation method, and then anti-miR-328-3p oligonucleotide was topically instilled to the myopic eyes. The axial length was measured to assess the therapeutic effect of anti-miR-328-3p. A toxicity study using much higher doses was conducted to assess the safety and ocular irritation of anti-miR-328-3p.

Results

The report assay and transfection of miR-328-3p mimic confirmed that miR-328-3p dose-dependently decreased both mRNA and protein expression of fibromodulin (FMOD) and collagen1A1 (COL1A1). We subsequently showed that FMOD promoted TGF-β1 expression, and overexpression of FMOD increased the phosphorylation levels of p38-MAPK and JNK. The ChIP study showed that retinoic acid binds to miR-328-3p promoter and up-regulates miR-328-3p expression. In myopic animal studies, anti-miR-328-3p was as effective as 1% atropine and had a dose-dependent effect on suppressing axial elongation. In the toxicity study, anti-miR-328-3p did not cause any unwanted effects in the eyes or other organs.

Conclusions

Micro (mi)R-328-3p affects myopia development via multiple routes. anti-miR-328-3p possesses a potential as a novel therapy for myopia control.

A multi-omics approach to visualize early neuronal differentiation from hESCs in 4D

Neuronal differentiation of pluripotent stem cells is an established method to study physiology, disease, and medication safety. However, the sequence of events in human neuronal differentiation and the ability of in vitro models to recapitulate early brain development are poorly understood. We developed a protocol optimized for the study of early human brain development and neuropharmacological applications. We comprehensively characterized gene expression and epigenetic profiles at four timepoints, because the cells differentiate from embryonic stem cells towards a heterogeneous population of progenitors, immature and mature neurons bearing telencephalic signatures. A multi-omics roadmap of neuronal differentiation, combined with searchable interactive gene analysis tools, allows for extensive exploration of early neuronal development and the effect of medications.

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Multi-omics charting a new neuronal differentiation protocol for human ES cells

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Single-cell analyses reveal marker genes during neuronal differentiation

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Identified transcriptional waves similar to early human brain development

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Searchable tools to visualize single-cell gene expression and chromatin state

Systems biology models to identify the influence of SARS-CoV-2 infections to the progression of human autoimmune diseases

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been circulating since 2019, and its global dominance is rising. Evidences suggest the respiratory illness SARS-CoV-2 has a sensitive affect on causing organ damage and other complications to the patients with autoimmune diseases (AD), posing a significant risk factor. The genetic interrelationships and molecular appearances between SARS-CoV-2 and AD are yet unknown. We carried out the transcriptomic analytical framework to delve into the SARS-CoV-2 impacts on AD progression. We analyzed both gene expression microarray and RNA-Seq datasets from SARS-CoV-2 and AD affected tissues. With neighborhood-based benchmarks and multilevel network topology, we obtained dysfunctional signaling and ontological pathways, gene disease (diseasesome) association network and protein-protein interaction network (PPIN), uncovered essential shared infection recurrence connectivities with biological insights underlying between SARS-CoV-2 and AD. We found a total of 77, 21, 9, 54 common DEGs for SARS-CoV-2 and inflammatory bowel disorder (IBD), SARS-CoV-2 and rheumatoid arthritis (RA), SARS-CoV-2 and systemic lupus erythematosus (SLE) and SARS-CoV-2 and type 1 diabetes (T1D). The enclosure of these common DEGs with bimolecular networks revealed 10 hub proteins (FYN, VEGFA, CTNNB1, KDR, STAT1, B2M, CD3G, ITGAV, TGFB3). Drugs such as amlodipine besylate, vorinostat, methylprednisolone, and disulfiram have been identified as a common ground between SARS-CoV-2 and AD from drug repurposing investigation which will stimulate the optimal selection of medications in the battle against this ongoing pandemic triggered by COVID-19.

Cognate DNA Recognition by Engrailed Homeodomain Involves a Conformational Change Controlled via an Electrostatic-Spring-Loaded Latch

Transcription factors must scan genomic DNA, recognize the cognate sequence of their control element(s), and bind tightly to them. The DNA recognition process is primarily carried out by their DNA binding domains (DBD), which interact with the cognate site with high affinity and more weakly with any other DNA sequence. DBDs are generally thought to bind to their cognate DNA without changing conformation (lock-and-key). Here, we used nuclear magnetic resonance and circular dichroism to investigate the interplay between DNA recognition and DBD conformation in the engrailed homeodomain (enHD), as a model case for the homeodomain family of eukaryotic DBDs. We found that the conformational ensemble of enHD is rather flexible and becomes gradually more disordered as ionic strength decreases following a Debye–Hückel’s dependence. Our analysis indicates that enHD’s response to ionic strength is mediated by a built-in electrostatic spring-loaded latch that operates as a conformational transducer. We also found that, at moderate ionic strengths, enHD changes conformation upon binding to cognate DNA. This change is of larger amplitude and somewhat orthogonal to the response to ionic strength. As a consequence, very high ionic strengths (e.g., 700 mM) block the electrostatic-spring-loaded latch and binding to cognate DNA becomes lock-and-key. However, the interplay between enHD conformation and cognate DNA binding is robust across a range of ionic strengths (i.e., 45 to 300 mM) that covers the physiologically-relevant conditions. Therefore, our results demonstrate the presence of a mechanism for the conformational control of cognate DNA recognition on a eukaryotic DBD. This mechanism can function as a signal transducer that locks the DBD in place upon encountering the cognate site during active DNA scanning. The electrostatic-spring-loaded latch of enHD can also enable the fine control of DNA recognition in response to transient changes in local ionic strength induced by variate physiological processes.

Potential biomarkers and signaling pathways associated with the pathogenesis of primary salivary gland carcinoma: a bioinformatics study

Salivary gland carcinoma (SGC) is rare cancer, constituting 6% of neoplasms in the head and neck area. The most responsible genes and pathways involved in the pathology of this disorder have not been fully understood. We aimed to identify differentially expressed genes (DEGs), the most critical hub genes, transcription factors, signaling pathways, and biological processes (BPs) associated with the pathogenesis of primary SGC. The mRNA dataset GSE153283 in the Gene Expression Omnibus database was re-analyzed for determining DEGs in cancer tissue of patients with primary SGC compared to the adjacent normal tissue (adjusted p-value < 0.001; |Log2 fold change| > 1). A protein interaction map (PIM) was built, and the main modules within the network were identified and focused on the different pathways and BP analyses. The hub genes of PIM were discovered, and their associated gene regulatory network was built to determine the master regulators involved in the pathogenesis of primary SGC. A total of 137 genes were found to be differentially expressed in primary SGC. The most significant pathways and BPs that were deregulated in the primary disease condition were associated with the cell cycle and fibroblast proliferation procedures. TP53, EGF, FN1, NOTCH1, EZH2, COL1A1, SPP1, CDKN2A, WNT5A, PDGFRB, CCNB1, and H2AFX were demonstrated to be the most critical genes linked with the primary SGC. SPIB, FOXM1, and POLR2A significantly regulate all the hub genes. This study illustrated several hub genes and their master regulators that might be appropriate targets for the therapeutic aims of primary SGC.

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.

CREB1K292 and HINFPK330 as Putative Common Therapeutic Targets in Alzheimer's and Parkinson's Disease

Integration of omics data and deciphering the mechanism of a biological regulatory network could be a promising approach to reveal the molecular mechanism involved in the progression of complex diseases, including Alzheimer's and Parkinson's. Despite having an overlapping mechanism in the etiology of Alzheimer's disease (AD) and Parkinson's disease (PD), the exact mechanism and signaling molecules behind them are still unknown. Further, the acetylation mechanism and histone deacetylase (HDAC) enzymes provide a positive direction toward studying the shared phenomenon between AD and PD pathogenesis. For instance, increased expression of HDACs causes a decrease in protein acetylation status, resulting in decreased cognitive and memory function. Herein, we employed an integrative approach to analyze the transcriptomics data that established a potential relationship between AD and PD. Data preprocessing and analysis of four publicly available microarray datasets revealed 10 HUB proteins, namely, CDC42, CD44, FGFR1, MYO5A, NUMA1, TUBB4B, ARHGEF9, USP5, INPP5D, and NUP93, that may be involved in the shared mechanism of AD and PD pathogenesis. Further, we identified the relationship between the HUB proteins and transcription factors that could be involved in the overlapping mechanism of AD and PD. CREB1 and HINFP were the crucial regulatory transcription factors that were involved in the AD and PD crosstalk. Further, lysine acetylation sites and HDAC enzyme prediction revealed the involvement of 15 and 27 potential lysine residues of CREB1 and HINFP, respectively. Our results highlighted the importance of HDAC1(K292) and HDAC6(K330) association with CREB1 and HINFP, respectively, in the AD and PD crosstalk. However, different datasets with a large number of samples and wet lab experimentation are required to validate and pinpoint the exact role of CREB1 and HINFP in the AD and PD crosstalk. It is also possible that the different datasets may or may not affect the results due to analysis parameters. In conclusion, our study potentially highlighted the crucial proteins, transcription factors, biological pathways, lysine residues, and HDAC enzymes shared between AD and PD at the molecular level. The findings can be used to study molecular studies to identify the possible relationship in the AD-PD crosstalk.

Pharmacological Disruption of Phosphorylated Eukaryotic Initiation Factor-2α/Activating Transcription Factor 4/Indian Hedgehog Protects Intervertebral Disc Degeneration via Reducing the Reactive Oxygen Species and Apoptosis of Nucleus Pulposus Cells

Excessive reactive oxygen species (ROS) and apoptosis in nucleus pulposus (NP) cells accelerate the process of intervertebral disc degeneration (IDD). Here, we integrated pathological samples and in vitro and in vivo framework to investigate the impact of phosphorylation of eukaryotic initiation factor-2α (eIF2α)/activating transcription factor 4 (ATF4)/Indian hedgehog (Ihh) signaling in the IDD. From the specimen analysis of the IDD patients, we found phosphorylated eIF2α (p-eIF2α), ATF4 and Ihh protein levels were positively related while the NP tissue went degenerative. In vitro, tumor necrosis factor (TNF)-α caused the NP cell degeneration and induced a cascade of upregulation of p-eIF2α, ATF4, and Ihh. Interestingly, ATF4 could enhance Ihh expression through binding its promoter region, and silencing of ATF4 decreased Ihh and protected the NP cells from degeneration. Moreover, ISRIB inhibited the p-eIF2α, which resulted in a suppression of ATF4/Ihh, and alleviated the TNF-α-induced ROS production and apoptosis of NP cells. On the contrary, further activating p-eIF2α aggravated the NP cell degeneration, with amplification of ATF4/Ihh and a higher level of ROS and apoptosis. Additionally, applying cyclopamine (CPE) to suppress Ihh was efficient to prevent NP cell apoptosis but did not decrease the ROS level. In an instability-induced IDD model in mice, ISRIB suppressed p-eIF2α/ATF4/Ihh and prevented IDD via protecting the anti-oxidative enzymes and decreased the NP cell apoptosis. CPE prevented NP cell apoptosis but did not affect anti-oxidative enzyme expression. Taken together, p-eIF2α/ATF4/Ihh signaling involves the ROS level and apoptosis in NP cells, the pharmacological disruption of which may provide promising methods in preventing IDD.

ΔNp63 is a pioneer factor that binds inaccessible chromatin and elicits chromatin remodeling

BACKGROUND

ΔNp63 is a master transcriptional regulator playing critical roles in epidermal development and other cellular processes. Recent studies suggest that ΔNp63 functions as a pioneer factor that can target its binding sites within inaccessible chromatin and induce chromatin remodeling.

METHODS

In order to examine if ΔNp63 can bind to inaccessible chromatin and to determine if specific histone modifications are required for binding, we induced ΔNp63 expression in two p63-naïve cell lines. ΔNp63 binding was then examined by ChIP-seq and the chromatin at ΔNp63 targets sites was examined before and after binding. Further analysis with competitive nucleosome binding assays was used to determine how ΔNp63 directly interacts with nucleosomes.

RESULTS

Our results show that before ΔNp63 binding, targeted sites lack histone modifications, indicating ΔNp63's capability to bind at unmodified chromatin. Moreover, the majority of the sites that are bound by ectopic ΔNp63 expression exist in an inaccessible state. Once bound, ΔNp63 induces acetylation of the histone and the repositioning of nucleosomes at its binding sites. Further analysis with competitive nucleosome binding assays reveal that ΔNp63 can bind directly to nucleosome edges with significant binding inhibition occurring within 50 bp of the nucleosome dyad.

CONCLUSION

Overall, our results demonstrate that ΔNp63 is a pioneer factor that binds nucleosome edges at inaccessible and unmodified chromatin sites and induces histone acetylation and nucleosome repositioning.

Deletion of Sox9 in the liver leads to hepatic cystogenesis in mice by transcriptionally downregulating Sec63

Hepatic cysts are found in heterogeneous disorders with different pathogeneses, of which simple hepatic cysts and polycystic liver diseases are two major types. The process of hepatic cytogenesis for these two diseases is caused by defects in remodelling of the ductal plate during biliary tract development, which is called ductal plate malformation. SOX9 is a transcription factor participating in the process of bile duct development, and thus, its dysregulation may play important roles in hepatic cystogenesis. SEC63 encodes an endoplasmic reticulum membrane protein that is mutated in human autosomal dominant polycystic liver disease. However, the transcriptional regulation of SEC63 is largely unknown. In the present study, a liver-specific Sox9 knockout (Sox9^LKO ) mouse was generated to investigate the roles and underlying mechanism of SOX9 in hepatic cystogenesis. We found that hepatic cysts began to be observed in Sox9^LKO mice at 6 months of age. The number and size of cysts increased with age in Sox9^LKO mice. In addition, the characteristics of hepatic cytogenesis, including the activation of proliferation, absence of primary cilium, and disorder of polarity in biliary epithelial cells, were detected in the livers of Sox9^LKO mice. RNAi silencing of SOX9 in human intrahepatic biliary epithelial cells (HIBEpic) resulted in increased proliferation and reduced formation of the primary cilium. Moreover, Sec63 was downregulated in primary biliary epithelial cells from Sox9^LKO mice and SEC63 in HIBEpic transfected with siSOX9. Chromatin immunoprecipitation assays and luciferase reporter assays further demonstrated that SOX9 transcriptionally regulated the expression of SEC63 in biliary epithelial cells. Importantly, the overexpression of SEC63 in HIBEpic partially reversed the effects of SOX9 depletion on the formation of primary cilia and cell proliferation. These findings highlight the biological significance of SOX9 in hepatic cytogenesis and elucidate a novel molecular mechanism underlying hepatic cytogenesis. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

What Can Machine Learning Approaches in Genomics Tell Us about the Molecular Basis of Amyotrophic Lateral Sclerosis?

Amyotrophic Lateral Sclerosis (ALS) is the most common late-onset motor neuron disorder, but our current knowledge of the molecular mechanisms and pathways underlying this disease remain elusive. This review (1) systematically identifies machine learning studies aimed at the understanding of the genetic architecture of ALS, (2) outlines the main challenges faced and compares the different approaches that have been used to confront them, and (3) compares the experimental designs and results produced by those approaches and describes their reproducibility in terms of biological results and the performances of the machine learning models. The majority of the collected studies incorporated prior knowledge of ALS into their feature selection approaches, and trained their machine learning models using genomic data combined with other types of mined knowledge including functional associations, protein-protein interactions, disease/tissue-specific information, epigenetic data, and known ALS phenotype-genotype associations. The importance of incorporating gene-gene interactions and cis-regulatory elements into the experimental design of future ALS machine learning studies is highlighted. Lastly, it is suggested that future advances in the genomic and machine learning fields will bring about a better understanding of ALS genetic architecture, and enable improved personalized approaches to this and other devastating and complex diseases.

ROS/NF-κB Signaling Pathway-Mediated Transcriptional Activation of TRIM37 Promotes HBV-Associated Hepatic Fibrosis

Hepatic fibrosis is an inflammatory response that leads to liver cirrhosis in the most advanced condition. Liver cirrhosis is a leading cause of deaths associated with liver diseases; hence, understanding the underlying mechanisms of hepatic fibrosis is critical to develop effective therapies. Tripartite motif (TRIM) family proteins have been shown to be involved in liver fibrosis; however, the exact role of several TRIM proteins in this process remained unexplored. In this study, we investigated the role of TRIM37 in hepatitis B virus (HBV)-associated hepatic fibrosis. We analyzed TRIM37 expression in hepatic fibrosis patients and performed functional and mechanistic studies in tissue culture and mouse models to identify the role of TRIM37 in hepatic fibrosis. We found an increased expression of TRIM37 in hepatic fibrosis patients. Mechanistically, we showed that TRIM37 physically interacts with SMAD7 and promotes ubiquitination-mediated degradation of SMAD7, and that SMAD7 is a key mediator of TRM37-induced hepatic fibrosis. Furthermore, we showed nuclear factor κB (NF-κB) activation mediated by reactive oxygen species (ROS) is necessary for the transcriptional induction of TRIM37 during HBV infection. Our study shows TRIM37 as an important promoter of HBV-associated hepatic fibrosis.

Functional fine-mapping of noncoding risk variants in amyotrophic lateral sclerosis utilizing convolutional neural network

Recent large-scale genome-wide association studies have identified common genetic variations that may contribute to the risk of amyotrophic lateral sclerosis (ALS). However, pinpointing the risk variants in noncoding regions and underlying biological mechanisms remains a major challenge. Here, we constructed a convolutional neural network model with a large-scale GWAS meta-analysis dataset to unravel functional noncoding variants associated with ALS based on their epigenetic features. After filtering and prioritizing of candidates, we fine-mapped two new risk variants, rs2370964 and rs3093720, on chromosome 3 and 17, respectively. Further analysis revealed that these polymorphisms are associated with the expression level of CX3CR1 and TNFAIP1, and affect the transcription factor binding sites for CTCF, NFATc1 and NR3C1. Our results may provide new insights for ALS pathogenesis, and the proposed research methodology can be applied for other complex diseases as well.

Prediction of TF-Binding Site by Inclusion of Higher Order Position Dependencies

Most proposed methods for TF-binding site (TFBS) predictions only use low order dependencies for predictions due to the lack of efficient methods to extract higher order dependencies. In this work, we first propose a novel method to extract higher order dependencies by applying CNN on histone modification features. We then propose a novel TFBS prediction method, referred to as CNN_TF, by incorporating low order and higher order dependencies. CNN_TF is first evaluated on 13 TFs in the mES cell. Results show that using higher order dependencies outperforms low order dependencies significantly on 11 TFs. This indicates that higher order dependencies are indeed more effective for TFBS predictions than low order dependencies. Further experiments show that using both low order dependencies and higher order dependencies improves performance significantly on 12 TFs, indicating the two dependency types are complementary. To evaluate the influence of cell-types on prediction performances, CNN_TF was applied to five TFs in five cell-types of humans. Even though low order dependencies and higher order dependencies show different contributions in different cell-types, they are always complementary in predictions. When comparing to several state-of-the-art methods, CNN_TF outperforms them by at least 5.3 percent in AUPR.

MTTFsite: cross-cell type TF binding site prediction by using multi-task learning

Motivation

The prediction of transcription factor binding sites (TFBSs) is crucial for gene expression analysis. Supervised learning approaches for TFBS predictions require large amounts of labeled data. However, many TFs of certain cell types either do not have sufficient labeled data or do not have any labeled data.

Results

In this paper, a multi-task learning framework (called MTTFsite) is proposed to address the lack of labeled data problem by leveraging on labeled data available in cross-cell types. The proposed MTTFsite contains a shared CNN to learn common features for all cell types and a private CNN for each cell type to learn private features. The common features are aimed to help predicting TFBSs for all cell types especially those cell types that lack labeled data. MTTFsite is evaluated on 241 cell type TF pairs and compared with a baseline method without using any multi-task learning model and a fully shared multi-task model that uses only a shared CNN and do not use private CNNs. For cell types with insufficient labeled data, results show that MTTFsite performs better than the baseline method and the fully shared model on more than 89% pairs. For cell types without any labeled data, MTTFsite outperforms the baseline method and the fully shared model by more than 80 and 93% pairs, respectively. A novel gene expression prediction method (called TFChrome) using both MTTFsite and histone modification features is also presented. Results show that TFBSs predicted by MTTFsite alone can achieve good performance. When MTTFsite is combined with histone modification features, a significant 5.7% performance improvement is obtained.

Availability and implementation

The resource and executable code are freely available at http://hlt.hitsz.edu.cn/MTTFsite/ and http://www.hitsz-hlt.com:8080/MTTFsite/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Convolutional neural network model to predict causal risk factors that share complex regulatory features

Major progress in disease genetics has been made through genome-wide association studies (GWASs). One of the key tasks for post-GWAS analyses is to identify causal noncoding variants with regulatory function. Here, on the basis of >2000 functional features, we developed a convolutional neural network framework for combinatorial, nonlinear modeling of complex patterns shared by risk variants scattered among multiple associated loci. When applied for major psychiatric disorders and autoimmune diseases, neural and immune features, respectively, exhibited high explanatory power while reflecting the pathophysiology of the relevant disease. The predicted causal variants were concentrated in active regulatory regions of relevant cell types and tended to be in physical contact with transcription factors while residing in evolutionarily conserved regions and resulting in expression changes of genes related to the given disease. We demonstrate some examples of novel candidate causal variants and associated genes. Our method is expected to contribute to the identification and functional interpretation of potential causal noncoding variants in post-GWAS analyses.

Enhancing of Particle Swarm Optimization Based Method for Multiple Motifs Detection in DNA Sequences Collections

Genome sequence data consists of DNA sequences or input sequences. Each one includes nucleotides with chemical structures presented as characters: ^'A^', ^'C^',^' G^', and 'T', and groups of motif sequences, called Transcription Factor Binding Sites (TFBSs), which are subsequences of DNA that lead to protein-synthesis. The detection of TFBSs is an important problem for bioinformatics research. With the similar patterns of motif sequences in TFBSs, computational algorithms for TFBSs detection have been improved to reduce resources used in laboratory setting. The metaheuristic algorithm is the important issue that has been continually improved to detect TFBSs with greater precision and recall. This paper proposes PSO_HD by applying Particle Swarm Optimization (PSO) as a pre-process and using Hamming distance to improve the efficiency of detecting TFBSs with more precision and recall. In order to measure its efficiency, the paper compares the TFBSs detection using PSO_HD algorithm with relevant algorithms in eight datasets. F-score is used as a measurement unit and compared to the related algorithms. The experimental results show that PSO_HD algorithm gives the highest average F-score, which can be indicated that the PSO_HD algorithm can improve the efficiency of detecting TFBSs with more precision and recall.

p16 deficiency attenuates intervertebral disc degeneration by adjusting oxidative stress and nucleus pulposus cell cycle

The cell cycle regulator p16 is known as a biomarker and an effector of aging. However, its function in intervertebral disc degeneration (IVDD) is unclear. In this study, p16 expression levels were found to be positively correlated with the severity of human IVDD. In a mouse tail suspension (TS)-induced IVDD model, lumbar intervertebral disc height index and matrix protein expression levels were reduced significantly were largely rescued by p16 deletion. In TS mouse discs, reactive oxygen species levels, proportions of senescent cells, and the senescence-associated secretory phenotype (SASP) were all increased, cell cycling was delayed, and expression was downregulated for Sirt1, superoxide dismutase 1/2, cyclin-dependent kinases 4/6, phosphorylated retinoblastoma protein, and transcription factor E2F1/2. However, these effects were rescued by p16 deletion. Our results demonstrate that p16 plays an important role in IVDD pathogenesis and that its deletion attenuates IVDD by promoting cell cycle and inhibiting SASP, cell senescence, and oxidative stress.

Neck and shoulder pain, lower back pain and leg numbness are conditions that many people will encounter as years go by. This is because intervertebral discs, the padding structures that fit between the bones in the spine, degenerate with age: their cells enter a ‘senescent’, inactive state, and stop multiplying.

A protein known as p16, an important regulator of cell growth and division, is known to accumulate in senescent cells. In fact, in mouse fat tissue, muscles or eyes, removing the cells that contain high levels of p16 delays aging-associated disorders. However, it was still unknown whether deactivating the gene that codes p16 in senescent cells could delay disc degeneration.

Here, Che, Li et al. discovered that p16 is highly present in the senescent cells of severely degenerated human intervertebral discs. The cells in the nucleus pulposus, the jelly-like and most critical tissue in the intervertebral discs, were extracted and grown in the lab under conditions that replicate the early stages of damage to the spine. Drugs and genetic manipulations were then used to decrease the amount of p16 in these cells.

The experiments showed that reducing the levels of p16 results in the senescent cells multiplying more and showing fewer signs of damage and aging. In addition, the discs of mice in which the gene that codes for p16 had been deleted were less prone to degeneration compared to ‘normal’ mice in similar conditions.

Overall, the work by Che, Li et al. shows that inhibiting p16 in disc cells delays the aging process and reduces the degeneration of intervertebral discs. These findings may one day be applicable to people with intervertebral disc diseases who, for example, could potentially benefit from a gene therapy targeting the cells which produce p16.

Eukaryotic transcription factors can track and control their target genes using DNA antennas

Eukaryotic transcription factors (TF) function by binding to short 6-10 bp DNA recognition sites located near their target genes, which are scattered through vast genomes. Such process surmounts enormous specificity, efficiency and celerity challenges using a molecular mechanism that remains poorly understood. Combining biophysical experiments, theory and bioinformatics, we dissect the interplay between the DNA-binding domain of Engrailed, a Drosophila TF, and the regulatory regions of its target genes. We find that Engrailed binding affinity is strongly amplified by the DNA regions flanking the recognition site, which contain long tracts of degenerate recognition-site repeats. Such DNA organization operates as an antenna that attracts TF molecules in a promiscuous exchange among myriads of intermediate affinity binding sites. The antenna ensures a local TF supply, enables gene tracking and fine control of the target site's basal occupancy. This mechanism illuminates puzzling gene expression data and suggests novel engineering strategies to control gene expression.

MYC and Twist1 cooperate to drive metastasis by eliciting crosstalk between cancer and innate immunity

Metastasis is a major cause of cancer mortality. We generated an autochthonous transgenic mouse model whereby conditional expression of MYC and Twist1 enables hepatocellular carcinoma (HCC) to metastasize in >90% of mice. MYC and Twist1 cooperate and their sustained expression is required to elicit a transcriptional program associated with the activation of innate immunity, through secretion of a cytokinome that elicits recruitment and polarization of tumor associated macrophages (TAMs). Systemic treatment with Ccl2 and Il13 induced MYC-HCCs to metastasize; whereas, blockade of Ccl2 and Il13 abrogated MYC/Twist1-HCC metastasis. Further, in 33 human cancers (n = 9502) MYC and TWIST1 predict poor survival (p=4.3×10⁻¹⁰), CCL2/IL13 expression (p<10⁻¹⁰⁹) and TAM infiltration (p<10⁻⁹⁶). Finally, in the plasma of patients with HCC (n = 25) but not cirrhosis (n = 10), CCL2 and IL13 were increased and IL13 predicted invasive tumors. Therefore, MYC and TWIST1 generally appear to cooperate in human cancer to elicit a cytokinome that enables metastasis through crosstalk between cancer and immune microenvironment.

Cancer develops when cells in the body gain mutations that allow them to grow and divide rapidly and uncontrollably. As the disease progresses these cancer cells develop the ability to spread around the body. This process of spreading, called metastasis, is responsible for most cancer-related deaths in humans, but no current treatments target it.

Mutations that increase the levels of two proteins known as MYC and TWIST1 in cells cause many human cancers. In healthy adult cells, normal levels of MYC and TWIST1 act as key regulators that switch thousands of genes on or off. TWIST1 is known to control the movement and spread of cells in the embryo. However, it is not known how MYC and TWIST1 work together to promote the metastasis of cancer cells.

To address this question, Dhanasekaran, Baylot et al. used mice to investigate the roles of MYC and TWIST1 in the metastasis of cancer cells. The experiments showed that these two proteins work together to reprogram mouse cancer cells to release signal molecules known as cytokines. These molecules convert immune cells known as macrophages to a tumor-friendly state that allows cancers cells to spread around the body. Inhibiting two cytokines known as CCL2 and IL13 prevented the cancer cells from moving.

Further experiments analyzed tumor samples from around 10,000 human patients with 33 different cancers. This revealed that patients that had higher levels of MYC and TWIST1 proteins in their tumors also had increased levels of CCL2 and IL13, more activated macrophages and were less likely to recover from their cancer.

The findings of Dhanasekaran, Baylot et al. suggest that MYC and TWIST1 may instigate metastasis in many human cancers, and therapies targeting specific cytokines may prevent these cancers from spreading around the body. Furthermore, screening blood for the levels of cytokines may help to identify the cancer patients who would benefit from such therapies.

A gene regulatory network explains RET-EDNRB epistasis in Hirschsprung disease

Disruptions in gene regulatory networks (GRNs), driven by multiple deleterious variants, potentially underlie complex traits and diseases. Hirschsprung disease (HSCR), a multifactorial disorder of enteric nervous system (ENS) development, is associated with at least 24 genes and seven chromosomal loci, with RET and EDNRB as its major genes. We previously demonstrated that RET transcription in the ENS is controlled by an extensive GRN involving the transcription factors (TFs) RARB, GATA2 and SOX10 and other HSCR genes. We now demonstrate, using human and mouse cellular and animal models, that EDNRB is transcriptionally regulated in the ENS by GATA2, SOX10 and NKX2.5 TFs. Significantly, RET and EDNRB expression is regulated by their shared use of GATA2 and SOX10, and in turn, these TFs are controlled by EDNRB and RET in a dose-dependent manner. This study expands the ENS development GRN to include both RET and EDNRB, uncovers the mechanistic basis for RET-EDNRB epistasis and emphasizes how functionally different genes associated with a complex disorder can be united through a common GRN.

Predicting functional variants in enhancer and promoter elements using RegulomeDB

Here we present a computational model, Score of Unified Regulatory Features (SURF), that predicts functional variants in enhancer and promoter elements. SURF is trained on data from massively parallel reporter assays and predicts the effect of variants on reporter expression levels. It achieved the top performance in the Fifth Critical Assessment of Genome Interpretation "Regulation Saturation" challenge. We also show that features queried through RegulomeDB, which are direct annotations from functional genomics data, help improve prediction accuracy beyond transfer learning features from DNA sequence-based deep learning models. Some of the most important features include DNase footprints, especially when coupled with complementary ChIP-seq data. Furthermore, we found our model achieved good performance in predicting allele-specific transcription factor binding events. As an extension to the current scoring system in RegulomeDB, we expect our computational model to prioritize variants in regulatory regions, thus help the understanding of functional variants in noncoding regions that lead to disease.

Hamiltonian energy as an efficient approach to identify the significant key regulators in biological networks

The topological characteristics of biological networks enable us to identify the key nodes in terms of modularity. However, due to a large size of the biological networks with many hubs and functional modules across intertwined layers within the network, it often becomes difficult to accomplish the task of identifying potential key regulators. We use for the first time a generalized formalism of Hamiltonian Energy (HE) with a recursive approach. The concept, when applied to the Apoptosis Regulatory Gene Network (ARGN), helped us identify 11 Motif hubs (MHs), which influenced the network up to motif levels. The approach adopted allowed to classify MHs into 5 significant motif hubs (S-MHs) and 6 non-significant motif hubs (NS-MHs). The significant motif hubs had a higher HE value and were considered as high-active key regulators; while the non-significant motif hubs had a relatively lower HE value and were considered as low-active key regulators, in network control mechanism. Further, we compared the results of the HE analyses with the topological characterization, after subjecting to the three conditions independently: (i) removing all MHs, (ii) removing only S-MHs, and (iii) removing only NS-MHs from the ARGN. This procedure allowed us to cross-validate the role of 5 S-MHs, NFk-B1, BRCA1, CEBPB, AR, and POU2F1 as the potential key regulators. The changes in HE calculations further showed that the removal of 5 S-MHs could cause perturbation at all levels of the network, a feature not discernible by topological analysis alone.

JASPAR 2018: update of the open-access database of transcription factor binding profiles and its web framework

JASPAR (http://jaspar.genereg.net) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) and TF flexible models (TFFMs) for TFs across multiple species in six taxonomic groups. In the 2018 release of JASPAR, the CORE collection has been expanded with 322 new PFMs (60 for vertebrates and 262 for plants) and 33 PFMs were updated (24 for vertebrates, 8 for plants and 1 for insects). These new profiles represent a 30% expansion compared to the 2016 release. In addition, we have introduced 316 TFFMs (95 for vertebrates, 218 for plants and 3 for insects). This release incorporates clusters of similar PFMs in each taxon and each TF class per taxon. The JASPAR 2018 CORE vertebrate collection of PFMs was used to predict TF-binding sites in the human genome. The predictions are made available to the scientific community through a UCSC Genome Browser track data hub. Finally, this update comes with a new web framework with an interactive and responsive user-interface, along with new features. All the underlying data can be retrieved programmatically using a RESTful API and through the JASPAR 2018 R/Bioconductor package.

Shiny-Seq: advanced guided transcriptome analysis

Objective

A comprehensive analysis of RNA-Seq data uses a wide range of different tools and algorithms, which are normally limited to R users only. While several tools and advanced analysis pipelines are available, some require programming skills and others lack the support for many important features that enable a more comprehensive data analysis. There is thus, a need for a guided and easy to use comprehensive RNA-Seq data platform, which integrates the state of the art analysis workflow.

Results

We present the tool Shiny-Seq, which provides a guided and easy to use comprehensive RNA-Seq data analysis pipeline. It has many features such as batch effect estimation and removal, quality check with several visualization options, enrichment analysis with multiple biological databases, identification of patterns using advanced methods such as weighted gene co-expression network analysis, summarizing analysis as power point presentation and all results as tables via a one-click feature. The source code is published on GitHub (https://github.com/schultzelab/Shiny-Seq) and licensed under GPLv3. Shiny-Seq is written in R using the Shiny framework. In addition, the application is hosted on a public website hosted by the shinyapps.io server (https://schultzelab.shinyapps.io/Shiny-Seq/) and as a Docker image https://hub.docker.com/r/makaho/shiny-seq.

A screen for deeply conserved non-coding GWAS SNPs uncovers a MIR-9-2 functional mutation associated to retinal vasculature defects in human

Thousands of human disease-associated single nucleotide polymorphisms (SNPs) lie in the non-coding genome, but only a handful have been demonstrated to affect gene expression and human biology. We computationally identified risk-associated SNPs in deeply conserved non-exonic elements (CNEs) potentially contributing to 45 human diseases. We further demonstrated that human CNE1/rs17421627 associated with retinal vasculature defects showed transcriptional activity in the zebrafish retina, while introducing the risk-associated allele completely abolished CNE1 enhancer activity. Furthermore, deletion of CNE1 led to retinal vasculature defects and to a specific downregulation of microRNA-9, rather than MEF2C as predicted by the original genome-wide association studies. Consistent with these results, miR-9 depletion affects retinal vasculature formation, demonstrating MIR-9-2 as a critical gene underpinning the associated trait. Importantly, we validated that other CNEs act as transcriptional enhancers that can be disrupted by conserved non-coding SNPs. This study uncovers disease-associated non-coding mutations that are deeply conserved, providing a path for in vivo testing to reveal their cis-regulated genes and biological roles.

Cross-Cell-Type Prediction of TF-Binding Site by Integrating Convolutional Neural Network and Adversarial Network

Transcription factor binding sites (TFBSs) play an important role in gene expression regulation. Many computational methods for TFBS prediction need sufficient labeled data. However, many transcription factors (TFs) lack labeled data in cell types. We propose a novel method, referred to as DANN_TF, for TFBS prediction. DANN_TF consists of a feature extractor, a label predictor, and a domain classifier. The feature extractor and the domain classifier constitute an Adversarial Network, which ensures that learned features are common features across different cell types. DANN_TF is evaluated on five TFs in five cell types with a total of 25 cell-type TF pairs and compared to a baseline method which does not use Adversarial Network. For both data augmentation and cross-cell-type prediction, DANN_TF performs better than the baseline method on most cell-type TF pairs. DANN_TF is further evaluated by an additional 13 TFs in the five cell types with a total of 65 cell-type TF pairs. Results show that DANN_TF achieves significantly higher AUC than the baseline method on 96.9% pairs of the 65 cell-type TF pairs. This is a strong indication that DANN_TF can indeed learn common features for cross-cell-type TFBS prediction.

HiCDB: a sensitive and robust method for detecting contact domain boundaries

Contact domains are closely linked to gene regulation and lineage commitment, while current understanding of contact domains and their boundaries is still limited. Here, we present a novel method HiCDB, which is constructively based on local relative insulation metric and multi-scale aggregation approach to detect contact domain boundaries (CDBs) on Hi-C maps. Compared with other ‘state-of-art’ methods, HiCDB shows improved sensitivity and specificity in determining CDBs at various Hi-C resolutions. The superiority of HiCDB enabled us to study the epigenetic features of detected CDBs and showed enrichment of architectural proteins and cell-type-specific transcription factor binding sites at CDBs. The further comparison of GM12878 and IMR90 Hi-C datasets suggested that cell-type-specific CDBs are marked by active regulatory signals and correlate with activation of nearby cell identity genes.

Independent erosion of conserved transcription factor binding sites points to shared hindlimb, vision and external testes loss in different mammals

Genetic variation in cis-regulatory elements is thought to be a major driving force in morphological and physiological changes. However, identifying transcription factor binding events that code for complex traits remains a challenge, motivating novel means of detecting putatively important binding events. Using a curated set of 1154 high-quality transcription factor motifs, we demonstrate that independently eroded binding sites are enriched for independently lost traits in three distinct pairs of placental mammals. We show that these independently eroded events pinpoint the loss of hindlimbs in dolphin and manatee, degradation of vision in naked mole-rat and star-nosed mole, and the loss of external testes in white rhinoceros and Weddell seal. We additionally show that our method may also be utilized with more than two species. Our study exhibits a novel methodology to detect cis-regulatory mutations which help explain a portion of the molecular mechanism underlying complex trait formation and loss.

Transcription factors–DNA interactions in rice: identification and verification

The completion of the rice genome sequence paved the way for rice functional genomics research. Additionally, the functional characterization of transcription factors is currently a popular and crucial objective among researchers. Transcription factors are one of the groups of proteins that bind to either enhancer or promoter regions of genes to regulate expression. On the basis of several typical examples of transcription factor analyses, we herein summarize selected research strategies and methods and introduce their advantages and disadvantages. This review may provide some theoretical and technical guidelines for future investigations of transcription factors, which may be helpful to develop new rice varieties with ideal traits.

Pancreatic islet chromatin accessibility and conformation reveals distal enhancer networks of type 2 diabetes risk

Genetic variants affecting pancreatic islet enhancers are central to T2D risk, but the gene targets of islet enhancer activity are largely unknown. We generate a high-resolution map of islet chromatin loops using Hi-C assays in three islet samples and use loops to annotate target genes of islet enhancers defined using ATAC-seq and published ChIP-seq data. We identify candidate target genes for thousands of islet enhancers, and find that enhancer looping is correlated with islet-specific gene expression. We fine-map T2D risk variants affecting islet enhancers, and find that candidate target genes of these variants defined using chromatin looping and eQTL mapping are enriched in protein transport and secretion pathways. At IGF2BP2, a fine-mapped T2D variant reduces islet enhancer activity and IGF2BP2 expression, and conditional inactivation of IGF2BP2 in mouse islets impairs glucose-stimulated insulin secretion. Our findings provide a resource for studying islet enhancer function and identifying genes involved in T2D risk.

Risk loci for type 2 diabetes (T2D) reside in pancreatic islet enhancers. Here, the authors generate high-resolution maps of islet chromatin conformation using Hi-C which they combine with ATAC-seq and ChIP-seq data to annotate candidate target genes of enhancers and validate IGF2BP2 activity in mouse islets.

MD-SVM: a novel SVM-based algorithm for the motif discovery of transcription factor binding sites

BACKGROUND

Transcription factors (TFs) play important roles in the regulation of gene expression. They can activate or block transcription of downstream genes in a manner of binding to specific genomic sequences. Therefore, motif discovery of these binding preference patterns is of central significance in the understanding of molecular regulation mechanism. Many algorithms have been proposed for the identification of transcription factor binding sites. However, it remains a challengeable problem.

RESULTS

Here, we proposed a novel motif discovery algorithm based on support vector machine (MD-SVM) to learn a discriminative model for TF binding sites. MD-SVM firstly obtains position weight matrix (PWM) from a set of training datasets. Then it translates the MD problem into a computational framework of multiple instance learning (MIL). It was applied to several real biological datasets. Results show that our algorithm outperforms MI-SVM in terms of both accuracy and specificity.

CONCLUSIONS

In this paper, we modeled the TF motif discovery problem as a MIL optimization problem. The SVM algorithm was adapted to discriminate positive and negative bags of instances. Compared to other svm-based algorithms, MD-SVM show its superiority over its competitors in term of ROC AUC. Hopefully, it could be of benefit to the research community in the understanding of molecular functions of DNA functional elements and transcription factors.

The miR206-JunD Circuit Mediates the Neurotoxic Effect of Methylmercury in Cortical Neurons

Methylmercury (MeHg) causes neuronal death through different pathways. Particularly, we found that in cortical neurons it increased the expression of Repressor Element-1 Silencing Transcription Factor (REST), histone deacetylase (HDAC)4, Specificity Protein (Sp)1, Sp4, and reduced the levels of brain-derived neurotrophic factor (BDNF). Herein, in rat cortical neurons we investigated whether microRNA (miR)206 can modulate MeHg-induced cell death by regulating REST/HDAC4/Sp1/Sp4/BDNF axis. MeHg (1 µM) reduced miR206 expression after both 12 and 24 h and miR206 transfection prevented MeHg-induced neuronal death. Furthermore, miR206 reverted MeHg-induced REST and Sp4 increase and BDNF reduction at gene and protein level, and reverted HDAC4 protein increase, but not HDAC4 mRNA upregulation. Moreover, since no miR206 seed sequences were identified in the 3'-untranslated regions (3'-UTRs) of REST and SP4, we investigated the role of JunD, that presents a consensus motif on REST, Sp4, and BDNF promoters. Indeed, MeHg increased JunD mRNA and protein levels, and JunD knockdown counteracted MeHg-induced REST, Sp4 increase, but not BDNF reduction. Furthermore, we identified a miR206 binding site in the 3'-UTR of JunD mRNA (miR206/JunD) and mutagenesis of miR206/JunD site reverted JunD luciferase activity reduction induced by miR206. Finally, miR206 prevented MeHg-increased JunD binding to REST and Sp4 promoters, and MeHg-reduced BDNF expression was determined by the increase of HDAC4 binding on BDNF promoter IV. Collectively, these results suggest that miR206 downregulation induced by MeHg exposure determines an upregulation of HDAC4, that in turn downregulated BDNF, and the activation of JunD that, by binding REST and Sp4 gene promoters, increased their expression.

HCP5 is a SMAD3-responsive long non-coding RNA that promotes lung adenocarcinoma metastasis via miR-203/SNAI axis

Introduction: Transforming growth factor-beta (TGFβ) signaling plays a vital role in lung adenocarcinoma (LUAD) progression. However, the involvement of TGFβ-regulated long non-coding RNAs (lncRNAs) in metastasis of LUAD remains poorly understood.

Methods: We performed bioinformatic analyses to identify putative lncRNAs regulated by TGF-β/SMAD3 and validated the results by quantitative PCR in LUAD cells. We performed luciferase reporter and chromatin immunoprecipitation assays to demonstrate the transcriptional regulation of the lncRNA histocompatibility leukocyte antigen complex P5 (HCP5) we decided to focus on. Stable HCP5 knockdown and HCP5-overexpressing A549 cell variants were generated respectively, to study HCP5 function and understand its mechanism of action. We also confirmed our findings in mouse xenografts and metastasis models. We analyzed the correlation between the level of lncRNA expression with EGFR, KRAS mutations, smoke state and prognostic of LUAD patients.

Results: We found that the lncRNA HCP5 is induced by TGFβ and transcriptionally regulated by SMAD3, which promotes LUAD tumor growth and metastasis. Moreover, HCP5 is overexpressed in tumor tissues of patients with LUAD, specifically in patients with EGFR and KRAS mutations and current smoker. HCP5 high expression level is positively correlated with poor prognosis of patients with LUAD. Finally, we demonstrated that upregulation of HCP5 increases the expression of Snail and Slug by sponging the microRNA-203 (miR-203) and promoting epithelial-mesenchymal transition (EMT) in LUAD cells.

Conclusions: Our work demonstrates that the lncRNA HCP5 is transcriptionally regulated by SMAD3 and acts as a new regulator in the TGFβ/SMAD signaling pathway. Therefore, HCP5 can serve as a potential therapeutic target in LUAD.