TFCat: the curated catalog of mouse and human transcription factors

Comparative transcriptome analysis of transcultured human skin-derived precursors (tSKPs) from adherent monolayer culture system and tSKPs-derived fibroblasts (tFBs) by RNA-Seq

Transcultured human skin derived precursors (tSKPs) from adherent monolayer culture system have similar characteristics as traditional skin derived precursors (SKPs), making tSKPs a suitable candidate for regenerative medicine. tSKPs can differentiate into fibroblasts. However, little is known about the molecular mechanism of the transition from tSKPs to fibroblasts. Here, we compared the transcriptional profiles of human tSKPs and tSKPs-derived fibroblasts (tFBs) by RNA-Sequence aiming to determine the candidate genes and pathways involving in the differentiation process. A total of 1042 differentially expressed genes (DEGs) were identified between tSKPs and tFBs, with 490 genes up-regulated and 552 genes down-regulated. Our study showed that these DEGs were significantly enriched in tumor necrosis factor signaling pathway, focal adhesion, extracellular matrix-receptor interaction and phosphatidylinositol 3 kinase (PI3K)/protein kinase B (Akt) signaling pathway. A further transcription factors (TFs) analysis of DEGs revealed the significantly down-expressed TFs (p21, Foxo1and Foxc1) in tFBs were mostly the downstream nodes of PI3K-Akt signaling pathway, which suggested PI3K-Akt signaling pathway might play an important role in tSKPs differentiation. The results of our study are useful for investigating the molecular mechanisms in tSKPs differentiation into tFBs, making it possible to take advantage of their potential application in regenerative medicine.

Skewed X-Chromosome Inactivation and Compensatory Upregulation of Escape Genes Precludes Major Clinical Symptoms in a Female With a Large Xq Deletion

In mammalian females, X-chromosome inactivation (XCI) acts as a dosage compensation mechanism that equalizes X-linked genes expression between homo- and heterogametic sexes. However, approximately 12–23% of X-linked genes escape from XCI, being bi-allelic expressed. Herein, we report on genetic and functional data from an asymptomatic female of a Fragile X syndrome family, who harbors a large deletion on the X-chromosome. Array-CGH uncovered that the de novo, terminal, paternally originated 32 Mb deletion on Xq25-q28 spans 598 RefSeq genes, including escape and variable escape genes. Androgen receptor (AR) and retinitis pigmentosa 2 (RP2) methylation assays showed extreme skewed XCI ratios from both peripheral blood and buccal mucosa, silencing the abnormal X-chromosome. Surprisingly, transcriptome-wide analysis revealed that escape and variable escape genes spanning the deletion are mostly upregulated on the active X-chromosome, precluding major clinical/cognitive phenotypes in the female. Metaphase high count, hemizygosity concordance for microsatellite markers, and monoallelic expression of genes within the deletion suggest the absence of mosaicism in both blood and buccal mucosa. Taken together, our data suggest that an additional protective gene-by-gene mechanism occurs at the transcriptional level in the active X-chromosome to counterbalance detrimental phenotype effects of large Xq deletions.

Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data

We developed Lisa (http://lisa.cistrome.org/) to predict the transcriptional regulators (TRs) of differentially expressed or co-expressed gene sets. Based on the input gene sets, Lisa first uses histone mark ChIP-seq and chromatin accessibility profiles to construct a chromatin model related to the regulation of these genes. Using TR ChIP-seq peaks or imputed TR binding sites, Lisa probes the chromatin models using in silico deletion to find the most relevant TRs. Applied to gene sets derived from targeted TF perturbation experiments, Lisa boosted the performance of imputed TR cistromes and outperformed alternative methods in identifying the perturbed TRs.

MYC regulates coelomocytes apoptosis by targeting Bax expression in sea cucumber Apostichopus japonicus

Myelocytomatosis viral oncogene (MYC), a multifunctional transcription factor, (TF) exerts various physiological and pathological effects on animals. AjMYC could induce coelomocyte apoptosis in Apostichopus japonicus, but the underlying molecular mechanism remains poorly understood. In this study, the promoter sequence of apoptosis regulator Bcl-2-associated X (Bax) was cloned by genomic walking. The AjBax promoter region spaning 1189 bp, containing several transcription factor binding sites, included four potential E-boxes (-1030 bp to -1019 bp, -785 bp to -774 bp, -570 bp to -559 bp, -100 bp to -89 bp), two P53 binding sites (-439 bp to -430 bp, -845 bp to -836 bp), and one NF-κB site (-191 bp to -182 bp). Transient transfection of EPC cells with 5'-deletion constructs linked to luciferase reporter revealed that the region -1189/+454 contributed importantly to the expression of the AjBax. In addition, the AjBax promoter was induced by LPS, PGN or MAN. The four potential MYC binding sites were cotransfected with AjMYC in EPC cell whether AjMYC could activate AjBax expression as a transcriptional factor. Only P1 (-1189/+454) fragment containing the first MYC binding site transfection increased the luciferase activity by 2.08-fold (p < 0.01) compared with the control. The first MYC binding site -1030/-1019 was essential to induce AjBax transcription. Further functional assay indicated that AjBax was significantly induced by 3.54-fold increase (p < 0.01) after AjMYC overexpression in sea cucumber coelomocytes. All our findings supported that AjMYC could regulate coelomocyte apoptosis by directly targeting AjBax expression in A. japonicus.

PanglaoDB: a web server for exploration of mouse and human single-cell RNA sequencing data

Single-cell RNA sequencing is an increasingly used method to measure gene expression at the single cell level and build cell-type atlases of tissues. Hundreds of single-cell sequencing datasets have already been published. However, studies are frequently deposited as raw data, a format difficult to access for biological researchers due to the need for data processing using complex computational pipelines. We have implemented an online database, PanglaoDB, accessible through a user-friendly interface that can be used to explore published mouse and human single cell RNA sequencing studies. PanglaoDB contains pre-processed and pre-computed analyses from more than 1054 single-cell experiments covering most major single cell platforms and protocols, based on more than 4 million cells from a wide range of tissues and organs. The online interface allows users to query and explore cell types, genetic pathways and regulatory networks. In addition, we have established a community-curated cell-type marker compendium, containing more than 6000 gene-cell-type associations, as a resource for automatic annotation of cell types.

Transcriptional Signature Derived from Murine Tumor-Associated Macrophages Correlates with Poor Outcome in Breast Cancer Patients

Tumor-associated macrophages (TAMs) are frequently the most abundant immune cells in cancers and are associated with poor survival. Here, we generated TAM molecular signatures from K14cre;Cdh1flox/flox;Trp53flox/flox (KEP) and MMTV-NeuT (NeuT) transgenic mice that resemble human invasive lobular carcinoma (ILC) and HER2+ tumors, respectively. Determination of TAM-specific signatures requires comparison with healthy mammary tissue macrophages to avoid overestimation of gene expression differences. TAMs from the two models feature a distinct transcriptomic profile, suggesting that the cancer subtype dictates their phenotype. The KEP-derived signature reliably correlates with poor overall survival in ILC but not in triple-negative breast cancer patients, indicating that translation of murine TAM signatures to patients is cancer subtype dependent. Collectively, we show that a transgenic mouse tumor model can yield a TAM signature relevant for human breast cancer outcome prognosis and provide a generalizable strategy for determining and applying immune cell signatures provided the murine model reflects the human disease.

Expression of Protein-Coding Gene Orthologs in Zebrafish and Mouse Inner Ear Non-sensory Supporting Cells

Non-mammalian vertebrates, including zebrafish, retain the ability to regenerate hair cells (HCs) due to unknown molecular mechanisms that regulate proliferation and conversion of non-sensory supporting cells (nsSCs) to HCs. This regenerative capacity is not conserved in mammals. Identification of uniquely expressed orthologous genes in zebrafish nsSCs may reveal gene candidates involved in the proliferation and transdifferentiation of zebrafish nsSCs to HCs in the inner ear. A list of orthologous protein-coding genes was generated based on an Ensembl Biomart comparison of the zebrafish and mouse genomes. Our previously published RNA-seq-based transcriptome datasets of isolated inner ear zebrafish nsSCs and HCs, and mouse non-sensory supporting pillar and Deiters’ cells, and HCs, were merged to analyze gene expression patterns between the two species. Out of 17,498 total orthologs, 11,752 were expressed in zebrafish nsSCs and over 10,000 orthologs were expressed in mouse pillar and Deiters’ cells. Differentially expressed genes common among the zebrafish nsSCs and mouse pillar and Deiters’ cells, compared to species-specific HCs, included 306 downregulated and 314 upregulated genes; however, over 1,500 genes were uniquely upregulated in zebrafish nsSCs. Functional analysis of genes uniquely expressed in nsSCs identified several transcription factors associated with cell fate determination, cell differentiation and nervous system development, indicating inherent molecular properties of nsSCs that promote self-renewal and transdifferentiation into new HCs. Our study provides a means of characterizing these orthologous genes, involved in proliferation and transdifferentiation of nsSCs to HCs in zebrafish, which may lead to identification of potential targets for HC regeneration in mammals.

The Transcription Factor Function of Parkin: Breaking the Dogma

PRKN (PARK2) is a key gene involved in both familial and sporadic Parkinson’s disease that encodes parkin (PK). Since its discovery by the end of the 90s, both functional and more recently, structural studies led to a consensual view of PK as an E3 ligase only. It is generally considered that this function conditions the cellular load of a subset of cytosolic proteins prone to proteasomal degradation and that a loss of E3 ligase function triggers an accumulation of potentially toxic substrates and, consequently, a neuronal loss. Furthermore, PK molecular interplay with PTEN-induced kinase 1 (PINK1), a serine threonine kinase also involved in recessive cases of Parkinson’s disease, is considered to underlie the mitophagy process. Thus, since mitochondrial homeostasis significantly governs cell health, there is a huge interest of the scientific community centered on PK function. In 2009, we have demonstrated that PK could also act as a transcription factor (TF) and induces neuroprotection via the downregulation of the pro-apoptotic and tumor suppressor factor, p53. Importantly, the DNA-binding properties of PK and its nuclear localization suggested an important role in the control of several genes. The duality of PK subcellular localization and of its associated ubiquitin ligase and TF functions suggests that PK could behave as a key molecular modulator of various physiological cellular signaling pathways that could be disrupted in pathological contexts. Here, we update the current knowledge on PK direct and indirect TF-mediated control of gene expression.

The Human Transcription Factors

Transcription factors (TFs) recognize specific DNA sequences to control chromatin and transcription, forming a complex system that guides expression of the genome. Despite keen interest in understanding how TFs control gene expression, it remains challenging to determine how the precise genomic binding sites of TFs are specified and how TF binding ultimately relates to regulation of transcription. This review considers how TFs are identified and functionally characterized, principally through the lens of a catalog of over 1,600 likely human TFs and binding motifs for two-thirds of them. Major classes of human TFs differ markedly in their evolutionary trajectories and expression patterns, underscoring distinct functions. TFs likewise underlie many different aspects of human physiology, disease, and variation, highlighting the importance of continued effort to understand TF-mediated gene regulation.

ApicoTFdb: the comprehensive web repository of apicomplexan transcription factors and transcription-associated co-factors

Despite significant progress in apicomplexan genome sequencing and genomics, the current list of experimentally validated transcription factors (TFs) in these genomes is incomplete and mainly consists of AP2 family of proteins, with only a limited number of non-AP2 family TFs and transcription-associated co-factors (TcoFs). We have performed a systematic bioinformatics-aided prediction of TFs and TcoFs in apicomplexan genomes and developed the ApicoTFdb database which consists of experimentally validated as well as computationally predicted TFs and TcoFs in 14 apicomplexan species. The predicted TFs are manually curated to complement the existing annotations. The current version of the database includes 1292 TFs which includes experimentally validated and computationally predicted TFs, representing 20 distinct families across 14 apicomplexan species. The predictions include TFs of TUB, NAC, BSD, HTH, Cupin/Jumonji, winged helix and FHA family proteins, not reported earlier as TFs in the genomes. Apart from TFs, ApicoTFdb also classifies TcoFs into three main subclasses: TRs, CRRs and RNARs, representing 2491 TcoFs in 14 apicomplexan species, are analyzed in this study. The database is designed to integrate different tools for comparative analysis. All entries in the database are dynamically linked with other databases, literature reference, protein–protein interactions, pathways and annotations associated with each protein. ApicoTFdb will be useful to the researchers interested in less-studied gene regulatory mechanisms mediating the complex life cycle of the apicomplexan parasites. The database will aid in the discovery of novel drug targets to much needed combat the growing drug resistance in the parasites.

Molecular Interaction Networks to Select Factors for Cell Conversion

The process of identifying sets of transcription factors that can induce a cell conversion can be time-consuming and expensive. To help alleviate this, a number of computational tools have been developed which integrate gene expression data with molecular interaction networks in order to predict these factors. One such approach is Mogrify, an algorithm which ranks transcriptions factors based on their regulatory influence in different cell types and tissues. These ranks are then used to identify a nonredundant set of transcription factors to promote cell conversion between any two cell types/tissues. Here we summarize the important concepts and data sources that were used in the implementation of this approach. Furthermore, we describe how the associated web resource ( www.mogrify.net ) can be used to tailor predictions to specific experimental scenarios, for instance, limiting the set of possible transcription factors and including domain knowledge. Finally, we describe important considerations for the effective selection of reprogramming factors. We envision that such data-driven approaches will become commonplace in the field, rapidly accelerating the progress in stem cell biology.

Transcription Factors Activate Genes through the Phase-Separation Capacity of Their Activation Domains

Gene expression is controlled by transcription factors (TFs) that consist of DNA-binding domains (DBDs) and activation domains (ADs). The DBDs have been well characterized, but little is known about the mechanisms by which ADs effect gene activation. Here, we report that diverse ADs form phase-separated condensates with the Mediator coactivator. For the OCT4 and GCN4 TFs, we show that the ability to form phase-separated droplets with Mediator in vitro and the ability to activate genes in vivo are dependent on the same amino acid residues. For the estrogen receptor (ER), a ligand-dependent activator, we show that estrogen enhances phase separation with Mediator, again linking phase separation with gene activation. These results suggest that diverse TFs can interact with Mediator through the phase-separating capacity of their ADs and that formation of condensates with Mediator is involved in gene activation.

Thirty biologically interpretable clusters of transcription factors distinguish cancer type

Background

Transcription factors are essential regulators of gene expression and play critical roles in development, differentiation, and in many cancers. To carry out their regulatory programs, they must cooperate in networks and bind simultaneously to sites in promoter or enhancer regions of genes. We hypothesize that the mRNA co-expression patterns of transcription factors can be used both to learn how they cooperate in networks and to distinguish between cancer types.

Results

We recently developed a new algorithm, Thresher, that combines principal component analysis, outlier filtering, and von Mises-Fisher mixture models to cluster genes (in this case, transcription factors) based on expression, determining the optimal number of clusters in the process. We applied Thresher to the RNA-Seq expression data of 486 transcription factors from more than 10,000 samples of 33 kinds of cancer studied in The Cancer Genome Atlas (TCGA). We found that 30 clusters of transcription factors from a 29-dimensional principal component space were able to distinguish between most cancer types, and could separate tumor samples from normal controls. Moreover, each cluster of transcription factors could be either (i) linked to a tissue-specific expression pattern or (ii) associated with a fundamental biological process such as cell cycle, angiogenesis, apoptosis, or cytoskeleton. Clusters of the second type were more likely also to be associated with embryonically lethal mouse phenotypes.

Conclusions

Using our approach, we have shown that the mRNA expression patterns of transcription factors contain most of the information needed to distinguish different cancer types. The Thresher method is capable of discovering biologically interpretable clusters of genes. It can potentially be applied to other gene sets, such as signaling pathways, to decompose them into simpler, yet biologically meaningful, components.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5093-z) contains supplementary material, which is available to authorized users.

Contributions of regulated transcription and mRNA decay to the dynamics of gene expression

Organisms have acquired sophisticated regulatory networks that control gene expression in response to cellular perturbations. Understanding of the mechanisms underlying the coordinated changes in gene expression in response to external and internal stimuli is a fundamental issue in biology. Recent advances in high-throughput technologies have enabled the measurement of diverse biological information, including gene expression levels, kinetics of gene expression, and interactions among gene expression regulatory molecules. By coupling these technologies with quantitative modeling, we can now uncover the biological roles and mechanisms of gene regulation at the system level. This review consists of two parts. First, we focus on the methods using uridine analogs that measure synthesis and decay rates of RNAs, which demonstrate how cells dynamically change the regulation of gene expression in response to both internal and external cues. Second, we discuss the underlying mechanisms of these changes in kinetics, including the functions of transcription factors and RNA-binding proteins. Overall, this review will help to clarify a system-level view of gene expression programs in cells. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs RNA Turnover and Surveillance > Regulation of RNA Stability RNA Methods > RNA Analyses in vitro and In Silico.

A comprehensive manually-curated compendium of bovine transcription factors

Transcription factors (TFs) are pivotal regulatory proteins that control gene expression in a context-dependent and tissue-specific manner. In contrast to human, where comprehensive curated TF collections exist, bovine TFs are only rudimentary recorded and characterized. In this article, we present a manually-curated compendium of 865 sequence-specific DNA-binding bovines TFs, which we analyzed for domain family distribution, evolutionary conservation, and tissue-specific expression. In addition, we provide a list of putative transcription cofactors derived from known interactions with the identified TFs. Since there is a general lack of knowledge concerning the regulation of gene expression in cattle, the curated list of TF should provide a basis for an improved comprehension of regulatory mechanisms that are specific to the species.

Control of human gene expression: High abundance of divergent transcription in genes containing both INR and BRE elements in the core promoter

Background

DNA sequence elements in the core promoter can play a central role in regulation of gene expression. Core elements (e.g. INR and TATA box) are located within ~50bp of the transcription start site and both upstream and downstream elements are known. Although all can affect the level of gene expression, their mechanism of action has yet to be fully defined. The studies described here are focused on two core promoter elements, INR and BRE, in the human genome. The locations of the two elements were determined in a large number of human promoters and the results were interpreted in terms of overall promoter function.

Results

A total of 13,406 promoters were collected from the reference version of the human genome and found to contain 62,891 INR sequences and 32,290 BRE. An INR sequence was found in the core region of 1231 (9.2%) promoters and a BRE in 2592 (19.3%); 121 promoters (0.9%) have both INR and BRE elements. Counts support the view that most human promoters lack an INR or BRE element in the core promoter. Further analysis was carried out with the aligned aggregate of promoters from each chromosome. The results showed distinct INR distributions in separate chromosome groups indicating a degree of chromosome specificity to the way core promoter elements are deployed in the genome. The rare promoters with both INR and BRE elements were found to be enriched among the genes with divergent transcription. Enrichment raises the possibility that core promoter elements can have a function in chromosome organization as well as in initiation of transcription.

The multisystemic functions of FOXD1 in development and disease

Transcription factors (TFs) participate in a wide range of cellular processes due to their inherent function as essential regulatory proteins. Their dysfunction has been linked to numerous human diseases. The forkhead box (FOX) family of TFs belongs to the "winged helix" superfamily, consisting of proteins sharing a related winged helix-turn-helix DNA-binding motif. FOX genes have been extensively present during vertebrates and invertebrates' evolution, participating in numerous molecular cascades and biological functions, such as embryonic development and organogenesis, cell cycle regulation, metabolism control, stem cell niche maintenance, signal transduction, and many others. FOXD1, a forkhead TF, has been related to different key biological processes such as kidney and retina development and embryo implantation. FOXD1 dysfunction has been linked to different pathologies, thereby constituting a diagnostic biomarker and a promising target for future therapies. This paper aims to present, for the first time, a comprehensive review of FOXD1's role in mouse development and human disease. Molecular, structural, and functional aspects of FOXD1 are presented in light of physiological and pathogenic conditions, including its role in human disease aetiology, such as cancer and recurrent pregnancy loss. Taken together, the information given here should enable a better understanding of FOXD1 function for basic science researchers and clinicians.

Cellular Differentiation of Human Monocytes Is Regulated by Time-Dependent Interleukin-4 Signaling and the Transcriptional Regulator NCOR2

Human in vitro generated monocyte-derived dendritic cells (moDCs) and macrophages are used clinically, e.g., to induce immunity against cancer. However, their physiological counterparts, ontogeny, transcriptional regulation, and heterogeneity remains largely unknown, hampering their clinical use. High-dimensional techniques were used to elucidate transcriptional, phenotypic, and functional differences between human in vivo and in vitro generated mononuclear phagocytes to facilitate their full potential in the clinic. We demonstrate that monocytes differentiated by macrophage colony-stimulating factor (M-CSF) or granulocyte macrophage colony-stimulating factor (GM-CSF) resembled in vivo inflammatory macrophages, while moDCs resembled in vivo inflammatory DCs. Moreover, differentiated monocytes presented with profound transcriptomic, phenotypic, and functional differences. Monocytes integrated GM-CSF and IL-4 stimulation combinatorically and temporally, resulting in a mode- and time-dependent differentiation relying on NCOR2. Finally, moDCs are phenotypically heterogeneous and therefore necessitate the use of high-dimensional phenotyping to open new possibilities for better clinical tailoring of these cellular therapies.

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In vitro monocyte cultures model in vivo inflammatory dendritic cells and macrophages

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Monocyte-derived dendritic cells integrate interleukin-4 signaling time dependently

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NCOR2 controls differentiation of in vitro generated monocyte-derived dendritic cells

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In vitro generated monocyte-derived cells are phenotypically heterogeneous

Profiling the transcriptome with RNA SPOTs

Single molecule FISH (smFISH) has been the gold standard in quantifying individual transcripts abundances. Here, we demonstrate the scaling up of smFISH to the transcriptome level by profiling of 10,212 different mRNAs from mouse fibroblast and embryonic stem cells. This methods, called RNA SPOTs (Sequential Probing of Targets), provides an accurate and low-cost alternative to sequencing in profiling transcriptomes.

A genome-wide interactome of DNA-associated proteins in the human liver

Large-scale efforts like the ENCODE Project have made tremendous progress in cataloging the genomic binding patterns of DNA-associated proteins (DAPs), such as transcription factors (TFs). However, most chromatin immunoprecipitation-sequencing (ChIP-seq) analyses have focused on a few immortalized cell lines whose activities and physiology differ in important ways from endogenous cells and tissues. Consequently, binding data from primary human tissue are essential to improving our understanding of in vivo gene regulation. Here, we identify and analyze more than 440,000 binding sites using ChIP-seq data for 20 DAPs in two human liver tissue samples. We integrated binding data with transcriptome and phased WGS data to investigate allelic DAP interactions and the impact of heterozygous sequence variation on the expression of neighboring genes. Our tissue-based data set exhibits binding patterns more consistent with liver biology than cell lines, and we describe uses of these data to better prioritize impactful noncoding variation. Collectively, our rich data set offers novel insights into genome function in human liver tissue and provides a valuable resource for assessing disease-related disruptions.

Novel atherogenic pathways from the differential transcriptome analysis of diabetic epicardial adipose tissue

BACKGROUND AND AIM

To evaluate the epicardial adipose tissue (EAT) transcriptome in comparison to subcutaneous fat (SAT) in coronary artery disease (CAD) and type 2 diabetes (T2DM).

METHODS AND RESULTS

SAT and EAT samples were obtained from subjects with T2DM and CAD (n = 5) and those without CAD with or without T2DM (=3) undergoing elective cardiac surgery. RNA-sequencing analysis was performed in both EAT and SAT. Gene enrichment analysis was conducted to identify pathways affected by the differentially expressed genes. Changes of top genes were verified by quantitative RT-PCR (qRT-PCR), western blot, and immunofluorescence. A total of 592 genes were differentially expressed in diabetic EAT, whereas there was no obvious changes in SAT transcriptome between diabetics and non-diabetics. Diabetic EAT was mainly enriched in inflammatory genes, such as Colony Stimulating Factor 3 (CSF3), Interleukin-1b (IL-1b), IL-6. KEGG pathway analysis confirmed that upregulated genes were involved in inflammatory pathways, such as Tumor Necrosis Factor (TNF), Nuclear Factor-κB (NF-κB) and advanced glycation end-products-receptor advanced glycation end products (AGE-RAGE). The overexpression of inflammatory genes in diabetic EAT was largely correlated with upregulated transcription factors such as NF-κB and FOS.

CONCLUSIONS

Diabetic EAT transcriptome is significantly different when compared to diabetic SAT and highly enriched with genes involved in innate immune response and endothelium, like Pentraxin3 (PTX3) and Endothelial lipase G (LIPG). EAT inflammatory genes expression could be induced by upregulated transcription factors, mainly NF-kB and FOSL, primarily activated by the overexpressed AGE-RAGE signaling. This suggests a unique and novel atherogenic pathway in diabetes.

Transcription Factor Repertoire of Necrotrophic Fungal Phytopathogen Ascochyta rabiei: Predominance of MYB Transcription Factors As Potential Regulators of Secretome

Transcription factors (TFs) are the key players in gene expression and their study is highly significant for shedding light on the molecular mechanisms and evolutionary history of organisms. During host-pathogen interaction, extensive reprogramming of gene expression facilitated by TFs is likely to occur in both host and pathogen. To date, the knowledge about TF repertoire in filamentous fungi is in infancy. The necrotrophic fungus Ascochyta rabiei, that causes destructive Ascochyta blight (AB) disease of chickpea (Cicer arietinum), demands more comprehensive study for better understanding of Ascochyta-legume pathosystem. In the present study, we performed the genome-wide identification and analysis of TFs in A. rabiei. Taking advantage of A. rabiei genome sequence, we used a bioinformatic approach to predict the TF repertoire of A. rabiei. For identification and classification of A. rabiei TFs, we designed a comprehensive pipeline using a combination of BLAST and InterProScan software. A total of 381 A. rabiei TFs were predicted and divided into 32 fungal specific families of TFs. The gene structure, domain organization and phylogenetic analysis of abundant families of A. rabiei TFs were also carried out. Comparative study of A. rabiei TFs with that of other necrotrophic, biotrophic, hemibiotrophic, symbiotic, and saprotrophic fungi was performed. It suggested presence of both conserved as well as unique features among them. Moreover, cis-acting elements on promoter sequences of earlier predicted A. rabiei secretome were also identified. With the help of published A. rabiei transcriptome data, the differential expression of TF and secretory protein coding genes was analyzed. Furthermore, comprehensive expression analysis of few selected A. rabiei TFs using quantitative real-time polymerase chain reaction revealed variety of expression patterns during host colonization. These genes were expressed in at least one of the time points tested post infection. Overall, this study illustrates the first genome-wide identification and analysis of TF repertoire of A. rabiei. This work would provide the basis for further studies to dissect role of TFs in the molecular mechanisms during A. rabiei-chickpea interactions.

mTFkb: a knowledgebase for fundamental annotation of mouse transcription factors

Transcription factors (TFs) are well-known important regulators in cell biology and tissue development. However, in mouse, one of the most widely-used model species, currently the vast majority of the known TFs have not been functionally studied due to the lack of sufficient annotations. To this end, we collected and analyzed the whole transcriptome sequencing data from more than 30 major mouse tissues and used the expression profiles to annotate the TFs. We found that the expression patterns of the TFs are highly correlated with the histology of the tissue types thus can be used to infer the potential functions of the TFs. Furthermore, we found that as many as 30% TFs display tissue-specific expression pattern, and these tissue-specific TFs are among the key TFs in their corresponding tissues. We also observed signals of divergent transcription associated with many TFs with unique expression pattern. Lastly, we have integrated all the data, our analysis results as well as various annotation resources to build a web-based database named mTFkb freely accessible at http://www.myogenesisdb.org/mTFkb/. We believe that mTFkb could serve as a useful and valuable resource for TF studies in mouse.

Wounding induces dedifferentiation of epidermal Gata6+ cells and acquisition of stem cell properties

The epidermis is maintained by multiple stem cell populations whose progeny differentiate along diverse, and spatially distinct, lineages. Here we show that the transcription factor Gata6 controls the identity of the previously uncharacterized sebaceous duct (SD) lineage and identify the Gata6 downstream transcription factor network that specifies a lineage switch between sebocytes and SD cells. During wound healing differentiated Gata6⁺ cells migrate from the SD into the interfollicular epidermis and dedifferentiate, acquiring the ability to undergo long-term self-renewal and differentiate into a much wider range of epidermal lineages than in undamaged tissue. Our data not only demonstrate that the structural and functional complexity of the junctional zone is regulated by Gata6, but also reveal that dedifferentiation is a previously unrecognized property of post-mitotic, terminally differentiated cells that have lost contact with the basement membrane. This resolves the long-standing debate about the contribution of terminally differentiated cells to epidermal wound repair.

Mapping cell type-specific transcriptional enhancers using high affinity, lineage-specific Ep300 bioChIP-seq

Understanding the mechanisms that regulate cell type-specific transcriptional programs requires developing a lexicon of their genomic regulatory elements. We developed a lineage-selective method to map transcriptional enhancers, regulatory genomic regions that activate transcription, in mice. Since most tissue-specific enhancers are bound by the transcriptional co-activator Ep300, we used Cre-directed, lineage-specific Ep300 biotinylation and pulldown on immobilized streptavidin followed by next generation sequencing of co-precipitated DNA to identify lineage-specific enhancers. By driving this system with lineage-specific Cre transgenes, we mapped enhancers active in embryonic endothelial cells/blood or skeletal muscle. Analysis of these enhancers identified new transcription factor heterodimer motifs that likely regulate transcription in these lineages. Furthermore, we identified candidate enhancers that regulate adult heart- or lung- specific endothelial cell specialization. Our strategy for tissue-specific protein biotinylation opens new avenues for studying lineage-specific protein-DNA and protein-protein interactions.

The Role of the Histone Methyltransferase Enhancer of Zeste Homolog 2 (EZH2) in the Pathobiological Mechanisms Underlying Inflammatory Bowel Disease (IBD)

Regulatory T (Treg) cells expressing the transcription factor FOXP3 play a pivotal role in maintaining immunologic self-tolerance. We and others have shown previously that EZH2 is recruited to the FOXP3 promoter and its targets in Treg cells. To further address the role for EZH2 in Treg cellular function, we have now generated mice that lack EZH2 specifically in Treg cells (EZH2Δ/ΔFOXP3+). We find that EZH2 deficiency in FOXP3+ T cells results in lethal multiorgan autoimmunity. We further demonstrate that EZH2Δ/ΔFOXP3+ T cells lack a regulatory phenotype in vitro and secrete proinflammatory cytokines. Of special interest, EZH2Δ/ΔFOXP3+ mice develop spontaneous inflammatory bowel disease. Guided by these results, we assessed the FOXP3 and EZH2 gene networks by RNA sequencing in isolated intestinal CD4+ T cells from patients with Crohn's disease. Gene network analysis demonstrates that these CD4+ T cells display a Th1/Th17-like phenotype with an enrichment of gene targets shared by FOXP3 and EZH2. Combined, these results suggest that the inflammatory milieu found in Crohn's disease could lead to or result from deregulation of FOXP3/EZH2-enforced T cell gene networks contributing to the underlying intestinal inflammation.

TcoF-DB v2: update of the database of human and mouse transcription co-factors and transcription factor interactions

Transcription factors (TFs) play a pivotal role in transcriptional regulation, making them crucial for cell survival and important biological functions. For the regulation of transcription, interactions of different regulatory proteins known as transcription co-factors (TcoFs) and TFs are essential in forming necessary protein complexes. Although TcoFs themselves do not bind DNA directly, their influence on transcriptional regulation and initiation, although indirect, has been shown to be significant, with the functionality of TFs strongly influenced by the presence of TcoFs. In the TcoF-DB v2 database, we collect information on TcoFs. In this article, we describe updates and improvements implemented in TcoF-DB v2. TcoF-DB v2 provides several new features that enables exploration of the roles of TcoFs. The content of the database has significantly expanded, and is enriched with information from Gene Ontology, biological pathways, diseases and molecular signatures. TcoF-DB v2 now includes many more TFs; has substantially increased the number of human TcoFs to 958, and now includes information on mouse (418 new TcoFs). TcoF-DB v2 enables the exploration of information on TcoFs and allows investigations into their influence on transcriptional regulation in humans and mice. TcoF-DB v2 can be accessed at http://tcofdb.org/.

ChiLin: a comprehensive ChIP-seq and DNase-seq quality control and analysis pipeline

BACKGROUND

Transcription factor binding, histone modification, and chromatin accessibility studies are important approaches to understanding the biology of gene regulation. ChIP-seq and DNase-seq have become the standard techniques for studying protein-DNA interactions and chromatin accessibility respectively, and comprehensive quality control (QC) and analysis tools are critical to extracting the most value from these assay types. Although many analysis and QC tools have been reported, few combine ChIP-seq and DNase-seq data analysis and quality control in a unified framework with a comprehensive and unbiased reference of data quality metrics.

RESULTS

ChiLin is a computational pipeline that automates the quality control and data analyses of ChIP-seq and DNase-seq data. It is developed using a flexible and modular software framework that can be easily extended and modified. ChiLin is ideal for batch processing of many datasets and is well suited for large collaborative projects involving ChIP-seq and DNase-seq from different designs. ChiLin generates comprehensive quality control reports that include comparisons with historical data derived from over 23,677 public ChIP-seq and DNase-seq samples (11,265 datasets) from eight literature-based classified categories. To the best of our knowledge, this atlas represents the most comprehensive ChIP-seq and DNase-seq related quality metric resource currently available. These historical metrics provide useful heuristic quality references for experiment across all commonly used assay types. Using representative datasets, we demonstrate the versatility of the pipeline by applying it to different assay types of ChIP-seq data. The pipeline software is available open source at https://github.com/cfce/chilin .

CONCLUSION

ChiLin is a scalable and powerful tool to process large batches of ChIP-seq and DNase-seq datasets. The analysis output and quality metrics have been structured into user-friendly directories and reports. We have successfully compiled 23,677 profiles into a comprehensive quality atlas with fine classification for users.

DNA Shape Features Improve Transcription Factor Binding Site Predictions In Vivo

Interactions of transcription factors (TFs) with DNA comprise a complex interplay between base-specific amino acid contacts and readout of DNA structure. Recent studies have highlighted the complementarity of DNA sequence and shape in modeling TF binding in vitro. Here, we have provided a comprehensive evaluation of in vivo datasets to assess the predictive power obtained by augmenting various DNA sequence-based models of TF binding sites (TFBSs) with DNA shape features (helix twist, minor groove width, propeller twist, and roll). Results from 400 human ChIP-seq datasets for 76 TFs show that combining DNA shape features with position-specific scoring matrix (PSSM) scores improves TFBS predictions. Improvement has also been observed using TF flexible models and a machine-learning approach using a binary encoding of nucleotides in lieu of PSSMs. Incorporating DNA shape information is most beneficial for E2F and MADS-domain TF families. Our findings indicate that incorporating DNA sequence and shape information benefits the modeling of TF binding under complex in vivo conditions.

Protein-Induced Pluripotent Stem Cells Ameliorate Cognitive Dysfunction and Reduce Aβ Deposition in a Mouse Model of Alzheimer's Disease

Transplantation of stem cells into the brain attenuates functional deficits in the central nervous system via cell replacement, the release of specific neurotransmitters, and the production of neurotrophic factors. To identify patient‐specific and safe stem cells for treating Alzheimer's disease (AD), we generated induced pluripotent stem cells (iPSCs) derived from mouse skin fibroblasts by treating protein extracts of embryonic stem cells. These reprogrammed cells were pluripotent but nontumorigenic. Here, we report that protein‐iPSCs differentiated into glial cells and decreased plaque depositions in the 5XFAD transgenic AD mouse model. We also found that transplanted protein‐iPSCs mitigated the cognitive dysfunction observed in these mice. Proteomic analysis revealed that oligodendrocyte‐related genes were upregulated in brains injected with protein‐iPSCs, providing new insights into the potential function of protein‐iPSCs. Taken together, our data indicate that protein‐iPSCs might be a promising therapeutic approach for AD. Stem Cells Translational Medicine2017;6:293–305

Disrupted cooperation between transcription factors across diverse cancer types

Background

Transcription Factors (TFs), essential for many cellular processes, generally work coordinately to induce transcriptional change in response to internal and external signals. Disrupted cooperation between TFs, leading to dysregulation of target genes, contributes to the pathogenesis of many diseases, including cancer. Although the aberrant activation of individual TFs and the functional effects have been widely studied, the perturbation of TF cooperativity in cancer has rarely been explored.

Results

We used TF co-expression as proxy as cooperativity and performed a large-scale study on disrupted TF cooperation across seven cancer types. While the connectivity of downstream effectors, like metabolic genes and TF targets, were more or similarly disrupted than/with non-TFs, the cooperativity of TFs (upstream regulators) were consistently less disturbed in all studied cancer types. Highly coordinated TFs in normal, however, generally lost that cooperation in cancer. Although different types of cancer shared very few TF pairs with highly disrupted cooperation, the cooperativity of interferon regulatory factors (IRF) was highly disrupted in six cancer types. Specifically, the cooperativity of IRF8 was highly perturbed in lung cancer, which was further validated by two independent lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) datasets. More interestingly, the cooperativity of IRF8 was markedly associated with tumor progression and even contributed to the patient survival independent of tumor stage.

Conclusions

Our findings underscore the far more important role of TF cooperativity in tumorigenesis than previously appreciated. Disrupted cooperation of TFs provides potential clinical utility as prognostic markers for predicting the patient survival.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2842-8) contains supplementary material, which is available to authorized users.

A catalog of Xenopus tropicalis transcription factors and their regional expression in the early gastrula stage embryo

Gene regulatory networks (GRNs) involve highly combinatorial interactions between transcription factors and short sequence motifs in cis-regulatory modules of target genes to control cellular phenotypes. The GRNs specifying most cell types are largely unknown and are the subject of wide interest. A catalog of transcription factors is a valuable tool toward obtaining a deeper understanding of the role of these critical effectors in any biological setting. Here we present a comprehensive catalog of the transcription factors for the diploid frog Xenopus tropicalis. We identify 1235 genes encoding DNA-binding transcription factors, comparable to the numbers found in typical mammalian species. In detail, the repertoire of X. tropicalis transcription factor genes is nearly identical to human and mouse, with the exception of zinc finger family members, and a small number of species/lineage-specific gene duplications and losses relative to the mammalian repertoires. We applied this resource to the identification of transcription factors differentially expressed in the early gastrula stage embryo. We find transcription factor enrichment in Spemann's organizer, the ventral mesoderm, ectoderm and endoderm, and report 218 TFs that show regionalized expression patterns at this stage. Many of these have not been previously reported as expressed in the early embryo, suggesting thus far unappreciated roles for many transcription factors in the GRNs regulating early development. We expect our transcription factor catalog will facilitate myriad studies using Xenopus as a model system to understand basic biology and human disease.

Dry and wet approaches for genome-wide functional annotation of conventional and unconventional transcriptional activators

Transcription factors (TFs) are master gene products that regulate gene expression in response to a variety of stimuli. They interact with DNA in a sequence-specific manner using a variety of DNA-binding domain (DBD) modules. This allows to properly position their second domain, called "effector domain", to directly or indirectly recruit positively or negatively acting co-regulators including chromatin modifiers, thus modulating preinitiation complex formation as well as transcription elongation. At variance with the DBDs, which are comprised of well-defined and easily recognizable DNA binding motifs, effector domains are usually much less conserved and thus considerably more difficult to predict. Also not so easy to identify are the DNA-binding sites of TFs, especially on a genome-wide basis and in the case of overlapping binding regions. Another emerging issue, with many potential regulatory implications, is that of so-called "moonlighting" transcription factors, i.e., proteins with an annotated function unrelated to transcription and lacking any recognizable DBD or effector domain, that play a role in gene regulation as their second job. Starting from bioinformatic and experimental high-throughput tools for an unbiased, genome-wide identification and functional characterization of TFs (especially transcriptional activators), we describe both established (and usually well affordable) as well as newly developed platforms for DNA-binding site identification. Selected combinations of these search tools, some of which rely on next-generation sequencing approaches, allow delineating the entire repertoire of TFs and unconventional regulators encoded by the any sequenced genome.

Gene regulation knowledge commons: community action takes care of DNA binding transcription factors

A large gap remains between the amount of knowledge in scientific literature and the fraction that gets curated into standardized databases, despite many curation initiatives. Yet the availability of comprehensive knowledge in databases is crucial for exploiting existing background knowledge, both for designing follow-up experiments and for interpreting new experimental data. Structured resources also underpin the computational integration and modeling of regulatory pathways, which further aids our understanding of regulatory dynamics. We argue how cooperation between the scientific community and professional curators can increase the capacity of capturing precise knowledge from literature. We demonstrate this with a project in which we mobilize biological domain experts who curate large amounts of DNA binding transcription factors, and show that they, although new to the field of curation, can make valuable contributions by harvesting reported knowledge from scientific papers. Such community curation can enhance the scientific epistemic process.

Database URL: http://www.tfcheckpoint.org

Transcription Factors Expressed in Mouse Cochlear Inner and Outer Hair Cells

Regulation of gene expression is essential to determining the functional complexity and morphological diversity seen among different cells. Transcriptional regulation is a crucial step in gene expression regulation because the genetic information is directly read from DNA by sequence-specific transcription factors (TFs). Although several mouse TF databases created from genome sequences and transcriptomes are available, a cell type-specific TF database from any normal cell populations is still lacking. We identify cell type-specific TF genes expressed in cochlear inner hair cells (IHCs) and outer hair cells (OHCs) using hair cell-specific transcriptomes from adult mice. IHCs and OHCs are the two types of sensory receptor cells in the mammalian cochlea. We show that 1,563 and 1,616 TF genes are respectively expressed in IHCs and OHCs among 2,230 putative mouse TF genes. While 1,536 are commonly expressed in both populations, 73 genes are differentially expressed (with at least a twofold difference) in IHCs and 13 are differentially expressed in OHCs. Our datasets represent the first cell type-specific TF databases for two populations of sensory receptor cells and are key informational resources for understanding the molecular mechanism underlying the biological properties and phenotypical differences of these cells.

Characterization of inflammatory markers and transcriptome profiles of differentially activated embryonic stem cell-derived microglia

Microglia, the immune cells of the CNS, are highly adaptive cells that can acquire different pro- and anti-inflammatory activation states with distinct functions in CNS homeostasis and pathologies. To study microglial function in vitro, primary microglia or immortalized cell lines are commonly used. An alternative to these cells are embryonic stem cell-derived microglia (ESdM). ESdM have previously been shown to be very similar to primary microglia in terms of expression profiles and surface molecules. In this study, ESdM and primary microglia were treated with different inflammatory stimulants to analyze their ability to adopt different activation states. Using quantitative real-time PCR, comparative transcriptomics, ELISA, and flow cytometry, we found that different activation states can be induced in ESdM, which are similar to those found in primary microglia. These states are characterized by specific sets of inflammatory marker molecules and differential transcriptome signatures. Our results show that ESdM are a valuable alternative cell model to study microglial functions and neuroinflammatory mechanisms.

The transcriptional regulator network of human inflammatory macrophages is defined by open chromatin

Differentiation of inflammatory macrophages from monocytes is characterized by an orderly integration of epigenetic and transcriptional regulatory mechanisms guided by lineage-determining transcription factors such as PU.1. Further activation of macrophages leads to a stimulus- or microenvironment-specific signal integration with subsequent transcriptional control established by the action of tissue- or signal-associated transcription factors. Here, we assess four histone modifications during human macrophage activation and integrate this information with the gene expression data from 28 different macrophage activation conditions in combination with GM-CSF. Bioinformatically, for inflammatory macrophages we define a unique network of transcriptional and epigenetic regulators (TRs), which was characterized by accessible promoters independent of the activation signal. In contrast to the general accessibility of promoters of TRs, mRNA expression of central TRs belonging to the TR network displayed stimulus-specific expression patterns, indicating a second level of transcriptional regulation beyond epigenetic chromatin changes. In contrast, stringent integration of epigenetic and transcriptional regulation was observed in networks of TRs established from somatic tissues and tissue macrophages. In these networks, clusters of TRs with permissive histone marks were associated with high gene expression whereas clusters with repressive chromatin marks were associated with absent gene expression. Collectively, these results support that macrophage activation during inflammation in contrast to lineage determination is mainly regulated transcriptionally by a pre-defined TR network.

A predictive computational framework for direct reprogramming between human cell types

Transdifferentiation, the process of converting from one cell type to another without going through a pluripotent state, has great promise for regenerative medicine. The identification of key transcription factors for reprogramming is currently limited by the cost of exhaustive experimental testing of plausible sets of factors, an approach that is inefficient and unscalable. Here we present a predictive system (Mogrify) that combines gene expression data with regulatory network information to predict the reprogramming factors necessary to induce cell conversion. We have applied Mogrify to 173 human cell types and 134 tissues, defining an atlas of cellular reprogramming. Mogrify correctly predicts the transcription factors used in known transdifferentiations. Furthermore, we validated two new transdifferentiations predicted by Mogrify. We provide a practical and efficient mechanism for systematically implementing novel cell conversions, facilitating the generalization of reprogramming of human cells. Predictions are made available to help rapidly further the field of cell conversion.

A novel analysis strategy for integrating methylation and expression data reveals core pathways for thyroid cancer aetiology

Background

Recently, a wide range of diseases have been associated with changes in DNA methylation levels, which play a vital role in gene expression regulation. With ongoing developments in technology, attempts to understand disease mechanism have benefited greatly from epigenetics and transcriptomics studies. In this work, we have used expression and methylation data of thyroid carcinoma as a case study and explored how to optimally incorporate expression and methylation information into the disease study when both data are available. Moreover, we have also investigated whether there are important post-translational modifiers which could drive critical insights on thyroid cancer genetics.

Results

In this study, we have conducted a threshold analysis for varying methylation levels to identify whether setting a methylation level threshold increases the performance of functional enrichment. Moreover, in order to decide on best-performing analysis strategy, we have performed data integration analysis including comparison of 10 different analysis strategies. As a result, combining methylation with expression and using genes with more than 15% methylation change led to optimal detection rate of thyroid-cancer associated pathways in top 20 functional enrichment results. Furthermore, pooling the data from different experiments increased analysis confidence by improving the data range. Consequently, we have identified 207 transcription factors and 245 post-translational modifiers with more than 15% methylation change which may be important in understanding underlying mechanisms of thyroid cancer.

Conclusion

While only expression or only methylation information would not reveal both primary and secondary mechanisms involved in disease state, combining expression and methylation led to a better detection of thyroid cancer-related genes and pathways that are found in the recent literature. Moreover, focusing on genes that have certain level of methylation change improved the functional enrichment results, revealing the core pathways involved in disease development such as; endocytosis, apoptosis, glutamatergic synapse, MAPK, ErbB, TGF-beta and Toll-like receptor pathways. Overall, in addition to novel analysis framework, our study reveals important thyroid-cancer related mechanisms, secondary molecular alterations and contributes to better knowledge of thyroid cancer aetiology.

JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles

JASPAR (http://jaspar.genereg.net) is an open-access database storing curated, non-redundant transcription factor (TF) binding profiles representing transcription factor binding preferences as position frequency matrices for multiple species in six taxonomic groups. For this 2016 release, we expanded the JASPAR CORE collection with 494 new TF binding profiles (315 in vertebrates, 11 in nematodes, 3 in insects, 1 in fungi and 164 in plants) and updated 59 profiles (58 in vertebrates and 1 in fungi). The introduced profiles represent an 83% expansion and 10% update when compared to the previous release. We updated the structural annotation of the TF DNA binding domains (DBDs) following a published hierarchical structural classification. In addition, we introduced 130 transcription factor flexible models trained on ChIP-seq data for vertebrates, which capture dinucleotide dependencies within TF binding sites. This new JASPAR release is accompanied by a new web tool to infer JASPAR TF binding profiles recognized by a given TF protein sequence. Moreover, we provide the users with a Ruby module complementing the JASPAR API to ease programmatic access and use of the JASPAR collection of profiles. Finally, we provide the JASPAR2016 R/Bioconductor data package with the data of this release.

Transcriptome dynamics of the microRNA inhibition response

We report a high-resolution time series study of transcriptome dynamics following antimiR-mediated inhibition of miR-9 in a Hodgkin lymphoma cell-line—the first such dynamic study of the microRNA inhibition response—revealing both general and specific aspects of the physiological response. We show miR-9 inhibition inducing a multiphasic transcriptome response, with a direct target perturbation before 4 h, earlier than previously reported, amplified by a downstream peak at ∼32 h consistent with an indirect response due to secondary coherent regulation. Predictive modelling indicates a major role for miR-9 in post-transcriptional control of RNA processing and RNA binding protein regulation. Cluster analysis identifies multiple co-regulated gene regulatory modules. Functionally, we observe a shift over time from mRNA processing at early time points to translation at later time points. We validate the key observations with independent time series qPCR and we experimentally validate key predicted miR-9 targets. Methodologically, we developed sensitive functional data analytic predictive methods to analyse the weak response inherent in microRNA inhibition experiments. The methods of this study will be applicable to similar high-resolution time series transcriptome analyses and provides the context for more accurate experimental design and interpretation of future microRNA inhibition studies.

REGULATOR: a database of metazoan transcription factors and maternal factors for developmental studies

BACKGROUND

Genes encoding transcription factors that constitute gene-regulatory networks and maternal factors accumulating in egg cytoplasm are two classes of essential genes that play crucial roles in developmental processes. Transcription factors control the expression of their downstream target genes by interacting with cis-regulatory elements. Maternal factors initiate embryonic developmental programs by regulating the expression of zygotic genes and various other events during early embryogenesis.

RESULTS

This article documents the transcription factors of 77 metazoan species as well as human and mouse maternal factors. We improved the previous method using a statistical approach adding Gene Ontology information to Pfam based identification of transcription factors. This method detects previously un-discovered transcription factors. The novel features of this database are: (1) It includes both transcription factors and maternal factors, although the number of species, in which maternal factors are listed, is limited at the moment. (2) Ontological representation at the cell, tissue, organ, and system levels has been specially designed to facilitate development studies. This is the unique feature in our database and is not available in other transcription factor databases.

CONCLUSIONS

A user-friendly web interface, REGULATOR ( http://www.bioinformatics.org/regulator/ ), which can help researchers to efficiently identify, validate, and visualize the data analyzed in this study, are provided. Using this web interface, users can browse, search, and download detailed information on species of interest, genes, transcription factor families, or developmental ontology terms.

Transcriptional selectors, masters, and combinatorial codes: regulatory principles of neural subtype specification

The broad range of tissue and cellular diversity of animals is generated to a large extent by the hierarchical deployment of sequence-specific transcription factors and co-factors (collectively referred to as TF's herein) during development. Our understanding of these developmental processes has been facilitated by the recognition that the activities of many TF's can be meaningfully described by a few functional categories that usefully convey a sense for how the TF's function, and also provides a sense for the regulatory organization of the developmental processes in which they participate. Here, we draw on examples from studies in Caenorhabditis elegans, Drosophila melanogaster, and vertebrates to discuss how the terms spatial selector, temporal selector, tissue/cell type selector, terminal selector and combinatorial code may be usefully applied to categorize the activities of TF's at critical steps of nervous system construction. While we believe that these functional categories are useful for understanding the organizational principles by which TF's direct nervous system construction, we however caution against the assumption that a TF's function can be solely or fully defined by any single functional category. Indeed, most TF's play diverse roles within different functional categories, and their roles can blur the lines we draw between these categories. Regardless, it is our belief that the concepts discussed here are helpful in clarifying the regulatory complexities of nervous system development, and hope they prove useful when interpreting mutant phenotypes, designing future experiments, and programming specific neuronal cell types for use in therapies. WIREs Dev Biol 2015, 4:505–528. doi: 10.1002/wdev.191

For further resources related to this article, please visit the WIREs website.

An atlas of mouse CD4(+) T cell transcriptomes

BACKGROUND

CD4(+) T cells are key regulators of the adaptive immune system and can be divided into T helper (Th) cells and regulatory T (Treg) cells. During an immune response Th cells mature from a naive state into one of several effector subtypes that exhibit distinct functions. The transcriptional mechanisms that underlie the specific functional identity of CD4(+) T cells are not fully understood.

RESULTS

To assist investigations into the transcriptional identity and regulatory processes of these cells we performed mRNA-sequencing on three murine T helper subtypes (Th1, Th2 and Th17) as well as on splenic Treg cells and induced Treg (iTreg) cells. Our integrated analysis of this dataset revealed the gene expression changes associated with these related but distinct cellular identities. Each cell subtype differentially expresses a wealth of 'subtype upregulated' genes, some of which are well known whilst others promise new insights into signalling processes and transcriptional regulation. We show that hundreds of genes are regulated purely by alternative splicing to extend our knowledge of the role of post-transcriptional regulation in cell differentiation.

CONCLUSIONS

This CD4(+) transcriptome atlas provides a valuable resource for the study of CD4(+) T cell populations. To facilitate its use by others, we have made the data available in an easily accessible online resource at www.th-express.org.

A property-based analysis of human transcription factors

Background

Transcription factors are essential proteins for regulating gene expression. This regulation depends upon specific features of the transcription factors, including how they interact with DNA, how they interact with each other, and how they are post-translationally modified. Reliable information about key properties associated with transcription factors will therefore be useful for data analysis, in particular of data from high-throughput experiments.

Results

We have used an existing list of 1978 human proteins described as transcription factors to make a well-annotated data set, which includes information on Pfam domains, DNA-binding domains, post-translational modifications and protein–protein interactions. We have then used this data set for enrichment analysis. We have investigated correlations within this set of features, and between the features and more general protein properties. We have also used the data set to analyze previously published gene lists associated with cell differentiation, cancer, and tissue distribution.

Conclusions

The study shows that well-annotated feature list for transcription factors is a useful resource for extensive data analysis; both of transcription factor properties in general and of properties associated with specific processes. However, the study also shows that such analyses are easily biased by incomplete coverage in experimental data, and by how gene sets are defined.

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-015-1039-6) contains supplementary material, which is available to authorized users.

Network representations of immune system complexity

The mammalian immune system is a dynamic multiscale system composed of a hierarchically organized set of molecular, cellular, and organismal networks that act in concert to promote effective host defense. These networks range from those involving gene regulatory and protein–protein interactions underlying intracellular signaling pathways and single‐cell responses to increasingly complex networks of in vivo cellular interaction, positioning, and migration that determine the overall immune response of an organism. Immunity is thus not the product of simple signaling events but rather nonlinear behaviors arising from dynamic, feedback‐regulated interactions among many components. One of the major goals of systems immunology is to quantitatively measure these complex multiscale spatial and temporal interactions, permitting development of computational models that can be used to predict responses to perturbation. Recent technological advances permit collection of comprehensive datasets at multiple molecular and cellular levels, while advances in network biology support representation of the relationships of components at each level as physical or functional interaction networks. The latter facilitate effective visualization of patterns and recognition of emergent properties arising from the many interactions of genes, molecules, and cells of the immune system. We illustrate the power of integrating ‘omics’ and network modeling approaches for unbiased reconstruction of signaling and transcriptional networks with a focus on applications involving the innate immune system. We further discuss future possibilities for reconstruction of increasingly complex cellular‐ and organism‐level networks and development of sophisticated computational tools for prediction of emergent immune behavior arising from the concerted action of these networks. WIREs Syst Biol Med 2015, 7:13–38. doi: 10.1002/wsbm.1288

This article is categorized under: 1

Analytical and Computational Methods > Computational Methods

2

Laboratory Methods and Technologies > Macromolecular Interactions, Methods

Cold-inducible Zfp516 activates UCP1 transcription to promote browning of white fat and development of brown fat

Uncoupling protein 1 (UCP1) mediates nonshivering thermogenesis and, upon cold exposure, is induced in brown adipose tissue (BAT) and subcutaneous white adipose tissue (iWAT). Here, by high-throughput screening using the UCP1 promoter, we identify Zfp516 as a transcriptional activator of UCP1 as well as PGC1α, thereby promoting a BAT program. Zfp516 itself is induced by cold and sympathetic stimulation through the cAMP-CREB/ATF2 pathway. Zfp516 directly binds to the proximal region of the UCP1 promoter, not to the enhancer region where other transcription factors bind, and interacts with PRDM16 to activate the UCP1 promoter. Although ablation of Zfp516 causes embryonic lethality, knockout embryos still show drastically reduced BAT mass. Overexpression of Zfp516 in adipose tissue promotes browning of iWAT even at room temperature, increasing body temperature and energy expenditure and preventing diet-induced obesity. Zfp516 may represent a future target for obesity therapeutics.