Transcription Factor Binding Profiles Research Articles

Deep Mining of Natural Genetic Variation in Erythroid Cells Reveals New Insights about In Vivo Transcription Factor Binding and Chromatin Accessibility

Erythroid transcription factors (TFs) control gene expression programs, lineage decisions, and disease outcomes. How transcription factors contact DNA has been studied extensively in vitro, but in vivo binding characteristics are less well understood as they are influenced in a reciprocal manner by chromatin accessibility and neighboring transcription factors. Here, we present a comparative analysis approach that takes advantage of non-coding sequence variation between functionally equivalent erythroid cell lines to conduct an in-depth analysis of erythroid TF binding profiles and chromatin features.Specifically, we analyzed ChIP-seq datasets to identify millions of genetic non-coding variants between the mouse erythroleukemia cell line (MEL), a GATA1-inducible erythroid progenitor cell line (G1E-ER4), and primary murine erythroblast cells. We found that while these cell lines are highly positively correlated in chromatin features, larger differences in TF binding intensity are correlated with higher degrees of genetic variation between cell lines.We next examined discriminatory genetic variants between the cell lines that are located in ChIP-seq peaks of the erythroid transcription factor GATA1. Hundreds of such variants fall within GATA1 motifs. Differential GATA1 binding intensities associated with the variants revealed nucleotide positions that contribute most to in vivo GATA1 chromatin occupancy and identified which alternative nucleotides are most likely to disrupt binding. Notably, this additional information about GATA1's in vivo nucleotide binding preferences improved prediction of GATA1 binding sites genome-wide. We applied similar approaches to determine the bp-resolution in vivo binding preferences of TAL1/SCL and CTCF.We additionally identified thousands of discriminatory genetic variants within GATA1 sites that fall outside canonical GATA elements but within binding sites of other known TFs. Association of these variants with differential GATA1 binding intensities revealed that the hematopoietic transcription factors TAL1/SCL and KLF1 positively regulate GATA1 chromatin occupancy. Strikingly, we identified a number of motifs not previously implicated in cooperating with GATA1 that positively impact GATA1 chromatin binding. Notably, we also defined motifs associated with negative regulation of GATA1 chromatin occupancy. Applying a similar analysis to TAL1/SCL and CTCF revealed additional motifs involved in regulating the chromatin occupancy of these TFs.Finally, we associated discriminatory genetic variation between erythroid cell lines with large changes in sub-kb-scale DNase hypersensitivity. We found that single base pair substitutions within or near a number of erythroid TF motifs, including that for the RUNX family of nuclear factors, are strongly associated with changes in chromatin accessibility. Our findings use novel methods in comparative ChIP-seq and DNase-seq analysis to reveal new insights about the genetic basis for erythroid TF chromatin occupancy and chromatin accessibility. DisclosuresNo relevant conflicts of interest to declare.

Genome-Wide Analysis of the Distinct Types of Chromatin Interactions in Arabidopsis thaliana.

The three-dimensional shapes of chromosomes regulate gene expression and genome function. Our knowledge of the role of chromatin interaction is evolving rapidly. Here, we present a study of global chromatin interaction patterns in Arabidopsis thaliana. High-throughput experimental techniques have been developed to map long-range interactions within chromatin. We have integrated data from multiple experimental sources including Hi-C, BS-seq, ChIP-chip and ChIP-seq data for 17 epigenetic marks and 35 transcription factors. We identified seven groups of interacting loci, which can be distinguished by their epigenetic profiles. Furthermore, the seven groups of interacting loci can be divided into three types of chromatin linkages based on expression status. We observed that two interacting loci sometimes share common epigenetic and transcription factor-binding profiles. Different groups of loci display very different relationships between epigenetic marks and the binding of transcription factors. Distinctive types of chromatin linkages exhibit different gene expression profiles. Our study unveils an entirely unexplored regulatory interaction, linking epigenetic profiles, transcription factor binding and the three-dimensional spatial organization of the Arabidopsis nuclear genome.

A graphical model approach visualizes regulatory relationships between genome-wide transcription factor binding profiles

Integrated analysis of multiple genome-wide transcription factor (TF)-binding profiles will be vital to advance our understanding of the global impact of TF binding. However, existing methods for measuring similarity in large numbers of chromatin immunoprecipitation assays with sequencing (ChIP-seq), such as correlation, mutual information or enrichment analysis, are limited in their ability to display functionally relevant TF relationships. In this study, we propose the use of graphical models to determine conditional independence between TFs and showed that network visualization provides a promising alternative to distinguish ‘direct’ versus ‘indirect’ TF interactions. We applied four algorithms to measure ‘direct’ dependence to a compendium of 367 mouse haematopoietic TF ChIP-seq samples and obtained a consensus network known as a ‘TF association network’ where edges in the network corresponded to likely causal pairwise relationships between TFs. The ‘TF association network’ illustrates the role of TFs in developmental pathways, is reminiscent of combinatorial TF regulation, corresponds to known protein–protein interactions and indicates substantial TF-binding reorganization in leukemic cell types. With the rapid increase in TF ChIP-Seq data sets, the approach presented here will be a powerful tool to study transcriptional programmes across a wide range of biological systems.

Maps of context-dependent putative regulatory regions and genomic signal interactions.

Gene transcription is regulated mainly by transcription factors (TFs). ENCODE and Roadmap Epigenomics provide global binding profiles of TFs, which can be used to identify regulatory regions. To this end we implemented a method to systematically construct cell-type and species-specific maps of regulatory regions and TF–TF interactions. We illustrated the approach by developing maps for five human cell-lines and two other species. We detected ∼144k putative regulatory regions among the human cell-lines, with the majority of them being ∼300 bp. We found ∼20k putative regulatory elements in the ENCODE heterochromatic domains suggesting a large regulatory potential in the regions presumed transcriptionally silent. Among the most significant TF interactions identified in the heterochromatic regions were CTCF and the cohesin complex, which is in agreement with previous reports. Finally, we investigated the enrichment of the obtained putative regulatory regions in the 3D chromatin domains. More than 90% of the regions were discovered in the 3D contacting domains. We found a significant enrichment of GWAS SNPs in the putative regulatory regions. These significant enrichments provide evidence that the regulatory regions play a crucial role in the genomic structural stability. Additionally, we generated maps of putative regulatory regions for prostate and colorectal cancer human cell-lines.

MGMT DNA repair gene promoter/enhancer haplotypes alter transcription factor binding and gene expression.

The O6-methylguanine-DNA methyltransferase (MGMT) protein removes O6-alkyl-guanine adducts from DNA. MGMT expression can thus alter the sensitivity of cells and tissues to environmental and chemotherapeutic alkylating agents. Previously, we defined the haplotype structure encompassing single nucleotide polymorphisms (SNPs) in the MGMT promoter/enhancer (P/E) region and found that haplotypes, rather than individual SNPs, alter MGMT promoter activity. The exact mechanism(s) by which these haplotypes exert their effect on MGMT promoter activity is currently unknown, but we noted that many of the SNPs comprising the MGMT P/E haplotypes arelocated within or in close proximity to putative transcription factor binding sites. Thus, these haplotypes could potentiallyaffect transcription factor binding and, subsequently, alter MGMT promoter activity. In this study, we test the hypothesis that MGMT P/E haplotypes affect MGMT promoter activity by altering transcription factor (TF) binding to the P/E region. We used a promoter binding TF profiling array and a reporter assay to evaluate the effect of different P/E haplotypes on TF binding and MGMT expression, respectively. Our data revealed a significant difference in TF binding profiles between the different haplotypes evaluated. We identified TFs that consistently showed significant haplotype-dependent binding alterations (p≤0.01) and revealed their role in regulating MGMT expression using siRNAs and a dual-luciferase reporter assay system. The data generated support our hypothesis that promoter haplotypes alter the binding of TFs to the MGMT P/E and, subsequently, affect their regulatory function on MGMT promoter activity and expression level.

Histone H4 lysine 20 acetylation is associated with gene repression in human cells.

Histone acetylation is generally associated with gene activation and chromatin decondensation. Recent mass spectrometry analysis has revealed that histone H4 lysine 20, a major methylation site, can also be acetylated. To understand the function of H4 lysine 20 acetylation (H4K20ac), we have developed a specific monoclonal antibody and performed ChIP-seq analysis using HeLa-S3 cells. H4K20ac was enriched around the transcription start sites (TSSs) of minimally expressed genes and in the gene body of expressed genes, in contrast to most histone acetylation being enriched around the TSSs of expressed genes. The distribution of H4K20ac showed little correlation with known histone modifications, including histone H3 methylations. A motif search in H4K20ac-enriched sequences, together with transcription factor binding profiles based on ENCODE ChIP-seq data, revealed that most transcription activators are excluded from H4K20ac-enriched genes and a transcription repressor NRSF/REST co-localized with H4K20ac. These results suggest that H4K20ac is a unique acetylation mark associated with gene repression.

Transcription Factor Information System (TFIS): A Tool for Detection of Transcription Factor Binding Sites.

Transcription factors are trans-acting proteins that interact with specific nucleotide sequences known as transcription factor binding site (TFBS), and these interactions are implicated in regulation of the gene expression. Regulation of transcriptional activation of a gene often involves multiple interactions of transcription factors with various sequence elements. Identification of these sequence elements is the first step in understanding the underlying molecular mechanism(s) that regulate the gene expression. For in silico identification of these sequence elements, we have developed an online computational tool named transcription factor information system (TFIS) for detecting TFBS for the first time using a collection of JAVA programs and is mainly based on TFBS detection using position weight matrix (PWM). The database used for obtaining position frequency matrices (PFM) is JASPAR and HOCOMOCO, which is an open-access database of transcription factor binding profiles. Pseudo-counts are used while converting PFM to PWM, and TFBS detection is carried out on the basis of percent score taken as threshold value. TFIS is equipped with advanced features such as direct sequence retrieving from NCBI database using gene identification number and accession number, detecting binding site for common TF in a batch of gene sequences, and TFBS detection after generating PWM from known raw binding sequences in addition to general detection methods. TFIS can detect the presence of potential TFBSs in both the directions at the same time. This feature increases its efficiency. And the results for this dual detection are presented in different colors specific to the orientation of the binding site. Results obtained by the TFIS are more detailed and specific to the detected TFs as integration of more informative links from various related web servers are added in the result pages like Gene Ontology, PAZAR database and Transcription Factor Encyclopedia in addition to NCBI and UniProt. Common TFs like SP1, AP1 and NF-KB of the Amyloid beta precursor gene is easily detected using TFIS along with multiple binding sites. In another scenario of embryonic developmental process, TFs of the FOX family (FOXL1 and FOXC1) were also identified. TFIS is platform-independent which is publicly available along with its support and documentation at http://tfistool.appspot.com and http://www.bioinfoplus.com/tfis/ . TFIS is licensed under the GNU General Public License, version 3 (GPL-3.0).

Collaborative Completion of Transcription Factor Binding Profiles via Local Sensitive Unified Embedding.

Although the newly available ChIP-seq data provides immense opportunities for comparative study of regulatory activities across different biological conditions, due to cost, time or sample material availability, it is not always possible for researchers to obtain binding profiles for every protein in every sample of interest, which considerably limits the power of integrative studies. Recently, by leveraging related information from measured data, Ernst et al. proposed ChromImpute for predicting additional ChIP-seq and other types of datasets, it is demonstrated that the imputed signal tracks accurately approximate the experimentally measured signals, and thereby could potentially enhance the power of integrative analysis. Despite the success of ChromImpute, in this paper, we reexamine its learning process, and show that its performance may degrade substantially and sometimes may even fail to output a prediction when the available data is scarce. This limitation could hurt its applicability to important predictive tasks, such as the imputation of TF binding data. To alleviate this problem, we propose a novel method called Local Sensitive Unified Embedding (LSUE) for imputing new ChIP-seq datasets. In LSUE, the ChIP-seq data compendium are fused together by mapping proteins, samples, and genomic positions simultaneously into the Euclidean space, thereby making their underling associations directly evaluable using simple calculations. In contrast to ChromImpute which mainly makes use of the local correlations between available datasets, LSUE can better estimate the overall data structure by formulating the representation learning of all involved entities as a single unified optimization problem. Meanwhile, a novel form of local sensitive low rank regularization is also proposed to further improve the performance of LSUE. Experimental evaluations on the ENCODE TF ChIP-seq data illustrate the performance of the proposed model. The code of LSUE is available at https://github.com/ekffar/LSUE.

Comparison of Expression and Epigenetic Profiles in Human and Mouse Erythropoiesis and Megakaryopoiesis Using a Systems Biology Model

To date numerous datasets of gene expression and epigenetic profiles for mouse and human hematopoietic cells have been generated. While individual data sets for a particular cell type have been correlated, no approach exists to harness all expression and epigenetic profiles for the different types of hematopoietic cells. Our goal is to develop a systems biology platform to compare epigenetic profiles of hematopoietic cells towards a better understanding of epigenetic mechanisms governing hematopoiesis. To provide the necessary foundation to support systematic studies of hematopoiesis, we have developed the Systems Biology Repository (SBR, http://sbrblood.nhgri.nih.gov), a data "ranch" for organizing and analyzing transcriptome and epigenome data cells throughout differentiation.To populate SBR, we extracted, curated, annotated, and integrated all human and mouse hematopoietic datasets available through the Encyclopedia of DNA Elements (ENCODE), the Gene Expression Omnibus (GEO) and the Short Read Repository (SRR). These include genome-wide profiles of DNA methylation, histone methylation and acetylation, transcription factor occupancy (ChIPSeq), chromatin accessibility (DNaseISeq, ATACSeq, FAIRESeq), and coding as well as non-coding transcriptional profiles (RNASeq).To demonstrate the utility of SBR, we conducted three different analyses. The first was a vertical study of HistoneSeq (H3K4me1, H3K4me2, H3K4me3, and H3K27ac), DNA methylation and RNASeq profiles during mouse erythroid differentiation. We found a global decrease in DNA methylation from hematopoietic stem and progenitor cells (HSC) through common myeloid progenitors (CMP), erythroid progenitor cells (MEP) and erythroblasts (ERY; 92936 peaks in HSC to 14422 in ERY). The number of expressed genes (using a tags per million cutoff of 10) increased in erythroid progenitors (8901 in HSC to 10778 in CMP and 10670 in MEP) before decreasing in ERY (8654). 62% of histone marks delineating active enhancers (H3K27ac, H3K4me1) are present in both HSC and ERY, while 48% arise de novo during differentiation. In contrast, only 16% of active promoter specific histone marks (H3K4me2, H3K4me3) are present in both HSC and ERY.For a horizontal analysis we compared the DNA methylation, RNASeq, histone modification (H3K4me1, H3K4me2, H3K4me3, and H3K27ac) and transcription factor binding (GATA1 and NFE2) profiles of erythroblasts (ERY) and megakaryocytes (MEG). We found a similar relationship between gene expression and the histone and DNA methylation profiles in each cell type but differences between expression and in transcription factor occupancy. DNA methylation and H3K4me3 was enriched in the gene body of expressed genes (>36%) for both ERY (p ≤ 0.001) and MEG (p ≤ 0.01). In contrast DNA methylation was enriched in the upstream and downstream regions of non-coding RNA genes (p ≤ 0.001). Transcription factor occupancy was cell type specific: 79% of GATA1 sites are in ERY and 72% of NFE2 sites are in MEG. In erythroblasts, DNA methylation and GATA1 binding in the gene body are associated with gene silencing (4 fold difference, p ≤ 0.001), while in megakaryocytes, DNA methylation and NFE2 binding in the gene body are associated with gene activation (8 fold difference, p ≤ 0.001).We used the Mouse Genome Informatics homology map data to perform a cross-species comparison of the expression profiles of mouse and human multipotent progenitors (MPP), proerythroblasts and orthochromatic erythroblasts. We found a total of 5247 genes expressed at significantly different levels (p ≤ 0.001) between human and mouse MPP, while only 2010 genes were expressed at significantly similar levels (p ≤ 0.001). At the proerythroblast and orthochromatic erythroblast stages 7696 genes and 6571 genes were expressed at significantly different levels (p ≤ 0.001) between human and mouse respectively, while 2024 and 2560 genes were expressed at significantly similar levels (p ≤ 0.001). These data are consistent with previous studies showing differences in the transcriptional profiles of mouse and human hematopoietic cells.In summary, SBR provides a foundation to model the genetic and epigenetic landscape in both the mouse and human hematopoietic system, and enables functional correlations to be made between the species. As SBR is expanded to include data from patient cells, it will be possible to model epigenetic changes associated with disease. DisclosuresNo relevant conflicts of interest to declare.

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.

Transcription factor co-occupied regions in the murine genome constitute T-helper-cell subtype-specific enhancers.

Transcription factors (TFs) regulate cell-type-specific gene expression programs by combinatorial binding to cis-genomic elements, particularly enhancers, subsequently leading to the recruitment of cofactors, and the general transcriptional machinery to target genes. Using data integration of genome-wide TF binding profiles, we defined regions with combinatorial binding of lineage-specific master TFs (T-BET, GATA3, and ROR-γt) and STATs (STAT1 and STAT4, STAT6, and STAT3) in murine T helper (Th) 1, Th2, and Th17 cells, respectively. Stringently excluding promoter regions, we revealed precise genomic elements which were preferentially associated with the enhancer marks p300 and H3K4me1. Furthermore, closely adjacent TF co-occupied regions constituted larger enhancer domains in the respective Th-cell subset (177 in Th1, 141 in Th2, and 266 in Th17 cells) with characteristics of so-called super-enhancers. Importantly, 89% of these super-enhancer regions were Th-cell subtype-specific. Genes associated with super-enhancers, including relevant Th-cell genes (such as Ifng in Th1, Il13 in Th2, and Il17a in Th17 cells), showed strong transcriptional activity. Altogether, the discovered catalog of enhancers provides information about crucial Th-cell subtype-specific regulatory hubs, which will be useful for revealing cell-type-specific gene regulation processes.

Abstract B05: Transcriptional antagonism between the cooperative oncogenes TLX1 and NOTCH1 in T-cell acute lymphoblastic leukemia.

Abstract Introduction: Combined activation of specific oncogenes is a general feature of human cancer and suggests that co-occurrence of particular oncogenic factors provides a selective advantage during cellular transformation. However, the exact molecular mechanisms by which oncoproteins cooperate during malignant transformation often remains elusive. Here, we study the functional relationship between the cooperative oncogenes NOTCH1 and TLX1 in the context of T-cell acute lymphoblastic leukemia to better understand their cooperative mechanism of action during T cell transformation. Methods: In this study, we performed chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) for the TLX1 homeobox oncoprotein in the T-ALL cell line ALL-SIL and analyzed the transcriptional response before and after TLX1 modulation using microarray based methods. We performed integration of TLX1 ChIPseq data with publically available transcription factor binding profiles in T-ALL and evaluated the immunophenotypic and transcriptional effects of ectopic TLX1 expression in thymus-derived CD34+ T-cell progenitors. Results: Integration of TLX1 ChIPseq data with gene expression profiles after TLX1 knockdown in the TLX1 positive T-ALL cell line ALL-SIL, confirmed the previously established role for TLX1 as transcriptional repressor in T-ALL biology. In line with previous reports (Della-Gatta et al., Nature Medicine, 2012), de novo TLX1 motif discovery identified RUNX1 and ETS1 as important mediators of the global TLX1 transcriptional network. Next, we used TLX1 ChIPseq data to define TLX1 bound super-enhancer including several loci critically involved in T-cell biology (e.g. T-cell receptor loci, RAG2, MYB). Furthermore, Gene set Enrichment Analysis (GSEA) showed that TLX1-defined super-enhancers were significantly affected by JQ1 treatment in ALL-SIL. Integration of our TLX1 ChIP-seq data with publically available ChIP-seq data for ICN1, RUNX1 and ETS1 in T-ALL cells (Wang et al., PNAS, 2013) showed a remarkable genome-wide overlap between the binding sites of these four transcription factors. Integration of these binding patterns with transcriptional read-out revealed an unprecedented transcriptional antagonism between TLX1 and NOTCH1, in which TLX1 suppresses the oncogenic NOTCH1 transcriptional program including IL7R, NOTCH3 and c-MYC. In line with this observation, ectopic TLX1 expression in CD34+ human thymic precursor T-cells broadly interfered with the normal T-cell differentiation program causing differentiation arrest, massive apoptosis and a significant downregulation of NOTCH1 target genes including reduced IL7R-alpha surface expression. Conclusion: In conclusion, our study reveals unexpected transcriptional antagonism between the cooperative oncogenes TLX1 and NOTCH1 in the biology of T-ALL. TLX1 mediated suppression of NOTCH signaling might be critically involved in the pre-leukemic phenotype (reduced thymus size and decreased cellularity) that has been observed in Lck-TLX1 transgenic mice (De Keersmaecker et al., Nature Medicine, 2010). Moreover, our results suggests that full malignant transformation of TLX1-driven leukemias might only be possible through acquisition of secondary NOTCH1 mutations that can overcome the initial TLX1 mediated suppression of NOTCH1 signaling, which is in line with the high frequency of gain-of-function NOTCH1 mutations in TLX1 positive human T-ALL. Citation Format: Kaat Durinck, Wouter Van Loocke, Joni Van der Meulen, Inge Van de Walle, Pieter Rondou, Charles E. De Bock, Bruce Poppe, Jan Cools, Jean Soulier, Tom Taghon, Frank Speleman, Pieter Van Vlierberghe. Transcriptional antagonism between the cooperative oncogenes TLX1 and NOTCH1 in T-cell acute lymphoblastic leukemia. [abstract]. In: Proceedings of the AACR Special Conference on Hematologic Malignancies: Translating Discoveries to Novel Therapies; Sep 20-23, 2014; Philadelphia, PA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(17 Suppl):Abstract nr B05.

238. BTK-Promoter LV Vectors Utilizing Conserved Intron Element Mediate Functional Rescue in Murine XLA

X-linked agammaglobulinema (XLA) is a rare immunodeficiency disorder caused by a mutation in the gene coding Bruton's tryosine kinase (BTK). BTK is required for signal transduction downstream of the B cell antigen receptor (BCR) and is essential for normal B cell development, activation, and survival. Patients lacking BTK have very few mature B cells, markedly reduced antibody production, and suffer from recurrent and life-threatening infections. XLA is an ideal candidate for hematopoietic gene therapy, as B cells that express BTK are positively selected during development. We previously developed a SIN-lentiviral (LV) construct that used the human BTK promoter (BTKp) to drive BTK expression. We also incorporated a truncated, 0.7 kb, fragment derived from the HNRPA2B1/CBX3 ubiquitously acting chromatin opening element (UCOE) upstream of the BTKp to facilitate stable BTK expression over time. Bone marrow transplantation in a murine XLA model (BTK-/-Tec-/- mice) using LV transduced hematopoietic stem cells (HSCs) reconstituted myeloid and B cell numbers, BCR-dependent B cell proliferation and T-dependent antibody responses. The goal of the current study was to further optimize BTK expression in B and myeloid cells while reducing the viral copy number (VCN) required for efficient functional reconstitution. Using the ENCODE database, we identified several highly conserved upstream and intronic regions exhibiting histone modifications and transcription factor binding profiles in B cells consistent with enhancer regions. These conserved elements were introduced individually or in tandem into the LV construct between the UCOE and BTKp and tested for their ability to rescue BTK expression and B cell development in the murine XLA model. Addition of two key intronic regions led to consistent BTK expression and rescued the development and function of B cells, despite a >5-fold reduction in VCN per splenic B cell. Our findings illustrate the usefulness of this strategy for improving the efficacy of endogenous promoter-based genetic therapies. This new LV vector, UCOE. I4-5.BTKpro-hBTK, is currently being evaluated using mobilized CD34+ stem cells isolated from XLA patients and in additional pretoxicology studies designed to support its application in a future LV clinical trial for XLA.

ZNF143 provides sequence specificity to secure chromatin interactions at gene promoters

Chromatin interactions connect distal regulatory elements to target gene promoters guiding stimulus- and lineage-specific transcription. Few factors securing chromatin interactions have so far been identified. Here, by integrating chromatin interaction maps with the large collection of transcription factor-binding profiles provided by the ENCODE project, we demonstrate that the zinc-finger protein ZNF143 preferentially occupies anchors of chromatin interactions connecting promoters with distal regulatory elements. It binds directly to promoters and associates with lineage-specific chromatin interactions and gene expression. Silencing ZNF143 or modulating its DNA-binding affinity using single-nucleotide polymorphisms (SNPs) as a surrogate of site-directed mutagenesis reveals the sequence dependency of chromatin interactions at gene promoters. We also find that chromatin interactions alone do not regulate gene expression. Together, our results identify ZNF143 as a novel chromatin-looping factor that contributes to the architectural foundation of the genome by providing sequence specificity at promoters connected with distal regulatory elements.

Genetic Architecture of Transcription and Chromatin Regulation.

DNA microarray and next-generation sequencing provide data that can be used for the genetic analysis of multiple quantitative traits such as gene expression levels, transcription factor binding profiles, and epigenetic signatures. In particular, chromatin opening is tightly coupled with gene transcription. To understand how these two processes are genetically regulated and associated with each other, we examined the changes of chromatin accessibility and gene expression in response to genetic variation by means of quantitative trait loci mapping. Regulatory patterns commonly observed in yeast and human across different technical platforms and experimental designs suggest a higher genetic complexity of transcription regulation in contrast to a more robust genetic architecture of chromatin regulation.

Genomic Organization and Isoform-Dependent Expression Patterns of Wap65 genes in Various Tissues during Immune Challenges in the Mud Loach Misgurnus mizolepis

Genomic organization, including the structural characteristics of 5'-flanking regions of two 65-kDa protein (WAP65) isoform genes associated with warm temperature acclimation, were characterized and their transcriptional responses to immune challenges were examined in the intestine, kidney and spleen of the mud loach (Misgurnus mizolepis; Cypriniformes). Both mud loach Wap65 isoform genes displayed a 10-exon structure that is common to most teleostean Wap65 genes. The two mud loach Wap65 isoforms were predicted to possess various stress- and immune-related transcription factor binding sites in their regulatory regions; however, the predicted motif profiles differed between the two isoforms, and the inflammation-related transcription factor binding motifs, such as NF-<TEX>${\kappa}B$</TEX> and CREBP sites, were more highlighted in the Wap65-2 isoform than the Wap65-1 isoform. The results of qRT-PCR indicated that experimental immune challenges using Edwardsiella tarda, lipopolysaccharide or polyI:C induced the Wap65-2 isoform more than Wap65-1 isoform, although modulation patterns in response to these challenges were tissue- and stimulant-dependent. This study confirms that functional diversification between the two mud loach Wap65 isoforms (i.e., closer involvement of Wap65-2 in the acute phase of inflammation and innate immunity) occurs at the mRNA level in multiple tissues, and suggests that such differential modulation patterns between the two isoforms are related to the different transcription factor binding profiles in their regulatory regions.

Transcriptional Antagonism Between the Cooperative Oncogenes TLX1 and NOTCH1 in T-Cell Acute Lymphoblastic Leukemia

Introduction: Combined activation of specific oncogenes is a general feature of human cancer and suggests that co-occurrence of particular oncogenic factors provides a selective advantage during cellular transformation. However, the exact molecular mechanisms by which oncoproteins cooperate during malignant transformation often remains elusive.Here, we study the functional relationship between the cooperative oncogenes NOTCH1 and TLX1 in the context of T-cell acute lymphoblastic leukemia to better understand their cooperative mechanism of action during T cell transformation.Methods: In this study, we performed chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) for the TLX1 homeobox oncoprotein in the T-ALL cell line ALL-SIL and analyzed the transcriptional response before and after TLX1 modulation using microarray based methods. We performed integration of TLX1 ChIPseq data with publically available transcription factor binding profiles in T-ALL and evaluated the immunophenotypic and transcriptional effects of ectopic TLX1 expression in thymus-derived CD34+ T-cell progenitors.Results: Integration of TLX1 ChIP-seq data with gene expression profiles after TLX1 knockdown in the TLX1 positive T-ALL cell line ALL-SIL, confirmed the previously established role for TLX1 as transcriptional repressor in T-ALL biology. In line with previous reports (Della-Gatta et al., Nature Medicine, 2012), de novo TLX1 motif discovery identified RUNX1 and ETS1 as important mediators of the global TLX1 transcriptional network.Next, we used TLX1 ChIP-seq data to define TLX1 super-enhancers including several loci critically involved in T-cell biology (e.g. T-cell receptor loci, RAG2, MYB). Furthermore, Gene set Enrichment Analysis (GSEA) showed that TLX1-defined super-enhancers were significantly affected by JQ1 treatment in ALL-SIL.Integration of our TLX1 ChIP-seq data with publically available ChIP-seq data for ICN1, RUNX1 and ETS1 in T-ALL cells (Wang et al., PNAS, 2013) showed a remarkable genome-wide overlap between the binding sites of these four transcription factors. Integration of these binding patterns with transcriptional read-out revealed an unprecedented transcriptional antagonism between TLX1 and NOTCH1, in which TLX1 suppresses the oncogenic NOTCH1 transcriptional program including IL7R, NOTCH3 and c-MYC. In line with this observation, ectopic TLX1 expression in CD34+ human thymic precursor T-cells broadly interfered with the normal T-cell differentiation program causing differentiation arrest, massive apoptosis and a significant downregulation of NOTCH1 target genes including reduced IL7R-alpha surface expression.Conclusion: In conclusion, our study reveals unexpected transcriptional antagonism between the cooperative oncogenes TLX1 and NOTCH1 in the biology of T-ALL. TLX1 mediated suppression of NOTCH signaling might be critically involved in the pre-leukemic phenotype (reduced thymus size and decreased cellularity) that has been observed in Lck-TLX1 transgenic mice (De Keersmaecker et al., Nature Medicine, 2010). Moreover, our results suggests that full malignant transformation of TLX1-driven leukemias might only be possible through acquisition of secondary NOTCH1 mutations that can overcome the initial TLX1 mediated suppression of NOTCH1 signaling, which is in line with the high frequency of gain-of-function NOTCH1 mutations in TLX1 positive human T-ALL. DisclosuresNo relevant conflicts of interest to declare.

CisMEP: an integrated repository of genomic epigenetic profiles and cis-regulatory modules in Drosophila.

BackgroundCis-regulatory modules (CRMs), or the DNA sequences required for regulating gene expression, play the central role in biological researches on transcriptional regulation in metazoan species. Nowadays, the systematic understanding of CRMs still mainly resorts to computational methods due to the time-consuming and small-scale nature of experimental methods. But the accuracy and reliability of different CRM prediction tools are still unclear. Without comparative cross-analysis of the results and combinatorial consideration with extra experimental information, there is no easy way to assess the confidence of the predicted CRMs. This limits the genome-wide understanding of CRMs.DescriptionIt is known that transcription factor binding and epigenetic profiles tend to determine functions of CRMs in gene transcriptional regulation. Thus integration of the genome-wide epigenetic profiles with systematically predicted CRMs can greatly help researchers evaluate and decipher the prediction confidence and possible transcriptional regulatory functions of these potential CRMs. However, these data are still fragmentary in the literatures. Here we performed the computational genome-wide screening for potential CRMs using different prediction tools and constructed the pioneer database, cisMEP (cis-regulatory module epigenetic profile database), to integrate these computationally identified CRMs with genomic epigenetic profile data. cisMEP collects the literature-curated TFBS location data and nine genres of epigenetic data for assessing the confidence of these potential CRMs and deciphering the possible CRM functionality.ConclusionscisMEP aims to provide a user-friendly interface for researchers to assess the confidence of different potential CRMs and to understand the functions of CRMs through experimentally-identified epigenetic profiles. The deposited potential CRMs and experimental epigenetic profiles for confidence assessment provide experimentally testable hypotheses for the molecular mechanisms of metazoan gene regulation. We believe that the information deposited in cisMEP will greatly facilitate the comparative usage of different CRM prediction tools and will help biologists to study the modular regulatory mechanisms between different TFs and their target genes.

Shared transcription factors contribute to distinct cell fates

Genome-wide transcription factor (TF) binding profiles differ dramatically between cell types. However, not much is known about the relationship between cell-type-specific binding patterns and gene expression. A recent study demonstrated how the same TFs can have functional roles when binding to largely non-overlapping genomic regions in hematopoietic progenitor and mast cells. Cell-type specific binding profiles of shared TFs are therefore not merely the consequence of opportunistic and functionally irrelevant binding to accessible chromatin, but instead have the potential to make meaningful contributions to cell-type specific transcriptional programs.

Automation Highlights from the Literature

Automation Highlights from the Literature