Transcriptional enhancement by GATA1-occupied DNA segments is strongly associated with evolutionary constraint on the binding site motif

Transcriptional enhancers: from prediction to functional assessment on a genome-wide scale

Enhancers are cis-regulatory sequences located distally to target genes. These sequences consolidate developmental and environmental cues to coordinate gene expression in a tissue-specific manner. Enhancer function and tissue specificity depend on the expressed set of transcription factors, which recognize binding sites and recruit cofactors that regulate local chromatin organization and gene transcription. Unlike other genomic elements, enhancers are challenging to identify because they function independently of orientation, are often distant from their promoters, have poorly defined boundaries, and display no reading frame. In addition, there are no defined genetic or epigenetic features that are unambiguously associated with enhancer activity. Over recent years there have been developments in both empirical assays and computational methods for enhancer prediction. We review genome-wide tools, CRISPR advancements, and high-throughput screening approaches that have improved our ability to both observe and manipulate enhancers in vitro at the level of primary genetic sequences, chromatin states, and spatial interactions. We also highlight contemporary animal models and their importance to enhancer validation. Together, these experimental systems and techniques complement one another and broaden our understanding of enhancer function in development, evolution, and disease.

A Unique Epigenomic Landscape Defines Human Erythropoiesis

Mammalian erythropoiesis yields a highly specialized cell type, the mature erythrocyte, evolved to meet the organismal needs of increased oxygen-carrying capacity. To better understand the regulation of erythropoiesis, we performed genome-wide studies of chromatin accessibility, DNA methylation, and transcriptomics using a recently developed strategy to obtain highly purified populations of primary human erythroid cells. The integration of gene expression, DNA methylation, and chromatin state dynamics reveals that stage-specific gene regulation during erythropoiesis is a stepwise and hierarchical process involving many cis-regulatory elements. Erythroid-specific, nonpromoter sites of chromatin accessibility are linked to erythroid cell phenotypic variation and inherited disease. Comparative analyses of stage-specific chromatin accessibility indicate that there is limited early chromatin priming of erythroid genes during hematopoiesis. The epigenome of terminally differentiating erythroid cells defines a distinct subset of highly specialized cells that are vastly dissimilar from other hematopoietic and nonhematopoietic cell types. These epigenomic and transcriptome data are powerful tools to study human erythropoiesis.

Schulz et al. use genome-wide studies of chromatin accessibility, DNA methylation, and transcriptomes in primary human erythroid cells to reveal important characteristics of erythropoiesis. Chromatin accessibility of terminal erythroid differentiation is markedly dissimilar from other hematopoietic cell types. Epigenomic changes are linked to erythroid cell traits and disease genes.

Systematic integration of GATA transcription factors and epigenomes via IDEAS paints the regulatory landscape of hematopoietic cells

Members of the GATA family of transcription factors play key roles in the differentiation of specific cell lineages by regulating the expression of target genes. Three GATA factors play distinct roles in hematopoietic differentiation. In order to better understand how these GATA factors function to regulate genes throughout the genome, we are studying the epigenomic and transcriptional landscapes of hematopoietic cells in a model-driven, integrative fashion. We have formed the collaborative multi-lab VISION project to conduct ValIdated Systematic IntegratiON of epigenomic data in mouse and human hematopoiesis. The epigenomic data included nuclease accessibility in chromatin, CTCF occupancy, and histone H3 modifications for 20 cell types covering hematopoietic stem cells, multilineage progenitor cells, and mature cells across the blood cell lineages of mouse. The analysis used the Integrative and Discriminative Epigenome Annotation System (IDEAS), which learns all common combinations of features (epigenetic states) simultaneously in two dimensions-along chromosomes and across cell types. The result is a segmentation that effectively paints the regulatory landscape in readily interpretable views, revealing constitutively active or silent loci as well as the loci specifically induced or repressed in each stage and lineage. Nuclease accessible DNA segments in active chromatin states were designated candidate cis-regulatory elements in each cell type, providing one of the most comprehensive registries of candidate hematopoietic regulatory elements to date. Applications of VISION resources are illustrated for the regulation of genes encoding GATA1, GATA2, GATA3, and Ikaros. VISION resources are freely available from our website http://usevision.org.

A novel role of CKIP-1 in promoting megakaryocytic differentiation

Casein kinase 2-interacting protein-1 (CKIP-1) is a known regulator of cardiomyocytes and macrophage proliferation. In this study, we showed that CKIP-1 was involved in the process of megakaryocytic differentiation. During megakaryocytic differentiation of K562 cells, CKIP-1 was dramatically upregulated and this upregulation induced by PMA was mediated through downregulation of transcription factor GATA-1. By transient transfection, oligonucleotide-directed mutagenesis and chromatin immunoprecipitation assays, we identified the transcriptional regulation of CKIP-1 by GATA-1. Overexpression of CKIP-1 initiated events of spontaneous megakaryocytic differentiation in K562 cells. Conversely, knockdown of CKIP-1 in cell lines suppressed megakaryocytic differentiation. Mechanistically, overexpression of CKIP-1 changed the expression levels of transcription factors that have been shown to be critical in erythro-megakaryocytic differentiation such as Fli-1, c-Myb and c-Myc. In vivo analysis confirmed that CKIP-1^−/− mice had decreased number of CD41⁺ cells harvested from bone marrow, and lower platelet levels when compared to wild-type littermates. This is the first direct evidence suggesting that CKIP-1 is a novel regulator of megakaryocytic differentiation.

Genome-Wide Organization of GATA1 and TAL1 Determined at High Resolution

Erythroid development and differentiation from multiprogenitor cells into red blood cells requires precise transcriptional regulation. Key erythroid transcription factors, GATA1 and TAL1, cooperate, along with other proteins, to regulate many aspects of this process. How GATA1 and TAL1 are juxtaposed along the DNA and their cognate DNA binding site across the mouse genome remains unclear. We applied high-resolution ChIP-exo (chromatin immunoprecipitation followed by 5′-to-3′ exonuclease treatment and then massively parallel DNA sequencing) to GATA1 and TAL1 to study their positional organization across the mouse genome during GATA1-dependent maturation. Two complementary methods, MultiGPS and peak pairing, were used to determine high-confidence binding locations by ChIP-exo. We identified ∼10,000 GATA1 and ∼15,000 TAL1 locations, which were essentially confirmed by ChIP-seq (chromatin immunoprecipitation followed by massively parallel DNA sequencing). Of these, ∼4,000 locations were bound by both GATA1 and TAL1. About three-quarters of them were tightly linked to a partial E-box located 7 or 8 bp upstream of a WGATAA motif. Both TAL1 and GATA1 generated distinct characteristic ChIP-exo peaks around WGATAA motifs that reflect their positional arrangement within a complex. We show that TAL1 and GATA1 form a precisely organized complex at a compound motif consisting of a TG 7 or 8 bp upstream of a WGATAA motif across thousands of genomic locations.

Occupancy by key transcription factors is a more accurate predictor of enhancer activity than histone modifications or chromatin accessibility

Background

Regulated gene expression controls organismal development, and variation in regulatory patterns has been implicated in complex traits. Thus accurate prediction of enhancers is important for further understanding of these processes. Genome-wide measurement of epigenetic features, such as histone modifications and occupancy by transcription factors, is improving enhancer predictions, but the contribution of these features to prediction accuracy is not known. Given the importance of the hematopoietic transcription factor TAL1 for erythroid gene activation, we predicted candidate enhancers based on genomic occupancy by TAL1 and measured their activity. Contributions of multiple features to enhancer prediction were evaluated based on the results of these and other studies.

Results

TAL1-bound DNA segments were active enhancers at a high rate both in transient transfections of cultured cells (39 of 79, or 56%) and transgenic mice (43 of 66, or 65%). The level of binding signal for TAL1 or GATA1 did not help distinguish TAL1-bound DNA segments as active versus inactive enhancers, nor did the density of regulation-related histone modifications. A meta-analysis of results from this and other studies (273 tested predicted enhancers) showed that the presence of TAL1, GATA1, EP300, SMAD1, H3K4 methylation, H3K27ac, and CAGE tags at DNase hypersensitive sites gave the most accurate predictors of enhancer activity, with a success rate over 80% and a median threefold increase in activity. Chromatin accessibility assays and the histone modifications H3K4me1 and H3K27ac were sensitive for finding enhancers, but they have high false positive rates unless transcription factor occupancy is also included.

Conclusions

Occupancy by key transcription factors such as TAL1, GATA1, SMAD1, and EP300, along with evidence of transcription, improves the accuracy of enhancer predictions based on epigenetic features.

Electronic supplementary material

The online version of this article (doi:10.1186/s13072-015-0009-5) contains supplementary material, which is available to authorized users.

Identifying transcriptional cis-regulatory modules in animal genomes

Gene expression is regulated through the activity of transcription factors (TFs) and chromatin-modifying proteins acting on specific DNA sequences, referred to as cis-regulatory elements. These include promoters, located at the transcription initiation sites of genes, and a variety of distal cis-regulatory modules (CRMs), the most common of which are transcriptional enhancers. Because regulated gene expression is fundamental to cell differentiation and acquisition of new cell fates, identifying, characterizing, and understanding the mechanisms of action of CRMs is critical for understanding development. CRM discovery has historically been challenging, as CRMs can be located far from the genes they regulate, have few readily identifiable sequence characteristics, and for many years were not amenable to high-throughput discovery methods. However, the recent availability of complete genome sequences and the development of next-generation sequencing methods have led to an explosion of both computational and empirical methods for CRM discovery in model and nonmodel organisms alike. Experimentally, CRMs can be identified through chromatin immunoprecipitation directed against TFs or histone post-translational modifications, identification of nucleosome-depleted 'open' chromatin regions, or sequencing-based high-throughput functional screening. Computational methods include comparative genomics, clustering of known or predicted TF-binding sites, and supervised machine-learning approaches trained on known CRMs. All of these methods have proven effective for CRM discovery, but each has its own considerations and limitations, and each is subject to a greater or lesser number of false-positive identifications. Experimental confirmation of predictions is essential, although shortcomings in current methods suggest that additional means of validation need to be developed. For further resources related to this article, please visit the WIREs website.

CONFLICT OF INTEREST

The authors have declared no conflicts of interest for this article.

Altered chromatin occupancy of master regulators underlies evolutionary divergence in the transcriptional landscape of erythroid differentiation

Erythropoiesis is one of the best understood examples of cellular differentiation. Morphologically, erythroid differentiation proceeds in a nearly identical fashion between humans and mice, but recent evidence has shown that networks of gene expression governing this process are divergent between species. We undertook a systematic comparative analysis of six histone modifications and four transcriptional master regulators in primary proerythroblasts and erythroid cell lines to better understand the underlying basis of these transcriptional differences. Our analyses suggest that while chromatin structure across orthologous promoters is strongly conserved, subtle differences are associated with transcriptional divergence between species. Many transcription factor (TF) occupancy sites were poorly conserved across species (∼25% for GATA1, TAL1, and NFE2) but were more conserved between proerythroblasts and cell lines derived from the same species. We found that certain cis-regulatory modules co-occupied by GATA1, TAL1, and KLF1 are under strict evolutionary constraint and localize to genes necessary for erythroid cell identity. More generally, we show that conserved TF occupancy sites are indicative of active regulatory regions and strong gene expression that is sustained during maturation. Our results suggest that evolutionary turnover of TF binding sites associates with changes in the underlying chromatin structure, driving transcriptional divergence. We provide examples of how this framework can be applied to understand epigenomic variation in specific regulatory regions, such as the β-globin gene locus. Our findings have important implications for understanding epigenomic changes that mediate variation in cellular differentiation across species, while also providing a valuable resource for studies of hematopoiesis.

The process whereby blood progenitor cells differentiate into red blood cells, known as erythropoiesis, is very similar between mice and humans. Yet, while studies of this process in mouse have substantially improved our knowledge of human erythropoiesis, recent work has shown a significant divergence in global gene expression across species, suggesting that extrapolation from mouse models to human is not always straightforward. In order to better understand these differences, we have performed a comparative epigenomic analysis of six histone modifications and four master transcription factors. By globally comparing chromatin structure across primary cells and model cell lines in both species, we discovered that while chromatin structure is well conserved at orthologous promoters, subtle changes are predictive of species-specific gene expression. Furthermore, we discovered that the genomic localizations of master transcription factors are poorly conserved, and species-specific losses or gains are associated with changes to the underlying chromatin structure and concomitant gene expression. By using our comparative epigenomics framework, we identified a putative human-specific cis-regulatory module that drives expression of human, but not mouse, GDF15, a gene implicated in iron homeostasis. Our results provide a resource to aid researchers in interpreting genetic and epigenetic differences between species.

Wogonin induces cell cycle arrest and erythroid differentiation in imatinib-resistant K562 cells and primary CML cells

Wogonin, a flavonoid derived from Scutellaria baicalensis Georgi, has been demonstrated to be highly effective in treating hematologic malignancies. In this study, we investigated the anticancer effects of wogonin on K562 cells, K562 imatinib-resistant cells, and primary patient-derived CML cells. Wogonin up-regulated transcription factor GATA-1 and enhanced binding between GATA-1 and FOG-1, thereby increasing expression of erythroid-differentiation genes. Wogonin also up-regulated the expression of p21 and induced cell cycle arrest. Studies employing benzidine staining and analyses of cell surface markers glycophorin A (GPA) and CD71 indicated that wogonin promoted differentiation of K562, imatinib-resistant K562, and primary patient-derived CML cells. Wogonin also enhanced binding between GATA-1 and MEK, resulting in inhibition of the growth of CML cells. Additionally, in vivo studies showed that wogonin decreased the number of CML cells and prolonged survival of NOD/SCID mice injected with K562 and imatinib-resistant K562 cells. These data suggested that wogonin induces cycle arrest and erythroid differentiation in vitro and inhibits proliferation in vivo.

Automated discovery of tissue-targeting enhancers and transcription factors from binding motif and gene function data

Identifying enhancers regulating gene expression remains an important and challenging task. While recent sequencing-based methods provide epigenomic characteristics that correlate well with enhancer activity, it remains onerous to comprehensively identify all enhancers across development. Here we introduce a computational framework to identify tissue-specific enhancers evolving under purifying selection. First, we incorporate high-confidence binding site predictions with target gene functional enrichment analysis to identify transcription factors (TFs) likely functioning in a particular context. We then search the genome for clusters of binding sites for these TFs, overcoming previous constraints associated with biased manual curation of TFs or enhancers. Applying our method to the placenta, we find 33 known and implicate 17 novel TFs in placental function, and discover 2,216 putative placenta enhancers. Using luciferase reporter assays, 31/36 (86%) tested candidates drive activity in placental cells. Our predictions agree well with recent epigenomic data in human and mouse, yet over half our loci, including 7/8 (87%) tested regions, are novel. Finally, we establish that our method is generalizable by applying it to 5 additional tissues: heart, pancreas, blood vessel, bone marrow, and liver.

Enhancers are distal gene regulatory elements that can activate tissue- and time-point specific gene expression. Identification of active enhancers is challenging, and is the subject of intense investigation. We developed an automated computational framework to predict transcription factors (TFs) and enhancers that target a tissue of interest by combining two growing resources: TF binding motifs and target gene function annotations. We applied our framework to the placenta, and confirmed our enhancer predictions are more active in placental cell types than others. To demonstrate generalizability, we applied our approach to 5 additional tissues. The combination of experimental sampling with computational prediction approaches will aid in the identification of those enhancers that are most likely active in a particular tissue, as well as the characterization of groups of TFs associated with these enhancers.

PRISM offers a comprehensive genomic approach to transcription factor function prediction

The human genome encodes 1500–2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells.

Identification of biologically relevant enhancers in human erythroid cells

Identification of cell type-specific enhancers is important for understanding the regulation of programs controlling cellular development and differentiation. Enhancers are typically marked by the co-transcriptional activator protein p300 or by groups of cell-expressed transcription factors. We hypothesized that a unique set of enhancers regulates gene expression in human erythroid cells, a highly specialized cell type evolved to provide adequate amounts of oxygen throughout the body. Using chromatin immunoprecipitation followed by massively parallel sequencing, genome-wide maps of candidate enhancers were constructed for p300 and four transcription factors, GATA1, NF-E2, KLF1, and SCL, using primary human erythroid cells. These data were combined with gene expression analyses, and candidate enhancers were identified. Consistent with their predicted function as candidate enhancers, there was statistically significant enrichment of p300 and combinations of co-localizing erythroid transcription factors within 1-50 kb of the transcriptional start site (TSS) of genes highly expressed in erythroid cells. Candidate enhancers were also enriched near genes with known erythroid cell function or phenotype. Candidate enhancers exhibited moderate conservation with mouse and minimal conservation with nonplacental vertebrates. Candidate enhancers were mapped to a set of erythroid-associated, biologically relevant, SNPs from the genome-wide association studies (GWAS) catalogue of NHGRI, National Institutes of Health. Fourteen candidate enhancers, representing 10 genetic loci, mapped to sites associated with biologically relevant erythroid traits. Fragments from these loci directed statistically significant expression in reporter gene assays. Identification of enhancers in human erythroid cells will allow a better understanding of erythroid cell development, differentiation, structure, and function and provide insights into inherited and acquired hematologic disease.

Nuclear RNA sequencing of the mouse erythroid cell transcriptome

In addition to protein coding genes a substantial proportion of mammalian genomes are transcribed. However, most transcriptome studies investigate steady-state mRNA levels, ignoring a considerable fraction of the transcribed genome. In addition, steady-state mRNA levels are influenced by both transcriptional and posttranscriptional mechanisms, and thus do not provide a clear picture of transcriptional output. Here, using deep sequencing of nuclear RNAs (nucRNA-Seq) in parallel with chromatin immunoprecipitation sequencing (ChIP-Seq) of active RNA polymerase II, we compared the nuclear transcriptome of mouse anemic spleen erythroid cells with polymerase occupancy on a genome-wide scale. We demonstrate that unspliced transcripts quantified by nucRNA-seq correlate with primary transcript frequencies measured by RNA FISH, but differ from steady-state mRNA levels measured by poly(A)-enriched RNA-seq. Highly expressed protein coding genes showed good correlation between RNAPII occupancy and transcriptional output; however, genome-wide we observed a poor correlation between transcriptional output and RNAPII association. This poor correlation is due to intergenic regions associated with RNAPII which correspond with transcription factor bound regulatory regions and a group of stable, nuclear-retained long non-coding transcripts. In conclusion, sequencing the nuclear transcriptome provides an opportunity to investigate the transcriptional landscape in a given cell type through quantification of unspliced primary transcripts and the identification of nuclear-retained long non-coding RNAs.

Classification of human genomic regions based on experimentally determined binding sites of more than 100 transcription-related factors

Background

Transcription factors function by binding different classes of regulatory elements. The Encyclopedia of DNA Elements (ENCODE) project has recently produced binding data for more than 100 transcription factors from about 500 ChIP-seq experiments in multiple cell types. While this large amount of data creates a valuable resource, it is nonetheless overwhelmingly complex and simultaneously incomplete since it covers only a small fraction of all human transcription factors.

Results

As part of the consortium effort in providing a concise abstraction of the data for facilitating various types of downstream analyses, we constructed statistical models that capture the genomic features of three paired types of regions by machine-learning methods: firstly, regions with active or inactive binding; secondly, those with extremely high or low degrees of co-binding, termed HOT and LOT regions; and finally, regulatory modules proximal or distal to genes. From the distal regulatory modules, we developed computational pipelines to identify potential enhancers, many of which were validated experimentally. We further associated the predicted enhancers with potential target transcripts and the transcription factors involved. For HOT regions, we found a significant fraction of transcription factor binding without clear sequence motifs and showed that this observation could be related to strong DNA accessibility of these regions.

Conclusions

Overall, the three pairs of regions exhibit intricate differences in chromosomal locations, chromatin features, factors that bind them, and cell-type specificity. Our machine learning approach enables us to identify features potentially general to all transcription factors, including those not included in the data.

Genomic approaches towards finding cis-regulatory modules in animals

Differential gene expression is the fundamental mechanism underlying animal development and cell differentiation. However, it is a challenge to identify comprehensively and accurately the DNA sequences that are required to regulate gene expression: namely, cis-regulatory modules (CRMs). Three major features, either singly or in combination, are used to predict CRMs: clusters of transcription factor binding site motifs, non-coding DNA that is under evolutionary constraint and biochemical marks associated with CRMs, such as histone modifications and protein occupancy. The validation rates for predictions indicate that identifying diagnostic biochemical marks is the most reliable method, and understanding is enhanced by the analysis of motifs and conservation patterns within those predicted CRMs.

Validation of skeletal muscle cis-regulatory module predictions reveals nucleotide composition bias in functional enhancers

We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs) using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions.

For efficient identification of genomic sequences responsible for regulating gene expression, a number of computer programs have been developed for automatic annotation of these regulatory regions. We searched for potential regulatory regions responsible for controlling the expression of skeletal muscle-specific genes using these programs, and validated the predictions in a popular cell culture model for muscle. We were able to identify 19 previously uncharacterized regulatory regions for muscle genes. The accuracy of the predictions made by these programs leaves much to be desired, leading us to conclude that other signals in addition to the sequence information will be required to achieve sufficient predictive power for genome annotation. Genomic regions with confirmed regulatory function were compared against non-functional sequences, revealing sequence conservation, composition and chromatin modification properties as important signals in determining regulatory region functionality.

Dynamics of the epigenetic landscape during erythroid differentiation after GATA1 restoration

Interplays among lineage-specific nuclear proteins, chromatin modifying enzymes, and the basal transcription machinery govern cellular differentiation, but their dynamics of action and coordination with transcriptional control are not fully understood. Alterations in chromatin structure appear to establish a permissive state for gene activation at some loci, but they play an integral role in activation at other loci. To determine the predominant roles of chromatin states and factor occupancy in directing gene regulation during differentiation, we mapped chromatin accessibility, histone modifications, and nuclear factor occupancy genome-wide during mouse erythroid differentiation dependent on the master regulatory transcription factor GATA1. Notably, despite extensive changes in gene expression, the chromatin state profiles (proportions of a gene in a chromatin state dominated by activating or repressive histone modifications) and accessibility remain largely unchanged during GATA1-induced erythroid differentiation. In contrast, gene induction and repression are strongly associated with changes in patterns of transcription factor occupancy. Our results indicate that during erythroid differentiation, the broad features of chromatin states are established at the stage of lineage commitment, largely independently of GATA1. These determine permissiveness for expression, with subsequent induction or repression mediated by distinctive combinations of transcription factors.

A varying threshold method for ChIP peak-calling using multiple sources of information

Motivation: Gene regulation commonly involves interaction among DNA, proteins and biochemical conditions. Using chromatin immunoprecipitation (ChIP) technologies, protein–DNA interactions are routinely detected in the genome scale. Computational methods that detect weak protein-binding signals and simultaneously maintain a high specificity yet remain to be challenging. An attractive approach is to incorporate biologically relevant data, such as protein co-occupancy, to improve the power of protein-binding detection. We call the additional data related with the target protein binding as supporting tracks.

Results: We propose a novel but rigorous statistical method to identify protein occupancy in ChIP data using multiple supporting tracks (PASS2). We demonstrate that utilizing biologically related information can significantly increase the discovery of true protein-binding sites, while still maintaining a desired level of false positive calls. Applying the method to GATA1 restoration in mouse erythroid cell line, we detected many new GATA1-binding sites using GATA1 co-occupancy data.

Availability:http://stat.psu.edu/∼yuzhang/pass2.tar

Contact:yuzhang@stat.psu.edu

ChIP-Seq identification of weakly conserved heart enhancers

Accurate control of tissue-specific gene expression plays a pivotal role in heart development, but few cardiac transcriptional enhancers have thus far been identified. Extreme noncoding-sequence conservation has successfully predicted enhancers that are active in many tissues but has failed to identify substantial numbers of heart-specific enhancers. Here, we used ChIP-Seq with the enhancer-associated protein p300 from mouse embryonic day 11.5 heart tissue to identify over 3,000 candidate heart enhancers genome wide. Compared to enhancers active in other tissues we studied at this time point, most candidate heart enhancers were less deeply conserved in vertebrate evolution. Nevertheless, transgenic mouse assays of 130 candidate regions revealed that most function reproducibly as enhancers active in the heart, irrespective of their degree of evolutionary constraint. These results provide evidence for a large population of poorly conserved heart enhancers and suggest that the evolutionary conservation of embryonic enhancers can vary depending on tissue type.

Evolution of gene regulation--on the road towards computational inferences

If fragments of DNA are transcribed (expressed), they deserve to be called (parts of) a gene. Whether transcription takes place depends on the 'gene regulatory network'. This network is defined as the complex interplay of the sequence, biochemical modifications and structure of the chromosomal DNA with the regulatory proteins/RNA (transcription factors, co-factors, regulating RNA and the transcriptional apparatus itself). Gene regulatory networks play a role in various stages of development as well as in the maintenance of the organism; in this review we will concentrate on the former. Their evolutionary reconstruction is daunting (to say the least), and bioinformatics tools are in their infancy. However, gain of understanding offers a reward beyond itself, since evolutionary considerations can enable discoveries in the first place, e.g. the computational identification of conserved transcription factor binding sites. We discuss the evolution of gene regulation in the context of the 'Genetic Theory of Morphological Evolution' as described by Carroll, identifying those parts of the theory that are relevant for bioinformatics, and their implications. We discuss the important question of how bioinformatics analysis results on the evolution of gene regulation may be validated. Finally, we briefly exemplify use of the UCSC genome browser, exploiting its pre-computed alignments to describe the evolution of gene regulation.

GATA-1 directly regulates p21 gene expression during erythroid differentiation

Lineage-determination transcription factors coordinate cell differentiation and proliferation by controlling the synthesis of lineage-specific gene products as well as cell cycle regulators. GATA-1 is a master regulator of erythropoiesis. Its role in regulating erythroid-specific genes has been extensively studied, whereas its role in controlling genes that regulate cell proliferation is less understood. Ectopic expression of GATA-1 in erythroleukemia cells releases the block to their differentiation and leads to terminal cell division. An early event in reprogramming the erythroleukemia cells is induction of the cyclin-dependent kinase inhibitor p21. Remarkably, ectopic expression of p21 also induces the erythroleukemia cells to differentiate. We now report that GATA-1 directly regulates transcription of the p21 gene in both erythroleukemia cells and normal erythroid progenitors. Using reporter, electrophoretic mobility shift, and chromatin immunoprecipitation assays, we show that GATA-1 stimulates p21 gene transcription by binding to consensus binding sites in the upstream region of the p21 gene promoter. This activity is also dependent on a binding site for Sp1/KLF-like factors near the transcription start site. Our findings indicate that p21 is a crucial downstream gene target and effector of GATA-1 during red blood cell terminal differentiation.

Primary sequence and epigenetic determinants of in vivo occupancy of genomic DNA by GATA1

DNA sequence motifs and epigenetic modifications contribute to specific binding by a transcription factor, but the extent to which each feature determines occupancy in vivo is poorly understood. We addressed this question in erythroid cells by identifying DNA segments occupied by GATA1 and measuring the level of trimethylation of histone H3 lysine 27 (H3K27me3) and monomethylation of H3 lysine 4 (H3K4me1) along a 66 Mb region of mouse chromosome 7. While 91% of the GATA1-occupied segments contain the consensus binding-site motif WGATAR, only ∼0.7% of DNA segments with such a motif are occupied. Using a discriminative motif enumeration method, we identified additional motifs predictive of occupancy given the presence of WGATAR. The specific motif variant AGATAA and occurrence of multiple WGATAR motifs are both strong discriminators. Combining motifs to pair a WGATAR motif with a binding site motif for GATA1, EKLF or SP1 improves discriminative power. Epigenetic modifications are also strong determinants, with the factor-bound segments highly enriched for H3K4me1 and depleted of H3K27me3. Combining primary sequence and epigenetic determinants captures 52% of the GATA1-occupied DNA segments and substantially increases the specificity, to one out of seven segments with the required motif combination and epigenetic signals being bound.

Dissecting the regulatory switches of development: lessons from enhancer evolution in Drosophila

Cis-regulatory modules are non-protein-coding regions of DNA essential for the control of gene expression. One class of regulatory modules is embryonic enhancers, which drive gene expression during development as a result of transcription factor protein binding at the enhancer sequences. Recent comparative studies have begun to investigate the evolution of the sequence architecture within enhancers. These analyses are illuminating the way that developmental biologists think about enhancers by revealing their molecular mechanism of function.

Erythroid GATA1 function revealed by genome-wide analysis of transcription factor occupancy, histone modifications, and mRNA expression

The transcription factor GATA1 regulates an extensive program of gene activation and repression during erythroid development. However, the associated mechanisms, including the contributions of distal versus proximal cis-regulatory modules, co-occupancy with other transcription factors, and the effects of histone modifications, are poorly understood. We studied these problems genome-wide in a Gata1 knockout erythroblast cell line that undergoes GATA1-dependent terminal maturation, identifying 2616 GATA1-responsive genes and 15,360 GATA1-occupied DNA segments after restoration of GATA1. Virtually all occupied DNA segments have high levels of H3K4 monomethylation and low levels of H3K27me3 around the canonical GATA binding motif, regardless of whether the nearby gene is induced or repressed. Induced genes tend to be bound by GATA1 close to the transcription start site (most frequently in the first intron), have multiple GATA1-occupied segments that are also bound by TAL1, and show evolutionary constraint on the GATA1-binding site motif. In contrast, repressed genes are further away from GATA1-occupied segments, and a subset shows reduced TAL1 occupancy and increased H3K27me3 at the transcription start site. Our data expand the repertoire of GATA1 action in erythropoiesis by defining a new cohort of target genes and determining the spatial distribution of cis-regulatory modules throughout the genome. In addition, we begin to establish functional criteria and mechanisms that distinguish GATA1 activation from repression at specific target genes. More broadly, these studies illustrate how a "master regulator" transcription factor coordinates tissue differentiation through a panoply of DNA and protein interactions.

Insights into GATA-1-mediated gene activation versus repression via genome-wide chromatin occupancy analysis

The transcription factor GATA-1 is required for terminal erythroid maturation and functions as an activator or repressor depending on gene context. Yet its in vivo site selectivity and ability to distinguish between activated versus repressed genes remain incompletely understood. In this study, we performed GATA-1 ChIP-seq in erythroid cells and compared it to GATA-1-induced gene expression changes. Bound and differentially expressed genes contain a greater number of GATA-binding motifs, a higher frequency of palindromic GATA sites, and closer occupancy to the transcriptional start site versus nondifferentially expressed genes. Moreover, we show that the transcription factor Zbtb7a occupies GATA-1-bound regions of some direct GATA-1 target genes, that the presence of SCL/TAL1 helps distinguish transcriptional activation versus repression, and that polycomb repressive complex 2 (PRC2) is involved in epigenetic silencing of a subset of GATA-1-repressed genes. These data provide insights into GATA-1-mediated gene regulation in vivo.

Chromatin architecture and transcription factor binding regulate expression of erythrocyte membrane protein genes

Erythrocyte membrane protein genes serve as excellent models of complex gene locus structure and function, but their study has been complicated by both their large size and their complexity. To begin to understand the intricate interplay of transcription, dynamic chromatin architecture, transcription factor binding, and genomic organization in regulation of erythrocyte membrane protein genes, we performed chromatin immunoprecipitation (ChIP) coupled with microarray analysis and ChIP coupled with massively parallel DNA sequencing in both erythroid and nonerythroid cells. Unexpectedly, most regions of GATA-1 and NF-E2 binding were remote from gene promoters and transcriptional start sites, located primarily in introns. Cooccupancy with FOG-1, SCL, and MTA-2 was found at all regions of GATA-1 binding, with cooccupancy of SCL and MTA-2 also found at regions of NF-E2 binding. Cooccupancy of GATA-1 and NF-E2 was found frequently. A common signature of histone H3 trimethylation at lysine 4, GATA-1, NF-E2, FOG-1, SCL, and MTA-2 binding and consensus GATA-1-E-box binding motifs located 34 to 90 bp away from NF-E2 binding motifs was found frequently in erythroid cell-expressed genes. These results provide insights into our understanding of membrane protein gene regulation in erythropoiesis and the regulation of complex genetic loci in erythroid and nonerythroid cells and identify numerous candidate regions for mutations associated with membrane-linked hemolytic anemia.

ChIP-seq accurately predicts tissue-specific activity of enhancers

A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover because they are scattered among the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here we present the results of chromatin immunoprecipitation with the enhancer-associated protein p300 followed by massively parallel sequencing, and map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain and limb tissue. We tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases demonstrated reproducible enhancer activity in the tissues that were predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities, and suggest that such data sets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.

SCL and associated proteins distinguish active from repressive GATA transcription factor complexes

GATA-1 controls hematopoietic development by activating and repressing gene transcription, yet the in vivo mechanisms that specify these opposite activities are unknown. By examining the composition of GATA-1-associated protein complexes in a conditional erythroid rescue system as well as through the use of tiling arrays we detected the SCL/TAL1, LMO2, Ldb1, E2A complex at all positively acting GATA-1-bound elements examined. Similarly, the SCL complex is present at all activating GATA elements in megakaryocytes and mast cells. In striking contrast, at sites where GATA-1 functions as a repressor, the SCL complex is depleted. A DNA-binding defective form of SCL maintains association with a subset of active GATA elements indicating that GATA-1 is a key determinant for SCL recruitment. Knockdown of LMO2 selectively impairs activation but not repression by GATA-1. ETO-2, an SCL-associated protein with the potential for transcription repression, is also absent from GATA-1-repressed genes but, unlike SCL, fails to accumulate at GATA-1-activated genes. Together, these studies identify the SCL complex as a critical and consistent determinant of positive GATA-1 activity in multiple GATA-1-regulated hematopoietic cell lineages.