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1.  Chromatin Immunoprecipitation from Human Embryonic Stem Cells 
The functional and structural complexity of the myriad of cells in metazoan organisms arises from a small number of stem cells. Stem cells are characterized by two fundamental properties: self-renewal and multipotency that allows a stem cell to differentiate into virtually any cell type 1. The progression stem cell to differentiated cell is characterized by loss of multipotency, structural and morphological changes and the hierarchic activity of transcription factors and signaling molecules, whose activities establish and maintain cell-type specific gene expression patterns. At the molecular level, cell differentiation involves dynamic changes of the structure and composition of chromatin and the detection of those dynamic changes can provide valuable insights into the functional features of stem cells and the cell differentiation process 2,3. Chromatin is a highly compacted DNA-protein complex that forms when cells package chromosomal DNA with proteins, mainly histones 4. Stemcellness and cell differentiation has been correlated with the presence of specific arrays of regulatory proteins such as epigenetic factors, histone variants, and transcription factors 2,3,5.
Chromatin immunoprecipitation (ChIP) provides a valuable method to monitor the presence of RNA, proteins, and protein modifications in chromatin 6,7. The comparison of chromatin from different cell types can elucidate dynamic changes in protein-chromatin associations that occur during cell differentiation.
Chromatin immunoprecipitation involves the purification of in vivo cross-linked chromatin. The isolated chromatin is reduced to smaller fragments by enzymatic digestion or mechanical force. Chromatin fragments are precipitated using specific antibodies to target proteins or protein and DNA modifications. The precipitated DNA or RNA is purified and used as a template for PCR or DNA microarray based assays. Prerequisites for a successful ChIP are high quality antibodies to the desired antigen and the availability of chromatin from control cells that do not express the target molecule. ChIP can correlate the presence of proteins, protein and RNA modifications, and RNA with specific target DNA, and depending on the choice of outread tool, detects the association of target molecules at specific target genes or in the context of an entire genome. The comparison of the distribution of proteins in the chromatin of differentiating cells can elucidate the dynamic changes of chromatin composition that coincide with the progression of cells along a cell lineage.
doi:10.3791/780
PMCID: PMC3253610  PMID: 19066517
2.  Epigenetic Regulation of Hematopoietic Stem Cells 
Hematopoietic stem cells are endowed with a distinct potential to bolster self-renewal and to generate progeny that differentiate into mature cells of myeloid and lymphoid lineages. Both hematopoietic stem cells and mature cells have the same genome, but their gene expression is controlled by an additional layer of epigenetics such as DNA methylation and post-translational histone modifications, enabling each cell-type to acquire various forms and functions. Until recently, several studies have largely focussed on the transcription factors andniche factors for the understanding of the molecular mechanisms by which hematopoietic cells replicate and differentiate. Several lines of emerging evidence suggest that epigenetic modifications eventually result in a defined chromatin structure and an “individual” gene expression pattern, which play an essential role in the regulation of hematopoietic stem cell self-renewal and differentiation. Distinct epigenetic marks decide which sets of genes may be expressed and which genes are kept silent. Epigenetic mechanisms are interdependent and ensure lifelong production of blood and bone marrow, thereby contributing to stem cell homeostasis. The epigenetic analysis of hematopoiesis raises the exciting possibility that chromatin structure is dynamic enough for regulated expression of genes. Though controlled chromatin accessibility plays an essential role in maintaining blood homeostasis; mutations in chromatin impacts on the regulation of genes critical to the development of leukemia. In this review, we explored the contribution of epigenetic machinery which has implications for the ramification of molecular details of hematopoietic self-renewal for normal development and underlying events that potentially co-operate to induce leukemia.
doi:10.15283/ijsc.2016.9.1.36
PMCID: PMC4961102  PMID: 27426084
Epigenetics; Self-renewal; Regulation; Hematopoietic stem cells
3.  A multiplexed system for quantitative comparisons of chromatin landscapes 
Molecular cell  2015;61(1):170-180.
Genome-wide profiling of histone modifications can provide systematic insight into the regulatory elements and programs engaged in a given cell type. However, conventional chromatin immunoprecipitation and sequencing (ChIP-seq) does not capture quantitative information on histone modification levels, requires large amounts of starting material, and involves tedious processing of each individual sample. Here we address these limitations with a technology that leverages DNA barcoding to profile chromatin quantitatively and in multiplexed format. We concurrently map relative levels of multiple histone modifications across multiple samples, each comprising as few as a thousand cells. We demonstrate the technology by monitoring dynamic changes following inhibition of P300, EZH2 or KDM5, by linking altered epigenetic landscapes to chromatin regulator mutations, and by mapping active and repressive marks in purified human hematopoietic stem cells. Hence, this technology enables quantitative studies of chromatin state dynamics across rare cell types, genotypes, environmental conditions and drug treatments.
doi:10.1016/j.molcel.2015.11.003
PMCID: PMC4707994  PMID: 26687680
4.  Bayesian Inference of Spatial Organizations of Chromosomes 
PLoS Computational Biology  2013;9(1):e1002893.
Knowledge of spatial chromosomal organizations is critical for the study of transcriptional regulation and other nuclear processes in the cell. Recently, chromosome conformation capture (3C) based technologies, such as Hi-C and TCC, have been developed to provide a genome-wide, three-dimensional (3D) view of chromatin organization. Appropriate methods for analyzing these data and fully characterizing the 3D chromosomal structure and its structural variations are still under development. Here we describe a novel Bayesian probabilistic approach, denoted as “Bayesian 3D constructor for Hi-C data” (BACH), to infer the consensus 3D chromosomal structure. In addition, we describe a variant algorithm BACH-MIX to study the structural variations of chromatin in a cell population. Applying BACH and BACH-MIX to a high resolution Hi-C dataset generated from mouse embryonic stem cells, we found that most local genomic regions exhibit homogeneous 3D chromosomal structures. We further constructed a model for the spatial arrangement of chromatin, which reveals structural properties associated with euchromatic and heterochromatic regions in the genome. We observed strong associations between structural properties and several genomic and epigenetic features of the chromosome. Using BACH-MIX, we further found that the structural variations of chromatin are correlated with these genomic and epigenetic features. Our results demonstrate that BACH and BACH-MIX have the potential to provide new insights into the chromosomal architecture of mammalian cells.
Author Summary
Understanding how chromosomes fold provides insights into the complex relationship among chromatin structure, gene activity and the functional state of the cell. Recently, chromosome conformation capture based technologies, such as Hi-C and TCC, have been developed to provide a genome-wide, high resolution and three-dimensional (3D) view of chromatin organization. However, statistical methods for analyzing these data are still under development. Here we propose two Bayesian methods, BACH to infer the consensus 3D chromosomal structure and BACH-MIX to reveal structural variations of chromatin in a cell population. Applying BACH and BACH-MIX to a high resolution Hi-C dataset, we found that most local genomic regions exhibit homogeneous 3D chromosomal structures. Furthermore, spatial properties of 3D chromosomal structures and structural variations of chromatin are associated with several genomic and epigenetic features. Noticeably, gene rich, accessible and early replicated genomic regions tend to be more elongated and exhibit higher structural variations than gene poor, inaccessible and late replicated genomic regions.
doi:10.1371/journal.pcbi.1002893
PMCID: PMC3561073  PMID: 23382666
5.  Progressive Chromatin Condensation and H3K9 Methylation Regulate the Differentiation of Embryonic and Hematopoietic Stem Cells 
Stem Cell Reports  2015;5(5):728-740.
Summary
Epigenetic regulation serves as the basis for stem cell differentiation into distinct cell types, but it is unclear how global epigenetic changes are regulated during this process. Here, we tested the hypothesis that global chromatin organization affects the lineage potential of stem cells and that manipulation of chromatin dynamics influences stem cell function. Using nuclease sensitivity assays, we found a progressive decrease in chromatin digestion among pluripotent embryonic stem cells (ESCs), multipotent hematopoietic stem cells (HSCs), and mature hematopoietic cells. Quantitative high-resolution microscopy revealed that ESCs contain significantly more euchromatin than HSCs, with a further reduction in mature cells. Increased cellular maturation also led to heterochromatin localization to the nuclear periphery. Functionally, prevention of heterochromatin formation by inhibition of the histone methyltransferase G9A resulted in delayed HSC differentiation. Our results demonstrate global chromatin rearrangements during stem cell differentiation and that heterochromatin formation by H3K9 methylation regulates HSC differentiation.
Graphical Abstract
Highlights
•Nuclease sensitivity decreases progressively with stem cell differentiation•Distinct chromatin architecture is apparent in cells of different lineage potential•Stem cell differentiation leads to perinuclear heterochromatin localization•G9a-mediated heterochromatin formation facilitates stem cell differentiation
Forsberg and colleagues use a variety of approaches to investigate global chromatin structure and architecture in pluripotent, multipotent, and differentiated cells. They show that progressive changes in nuclease sensitivity, chromatin condensation, and heterochromatin localization correlate with the lineage potential of embryonic and adult stem cells and committed cells. Functionally, inhibition of heterochromatin formation delayed hematopoietic stem cell differentiation. These data provide new insights on the epigenetic regulation of stem cell lineage potential and differentiation.
doi:10.1016/j.stemcr.2015.09.009
PMCID: PMC4649257  PMID: 26489895
6.  C/EBPα Is Required for Long-Term Self-Renewal and Lineage Priming of Hematopoietic Stem Cells and for the Maintenance of Epigenetic Configurations in Multipotent Progenitors 
PLoS Genetics  2014;10(1):e1004079.
Transcription factors are key regulators of hematopoietic stem cells (HSCs) and act through their ability to bind DNA and impact on gene transcription. Their functions are interpreted in the complex landscape of chromatin, but current knowledge on how this is achieved is very limited. C/EBPα is an important transcriptional regulator of hematopoiesis, but its potential functions in HSCs have remained elusive. Here we report that C/EBPα serves to protect adult HSCs from apoptosis and to maintain their quiescent state. Consequently, deletion of Cebpa is associated with loss of self-renewal and HSC exhaustion. By combining gene expression analysis with genome-wide assessment of C/EBPα binding and epigenetic configurations, we show that C/EBPα acts to modulate the epigenetic states of genes belonging to molecular pathways important for HSC function. Moreover, our data suggest that C/EBPα acts as a priming factor at the HSC level where it actively promotes myeloid differentiation and counteracts lymphoid lineage choice. Taken together, our results show that C/EBPα is a key regulator of HSC biology, which influences the epigenetic landscape of HSCs in order to balance different cell fate options.
Author Summary
Hematopoietic stem cells (HSCs) are required for the lifelong generation of blood cells. To fulfill this requirement HSCs carefully balance cell fate decisions such as self-renewal, differentiation, quiescence, proliferation and death. These features are regulated in part by transcription factors, which act by controlling the expression of genes important for the functional properties of HSCs. C/EBPα is a well-known inducer of myeloid differentiation. It is lowly expressed in HSCs and its potential function in these cells has been extensively debated. Here, we demonstrate that Cebpa deletion impacts on HSC self-renewal, differentiation, quiescence and survival. Through gene expression and ChIP-seq analyses of stem and progenitor cell-enriched cell populations, we further show that C/EBPα binds to regulatory regions of genes that are induced during granulocytic differentiation, suggesting that C/EBPα acts to prime HSCs for differentiation along the myeloid lineage. Finally, we demonstrate that C/EBPα loss leads to epigenetic changes at genes central to HSC biology, which implies that it may act to recruit chromatin writers/erasers through mechanisms that remain to be characterized. In conclusion, our work identifies C/EBPα as a central hub for HSC function and highlights how a single transcription factor may coordinate several HSC fate options.
doi:10.1371/journal.pgen.1004079
PMCID: PMC3886906  PMID: 24415956
7.  Embryonic Stem Cell Specific “Master” Replication Origins at the Heart of the Loss of Pluripotency 
PLoS Computational Biology  2015;11(2):e1003969.
Epigenetic regulation of the replication program during mammalian cell differentiation remains poorly understood. We performed an integrative analysis of eleven genome-wide epigenetic profiles at 100 kb resolution of Mean Replication Timing (MRT) data in six human cell lines. Compared to the organization in four chromatin states shared by the five somatic cell lines, embryonic stem cell (ESC) line H1 displays (i) a gene-poor but highly dynamic chromatin state (EC4) associated to histone variant H2AZ rather than a HP1-associated heterochromatin state (C4) and (ii) a mid-S accessible chromatin state with bivalent gene marks instead of a polycomb-repressed heterochromatin state. Plastic MRT regions (≲ 20% of the genome) are predominantly localized at the borders of U-shaped timing domains. Whereas somatic-specific U-domain borders are gene-dense GC-rich regions, 31.6% of H1-specific U-domain borders are early EC4 regions enriched in pluripotency transcription factors NANOG and OCT4 despite being GC poor and gene deserts. Silencing of these ESC-specific “master” replication initiation zones during differentiation corresponds to a loss of H2AZ and an enrichment in H3K9me3 mark characteristic of late replicating C4 heterochromatin. These results shed a new light on the epigenetically regulated global chromatin reorganization that underlies the loss of pluripotency and lineage commitment.
Author Summary
During development, embryonic stem cell (ESC) enter a program of cell differentiation eventually leading to all the necessary differentiated cell types. Understanding the mechanisms responsible for the underlying modifications of the gene expression program is of fundamental importance, as it will likely have strong impact on the development of regenerative medicine. We show that besides some epigenetic regulation, ubiquitous master replication origins at replication timing U-domain borders shared by 6 human cell types are transcriptionally active open chromatin regions specified by a local enrichment in nucleosome free regions encoded in the DNA sequence suggesting that they have been selected during evolution. In contrast, ESC specific master replication origins bear a unique epigenetic signature (enrichment in CTCF, H2AZ, NANOG, OCT4, …) likely contributing to maintain ESC chromatin in a highly dynamic and accessible state that is refractory to polycomb and HP1 heterochromatin spreading. These ESC specific master origins thus appear as key genomic regions where epigenetic control of chromatin organization is at play to maintain pluripotency of stem cell lineages and to guide lineage commitment to somatic cell types.
doi:10.1371/journal.pcbi.1003969
PMCID: PMC4319821  PMID: 25658386
8.  Isoform-Specific Potentiation of Stem and Progenitor Cell Engraftment by AML1/RUNX1  
PLoS Medicine  2007;4(5):e172.
Background
AML1/RUNX1 is the most frequently mutated gene in leukaemia and is central to the normal biology of hematopoietic stem and progenitor cells. However, the role of different AML1 isoforms within these primitive compartments is unclear. Here we investigate whether altering relative expression of AML1 isoforms impacts the balance between cell self-renewal and differentiation in vitro and in vivo.
Methods and Findings
The human AML1a isoform encodes a truncated molecule with DNA-binding but no transactivation capacity. We used a retrovirus-based approach to transduce AML1a into primitive haematopoietic cells isolated from the mouse. We observed that enforced AML1a expression increased the competitive engraftment potential of murine long-term reconstituting stem cells with the proportion of AML1a-expressing cells increasing over time in both primary and secondary recipients. Furthermore, AML1a expression dramatically increased primitive and committed progenitor activity in engrafted animals as assessed by long-term culture, cobblestone formation, and colony assays. In contrast, expression of the full-length isoform AML1b abrogated engraftment potential. In vitro, AML1b promoted differentiation while AML1a promoted proliferation of progenitors capable of short-term lymphomyeloid engraftment. Consistent with these findings, the relative abundance of AML1a was highest in the primitive stem/progenitor compartment of human cord blood, and forced expression of AML1a in these cells enhanced maintenance of primitive potential both in vitro and in vivo.
Conclusions
These data demonstrate that the “a” isoform of AML1 has the capacity to potentiate stem and progenitor cell engraftment, both of which are required for successful clinical transplantation. This activity is consistent with its expression pattern in both normal and leukaemic cells. Manipulating the balance of AML1 isoform expression may offer novel therapeutic strategies, exploitable in the contexts of leukaemia and also in cord blood transplantation in adults, in whom stem and progenitor cell numbers are often limiting.
The truncated "a" isoform of AML1 is shown to have the capacity to potentiate stem and progenitor cell engraftment, both of which are required for successful clinical transplantation.
Editors' Summary
Background.
Blood contains red blood cells (which carry oxygen round the body), platelets (which help the blood to clot), and white blood cells (which fight off infections). All these cells, which are regularly replaced, are derived from hematopoietic stem cells, blood-forming cells present in the bone marrow. Like all stem cells, hematopoietic stem cells self-renew (reproduce themselves) and produce committed progenitor cells, which develop into mature blood cells in a process called hematopoiesis. Many proteins control hematopoiesis, some of which are called transcription factors; these factors bind to DNA through their DNA-binding domain and then control the expression of genes (that is, how DNA is turned into proteins) through particular parts of the protein (their transcription regulatory domains). An important hematopoietic transcription factor is AML1—a protein first identified because of its involvement in acute myelogenous leukemia (AML, a form of blood cancer). Mutations (changes) in the AML1 gene are now known to be present in other types of leukemia, which are often characterized by overproliferation of immature blood cells.
Why Was This Study Done?
Because of AML1′s crucial role in hematopoiesis, knowing more about which genes it regulates and how its activity is regulated could provide clues to treating leukemia and to improving hematopoietic cell transplantation. Many cancer treatments destroy hematopoietic stem cells, leaving patients vulnerable to infection. Transplants of bone marrow or cord blood (the cord that links mother and baby during pregnancy contains peripheral blood stem cells) can replace the missing cells, but cord blood in particular often contains insufficient stem cells for successful transplantation. It would be useful, therefore, to expand the stem cell content of these tissues before transplantation. In this study, the researchers investigated the effect of AML1 on self-renewal and differentiation of hematopoietic stem and progenitor cells in the laboratory (in vitro) and in animals (in vivo). In particular, they have asked how two isoforms (closely related versions) of AML1 affect the ability of these cells to grow and differentiate (engraft) in mice after transplantation.
What Did the Researchers Do and Find?
The researchers artificially expressed AML1a and AML1b (both isoforms contain a DNA binding domain, but only AML1b has transcription regulatory domains) in mouse hematopoietic stem and progenitor cells and then tested the cells' ability to engraft in mice. AML1a-expressing cells engrafted better than unaltered cells and outgrew unaltered cells when transplanted as a mixture. AML1b-expressing cells, however, did not engraft. In vitro, AML1a-expressing cells grew more than AML1b-expressing cells, whereas differentiation was promoted in AML1b-expressing cells. To investigate whether the isoforms have the same effects in human cells, the researchers measured the amount of AML1a and AML1b mRNA (the template for protein production) made by progenitor cells in human cord blood. Although AML1b (together with AML1c, an isoform with similar characteristics) mRNA predominated in all the progenitor cell types, the relative abundance of AML1a was greatest in the stem and progenitor cells. Furthermore, forced expression of AML1a in these cells improved their ability to divide in vitro and to engraft in mice.
What Do These Findings Mean?
These findings indicate that AML1a expression increases the self-renewal capacity of hematopoietic stem and progenitor cells and consequently improves their ability to engraft in mice, whereas AML1b expression encourages the differentiation of these cell types. These activities are consistent with the expression patterns of the two isoforms in normal hematopoietic cells and in leukemic cells—the mutated AML made by many leukemic cells resembles AML1a. Because the AML1 isoforms were expressed at higher than normal levels in these experiments, the physiological relevance of these findings needs to be confirmed by showing that normal levels of AML1a and AML1b produce similar results. Nevertheless, these results suggest that manipulating the balance of AML1 isoforms made by hematopoietic cells might be useful clinically. In leukemia, a shift toward AML1b expression might slow the proliferation of leukemic cells and encourage their differentiation. Conversely, in cord blood transplantation, a shift toward AML1a expression might improve patient outcomes by expanding the stem and progenitor cell populations.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0040172.
Wikipedia has pages on hematopoiesis and hematopoietic stem cells (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
The US National Cancer Institute has a fact sheet on bone marrow and peripheral blood stem cell transplantation (in English and Spanish) and information for patients and professionals on leukemia (in English)
The American Society of Hematology provides patient information about blood diseases, including information on bone marrow and stem cell transplantation
doi:10.1371/journal.pmed.0040172
PMCID: PMC1868041  PMID: 17503961
9.  Epigenetic Mechanisms in Mood Disorders: Targeting Neuroplasticity 
Neuroscience  2013;0:112-130.
Developing novel therapeutics and diagnostic tools based upon an understanding of neuroplasticity is critical in order to improve the treatment and ultimately the prevention of a broad range of nervous system disorders. In the case of mood disorders, such as major depressive disorder and bipolar disorder, where diagnoses are based solely on nosology rather than pathophysiology, there exists a clear unmet medical need to advance our understanding of the underlying molecular mechanisms and to develop fundamentally new mechanism experimental medicines with improved efficacy. In this context, recent preclinical molecular, cellular, and behavioral findings have begun to reveal the importance of epigenetic mechanisms that alter chromatin structure and dynamically regulate patterns of gene expression that may play a critical role in the pathophysiology of mood disorders. Here, we will review recent advances involving the use of animal models in combination with genetic and pharmacological probes to dissect the underlying molecular mechanisms and neurobiological consequence of targeting this chromatin-mediated neuroplasticity. We discuss evidence for the direct and indirect effects of mood stabilizers, antidepressants, and antipsychotics, among their many other effects, on chromatin-modifying enzmyes and on the epigenetic state of defined genomic loci, in defined cell types and in specific regions of the brain. These data, as well as findings from patient-derived tissue, have also begun to reveal alterations of epigenetic mechanisms in the pathophysiology and treatment of mood disorders. We summarize growing evidence supporting the notion that selectively targeting chromatin-modifying complexes, including those containing histone deacetylases (HDACs), provides a means to reversibly alter the acetylation state of neuronal chromatin and benefically impact neuronal activity-regulated gene transcription and mood-related behaviors. Looking beyond current knowledge, we discuss how high-resolution, whole-genome methodologies, such as RNA-sequencing (RNA-Seq) for transcriptome analysis and chromatin immunoprecipitation-sequencng (ChIP-Seq) for analyzing genome-wide occupancy of chromatin-associated factors, are beginning to provide an unprecedented view of both specific genomic loci as well as global properties of chromatin in the nervous system. These methodologies when applied to the characterization of model systems, including those of patient-derived induced pluripotent (iPS) cell and induced neurons (iNs), will greatly shape our understanding of epigenetic mechanisms and the impact of genetic variation on the regulatory regions of the human genome that can affect neuroplasticty. Finally, we point out critical unanswered questions and areas where additional data are needed in order to better understand the potential to target mechanisms of chromatin-mediated neuroplasticity for novel treatments of mood and other psychiatric disorders.
doi:10.1016/j.neuroscience.2013.01.041
PMCID: PMC3830721  PMID: 23376737
10.  Allele-Specific Chromatin Immunoprecipitation Studies Show Genetic Influence on Chromatin State in Human Genome 
PLoS Genetics  2007;3(5):e81.
Several recent studies have shown a genetic influence on gene expression variation, including variation between the two chromosomes within an individual and variation between individuals at the population level. We hypothesized that genetic inheritance may also affect variation in chromatin states. To test this hypothesis, we analyzed chromatin states in 12 lymphoblastoid cells derived from two Centre d'Etude du Polymorphisme Humain families using an allele-specific chromatin immunoprecipitation (ChIP-on-chip) assay with Affymetrix 10K SNP chip. We performed the allele-specific ChIP-on-chip assays for the 12 lymphoblastoid cells using antibodies targeting at RNA polymerase II and five post-translation modified forms of the histone H3 protein. The use of multiple cell lines from the Centre d'Etude du Polymorphisme Humain families allowed us to evaluate variation of chromatin states across pedigrees. These studies demonstrated that chromatin state clustered by family. Our results support the idea that genetic inheritance can determine the epigenetic state of the chromatin as shown previously in model organisms. To our knowledge, this is the first demonstration in humans that genetics may be an important factor that influences global chromatin state mediated by histone modification, the hallmark of the epigenetic phenomena.
Author Summary
Human health and disease are determined by an interaction between genetic background and environmental exposures. Both normal development and disease are mediated by epigenetic regulation of gene expression. The epigenetic regulation causes heritable changes in gene expression, which is not associated with DNA sequence changes. Instead, it is mediated by chemical modification of DNA such as DNA methylation or by protein modifications such as histone acetylation and methylation. Although much has been known about epigenetic inheritance during development, little is known about the influence of the genetic background on epigenetic processes such as histone modifications. In this report the authors studied five histone modifications on a genome-wide level in cells from different families. Global epigenetic states, as measured by these histone modifications, showed a similar pattern for cells derived from the same family. This study demonstrates that genetic inheritance may be an important factor influencing global chromatin states mediated by histone modifications in humans. These observations illustrate the importance of integrating genetic and epigenetic information into studies of human health and complex diseases.
doi:10.1371/journal.pgen.0030081
PMCID: PMC1868950  PMID: 17511522
11.  CAF-1 Is Essential for Heterochromatin Organization in Pluripotent Embryonic Cells 
PLoS Genetics  2006;2(11):e181.
During mammalian development, chromatin dynamics and epigenetic marking are important for genome reprogramming. Recent data suggest an important role for the chromatin assembly machinery in this process. To analyze the role of chromatin assembly factor 1 (CAF-1) during pre-implantation development, we generated a mouse line carrying a targeted mutation in the gene encoding its large subunit, p150CAF-1. Loss of p150CAF-1 in homozygous mutants leads to developmental arrest at the 16-cell stage. Absence of p150CAF-1 in these embryos results in severe alterations in the nuclear organization of constitutive heterochromatin. We provide evidence that in wild-type embryos, heterochromatin domains are extensively reorganized between the two-cell and blastocyst stages. In p150CAF-1 mutant 16-cell stage embryos, the altered organization of heterochromatin displays similarities to the structure of heterochromatin in two- to four-cell stage wild-type embryos, suggesting that CAF-1 is required for the maturation of heterochromatin during preimplantation development. In embryonic stem cells, depletion of p150CAF-1 using RNA interference results in the mislocalization, loss of clustering, and decondensation of pericentric heterochromatin domains. Furthermore, loss of CAF-1 in these cells results in the alteration of epigenetic histone methylation marks at the level of pericentric heterochromatin. These alterations of heterochromatin are not found in p150CAF-1-depleted mouse embryonic fibroblasts, which are cells that are already lineage committed, suggesting that CAF-1 is specifically required for heterochromatin organization in pluripotent embryonic cells. Our findings underline the role of the chromatin assembly machinery in controlling the spatial organization and epigenetic marking of the genome in early embryos and embryonic stem cells.
Synopsis
Chromatin is the support of our genetic information. It is composed of numerous repeated units called nucleosomes, in which DNA wraps around a core of histone proteins. Modifications in the composition and biochemical properties of nucleosomes play major roles in the regulation of genome function. Such modifications are termed “epigenetic” when they are inherited across cell divisions and confer new information to chromatin, in addition to the genetic information provided by DNA. It is usually believed that during genome replication, the basic chromatin assembly machinery builds up “naïve” nucleosomes, and, in a subsequent step, nucleosomes are selectively modified by a series of enzymes to acquire epigenetic information. Here, the authors studied the role of a basic chromatin assembly factor (CAF-1) in mouse embryonic stem cells and early embryos. Surprisingly, they show that CAF-1 confers epigenetic information to specific genomic regions. In addition, this study revealed that CAF-1 is required for the proper spatial organization of chromosomes in the nucleus. This new knowledge may contribute to better understanding the role of chromatin in the maintenance of embryonic stem cell identity and plasticity.
doi:10.1371/journal.pgen.0020181
PMCID: PMC1630711  PMID: 17083276
12.  Histone demethylase LSD1-mediated repression of GATA-2 is critical for erythroid differentiation 
Background
The transcription factor GATA-2 is predominantly expressed in hematopoietic stem and progenitor cells and counteracts the erythroid-specific transcription factor GATA-1, to modulate the proliferation and differentiation of hematopoietic cells. During hematopoietic cell differentiation, GATA-2 exhibits dynamic expression patterns, which are regulated by multiple transcription factors.
Methods
Stable LSD1-knockdown cell lines were established by growing murine erythroleukemia (MEL) or mouse embryonic stem cells together with virus particles, in the presence of Polybrene® at 4 μg/mL, for 24–48 hours followed by puromycin selection (1 μg/mL) for 2 weeks. Real-time polymerase chain reaction (PCR)-based quantitative chromatin immunoprecipitation (ChIP) analysis was used to test whether the TAL1 transcription factor is bound to 1S promoter in the GATA-2 locus or whether LSD1 colocalizes with TAL1 at the 1S promoter. The sequential ChIP assay was utilized to confirm the role of LSD1 in the regulation of H3K4me2 at the GATA-2 locus during erythroid differentiation. Western blot analysis was employed to detect the protein expression. The alamarBlue® assay was used to examine the proliferation of the cells, and the absorbance was monitored at optical density (OD) 570 nm and OD 600 nm.
Results
In this study, we showed that LSD1 regulates the expression of GATA-2 during erythroid differentiation. Knockdown of LSD1 results in increased GATA-2 expression and inhibits the differentiation of MEL and embryonic stem cells. Furthermore, we demonstrated that LSD1 binds to the 1S promoter of the GATA-2 locus and suppresses GATA-2 expression, via histone demethylation.
Conclusion
Our data revealed that LSD1 mediates erythroid differentiation, via epigenetic modification of the GATA-2 locus.
doi:10.2147/DDDT.S81911
PMCID: PMC4482369  PMID: 26124638
LSD1; GATA factor switching; histone demethylation
13.  Embedding the Future of Regenerative Medicine into the Open Epigenomic Landscape of Pluripotent Human Embryonic Stem Cells 
It has been recognized that pluripotent human embryonic stem cells (hESCs) must be transformed into fate-restricted derivatives before use for cell therapy. Realizing the therapeutic potential of pluripotent hESC derivatives demands a better understanding of how a pluripotent cell becomes progressively constrained in its fate options to the lineages of tissue or organ in need of repair. Discerning the intrinsic plasticity and regenerative potential of human stem cell populations reside in chromatin modifications that shape the respective epigenomes of their derivation routes. The broad potential of pluripotent hESCs is defined by an epigenome constituted of open conformation of chromatin mediated by a pattern of Oct-4 global distribution that corresponds genome-wide closely with those of active chroma tin modifications. Dynamic alterations in chromatin states correlate with loss-of-Oct4-associated hESC differentiation. The epigenomic transition from pluripotence to restriction in lineage choices is characterized by genome-wide increases in histone H3K9 methylation that mediates global chromatin-silencing and somatic identity. Human stem cell derivatives retain more open epigenomic landscape, therefore, more developmental potential for scale-up regeneration, when derived from the hESCs in vitro than from the CNS tissue in vivo. Recent technology breakthrough enables direct conversion of pluripotent hESCs by small molecule induction into a large supply of lineage-specific neuronal cells or heart muscle cells with adequate capacity to regenerate neurons and contractile heart muscles for developing safe and effective stem cell therapies. Nuclear translocation of NAD-dependent histone deacetylase SIRT1 and global chromatin silencing lead to hESC cardiac fate determination, while silencing of pluripotence-associated hsa-miR-302 family and drastic up-regulation of neuroectodermal Hox miRNA hsa-miR-10 family lead to hESC neural fate determination. These recent studies place global chromatin dynamics as central to tracking the normal pluripotence and lineage progres sion of hESCs. Embedding lineage-specific genetic and epigenetic developmental programs into the open epigenomic landscape of pluripotent hESCs offers a new repository of human stem cell therapy derivatives for the future of regenerative medicine.
PMCID: PMC4190676  PMID: 25309947
Human embryonic stem cell; stem cell; pluripotent; epigenome; chromatin; regenerative medicine; neurological disease; heart disease; cell therapy
14.  CTCF and CohesinSA-1 Mark Active Promoters and Boundaries of Repressive Chromatin Domains in Primary Human Erythroid Cells 
PLoS ONE  2016;11(5):e0155378.
Background
CTCF and cohesinSA-1 are regulatory proteins involved in a number of critical cellular processes including transcription, maintenance of chromatin domain architecture, and insulator function. To assess changes in the CTCF and cohesinSA-1 interactomes during erythropoiesis, chromatin immunoprecipitation coupled with high throughput sequencing and mRNA transcriptome analyses via RNA-seq were performed in primary human hematopoietic stem and progenitor cells (HSPC) and primary human erythroid cells from single donors.
Results
Sites of CTCF and cohesinSA-1 co-occupancy were enriched in gene promoters in HSPC and erythroid cells compared to single CTCF or cohesin sites. Cell type-specific CTCF sites in erythroid cells were linked to highly expressed genes, with the opposite pattern observed in HSPCs. Chromatin domains were identified by ChIP-seq with antibodies against trimethylated lysine 27 histone H3, a modification associated with repressive chromatin. Repressive chromatin domains increased in both number and size during hematopoiesis, with many more repressive domains in erythroid cells than HSPCs. CTCF and cohesinSA-1 marked the boundaries of these repressive chromatin domains in a cell-type specific manner.
Conclusion
These genome wide data, changes in sites of protein occupancy, chromatin architecture, and related gene expression, support the hypothesis that CTCF and cohesinSA-1 have multiple roles in the regulation of gene expression during erythropoiesis including transcriptional regulation at gene promoters and maintenance of chromatin architecture. These data from primary human erythroid cells provide a resource for studies of normal and perturbed erythropoiesis.
doi:10.1371/journal.pone.0155378
PMCID: PMC4878738  PMID: 27219007
15.  GINS motion reveals replication fork progression is remarkably uniform throughout the yeast genome 
Time-resolved ChIP-chip can be utilized to monitor the genome-wide dynamics of the GINS complex, yielding quantitative information on replication fork movement.Replication forks progress at remarkably uniform rates across the genome, regardless of location.GINS progression appears to be arrested, albeit with very low frequency, at sites of highly transcribed genes.Comparison of simulation with data leads to novel biological insights regarding the dynamics of replication fork progression
In mitotic division, cells duplicate their DNA in S phase to ensure that the proper genetic material is passed on to their progeny. This process of DNA replication is initiated from several hundred specific sites, termed origins of replication, spaced across the genome. It is essential for replication to begin only after G1 and finish before the initiation of anaphase (Blow and Dutta, 2005; Machida et al, 2005). To ensure proper timing, the beginning stages of DNA replication are tightly coupled to the cell cycle through the activity of cyclin-dependent kinases (Nguyen et al, 2001; Masumoto et al, 2002; Sclafani and Holzen, 2007), which promote the accumulation of the pre-RC at the origins and initiate replication. Replication fork movement occurs subsequent to the firing of origins on recruitment of the replicative helicase and the other fork-associated proteins as the cell enters S phase (Diffley, 2004). The replication machinery itself (polymerases, PCNA, etc.) trails behind the helicase, copying the newly unwound DNA in the wake of the replication fork.
One component of the pre-RC, the GINS complex, consists of a highly conserved set of paralogous proteins (Psf1, Psf2, Psf3 and Sld5 (Kanemaki et al, 2003; Kubota et al, 2003; Takayama et al, 2003)). Previous work suggests that the GINS complex is an integral component of the replication fork and that its interaction with the genome correlates directly to the movement of the fork (reviewed in Labib and Gambus, 2007). Here, we used the GINS complex as a surrogate to measure features of the dynamics of replication—that is, to determine which origins in the genome are active, the timing of their firing and the rates of replication fork progression.
The timing of origin firing and the rates of fork progression have also been investigated by monitoring nascent DNA synthesis (Raghuraman et al, 2001; Yabuki et al, 2002). Origin firing was observed to occur as early as 14 min into the cell cycle and as late as 44 min (Raghuraman et al, 2001). A wide range of nucleotide incorporation rates (0.5–11 kb/min) were observed, with a mean of 2.9 kb/min (Raghuraman et al, 2001), whereas a second study reported a comparable mean rate of DNA duplication of 2.8±1.0 kb/min (Yabuki et al, 2002). In addition to these observations, replication has been inferred to progress asymmetrically from certain origins (Raghuraman et al, 2001). These data have been interpreted to mean that the dynamics of replication fork progression are strongly affected by local chromatin structure or architecture, and perhaps by interaction with the machineries controlling transcription, repair and epigenetic maintenance (Deshpande and Newlon, 1996; Rothstein et al, 2000; Raghuraman et al, 2001; Ivessa et al, 2003). In this study, we adopted a complementary ChIP-chip approach for assaying replication dynamics, in which we followed GINS complexes as they traverse the genome during the cell cycle (Figure 1). These data reveal that GINS binds to active replication origins and spreads bi-directionally and symmetrically as S phase progresses (Figure 3). The majority of origins appear to fire in the first ∼15 min of S phase. A small fraction (∼10%) of the origins to which GINS binds show no evidence of spreading (category 3 origins), although it remains possible that these peaks represent passively fired origins (Shirahige et al, 1998). Once an active origin fires, the GINS complex moves at an almost constant rate of 1.6±0.3 kb/min. Its movement through the inter-origin regions is consistent with that of a protein complex associated with a smoothly moving replication fork. This progression rate is considerably lower and more tightly distributed than those inferred from previous genome-wide measurements assayed through nascent DNA production (Raghuraman et al, 2001; Yabuki et al, 2002). Our study leads us to a different view of replication fork dynamics wherein fork progression is highly uniform in rate and little affected by genomic location.
In this work, we also observe a large number of low-intensity persistent features at sites of high transcriptional activity (e.g. tRNA genes). We were able to accurately simulate these features by assuming they are the result of low probability arrest of replication forks at these sites, rather than fork pausing (Deshpande and Newlon, 1996). The extremely low frequency of these events in wild-type cells suggests they are due to low probability stochastic occurrences during the replication process. It is hoped that future studies will resolve whether these persistent features indeed represent rare instances of fork arrest, or are the result of some alternative process. These may include, for example, the deposition of GINS complexes (or perhaps more specifically Psf2) once a pause has been resolved.
In this work, we have made extensive use of modeling to test a number of different hypotheses and assumptions. In particular, iterative modeling allowed us to infer that GINS progression is uniform and smooth throughout the genome. We have also demonstrated the potential of simulations for estimating firing efficiencies. In the future, extending such firing efficiency simulations to the whole genome should allow us to make correlations with chromosomal features such as nucleosome occupancy. Such correlations may help in determining factors that govern the probability of replication initiation throughout the genome.
Previous studies have led to a picture wherein the replication of DNA progresses at variable rates over different parts of the budding yeast genome. These prior experiments, focused on production of nascent DNA, have been interpreted to imply that the dynamics of replication fork progression are strongly affected by local chromatin structure/architecture, and by interaction with machineries controlling transcription, repair and epigenetic maintenance. Here, we adopted a complementary approach for assaying replication dynamics using whole genome time-resolved chromatin immunoprecipitation combined with microarray analysis of the GINS complex, an integral member of the replication fork. Surprisingly, our data show that this complex progresses at highly uniform rates regardless of genomic location, revealing that replication fork dynamics in yeast is simpler and more uniform than previously envisaged. In addition, we show how the synergistic use of experiment and modeling leads to novel biological insights. In particular, a parsimonious model allowed us to accurately simulate fork movement throughout the genome and also revealed a subtle phenomenon, which we interpret as arising from low-frequency fork arrest.
doi:10.1038/msb.2010.8
PMCID: PMC2858444  PMID: 20212525
cell cycle; ChIP-chip; DNA replication; replication fork; simulation
16.  Human genome meeting 2016 
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Human Genomics  2016;10(Suppl 1):12.
Table of contents
O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder
A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson
O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents
R. Polimanti, J. Gelernter
O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort
X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group
O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus
A. Kapoor, D. Lee, A. Chakravarti
O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells
C. Maercker, F. Graf, M. Boutros
O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies
G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis
O7 Role of microRNA in LCL to IPSC reprogramming
S. Kumar, J. Curran, J. Blangero
O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease
S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti
O9 Metabolomic profiling for the diagnosis of neurometabolic disorders
T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea
O10 A novel causal methylation network approach to Alzheimer’s disease
Z. Hu, P. Wang, Y. Zhu, J. Zhao, M. Xiong, David A Bennett
O11 A microRNA signature identifies subtypes of triple-negative breast cancer and reveals MIR-342-3P as regulator of a lactate metabolic pathway
A. Hidalgo-Miranda, S. Romero-Cordoba, S. Rodriguez-Cuevas, R. Rebollar-Vega, E. Tagliabue, M. Iorio, E. D’Ippolito, S. Baroni
O12 Transcriptome analysis identifies genes, enhancer RNAs and repetitive elements that are recurrently deregulated across multiple cancer types
B. Kaczkowski, Y. Tanaka, H. Kawaji, A. Sandelin, R. Andersson, M. Itoh, T. Lassmann, the FANTOM5 consortium, Y. Hayashizaki, P. Carninci, A. R. R. Forrest
O13 Elevated mutation and widespread loss of constraint at regulatory and architectural binding sites across 11 tumour types
C. A. Semple
O14 Exome sequencing provides evidence of pathogenicity for genes implicated in colorectal cancer
E. A. Rosenthal, B. Shirts, L. Amendola, C. Gallego, M. Horike-Pyne, A. Burt, P. Robertson, P. Beyers, C. Nefcy, D. Veenstra, F. Hisama, R. Bennett, M. Dorschner, D. Nickerson, J. Smith, K. Patterson, D. Crosslin, R. Nassir, N. Zubair, T. Harrison, U. Peters, G. Jarvik, NHLBI GO Exome Sequencing Project
O15 The tandem duplicator phenotype as a distinct genomic configuration in cancer
F. Menghi, K. Inaki, X. Woo, P. Kumar, K. Grzeda, A. Malhotra, H. Kim, D. Ucar, P. Shreckengast, K. Karuturi, J. Keck, J. Chuang, E. T. Liu
O16 Modeling genetic interactions associated with molecular subtypes of breast cancer
B. Ji, A. Tyler, G. Ananda, G. Carter
O17 Recurrent somatic mutation in the MYC associated factor X in brain tumors
H. Nikbakht, M. Montagne, M. Zeinieh, A. Harutyunyan, M. Mcconechy, N. Jabado, P. Lavigne, J. Majewski
O18 Predictive biomarkers to metastatic pancreatic cancer treatment
J. B. Goldstein, M. Overman, G. Varadhachary, R. Shroff, R. Wolff, M. Javle, A. Futreal, D. Fogelman
O19 DDIT4 gene expression as a prognostic marker in several malignant tumors
L. Bravo, W. Fajardo, H. Gomez, C. Castaneda, C. Rolfo, J. A. Pinto
O20 Spatial organization of the genome and genomic alterations in human cancers
K. C. Akdemir, L. Chin, A. Futreal, ICGC PCAWG Structural Alterations Group
O21 Landscape of targeted therapies in solid tumors
S. Patterson, C. Statz, S. Mockus
O22 Genomic analysis reveals novel drivers and progression pathways in skin basal cell carcinoma
S. N. Nikolaev, X. I. Bonilla, L. Parmentier, B. King, F. Bezrukov, G. Kaya, V. Zoete, V. Seplyarskiy, H. Sharpe, T. McKee, A. Letourneau, P. Ribaux, K. Popadin, N. Basset-Seguin, R. Ben Chaabene, F. Santoni, M. Andrianova, M. Guipponi, M. Garieri, C. Verdan, K. Grosdemange, O. Sumara, M. Eilers, I. Aifantis, O. Michielin, F. de Sauvage, S. Antonarakis
O23 Identification of differential biomarkers of hepatocellular carcinoma and cholangiocarcinoma via transcriptome microarray meta-analysis
S. Likhitrattanapisal
O24 Clinical validity and actionability of multigene tests for hereditary cancers in a large multi-center study
S. Lincoln, A. Kurian, A. Desmond, S. Yang, Y. Kobayashi, J. Ford, L. Ellisen
O25 Correlation with tumor ploidy status is essential for correct determination of genome-wide copy number changes by SNP array
T. L. Peters, K. R. Alvarez, E. F. Hollingsworth, D. H. Lopez-Terrada
O26 Nanochannel based next-generation mapping for interrogation of clinically relevant structural variation
A. Hastie, Z. Dzakula, A. W. Pang, E. T. Lam, T. Anantharaman, M. Saghbini, H. Cao, BioNano Genomics
O27 Mutation spectrum in a pulmonary arterial hypertension (PAH) cohort and identification of associated truncating mutations in TBX4
C. Gonzaga-Jauregui, L. Ma, A. King, E. Berman Rosenzweig, U. Krishnan, J. G. Reid, J. D. Overton, F. Dewey, W. K. Chung
O28 NORTH CAROLINA macular dystrophy (MCDR1): mutations found affecting PRDM13
K. Small, A. DeLuca, F. Cremers, R. A. Lewis, V. Puech, B. Bakall, R. Silva-Garcia, K. Rohrschneider, M. Leys, F. S. Shaya, E. Stone
O29 PhenoDB and genematcher, solving unsolved whole exome sequencing data
N. L. Sobreira, F. Schiettecatte, H. Ling, E. Pugh, D. Witmer, K. Hetrick, P. Zhang, K. Doheny, D. Valle, A. Hamosh
O30 Baylor-Johns Hopkins Center for Mendelian genomics: a four year review
S. N. Jhangiani, Z. Coban Akdemir, M. N. Bainbridge, W. Charng, W. Wiszniewski, T. Gambin, E. Karaca, Y. Bayram, M. K. Eldomery, J. Posey, H. Doddapaneni, J. Hu, V. R. Sutton, D. M. Muzny, E. A. Boerwinkle, D. Valle, J. R. Lupski, R. A. Gibbs
O31 Using read overlap assembly to accurately identify structural genetic differences in an ashkenazi jewish trio
S. Shekar, W. Salerno, A. English, A. Mangubat, J. Bruestle
O32 Legal interoperability: a sine qua non for international data sharing
A. Thorogood, B. M. Knoppers, Global Alliance for Genomics and Health - Regulatory and Ethics Working Group
O33 High throughput screening platform of competent sineups: that can enhance translation activities of therapeutic target
H. Takahashi, K. R. Nitta, A. Kozhuharova, A. M. Suzuki, H. Sharma, D. Cotella, C. Santoro, S. Zucchelli, S. Gustincich, P. Carninci
O34 The undiagnosed diseases network international (UDNI): clinical and laboratory research to meet patient needs
J. J. Mulvihill, G. Baynam, W. Gahl, S. C. Groft, K. Kosaki, P. Lasko, B. Melegh, D. Taruscio
O36 Performance of computational algorithms in pathogenicity predictions for activating variants in oncogenes versus loss of function mutations in tumor suppressor genes
R. Ghosh, S. Plon
O37 Identification and electronic health record incorporation of clinically actionable pharmacogenomic variants using prospective targeted sequencing
S. Scherer, X. Qin, R. Sanghvi, K. Walker, T. Chiang, D. Muzny, L. Wang, J. Black, E. Boerwinkle, R. Weinshilboum, R. Gibbs
O38 Melanoma reprogramming state correlates with response to CTLA-4 blockade in metastatic melanoma
T. Karpinets, T. Calderone, K. Wani, X. Yu, C. Creasy, C. Haymaker, M. Forget, V. Nanda, J. Roszik, J. Wargo, L. Haydu, X. Song, A. Lazar, J. Gershenwald, M. Davies, C. Bernatchez, J. Zhang, A. Futreal, S. Woodman
O39 Data-driven refinement of complex disease classification from integration of heterogeneous functional genomics data in GeneWeaver
E. J. Chesler, T. Reynolds, J. A. Bubier, C. Phillips, M. A. Langston, E. J. Baker
O40 A general statistic framework for genome-based disease risk prediction
M. Xiong, L. Ma, N. Lin, C. Amos
O41 Integrative large-scale causal network analysis of imaging and genomic data and its application in schizophrenia studies
N. Lin, P. Wang, Y. Zhu, J. Zhao, V. Calhoun, M. Xiong
O42 Big data and NGS data analysis: the cloud to the rescue
O. Dobretsberger, M. Egger, F. Leimgruber
O43 Cpipe: a convergent clinical exome pipeline specialised for targeted sequencing
S. Sadedin, A. Oshlack, Melbourne Genomics Health Alliance
O44 A Bayesian classification of biomedical images using feature extraction from deep neural networks implemented on lung cancer data
V. A. A. Antonio, N. Ono, Clark Kendrick C. Go
O45 MAV-SEQ: an interactive platform for the Management, Analysis, and Visualization of sequence data
Z. Ahmed, M. Bolisetty, S. Zeeshan, E. Anguiano, D. Ucar
O47 Allele specific enhancer in EPAS1 intronic regions may contribute to high altitude adaptation of Tibetans
C. Zeng, J. Shao
O48 Nanochannel based next-generation mapping for structural variation detection and comparison in trios and populations
H. Cao, A. Hastie, A. W. Pang, E. T. Lam, T. Liang, K. Pham, M. Saghbini, Z. Dzakula
O49 Archaic introgression in indigenous populations of Malaysia revealed by whole genome sequencing
Y. Chee-Wei, L. Dongsheng, W. Lai-Ping, D. Lian, R. O. Twee Hee, Y. Yunus, F. Aghakhanian, S. S. Mokhtar, C. V. Lok-Yung, J. Bhak, M. Phipps, X. Shuhua, T. Yik-Ying, V. Kumar, H. Boon-Peng
O50 Breast and ovarian cancer prevention: is it time for population-based mutation screening of high risk genes?
I. Campbell, M.-A. Young, P. James, Lifepool
O53 Comprehensive coverage from low DNA input using novel NGS library preparation methods for WGS and WGBS
C. Schumacher, S. Sandhu, T. Harkins, V. Makarov
O54 Methods for large scale construction of robust PCR-free libraries for sequencing on Illumina HiSeqX platform
H. DoddapaneniR. Glenn, Z. Momin, B. Dilrukshi, H. Chao, Q. Meng, B. Gudenkauf, R. Kshitij, J. Jayaseelan, C. Nessner, S. Lee, K. Blankenberg, L. Lewis, J. Hu, Y. Han, H. Dinh, S. Jireh, K. Walker, E. Boerwinkle, D. Muzny, R. Gibbs
O55 Rapid capture methods for clinical sequencing
J. Hu, K. Walker, C. Buhay, X. Liu, Q. Wang, R. Sanghvi, H. Doddapaneni, Y. Ding, N. Veeraraghavan, Y. Yang, E. Boerwinkle, A. L. Beaudet, C. M. Eng, D. M. Muzny, R. A. Gibbs
O56 A diploid personal human genome model for better genomes from diverse sequence data
K. C. C. Worley, Y. Liu, D. S. T. Hughes, S. C. Murali, R. A. Harris, A. C. English, X. Qin, O. A. Hampton, P. Larsen, C. Beck, Y. Han, M. Wang, H. Doddapaneni, C. L. Kovar, W. J. Salerno, A. Yoder, S. Richards, J. Rogers, J. R. Lupski, D. M. Muzny, R. A. Gibbs
O57 Development of PacBio long range capture for detection of pathogenic structural variants
Q. Meng, M. Bainbridge, M. Wang, H. Doddapaneni, Y. Han, D. Muzny, R. Gibbs
O58 Rhesus macaques exhibit more non-synonymous variation but greater impact of purifying selection than humans
R. A. Harris, M. Raveenedran, C. Xue, M. Dahdouli, L. Cox, G. Fan, B. Ferguson, J. Hovarth, Z. Johnson, S. Kanthaswamy, M. Kubisch, M. Platt, D. Smith, E. Vallender, R. Wiseman, X. Liu, J. Below, D. Muzny, R. Gibbs, F. Yu, J. Rogers
O59 Assessing RNA structure disruption induced by single-nucleotide variation
J. Lin, Y. Zhang, Z. Ouyang
P1 A meta-analysis of genome-wide association studies of mitochondrial dna copy number
A. Moore, Z. Wang, J. Hofmann, M. Purdue, R. Stolzenberg-Solomon, S. Weinstein, D. Albanes, C.-S. Liu, W.-L. Cheng, T.-T. Lin, Q. Lan, N. Rothman, S. Berndt
P2 Missense polymorphic genetic combinations underlying down syndrome susceptibility
E. S. Chen
P4 The evaluation of alteration of ELAM-1 expression in the endometriosis patients
H. Bahrami, A. Khoshzaban, S. Heidari Keshal
P5 Obesity and the incidence of apolipoprotein E polymorphisms in an assorted population from Saudi Arabia population
K. K. R. Alharbi
P6 Genome-associated personalized antithrombotical therapy for patients with high risk of thrombosis and bleeding
M. Zhalbinova, A. Akilzhanova, S. Rakhimova, M. Bekbosynova, S. Myrzakhmetova
P7 Frequency of Xmn1 polymorphism among sickle cell carrier cases in UAE population
M. Matar
P8 Differentiating inflammatory bowel diseases by using genomic data: dimension of the problem and network organization
N. Mili, R. Molinari, Y. Ma, S. Guerrier
P9 Vulnerability of genetic variants to the risk of autism among Saudi children
N. Elhawary, M. Tayeb, N. Bogari, N. Qotb
P10 Chromatin profiles from ex vivo purified dopaminergic neurons establish a promising model to support studies of neurological function and dysfunction
S. A. McClymont, P. W. Hook, L. A. Goff, A. McCallion
P11 Utilization of a sensitized chemical mutagenesis screen to identify genetic modifiers of retinal dysplasia in homozygous Nr2e3rd7 mice
Y. Kong, J. R. Charette, W. L. Hicks, J. K. Naggert, L. Zhao, P. M. Nishina
P12 Ion torrent next generation sequencing of recessive polycystic kidney disease in Saudi patients
B. M. Edrees, M. Athar, F. A. Al-Allaf, M. M. Taher, W. Khan, A. Bouazzaoui, N. A. Harbi, R. Safar, H. Al-Edressi, A. Anazi, N. Altayeb, M. A. Ahmed, K. Alansary, Z. Abduljaleel
P13 Digital expression profiling of Purkinje neurons and dendrites in different subcellular compartments
A. Kratz, P. Beguin, S. Poulain, M. Kaneko, C. Takahiko, A. Matsunaga, S. Kato, A. M. Suzuki, N. Bertin, T. Lassmann, R. Vigot, P. Carninci, C. Plessy, T. Launey
P14 The evolution of imperfection and imperfection of evolution: the functional and functionless fractions of the human genome
D. Graur
P16 Species-independent identification of known and novel recurrent genomic entities in multiple cancer patients
J. Friis-Nielsen, J. M. Izarzugaza, S. Brunak
P18 Discovery of active gene modules which are densely conserved across multiple cancer types reveal their prognostic power and mutually exclusive mutation patterns
B. S. Soibam
P19 Whole exome sequencing of dysplastic leukoplakia tissue indicates sequential accumulation of somatic mutations from oral precancer to cancer
D. Das, N. Biswas, S. Das, S. Sarkar, A. Maitra, C. Panda, P. Majumder
P21 Epigenetic mechanisms of carcinogensis by hereditary breast cancer genes
J. J. Gruber, N. Jaeger, M. Snyder
P22 RNA direct: a novel RNA enrichment strategy applied to transcripts associated with solid tumors
K. Patel, S. Bowman, T. Davis, D. Kraushaar, A. Emerman, S. Russello, N. Henig, C. Hendrickson
P23 RNA sequencing identifies gene mutations for neuroblastoma
K. Zhang
P24 Participation of SFRP1 in the modulation of TMPRSS2-ERG fusion gene in prostate cancer cell lines
M. Rodriguez-Dorantes, C. D. Cruz-Hernandez, C. D. P. Garcia-Tobilla, S. Solorzano-Rosales
P25 Targeted Methylation Sequencing of Prostate Cancer
N. Jäger, J. Chen, R. Haile, M. Hitchins, J. D. Brooks, M. Snyder
P26 Mutant TPMT alleles in children with acute lymphoblastic leukemia from México City and Yucatán, Mexico
S. Jiménez-Morales, M. Ramírez, J. Nuñez, V. Bekker, Y. Leal, E. Jiménez, A. Medina, A. Hidalgo, J. Mejía
P28 Genetic modifiers of Alström syndrome
J. Naggert, G. B. Collin, K. DeMauro, R. Hanusek, P. M. Nishina
P31 Association of genomic variants with the occurrence of angiotensin-converting-enzyme inhibitor (ACEI)-induced coughing among Filipinos
E. M. Cutiongco De La Paz, R. Sy, J. Nevado, P. Reganit, L. Santos, J. D. Magno, F. E. Punzalan , D. Ona , E. Llanes, R. L. Santos-Cortes , R. Tiongco, J. Aherrera, L. Abrahan, P. Pagauitan-Alan; Philippine Cardiogenomics Study Group
P32 The use of “humanized” mouse models to validate disease association of a de novo GARS variant and to test a novel gene therapy strategy for Charcot-Marie-Tooth disease type 2D
K. H. Morelli, J. S. Domire, N. Pyne, S. Harper, R. Burgess
P34 Molecular regulation of chondrogenic human induced pluripotent stem cells
M. A. Gari, A. Dallol, H. Alsehli, A. Gari, M. Gari, A. Abuzenadah
P35 Molecular profiling of hematologic malignancies: implementation of a variant assessment algorithm for next generation sequencing data analysis and clinical reporting
M. Thomas, M. Sukhai, S. Garg, M. Misyura, T. Zhang, A. Schuh, T. Stockley, S. Kamel-Reid
P36 Accessing genomic evidence for clinical variants at NCBI
S. Sherry, C. Xiao, D. Slotta, K. Rodarmer, M. Feolo, M. Kimelman, G. Godynskiy, C. O’Sullivan, E. Yaschenko
P37 NGS-SWIFT: a cloud-based variant analysis framework using control-accessed sequencing data from DBGAP/SRA
C. Xiao, E. Yaschenko, S. Sherry
P38 Computational assessment of drug induced hepatotoxicity through gene expression profiling
C. Rangel-Escareño, H. Rueda-Zarate
P40 Flowr: robust and efficient pipelines using a simple language-agnostic approach;ultraseq; fast modular pipeline for somatic variation calling using flowr
S. Seth, S. Amin, X. Song, X. Mao, H. Sun, R. G. Verhaak, A. Futreal, J. Zhang
P41 Applying “Big data” technologies to the rapid analysis of heterogenous large cohort data
S. J. Whiite, T. Chiang, A. English, J. Farek, Z. Kahn, W. Salerno, N. Veeraraghavan, E. Boerwinkle, R. Gibbs
P42 FANTOM5 web resource for the large-scale genome-wide transcription start site activity profiles of wide-range of mammalian cells
T. Kasukawa, M. Lizio, J. Harshbarger, S. Hisashi, J. Severin, A. Imad, S. Sahin, T. C. Freeman, K. Baillie, A. Sandelin, P. Carninci, A. R. R. Forrest, H. Kawaji, The FANTOM Consortium
P43 Rapid and scalable typing of structural variants for disease cohorts
W. Salerno, A. English, S. N. Shekar, A. Mangubat, J. Bruestle, E. Boerwinkle, R. A. Gibbs
P44 Polymorphism of glutathione S-transferases and sulphotransferases genes in an Arab population
A. H. Salem, M. Ali, A. Ibrahim, M. Ibrahim
P46 Genetic divergence of CYP3A5*3 pharmacogenomic marker for native and admixed Mexican populations
J. C. Fernandez-Lopez, V. Bonifaz-Peña, C. Rangel-Escareño, A. Hidalgo-Miranda, A. V. Contreras
P47 Whole exome sequence meta-analysis of 13 white blood cell, red blood cell, and platelet traits
L. Polfus, CHARGE and NHLBI Exome Sequence Project Working Groups
P48 Association of adipoq gene with type 2 diabetes and related phenotypes in african american men and women: The jackson heart study
S. Davis, R. Xu, S. Gebeab, P Riestra, A Gaye, R. Khan, J. Wilson, A. Bidulescu
P49 Common variants in casr gene are associated with serum calcium levels in koreans
S. H. Jung, N. Vinayagamoorthy, S. H. Yim, Y. J. Chung
P50 Inference of multiple-wave population admixture by modeling decay of linkage disequilibrium with multiple exponential functions
Y. Zhou, S. Xu
P51 A Bayesian framework for generalized linear mixed models in genome-wide association studies
X. Wang, V. Philip, G. Carter
P52 Targeted sequencing approach for the identification of the genetic causes of hereditary hearing impairment
A. A. Abuzenadah, M. Gari, R. Turki, A. Dallol
P53 Identification of enhancer sequences by ATAC-seq open chromatin profiling
A. Uyar, A. Kaygun, S. Zaman, E. Marquez, J. George, D. Ucar
P54 Direct enrichment for the rapid preparation of targeted NGS libraries
C. L. Hendrickson, A. Emerman, D. Kraushaar, S. Bowman, N. Henig, T. Davis, S. Russello, K. Patel
P56 Performance of the Agilent D5000 and High Sensitivity D5000 ScreenTape assays for the Agilent 4200 Tapestation System
R. Nitsche, L. Prieto-Lafuente
P57 ClinVar: a multi-source archive for variant interpretation
M. Landrum, J. Lee, W. Rubinstein, D. Maglott
P59 Association of functional variants and protein physical interactions of human MUTY homolog linked with familial adenomatous polyposis and colorectal cancer syndrome
Z. Abduljaleel, W. Khan, F. A. Al-Allaf, M. Athar , M. M. Taher, N. Shahzad
P60 Modification of the microbiom constitution in the gut using chicken IgY antibodies resulted in a reduction of acute graft-versus-host disease after experimental bone marrow transplantation
A. Bouazzaoui, E. Huber, A. Dan, F. A. Al-Allaf, W. Herr, G. Sprotte, J. Köstler, A. Hiergeist, A. Gessner, R. Andreesen, E. Holler
P61 Compound heterozygous mutation in the LDLR gene in Saudi patients suffering severe hypercholesterolemia
F. Al-Allaf, A. Alashwal, Z. Abduljaleel, M. Taher, A. Bouazzaoui, H. Abalkhail, A. Al-Allaf, R. Bamardadh, M. Athar
doi:10.1186/s40246-016-0063-5
PMCID: PMC4896275  PMID: 27294413
17.  Chromatin states modify network motifs contributing to cell-specific functions 
Scientific Reports  2015;5:11938.
Epigenetic modification can affect many important biological processes, such as cell proliferation and apoptosis. It can alter chromatin conformation and contribute to gene regulation. To investigate how chromatin states associated with network motifs, we assembled chromatin state-modified regulatory networks by combining 269 ChIP-seq data and chromatin states in four cell types. We found that many chromatin states were significantly associated with network motifs, especially for feedforward loops (FFLs). These distinct chromatin state compositions contribute to different expression levels and translational control of targets in FFLs. Strikingly, the chromatin state-modified FFLs were highly cell-specific and, to a large extent, determined cell-selective functions, such as the embryonic stem cell-specific bivalent modification-related FFL with an important role in poising developmentally important genes for expression. Besides, comparisons of chromatin state-modified FFLs between cancerous/stem and primary cell lines revealed specific type of chromatin state alterations that may act together with motif structural changes cooperatively contribute to cell-to-cell functional differences. Combination of these alterations could be helpful in prioritizing candidate genes. Together, this work highlights that a dynamic epigenetic dimension can help network motifs to control cell-specific functions.
doi:10.1038/srep11938
PMCID: PMC4500950  PMID: 26169043
18.  Transcriptional, epigenetic and retroviral signatures identify regulatory regions involved in hematopoietic lineage commitment 
Scientific Reports  2016;6:24724.
Genome-wide approaches allow investigating the molecular circuitry wiring the genetic and epigenetic programs of human somatic stem cells. Hematopoietic stem/progenitor cells (HSPC) give rise to the different blood cell types; however, the molecular basis of human hematopoietic lineage commitment is poorly characterized. Here, we define the transcriptional and epigenetic profile of human HSPC and early myeloid and erythroid progenitors by a combination of Cap Analysis of Gene Expression (CAGE), ChIP-seq and Moloney leukemia virus (MLV) integration site mapping. Most promoters and transcripts were shared by HSPC and committed progenitors, while enhancers and super-enhancers consistently changed upon differentiation, indicating that lineage commitment is essentially regulated by enhancer elements. A significant fraction of CAGE promoters differentially expressed upon commitment were novel, harbored a chromatin enhancer signature, and may identify promoters and transcribed enhancers driving cell commitment. MLV-targeted genomic regions co-mapped with cell-specific active enhancers and super-enhancers. Expression analyses, together with an enhancer functional assay, indicate that MLV integration can be used to identify bona fide developmentally regulated enhancers. Overall, this study provides an overview of transcriptional and epigenetic changes associated to HSPC lineage commitment, and a novel signature for regulatory elements involved in cell identity.
doi:10.1038/srep24724
PMCID: PMC4837375  PMID: 27095295
19.  CTCF-Mediated and Pax6-Associated Gene Expression in Corneal Epithelial Cell-Specific Differentiation 
PLoS ONE  2016;11(9):e0162071.
Background
The purpose of the study is to elicit the epigenetic mechanism involving CCCTC binding factor (CTCF)-mediated chromatin remodeling that regulates PAX6 gene interaction with differentiation-associated genes to control corneal epithelial differentiation.
Methods
Cell cycle progression and specific keratin expressions were measured to monitor changes of differentiation-induced primary human limbal stem/progenitor (HLS/P), human corneal epithelial (HCE) and human telomerase-immortalized corneal epithelial (HTCE) cells. PAX6-interactive and differentiation-associated genes in chromatin remodeling mediated by the epigenetic factor CTCF were detected by circular chromosome conformation capture (4C) and ChIP (Chromatin immunoprecipitation)-on-chip approaches, and verified by FISH (Fluorescent in situ hybridization). Furthermore, CTCF activities were altered by CTCF-shRNA to study the effect of CTCF on mediating interaction of Pax6 and differentiation-associated genes in corneal epithelial cell fate.
Results
Our results demonstrated that differentiation-induced human corneal epithelial cells expressed typical corneal epithelial characteristics including morphological changes, increased keratin12 expression and G0/G1 accumulations. Expressions of CTCF and PAX6 were suppressed and elevated following the process of differentiation, respectively. During corneal epithelial cell differentiation, differentiation-induced RCN1 and ADAM17 were found interacting with PAX6 in the process of CTCF-mediated chromatin remodeling detected by 4C and verified by ChIP-on-chip and FISH. Diminished CTCF mRNA with CTCF-shRNA in HTCE cells weakened the interaction of PAX6 gene in controlling RCN1/ADAM17 and enhanced early onset of the genes in cell differentiation.
Conclusion
Our results explain how epigenetic factor CTCF-mediated chromatin remodeling regulates interactions between eye-specific PAX6 and those genes that are induced/associated with cell differentiation to modulate corneal epithelial cell-specific differentiation.
doi:10.1371/journal.pone.0162071
PMCID: PMC5008733  PMID: 27583466
20.  Alcohol induced epigenetic alterations to developmentally crucial genes regulating neural stemness and differentiation 
Background
From studies using a diverse range of model organisms, we now acknowledge that epigenetic changes to chromatin structure provide a plausible link between environmental teratogens and alterations in gene expression leading to disease. Observations from a number of independent laboratories indicate ethanol has the capacity to act as a powerful epigenetic disruptor and potentially derail the coordinated processes of cellular differentiation. In this study, we sought to examine whether primary neurospheres cultured under conditions maintaining stemness were susceptible to alcohol-induced alterations of the histone code. We focused our studies on trimethylated histone 3 lysine 4 and trimethylated histone 3 lysine 27, as these are two of the most prominent post-translational histone modifications regulating stem cell maintenance and neural differentiation.
Methods
Primary neurosphere cultures were maintained under conditions promoting the stem cell state and treated with ethanol for five days. Control and ethanol treated cellular extracts were examined using a combination of quantitative RT-PCR and chromatin immunoprecipitation techniques.
Results
We find that the regulatory regions of genes controlling both neural precursor cell identity and processes of differentiation exhibited significant declines in the enrichment of the chromatin marks examined. Despite these widespread changes in chromatin structure, only a small subset of genes including Dlx2, Fabp7, Nestin, Olig2, and Pax6 displayed ethanol induced alterations in transcription. Unexpectedly, the majority of chromatin modifying enzymes examined including members of the Polycomb Repressive Complex displayed minimal changes in expression and localization. Only transcripts encoding Dnmt1, Uhrf1, Ehmt1, Ash2l, Wdr5, and Kdm1b exhibited significant differences.
Conclusions
Our results indicate primary neurospheres maintained as stem cells in vitro are susceptible to alcohol-induced perturbation of the histone code and errors in the epigenetic program. These observations indicate that alterations to chromatin structure may represent a crucial component of alcohol teratogenesis and progress towards a better understanding of the developmental origins of FASDs.
doi:10.1111/acer.12080
PMCID: PMC3688681  PMID: 23488822
Epigenetic Programming; Bivalent Genes; Chromatin; Fetal Alcohol Syndrome; Neural Stem Cells
21.  Short-term memory in gene induction reveals the regulatory principle behind stochastic IL-4 expression 
Combining experiments on primary T cells and mathematical modeling, we characterized the stochastic expression of the interleukin-4 cytokine gene in its physiologic context, showing that a two-step model of transcriptional regulation acting on chromatin rearrangement and RNA polymerase recruitment accounts for the level, kinetics, and population variability of expression.A rate-limiting step upstream of transcription initiation, but occurring at the level of an individual allele, controls whether the interleukin-4 gene is expressed during antigenic stimulation, suggesting that the observed stochasticity of expression is linked to the dynamics of chromatin rearrangement.The computational analysis predicts that the probability to re-express an interleukin-4 gene that has been expressed once is transiently increased. In support, we experimentally demonstrate a short-term memory for interleukin-4 expression at the predicted time scale of several days.The model provides a unifying framework that accounts for both graded and binary modes of gene regulation. Graded changes in expression level can be achieved by controlling transcription initiation, whereas binary regulation acts at the level of chromatin rearrangement and is targeted during the differentiation of T cells that specialize in interleukin-4 production.
Cell populations are typically heterogeneous with respect to protein expression even when clonally derived from a single progenitor. In bacteria and yeast, such heterogeneity has been shown to be due to intrinsically stochastic dynamics of gene expression (Raj and van Oudenaarden, 2008). Thus, cross-population heterogeneity may be an unavoidable by-product of random fluctuations in molecular interactions (Raser and O'Shea, 2004; Pedraza and van Oudenaarden, 2005). The phenotypic variability deriving from it may also be beneficial for cell function, differentiation, or adaptation to changing environments (Chang et al, 2008; Feinerman et al, 2008; Losick and Desplan, 2008). However, little is known about how gene-expression variability is caused in mammalian cells.
Two principal modes of gene regulation have been identified: graded and binary. In the graded mode, transcriptional regulators can tune the level of a gene product in a continuous manner (Hazzalin and Mahadevan, 2002). In the binary mode, the gene is expressed at an invariant level, whereas its probability of being expressed in a given cell is regulated, so that the gene has discrete ‘on' and ‘off' states (Walters et al, 1995; Hume, 2000; Biggar and Crabtree, 2001). In humans and mice, cytokine genes are expressed in a binary manner (Bix and Locksley, 1998; Riviere et al, 1998; Hu-Li et al, 2001; Apostolou and Thanos, 2008). A particularly well-studied case is the interleukin-4 (il4) gene that is critical for antibody-based immune responses. This gene is expressed by antigen-stimulated T cells initially with low probability, so that in most IL-4-positive cells only one allele is active (Bix and Locksley, 1998; Riviere et al, 1998). The expressed allele is not imprinted but chosen stochastically during each cell stimulation (Hu-Li et al, 2001).
Here, we have studied the dynamics of IL-4 expression quantitatively. Primary murine CD4+ T cells have been differentiated uniformly into type-2 T-helper (Th2) cells that express the lineage-specifying transcription factor (TF) Gata-3 and are competent to activate the il4 gene upon challenge with antigen. Using T cells heterozygous for an il4 wild-type allele and an il4 allele with GFP knock-in after the promoter, the alleles are found to be expressed stochastically and in an uncorrelated manner (Figure 2A; Hu-Li et al, 2001). To account for the observed stochastic dynamics of IL-4 expression, we considered a basic model of gene transcription, mRNA translation, turnover, and protein secretion (Figure 2B). However, our experimental estimates of the intracellular life times of IL-4 mRNA and protein (∼1 h) and their absolute numbers (mRNA∼103, protein∼105) rule out random fluctuations in transcription, translation as well as mRNA and protein turnover as an explanation for the observed stochastic properties of IL-4 expression (Thattai and van Oudenaarden, 2001; Paulsson, 2004).
As il4 is known to be strongly regulated at the chromatin level (Ansel et al, 2006), we included in the model a reversible step of chromatin opening that is permissive for transcription (Figure 2C and D). Both chromatin opening and transcription initiation are driven by TFs that are transiently activated during the antigen stimulus, with NFAT1 playing a prominent role (Agarwal et al, 2000; Avni et al, 2002; Guo et al, 2004). The model accounts for the kinetics of NFAT1 TF activity (Figure 2E) (Loh et al, 1996). Using a best-fit procedure for estimating the kinetics of the chromatin transition and TF activity from experimental data, we found that the model accurately reproduces the distribution of IL-4 expression within the cell population over the entire time course of a stimulation (Figure 3A). At the same time, it accounts for the measured kinetics of IL-4 mRNA, intracellular and secreted protein (Figure 3B). Additional data show that the model can also explain IL-4 expression at different stages of Th2 differentiation and upon pharmacological inhibition of NFAT1 activity. In each case, the model predicts a slow and stochastic chromatin opening (Step 1 in Figure 2C) that is the limiting step for the activation of the gene.
The slowness of chromatin opening inferred by the model implies an extended lifetime of the open chromatin state (several days), which lasts longer than TF activity during antigenic stimulation (several hours). This indicates that acute IL-4 expression is terminated by the cessation of TF activity (Step 2 in Figure 2C), rather than by the closing of the chromatin (Step 1). In support of this prediction, we observed an elevated fraction of IL-4-producing cells after secondary stimulations administered within a few days of the primary stimulus. Consistent with the model, this elevation disappeared with a half-life of ∼3 days (Figure 4B). To test whether this ‘short-term memory' for activation of the il4 gene is indeed due to the IL-4 producers in the primary stimulation, we sorted stimulated Th2 cells into viable IL-4-producing and non-producing fractions using the cytokine secretion assay (Ouyang et al, 2000) and cultured them separately for different resting periods. The probability of IL-4 re-expression in the positive-sorted cells was consistently larger than in negative-sorted cells and decreased progressively over several days (Figure 4C). By contrast, the sorted IL-4 negative cells exhibited a constant induction probability indistinguishable from the unsorted population. This behavior was not due to differential cell proliferation in the sorted populations or different success of Th2 differentiation. Moreover, using heterozygous il4-wild-type/il4-gfp cells, and sorting for expression of the wild-type allele, we observed that expression of the il4-gfp allele was similar in IL-4-positive and negative sorted fractions. Taken together, these findings imply that stochastic, slow chromatin changes at individual il4 genes govern the binary expression pattern of this cytokine.
In conclusion, we propose an experimentally based model of inducible gene expression where strong stochasticity arises from slow (hours to days) chromatin opening and closing transitions, rather than being due to small numbers of mRNA or protein molecules or transcriptional bursting (Raj et al, 2006). This rate-limiting step upstream of transcription initiation (which may entail several interacting epigenetic processes) naturally gives rise to a binary expression pattern of the gene. By contrast, regulation at the level of transcription initiation can have a graded effect on the expression level. We provide evidence that both binary and graded regulation can occur for the il4 gene. Physiological regulation of il4 seems to be mainly binary, thus enabling a dose–response within a population while producing an unequivocal all-or-none signal at the single-cell level.
Although cell-to-cell variability has been recognized as an unavoidable consequence of stochasticity in gene expression, it may also serve a functional role for tuning physiological responses within a cell population. In the immune system, remarkably large variability in the expression of cytokine genes has been observed in homogeneous populations of lymphocytes, but the underlying molecular mechanisms are incompletely understood. Here, we study the interleukin-4 gene (il4) in T-helper lymphocytes, combining mathematical modeling with the experimental quantification of expression variability and critical parameters. We show that a stochastic rate-limiting step upstream of transcription initiation, but acting at the level of an individual allele, controls il4 expression. Only a fraction of cells reaches an active, transcription-competent state in the transient time window determined by antigen stimulation. We support this finding by experimental evidence of a previously unknown short-term memory that was predicted by the model to arise from the long lifetime of the active state. Our analysis shows how a stochastic mechanism acting at the chromatin level can be integrated with transcriptional regulation to quantitatively control cell-to-cell variability.
doi:10.1038/msb.2010.13
PMCID: PMC2872609  PMID: 20393579
cytokines; cytokine secretion assay; epigenetic regulation; gene expression; stochastic model
22.  Hematopoietic Transcriptional Mechanisms: From Locus-Specific to Genome-Wide Vantage Points 
Experimental hematology  2014;42(8):618-629.
Hematopoiesis is an exquisitely regulated process in which stem cells in the developing embryo and the adult generate progenitor cells that give rise to all blood lineages. Master regulatory transcription factors control hematopoiesis by integrating signals from the microenvironment and dynamically establishing and maintaining genetic networks. One of the most rudimentary aspects of cell type-specific transcription factor function, how they occupy a highly restricted cohort of cis-elements in chromatin remains poorly understood. Transformative technological advances involving the coupling of next-generation DNA sequencing technology with the chromatin immunoprecipitation assay (ChIP-seq) have enabled genome-wide mapping of factor occupancy patterns. However, formidable problems remain, notably ChIP-seq analysis yields hundreds to thousands of chromatin sites occupied by a given transcription factor, and only a fraction of the sites appear to be endowed with critical, non-redundant function. It has become en vogue to map transcription factor occupancy patterns genome-wide, while utilizing powerful statistical tools to establish correlations to inform biology and mechanisms. With the advent of revolutionary genome editing technologies, one can now reach beyond correlations to conduct definitive hypothesis testing. This review will focus on key discoveries that have emerged during the path from single loci to genome-wide analyses, specifically in the context of hematopoietic transcriptional mechanisms.
doi:10.1016/j.exphem.2014.05.004
PMCID: PMC4125519  PMID: 24816274
23.  Dissecting the retinoid-induced differentiation of F9 embryonal stem cells by integrative genomics 
We reveal how the RXRα−RARγ heterodimer upon activation by ATRA sets up a sequence of temporally controlled events that generate different subsets of primary and secondarily induced gene networks.We established RARγ and RXRα chromatin immunoprecipitation (ChIP) analyses coupled with massive parallel sequencing (ChIP-seq) together with the corresponding microarray transcriptomics at five time points during differentiation using pan-RAR and RAR isotype-selective ligands.Gene-regulatory decisions were inferred in silico from the dynamic changes of the transcriptomics patterns that correlated with the expression of RXRα−RARγ and other annotated transcription factors (TFs).Our analysis provides a temporal view of retinoic acid (RA) signalling during F9 cell differentiation, reveals RA receptor (RAR) heterodimer dynamics and promiscuity, and predicts decisions that diversify the RA signal into distinct gene-regulatory programs.
Nuclear receptors are ligand-inducible transcription factors, which upon induction by their cognate ligand induce complex temporally controlled physiological programs. Retinoic acid (RA) and its receptors are key regulators of multiple physiological processes, including embryogenesis, organogenesis, immune functions, reproduction and organ homeostasis. While insight into (some of) the physiological functions of the various RA receptor (RAR) and retinoid X receptor (RXR) subtypes has been obtained by exploiting mouse genetics (for a review, see Mark et al, 2006) we are far from an understanding of the molecular circuitries and gene networks that are at the basis of these physiological events.
RAs act by interacting with a complex receptor system that comprises heterodimers formed by one of the three RXR (RARα, β and γ) and RAR (RARα, β and γ) isotypes. While insight into the role of heterodimerization on response element preference and contribution of RAR and RXR to transcription activation of model genes has been obtained (for review, see Gronemeyer et al, 2004) very little is known about the role and dynamics of target gene interaction of the various RXR–RAR heterodimers at a global scale in the context of a biological program.
More fundamentally, in order to develop a systems biology of nuclear receptors we need to establish approaches that reveal how the initial event, the information embedded in the chemical structure of a small molecular weight compound, is propagated through binding to cognate receptor(s), recruitment of co-regulatory factors, epigenetic modulators and additional complexes/machineries to establish temporally controlled gene programs. In this respect, a recent study has revealed the impact of epigenetic modulator crosstalk in the setting up of subprograms for oestrogen receptor signalling (Ceschin et al, 2011).
In the present study, we have used mouse F9 EC cells, a homogeneous cell system which is known to differentiate upon RA exposure and require RARγ for this response (Taneja et al, 1996), in order to integrate at a genome-wide scale (i) the dynamics of RXRα and RARγ binding by chromatin immunoprecipitation (ChIP) analyses coupled with massive parallel sequencing (ChIP-seq), (ii) the correlated temporal regulation of gene programs by global transcriptomics analyses, including (iii) the response to isotype-selective RAR ligands (Box 1). Our study revealed an unexpected highly dynamic association of the RXRα–RARγ with target chromatin and an unexpected dynamics of the heterodimer composition itself, which is indicative of partner swapping.
Inspired by early works on the dynamics of Drosophila puffing patterns during ecdysone-induced metamorphosis (Ashburner et al, 1974) our working hypothesis was that diversification of gene programming is achieved by the sequential activation of separable gene cohorts that constitute the various facets of differentiation, such as altered proliferation, cell physiology, signalling and finally terminal apoptogenic differentiation. To identify these temporally activated subroutines within the overall program, we inferred gene-regulatory decisions in silico from dynamically altered global gene expression patterns that occurred due to the action of RXRα−RARγ and other annotated TFs (Ernst et al, 2007). This dynamic regulatory map was used to reconstruct RXRα–RARγ signalling networks by integration of functional co-citation. Altogether we present a genome-wide view of the temporal gene-regulatory events and the corresponding gene programs elicited by the RXRα–RARγ during F9 cell differentiation. Our study deciphers some of the mechanisms by which the chemical information encoded in RA is diversified to regulate different cohorts of genes.
Retinoic acid (RA) triggers physiological processes by activating heterodimeric transcription factors (TFs) comprising retinoic acid receptor (RARα, β, γ) and retinoid X receptor (RXRα, β, γ). How a single signal induces highly complex temporally controlled networks that ultimately orchestrate physiological processes is unclear. Using an RA-inducible differentiation model, we defined the temporal changes in the genome-wide binding patterns of RARγ and RXRα and correlated them with transcription regulation. Unexpectedly, both receptors displayed a highly dynamic binding, with different RXRα heterodimers targeting identical loci. Comparison of RARγ and RXRα co-binding at RA-regulated genes identified putative RXRα–RARγ target genes that were validated with subtype-selective agonists. Gene-regulatory decisions during differentiation were inferred from TF-target gene information and temporal gene expression. This analysis revealed six distinct co-expression paths of which RXRα–RARγ is associated with transcription activation, while Sox2 and Egr1 were predicted to regulate repression. Finally, RXRα–RARγ regulatory networks were reconstructed through integration of functional co-citations. Our analysis provides a dynamic view of RA signalling during cell differentiation, reveals RAR heterodimer dynamics and promiscuity, and predicts decisions that diversify the RA signal into distinct gene-regulatory programs.
This study provides a dynamic view of retinoic acid signalling during cell differentiation, reveals RAR/RXR heterodimer dynamics and promiscuity, and predicts decisions that diversify the RA signal into distinct gene-regulatory programs.
doi:10.1038/msb.2011.73
PMCID: PMC3261707  PMID: 21988834
ChIP-seq; retinoic acid-induced differentiation; RXR–RAR heterodimers; temporal control of gene networks; transcriptomics
24.  Dynamic interaction networks in a hierarchically organized tissue 
We have integrated gene expression profiling with database and literature mining, mechanistic modeling, and cell culture experiments to identify intercellular and intracellular networks regulating blood stem cell self-renewal.Blood stem cell fate in vitro is regulated non-autonomously by a coupled positive–negative intercellular feedback circuit, composed of megakaryocyte-derived stimulatory growth factors (VEGF, PDGF, EGF, and serotonin) versus monocyte-derived inhibitory factors (CCL3, CCL4, CXCL10, TGFB2, and TNFSF9).The antagonistic signals converge in a core intracellular network focused around PI3K, Raf, PLC, and Akt.Model simulations enable functional classification of the novel endogenous ligands and signaling molecules.
Intercellular (between cell) communication networks are required to maintain homeostasis and coordinate regenerative and developmental cues in multicellular organisms. Despite the recognized importance of intercellular networks in regulating adult stem and progenitor cell fate, the specific cell populations involved, and the underlying molecular mechanisms are largely undefined. Although a limited number of studies have applied novel bioinformatic approaches to unravel intercellular signaling in other cell systems (Frankenstein et al, 2006), a comprehensive analysis of intercellular communication in a stem cell-derived, hierarchical tissue network has yet to be reported.
As a model system to explore intercellular communication networks in a hierarchically organized tissue, we cultured human umbilical cord blood (UCB)-derived stem and progenitor cells in defined, minimal cytokine-supplemented liquid culture (Madlambayan et al, 2006). To systematically explore the molecular and cellular dynamics underlying primitive progenitor growth and differentiation, gene expression profiles of primitive (lineage negative; Lin−) and mature (lineage positive; Lin+) populations were generated during phases of stem cell expansion versus depletion. Parallel phenotypic and subproteomic experiments validated that mRNA expression correlated with complex measures of proteome activity (protein secretion and cell surface expression). Using a curated list of secreted ligand–receptor interactions and published expression profiles of purified mature blood populations, we implemented a novel algorithm to reconstruct the intercellular signaling networks established between stem cells and multi-lineage progeny in vitro. By correlating differential expression patterns with stem cell growth, we predict cell populations, pathways, and secreted ligands associated with stem cell self-renewal and differentiation (Figure 3A).
We then tested the correlative predictions in a series of cell culture experiments. UCB progenitor cell cultures were supplemented with saturating amounts of 18 putative regulatory ligands, or cocultured with purified mature blood lineages (megakaryocytes, monocytes, and erythrocytes), and analyzed for effects on total cell, progenitor, and primitive progenitor growth. At the primitive progenitor level, 3/5 novel predicted stimulatory ligands (EGF, PDGFB, and VEGF) displayed significant positive effects, 5/7 predicted inhibitory factors (CCL3, CCL4, CXCL10, TNFSF9, and TGFB2) displayed negative effects, whereas only 1/5 non-correlated ligand (CXCL7) displayed an effect. Also consistent with predictions from gene expression data, megakaryocytes and monocytes were found to stimulate and inhibit primitive progenitor growth, respectively, and these effects were attributable to differential secretome profiles of stimulatory versus inhibitory ligands.
Cellular responses to external stimuli, particularly in heterogeneous and dynamic cell populations, represent complex functions of multiple cell fate decisions acting both directly and indirectly on the target (stem cell) populations. Experimentally distinguishing the mode of action of cytokines is thus a difficult task. To address this we used our previously published interactive model of hematopoiesis (Kirouac et al, 2009) to classify experimentally identified regulatory ligands into one of four distinct functional categories based on their differential effects on cell population growth. TGFB2 was classified as a proliferation inhibitor, CCL4, CXCL10, SPARC, and TNFSF9 as self-renewal inhibitors, CCL3 a proliferation stimulator, and EGF, VEGF, and PDGFB as self-renewal stimulators.
Stem and progenitor cells exposed to combinatorial extracellular signals must propagate this information through intracellular molecular networks, and respond appropriately by modifying cell fate decisions. To explore how our experimentally identified positive and negative regulatory signals are integrated at the intracellular level, we constructed a blood stem cell self-renewal signaling network through extensive literature curation and protein–protein interaction (PPI) network mapping. We find that signal transduction pathways activated by the various stimulatory and inhibitory ligands converge on a limited set of molecular control nodes, forming a core subnetwork enriched for known regulators of self-renewal (Figure 6A). To experimentally test the intracellular signaling molecules computationally predicted as regulators of stem cell self-renewal, we obtained five small molecule antagonists against the kinases Phosphatidylinositol 3-kinase (PI3K), Raf, Akt, Phospholipase C (PLC), and MEK1. Liquid cultures were supplemented with the five molecules individually, and resultant cell population outputs compared against model simulations to deconvolute the functional effects on proliferation (and survival) versus self-renewal. This analysis classifies inhibition of PI3K and Raf activity as selectively targeting self-renewal, PLC as selectively targeting survival, and Akt as selectively targeting proliferation; MEK inhibition appears non-specific for these processes.
This represents the first systematic characterization of how cell fate decisions are regulated non-autonomously through lineage-specific interactions with differentiated progeny. The complex intercellular communication networks can be approximated as an antagonistic positive–negative feedback circuit, wherein progenitor expansion is modulated by a balance of megakaryocyte-derived stimulatory factors (EGF, PDGF, VEGF, and possibly serotonin) versus monocyte-derived inhibitory factors (CCL3, CCL4, CXCL10, TGFB2, and TNFSF9). This complex milieu of endogenous regulatory signals is integrated and processed within a core intracellular signaling network, resulting in modulation of cell-level kinetic parameters (proliferation, survival, and self-renewal). We reconstruct a stem cell associated intracellular network, and identify PI3K, Raf, Akt, and PLC as functionally distinct signal integration nodes, linking extracellular and intracellular signaling. These findings lay the groundwork for novel strategies to control blood stem cell self-renewal in vitro and in vivo.
Intercellular (between cell) communication networks maintain homeostasis and coordinate regenerative and developmental cues in multicellular organisms. Despite the importance of intercellular networks in stem cell biology, their rules, structure and molecular components are poorly understood. Herein, we describe the structure and dynamics of intercellular and intracellular networks in a stem cell derived, hierarchically organized tissue using experimental and theoretical analyses of cultured human umbilical cord blood progenitors. By integrating high-throughput molecular profiling, database and literature mining, mechanistic modeling, and cell culture experiments, we show that secreted factor-mediated intercellular communication networks regulate blood stem cell fate decisions. In particular, self-renewal is modulated by a coupled positive–negative intercellular feedback circuit composed of megakaryocyte-derived stimulatory growth factors (VEGF, PDGF, EGF, and serotonin) versus monocyte-derived inhibitory factors (CCL3, CCL4, CXCL10, TGFB2, and TNFSF9). We reconstruct a stem cell intracellular network, and identify PI3K, Raf, Akt, and PLC as functionally distinct signal integration nodes, linking extracellular, and intracellular signaling. This represents the first systematic characterization of how stem cell fate decisions are regulated non-autonomously through lineage-specific interactions with differentiated progeny.
doi:10.1038/msb.2010.71
PMCID: PMC2990637  PMID: 20924352
cellular networks; hematopoiesis; intercellular signaling; self-renewal; stem cells
25.  Biased, Non-equivalent Gene-Proximal and -Distal Binding Motifs of Orphan Nuclear Receptor TR4 in Primary Human Erythroid Cells 
PLoS Genetics  2014;10(5):e1004339.
We previously reported that TR2 and TR4 orphan nuclear receptors bind to direct repeat (DR) elements in the ε- and γ-globin promoters, and act as molecular anchors for the recruitment of epigenetic corepressors of the multifaceted DRED complex, thereby leading to ε- and γ-globin transcriptional repression during definitive erythropoiesis. Other than the ε- and γ-globin and the GATA1 genes, TR4-regulated target genes in human erythroid cells remain unknown. Here, we identified TR4 binding sites genome-wide using chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-seq) as human primary CD34+ hematopoietic progenitors differentiated progressively to late erythroid precursors. We also performed whole transcriptome analyses by RNA-seq to identify TR4 downstream targets after lentiviral-mediated TR4 shRNA knockdown in erythroid cells. Analyses from combined ChIP-seq and RNA-seq datasets indicate that DR1 motifs are more prevalent in the proximal promoters of TR4 direct target genes, which are involved in basic biological functions (e.g., mRNA processing, ribosomal assembly, RNA splicing and primary metabolic processes). In contrast, other non-DR1 repeat motifs (DR4, ER6 and IR1) are more prevalent at gene-distal TR4 binding sites. Of these, approximately 50% are also marked with epigenetic chromatin signatures (such as P300, H3K27ac, H3K4me1 and H3K27me3) associated with enhancer function. Thus, we hypothesize that TR4 regulates gene transcription via gene-proximal DR1 sites as TR4/TR2 heterodimers, while it can associate with novel nuclear receptor partners (such as RXR) to bind to distant non-DR1 consensus sites. In summary, this study reveals that the TR4 regulatory network is far more complex than previously appreciated and that TR4 regulates basic, essential biological processes during the terminal differentiation of human erythroid cells.
Author Summary
Sequential genome-wide binding studies investigated by deep sequencing (ChIP-seq) represent a powerful tool for investigating the temporal sequence of gene activation and repression events that take place as cells differentiate. Here, we report the binding of an “orphan” nuclear receptor (one for which no ligand has been identified) to its cognate genomic regulatory sites and perform the functional analysis to validate its downstream targets as precursor cells differentiate from very early human hematopoietic progenitors into red blood cells. We discovered that when this receptor is bound at gene proximal promoters, it recognizes a different DNA sequence than when it binds to more distant regulatory sites (enhancers and silencers). Since this receptor can either activate or repress specific target genes, the data suggest the intriguing possibility that the two different modes of DNA recognition may reflect association of the receptor with different partner molecules when regulating gene expression from proximal or distal sequences.
doi:10.1371/journal.pgen.1004339
PMCID: PMC4014424  PMID: 24811540

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