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McKeown MR, Corces MR, Eaton ML, Fiore C, Lee E, Lopez JT, Chen MW, Smith D, Chan SM, Koenig JL, Austgen K, Guenther MG, Orlando DA, Lovén J, Fritz CC, Majeti R. Superenhancer Analysis Defines Novel Epigenomic Subtypes of Non-APL AML, Including an RARα Dependency Targetable by SY-1425, a Potent and Selective RARα Agonist. Cancer Discov 2017; 7:1136-1153. [PMID: 28729405 PMCID: PMC5962349 DOI: 10.1158/2159-8290.cd-17-0399] [Citation(s) in RCA: 86] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2016] [Revised: 06/22/2017] [Accepted: 07/18/2017] [Indexed: 01/11/2023]
Abstract
We characterized the enhancer landscape of 66 patients with acute myeloid leukemia (AML), identifying 6 novel subgroups and their associated regulatory loci. These subgroups are defined by their superenhancer (SE) maps, orthogonal to somatic mutations, and are associated with distinct leukemic cell states. Examination of transcriptional drivers for these epigenomic subtypes uncovers a subset of patients with a particularly strong SE at the retinoic acid receptor alpha (RARA) gene locus. The presence of a RARA SE and concomitant high levels of RARA mRNA predisposes cell lines and ex vivo models to exquisite sensitivity to a selective agonist of RARα, SY-1425 (tamibarotene). Furthermore, only AML patient-derived xenograft (PDX) models with high RARA mRNA were found to respond to SY-1425. Mechanistically, we show that the response to SY-1425 in RARA-high AML cells is similar to that of acute promyelocytic leukemia treated with retinoids, characterized by the induction of known retinoic acid response genes, increased differentiation, and loss of proliferation.Significance: We use the SE landscape of primary human AML to elucidate transcriptional circuitry and identify novel cancer vulnerabilities. A subset of patients were found to have an SE at RARA, which is predictive for response to SY-1425, a potent and selective RARα agonist, in preclinical models, forming the rationale for its clinical investigation in biomarker-selected patients. Cancer Discov; 7(10); 1136-53. ©2017 AACR.See related commentary by Wang and Aifantis, p. 1065.This article is highlighted in the In This Issue feature, p. 1047.
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Affiliation(s)
| | - M Ryan Corces
- Program in Cancer Biology, Cancer Institute, Institute for Stem Cell Biology and Regenerative Medicine, and Ludwig Center Stanford University School of Medicine, Stanford, California
| | | | - Chris Fiore
- Syros Pharmaceuticals, Cambridge, Massachusetts
| | - Emily Lee
- Syros Pharmaceuticals, Cambridge, Massachusetts
| | | | | | | | - Steven M Chan
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Julie L Koenig
- Program in Cancer Biology, Cancer Institute, Institute for Stem Cell Biology and Regenerative Medicine, and Ludwig Center Stanford University School of Medicine, Stanford, California
| | | | | | | | - Jakob Lovén
- Syros Pharmaceuticals, Cambridge, Massachusetts
| | | | - Ravindra Majeti
- Program in Cancer Biology, Cancer Institute, Institute for Stem Cell Biology and Regenerative Medicine, and Ludwig Center Stanford University School of Medicine, Stanford, California.
- Department of Medicine, Division of Hematology, Stanford University School of Medicine, Stanford, California
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McKeown MR, Lee E, Fiore C, Eaton ML, Fritz CC, Olson E. Abstract 3085: SY-1425 (tamibarotene), a selective RARα agonist, shows synergistic anti-tumor activity with hypomethylating agents in a biomarker selected subset of AML. Cancer Res 2017. [DOI: 10.1158/1538-7445.am2017-3085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
In patients with acute myeloid leukemia (AML) (≥ 60 years) and myelodysplastic syndrome (MDS), the use of hypomethylating agents (HMAs) may extend survival, but cure rates are very low and new treatment approaches are needed. HMAs, such as azacitidine, work by inhibiting DNMT1, leading to depletion of DNA methylation in the tumor cells. Hypomethylation, in turn, leads to the re-expression of genes associated with differentiation and growth arrest. We have recently explored the potent and selective RARα agonist SY-1425 in a genomically defined subset of AML. SY-1425 binds to RARα and causes a transition from repression to strong activation of target genes, thus reprogramming the tumor cells toward terminal maturation in RARA-high AML models, supporting our recently initiated Phase 2 trial in a biomarker-selected subset of AML and MDS (NCT02807558). Based on potential mechanistic synergy, we evaluated SY-1425 in combination with HMAs and identified a synergistic anti-proliferative effect. In RARA-high AML cell lines, but not RARA-low, the combination of SY-1425 with either azacitidine or decitabine showed synergistic anti-proliferative effects on the cells, with combination indices less than 0.5 over a range of concentrations from 0.01 to 100nM of SY-1425 and 0.1 to 1µM of HMAs. SY-1425 and azacitidine were also co-administered to a disseminated patient-derived xenograft (PDX) mouse model of RARA-high AML. The combination demonstrated superior reduction of tumor burden vs either therapy alone, leading to deeper and more durable responses with less than 1% detectable tumor burden. A follow-up study in the RARA-high PDX model investigated different treatment schedules of SY-1425 and azacitidine over a period of 56 days, supporting a regimen that maximizes anti-tumor activity and tolerability. Mechanistic studies using RNA-seq and ChIP-seq in AML cell line models have revealed that while azacitidine had only moderate suppressive or activating effects over a broad set of genes, the addition of SY-1425 in RARA-high models resulted in strong and specific induction of genes bound by RARα. It is hypothesized that azacitidine acts to prime the tumor cells for reprogramming by SY-1425. The loss of methyl-cytosine residues following azacitidine treatment lowers the barrier to SY-1425 mediated gene induction. It was observed that the two agents work cooperatively to promote terminal differentiation and decrease proliferation of the AML tumor cells, with the potential for increased clinical benefit in a subset of AML defined by a RARA super-enhancer. Based on the largely non-overlapping clinical toxicity profiles of azacitidine and SY-1425, supported by the observed tolerability of the combination in preclinical models, these findings provide a strong rationale for a planned study of this combination in biomarker selected, newly diagnosed AML patients.
Citation Format: Michael R. McKeown, Emily Lee, Chris Fiore, Matthew L. Eaton, Christian C. Fritz, Eric Olson. SY-1425 (tamibarotene), a selective RARα agonist, shows synergistic anti-tumor activity with hypomethylating agents in a biomarker selected subset of AML [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3085. doi:10.1158/1538-7445.AM2017-3085
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Affiliation(s)
| | - Emily Lee
- Syros Pharmaceuticals, Cambridge, MA
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Austgen K, McKeown MR, Smith D, Lee E, Fiore C, Eaton ML, Fritz C, Lodie T, Olson E. Abstract 2644: SY-1425, a selective RARα agonist, induces high levels of CD38 expression in RARA-high AML tumors creating a susceptibility to anti-CD38 therapeutic antibody treatment. Cancer Res 2017. [DOI: 10.1158/1538-7445.am2017-2644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
CD38 is a cell surface protein expressed primarily on white blood cells and considered a marker of differentiation initiation. CD38 is involved in the immune system by engaging cross-talk with T and B cells as well as activation of NK cells. In multiple myeloma (MM), a subset of tumor cells have high CD38 expression (CD38hi), which has led to the development of effective anti-CD38 therapeutic antibodies, such as daratumumab (DARA). Thus, cancer cells that express CD38 can be selectively targeted for elimination by the immune system using these therapeutic antibodies. In multiple myeloma, DARA is most effective in patients whose tumor cells are CD38hi. In contrast, CD38 expression in AML tumors is generally observed to be negative (CD38neg) or dim (CD38dim), and DARA has not shown activity in preclinical AML models. We previously reported that SY-1425, a clinical stage RARα agonist with improved pharmacokinetics, potency, and selectivity over pan-retinoic acid agonists, induces differentiation in non-APL AML cell lines and primary patient samples with a RARA super-enhancer associated biomarker (RARA-high). Since CD38 was found to be among the most differentially expressed genes in response to SY-1425, we hypothesized that SY-1425 mediated CD38 induction to levels comparable to MM may sensitize RARA-high AML cells to anti-CD38 therapy. We demonstrate that SY-1425 treatment of four RARA-high AML cell lines and four RARA-high primary AML patient PBMCs induces the CD38hi phenotype, as measured by flow cytometry, similar to that found in the DARA sensitive MM cells. In contrast, we see no induction in RARA-low cell lines. We then demonstrated the activity of the SY-1425 and DARA combination in an ex vivo NK cell co-culture assay. Two RARA-high AML cell lines treated with SY-1425 and DARA were co-cultured with NK cells and monitored for both antibody dependent cell-mediated cytotoxicity (ADCC) and NK cell activation by interferon gamma production. The combination of SY-1425 and DARA led to a six-fold increase in tumor cell death relative to the single agent controls, and 5-10 fold increases in NK cell activation is observed only in the SY-1425 and DARA combination treatment of RARA-high AML cell lines. Neither single agent, when administered alone, resulted in ADCC. Furthermore, a RARA-low AML cell line does not respond in the ADCC assay following the combination treatment due to the lack of CD38 induction in this SY-1425 insensitive line. In summary, we have identified a novel and rational combination treatment approach for a subset of patients with RARA-high AML. By inducing the expression of CD38, SY-1425 in combination with DARA elicits tumor cell death and NK cell activation. Based on these findings, a phase 2 clinical study with SY-1425 in combination with an anti-CD38 antibody is planned in AML using an RARA biomarker patient selection strategy.
Citation Format: Kathryn Austgen, Michael R. McKeown, Darren Smith, Emily Lee, Chris Fiore, Matthew L. Eaton, Christian Fritz, Tracey Lodie, Eric Olson. SY-1425, a selective RARα agonist, induces high levels of CD38 expression in RARA-high AML tumors creating a susceptibility to anti-CD38 therapeutic antibody treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2644. doi:10.1158/1538-7445.AM2017-2644
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Affiliation(s)
| | | | | | - Emily Lee
- Syros Pharmaceuticals, Cambridge, MA
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McKeown MR, Eaton ML, Fiore C, Lee E, Austgen K, Smith D, Corces MR, Majeti R, Fritz CC. Abstract 1511: AML patient clustering by super-enhancers reveals an RARA associated transcription factor signaling partner. Cancer Res 2017. [DOI: 10.1158/1538-7445.am2017-1511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Prior studies have shown that the RARA gene is associated with a super-enhancer (SE) and has upregulated mRNA expression in a subset of AML patients. Furthermore, this has been found to confer increased sensitivity to SY-1425, a potent and selective RARα agonist. We sought to better characterize the cell state and transcription factor circuitry in these RARA-high AML cells. Clustering of 62 primary AML patient samples based on their genome wide SE maps identified six discrete clusters. RARA-high patients partitioned principally into cluster 2, and to a lesser extent 1, suggesting that RARA upregulation is associated with a specific transcription factor (TF) network and cell state. To start unraveling the TF circuitry in the RARA-high cluster, we investigated which other TFs were SE associated with clusters 1 and 2. In particular, interferon regulatory factor 8 (IRF8) was found to be strongly associated with clusters 1 and 2 by SE and mRNA expression, similar to RARA. Moreover, the expression of both genes is correlated in primary patient samples. IRF8 is involved in interferon signaling and previous studies have shown crosstalk between interferon and retinoic acid signaling. Furthermore, aberrant IRF8 pathway signaling is implicated in AML and CML pathogenesis. The tight clustering of RARA and IRF8 in patient subgroups defined by genome wide enhancer maps suggests RARα and IRF8 may form an integrated transcriptional circuit. Indeed, treatment with SY-1425 was found to strongly induce interferon-like gene expression changes in AML cells with high RARA or IRF8 levels, including the tumor suppressive IFN responsive gene IRF1. While RARA-high AML cell line models have been previously shown to respond to SY-1425, we found that models with high IRF8 expression and low levels of RARA were also found to respond to SY-1425. Such IRF8-high, RARA-low AML cell lines showed activation of similar transcriptional pathways as RARA-high cell lines in response to SY-1425 based on GSEA. IRF8-high AML also had comparable low nM EC50 anti-proliferative effects following SY-1425 treatment. In addition, SY-1425 was found to elicit differentiation in both RARA-high and IRF8-high AML cell lines based on flow cytometry. While RARA and IRF8 expression appear correlated, this data suggests that IRF8 levels may predict for sensitivity to SY-1425 in addition to RARA levels, particularly in cases of AML with high IRF8 expression but low RARA levels. Insights derived from enhancer analysis, transcriptional profiling and differentiation response in preclinical models support the recently initiated Phase 2 trial of SY-1425 (NCT02807558) in which we are evaluating the SE based patient selection strategies and gene circuitry derived pharmacodynamics clinical measurements, including differentiation markers, in patients with AML and MDS.
Citation Format: Michael R. McKeown, Matthew L. Eaton, Chris Fiore, Emily Lee, Katie Austgen, Darren Smith, M. Ryan Corces, Ravindra Majeti, Christian C. Fritz. AML patient clustering by super-enhancers reveals an RARA associated transcription factor signaling partner [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1511. doi:10.1158/1538-7445.AM2017-1511
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Affiliation(s)
| | | | | | - Emily Lee
- 1Syros Pharmaceuticals, Cambridge, MA
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McKeown MR, Fiore C, Lee E, Eaton ML, Orlando D, Guenther MG, Collins C, Chen MW, Fritz CC, di Tomaso E. Abstract P6-11-18: A novel subgroup of estrogen receptor positive breast cancer may benefit from super-enhancer guided patient selection for retinoic acid receptor α agonist treatment. Cancer Res 2017. [DOI: 10.1158/1538-7445.sabcs16-p6-11-18] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Endocrine-resistance remains a major challenge for treatment of breast cancer. Multiple mechanisms for endocrine resistance have been proposed, including altered expression of ER co-regulators such as Retinoic Acid Receptor Alpha (RARα). Furthermore, crosstalk between estradiol and RA signaling is known and upregulation of RARα has been observed in tamoxifen resistance. We propose a novel treatment paradigm for a newly-defined subset of HR+ patients based on our discovery of a super-enhancer (SE) associated with the RARA locus. SEs are large, highly active chromatin regions that pinpoint cancer vulnerabilities. The RARA SE-identified vulnerability can be targeted using the potent, selective, and metabolically stable RARα agonist SY-1425 (tamibarotene). SY-1425 is approved in Japan to treat Acute Promyelocytic Leukemia, has a well-established efficacy and safety profile, and may enhance response to hormonal therapy (HT) in this newly-defined subset of HR+ patients potentially delaying the need for alternate treatment.
Tumor samples from 42 breast cancer patients were analyzed across a range of molecular subtypes. We identified an SE linked to the RARA gene in 54.5% of the hormone positive patient samples. RARA SEs predicted sensitivity to SY-1425 in 12 breast cancer cell lines confirming their functional role, and showed a correlation with RARA gene expression. A panel of 37 breast cancer cell lines was tested for SY-1425 anti-proliferative activity and gene expression levels, and identified RARA as the single best predictor of response. Proliferation of RARA-high cells was inhibited by SY-1425 with low nanomolar EC50s. Transcriptional profiling was performed on 4 HR+ and 3 HER2+/HR- breast cancer cell lines and analyzed by GSEA to examine the molecular response to SY-1425. Signatures for growth including E2F, MYC, DNA replication, and cell cycle were significantly downregulated while retinol metabolism and luminal signaling were upregulated. Estrogen signaling was also significantly altered by SY-1425, supporting known crosstalk between RARα and ER. Consistent with differentiation, CYP26A1 and VE-Cadherin were induced and Actin and Ki67 were diminished at relevant concentrations of SY-1425 and could serve as pharmacodynamic markers of response.
To test responses to SY-1425 in vivo, two cell line-derived models and two patient-derived breast cancer models (one RARA-high, and one RARA-low each) were treated with SY-1425. SY-1425 inhibited tumor growth in the RARA-high models, but not the RARA-low models (43% versus 0% TGI). Consistent with the observed changes in transcription, SY-1425 in combination with tamoxifen synergistically inhibited proliferation of RARA-high breast cancer cell lines.
Although a few clinical studies have investigated the use of ATRA in HR+ breast cancer without success, our results suggest that patient selection based on the RARA SE may predict which HR+ breast cancer patients could derive benefit by adding an RARα agonist to HT. The potential to prolong or increase the clinical effect of anti-estrogen therapy with SY-1425, which has improved potency, selectivity, and PK stability versus ATRA, would be an attractive strategy to explore.
Citation Format: McKeown MR, Fiore C, Lee E, Eaton ML, Orlando D, Guenther MG, Collins C, Chen MW, Fritz CC, di Tomaso E. A novel subgroup of estrogen receptor positive breast cancer may benefit from super-enhancer guided patient selection for retinoic acid receptor α agonist treatment [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P6-11-18.
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Affiliation(s)
| | - C Fiore
- Syros Pharmaceuticals, Cambridge, MA
| | - E Lee
- Syros Pharmaceuticals, Cambridge, MA
| | - ML Eaton
- Syros Pharmaceuticals, Cambridge, MA
| | - D Orlando
- Syros Pharmaceuticals, Cambridge, MA
| | | | - C Collins
- Syros Pharmaceuticals, Cambridge, MA
| | - MW Chen
- Syros Pharmaceuticals, Cambridge, MA
| | - CC Fritz
- Syros Pharmaceuticals, Cambridge, MA
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McKeown MR, Lee E, Fiore C, Eaton ML, Lopez J, Corces-Zimmerman R, Majeti R, Fritz C, Olson E. Abstract 1187: Discovery of new AML and MDS patient subsets sensitive to the highly selective RARα agonist SY-1425 (tamibarotene) through super-enhancer analysis. Cancer Res 2016. [DOI: 10.1158/1538-7445.am2016-1187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Super-enhancers (SEs) are large, highly active chromatin regions that regulate key cell identity genes including oncogenes in malignant cells. Using our gene control platform, we identified SEs genome-wide in 60 primary AML patient samples to enable the discovery of novel tumor vulnerabilities. One of the SEs that showed a highly asymmetric distribution amongst patient samples was associated with the gene encoding the retinoic acid receptor alpha (RARα). We have discovered that the presence of a RARA SE is predictive for response of non- APL AML cell lines to the highly selective RARα agonist SY-1425. SY-1425 is a clinical stage RARα agonist with improved PK, potency, and selectivity over existing pan-retinoic acid agonists.
SY-1425 has sub-nanomolar potency on RARα, with 200-2000 fold selectivity over other RAR family members. SY-1425 treatment of AML cell lines containing a RARA SE results in 0.2-2 nanomolar EC50 anti-proliferative effects, whereas proliferation of cell lines without SEs are not affected. The RARA enhancer level (as measured by H3K27ac ChIP-seq) is well correlated with mRNA levels for RARα. Two patient derived xenograft models with high RARα mRNA show prolonged survival and tumor cell differentiation response to SY-1425, whereas two models with low RARα mRNA do not show a treatment effect. In contrast, treatment with the non-selective agonist ATRA fails to show a survival benefit in a RARα mRNA high model, presumably due to its lower agonist activity and its inferior PK.
RARα is a nuclear hormone receptor that acts as a transcriptional repressor when unliganded and as a transcriptional activator when bound by an agonist. SY-1425 treatment of SE containing AML cells shows a transcriptional response very similar to retinoid treatment of APL cells. Analysis of ex vivo treated primary AML cells as well as analysis of bone marrow and blood samples from SY-1425 treated patient derived xenograft models support an anti-proliferative and differentiation induction effect in cells containing the RARA SE but not in cells lacking the RARA SE. In addition to AML, a sub-population of MDS patient samples also contain elevated RARα mRNA levels, suggesting the potential utility of SY-1425 in this closely related indication.
In summary, using our gene control platform, we have identified subsets of non-APL AML and MDS who may respond to the selective RARa agonist, SY-1425. A phase 2 clinical study with SY-1425 is being planned in patients identified with a novel biomarker based on these findings.
Citation Format: Michael R. McKeown, Emily Lee, Chris Fiore, Matthew L. Eaton, Jeremy Lopez, Ryan Corces-Zimmerman, Ravindra Majeti, Christian Fritz, Eric Olson. Discovery of new AML and MDS patient subsets sensitive to the highly selective RARα agonist SY-1425 (tamibarotene) through super-enhancer analysis. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1187.
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Affiliation(s)
| | - Emily Lee
- 1Syros Pharmaceuticals, Cambridge, MA
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Chibnik LB, Yu L, Eaton ML, Srivastava G, Schneider JA, Kellis M, Bennett DA, De Jager PL. Alzheimer's loci: epigenetic associations and interaction with genetic factors. Ann Clin Transl Neurol 2015; 2:636-47. [PMID: 26125039 PMCID: PMC4479524 DOI: 10.1002/acn3.201] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2015] [Revised: 02/20/2015] [Accepted: 03/06/2015] [Indexed: 12/12/2022] Open
Abstract
OBJECTIVE We explore the role of DNA methylation in Alzheimer's disease (AD). To elucidate where DNA methylation falls along the causal pathway linking risk factors to disease, we examine causal models to assess its role in the pathology of AD. METHODS DNA methylation profiles were generated in 740 brain samples using the Illumina HumanMet450K beadset. We focused our analysis on CpG sites from 11 AD susceptibility gene regions. The primary outcome was a quantitative measure of neuritic amyloid plaque (NP), a key early element of AD pathology. We tested four causal models: (1) independent associations, (2) CpG mediating the association of a variant, (3) reverse causality, and (4) genetic variant by CpG interaction. RESULTS Six genes regions (17 CpGs) showed evidence of CpG associations with NP, independent of genetic variation - BIN1 (5), CLU (5), MS4A6A (3), ABCA7 (2), CD2AP (1), and APOE (1). Together they explained 16.8% of the variability in NP. An interaction effect was seen in the CR1 region for two CpGs, cg10021878 (P = 0.01) and cg05922028 (P = 0.001), in relation to NP. In both cases, subjects with the risk allele rs6656401(AT) (/) (AA) display more methylation being associated with more NP burden, whereas subjects with the rs6656401(TT) protective genotype have an inverse association with more methylation being associated with less NP. INTERPRETATION These observations suggest that, within known AD susceptibility loci, methylation is related to pathologic processes of AD and may play a largely independent role by influencing gene expression in AD susceptibility loci.
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Affiliation(s)
- Lori B Chibnik
- Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology and Psychiatry, Brigham and Women's Hospital Boston, Massachusetts, 02115 ; Department of Neurology, Harvard Medical School Boston, Massachusetts, 02115 ; Medical and Population Genetics, Broad Institute of MIT and Harvard Cambridge, Massachusetts, 02142 ; Department of Epidemiology, Harvard T.H. Chan School of Public Health Boston, Massachusetts, 02115
| | - Lei Yu
- Medical and Population Genetics, Broad Institute of MIT and Harvard Cambridge, Massachusetts, 02142 ; Rush Alzheimer's Disease Center, Rush University Medical Center Chicago, Illinois, 60612
| | - Matthew L Eaton
- Medical and Population Genetics, Broad Institute of MIT and Harvard Cambridge, Massachusetts, 02142 ; Computer Science and Artificial Intelligence Laboratory, MIT Cambridge, Massachusetts, 02124
| | - Gyan Srivastava
- Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology and Psychiatry, Brigham and Women's Hospital Boston, Massachusetts, 02115 ; Department of Neurology, Harvard Medical School Boston, Massachusetts, 02115 ; Medical and Population Genetics, Broad Institute of MIT and Harvard Cambridge, Massachusetts, 02142
| | - Julie A Schneider
- Rush Alzheimer's Disease Center, Rush University Medical Center Chicago, Illinois, 60612
| | - Manolis Kellis
- Medical and Population Genetics, Broad Institute of MIT and Harvard Cambridge, Massachusetts, 02142 ; Computer Science and Artificial Intelligence Laboratory, MIT Cambridge, Massachusetts, 02124
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center Chicago, Illinois, 60612
| | - Philip L De Jager
- Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology and Psychiatry, Brigham and Women's Hospital Boston, Massachusetts, 02115 ; Department of Neurology, Harvard Medical School Boston, Massachusetts, 02115 ; Medical and Population Genetics, Broad Institute of MIT and Harvard Cambridge, Massachusetts, 02142
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Hatchi E, Skourti-Stathaki K, Ventz S, Pinello L, Yen A, Kamieniarz-Gdula K, Dimitrov S, Pathania S, McKinney KM, Eaton ML, Kellis M, Hill SJ, Parmigiani G, Proudfoot NJ, Livingston DM. BRCA1 recruitment to transcriptional pause sites is required for R-loop-driven DNA damage repair. Mol Cell 2015; 57:636-647. [PMID: 25699710 PMCID: PMC4351672 DOI: 10.1016/j.molcel.2015.01.011] [Citation(s) in RCA: 311] [Impact Index Per Article: 34.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2014] [Revised: 11/21/2014] [Accepted: 01/05/2015] [Indexed: 11/07/2022]
Abstract
The mechanisms contributing to transcription-associated genomic instability are both complex and incompletely understood. Although R-loops are normal transcriptional intermediates, they are also associated with genomic instability. Here, we show that BRCA1 is recruited to R-loops that form normally over a subset of transcription termination regions. There it mediates the recruitment of a specific, physiological binding partner, senataxin (SETX). Disruption of this complex led to R-loop-driven DNA damage at those loci as reflected by adjacent γ-H2AX accumulation and ssDNA breaks within the untranscribed strand of relevant R-loop structures. Genome-wide analysis revealed widespread BRCA1 binding enrichment at R-loop-rich termination regions (TRs) of actively transcribed genes. Strikingly, within some of these genes in BRCA1 null breast tumors, there are specific insertion/deletion mutations located close to R-loop-mediated BRCA1 binding sites within TRs. Thus, BRCA1/SETX complexes support a DNA repair mechanism that addresses R-loop-based DNA damage at transcriptional pause sites. Endogenous BRCA1 and senataxin (SETX) interact in a BRCA1-driven process BRCA1/SETX complexes are recruited to R-loop-associated termination regions (TRs) BRCA1/SETX complexes suppress transcriptional DNA damage arising at nearby R-loops BRCA1 breast cancers reveal indel mutations near BRCA1 TR binding regions
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Affiliation(s)
- Elodie Hatchi
- Department of Genetics, Harvard Medical School, Boston, MA 02215, USA; Department of Cancer Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA.
| | | | - Steffen Ventz
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA; Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
| | - Luca Pinello
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA; Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
| | - Angela Yen
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Computer Science and Artificial Intelligence Laboratory (CSAIL), MIT, Cambridge, MA 02139, USA
| | | | - Stoil Dimitrov
- Department of Genetics, Harvard Medical School, Boston, MA 02215, USA; Department of Cancer Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA
| | - Shailja Pathania
- Department of Genetics, Harvard Medical School, Boston, MA 02215, USA; Department of Cancer Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA
| | - Kristine M McKinney
- Department of Genetics, Harvard Medical School, Boston, MA 02215, USA; Department of Cancer Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA
| | - Matthew L Eaton
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Computer Science and Artificial Intelligence Laboratory (CSAIL), MIT, Cambridge, MA 02139, USA
| | - Manolis Kellis
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Computer Science and Artificial Intelligence Laboratory (CSAIL), MIT, Cambridge, MA 02139, USA
| | - Sarah J Hill
- Department of Genetics, Harvard Medical School, Boston, MA 02215, USA; Department of Cancer Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA
| | - Giovanni Parmigiani
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA; Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
| | | | - David M Livingston
- Department of Genetics, Harvard Medical School, Boston, MA 02215, USA; Department of Cancer Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA.
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9
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Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, Heravi-Moussavi A, Kheradpour P, Zhang Z, Wang J, Ziller MJ, Amin V, Whitaker JW, Schultz MD, Ward LD, Sarkar A, Quon G, Sandstrom RS, Eaton ML, Wu YC, Pfenning AR, Wang X, Claussnitzer M, Liu Y, Coarfa C, Harris RA, Shoresh N, Epstein CB, Gjoneska E, Leung D, Xie W, Hawkins RD, Lister R, Hong C, Gascard P, Mungall AJ, Moore R, Chuah E, Tam A, Canfield TK, Hansen RS, Kaul R, Sabo PJ, Bansal MS, Carles A, Dixon JR, Farh KH, Feizi S, Karlic R, Kim AR, Kulkarni A, Li D, Lowdon R, Elliott G, Mercer TR, Neph SJ, Onuchic V, Polak P, Rajagopal N, Ray P, Sallari RC, Siebenthall KT, Sinnott-Armstrong NA, Stevens M, Thurman RE, Wu J, Zhang B, Zhou X, Beaudet AE, Boyer LA, De Jager PL, Farnham PJ, Fisher SJ, Haussler D, Jones SJM, Li W, Marra MA, McManus MT, Sunyaev S, Thomson JA, Tlsty TD, Tsai LH, Wang W, Waterland RA, Zhang MQ, Chadwick LH, Bernstein BE, Costello JF, Ecker JR, Hirst M, Meissner A, Milosavljevic A, Ren B, Stamatoyannopoulos JA, Wang T, Kellis M. Integrative analysis of 111 reference human epigenomes. Nature 2015; 518:317-30. [PMID: 25693563 PMCID: PMC4530010 DOI: 10.1038/nature14248] [Citation(s) in RCA: 4014] [Impact Index Per Article: 446.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2014] [Accepted: 01/21/2015] [Indexed: 02/06/2023]
Abstract
The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.
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Affiliation(s)
- Anshul Kundaje
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [3] Department of Genetics, Department of Computer Science, 300 Pasteur Dr., Lane Building, L301, Stanford, California 94305-5120, USA
| | - Wouter Meuleman
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Jason Ernst
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [3] Department of Biological Chemistry, University of California, Los Angeles, 615 Charles E Young Dr South, Los Angeles, California 90095, USA
| | - Misha Bilenky
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada
| | - Angela Yen
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Alireza Heravi-Moussavi
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada
| | - Pouya Kheradpour
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Zhizhuo Zhang
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Jianrong Wang
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Michael J Ziller
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Department of Stem Cell and Regenerative Biology, 7 Divinity Ave, Cambridge, Massachusetts 02138, USA
| | - Viren Amin
- Epigenome Center, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA
| | - John W Whitaker
- Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Matthew D Schultz
- Genomic Analysis Laboratory, Howard Hughes Medical Institute &The Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, California 92037, USA
| | - Lucas D Ward
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Abhishek Sarkar
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Gerald Quon
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Richard S Sandstrom
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, Washington 98195, USA
| | - Matthew L Eaton
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Yi-Chieh Wu
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Andreas R Pfenning
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Xinchen Wang
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [3] Biology Department, Massachusetts Institute of Technology, 31 Ames St, Cambridge, Massachusetts 02142, USA
| | - Melina Claussnitzer
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Yaping Liu
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Cristian Coarfa
- Epigenome Center, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA
| | - R Alan Harris
- Epigenome Center, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA
| | - Noam Shoresh
- The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Charles B Epstein
- The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Elizabeta Gjoneska
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 43 Vassar St, Cambridge, Massachusetts 02139, USA
| | - Danny Leung
- 1] Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. [2] Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Wei Xie
- 1] Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. [2] Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - R David Hawkins
- 1] Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. [2] Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Ryan Lister
- Genomic Analysis Laboratory, Howard Hughes Medical Institute &The Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, California 92037, USA
| | - Chibo Hong
- Department of Neurosurgery, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, 1450 3rd Street, San Francisco, California 94158, USA
| | - Philippe Gascard
- Department of Pathology, University of California San Francisco, 513 Parnassus Avenue, San Francisco, California 94143-0511, USA
| | - Andrew J Mungall
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada
| | - Richard Moore
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada
| | - Eric Chuah
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada
| | - Angela Tam
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada
| | - Theresa K Canfield
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, Washington 98195, USA
| | - R Scott Hansen
- Department of Medicine, Division of Medical Genetics, University of Washington, 2211 Elliot Avenue, Seattle, Washington 98121, USA
| | - Rajinder Kaul
- Department of Medicine, Division of Medical Genetics, University of Washington, 2211 Elliot Avenue, Seattle, Washington 98121, USA
| | - Peter J Sabo
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, Washington 98195, USA
| | - Mukul S Bansal
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [3] Department of Computer Science &Engineering, University of Connecticut, 371 Fairfield Way, Storrs, Connecticut 06269, USA
| | - Annaick Carles
- Department of Microbiology and Immunology and Centre for High-Throughput Biology, University of British Columbia, 2125 East Mall, Vancouver, British Columbia V6T 1Z4, Canada
| | - Jesse R Dixon
- 1] Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. [2] Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Kai-How Farh
- The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Soheil Feizi
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Rosa Karlic
- Bioinformatics Group, Department of Molecular Biology, Division of Biology, Faculty of Science, University of Zagreb, Horvatovac 102a, 10000 Zagreb, Croatia
| | - Ah-Ram Kim
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Ashwinikumar Kulkarni
- Department of Molecular and Cell Biology, Center for Systems Biology, The University of Texas, Dallas, NSERL, RL10, 800 W Campbell Road, Richardson, Texas 75080, USA
| | - Daofeng Li
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA
| | - Rebecca Lowdon
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA
| | - GiNell Elliott
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA
| | - Tim R Mercer
- Institute for Molecular Bioscience, University of Queensland, St Lucia, Queensland 4072, Australia
| | - Shane J Neph
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, Washington 98195, USA
| | - Vitor Onuchic
- Epigenome Center, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA
| | - Paz Polak
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Brigham &Women's Hospital, 75 Francis Street, Boston, Massachusetts 02115, USA
| | - Nisha Rajagopal
- 1] Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. [2] Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Pradipta Ray
- Department of Molecular and Cell Biology, Center for Systems Biology, The University of Texas, Dallas, NSERL, RL10, 800 W Campbell Road, Richardson, Texas 75080, USA
| | - Richard C Sallari
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Kyle T Siebenthall
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, Washington 98195, USA
| | - Nicholas A Sinnott-Armstrong
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Michael Stevens
- 1] Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA. [2] Department of Computer Science and Engineeering, Washington University in St. Louis, St. Louis, Missouri 63130, USA
| | - Robert E Thurman
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, Washington 98195, USA
| | - Jie Wu
- 1] Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794-3600, USA. [2] Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | - Bo Zhang
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA
| | - Xin Zhou
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA
| | - Arthur E Beaudet
- Molecular and Human Genetics Department, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA
| | - Laurie A Boyer
- Biology Department, Massachusetts Institute of Technology, 31 Ames St, Cambridge, Massachusetts 02142, USA
| | - Philip L De Jager
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Brigham &Women's Hospital, 75 Francis Street, Boston, Massachusetts 02115, USA. [3] Harvard Medical School, 25 Shattuck St, Boston, Massachusetts 02115, USA
| | - Peggy J Farnham
- Department of Biochemistry, Keck School of Medicine, University of Southern California, 1450 Biggy Street, Los Angeles, California 90089-9601, USA
| | - Susan J Fisher
- ObGyn, Reproductive Sciences, University of California San Francisco, 35 Medical Center Way, San Francisco, California 94143, USA
| | - David Haussler
- Center for Biomolecular Sciences and Engineering, University of Santa Cruz, 1156 High Street, Santa Cruz, California 95064, USA
| | - Steven J M Jones
- 1] Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada. [2] Department of Molecular Biology and Biochemistry, Simon Fraser University, 8888 University Drive, Burnaby, British Columbia V5A 1S6, Canada. [3] Department of Medical Genetics, University of British Columbia, 2329 West Mall, Vancouver, BC, Canada, V6T 1Z4
| | - Wei Li
- Dan L. Duncan Cancer Center, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA
| | - Marco A Marra
- 1] Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada. [2] Department of Medical Genetics, University of British Columbia, 2329 West Mall, Vancouver, BC, Canada, V6T 1Z4
| | - Michael T McManus
- Department of Microbiology and Immunology, Diabetes Center, University of California, San Francisco, 513 Parnassus Ave, San Francisco, California 94143-0534, USA
| | - Shamil Sunyaev
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Brigham &Women's Hospital, 75 Francis Street, Boston, Massachusetts 02115, USA. [3] Harvard Medical School, 25 Shattuck St, Boston, Massachusetts 02115, USA
| | - James A Thomson
- 1] University of Wisconsin, Madison, Wisconsin 53715, USA. [2] Morgridge Institute for Research, 330 N. Orchard Street, Madison, Wisconsin 53707, USA
| | - Thea D Tlsty
- Department of Pathology, University of California San Francisco, 513 Parnassus Avenue, San Francisco, California 94143-0511, USA
| | - Li-Huei Tsai
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 43 Vassar St, Cambridge, Massachusetts 02139, USA
| | - Wei Wang
- Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Robert A Waterland
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, 1100 Bates Street, Houston, Texas 77030, USA
| | - Michael Q Zhang
- 1] Department of Molecular and Cell Biology, Center for Systems Biology, The University of Texas, Dallas, NSERL, RL10, 800 W Campbell Road, Richardson, Texas 75080, USA. [2] Bioinformatics Division, Center for Synthetic and Systems Biology, TNLIST, Tsinghua University, Beijing 100084, China
| | - Lisa H Chadwick
- National Institute of Environmental Health Sciences, 111 T.W. Alexander Drive, Research Triangle Park, North Carolina 27709, USA
| | - Bradley E Bernstein
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Massachusetts General Hospital, 55 Fruit St, Boston, Massachusetts 02114, USA. [3] Howard Hughes Medical Institute, 4000 Jones Bridge Road, Chevy Chase, Maryland 20815-6789, USA
| | - Joseph F Costello
- Department of Neurosurgery, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, 1450 3rd Street, San Francisco, California 94158, USA
| | - Joseph R Ecker
- Genomic Analysis Laboratory, Howard Hughes Medical Institute &The Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, California 92037, USA
| | - Martin Hirst
- 1] Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada. [2] Department of Microbiology and Immunology and Centre for High-Throughput Biology, University of British Columbia, 2125 East Mall, Vancouver, British Columbia V6T 1Z4, Canada
| | - Alexander Meissner
- 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Department of Stem Cell and Regenerative Biology, 7 Divinity Ave, Cambridge, Massachusetts 02138, USA
| | | | - Bing Ren
- 1] Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. [2] Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - John A Stamatoyannopoulos
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, Washington 98195, USA
| | - Ting Wang
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA
| | - Manolis Kellis
- 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA
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10
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De Jager PL, Srivastava G, Lunnon K, Burgess J, Schalkwyk LC, Yu L, Eaton ML, Keenan BT, Ernst J, McCabe C, Tang A, Raj T, Replogle J, Brodeur W, Gabriel S, Chai HS, Younkin C, Younkin SG, Zou F, Szyf M, Epstein CB, Schneider JA, Bernstein BE, Meissner A, Ertekin-Taner N, Chibnik LB, Kellis M, Mill J, Bennett DA. Alzheimer's disease: early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci. Nat Neurosci 2014; 17:1156-63. [PMID: 25129075 PMCID: PMC4292795 DOI: 10.1038/nn.3786] [Citation(s) in RCA: 612] [Impact Index Per Article: 61.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2014] [Accepted: 07/16/2014] [Indexed: 02/07/2023]
Abstract
Here, we leverage a unique collection of 708 prospectively collected autopsied brains to assess the methylation state of the brain's DNA in relation to Alzheimer's disease (AD). We find that the level of methylation at 71 of the 415,848 interrogated CpGs is significantly associated with the burden of AD pathology, including CpGs in the ABCA7 and BIN1 regions, which harbor known AD susceptibility variants. We validate 11 of the differentially methylated regions in an independent set of 117 subjects. Further, we functionally validate these CpG associations and identify the nearby genes whose RNA expression is altered in AD: ANK1, CDH23, DIP2A, RHBDF2, RPL13, RNF34, SERPINF1 and SERPINF2. Our analyses suggest that these DNA methylation changes may have a role in the onset of AD since (1) they are seen in presymptomatic subjects and (2) six of the validated genes connect to a known AD susceptibility gene network.
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Affiliation(s)
- Philip L De Jager
- 1] Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts, USA. [2] Harvard Medical School, Boston, Massachusetts, USA. [3] Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
| | - Gyan Srivastava
- 1] Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts, USA. [2] Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
| | - Katie Lunnon
- 1] University of Exeter Medical School, University of Exeter, Exeter, UK. [2] Institute of Psychiatry, King's College London, London, UK
| | - Jeremy Burgess
- 1] Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA. [2] Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA
| | - Leonard C Schalkwyk
- 1] University of Exeter Medical School, University of Exeter, Exeter, UK. [2] Institute of Psychiatry, King's College London, London, UK
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
| | - Matthew L Eaton
- 1] Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA. [2] Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Brendan T Keenan
- 1] Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts, USA. [2] Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
| | - Jason Ernst
- 1] Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA. [2] Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Cristin McCabe
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
| | - Anna Tang
- Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Towfique Raj
- 1] Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts, USA. [2] Harvard Medical School, Boston, Massachusetts, USA. [3] Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
| | - Joseph Replogle
- 1] Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts, USA. [2] Harvard Medical School, Boston, Massachusetts, USA. [3] Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
| | - Wendy Brodeur
- Genetic Analysis Platform, Broad Institute, Cambridge, Massachusetts, USA
| | - Stacey Gabriel
- Genetic Analysis Platform, Broad Institute, Cambridge, Massachusetts, USA
| | - High S Chai
- 1] Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA. [2] Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA
| | - Curtis Younkin
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Steven G Younkin
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Fanggeng Zou
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Moshe Szyf
- Department of Pharmacology and Therapeutics, McGill University, Montreal, Québec, Canada
| | | | - Julie A Schneider
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
| | - Bradley E Bernstein
- 1] Harvard Medical School, Boston, Massachusetts, USA. [2] Epigenomics Program, Broad Institute, Cambridge, Massachusetts, USA. [3] Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Alex Meissner
- 1] Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] Epigenomics Program, Broad Institute, Cambridge, Massachusetts, USA. [3] Harvard Stem Cell Institute, Harvard University, Cambridge, Massachusetts, USA
| | - Nilufer Ertekin-Taner
- 1] Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA. [2] Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA
| | - Lori B Chibnik
- 1] Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts, USA. [2] Harvard Medical School, Boston, Massachusetts, USA. [3] Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
| | - Manolis Kellis
- 1] Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA. [2] Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Jonathan Mill
- 1] University of Exeter Medical School, University of Exeter, Exeter, UK. [2] Institute of Psychiatry, King's College London, London, UK
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
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11
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Sher N, Bell GW, Li S, Nordman J, Eng T, Eaton ML, Macalpine DM, Orr-Weaver TL. Developmental control of gene copy number by repression of replication initiation and fork progression. Genome Res 2011; 22:64-75. [PMID: 22090375 DOI: 10.1101/gr.126003.111] [Citation(s) in RCA: 84] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Precise DNA replication is crucial for genome maintenance, yet this process has been inherently difficult to study on a genome-wide level in untransformed differentiated metazoan cells. To determine how metazoan DNA replication can be repressed, we examined regions selectively under-replicated in Drosophila polytene salivary glands, and found they are transcriptionally silent and enriched for the repressive H3K27me3 mark. In the first genome-wide analysis of binding of the origin recognition complex (ORC) in a differentiated metazoan tissue, we find that ORC binding is dramatically reduced within these large domains, suggesting reduced initiation as one mechanism leading to under-replication. Inhibition of replication fork progression by the chromatin protein SUUR is an additional repression mechanism to reduce copy number. Although repressive histone marks are removed when SUUR is mutated and copy number restored, neither transcription nor ORC binding is reinstated. Tethering of the SUUR protein to a specific site is insufficient to block replication, however. These results establish that developmental control of DNA replication, at both the initiation and elongation stages, is a mechanism to change gene copy number during differentiation.
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Affiliation(s)
- Noa Sher
- Whitehead Institute and Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, USA
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12
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Roy S, Ernst J, Kharchenko PV, Kheradpour P, Negre N, Eaton ML, Landolin JM, Bristow CA, Ma L, Lin MF, Washietl S, Arshinoff BI, Ay F, Meyer PE, Robine N, Washington NL, Di Stefano L, Berezikov E, Brown CD, Candeias R, Carlson JW, Carr A, Jungreis I, Marbach D, Sealfon R, Tolstorukov MY, Will S, Alekseyenko AA, Artieri C, Booth BW, Brooks AN, Dai Q, Davis CA, Duff MO, Feng X, Gorchakov AA, Gu T, Henikoff JG, Kapranov P, Li R, MacAlpine HK, Malone J, Minoda A, Nordman J, Okamura K, Perry M, Powell SK, Riddle NC, Sakai A, Samsonova A, Sandler JE, Schwartz YB, Sher N, Spokony R, Sturgill D, van Baren M, Wan KH, Yang L, Yu C, Feingold E, Good P, Guyer M, Lowdon R, Ahmad K, Andrews J, Berger B, Brenner SE, Brent MR, Cherbas L, Elgin SCR, Gingeras TR, Grossman R, Hoskins RA, Kaufman TC, Kent W, Kuroda MI, Orr-Weaver T, Perrimon N, Pirrotta V, Posakony JW, Ren B, Russell S, Cherbas P, Graveley BR, Lewis S, Micklem G, Oliver B, Park PJ, Celniker SE, Henikoff S, Karpen GH, Lai EC, MacAlpine DM, Stein LD, White KP, Kellis M. Identification of functional elements and regulatory circuits by Drosophila modENCODE. Science 2010; 330:1787-97. [PMID: 21177974 PMCID: PMC3192495 DOI: 10.1126/science.1198374] [Citation(s) in RCA: 899] [Impact Index Per Article: 64.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
To gain insight into how genomic information is translated into cellular and developmental programs, the Drosophila model organism Encyclopedia of DNA Elements (modENCODE) project is comprehensively mapping transcripts, histone modifications, chromosomal proteins, transcription factors, replication proteins and intermediates, and nucleosome properties across a developmental time course and in multiple cell lines. We have generated more than 700 data sets and discovered protein-coding, noncoding, RNA regulatory, replication, and chromatin elements, more than tripling the annotated portion of the Drosophila genome. Correlated activity patterns of these elements reveal a functional regulatory network, which predicts putative new functions for genes, reveals stage- and tissue-specific regulators, and enables gene-expression prediction. Our results provide a foundation for directed experimental and computational studies in Drosophila and related species and also a model for systematic data integration toward comprehensive genomic and functional annotation.
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Affiliation(s)
| | - Sushmita Roy
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Jason Ernst
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Peter V. Kharchenko
- Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Pouya Kheradpour
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Nicolas Negre
- Institute for Genomics and Systems Biology, Department of Human Genetics, The University of Chicago, 900 East 57th Street, Chicago, IL 60637, USA
| | - Matthew L. Eaton
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - Jane M. Landolin
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Christopher A. Bristow
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Lijia Ma
- Institute for Genomics and Systems Biology, Department of Human Genetics, The University of Chicago, 900 East 57th Street, Chicago, IL 60637, USA
| | - Michael F. Lin
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Stefan Washietl
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Bradley I. Arshinoff
- Department of Molecular Genetics, University of Toronto, 27 King’s College Circle, Toronto, Ontario M5S 1A1, Canada
- Ontario Institute for Cancer Research, 101 College Street, Suite 800, Toronto, Ontario M5G 0A3, Canada
| | - Ferhat Ay
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Patrick E. Meyer
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Machine Learning Group, Université Libre de Bruxelles, CP212, Brussels 1050, Belgium
| | - Nicolas Robine
- Sloan-Kettering Institute, 1275 York Avenue, Box 252, New York, NY 10065, USA
| | | | - Luisa Di Stefano
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown, MA 02129, USA
| | - Eugene Berezikov
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, Utrecht, Netherlands
| | - Christopher D. Brown
- Institute for Genomics and Systems Biology, Department of Human Genetics, The University of Chicago, 900 East 57th Street, Chicago, IL 60637, USA
| | - Rogerio Candeias
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Joseph W. Carlson
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Adrian Carr
- Department of Genetics and Cambridge Systems Biology Centre, University of Cambridge, Downing Street, Cambridge, CB2 3EH, UK
| | - Irwin Jungreis
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Daniel Marbach
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Rachel Sealfon
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Michael Y. Tolstorukov
- Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Sebastian Will
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Artyom A. Alekseyenko
- Department of Medicine and Department of Genetics, Brigham and Women’s Hospital, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Carlo Artieri
- Section of Developmental Genomics, Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Benjamin W. Booth
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Angela N. Brooks
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
| | - Qi Dai
- Sloan-Kettering Institute, 1275 York Avenue, Box 252, New York, NY 10065, USA
| | - Carrie A. Davis
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Michael O. Duff
- Department of Genetics and Developmental Biology, University of Connecticut Stem Cell Institute, 263 Farmington, CT 06030–6403, USA
| | - Xin Feng
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
- Ontario Institute for Cancer Research, 101 College Street, Suite 800, Toronto, Ontario M5G 0A3, Canada
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA
| | - Andrey A. Gorchakov
- Department of Medicine and Department of Genetics, Brigham and Women’s Hospital, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Tingting Gu
- Department of Biology CB-1137, Washington University, Saint Louis, MO 63130, USA
| | - Jorja G. Henikoff
- Sloan-Kettering Institute, 1275 York Avenue, Box 252, New York, NY 10065, USA
| | | | - Renhua Li
- Division of Extramural Research, National Human Genome Research Institute, NIH, 5635 Fishers Lane, Suite 4076, Bethesda, MD 20892–9305, USA
| | - Heather K. MacAlpine
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - John Malone
- Section of Developmental Genomics, Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Aki Minoda
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | | | - Katsutomo Okamura
- Sloan-Kettering Institute, 1275 York Avenue, Box 252, New York, NY 10065, USA
| | - Marc Perry
- Ontario Institute for Cancer Research, 101 College Street, Suite 800, Toronto, Ontario M5G 0A3, Canada
| | - Sara K. Powell
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - Nicole C. Riddle
- Department of Biology CB-1137, Washington University, Saint Louis, MO 63130, USA
| | - Akiko Sakai
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 240 Longwood Avenue, Boston, MA 02115, USA
| | - Anastasia Samsonova
- Department of Genetics and Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Jeremy E. Sandler
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Yuri B. Schwartz
- Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Noa Sher
- White-head Institute, Cambridge, MA 02142, USA
| | - Rebecca Spokony
- Institute for Genomics and Systems Biology, Department of Human Genetics, The University of Chicago, 900 East 57th Street, Chicago, IL 60637, USA
| | - David Sturgill
- Section of Developmental Genomics, Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Marijke van Baren
- Center for Genome Sciences, Washington University, 4444 Forest Park Boulevard, Saint Louis, MO 63108, USA
| | - Kenneth H. Wan
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Li Yang
- Department of Genetics and Developmental Biology, University of Connecticut Stem Cell Institute, 263 Farmington, CT 06030–6403, USA
| | - Charles Yu
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Elise Feingold
- Division of Extramural Research, National Human Genome Research Institute, NIH, 5635 Fishers Lane, Suite 4076, Bethesda, MD 20892–9305, USA
| | - Peter Good
- Division of Extramural Research, National Human Genome Research Institute, NIH, 5635 Fishers Lane, Suite 4076, Bethesda, MD 20892–9305, USA
| | - Mark Guyer
- Division of Extramural Research, National Human Genome Research Institute, NIH, 5635 Fishers Lane, Suite 4076, Bethesda, MD 20892–9305, USA
| | - Rebecca Lowdon
- Division of Extramural Research, National Human Genome Research Institute, NIH, 5635 Fishers Lane, Suite 4076, Bethesda, MD 20892–9305, USA
| | - Kami Ahmad
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 240 Longwood Avenue, Boston, MA 02115, USA
| | - Justen Andrews
- Department of Biology, Indiana University, 1001 East 3rd Street, Bloomington, IN 47405–7005, USA
| | - Bonnie Berger
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
| | - Steven E. Brenner
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
- Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA
| | - Michael R. Brent
- Center for Genome Sciences, Washington University, 4444 Forest Park Boulevard, Saint Louis, MO 63108, USA
| | - Lucy Cherbas
- Department of Biology, Indiana University, 1001 East 3rd Street, Bloomington, IN 47405–7005, USA
- Center for Genomics and Bioinformatics, Indiana University, 1001 East 3rd Street, Bloomington, IN 47405–7005, USA
| | - Sarah C. R. Elgin
- Department of Biology CB-1137, Washington University, Saint Louis, MO 63130, USA
| | - Thomas R. Gingeras
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
- Affymetrix, Santa Clara, CA 95051, USA
| | - Robert Grossman
- Institute for Genomics and Systems Biology, Department of Human Genetics, The University of Chicago, 900 East 57th Street, Chicago, IL 60637, USA
| | - Roger A. Hoskins
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Thomas C. Kaufman
- Department of Biology, Indiana University, 1001 East 3rd Street, Bloomington, IN 47405–7005, USA
| | - William Kent
- Center for Biomolecular Science and Engineering, School of Engineering and Howard Hughes Medical Institute (HHMI), University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Mitzi I. Kuroda
- Department of Medicine and Department of Genetics, Brigham and Women’s Hospital, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | | | - Norbert Perrimon
- Department of Genetics and Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Vincenzo Pirrotta
- Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, NJ 08854, USA
| | - James W. Posakony
- Division of Biological Sciences, Section of Cell and Developmental Biology, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Bing Ren
- Division of Biological Sciences, Section of Cell and Developmental Biology, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Steven Russell
- Department of Genetics and Cambridge Systems Biology Centre, University of Cambridge, Downing Street, Cambridge, CB2 3EH, UK
| | - Peter Cherbas
- Department of Biology, Indiana University, 1001 East 3rd Street, Bloomington, IN 47405–7005, USA
- Center for Genomics and Bioinformatics, Indiana University, 1001 East 3rd Street, Bloomington, IN 47405–7005, USA
| | - Brenton R. Graveley
- Department of Genetics and Developmental Biology, University of Connecticut Stem Cell Institute, 263 Farmington, CT 06030–6403, USA
| | - Suzanna Lewis
- Genome Sciences Division, LBNL, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Gos Micklem
- Department of Genetics and Cambridge Systems Biology Centre, University of Cambridge, Downing Street, Cambridge, CB2 3EH, UK
| | - Brian Oliver
- Section of Developmental Genomics, Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Peter J. Park
- Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Susan E. Celniker
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Steven Henikoff
- Basic Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109, USA
| | - Gary H. Karpen
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory (LBNL), 1 Cyclotron Road, Berkeley, CA 94720 USA
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
| | - Eric C. Lai
- Sloan-Kettering Institute, 1275 York Avenue, Box 252, New York, NY 10065, USA
| | - David M. MacAlpine
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - Lincoln D. Stein
- Ontario Institute for Cancer Research, 101 College Street, Suite 800, Toronto, Ontario M5G 0A3, Canada
| | - Kevin P. White
- Institute for Genomics and Systems Biology, Department of Human Genetics, The University of Chicago, 900 East 57th Street, Chicago, IL 60637, USA
| | - Manolis Kellis
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02140, USA
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13
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Abstract
DNA replication initiates from thousands of start sites throughout the Drosophila genome and must be coordinated with other ongoing nuclear processes such as transcription to ensure genetic and epigenetic inheritance. Considerable progress has been made toward understanding how chromatin modifications regulate the transcription program; in contrast, we know relatively little about the role of the chromatin landscape in defining how start sites of DNA replication are selected and regulated. Here, we describe the Drosophila replication program in the context of the chromatin and transcription landscape for multiple cell lines using data generated by the modENCODE consortium. We find that while the cell lines exhibit similar replication programs, there are numerous cell line-specific differences that correlate with changes in the chromatin architecture. We identify chromatin features that are associated with replication timing, early origin usage, and ORC binding. Primary sequence, activating chromatin marks, and DNA-binding proteins (including chromatin remodelers) contribute in an additive manner to specify ORC-binding sites. We also generate accurate and predictive models from the chromatin data to describe origin usage and strength between cell lines. Multiple activating chromatin modifications contribute to the function and relative strength of replication origins, suggesting that the chromatin environment does not regulate origins of replication as a simple binary switch, but rather acts as a tunable rheostat to regulate replication initiation events.
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Affiliation(s)
- Matthew L Eaton
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina 27710, USA
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14
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Dwyer MA, Joseph J, Wade HE, Eaton ML, Kunder RS, Kazmin D, Chang CY, McDonnell DP. WNT11 expression is induced by estrogen-related receptor alpha and beta-catenin and acts in an autocrine manner to increase cancer cell migration. Cancer Res 2010; 70:9298-308. [PMID: 20870744 PMCID: PMC2982857 DOI: 10.1158/0008-5472.can-10-0226] [Citation(s) in RCA: 114] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Elevated expression of the orphan nuclear receptor estrogen-related receptor α (ERRα) has been associated with a negative outcome in several cancers, although the mechanism(s) by which this receptor influences the pathophysiology of this disease and how its activity is regulated remain unknown. Using a chemical biology approach, it was determined that compounds, previously shown to inhibit canonical Wnt signaling, also inhibited the transcriptional activity of ERRα. The significance of this association was revealed in a series of biochemical and genetic experiments that show that (a) ERRα, β-catenin (β-cat), and lymphoid enhancer-binding factor-1 form macromolecular complexes in cells, (b) ERRα transcriptional activity is enhanced by β-cat expression and vice versa, and (c) there is a high level of overlap among genes previously shown to be regulated by ERRα or β-cat. Furthermore, silencing of ERRα and β-cat expression individually or together dramatically reduced the migratory capacity of breast, prostate, and colon cancer cells in vitro. This increased migration could be attributed to the ERRα/β-cat-dependent induction of WNT11. Specifically, using (a) conditioned medium from cells overexpressing recombinant WNT11 or (b) WNT11 neutralizing antibodies, we were able to show that this protein was the key mediator of the promigratory activities of ERRα/β-cat. Together, these data provide evidence for an autocrine regulatory loop involving transcriptional upregulation of WNT11 by ERRα and β-cat that influences the migratory capacity of cancer cells.
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Affiliation(s)
- Mary A. Dwyer
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC
| | - James Joseph
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC
| | - Hilary E. Wade
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC
| | - Matthew L. Eaton
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC
| | - Rebecca S. Kunder
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC
| | - Dmitri Kazmin
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC
| | - Ching-yi Chang
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC
| | - Donald P. McDonnell
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC
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15
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Müller P, Park S, Shor E, Huebert DJ, Warren CL, Ansari AZ, Weinreich M, Eaton ML, MacAlpine DM, Fox CA. The conserved bromo-adjacent homology domain of yeast Orc1 functions in the selection of DNA replication origins within chromatin. Genes Dev 2010; 24:1418-33. [PMID: 20595233 PMCID: PMC2895200 DOI: 10.1101/gad.1906410] [Citation(s) in RCA: 63] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2010] [Accepted: 05/11/2010] [Indexed: 12/15/2022]
Abstract
The origin recognition complex (ORC) binds to the specific positions on chromosomes that serve as DNA replication origins. Although ORC is conserved from yeast to humans, the DNA sequence elements that specify ORC binding are not. In particular, metazoan ORC shows no obvious DNA sequence specificity, whereas yeast ORC binds to a specific DNA sequence within all yeast origins. Thus, whereas chromatin must play an important role in metazoan ORC's ability to recognize origins, it is unclear whether chromatin plays a role in yeast ORC's recognition of origins. This study focused on the role of the conserved N-terminal bromo-adjacent homology domain of yeast Orc1 (Orc1BAH). Recent studies indicate that BAH domains are chromatin-binding modules. We show that the Orc1BAH domain was necessary for ORC's stable association with yeast chromosomes, and was physiologically relevant to DNA replication in vivo. This replication role was separable from the Orc1BAH domain's previously defined role in transcriptional silencing. Genome-wide analyses of ORC binding in ORC1 and orc1bahDelta cells revealed that the Orc1BAH domain contributed to ORC's association with most yeast origins, including a class of origins highly dependent on the Orc1BAH domain for ORC association (orc1bahDelta-sensitive origins). Orc1bahDelta-sensitive origins required the Orc1BAH domain for normal activity on chromosomes and plasmids, and were associated with a distinct local nucleosome structure. These data provide molecular insights into how the Orc1BAH domain contributes to ORC's selection of replication origins, as well as new tools for examining conserved mechanisms governing ORC's selection of origins within eukaryotic chromosomes.
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Affiliation(s)
- Philipp Müller
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - Sookhee Park
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - Erika Shor
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - Dana J. Huebert
- Program in Cellular and Molecular Biology, College of Agricultural and Life Sciences, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - Christopher L. Warren
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
- College of Agricultural and Life Sciences, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - Aseem Z. Ansari
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
- College of Agricultural and Life Sciences, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - Michael Weinreich
- Laboratory for Chromosome Replication, Van Andel Research Institute, Grand Rapids, Michigan 49503, USA
| | - Matthew L. Eaton
- Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina 27710, USA
| | - David M. MacAlpine
- Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina 27710, USA
| | - Catherine A. Fox
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
- Program in Cellular and Molecular Biology, College of Agricultural and Life Sciences, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
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16
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Abstract
The origin recognition complex (ORC) specifies replication origin location. The Saccharomyces cerevisiae ORC recognizes the ARS (autonomously replicating sequence) consensus sequence (ACS), but only a subset of potential genomic sites are bound, suggesting other chromosomal features influence ORC binding. Using high-throughput sequencing to map ORC binding and nucleosome positioning, we show that yeast origins are characterized by an asymmetric pattern of positioned nucleosomes flanking the ACS. The origin sequences are sufficient to maintain a nucleosome-free origin; however, ORC is required for the precise positioning of nucleosomes flanking the origin. These findings identify local nucleosomes as an important determinant for origin selection and function.
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Affiliation(s)
- Matthew L Eaton
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina 27710, USA
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17
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Abstract
Genetic tests are commercially available for the purpose of aiding in the differential diagnosis of Alzheimer disease among patients with dementia. Such patients often lack the mental capacity to consent to or reject such testing. If genetic testing is to be undertaken, it is important legally and ethically to consider who should participate in the decision to test. State law and the patient's previously expressed wishes will determine which individual should serve as the surrogate decision maker. Other family members should be included in the discussion of the decision, and their assent to the surrogate's decision should be sought.
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Affiliation(s)
- M L Eaton
- Stanford Program in Genomics, Ethics, and Society, Palo Alto, CA 94304, USA.
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18
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Eaton ML, Haye JS, Armstrong FD, Pegelow CH, Thomas M. Hospitalizations for painful episodes: association with school absenteeism and academic performance in children and adolescents with sickle cell anemia. Issues Compr Pediatr Nurs 1995; 18:1-9. [PMID: 8707636 DOI: 10.3109/01460869509080953] [Citation(s) in RCA: 31] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Painful episodes have been identified as one of the most frequent manifestations of sickle cell anemia (hemoglobin HbSS). This retrospective study compared the frequency of hospitalization and the academic performance of two groups of children with HbSS (ages 8 to 18 years) with differing frequencies of pain. A high frequency (HF) group (n = 10) was composed of children who had four or more hospitalizations for pain in the study period; those in the low frequency (LF) group (n = 11) had one or no hospitalizations for pain during the study period. The two groups were matched on age (within 6 months), gender, and ethnicity. Standardized assessments of academic achievement and school records of attendance and class grades were obtained for all participants. The standardized academic achievement for both groups was approximately one standard deviation below the normative mean of the population sample, and class grades were below a C average. School absence was frequent in both groups (LF mean = 16.8 days/year; HF mean = 35.4 days/year), and children in the HF group had significantly more absences than children in the LF group. The lack of difference in academic performance between the two groups suggests that there may be factors other than school absenteeism that affect academic achievement, which require further investigation.
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Berry DA, Eaton ML, Ekholm BP, Fox TL. Assessing differential drug effect. Biometrics 1984; 40:1109-15. [PMID: 6398711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
The regression effect gives a misleading impression of the relationship between drug or treatment effect and baseline measurement. We propose a method of adjusting for the regression effect; we also suggest a corresponding test for the differential drug effect. The likelihood ratio test for no differential drug effect is equivalent to a test for equality of variances, suggested by Pitman (1939, Biometrika 31, 9-12) and Morgan (1939, Biometrika 31, 13-19). The proposed adjustment and test are applied to an example of blood pressure data.
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Rumsfield JA, West DP, Tse CS, Eaton ML, Robinson LA. Isotretinoin in severe, recalcitrant cystic acne: a review. Drug Intell Clin Pharm 1983; 17:329-33. [PMID: 6222891 DOI: 10.1177/106002808301700502] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Isotretinoin, an isomer of retinoic acid, recently has been approved by the Food and Drug Administration for treatment of severe, recalcitrant acne. The most impressive effects include inhibition of sebum production and a reversible decrease in sebaceous gland size. Isotretinoin has proved to be an effective drug; response to therapy has been seen in virtually 100 percent of patients treated. Almost all patients experience reversible cutaneous and mucous-membrane symptoms while on isotretinoin treatment. Other common side effects include conjunctivitis (38 percent) and eye irritation (50 percent). The recommended dosage is 1-2 mg/kg/d for no longer than 16 weeks. Isotretinoin is currently the treatment of choice for severe, recalcitrant acne; however, because of potential side effects associated with retinoids, isotretinoin should be reserved for those patients who are unresponsive to conventional therapy, including topical and systemic antibiotics.
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Eaton ML, MacDonald FM, Church TR, Niewoehner DE. Effects of theophylline on breathlessness and exercise tolerance in patients with chronic airflow obstruction. Chest 1982; 82:538-42. [PMID: 7128220 DOI: 10.1378/chest.82.5.538] [Citation(s) in RCA: 65] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Theophylline is commonly prescribed for patients with nonasthmatic chronic airflow obstruction (CAO) even though clinical efficacy is not well established. We studied objective and subjective responses to theophylline in 14 men with CAO. Subjects randomly received week-long treatments of placebo or theophylline at two dosages: one that produced low (8.7-13.0 micrograms/ml) and the other high (16.0-23.6 micrograms/ml plasma concentrations. During the final three days of each treatment, we measured spirometric and hemodynamic function. Exercise tolerance was assessed with the 12 minute walk and progressive cycle ergometry. The patients' perception of breathlessness during the usual activities of daily living was evaluated with the oxygen cost diagram and the breathlessness rating. For low and high dose theophylline there were significant (p less than .05) increases in forced vital capacity (7.1 +/- 2.1 percent; 12.0 +/- 1.7 percent), forced expiratory volume at one second (14.6 +/- 4.9 percent; 12.1 +/- 3.3 percent) and in pulse rate (8.3 +/- 1.2 percent; 19.1 +/- 3.1 percent), but no changes in blood pressure. There were also no significant differences among the three treatments for any of the tests which assessed exercise tolerance or breathlessness. These results suggest that most patients with CAO experience little symptomatic benefit from taking theophylline.
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Abstract
We studied ventilatory, hemodynamic, and subjective responses to different plasma theophylline concentrations in 10 patients with "irreversible" airflow obstruction. Subjects received theophylline at doses that produced low (9.0 to 12.5 micrograms/mL) and high (17 to 22 micrograms/mL) peak plasma concentrations; subjects also received placebo. A significant (P less than 0.05) dose-related difference in pulmonary function was observed between each treatment. The mean maximal increase in forced expiratory volume at 1 second over placebo was 21.3% for high-dose theophylline and 6.0% for low dose. Both treatments were well tolerated with respect to hemodynamic changes and other adverse effects. Despite improved findings in pulmonary function tests patients were unable to distinguish either treatment from placebo in terms of improvement in breathlessness.
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Eaton ML, Holloway RL. Patient comprehension of written drug information. Am J Hosp Pharm 1980; 37:240-3. [PMID: 7361799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
The effect of the readability level of patient drug information materials on patient comprehension of and attitude toward the information was studied. The reading level of 108 outpatients at a Veterans Administration hospital who could read English, read type of normal size, and who were not receiving warfarin sodium was measured. Patients then were given, on a random basis, a warfarin drug monograph written on either the 5th- or 10th-grade level. To test comprehension, all subjects took a true-false test of recall written at the 5th-grade level. A significant relationship was found between comprehension and reading ability (p less than 0.001). Patients receiving the 5th-grade level monograph exhibited significantly better comprehension than those receiving the 10th-grade level material (p less than 0.001). As compared with those getting 10th-grade material, the group receiving the 5th-grade material had a more favorable perception of the level of difficulty, understandability, and clarity of the material. The study indicates that comprehension of written patient drug information can be improved by adjusting the readability of informational materials to the reading level of the patients.
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Eaton ML. Chronic hypervitaminosis A. Am J Hosp Pharm 1978; 35:1099-102. [PMID: 696755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
A case of chronic hypervitaminosis A in a 51-year-old female is discussed. The patient was ingesting 27,500--35,000 international units of vitamin A daily for 30 years. The patient displayed the classic symptoms of the disease, including skin and hair changes, esophageal varices and extensive liver disease. Vitamin A products were discontinued and the patient's dietary intake of the vitamin was minimized. Previous reports and studies of hypervitaminosis A are reviewed. Social factors causing increased consumption of vitamin A and regulations governing the sale of vitamin A are discussed. By being aware of the factors influencing vitamin A consumption, hypervitaminosis A can be detected and prevented more readily.
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