Maternal diet and aging alter the epigenetic control of a promoter–enhancer interaction at the Hnf4a gene in rat pancreatic islets

Maternal diet and aging alter the epigenetic control of a promoter–enhancer interaction at the Hnf4a gene in rat pancreatic islets
Ionel Sandovicia,b,1, Noel H. Smithc,1, Marloes Dekker Nitertd, Matthew Ackers-Johnsonc, Santiago Uribe-Lewise, Yoko Itoe, R. Huw Jonesc, Victor E. Marquezf, William Cairnsg, Mohammed Tadayyong, Laura P. O’Neillh, Adele Murrelle, Charlotte Lingd, Miguel Constânciaa,b,1,2, and Susan E. Ozannec,1,2
+ Author Affiliations

aMetabolic Research Laboratories, Department of Obstetrics and Gynaecology, University of Cambridge, Cambridge CB2 0SW, United Kingdom;
bCentre for Trophoblast Research, University of Cambridge, Cambridge CB2 3EG, United Kingdom;
cMetabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge CB2 OQQ, United Kingdom;
dDiabetes and Endocrinology Research Unit, Lund University, Malmö University Hospital, S-205 02 Malmö, Sweden;
eCancer Research United Kingdom Cambridge Research Institute, Department of Oncology, University of Cambridge, Cambridge CB2 0RE, United Kingdom;
fChemical Biology Laboratory, Center for Cancer Research, National Cancer Institute at Frederick, National Institutes of Health, Frederick, MD 21702;
gBiological Reagents and Assay Development, Medicines Research Centre, GlaxoSmithKline, Stevenage SG1 2NY, United Kingdom; and
hChromatin and Gene Expression Group, Institute of Biomedical Research, University of Birmingham Medical School, Birmingham B15 2TT, United Kingdom
Edited by R. Michael Roberts, University of Missouri, Columbia, MO, and approved February 11, 2011 (received for review December 20, 2010)

Abstract

Environmental factors interact with the genome throughout life to determine gene expression and, consequently, tissue function and disease risk. One such factor that is known to play an important role in determining long-term metabolic health is diet during critical periods of development. Epigenetic regulation of gene expression has been implicated in mediating these programming effects of early diet. The precise epigenetic mechanisms that underlie these effects remain largely unknown. Here, we show that the transcription factor Hnf4a, which has been implicated in the etiology of type 2 diabetes (T2D), is epigenetically regulated by maternal diet and aging in rat islets. Transcriptional activity of Hnf4a in islets is restricted to the distal P2 promoter through its open chromatin configuration and an islet-specific interaction between the P2 promoter and a downstream enhancer. Exposure to suboptimal nutrition during early development leads to epigenetic silencing at the enhancer region, which weakens the P2 promoter–enhancer interaction and results in a permanent reduction in Hnf4a expression. Aging leads to progressive epigenetic silencing of the entire Hnf4a locus in islets, an effect that is more pronounced in rats exposed to a poor maternal diet. Our findings provide evidence for environmentally induced epigenetic changes at the Hnf4a enhancer that alter its interaction with the P2 promoter, and consequently determine T2D risk. We therefore propose that environmentally induced changes in promoter-enhancer interactions represent a fundamental epigenetic mechanism by which nutrition and aging can influence long-term health.

To Assess Genome Assemblers, Steven Salzberg Organizes a Bake-Off

To Assess Genome Assemblers, Steven Salzberg Organizes a Bake-Off
March 2011
By Christie Rizk

http://www.genomeweb.com/informatics/assess-genome-assemblers-steven-salzberg-organizes-bake

Discovery and characterization of chromatin states for systematic annotation of the human genome

Discovery and characterization of chromatin states for systematic annotation of the human genome

Jason Ernst & Manolis Kellis
AffiliationsContributionsCorresponding author
Nature Biotechnology 28, 817–825 (2010) doi:10.1038/nbt.1662
Published online 25 July 2010
Abstract

A plethora of epigenetic modifications have been described in the human genome and shown to play diverse roles in gene regulation, cellular differentiation and the onset of disease. Although individual modifications have been linked to the activity levels of various genetic functional elements, their combinatorial patterns are still unresolved and their potential for systematic de novo genome annotation remains untapped. Here, we use a multivariate Hidden Markov Model to reveal 'chromatin states' in human T cells, based on recurrent and spatially coherent combinations of chromatin marks. We define 51 distinct chromatin states, including promoter-associated, transcription-associated, active intergenic, large-scale repressed and repeat-associated states. Each chromatin state shows specific enrichments in functional annotations, sequence motifs and specific experimentally observed characteristics, suggesting distinct biological roles. This approach provides a complementary functional annotation of the human genome that reveals the genome-wide locations of diverse classes of epigenetic function.

Genomics and Drug Response

Review Article

Genomic Medicine

W. Gregory Feero, M.D., Ph.D., Editor, Alan E. Guttmacher, M.D., Editor
Genomics and Drug Response

Liewei Wang, M.D., Ph.D., Howard L. McLeod, Pharm.D., and Richard M. Weinshilboum, M.D.

N Engl J Med 2011; 364:1144-1153March 24, 2011

Article
References
Glossary

Pharmacogenomics is the study of the role of inherited and acquired genetic variation in drug response.1 Clinically relevant pharmacogenetic examples, mainly involving drug metabolism, have been known for decades, but recently, the field of pharmacogenetics has evolved into “pharmacogenomics,” involving a shift from a focus on individual candidate genes to genomewide association studies. Such studies are based on a rapid scan of markers across the genome of persons affected by a particular disorder or drug-response phenotype and persons who are not affected, with tests for association that compare genetic variation in a case–control setting.2 An example is provided in this issue of the Journal: McCormack and colleagues, testing for genomewide association, identified an HLA allele that is associated with hypersensitivity reactions to the anticonvulsant and mood-stabilizing drug carbamazepine in persons of European descent.3 Pharmacogenomics facilitates the identification of biomarkers that can help physicians optimize drug selection, dose, and treatment duration and avert adverse drug reactions. In addition, pharmacogenomics can provide new insights into mechanisms of drug action and as a result can contribute to the development of new therapeutic agents.

Polycomb Targets Seek Closest Neighbours

Polycomb Targets Seek Closest Neighbours

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Mita Chotalia, Ana Pombo*

Genome Function Group, MRC Clinical Sciences Centre, Imperial College School of Medicine, Hammersmith Hospital Campus, London, United Kingdom

Citation: Chotalia M, Pombo A (2011) Polycomb Targets Seek Closest Neighbours. PLoS Genet 7(3): e1002031. doi:10.1371/journal.pgen.1002031

Editor: Wendy A. Bickmore, Medical Research Council Human Genetics Unit, United Kingdom

Published: March 24, 2011

Copyright: © 2011 Chotalia, Pombo. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The authors received no specific funding for this article.

Competing interests: The authors have declared that no competing interests exist.

* E-mail: ana.pombo@csc.mrc.ac.uk

Eukaryotic chromosomes occupy discrete territories with preferred positions within the cell nucleus, and establish extensive intra- and inter-chromosomal interactions. The mechanisms underlying chromatin interactions and their roles in gene activity and cellular function remain unclear. Nor is it clear to what extent individual loci are free to explore the entire nuclear space, or are constrained by their genomic context. At the local level, interactions between distant enhancer and promoter sequences, detected by 3C (chromosome conformation capture) technologies, have suggested a multi-step mechanism of gene regulation, involving protein binding to enhancer sequences followed by long-range chromatin contacts and activation of the target gene [1], [2]. Long-range interactions have also been described amongst distant, actively transcribed genes, which co-localise at transcription factories. However, long-range interactions are not only limited to events associated with gene activation, but also to those associated with gene repression, including for target genes of Polycomb group (PcG) proteins.

Mapping and analysis of chromatin state dynamics in nine human cell types

Mapping and analysis of chromatin state dynamics in nine human cell types

* Jason Ernst,1, 2
* Pouya Kheradpour,1, 2
* Tarjei S. Mikkelsen,1
* Noam Shoresh,1
* Lucas D. Ward,1, 2
* Charles B. Epstein,1
* Xiaolan Zhang,1
* Li Wang,1
* Robbyn Issner,1
* Michael Coyne,1
* Manching Ku,1, 3, 4
* Timothy Durham,1
* Manolis Kellis1, 2, 5
* & Bradley E. Bernstein1, 3, 4, 5

* Affiliations
* Contributions
* Corresponding author

Journal name:
Nature
Year published:
(2011)
DOI:
doi:10.1038/nature09906

Received
25 August 2010
Accepted
04 February 2011
Published online
23 March 2011

Abstract

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Chromatin profiling has emerged as a powerful means of genome annotation and detection of regulatory activity. The approach is especially well suited to the characterization of non-coding portions of the genome, which critically contribute to cellular phenotypes yet remain largely uncharted. Here we map nine chromatin marks across nine cell types to systematically characterize regulatory elements, their cell-type specificities and their functional interactions. Focusing on cell-type-specific patterns of promoters and enhancers, we define multicell activity profiles for chromatin state, gene expression, regulatory motif enrichment and regulator expression. We use correlations between these profiles to link enhancers to putative target genes, and predict the cell-type-specific activators and repressors that modulate them. The resulting annotations and regulatory predictions have implications for the interpretation of genome-wide association studies. Top-scoring disease single nucleotide polymorphisms are frequently positioned within enhancer elements specifically active in relevant cell types, and in some cases affect a motif instance for a predicted regulator, thus suggesting a mechanism for the association. Our study presents a general framework for deciphering cis-regulatory connections and their roles in disease.

LLM3D: a log-linear modeling-based method to predict functional gene regulatory interactions from genome-wide expression data

LLM3D: a log-linear modeling-based method to predict functional gene regulatory interactions from genome-wide expression data

1. Geert Geeven1,
2. Harold D. MacGillavry2,
3. Ruben Eggers3,
4. Marion M. Sassen2,
5. Joost Verhaagen1,3,
6. August B. Smit2,
7. Mathisca C. M. de Gunst1 and
8. Ronald E. van Kesteren2,*

+ Author Affiliations

1.
1Department of Mathematics, Faculty of Sciences, VU University, De Boelelaan 1081, 1081 HV Amsterdam, 2Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University, De Boelelaan 1085, 1081 HV Amsterdam and 3Department of Neuroregeneration, Netherlands Institute for Neuroscience, Meibergdreef 47, 1105 BA Amsterdam, The Netherlands

1. ↵*To whom correspondence should be addressed. Tel: +31 20 5987111; Fax: +31 20 5989281; Email: ronald.van.kesteren@cncr.vu.nl

* Received October 25, 2010.
* Revision received February 24, 2011.
* Accepted February 25, 2011.

Abstract

All cellular processes are regulated by condition-specific and time-dependent interactions between transcription factors and their target genes. While in simple organisms, e.g. bacteria and yeast, a large amount of experimental data is available to support functional transcription regulatory interactions, in mammalian systems reconstruction of gene regulatory networks still heavily depends on the accurate prediction of transcription factor binding sites. Here, we present a new method, log-linear modeling of 3D contingency tables (LLM3D), to predict functional transcription factor binding sites. LLM3D combines gene expression data, gene ontology annotation and computationally predicted transcription factor binding sites in a single statistical analysis, and offers a methodological improvement over existing enrichment-based methods. We show that LLM3D successfully identifies novel transcriptional regulators of the yeast metabolic cycle, and correctly predicts key regulators of mouse embryonic stem cell self-renewal more accurately than existing enrichment-based methods. Moreover, in a clinically relevant in vivo injury model of mammalian neurons, LLM3D identified peroxisome proliferator-activated receptor γ (PPARγ) as a neuron-intrinsic transcriptional regulator of regenerative axon growth. In conclusion, LLM3D provides a significant improvement over existing methods in predicting functional transcription regulatory interactions in the absence of experimental transcription factor binding data.

Brothers in Arms Against Cancer

Science 25 March 2011:
Vol. 331 no. 6024 pp. 1551-1552
DOI: 10.1126/science.331.6024.1551

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Brothers in Arms Against Cancer

1. Mitch Leslie

Summary

The tumor-suppressor protein p53 has been dubbed "the guardian of the genome." Few nonspecialists know that the celebrated p53 is closely related to two other proteins, p63 and p73. Yet these unheralded siblings are grabbing the attention of cancer biologists. New research suggests that p63 and p73 are fierce cancer killers that deserve equal billing with p53. Because efforts to exploit p53 in cancer therapies haven't yet paid off, some researchers are now looking to p73 and p63 as alternative tumor treatments. Researchers have shrunk or prevented tumors in animals by targeting p73, and the first clinical trials—attempting to use p73 to combat a hard-to-treat type of breast cancer—have already started.

The p53 family: guardians of maternal reproduction

Perspectives

Nature Reviews Molecular Cell Biology 12, 259-265 (April 2011) | doi:10.1038/nrm3086

OPINION:The p53 family: guardians of maternal reproduction

Arnold J. Levine1, Richard Tomasini2, Frank D. McKeon3, Tak W. Mak4 & Gerry Melino5 About the authors

Abstract

The p53 family of proteins consists of p53, p63 and p73, which are transcription factors that affect both cancer and development. It is now emerging that these proteins also regulate maternal reproduction. Whereas p63 is important for maturation of the egg, p73 ensures normal mitosis in the developing blastocyst. p53 subsequently regulates implantation of the embryo through transcriptional control of leukaemia inhibitory factor. Elucidating the cell biological basis of how these factors regulate female fertility may lead to new approaches to the control of human maternal reproduction.

Hypoxia and Inflammation

REVIEW ARTICLE
Hypoxia and Inflammation
Holger K. Eltzschig, M.D., Ph.D., and Peter Carmeliet, M.D., Ph.D.
N Engl J Med 2011; 364:656-665February 17, 2011
This article has no abstract; the first 100 words appear below.
Mammals have oxygen-sensing mechanisms that help them adapt quickly to hypoxia by increasing respiration, blood flow, and survival responses. If an inadequate supply of oxygen persists, additional mechanisms attempt to restore oxygenation or help the body adapt to hypoxia.1 These other mechanisms rely on oxygen-sensing prolyl hydroxylases (PHDs), which hydroxylate prolines in the alpha subunit of the hypoxia-inducible transcription factor (HIF). This transcription factor is a heterodimer with two subunits: HIF-1α or HIF-2α and HIF-1β (or aryl hydrocarbon receptor nuclear translocator [ARNT] protein). HIF-1α is ubiquitous, whereas HIF-2α is restricted to certain tissues.1
In this review, we show the ways . . .
Disclosure forms provided by the authors are available with the full text of this article at NEJM.org.
SOURCE INFORMATION

From the Department of Anesthesiology, University of Colorado Denver, Aurora (H.K.E.); the Department of Anesthesiology and Intensive Care Medicine, Tübingen University Hospital, Tübingen, Germany (H.K.E.); and Vesalius Research Center VIB, and Vesalius Research Center, K.U. Leuven — both in Leuven, Belgium (P.C.).
Address reprint requests to Dr. Eltzschig at the Department of Anesthesiology, University of Colorado Denver, 12700 E. 19th Ave., Mailstop B112, Research Complex 2, Rm. 7124, Aurora, CO 80045, or at holger.eltzschig@ucdenver.edu.