NOA: a novel Network Ontology Analysis method

NOA: a novel Network Ontology Analysis method
Jiguang Wang1, Qiang Huang1, Zhi-Ping Liu2, Yong Wang1, Ling-Yun Wu1, Luonan Chen2,3,* and Xiang-Sun Zhang1,*
+ Author Affiliations

1Key Laboratory of Management, Decision and Information Systems, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, 2Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200233, China and 3Collaborative Research Center for Innovative Mathematical Modelling, Institute of Industrial Science, University of Tokyo, Tokyo 153-8505, Japan
*To whom correspondence should be addressed. Tel: +86-21-6436-5937; Fax: +86-21-5497-2551; Email: lnchen@sibs.ac.cn
Correspondence may also be addressed to Xiang-Sun Zhang. Tel: +86-10-6256-1440; Fax: +86-10-6256-1963; Email: zxs@amt.ac.cn
Received December 13, 2010.
Revision received April 3, 2011.
Accepted April 5, 2011.
Abstract

Gene ontology analysis has become a popular and important tool in bioinformatics study, and current ontology analyses are mainly conducted in individual gene or a gene list. However, recent molecular network analysis reveals that the same list of genes with different interactions may perform different functions. Therefore, it is necessary to consider molecular interactions to correctly and specifically annotate biological networks. Here, we propose a novel Network Ontology Analysis (NOA) method to perform gene ontology enrichment analysis on biological networks. Specifically, NOA first defines link ontology that assigns functions to interactions based on the known annotations of joint genes via optimizing two novel indexes ‘Coverage’ and ‘Diversity’. Then, NOA generates two alternative reference sets to statistically rank the enriched functional terms for a given biological network. We compare NOA with traditional enrichment analysis methods in several biological networks, and find that: (i) NOA can capture the change of functions not only in dynamic transcription regulatory networks but also in rewiring protein interaction networks while the traditional methods cannot and (ii) NOA can find more relevant and specific functions than traditional methods in different types of static networks. Furthermore, a freely accessible web server for NOA has been developed at http://www.aporc.org/noa/.

Differential genome-wide profiling of tandem 3′ UTRs among human breast cancer and normal cells by high-throughput sequencing

Differential genome-wide profiling of tandem 3′ UTRs among human breast cancer and normal cells by high-throughput sequencing
Yonggui Fu1, Yu Sun1, Yuxin Li1, Jie Li, Xingqiang Rao, Chong Chen and Anlong Xu2
+ Author Affiliations

State Key Laboratory for Biocontrol, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, Department of Biochemistry, College of Life Sciences, Sun Yat-sen University, Higher Education Mega Center, Guangzhou, 510006, P.R. China
↵1 These authors contributed equally to this work.

Abstract

Tandem 3′ UTRs produced by alternative polyadenylation (APA) play an important role in gene expression by impacting mRNA stability, translation, and translocation in cells. Several studies have investigated APA site switching in various physiological states; nevertheless, they only focused on either the genes with two known APA sites or several candidate genes. Here, we developed a strategy to study APA sites in a genome-wide fashion with second-generation sequencing technology which could not only identify new polyadenylation sites but also analyze the APA site switching of all genes, especially those with more than two APA sites. We used this strategy to explore the profiling of APA sites in two human breast cancer cell lines, MCF7 and MB231, and one cultured mammary epithelial cell line, MCF10A. More than half of the identified polyadenylation sites are not included in human poly(A) databases. While MCF7 showed shortening 3′ UTRs, more genes in MB231 switched to distal poly(A) sites. Several gene ontology (GO) terms and pathways were enriched in the list of genes with switched APA sites, including cell cycle, apoptosis, and metabolism. These results suggest a more complex regulation of APA sites in cancer cells than previously thought. In short, our novel unbiased method can be a powerful approach to cost-effectively investigate the complex mechanism of 3′ UTR switching in a genome-wide fashion among various physiological processes and diseases.

Epigenetic Regulation of Cell Type–Specific Expression Patterns in the Human Mammary Epithelium

Epigenetic Regulation of Cell Type–Specific Expression Patterns in the Human Mammary Epithelium


Differentiation is an epigenetic program that involves the gradual loss of pluripotency and acquisition of cell type–specific features. Understanding these processes requires genome-wide analysis of epigenetic and gene expression profiles, which have been challenging in primary tissue samples due to limited numbers of cells available. Here we describe the application of high-throughput sequencing technology for profiling histone and DNA methylation, as well as gene expression patterns of normal human mammary progenitor-enriched and luminal lineage-committed cells. We observed significant differences in histone H3 lysine 27 tri-methylation (H3K27me3) enrichment and DNA methylation of genes expressed in a cell type–specific manner, suggesting their regulation by epigenetic mechanisms and a dynamic interplay between the two processes that together define developmental potential. The technologies we developed and the epigenetically regulated genes we identified will accelerate the characterization of primary cell epigenomes and the dissection of human mammary epithelial lineage-commitment and luminal differentiation.

Extensive chromatin remodelling and establishment of transcription factor ‘hotspots’ during early adipogenesis

The EMBO Journal (2011) 30, 1459 - 1472 doi:10.1038/emboj.2011.65
Published online: 22 March 2011


Subject Category: Chromatin and Transcription
Extensive chromatin remodelling and establishment of transcription factor ‘hotspots’ during early adipogenesis

Rasmus Siersbæk1, Ronni Nielsen1, Sam John2, Myong-Hee Sung2, Songjoon Baek2, Anne Loft1, Gordon L Hager2 and Susanne Mandrup1

Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, USA
Correspondence to:
Susanne Mandrup, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej 55, Odense 5230, Denmark. Tel.: +45 6550 2340; Fax: +45 6550 2467; E-mail: s.mandrup@bmb.sdu.dk

Gordon L Hager, Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892-5055, USA. Tel.: +1 301 496 9867; Fax: +1 301 496 4951; E-mail: hagerg@dce41.nci.nih.gov

Received 30 September 2010; Accepted 17 February 2011

Adipogenesis is tightly controlled by a complex network of transcription factors acting at different stages of differentiation. Peroxisome proliferator-activated receptor γ (PPARγ) and CCAAT/enhancer-binding protein (C/EBP) family members are key regulators of this process. We have employed DNase I hypersensitive site analysis to investigate the genome-wide changes in chromatin structure that accompany the binding of adipogenic transcription factors. These analyses revealed a dramatic and dynamic modulation of the chromatin landscape during the first hours of adipocyte differentiation that coincides with cooperative binding of multiple early transcription factors (including glucocorticoid receptor, retinoid X receptor, Stat5a, C/EBPβ and -δ) to transcription factor ‘hotspots’. Our results demonstrate that C/EBPβ marks a large number of these transcription factor ‘hotspots’ before induction of differentiation and chromatin remodelling and is required for their establishment. Furthermore, a subset of early remodelled C/EBP-binding sites persists throughout differentiation and is later occupied by PPARγ, indicating that early C/EBP family members, in addition to their well-established role in activation of PPARγ transcription, may act as pioneering factors for PPARγ binding.

The 2011 Pulitzer Prize Winners

For a distinguished example of explanatory reporting that illuminates a significant and complex subject, demonstrating mastery of the subject, lucid writing and clear presentation, using any available journalistic tool including text reporting, videos, databases, multimedia or interactive presentations or any combination of those formats, in print or online or both, Ten thousand dollars ($10,000).

Awarded Mark Johnson, Kathleen Gallagher, Gary Porter, Lou Saldivar and Alison Sherwood of the Milwaukee Journal Sentinel for their lucid examination of an epic effort to use genetic technology to save a 4-year-old boy imperiled by a mysterious disease, told with words, graphics, videos and other images



Finalists

Also nominated as finalists in this category were: The Wall Street Journal Staff for its penetration of the shadowy world of fraud and abuse in Medicare, probing previously concealed government databases to identify millions of dollars in waste and corrupt practices; and The Washington Post Staff for its exploration of how the military is using trauma surgery, brain science and other techniques both old and new to reduce fatalities among the wounded in warfare, telling the story with words, images and other tools.

A User's Guide to the Encyclopedia of DNA Elements (ENCODE)

Abstract Top
The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome.

MEME-ChIP: motif analysis of large DNA datasets

MEME-ChIP: motif analysis of large DNA datasets
Philip Machanick1 and Timothy L. Bailey1,*
+ Author Affiliations

1Institute for Molecular Bioscience, The University of Queensland, Brisbane 4072, Queensland, Australia.
↵*To whom correspondence should be addressed. Dr. Timothy Bailey, E-mail: t.bailey@imb.uq.edu.au
Received January 23, 2011.
Revision received March 18, 2011.
Accepted April 6, 2011.
Abstract

Motivation: Advances in high-throughput sequencing have resulted in rapid growth in large, high-quality datasets including those arising from transcription factor (TF) ChIP-seq experiments. While there are many existing tools for discovering TF binding site motifs in such datasets, most web-based tools cannot directly process such large datasets.

Results: The MEME-ChIP webservice is designed to analyse ChIP-seq “peak regions”—short genomic regions surrounding declared ChIP-seq “peaks”. Given a set of genomic regions, it performs 1) ab initio motif discovery, 2) motif enrichment analysis, 3) motif visualization, 4) binding affinity analysis and 5) motif identification. It runs two complementary motif discovery algorithms on the input data—MEME and DREME—and uses the motifs they discover in subsequent visualization, binding affinity and identification steps. MEME-ChIP also performs motif enrichment analysis using the AME algorithm, which can detect very low levels of enrichment of binding sites for TFs with known DNA-binding motifs. Importantly, unlike with the MEME webservice, there is no restriction on the size or number of uploaded sequences, allowing very large ChIP-seq datasets to be analyzed. The analyses performed by MEME-ChIP provide the user with a varied view of the binding and regulatory activity of the ChIP-ed TF, as well as the possible involvement of other DNA-binding TFs.

Availability: MEME-ChIP is available as part of the MEME Suite at http://meme.nbcr.net.

Contact: t.bailey@uq.edu.au

Design and validation issues in RNA-seq experiments

Design and validation issues in RNA-seq experiments
Zhide Fang
Zhide Fang obtained his PhD in Statistics in 1999. He is currently an Associate Professor in Biostatistics Program, School of Public Health, at Louisiana State University Health Sciences Center at New Orleans.

Xiangqin Cui
Xiangqin Cui obtained her PhD in Genetics in 2001 and did her postdoctoral training in Statistical Genetics from 2001 to 2004. She is currently an assistant professor in Department of Biostatistics, Section on Statistical Genetics, at the University of Alabama at Birmingham.

Corresponding author. Xiangqin Cui, Assistant Professor, Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, 327 Ryals Public Health Building, 1665 University BLVD, Birmingham, AL 35294, USA. Tel: +1-205-996-4154; Fax: +1-205-975-2540; E-mail: xcui@uab.edu
Received August 30, 2010.
Revision received February 2, 2011.
Abstract

The next-generation sequencing technologies are being rapidly applied in biological research. Tens of millions of short sequences generated in a single experiment provide us enormous information on genome composition, genetic variants, gene expression levels and protein binding sites depending on the applications. Various methods are being developed for analyzing the data generated by these technologies. However, the relevant experimental design issues have rarely been discussed. In this review, we use RNA-seq as an example to bring this topic into focus and to discuss experimental design and validation issues pertaining to next-generation sequencing in the quantification of transcripts.

Integrative analysis of genomic, functional and protein interaction data predicts long-range enhancer-target gene interactions

Integrative analysis of genomic, functional and protein interaction data predicts long-range enhancer-target gene interactions
Christian Rödelsperger1,2,3, Gao Guo3, Mateusz Kolanczyk2, Angelika Pletschacher3, Sebastian Köhler1,3, Sebastian Bauer3, Marcel H. Schulz2,4 and Peter N. Robinson1,2,3,*
+ Author Affiliations


1Berlin-Brandenburg Center for Regenerative Therapies, Charité-Universitätsmedizin Berlin, 2Max Planck Institute for Molecular Genetics, 3Institute for Medical Genetics, Charité-Universitätsmedizin, Berlin and 4International Max Planck Research School for Computational Biology and Scientific Computing, Berlin, Germany
↵*To whom correspondence should be addressed. Tel: +49 30 450566042; Fax: +49 30 450569915; Email: peter.robinson@charite.de
Received June 25, 2010.
Revision received October 14, 2010.
Accepted October 14, 2010.

Nucl. Acids Res. (2011) 39 (7): 2492-2502.
doi: 10.1093/nar/gkq1081

Abstract

Multicellular organismal development is controlled by a complex network of transcription factors, promoters and enhancers. Although reliable computational and experimental methods exist for enhancer detection, prediction of their target genes remains a major challenge. On the basis of available literature and ChIP-seq and ChIP-chip data for enhanceosome factor p300 and the transcriptional regulator Gli3, we found that genomic proximity and conserved synteny predict target genes with a relatively low recall of 12–27% within 2 Mb intervals centered at the enhancers. Here, we show that functional similarities between enhancer binding proteins and their transcriptional targets and proximity in the protein–protein interactome improve prediction of target genes. We used all four features to train random forest classifiers that predict target genes with a recall of 58% in 2 Mb intervals that may contain dozens of genes, representing a better than two-fold improvement over the performance of prediction based on single features alone. Genome-wide ChIP data is still relatively poorly understood, and it remains difficult to assign biological significance to binding events. Our study represents a first step in integrating various genomic features in order to elucidate the genomic network of long-range regulatory interactions.

Alzheimer’s Disease: The Challenge of the Second Century

NEURODEGENERATIVE DISEASE
Alzheimer’s Disease: The Challenge of the Second Century
David M. Holtzman1,2,3,4,*, John C. Morris1,3,4,5 and Alison M. Goate1,3,4,6
+ Author Affiliations

1Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA.
2Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO 63110, USA.
3Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA.
4Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA.
5Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63110, USA.
6Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA.
*↵To whom correspondence should be addressed. E-mail: holtzman@neuro.wustl.edu
Abstract

Alzheimer’s disease (AD) was first described a little more than 100 years ago. It is the most common cause of dementia with an estimated prevalence of 30 million people worldwide, a number that is expected to quadruple in 40 years. There currently is no effective treatment that delays the onset or slows the progression of AD. However, major scientific advances in the areas of genetics, biochemistry, cell biology, and neuroscience over the past 25 years have changed the way we think about AD. This review discusses some of the challenges to translating these basic molecular and cellular discoveries into clinical therapies. Current information suggests that if the disease is detected before the onset of overt symptoms, it is possible that treatments based on knowledge of underlying pathogenesis can and will be effective.

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.