Sunday, April 24, 2011

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.

Thursday, April 21, 2011

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.

Wednesday, April 20, 2011

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.

Monday, April 18, 2011

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.

Tuesday, April 12, 2011

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.

Wednesday, April 6, 2011

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.