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Posts Tagged ‘National Human Genome Research Institute’

Gene Expression: Algorithms for Protein Dynamics

Posted in Biological Networks, Gene Regulation and Evolution, Computational Biology/Systems and Bioinformatics, Genome Biology, Genomic Testing: Methodology for Diagnosis, Personalized and Precision Medicine & Genomic Research, Population Health Management, Genetics & Pharmaceutical, Scientist: Career considerations, Statistical Methods for Research Evaluation, tagged Alan Boyle, DNA, ENCODE, gene expression, National Human Genome Research Institute, Nucleic acid sequence, Stanford University School of Medicine on October 26, 2013| 1 Comment »

Gene Expression: Algorithms for Protein Dynamics

Reporter:  Aviva Lev-Ari, PhD, RN

Stanford-developed algorithm reveals complex protein dynamics behind gene expression

BY KRISTA CONGER

Michael Snyder

In yet another coup for a research concept known as “big data,” researchers at the Stanford University School of Medicine have developed a computerized algorithm to understand the complex and rapid choreography of hundreds of proteins that interact in mindboggling combinations to govern how genes are flipped on and off within a cell.

To do so, they coupled findings from 238 DNA-protein-binding experiments performed by the ENCODE project — a massive, multiyear international effort to identify the functional elements of the human genome — with a laboratory-based technique to identify binding patterns among the proteins themselves.

The analysis is sensitive enough to have identified many previously unsuspected, multipartner trysts. It can also be performed quickly and repeatedly to track how a cell responds to environmental changes or crucial developmental signals.

“At a very basic level, we are learning who likes to work with whom to regulate around 20,000 human genes,” said Michael Snyder, PhD, professor and chair of genetics at Stanford. “If you had to look through all possible interactions pair-wise, it would be ridiculously impossible. Here we can look at thousands of combinations in an unbiased manner and pull out important and powerful information. It gives us an unprecedented level of understanding.”

Snyder is the senior author of a paper describing the research published Oct. 24 in Cell. The lead authors are postdoctoral scholars Dan Xie, PhD, Alan Boyle, PhD, and Linfeng Wu, PhD.

Related News

• » Revolution in personalized medicine: First-ever integrative ‘omics’ profile lets scientist discover, track his diabetes onset
• » What makes you unique? Not genes so much as surrounding sequences, says study
• » Snyder, Cherry receive National Human Genome Research Institute grants to advance work on ENCODE project

Proteins control gene expression by either binding to specific regions of DNA, or by interacting with other DNA-bound proteins to modulate their function. Previously, researchers could only analyze two to three proteins and DNA sequences at a time, and were unable to see the true complexities of the interactions among proteins and DNA that occur in living cells.

The challenge resembled trying to figure out interactions in a crowded mosh pit by studying a few waltzing couples in an otherwise empty ballroom, and it has severely limited what could be learned about the dynamics of gene expression.

The ENCODE, for the Encyclopedia of DNA Elements, project was a five-year collaboration of more than 440 scientists in 32 labs around the world to reveal the complex interplay among regulatory regions, proteins and RNA molecules that governs when and how genes are expressed. The project has been generating a treasure trove of data for researchers to analyze for the last eight years.

In this study, the researchers combined data from genomics (a field devoted to the study of genes) and proteomics (which focuses on proteins and their interactions). They studied 128 proteins, called trans-acting factors, which are known to regulate gene expression by binding to regulatory regions within the genome. Some of the regions control the expression of nearby genes; others affect the expression of genes great distances away.

The researchers used 238 data sets generated by the ENCODE project to study the specific DNA sequences bound by each of the 128 trans-acting factors. But these factors aren’t monogamous; they bind many different sequences in a variety of protein-DNA combinations. Xie, Boyle and Snyder designed a machine-learning algorithm to analyze all the data and identify which trans-acting factors tend to be seen together and which DNA sequences they prefer.

Wu then performed immunoprecipitation experiments, which use antibodies to identify protein interactions in the cell nucleus. In this way, they were able to tell which proteins interacted directly with one another, and which were seen together because their preferred DNA binding sites were adjoining.

“Before our work, only the combination of two or three regulatory proteins were studied, which oversimplified how gene regulators collaborate to find their targets,” Xie said. “With our method we are able to study the combination of more than 100 regulators and see a much more complex structure of collaboration. For example, it had been believed that a key regulator of cell proliferation called FOS typically only works with JUN protein family members. We show, in addition to JUN, FOS has different partners under different circumstances. In fact, we found almost all the canonical combinations of two or three trans-acting factors have many more partners than we previously thought.”

To broaden their analysis, the researchers included data from other sources that explored protein-binding patterns in five cell types. They found that patterns of co-localization among proteins, in which several proteins are found clustered closely on the DNA to govern gene expression, vary according to cell type and the conditions under which the cells are grown. They also found that many of these clusters can be explained through interactions among proteins, and that not every protein bound to DNA directly.

“We’d like to understand how these interactions work together to make different cell types and how they gain their unique identities in development,” Snyder said. “Furthermore, diseased cells will have a very different type of wiring diagram. We hope to understand how these cells go astray.”

Other Stanford co-authors include life science research assistant Jie Zhai and life science research associate Trupti Kawli, PhD.

The research was supported by the National Human Genome Research Institute (grants U54HG004558 and U54HG006996).

Information about Stanford’s Department of Genetics, which also supported the work, is available at http://genetics.stanford.edu.

PRINT MEDIA CONTACT

Krista Conger | Tel (650) 725-5371

kristac@stanford.edu

BROADCAST MEDIA CONTACT

M.A. Malone | Tel (650) 723-6912

mamalone@stanford.edu

Stanford Medicine integrates research, medical education and patient care at its three institutions – Stanford University School of Medicine, Stanford Hospital & Clinics and Lucile Packard Children’s Hospital. For more information, please visit the Office of Communication & Public Affairs site at

http://mednews.stanford.edu/.http://med.stanford.edu/ism/2013/october/snyder.html?goback=%2Egde_5180384_member_5799368448383397888#sthash%2EhU03LKIX%2Edpuf

 

Dynamic trans-Acting Factor Colocalization in Human Cells

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Cell, Volume 155, Issue 3, 713-724, 24 October 2013
Copyright © 2013 Elsevier Inc. All rights reserved.
10.1016/j.cell.2013.09.043

Authors

Dan Xie,Alan P. Boyle,Linfeng Wu,Jie Zhai,Trupti Kawli,Michael SnyderSee Affiliations

• Highlights
• Colocalization patterns of 128 TFs in human cells
• An application of SOMs to study high-dimensional TF colocalization patterns
• Colocalization patterns are dynamic through stimulation and across cell types
• Many TF colocalizations can be explained by protein-protein interaction

Summary

Different trans-acting factors (TFs) collaborate and act in concert at distinct loci to perform accurate regulation of their target genes. To date, the cobinding of TF pairs has been investigated in a limited context both in terms of the number of factors within a cell type and across cell types and the extent of combinatorial colocalizations. Here, we use an approach to analyze TF colocalization within a cell type and across multiple cell lines at an unprecedented level. We extend this approach with large-scale mass spectrometry analysis of immunoprecipitations of 50 TFs. Our combined approach reveals large numbers of interesting TF-TF associations. We observe extensive change in TF colocalizations both within a cell type exposed to different conditions and across multiple cell types. We show distinct functional annotations and properties of different TF cobinding patterns and provide insights into the complex regulatory landscape of the cell.

http://www.cell.com/abstract/S0092-8674%2813%2901217-8#!

Personal Omics Profiling Reveals Dynamic Molecular and Medical Phenotypes

Cell, Volume 148, Issue 6, 1293-1307, 16 March 2012
Copyright © 2012 Elsevier Inc. All rights reserved.
10.1016/j.cell.2012.02.009

Authors

Rui Chen,George I. Mias,Jennifer Li-Pook-Than,Lihua Jiang,Hugo Y.K. Lam,Rong Chen,Elana Miriami,Konrad J. Karczewski,Manoj Hariharan,Frederick E. Dewey,Yong Cheng,Michael J. Clark,Hogune Im,Lukas Habegger,Suganthi Balasubramanian,Maeve O’Huallachain,Joel T. Dudley,Sara Hillenmeyer,Rajini Haraksingh,Donald Sharon,Ghia Euskirchen,Phil Lacroute,Keith Bettinger,Alan P. Boyle,Maya Kasowski,Fabian Grubert,Scott Seki,Marco Garcia,Michelle Whirl-Carrillo,Mercedes Gallardo,Maria A. Blasco,Peter L. Greenberg,Phyllis Snyder,Teri E. Klein,Russ B. Altman,Atul J. Butte,Euan A. Ashley,Mark Gerstein,Kari C. Nadeau,Hua Tang,Michael Snyder

Department of Genetics, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USADivision of Systems Medicine and Division of Immunology and Allergy, Department of Pediatrics, Stanford University, Stanford, CA 94305, USACenter for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Stanford University, Stanford, CA 94305, USADivision of Hematology, Department of Medicine, Stanford University, Stanford, CA 94305, USA

Personalized medicine aims to assess medical risks, monitor, diagnose and treat patients according to their specific genetic composition and molecular phenotype. The advent of genome sequencing and the analysis of physiological states has proven to be powerful (Cancer Genome Atlas Research Network, 2011). However, its implementation for the analysis of otherwise healthy individuals for estimation of disease risk and medical interpretation is less clear. Much of the genome is difficult to interpret and many complex diseases, such as diabetes, neurological disorders and cancer, likely involve a large number of different genes and biological pathways (Ashley et al., 2010,Grayson et al., 2011,Li et al., 2011), as well as environmental contributors that can be difficult to assess. As such, the combination of genomic information along with a detailed molecular analysis of samples will be important for predicting, diagnosing and treating diseases as well as for understanding the onset, progression, and prevalence of disease states (Snyder et al., 2009).

Presently, healthy and diseased states are typically followed using a limited number of assays that analyze a small number of markers of distinct types. With the advancement of many new technologies, it is now possible to analyze upward of 10⁵ molecular constituents. For example, DNA microarrays have allowed the subcategorization of lymphomas and gliomas (Mischel et al., 2003), and RNA sequencing (RNA-Seq) has identified breast cancer transcript isoforms (Li et al., 2011,van der Werf et al., 2007,Wu et al., 2010,Lapuk et al., 2010). Although transcriptome and RNA splicing profiling are powerful and convenient, they provide a partial portrait of an organism’s physiological state. Transcriptomic data, when combined with genomic, proteomic, and metabolomic data are expected to provide a much deeper understanding of normal and diseased states (Snyder et al., 2010). To date, comprehensive integrative omics profiles have been limited and have not been applied to the analysis of generally healthy individuals.

To obtain a better understanding of: (1) how to generate an integrative personal omics profile (iPOP) and examine as many biological components as possible, (2) how these components change during healthy and diseased states, and (3) how this information can be combined with genomic information to estimate disease risk and gain new insights into diseased states, we performed extensive omics profiling of blood components from a generally healthy individual over a 14 month period (24 months total when including time points with other molecular analyses). We determined the whole-genome sequence (WGS) of the subject, and together with transcriptomic, proteomic, metabolomic, and autoantibody profiles, used this information to generate an iPOP. We analyzed the iPOP of the individual over the course of healthy states and two viral infections (Figure 1A). Our results indicate that disease risk can be estimated by a whole-genome sequence and by regularly monitoring health states with iPOP disease onset may also be observed. The wealth of information provided by detailed longitudinal iPOP revealed unexpected molecular complexity, which exhibited dynamic changes during healthy and diseased states, and provided insight into multiple biological processes. Detailed omics profiling coupled with genome sequencing can provide molecular and physiological information of medical significance. This approach can be generalized for personalized health monitoring and medicine.

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Figure 1. Summary of Study

http://www.cell.com/abstract/S0092-8674%2812%2900166-3#Introduction

 

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ENCODE (Encyclopedia of DNA Elements) program: ‘Tragic’ Sequestration Impact on NHGRI Programs

Posted in Genome Biology, Scientist: Career considerations, tagged DNA, ENCODE, Eric Green, National Human Genome Research Institute, National Institutes of Health, NHGRI, NIH on September 18, 2013| Leave a Comment »

ENCODE (Encyclopedia of DNA Elements) program: ‘Tragic’ Sequestration Impact on NHGRI Programs

Reporter: Aviva Lev-Ari, PhD, RN

NHGRI’s Green Sees ‘Tragic’ Sequestration Impact on NHGRI Programs

September 13, 2013

By Matt Jones

NEW YORK (GenomeWeb News) – The funding squeeze from the sequestration of the US federal budget, now more than half-a-year old, has already had a sizable impact at the National Human Genome Research Institute, leading to cuts to ongoing programs, scaling back of new ones, and the deferring of efforts that have not yet launched.

The five percent cut in funding this year at NHGRI has led not only to trimmed-down renewal grants and fewer, smaller awards broadly, but also has chopped the budget for some of the institute’s important programs, according to NHGRI Director Eric Green.

The programs that have either had their funding reduced, and in one case delayed, include the ENCODE (Encyclopedia of DNA Elements) program, projects focused on using genome sequencing in newborns and in clinical medicine, and other initiatives, Green said in his Director’s Report to the National Advisory Council on Human Genomics Research this week.

In addition, many renewal grants have been trimmed, and there are “numerous examples of detrimental cuts” to the institute’s intramural research program, said Green. These cuts to large and small NHGRI programs come at a pivotal time for genomics, he noted, as the products of such research are beginning to translate into clinical possibilities.

“It is tragic. [That] is the word I would use,” Green told GenomeWeb Daily News this week.

“[The field of genomics] is just so exciting. There are so many opportunities,” he said. “This is precisely the time that we should be pushing the accelerator hard, and we just cannot do it because we don’t have enough fuel in our fuel tank.

“It’s frustrating. I think the opportunities now are just spectacular,” said Green. “It’s tragic because it is just so obvious that we could do some remarkable things in genomics and we are not being able to do it.”

ENCODE, a decade-old flagship project at NIH that aims to identify all of the functional elements in the human genome, had its budget reduced by 16 percent.

The Genomic Sequencing and Newborn Screening Disorders program was cut by half, which left the program to fund fewer research projects than planned and its research consortium to go forward without the benefit of a data coordinating center. This new initiative, an effort to support pioneering studies on how sequencing might be used in the care of newborns and in neonatal care that was created jointly with the Eunice Kennedy Shriver National Institute of Child Health and Human Development, had its budget cut from $10 million to $5 million.

The Genomic Medicine Pilot Demonstration Projects program had its budget cut by 20 percent, and NHGRI’s Bioinformatics Resources and Analysis Research Portfolio had $5 million sliced out of its budget. The new Genomics of Gene Regulation (GGR)request for applications was bumped out of this funding year entirely, and has been delayed until 2014, according to Green.

Because the sequestration plan was concocted and agreed to well in advance of its arrival earlier this year, Green told GWDN that the institute did have some time to try to react to the sequestration and mitigate the pain from the cuts, spreading them around fairly and evenly while maintaining priorities. He said leadership at the institute tried to prepare for the possibility of sequestration by being conservative in its planning.

Programs that were already ongoing, like ENCODE, were likely to take priority over those that were not yet launched, like GGR, in part because the infrastructure is already in place for ongoing projects and because it is easier to plan for how they operate and generate outputs, like data.

“With ENCODE you know for every million dollars you invest you get so much back,” said Green. “With a program like newborn sequencing … we don’t totally know what it’s going to look like or play out like. We won’t know what we are missing because we won’t be able to launch it to the scale that we wanted to launch it originally.”

Green said some of the projects being cut or delayed were created under NHGRI’sstrategic plan, a program it laid out in 2011 that involves restructuring of the institute’s divisions and some shifting in its research portfolio to include more efforts in applying genomics to medicine and healthcare.

“Some of these RFAs that we delayed really represent key elements that we started to anticipate two years ago,” said Green. “We knew we wanted to do more in sequencing, we knew we wanted to do some pilot projects in genomic medicine. We knew we wanted to continue to accelerate efforts in understanding how the genome works … ENCODE, GGR, and so forth. It just had to be slowed down,” he said.

Anastasia Wise, program director for the Genomic Sequencing and Newborn Screening Disorders program, told GWDN that the program was supposed to be much larger than the $5 million in awards unveiled last week, which funded a consortium of four research projects.

Wise said NHGRI and NICHD were each initially planning to provide double the amount of funding they were actually awarded, which is now expected to be a total of $25 million over five years, although that total could be subject to the availability of funding.

“There were definitely more scientifically meritorious applications than we were able to fund,” she said. “Even the four awards that we made ended up being cut an additional five percent because of the sequestration.”

She said the program “wanted to be able to make more awards, and we wanted to be able to fund a coordinating center to be able to bring the network together and help provide some harmonization of data and coordination of logistics between the different members of the consortium,” but it was unable to fund that part of the effort.

Although the fractured fiscal culture in Washington engenders caution at NHGRI as the agency looks forward, Green sees many scientific opportunities right now, as genomics begins to hit the clinic.

“Some people are saying we are not even going fast enough,” he said. “Lots of people have been discussing what the world is going to look like when somebody gets their genome sequenced in the newborn period, and [they] think about what the implications of that are for the patient for the rest of their lives. We want to start studying this,” he said.

“And we are starting to … but we’re not starting as aggressively as we wanted to,” Green said. “I mean, we took a big hit this year.”

Matt Jones is a staff reporter for GenomeWeb Daily News. He covers public policy, legislation, and funding issues that affect researchers in the genomics field, as well as the operations of research institutes. E-mail Matt Jones or follow GWDN’s headlines at @DailyNewsGW.

Related Stories

• NIH Awards up to $25M over Five Years to Teams Testing Genome Sequencing in Newborn Screening
  September 4, 2013 / GenomeWeb Daily News
• NHGRI to Unveil Funding for Tools to Interpret Non-coding Genomic Regions
  May 21, 2013 / GenomeWeb Daily News
• NIH to Fund Ethical, Legal, Social Studies of Genomics Research in Africa
  January 28, 2013 / GenomeWeb Daily News
• NHGRI, NICHD Plan $25M Newborn Sequencing Screening Grants Program
  May 25, 2012 / GenomeWeb Daily News
• NIH’s 2013 Budget Snips NHGRI by $1M, Favors Translational Science Center
  February 14, 2012 / GenomeWeb Daily News

SOURCE

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Genomics: Online Research Resources – genome.gov

Posted in Biological Networks, Gene Regulation and Evolution, Biomarkers & Medical Diagnostics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cell Biology, Signaling & Cell Circuits, Chemical Genetics, Computational Biology/Systems and Bioinformatics, FDA Regulatory Affairs, Genome Biology, Health Law & Patient Safety, Human Sensation and Cellular Transduction: Physiology and Therapeutics, Medical and Population Genetics, Personalized and Precision Medicine & Genomic Research, Population Health Management, Genetics & Pharmaceutical, Proteomics, tagged Division of Intramural Research, gene, genome, Genome project, Human Genome Project, National Human Genome Research Institute, NHGRI, Single-nucleotide polymorphism on June 2, 2013| Leave a Comment »

Reporter: Aviva Lev-Ari, PhD, RN

Online Research Resources

Contents
	From NHGRI
	Online Research Resources Developed at NHGRI
	NHGRI Reports and Publications
	The NHGRI Genome Sequencing Program (GSP)
	Beyond NHGRI
		The Completed Human Sequence
		Other Federal Agencies Involved in Genomics
		Human Genome Sequence Assemblies and Other Genomic Data Resources
		Underlying Map Information
		Sequencing Centers of the International Human Genome Sequencing Consortium
		Model Organism Genome Projects
			Archaea and Bacteria
			Eukaryotes
		Databases
			National Center for Biotechnology Information (NCBI) Databases and Tools
			Nucleotide Sequence Databases
			Trace Archives (Raw Sequence Data Repositories)
			Single Nucleotide Polymorphisms (SNPs)
			cDNAs and Expressed Sequence Tags (ESTs)
			Model Organism Databases
			Additional Sequence, Gene and Protein Databases
		Ethical, Legal and Social Implications (ELSI) Information
		Funding Agencies
		Additional Genome Resources
		Biology Resources
		Selected Journals

From NHGRI

Online Research Resources Developed at NHGRI
Software, databases and research project Web sites from NHGRI’s Division of Intramural Research (DIR).

NHGRI Reports and Publications

• Extramural Research Reports and Publications:
  Workshops and priority setting reports, long-range planning, and Ethical, Legal, and Social Implications (ELSI) reports
• Publications, Books and Recources from the Division of Intramural Research:
  Scientific publications by NHGRI investigators, genomics course materials, and program publications

The NHGRI Genome Sequencing Program (GSP) 
Genome sequencing projects currently in production and funded by NHGRI.

Beyond NHGRI

The Completed Human Sequence:

• At The National Center for Biotechnology Information (NCBI) [ncbi.nlm.nih.gov]
• At The University of California Santa Cruz (UCSC) Gateway [genome.cse.ucsc.edu]
• At Ensembl [ensembl.org]

Other Federal Agencies Involved in Genomics

Human Genome Sequence Assemblies and Other Genomic Data Resources

• UCSC Human Genome Browser Gateway [genome.cse.ucsc.edu]
• Ensembl Human Genome Server [useast.ensembl.org]
• NCBI Human Genome Guide [ncbi.nlm.nih.gov]
• Oak Ridge National Laboratory’s Genome Channel [compbio.ornl.gov]

 

Underlying Map Information

• GeneMap99 [ncbi.nlm.nih.gov]
• Marshfield Comprehensive Human Genetic Maps [research.marshfieldclinic.org]
• Genethon [w3.genethon.fr/php/index_us.php]

Sequencing Centers of the International Human Genome Sequencing Consortium

(Listed in order of total sequence contributed to the draft human sequence published February 15, 2001, Nature, 409:860-921)

• Whitehead Institute for Biomedical Research Center for Genome Research [broadinstitute.org]
  (Now the Broad Institute of MIT and Harvard)
• The Sanger Institute [sanger.ac.uk]
• Washington University Genome Sequencing Center [genome.wustl.edu]
• US DOE Joint Genome Institute [jgi.doe.gov]
• Baylor College of Medicine Human Genome Sequencing Center [hgsc.bcm.tmc.edu]
• RIKEN Genomic Sciences Center [gsc.riken.go.jp]
• Genoscope [genoscope.cns.fr]
• GTC Sequencing Center [genomecorp.com]
  (Now Oscient Pharmaceuticals)
• Department of Genome Analysis, Institute of Molecular Biotechnology [genome.imb-jena.de]
• Multimegabase Sequencing Center, The Institute for Systems Biology [systemsbiology.org]
• Beijing Genomics Institute Human Genome Center [genomics.cn]
• Stanford Genome Technology Center [med.stanford.edu]
• HudsonAlpha Genome Sequencing Center [hagsc.org/]
• University of Washington Genome Center [gs.washington.edu]
• Department of Molecular Biology, Keio University School of Medicine [dmb.med.keio.ac.jp]
• University of Texas Southwestern Medical Center at Dallas [utsouthwestern.edu]
• University of Oklahoma’s Advanced Center for Genome Technology [genome.ou.edu]
• Max Planck Institute for Molecular Genetics [seq.molgen.mpg.de]
• Cold Spring Harbor Laboratory, Lita Annenberg Hazen Genome Center [mccombielab.cshl.edu]
• GBF: German Research Centre for Biotechnology [helmholtz-hzi.de]

Model Organism Genome Projects

Archaea and Bacteria

• J. Craig Venter Institute [jcvi.org]
• The Sanger Institute – Bacterial Genomes [sanger.ac.uk]
• Bacillus subtilis Genome [pbil.univ-lyon1.fr]
• E. coli Genome Project [genome.wisc.edu]

Eukaryotes

• The Arabidopsis Information Resource (TAIR) [arabidopsis.org]
• C. elegans Genome Project [sanger.ac.uk]
• Flybase [flybase.bio.indiana.edu]
• Fugu Genomics Project [fugu.hgmp.mrc.ac.uk]
• Fungal Genome Resource [gene.genetics.uga.edu]
• Maize Genome Database (ZmDB) [maizegdb.org]
• Mouse Genome Informatics [informatics.jax.org]
• Pneumocystis Genome Project [biology.uky.edu]
• Rice Genome Research Program [rgp.dna.affrc.go.jp]
• Saccharomyces Genome Database [yeastgenome.org]
• The Zebrafish Model Organism Database [zfin.org]

Databases

National Center for Biotechnology Information (NCBI) Databases and Tools

• NCBI [ncbi.nlm.nih.gov]
• EntrezGene [ncbi.nlm.nih.gov]
  A searchable database of genes
• NCBI Reference Sequence Project (RefSeq) [ncbi.nlm.nih.gov]
• Macromolecular 3D Structures Database (MMDB) [ncbi.nlm.nih.gov]
• GenBank [ncbi.nlm.nih.gov]

Nucleotide Sequence Databases

• GenBank [ncbi.nlm.nih.gov]
• EMBL Nucleotide Sequence Database [ebi.ac.uk]
• DNA Data Bank of Japan [ddbj.nig.ac.jp]

Trace Archives (Raw Sequence Data Repositories)

• NCBI Trace Archive [ncbi.nlm.nih.gov]

Single Nucleotide Polymorphisms (SNPs)

• The SNP Consortium [snp.cshl.org]
• NCBI dbSNP [ncbi.nlm.nih.gov]

cDNAs and Expressed Sequence Tags (ESTs)

• Mammalian Gene Collection [mgc.nci.nih.gov]
• NCBI dbEST [ncbi.nlm.nih.gov]
• RIKEN Mouse Encyclopedia [osc.riken.go.jp]

Model Organism Databases

• Berkeley Drosophila Genome Project [fruitfly.org]
• Ciona savigny Database [broadinstitute.org]
• FlyBase, Drosophila Database [flybase.bio.indiana.edu]
• MGD, The Mouse Genome Database [informatics.jax.org]
• Saccharomyces Genome Database [yeastgenome.org]
• Tetraodon nigroviridis Database [broadinstitute.org]
• WormBase, The C. elegans Genome Database [wormbase.org]
• Gene Ontology Consortium [geneontology.org]
• The Generic Model Organism Project (GMOD) [gmod.org]
• Comprehensive Microbial Resource [cmr.jcvi.org]

Additional Sequence, Gene and Protein Databases

• InterPro protein sequence analysis & classification [ebi.ac.uk]
  An integrated database of predictive protein signatures used for the classification and automatic annotation of proteins and genomes.
• Eukaryotic Promoter Database [epd.isb-sib.ch]
• PROSITE [expasy.org]
  A database of protein families and domains.
• SWISS-PROT [web.expasy.org]
  A protein knowledgebase.
• BioMagResBank [bmrb.wisc.edu]
  NMR spectroscopy data on proteins, peptides, and nucleic acids.
• Protein Data Bank (PDB) [rcsb.org]
  The repository for 3-D biological macromolecular structure data.
• DSSP [swift.cmbi.ru.nl]
  A database of secondary structure protein assignments.
• FSSP [biocenter.helsinki.fi]
  A database of fold classifications based on structure-structure alignment of proteins.
• HSSP [cmbi.kun.nl]
  A database of homology-derived secondary structure of proteins.
• Nucleic Acid Database Project (NDB) [ndbserver.rutgers.edu]
  Structural information about nucleic acids.
• The I.M.A.G.E. Consortium [image.hudsonalpha.org]
  A public collection of genes.

Ethical, Legal and Social Implications (ELSI) Research Program

• Ethical, Legal and Social Implications (ELSI) Research Program (NHGRI)
• Ethical, Legal and Social Issues (ELSI) [ornl.gov]
  Department of Energy (DOE)

Funding Agencies

• National Human Genome Research Institute Grants
• Department of Energy Human Genome Program [genomics.energy.gov]
• The Wellcome Trust [wellcome.ac.uk]
• National Institutes of Health [nih.gov]
• National Science Foundation [nsf.gov]
• United States Department of Agriculture:
  Agricultural Research Service [ars.usda.gov]
  Cooperative State Research, Education and Extension Service [csrees.usda.gov]

Additional Genome Resources

• Basic Local Alignment Search Tool (BLAST) [blast.ncbi.nlm.nih.gov]
• NCBI Genomes Guide [ncbi.nlm.nih.gov]
• Ensembl Genome Browser Explore the Human Genome [ensembl.org]

Biology Resources

• Biolinks [mcb.harvard.edu]
• Entrez Cross-database Search [ncbi.nlm.nih.gov]
• PubMed Biomedical Literature Database [ncbi.nlm.nih.gov]

Selected Journals

• Cell [cell.com]
• Genome Research [genome.cshlp.org]
• Journal of Biological Chemistry [jbc.org]
• Journal of Molecular Biology [sciencedirect.com]
• Nature [nature.com]
• Nature Genetics [nature.com]
• Science [sciencemag.org]

Last Updated: October 16, 2012

SOURCE:

http://www.genome.gov/10000375

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What is the Future for Genomics in Clinical Medicine?

Posted in Bio Instrumentation in Experimental Life Sciences Research, Biological Networks, Gene Regulation and Evolution, Biomarkers & Medical Diagnostics, Cell Biology, Signaling & Cell Circuits, Chemical Biology and its relations to Metabolic Disease, Chemical Genetics, Computational Biology/Systems and Bioinformatics, Disease Biology, Small Molecules in Development of Therapeutic Drugs, Genome Biology, Genomic Testing: Methodology for Diagnosis, Infectious Disease & New Antibiotic Targets, International Global Work in Pharmaceutical, Interviews with Scientific Leaders, Medical and Population Genetics, Molecular Genetics & Pharmaceutical, Personalized and Precision Medicine & Genomic Research, Pharmaceutical Industry Competitive Intelligence, Population Health Management, Genetics & Pharmaceutical, Scientist: Career considerations, Stem Cells for Regenerative Medicine, Systemic Inflammatory Response Related Disorders, Technology Transfer: Biotech and Pharmaceutical, tagged biopharmaceutical research, Cell potency, Cellular differentiation, Code of Human Life, designer drugs, DNA, drug targets, Embryonic stem cell, gene expression, Genome Research, genomics to bedside, Human Genome Project, Human subject research, Max Planck Institute for Molecular Biomedicine, Medical research, microbiome, National Human Genome Research Institute, oligomers, oligonucleotide, Personalized medicine, pioneer transcription factros, polynucleotides, post translational modifications, reproductive research, Research Methodology, Scripps Research Institute, Scripps Translational Science Institute, SNPs, Stem cell, Stress, synthetic nucleotides, Technology Transfer, telomerase, telomere, transcription factor identification, transcription factors, Transcriptomics, Translational Medicine, University of Cambridge on February 17, 2013| 5 Comments »

What is the Future for Genomics in Clinical Medicine?

Author and Curator: Larry H Bernstein, MD, FCAP

 

Introduction

This is the last in a series of articles looking at the past and future of the genome revolution.  It is a revolution indeed that has had a beginning with the first phase discovery leading to the Watson-Crick model, the second phase leading to the completion of the Human Genome Project, a third phase in elaboration of ENCODE.  But we are entering a fourth phase, not so designated, except that it leads to designing a path to the patient clinical experience.
What is most remarkable on this journey, which has little to show in treatment results at this time, is that the boundary between metabolism and genomics is breaking down.  The reality is that we are a magnificent “magical” experience in evolutionary time, functioning in a bioenvironment, put rogether like a truly complex machine, and with interacting parts.  What are those parts – organelles, a genetic message that may be constrained and it may be modified based on chemical structure, feedback, crosstalk, and signaling pathways.  This brings in diet as a source of essential nutrients, exercise as a method for delay of structural loss (not in excess), stress oxidation, repair mechanisms, and an entirely unexpected impact of this knowledge on pharmacotherapy.  I illustrate this with some very new observations.

Gutenberg Redone

The first is a recent talk on how genomic medicine has constructed a novel version of the “printing press”, that led us out of the dark ages.

In our series The Creative Destruction of Medicine, I’m trying to get into critical aspects of how we can Schumpeter or reboot the future of healthcare by leveraging the big innovations that are occurring in the digital world, including digital medicine.

We have this big thing about evidence-based medicine and, of course, the sanctimonious randomized, placebo-controlled clinical trial. Well, that’s great if one can do that, but often we’re talking about needing thousands, if not tens of thousands, of patients for these types of clinical trials. And things are changing so fast with respect to medicine and, for example, genomically guided interventions that it’s going to become increasingly difficult to justify these very large clinical trials.

For example, there was a drug trial for melanoma and the mutation of BRAF, which is the gene that is found in about 60% of people with malignant melanoma. When that trial was done, there was a placebo control, and there was a big ethical charge asking whether it is justifiable to have a body count. This was a matched drug for the biology underpinning metastatic melanoma, which is essentially a fatal condition within 1 year, and researchers were giving some individuals a placebo.

The next observation is a progression of what he have already learned. The genome has a role is cellular regulation that we could not have dreamed of 25 years ago, or less. The role is far more than just the translation of a message from DNA to RNA to construction of proteins, lipoproteins, cellular and organelle structures, and more than a regulation of glycosidic and glycolytic pathways, and under the influence of endocrine and apocrine interactions. Despite what we have learned, the strength of inter-molecular interactions, strong and weak chemical bonds, essential for 3-D folding, we know little about the importance of trace metals that have key roles in catalysis and because of their orbital structures, are essential for organic-inorganic interplay. This will not be coming soon because we know almost nothing about the intracellular, interstitial, and intrvesicular distributions and how they affect the metabolic – truly metabolic events.

I shall however, use some new information that gives real cause for joy.

Reprogramming Alters Cells’ Fate

Kathy Liszewski

Gordon Conference  Report: June 21, 2012;32(11)

New and emerging strategies were showcased at Gordon Conference’s recent “Reprogramming Cell Fate” meeting. For example, cutting-edge studies described how only a handful of key transcription factors were needed to entirely reprogram cells.

M. Azim Surani, Ph.D., Marshall-Walton professor at the Gurdon Institute, University of Cambridge, U.K., is examining cellular reprogramming in a mouse model. Epiblast stem cells are derived from the early-stage embryonic stage after implantation of blastocysts, about six days into development, and retain the potential to undergo reversion to embryonic stem cells (ESCs) or to PGCs.”  They report two critical steps both of which are needed for exploring epigenetic reprogramming.  “Although there are two X chromosomes in females, the inactivation of one is necessary for cell differentiation. Only after epigenetic reprogramming of the X chromosome can pluripotency be acquired. Pluripotent stem cells can generate any fetal or adult cell type but are not capable of developing into a complete organism.”

The second read-out is the activation of Oct4, a key transcription factor involved in ESC development. The expression of Oct4 in epiSCs requires its proximal enhancer.  Dr. Surani said that their cell-based system demonstrates how a systematic analysis can be performed to analyze how other key genes contribute to the many-faceted events involved in reprogramming the germline.

Reprogramming Expressway

A number of other recent studies have shown the importance of Oct4 for self-renewal of undifferentiated ESCs. It is sufficient to induce pluripotency in neural tissues and somatic cells, among others. The expression of Oct4 must be tightly regulated to control cellular differentiation. But, Oct4 is much more than a simple regulator of pluripotency, according to Hans R. Schöler, Ph.D., professor in the department of cell and developmental biology at the Max Planck Institute for Molecular Biomedicine.

Oct4 has a critical role in committing pluripotent cells into the somatic cellular pathway. When embryonic stem cells overexpress Oct4, they undergo rapid differentiation and then lose their ability for pluripotency. Other studies have shown that Oct4 expression in somatic cells reprograms them for transformation into a particular germ cell layer and also gives rise to induced pluripotent stem cells (iPSCs) under specific culture conditions.

Oct4 is the gatekeeper into and out of the reprogramming expressway. By modifying experimental conditions, Oct4 plus additional factors can induce formation of iPSCs, epiblast stem cells, neural cells, or cardiac cells. Dr. Schöler suggests that Oct4 a potentially key factor not only for inducing iPSCs but also for transdifferention.  “Therapeutic applications might eventually focus less on pluripotency and more on multipotency, especially if one can dedifferentiate cells within the same lineage. Although fibroblasts are from a different germ layer, we recently showed that adding a cocktail of transcription factors induces mouse fibroblasts to directly acquire a neural stem cell identity.

Stem cell diagram illustrates a human fetus stem cell and possible uses on the circulatory, nervous, and immune systems. (Photo credit: Wikipedia)

English: Embryonic Stem Cells. (A) shows hESCs. (B) shows neurons derived from hESCs. (Photo credit: Wikipedia)

Transforming growth factor beta (TGF-β) is a secreted protein that controls proliferation, cellular differentiation, and other functions in most cells. http://en.wikipedia.org/wiki/TGFbeta (Photo credit: Wikipedia)

Pioneer Transcription Factors

Pioneer transcription factors take the lead in facilitating cellular reprogramming and responses to environmental cues. Multicellular organisms consist of functionally distinct cellular types produced by differential activation of gene expression. They seek out and bind specific regulatory sequences in DNA. Even though DNA is coated with and condensed into a thick fiber of chromatin. The pioneer factor, discovered by Prof. KS Zaret at UPenn SOM in 1996, he says, endows the competence for gene activity, being among the first transcription factors to engage and pry open the target sites in chromatin.

FoxA factors, expressed in the foregut endoderm of the mouse,are necessary for induction of the liver program. They found that nearly one-third of the DNA sites bound by FoxA in the adult liver occur near silent genes

A Nontranscriptional Role for HIF-1α as a Direct Inhibitor of DNA Replication

ME Hubbi, K Shitiz, DM Gilkes, S Rey,….GL Semenza. Johns Hopkins University SOM
Sci. Signal 2013; 6(262) 10pgs. [DOI: 10.1126/scisignal.2003417]   http:dx.doi.org/10.1126/scisignal.2003417

http://SciSignal.com/A Nontranscriptional Role for HIF-1α as a Direct Inhibitor of DNA Replication/

Many of the cellular responses to reduced O2 availability are mediated through the transcriptional activity of hypoxia-inducible factor 1 (HIF-1). We report a role for the isolated HIF-1α subunit as an inhibitor of DNA replication, and this role was independent of HIF-1β and transcriptional regulation. In response to hypoxia, HIF-1α bound to Cdc6, a protein that is essential for loading of the mini-chromosome maintenance (MCM) complex (which has DNA helicase activity) onto DNA, and promoted the interaction between Cdc6 and the MCM complex. The binding of HIF-1α to the complex decreased phosphorylation and activation of the MCM complex by the kinase Cdc7. As a result, HIF-1α inhibited firing of replication origins, decreased DNA replication, and induced cell cycle arrest in various cell types. To whom correspondence should be addressed. E-mail: gsemenza@jhmi.edu
Citation: M. E. Hubbi, Kshitiz, D. M. Gilkes, S. Rey, C. C. Wong, W. Luo, D.-H. Kim, C. V. Dang, A. Levchenko, G. L. Semenza, A Nontranscriptional Role for HIF-1α as a Direct Inhibitor of DNA Replication. Sci. Signal. 6, ra10 (2013).

Identification of a Candidate Therapeutic Autophagy-inducing Peptide

Nature 2013;494(7436).    http://nature.com/Identification_of_a_candidate_therapeutic_autophagy-inducing_peptide/   http://www.ncbi.nlm.nih.gov/pubmed/23364696
http://www.readcube.com/articles/10.1038/nature11866

Beth Levine and colleagues have constructed a cell-permeable peptide derived from part of an autophagy protein called beclin 1. This peptide is a potent inducer of autophagy in mammalian cells and in vivo in mice and was effective in the clearance of several viruses including chikungunya virus, West Nile virus and HIV-1.

Could this small autophagy-inducing peptide may be effective in the prevention and treatment of human diseases?

PR-Set7 Is a Nucleosome-Specific Methyltransferase that Modifies Lysine 20 of

Histone H4 and Is Associated with Silent Chromatin

K Nishioka, JC Rice, K Sarma, H Erdjument-Bromage, …, D Reinberg.   Molecular Cell, Vol. 9, 1201–1213, June, 2002, Copyright 2002 by Cell Press   http://www.cell.com/molecular-cell/abstract/S1097-2765(02)00548-8

http://www.sciencedirect.com/science/article/pii/S1097276502005488           http://www.ncbi.nlm.nih.gov/pubmed/12086618
http://www.cienciavida.cl/publications/b46e8d324fa4aefa771c4d6ece4d2e27_PR-Set7_Is_a_Nucleosome-Specific.pdf

We have purified a human histone H4 lysine 20methyl-transferase and cloned the encoding gene, PR/SET07. A mutation in Drosophila pr-set7 is lethal: second in-star larval death coincides with the loss of H4 lysine 20 methylation, indicating a fundamental role for PR-Set7 in development. Transcriptionally competent regions lack H4 lysine 20 methylation, but the modification coincided with condensed chromosomal regions polytene chromosomes, including chromocenter euchromatic arms. The Drosophila male X chromosome, which is hyperacetylated at H4 lysine 16, has significantly decreased levels of lysine 20 methylation compared to that of females. In vitro, methylation of lysine 20 and acetylation of lysine 16 on the H4 tail are competitive. Taken together, these results support the hypothesis that methylation of H4 lysine 20 maintains silent chromatin, in part, by precluding neighboring acetylation on the H4 tail.

Next-Generation Sequencing vs. Microarrays

Shawn C. Baker, Ph.D., CSO of BlueSEQ
GEN Feb 2013
With recent advancements and a radical decline in sequencing costs, the popularity of next generation sequencing (NGS) has skyrocketed. As costs become less prohibitive and methods become simpler and more widespread, researchers are choosing NGS over microarrays for more of their genomic applications. The immense number of journal articles citing NGS technologies it looks like NGS is no longer just for the early adopters. Once thought of as cost prohibitive and technically out of reach, NGS has become a mainstream option for many laboratories, allowing researchers to generate more complete and scientifically accurate data than previously possible with microarrays.

Gene Expression

Researchers have been eager to use NGS for gene expression experiments for a detailed look at the transcriptome. Arrays suffer from fundamental ‘design bias’ —they only return results from those regions for which probes have been designed. The various RNA-Seq methods cover all aspects of the transcriptome without any a priori knowledge of it, allowing for the analysis of such things as novel transcripts, splice junctions and noncoding RNAs. Despite NGS advancements, expression arrays are still cheaper and easier when processing large numbers of samples (e.g., hundreds to thousands).
Methylation
While NGS unquestionably provides a more complete picture of the methylome, whole genome methods are still quite expensive. To reduce costs and increase throughput, some researchers are using targeted methods, which only look at a portion of the methylome. Because details of exactly how methylation impacts the genome and transcriptome are still being investigated, many researchers find a combination of NGS for discovery and microarrays for rapid profiling.

Diagnostics

They are interested in ease of use, consistent results, and regulatory approval, which microarrays offer. With NGS, there’s always the possibility of revealing something new and unexpected. Clinicians aren’t prepared for the extra information NGS offers. But the power and potential cost savings of NGS-based diagnostics is alluring, leading to their cautious adoption for certain tests such as non-invasive prenatal testing.
Cytogenetics
Perhaps the application that has made the least progress in transitioning to NGS is cytogenetics. Researchers and clinicians, who are used to using older technologies such as karyotyping, are just now starting to embrace microarrays. NGS has the potential to offer even higher resolution and a more comprehensive view of the genome, but it currently comes at a substantially higher price due to the greater sequencing depth. While dropping prices and maturing technology are causing NGS to make headway in becoming the technology of choice for a wide range of applications, the transition away from microarrays is a long and varied one. Different applications have different requirements, so researchers need to carefully weigh their options when making the choice to switch to a new technology or platform. Regardless of which technology they choose, genomic researchers have never had more options.

Sequencing Hones In on Targets

Greg Crowther, Ph.D.

GEN Feb 2013

Cliff Han, PhD, team leader at the Joint Genome Institute in the Los Alamo National Lab, was one of a number of scientists who made presentations regarding target enrichment at the “Sequencing, Finishing, and Analysis in the Future” (SFAF) conference in Santa Fe, which was co-sponsored by the Los Alamos National Laboratory and DOE Joint Genome Institute. One of the main challenges is that of target enrichment: the selective sequencing of genomic or transcriptomic regions. The polymerase chain reaction (PCR) can be considered the original target-enrichment technique and continues to be useful in contexts such as genome finishing. “One target set is the unique gaps—the gaps in the unique sequence regions. Another is to enrich the repetitive sequences…ribosomal RNA regions, which together are about 5 kb or 6 kb.” The unique-sequence gaps targeted for PCR with 40-nucleotide primers complementary to sequences adjacent to the gaps, did not yield the several-hundred-fold enrichment expected based on previously published work. “We got a maximum of 70-fold enrichment and generally in the dozens of fold of enrichment,” noted Dr. Han.

“We enrich the genome, put the enriched fragments onto the Pacific Biosciences sequencer, and sequence the repeats,” continued Dr. Han. “In many parts of the sequence there will be a unique sequence anchored at one or both ends of it, and that will help us to link these scaffolds together.” This work, while promising, will remain unpublished for now, as the Joint Genome Institute has shifted its resources to other projects.
At the SFAF conference Dr. Jones focused on going beyond basic target enrichment and described new tools for more efficient NGS research. “Hybridization methods are flexible and have multiple stop-start sites, and you can capture very large sizes, but they require library prep,” said Jennifer Carter Jones, Ph.D., a genomics field applications scientist at Agilent. “With PCR-based methods, you have to design PCR primers and you’re doing multiplexed PCR, so it’s limited in the size that you can target. But the workflow is quick because there’s no library preparation; you’re just doing PCR.” She discussed Agilent’s recently acquired HaloPlex technology, a hybrid system that includes both a hybridization step and a PCR step. Because no library preparation is required, sequencing results can be obtained in about six hours, making it suitable for clinical uses. However, the hybridization step allows capture of targets of up to 5 megabases—longer than purely PCR-based methods can deliver. The Agilent talk also provided details on the applications of SureSelect, the company’s hybridization technology, to Methyl-Seq and RNA-Seq research. With this technology, 120-mer baits hybridize to targets, then are pulled down with streptavidin-coated magnetic beads.
These are selections from the SFAF conference, which is expected to be a boost to work on the microbiome, and lead to infectious disease therapeutic approaches.

Summary

We have finished a breathtaking ride through the genomic universe in several sessions.  This has been a thorough review of genomic structure and function in cellular regulation.  The items that have been discussed and can be studied in detail include:

1.  the classical model of the DNA structure
2. the role of ubiquitinylation in managing cellular function and in autophagy, mitophagy, macrophagy, and protein degradation
3. the nature of the tight folding of the chromatin in the nucleus
4. intramolecular bonds and short distance hydrophobic and hydrophilic interactions
5. trace metals in molecular structure
6. nuclear to membrane interactions
7. the importance of the Human Genome Project followed by Encode
8. the Fractal nature of chromosome structure
9. the oligomeric formation of short sequences and single nucletide polymorphisms (SNPs)and the potential to identify drug targets
10. Enzymatic components of gene regulation (ligase, kinases, phosphatases)
11. Methods of computational analysis in genomics
12. Methods of sequencing that have become more accurate and are dropping in cost
13. Chromatin remodeling
14. Triplex and quadruplex models not possible to construct at the time of Watson-Crick
15. sequencing errors
16. propagation of errors
17. oxidative stress and its expected and unintended effects
18. origins of cardiovascular disease
19. starvation and effect on protein loss
20. ribosomal damage and repair
21. mitochondrial damage and repair
22. miscoding and mutational changes
23. personalized medicine
24. Genomics to the clinics
25. Pharmacotherapy horizons
26. driver mutations
27. induced pluripotential embryonic stem cell (iPSCs)
28. The association of key targets with disease
29. The real possibility of moving genomic information to the bedside
30. Requirements for the next generation of electronic health record to enable item 29

Related articles

• Retrovirus in the human genome is active in pluripotent stem cells (sciencedaily.com)
• Learning from the linker: New study sheds light on cellular reprogramming (phys.org)
• A Quantitative System for Discriminating Induced Pluripotent Stem Cells, Embryonic Stem Cells and Somatic Cells (plosone.org)
• Stem Cell Therapies May Improve Following Finding That Retrovirus In The Human Genome Is Active In Pluripotent Stem Cells (medicalnewstoday.com)
• Leprosy spreads by reprogramming nerve cells into migratory stem cells (guardian.co.uk)
• Harvard Researchers: Embryonic Cells Can Cause Cancer (salem-news.com)

Other Related articles on this Open Access Online Scientific Journal, include the following:

http://pharmaceuticalintelligence.com/2013/01/14/oogonial-stem-cells-purified-a-view-towards-the-future-of-reproductive-biology/   SSaha

http://pharmaceuticalintelligence.com/2012/10/22/blood-vessel-generating-stem-cells-discovered/ RSaxena

http://pharmaceuticalintelligence.com/2012/08/22/a-possible-light-by-stem-cell-therapy-in-painful-dark-of-osteoarthritis-kartogenin-a-small-molecule-differentiates-stem-cells-to-chondrocyte-healthy-cartilage-cells/   ASarkar and RSaxena

http://pharmaceuticalintelligence.com/2012/08/07/human-embryonic-pluripotent-stem-cells-and-healing-post-myocardial-infarction/    LHB

http://pharmaceuticalintelligence.com/2013/02/03/genome-wide-detection-of-single-nucleotide-and-copy-number-variation-of-a-single-human-cell/  SJWilliams

http://pharmaceuticalintelligence.com/2013/01/09/gene-therapy-into-healthy-heart-muscle-reprogramming-scar-tissue-in-damaged-hearts/ ALev-Ari

http://pharmaceuticalintelligence.com/2013/01/03/differentiation-therapy-epigenetics-tackles-solid-tumors/  SJWilliams

http://pharmaceuticalintelligence.com/2012/12/09/naotech-therapy-for-breast-cancer/  TBarliya

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CRACKING THE CODE OF HUMAN LIFE: Milestones along the Way – Part IIA

Posted in Biological Networks, Gene Regulation and Evolution, Cell Biology, Signaling & Cell Circuits, Disease Biology, Small Molecules in Development of Therapeutic Drugs, Genome Biology, International Global Work in Pharmaceutical, Interviews with Scientific Leaders, Medical and Population Genetics, Molecular Genetics & Pharmaceutical, Personalized and Precision Medicine & Genomic Research, Population Health Management, Genetics & Pharmaceutical, Scientist: Career considerations, Technology Transfer: Biotech and Pharmaceutical, tagged Cdk2, Cold Spring Harbor Laboratory Press, Craig Venter, cullin ubiquitin ligase family, cyclin E, DNA, DNA damage, ENCODE, F-Box, Fbw7, Gene Regulation, genetics, genomics, Hox gene, Human, human genome, Human Genome Project, National Human Genome Research Institute, Notch propteins, Posttranslational modification, regulatory DNA, ribonucleotide reductase, RNA, RNRs, Science Translational Medicine, shRNA, signal transduction pathways, SNPs, SOS, STAT3, transcription factors on February 12, 2013| 3 Comments »

CRACKING THE CODE OF HUMAN LIFE: Milestones along the Way – Part IIA

Curator: Larry H Bernstein, MD, FCAP

• 

 

Introduction and purpose

This material goes beyond the Initiation Phase of Molecular Biology, Part I.

http://pharmaceuticalintelligence.com/2013/02/08/the-initiation-and-growth-of-molecular-biology-and-genomics/
Part II reviews the Human Genome Project and the decade beyond.

In a three part series:
Part IIA.  CRACKING THE CODE OF HUMAN LIFE: Milestones along the Way
Part IIB.  CRACKING THE CODE OF HUMAN LIFE: The Birth of BioInformatics & Computational Genomics
Part IIC.  CRACKING THE CODE OF HUMAN LIFE: Recent Advances in Genomic Analysis and Disease

Part III will conclude with Ubiquitin, it’s Role in Signaling and Regulatory Control.
Part I reviewed the huge expansion of the biological research enterprise after the Second World War. It concentrated on the

• discovery of cellular structures,
• metabolic function, and
• creation of a new science of Molecular Biology.
•  

Part II follows the race to delineation of the Human Genome, discovery methods and fundamental genomic patterns that are ancient in both animal and plant speciation. But it explores both the complexity and the systems view of the architecture that underlies and understanding of the genome.

These articles review a web-like connectivity between inter-connected scientific discoveries, as significant findings have led to novel hypotheses and many expectations over the last 75 years. This largely post WWII revolution has driven our understanding of biological and medical processes at an exponential pace owing to successive discoveries of

• chemical structure,
• the basic building blocks of DNA  and proteins,
• nucleotide and protein-protein interactions,
• protein folding, allostericity,
• genomic structure,
• DNA replication,
• nuclear polyribosome interaction, and
• metabolic control.

In addition, the emergence of methods for

• copying,
• removal,
• insertion,
• improvements in structural analysis
• developments in applied mathematics that have transformed the research framework.

Part IIA:

CRACKING THE CODE OF HUMAN LIFE:

Milestones along the Way

A NOVA interview with Francis Collins (NHGRI) (FC), J. Craig Venter (CELERA)(JCV), and Eric Lander (EL).
RK: For the past ten years, scientists all over the world have been painstakingly trying to read the tiny instructions buried inside our DNA. And now, finally, the “Human Genome” has been decoded.
EL: The genome is a storybook that’s been edited for a couple billion years.
The following will address the odd similarity of genes between man and yeast

EL: In the nucleus of your cell the DNA molecule resides that is about 10 angstroms wide curled up, but the amount of curling is limited by the negative charges that repel one another, but there are folds upon folds. If the DNA is stretched the length of the DNA would be thousands of feet.
EL: We have known for 2000 years that your kids look a lot like you. Well it’s because you must pass them instructions that give them the eyes, the hair color, and the nose shape they have. RK: Cracking the code of those minuscule differences in DNA that influence health and illness is what the Human Genome Project is all about. Since 1990, scientists all over the world have been involved in the effort to read all three billion As, Ts, Gs, and Cs of human DNA.  It took 10 years to find the one genetic mistake that causes cystic fibrosis. Another 10 years to find the gene for Huntington’s disease. Fifteen years to find one of the genes that increase the risk for breast cancer. One letter at a time, painfully slowly…     And then came the revolution. In the last ten years the entire process has been computerized. The computations can do a thousand every second and that has made all the difference. EL: This is basically a parts list with a lot of parts. If you take an airplane, a Boeing 777, I think it has like 100,000 parts. If I gave you a parts list for the Boeing 777 in one sense you’d know 100,000 components, screws and wires and rudders and things like that.  But you wouldn’t know how to put it together, or why it flies. We now have a parts list, and that’s not enough to understand why it flies.

The Human Genome (Photo credit: dullhunk)

A Quest For Clarity

Tracy Vence is a senior editor of Genome Technology
Tracy Vence @GenomeTechMag
Projects supported by the US National Institutes of Health will have produced 68,000 total human genomes — around 18,000 of those whole human genomes — through the end of this year, National Human Genome Research Institute estimates indicate. And in his book, The Creative Destruction of Medicine, the Scripps Research Institute’s Eric Topol projects that 1 million human genomes will have been sequenced by 2013 and 5 million by 2014.
Daniel MacArthur, a group leader in Massachusetts General Hospital’s Analytic and Translational Genetics Unit estimates that “From a capacity perspective … millions of genomes are not that far off. If you look at the rate that we’re scaling, we can certainly achieve that.”    The prospect of so many genomes has brought clinical interpretation into focus. But there is an important distinction to be made between the interpretation of an apparently healthy person’s genome and that of an individual who is already affected by a disease.
In an April Science Translational Medicine paper, Johns Hopkins University School of Medicine‘s Nicholas Roberts and his colleagues reported that personal genome sequences for healthy monozygotic twin pairs are not predictive of significant risk for 24 different diseases in those individuals. The researchers concluded that whole-genome sequencing was not likely to be clinically useful. Ambiguities have clouded even the most targeted interpretation efforts.

• Technological challenges,
• meager sample sizes,
• a need for increased,
• fail-safe automation and most important
• a lack of community-wide standards for the task.

have hampered researchers’ attempts to reliably interpret the clinical significance of genomic variation.

How signals from the cell surface affect transcription of genes in the nucleus.

 

James Darnell, Jr., MD, Astor Professor, Rockefeller
After graduation from Washington University School of Medicine he worked with Francois Jacob at the Pasteur Institute in Paris and served as Vice President for Academic Affairs at Rockefeller in 1990-91. He is the coauthor with S.E. Luria of General Virology and the founding author with Harvey Lodish and David Baltimore of Molecular Cell Biology, now in its sixth edition. His book RNA, Life’s Indispensable Molecule was published in July 2011 by Cold Spring Harbor Laboratory Press. A member of the National Academy of Sciences since 1973, recipient of  numerous awards, including the 2003 National Medal of Science, the 2002 Albert Lasker Award.
Using interferon as a model cytokine, the Darnell group discovered that cell transcription was quickly changed by binding of cytokines to the cell surface. The bound interferon led to the tyrosine phosphorylation of latent cytoplasmic proteins now called STATs (signal transducers and activators of transcription) that dimerize by

• reciprocal phosphotyrosine-SH2 interchange.
• accumulate in the nucleus,
• bind DNA and drive transcription.

This pathway has proved to be of wide importance with seven STATs now known in mammals that take part in a wide variety of developmental and homeostatic events in all multicellular animals. Crystallographic analysis defined functional domains in the STATs, and current attention is focused on two areas:

• how the STATs complete their cycle of  activation and inactivation, which requires regulated tyrosine dephosphorylation; and how
• persistent activation of STAT3 that occurs in a high proportion of many human cancers contributes to blocking apoptosis in cancer cells.

Current efforts are devoted to inhibiting STAT3 with modified peptides that can enter cells.

Cell cycle regulation and the cellular response to genotoxic stress

Stephen J Elledge, PhD, Gregor Mendel Professor of Genetics and Medicine, Investigator, Howard Hughes Medical Institute, Harvard Medical School
As a postdoctoral fellow at Stanford working on eukaryotic homologous recombination, he serendipitously found a family of genes known as ribonucleotide reductases. He subsequently showed that

• these genes are activated by DNA damage and
• could serve as tools to help scientists dissect the signaling pathways
• through which cells sense and respond to DNA damage and replication stress.

At Baylor College of Medicine he made a second major breakthrough with the discovery of the cyclin-dependent kinase 2 gene (Cdk2), which

• controls the G1-to-S cell cycle transition,
• an entry checkpoint for the cell proliferation cycle and
• a critical regulatory step in tumorigenesis.

From there, using a novel “two-hybrid” cloning method he developed, Elledge and Wade Harper, PhD, proceeded to

• isolate several members of the Cdk2-inhibitory family.

Their discoveries included the p21 and p57 genes, mutations in the latter (responsible for Beckwith-Wiedemann syndrome), characterized by somatic overgrowth and increased cancer risk. Elledge is also recognized for his work in understanding

• proteome remodeling through ubiquitin-mediated proteolysis.
• they identified F-box proteins that regulate protein degradation in the cell by

1. binding to specific target protein sequences and then
2. marking them with ubiquitin for destruction by the cell’s proteasome machinery.

This breakthrough resulted in

• the elucidation of the cullin ubiquitin ligase family,
• which controls regulated protein stability in eukaryotes.

  

Elledge’s recent research has focused on the cellular mechanisms underlying DNA damage detection and cancer using genetic technologies. In collaboration with Cold Spring Harbor Laboratory researcher Gregory Hannon, PhD, Elledge has generated complete human and mouse short hairpin RNA (shRNA) libraries for genome-wide loss-of-function studies. Their efforts have led to

• the identification of a number of tumor suppressor proteins
• genes upon which cancer cells uniquely depend for survival.

This work led to the development of the “non-oncogene addiction” concept. This is noted as follows:

• proteome remodeling through ubiquitin-mediated proteolysis
• F-box proteins regulate protein degradation in the cell by binding to specific target protein sequences
• and then marking them with ubiquitin for destruction by the cell’s proteasome machinery
• elucidation of the cullin ubiquitin ligase family, which controls regulated protein stability in eukaryotes

Playing the dual roles of inventor and investigator, Elledge developed original techniques to define

• what drives the cell cycle and
• how cells respond to DNA damage.

By using these tools, he and his colleagues have identified multiple genes involved in cell-cycle regulation.

Elledge’s work has earned him many awards, including a 2001 Paul Marks Prize for Cancer Research and a 2003 election to the National Academy of Sciences. In his Inaugural Article (1), published in this issue of PNAS, Elledge and his colleagues describe the function of Fbw7, a protein involved in controlling cell proliferation (see below). Elledge studied the error-prone DNA repair mechanism in E-Coli (Escherichia coli) called SOS mutagenesis for his PhD thesis at MIT. His work identified  and described

• the regulation of a group of enzymes now known as error-prone polymerases,
• the first members of which were the umuCD genes in E. coli.

It was then that he developed a new cloning tool. Elledge invented a technique that allowed him to approach future cloning problems of this type with great rapidity. With the new technique, “you could make large libraries in lambda that behave like plasmids. We called them `phasmid’ vectors, like plasmid and phage together”. The phasmid cloning method was an early cornerstone for molecular biology research.

Elledge began working on homologous recombination in postdoctoral fellowship at Stanford University, an important niche in the field of eukaryotic genetics. Working with the yeast genome, Elledge searched for rec A, a gene that allows DNA to recombine homologously. Although he never located rec A, he discovered a family of genes known as ribonucleotide reductases (RNRs), which are involved in DNA production. Rec A and RNRs share the same last 4 amino acids, which caused an antibody crossreaction in one of Elledge’s experiments. Initially disappointed with the false positives in his hunt for rec A, Elledge was later delighted with his luck. He found that

• RNRs are turned  on by DNA damage, and
• these genes are regulated by the cell cycle.

Prior to leaving Stanford, Elledge attended a talk at the University of California, San Francisco, by Paul Nurse, a leader in cell-cycle research who would later win the 2001 Nobel Prize in medicine. Nurse described his success in isolating the homolog of a key human cell-cycle kinase gene, Cdc2, by using a mutant strain of yeast (8). Although Nurse’s methods were primitive, Elledge was struck by the message he carried: that

• cell-cycle regulation was functionally conserved, and
• many human genes could be isolated by looking for complimentary genes in yeast.

Elledge then took advantage of his past successes in building phasmid vectors to build a versatile human cDNA library that could be expressed in yeast. After setting up a laboratory at Baylor, he introduced this library into yeast, screening for complimentary cell-cycle genes.  He quickly identified the same Cdc2 gene isolated by Nurse. However, Elledge also discovered a related gene known as Cdk2. Elledge subsequently found that

• Cdk2 controlled the G1 to S cell-cycle transition, a step that often goes awry in cancer. These results were published in the EMBO Journal in 1991.

He then continued to use

• RNRs to perform genetic screens to
• identify genes involved in sensing and responding to DNA damage.

He subsequently worked out the

• signal transduction pathways in both yeast and humans that recognize damaged DNA and replication problems.

These “checkpoint” pathways are central to the

• prevention of genomic instability and a key to understanding tumorigenesis.

This contribution is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected on April 29, 2003.

Defective cardiovascular development and elevated cyclin E and Notch proteins in mice lacking the Fbw7 F-box protein.

Tetzlaff MT, Yu W, Li M, Zhang P, Finegold M, Mahon K , Harper JW, Schwartz RJ, and SJ Elledge. PNAS 2004; 101(10): 3338-3345. cgi doi 10.1073.  pnas.0307875101

The mammalian F-box protein Fbw7 and its Caenorhabditis elegans counterpart Sel-10 have been implicated in

• the ubiquitin-mediated turnover of cyclin E
• as well as the Notch Lin-12 family of transcriptional activators. Both unregulated

1. Notch and cyclin E
2. promote tumorigenesis, and
3. inactivate mutations in human

Fbw7 studies suggest that it may be a tumor suppressor. To generate an in vivo system to assess the consequences of such unregulated signaling, we generated mice deficient for Fbw7.  Fbw7-null mice die around 10.5 days post coitus because of a combination of deficiencies in hematopoietic and vascular development and heart chamber mutations. The absence of Fbw7 results in elevated levels of cyclin E, concurrent with inappropriate DNA replication in placental giant trophoblast cells. Moreover, the levels of both Notch 1 and Notch 4 intracellular domains were elevated, leading to stimulation of downstream transcriptional pathways involving Hes1, Herp1, and Herp2. These data suggest essential functions for Fbw7 in controlling cyclin E and Notch signaling pathways in the mouse.

Science as an Adventure

Ubiquitins

Prof. Avram Hershko – Science as an Adventure
Prof. Avram Hershko shared the 2004 Nobel Prize in Chemistry with Aaron Ciechanover and Irwin Rose for “for the discovery of ubiquitin-mediated protein degradation.”

http://www.youtube.com/watch?v=lGJvsmG3mhw&feature=player_detailpage&list=EC8814C902ACB98559

Gene Switches

Nipam Patel is a professor in the Departments of Molecular and Cell Biology and Integrative Biology at UC Berkeley and runs a research laboratory that studies the role, during embryonic development, of homeotic genes (the genetic switches described in this feature). “Ghost in Your Genes” focuses on epigenetic “switches” that turn genes “on” or “off.” But not all switches are epigenetic; some are genetic. That is, other genes within the chromosome turn genes on or off. In an animal’s embryonic stage, these gene switches play a predominant role in laying out the animal’s basic body plan and perform other early functions;

• the epigenome begins to take over during the later stages of embryogenesis.

Beginning as a fertilized single egg that egg becomes many different kinds of cells.  Altogether, multicellular organisms like humans have thousands of differentiated cells. Each is optimized for use in the brain, the liver, the skin, and so on. Remarkably, the DNA inside all these cells is exactly the same. What makes the cells differ from one another is that different genes in that DNA are either turned on or off in each type of cell.

Take a typical cell, such as a red blood cell. Each gene within that cell has a coding region that encodes the information used to make a particular protein. (Hemoglobin shuttles oxygen to the tissues and carbon dioxide back out to the lungs—or gills, if you’re a fish.) But another region of the gene, called “regulatory DNA,” determines whether and when the gene will be expressed, or turned on, in a particular kind of cell. This precise transcribing of genes is handled by proteins known as transcription factors, which bind to the regulatory DNA, thereby generating instructions for the coding region.

One important class of transcription factors is encoded by the so called homeotic, or Hox, genes. Found in all animals, Hox genes act to “regionalize” the body along the embryo’s anterior-to-posterior (head-to-tail) axis. In a fruit fly, for example, Hox genes lay out the various main body segments—the head, thorax, and abdomen. Amazingly, all animals, from fruit flies to mice to people, rely on the same basic Hox-gene complex. Using different-colored antibody stains, we can see exactly where and to what degree Hox genes are expressed. Each Hox gene is expressed in a specific region along the anterior-to-posterior axis of the embryo.

A fly’s body has three main divisions: head, thorax, and abdomen. We’ll focus on the thorax, which itself has three main segments. In a normal adult fly, the second thoracic segment features a pair of wings, while the third thoracic segment has a pair of small, balloon-shaped structures called halteres. A modified second wing, the haltere serves as a flight stabilizer. In order for the pair of wings and the pair of halteres (as well as all other parts of the fly) to develop properly, the fly’s suite of

• Hox genes must be expressed in a precise way and at precise times.

During development, the fly’s two wings grow from a structure in the larva known as the wing imaginal disk. (An imago is an insect in its final, adult state.) The haltere grows from the larval haltere imaginal disk. Remember the Ubx Hox gene? Using staining again, we can detect the gene product of Ubx. This reveals that

• the Ubx gene is naturally “off” in the wing disk—
• and is “on” in the haltere disk.
• Now you’ll see what happens when the Ubx gene—just one of a large number of Hox genes—is turned off in the haltere disk. What if a genetic mutation caused the Ubx gene to be turned off, during the larval stage, in the third thoracic segment, the segment that normally produces the haltere? Instead of a pair of halteres, the fly has a second set of wings. With the switch of that single Hox gene, Ubx, from on to off, the third thoracic segment becomes an additional second thoracic segment and the pair of halteres became a second pair of wings. This illustrates the remarkable ability of transcription factors like Ubx to control patterning as well as cell type during development.

ENCODE

A. Data Suggests “Gene” Redefinition

As part of a huge collaborative effort called ENCODE (Encyclopedia of DNA Elements), a research team led by Cold Spring Harbor Laboratory (CSHL) Professor Thomas Gingeras, PhD, publishes a genome-wide analysis of RNA messages, called transcripts, produced within human cells.
Their analysis—one component of a massive release of research results by ENCODE teams from 32 institutes in 5 countries, with 30 papers appearing in 3 different high-level scientific journals—shows that three-quarters of the genome is capable of being transcribed.  This indicates that nearly all of our genome is dynamic and active.  It stands in marked contrast to consensus views prior to ENCODE’s comprehensive research efforts, which suggested that

• only the small protein-encoding fraction of the genome was transcribed.

The vast amount of data generated with advanced technologies by Gingeras’ group and others in the ENCODE project changes the prevailing understanding of what defines a gene. The current outstanding question concerns

• the nature and range of those functions.  It is thought that these
• “non-coding” RNA transcripts act something like components of a giant, complex switchboard, controlling a network of  many events in the cell by

1. regulating the processes of
2. replication,
3. transcription
4. and translation

– that is, the copying of DNA and the making of proteins is based on information carried by messenger RNAs.  With the understanding that so much of our DNA can be transcribed into RNA comes the realization that there is much less space between what we previously thought of as genes, Gingeras points out.

The full ENCODE Consortium data sets can be freely accessed through

• the ENCODE project portal as well as at the University of California at Santa Cruz genome browser,
• the National Center for Biotechnology Information, and
• the European Bioinformatics Institute.

Topic threads that run through several different papers can be explored via the ENCODE microsite page at http://Nature.com/encode.    Date: September 5, 2012   Source: Cold Spring Harbor Laboratory

1000 Genomes Project Team Reports on Variation Patterns

(from Phase I Data) October 31, 2012 GenomeWeb

In a study appearing online today in Nature, members of the 1000 Genomes Project Consortium presented an integrated haplotype map representing the genomic variation present in more than 1,000 individuals from 14 human populations.  Using data on 1,092 individuals tested by

• low-coverage whole-genome sequencing,
• deep exome sequencing, and/or
• dense genotyping,

the team looked at the nature and extent of the rare and common variation present in the genomes of individuals within these populations. In addition to population-specific differences in common variant profiles, for example, the researchers found distinct rare variant patterns within populations from different parts of the world — information that is expected to be important in interpreting future disease studies. They also encountered a surprising number of the variants that are expected to impact gene function, such as

• non-synonymous changes,
• loss-of-function variants, and, in some cases,
• potentially damaging mutations.

ENCODE was designed to pick up where the Human Genome Project left off.
Although that massive effort revealed the blue­print of human biology, it quickly became clear that the instruction manual for reading the blueprint was sketchy at best. Researchers could identify in its 3 billion letters many of the regions that code for proteins, but they make up little more than 1% of the genome, contained in around 20,000 genes. ENCODE, which started in 2003, is a massive data-collection effort designed to catalogue the

• ‘functional’ DNA sequences,
• learn when and in which cells they are active and
• trace their effects on how the genome is

1. packaged,
2. regulated and
3. read.

After an initial pilot phase, ENCODE scientists started applying their methods to the entire genome in 2007. That phase came to a close with the publication of 30 papers, in Nature, Genome Research and Genome Biology. The consortium has assigned some sort of function to roughly 80% of the genome, including

• more than 70,000 ‘promoter’ regions — the sites, just upstream of genes, where proteins bind to control gene expression —
• and nearly 400,000 ‘enhancer’ regions that regulate expression of  distant genes (see page 57)1. But the job is far from done.

Junk DNA? What Junk DNA?

New data reveals that at least 80% of the human genome encodes elements that have some sort of biological function. [© Gernot Krautberger – Fotolia.com] Far from containing vast amounts of junk DNA between its protein-coding genes, at least 80% of the human genome encodes elements that have some sort of biological function, according to newly released data from the Encyclopedia of DNA Elements (Encode) project, a five-year initiative that aims to delineate all functional elements within human DNA. The massive international project, data from which are published in 30 different papers in Nature, Genome Research, Genome Biology, the Journal of Biological Chemistry, Science, and Cell, has identified four million gene switches, effectively

• regulatory regions in the genome where
• proteins interact with the DNA to control gene expression.

Overall, the Encode data define regulatory switches that are scattered all over the three billion nucleotides of the genome. In fact, the data suggests,

• the regions that lie between gene-coding sequences contain a wealth of previously unrecognized functional elements,Including
• nonprotein-coding RNA transcribed sequences,
• transcription factor binding sites,
• chromatin structural elements, and
• DNA methylation sites.

The combined results suggest that 95% of the genome lies within 8 kb of a DNA-protein interaction, and 99% lies within 1.7 kb of at least one of the biochemical events, the researchers say. Importantly, given the complex three-dimensional nature of DNA, it’s also apparent that

• a regulatory element for one gene may be located quite some ‘linear’ distance from the gene itself.

“The information processing and the intelligence of the genome reside in the regulatory elements,” explains Jim Kent, director of the University of California, Santa Cruz Genome Browser project and head of the Encode Data Coordination Center. “With this project, we probably went from understanding less than 5% to now around 75% of them.”
The ENCODE results also identified SNPs within regulatory regions that are associated with a range of diseases, providing new insights into the roles that

• noncoding DNA plays in disease development.

“As much as nine out of 10 times, disease-linked genetic variants are not in protein-coding regions,” comments Mike Pazin, Encode program director at the National Human Genome Research Institute.  “Far from being junk DNA, this regulatory DNA clearly makes important contributions to human disease.”

Other Related Articles on this Open Access Online Scientific Journal, include the following: 

 

Big Data in Genomic Medicine LHB

http://pharmaceuticalintelligence.com/2012/12/17/big-data-in-genomic-medicine/

BRCA1 a tumour suppressor in breast and ovarian cancer – functions in transcription, ubiquitination and DNA repair S Saha
http://pharmaceuticalintelligence.com/2012/12/04/brca1-a-tumour-suppressor-in-breast-and-ovarian-cancer-functions-in-transcription-ubiquitination-and-dna-repair/

Computational Genomics Center: New Unification of Computational Technologies at Stanford A Lev-Ari
http://pharmaceuticalintelligence.com/2012/12/03/computational-genomics-center-new-unification-of-computational-technologies-at-stanford/

Personalized medicine gearing up to tackle cancer ritu saxena
http://pharmaceuticalintelligence.com/2013/01/07/personalized-medicine-gearing-up-to-tackle-cancer/

Differentiation Therapy – Epigenetics Tackles Solid Tumors sj Williams
http://pharmaceuticalintelligence.com/2013/01/03/differentiation-therapy-epigenetics-tackles-solid-tumors/

Mechanism involved in Breast Cancer Cell Growth: Function in Early Detection & Treatment A Lev-Ari
http://pharmaceuticalintelligence.com/2013/01/17/mechanism-involved-in-breast-cancer-cell-growth-function-in-early-detection-treatment/

The Molecular pathology of Breast Cancer Progression tilde barliya`
http://pharmaceuticalintelligence.com/2013/01/10/the-molecular-pathology-of-breast-cancer-progression/

Paradigm Shift in Human Genomics – Predictive Biomarkers and Personalized Medicine – Part 1 (pharmaceuticalintelligence.com) A Lev-Ari

http://pharmaceuticalintelligence.com/2013/01/13/paradigm-shift-in-human-genomics-predictive-biomarkers-and-personalized-medicine-part-1/

LEADERS in Genome Sequencing of Genetic Mutations for Therapeutic Drug Selection in Cancer Personalized Treatment: Part 2 A Lev-Ari
http://pharmaceuticalintelligence.com/2013/01/13/leaders-in-genome-sequencing-of-genetic-mutations-for-therapeutic-drug-selection-in-cancer-personalized-treatment-part-2/

Personalized Medicine: An Institute Profile – Coriell Institute for Medical Research: Part 3 A Lev-Ari
http://pharmaceuticalintelligence.com/2013/01/13/personalized-medicine-an-institute-profile-coriell-institute-for-medical-research-part-3/

Harnessing Personalized Medicine for Cancer Management, Prospects of Prevention and Cure: Opinions of Cancer Scientific Leaders @ http://pharmaceuticalintelligence.com ALA
http://pharmaceuticalintelligence.com/2013/01/13/7000/Harnessing Personalized Medicine for Cancer Management, Prospects of Prevention and Cure: Opinions of Cancer Scientific Leaders/

GSK for Personalized Medicine using Cancer Drugs needs Alacris systems biology model to determine the in silico effect of the inhibitor in its “virtual clinical trial” A Lev-Ari
http://pharmaceuticalintelligence.com/2012/11/14/gsk-for-personalized-medicine-using-cancer-drugs-needs-alacris-systems-biology-model-to-determine-the-in-silico-effect-of-the-inhibitor-in-its-virtual-clinical-trial/

Recurrent somatic mutations in chromatin-remodeling and ubiquitin ligase complex genes in serous endometrial tumors S Saha
http://pharmaceuticalintelligence.com/2012/11/19/recurrent-somatic-mutations-in-chromatin-remodeling-and-ubiquitin-ligase-complex-genes-in-serous-endometrial-tumors/

Personalized medicine-based cure for cancer might not be far away ritu saxena
http://pharmaceuticalintelligence.com/2012/11/20/personalized-medicine-based-cure-for-cancer-might-not-be-far-away/

Human Variome Project: encyclopedic catalog of sequence variants indexed to the human genome sequence A Lev-Ari
http://pharmaceuticalintelligence.com/2012/11/24/human-variome-project-encyclopedic-catalog-of-sequence-variants-indexed-to-the-human-genome-sequence/

Prostate Cancer Cells: Histone Deacetylase Inhibitors Induce Epithelial-to-Mesenchymal Transition sjwilliams
http://pharmaceuticalintelligence.com/2012/11/30/histone-deacetylase-inhibitors-induce-epithelial-to-mesenchymal-transition-in-prostate-cancer-cells/

Inspiration From Dr. Maureen Cronin’s Achievements in Applying Genomic Sequencing to Cancer Diagnostics A Lev-Ari
http://pharmaceuticalintelligence.com/2013/01/10/inspiration-from-dr-maureen-cronins-achievements-in-applying-genomic-sequencing-to-cancer-diagnostics/

The “Cancer establishments” examined by James Watson, co-discoverer of DNA w/Crick, 4/1953 A Lev-Ari
http://pharmaceuticalintelligence.com/2013/01/09/the-cancer-establishments-examined-by-james-watson-co-discover-of-dna-wcrick-41953/

Directions for genomics in personalized medicine lhb
http://pharmaceuticalintelligence.com/2013/01/27/directions-for-genomics-in-personalized-medicine/

How mobile elements in “Junk” DNA promote cancer. Part 1: Transposon-mediated tumorigenesis. SJwilliams
http://pharmaceuticalintelligence.com/2012/10/31/how-mobile-elements-in-junk-dna-prote-cancer-part1-transposon-mediated-tumorigenesis/

Mitochondria: More than just the “powerhouse of the cell” eritu saxena
http://pharmaceuticalintelligence.com/2012/07/09/mitochondria-more-than-just-the-powerhouse-of-the-cell/

Mitochondrial fission and fusion: potential therapeutic targets? Ritu saxena
http://pharmaceuticalintelligence.com/2012/10/31/mitochondrial-fission-and-fusion-potential-therapeutic-target/

Mitochondrial mutation analysis might be “1-step” away ritu saxena
http://pharmaceuticalintelligence.com/2012/08/14/mitochondrial-mutation-analysis-might-be-1-step-away/

mRNA interference with cancer expression lhb
http://pharmaceuticalintelligence.com/2012/10/26/mrna-interference-with-cancer-expression/

Expanding the Genetic Alphabet and linking the genome to the metabolome LHB
http://pharmaceuticalintelligence.com/2012/09/24/expanding-the-genetic-alphabet-and-linking-the-genome-to-the-metabolome/

Breast Cancer, drug resistance, and biopharmaceutical targets lhb
http://pharmaceuticalintelligence.com/2012/09/18/breast-cancer-drug-resistance-and-biopharmaceutical-targets/

Breast Cancer: Genomic profiling to predict Survival: Combination of Histopathology and Gene Expression Analysis A Lev-Ari
http://pharmaceuticalintelligence.com/2012/12/24/breast-cancer-genomic-profiling-to-predict-survival-combination-of-histopathology-and-gene-expression-analysis/

Gastric Cancer: Whole-genome reconstruction and mutational signatures A Lev-Ari
http://pharmaceuticalintelligence.com/2012/12/24/gastric-cancer-whole-genome-reconstruction-and-mutational-signatures-2/

Ubiquinin-Proteosome pathway, autophagy, the mitochondrion, proteolysis and cell apoptosis lhb
http://pharmaceuticalintelligence.com/2012/10/30/ubiquinin-proteosome-pathway-autophagy-the-mitochondrion-proteolysis-and-cell-apoptosis/

Genomic Analysis: FLUIDIGM Technology in the Life Science and Agricultural Biotechnology A Lev-Ari
http://pharmaceuticalintelligence.com/2012/08/22/genomic-analysis-fluidigm-technology-in-the-life-science-and-agricultural-biotechnology/

Reveals from ENCODE project will invite high synergistic collaborations to discover specific targets A. Sarkar

http://pharmaceuticalintelligence.com/2012/09/30/reveals-from-encode-project-will-lead-to-confusion-or-specific-target/

ENCODE: the key to unlocking the secrets of complex genetic diseases R. Saxena

http://pharmaceuticalintelligence.com/2012/09/26/encode-the-key-to-unlocking-the-secrets-of-complex-genetic-diseases/

Impact of evolutionary selection on functional regions: The imprint of evolutionary selection on ENCODE regulatory elements is manifested between species and within human populations s Saha

http://pharmaceuticalintelligence.com/2012/09/20/impact-of-evolutionary-selection-on-functional-regions-the-imprint-of-evolutionary-selection-on-encode-regulatory-elements-is-manifested-between-species-and-within-human-populations/

ENCODE Findings as Consortium A Lev-Ari

http://pharmaceuticalintelligence.com/2012/09/10/encode-findings-as-consortium/

Genomics Orientations for Personalized Medicine SJH, ALA, LHB

http://pharmaceuticalintelligence.com/biomed-e-books/genomics-orientations-for-personalized-medicine/

2013 Genomics: The Era Beyond the Sequencing of the Human Genome: Francis Collins, Craig Venter, Eric Lander, et al.

http://pharmaceuticalintelligence.com/2013/02/11/2013-genomics-the-era-beyond-the-sequencing-human-genome-francis-collins-craig-venter-eric-lander-et-al/

 Related Articles

• Life Stands on the shoulders of Giants (Viruses) (bytesizebio.net)
• New insights into the human genome by ENCODE project (slideshare.net)
• Unraveling the Human Genome: 6 Molecular Milestones (livescience.com)
• Melanoma Genes Found In “Junk” DNA (medicalnewstoday.com)
• Learning the alphabet of gene control (esciencenews.com)
• BEST OF THE WEB: On viral ‘junk’ DNA, a DNA-enhancing Ketogenic diet, and cometary kicks (sott.net)

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Nation’s Biobanks: Academic institutions, Research institutes and Hospitals – vary by Collections Size, Types of Specimens and Applications: Regulations are Needed

Posted in Bio Instrumentation in Experimental Life Sciences Research, Genome Biology, tagged BioMed Central, Medical research, National Human Genome Research Institute on January 26, 2013| Leave a Comment »

Nation’s Biobanks: Academic institutions, Research institutes and Hospitals – vary by Collections Size, Types of Specimens and Applications: Regulations are Needed

Reporter: Aviva Lev-Ari, PhD, RN

On this Open Access Online Scientific Journal a series of posts address the Gemonic Research Establishment

Personalized Medicine: An Institute Profile – Coriell Institute for Medical Research: Part 3

http://pharmaceuticalintelligence.com/2013/01/13/personalized-medicine-an-institute-profile-coriell-institute-for-medical-research-part-3/

Cancer Diagnostics by Genomic Sequencing: ‘No’ to Sequencing Patient’s DNA, ‘No’ to Sequencing Patient’s Tumor, ‘Yes’ to focus on Gene Mutation Aberration & Analysis of Gene Abnormalities

How to Tailor Cancer Therapy to the particular Genetics of a patient’s Cancer

THIS IS A SERIES OF FOUR POINTS OF VIEW IN SUPPORT OF the Paradigm Shift in Human Genomics

‘No’ to Sequencing Patient’s DNA, ‘No’ to Sequencing Patient’s Tumor, ‘Yes’ to focus on Gene Mutation Aberration & Analysis of Gene Abnormalities

PRESENTED in the following FOUR PARTS. Recommended to be read in its entirety for completeness and arrival to the End Point of Present and Future Frontier of Research in Genomics

Part 1:

Research Paradigm Shift in Human Genomics – Predictive Biomarkers and Personalized Medicine

http://pharmaceuticalintelligence.com/2013/01/13/paradigm-shift-in-human-genomics-predictive-biomarkers-and-personalized-medicine-part-1/

Part 2:

LEADERS in the Competitive Space of Genome Sequencing of Genetic Mutations for Therapeutic Drug Selection in Cancer Personalized Treatment

http://pharmaceuticalintelligence.com/2013/01/13/leaders-in-genome-sequencing-of-genetic-mutations-for-therapeutic-drug-selection-in-cancer-personalized-treatment-part-2/

Part 3:

Personalized Medicine: An Institute Profile – Coriell Institute for Medical Research

http://pharmaceuticalintelligence.com/2013/01/13/personalized-medicine-an-institute-profile-coriell-institute-for-medical-research-part-3/

Part 4:

The Consumer Market for Personal DNA Sequencing

http://pharmaceuticalintelligence.com/2013/01/13/consumer-market-for-personal-dna-sequencing-part-4/

We present the State of Affairs of Nation’s BioBank Industry

Characterizing Biobank Organizations in the U.S.: Results from a National Survey

Gail E Henderson, R Jean Cadigan, Teresa P Edwards, Ian Conlon, Anders G Nelson, James P Evans, Arlene M Davis, Catherine Zimmer and Bryan J Weiner

Genome Medicine 2013, 5:3 doi:10.1186/gm407

Published: 25 January 2013

Abstract (provisional)

Background

Effective translational biomedical research hinges on the operation of “biobanks,” repositories which assemble, store, and manage collections of human specimens and related data. Some are established intentionally to address particular research needs; many, however, have arisen opportunistically, in a variety of settings and with a variety of expectations regarding their functions and longevity. Despite their rising prominence, little is known about how biobanks are organized and function beyond simple classification systems (“government, academia, industry”). Methods: In 2012, we conducted the first national survey of biobanks in the U.S., collecting information on their origins, specimen collections, organizational structures, and market contexts and sustainability. From a list of 636 biobanks assembled through a multi-faceted search strategy, representatives from 456 U.S. biobanks were successfully recruited for a 30 minute online survey (72% response rate). Both closed and open-ended responses were analyzed using descriptive statistics. Results: While nearly two-thirds of biobanks were established within the last decade, 17% have been in existence for over 20 years. Fifty-three percent listed research on a particular disease as the most important reason for establishment; 29% listed research generally. Other reasons included response to a grant or gift, and intent to centralize, integrate, or harmonize existing research structures. Biobank collections are extraordinarily diverse in number and types of specimens and in sources (often multiple) from which they are obtained, including from individuals, clinics/hospitals, public health programs, and research studies. Forty-four percent of biobanks store pediatric specimens, and 36% include post-mortem specimens. Most biobanks are affiliated in one or multiple ways with other entities: 88% are part of at least one or more larger organizations (67% of these are academic, 23% hospitals, 13% research institutes). The majority of biobanks seem to fill a particular “niche” within a larger organization or research area; a minority are concerned about competition for services, although many are worried about underutilization of specimens and long term funding. Conclusions: Effective utilization of biobank collections and effective policies to govern their use will require understanding the immense diversity found in organizational features, including the very different history and primary goals that many biobanks have.

The complete article is available as a provisional PDF. The fully formatted PDF and HTML versions are in production.

http://genomemedicine.com/content/5/1/3/abstract

US Sees Boom in Diverse Range of Biobanks, But Regulations are Lacking

January 25, 2013

By Matt Jones

NEW YORK (GenomeWeb News) – The past decade has seen a dramatic rise in the number and diversity of biobanks in the US, from academic institutions to research institutes and hospitals, and any efforts at creating regulations or governing rules for them will require more than a ‘one-size-fits-all’ approach, according to a new survey.

Funded by the National Human Genome Research Institute and published today in BioMed Central‘s Genome Medicine, the survey found that nearly two-thirds of the nation’s biobanks were launched over the past decade, and they are an “extraordinarily diverse” group, from the size of their collections to the types of specimens they harbor to their fields of study and applications.

The study’s lead author, Gail Henderson, professor and chair of the Department of Social Medicine at the University of North Carolina at Chapel Hill, told GenomeWeb Daily News this week that the “rise of genomics and large-scale gene-environment studies” have led biobanks to “play an increasingly important role in biomedical research.”

“Many articles discuss the ways they are changing the research enterprise – but they have never been systematically studied,” and there is little empirical data or details “on how they are run or on the policies and practices they have to manage their work,” Henderson said.

Although it is difficult to determine the exact number of biobanks operating in the US, by hunting through a range of sources the UNC-based research team was able to create a list of nearly 800 banks. Their online survey generated responses from 456 biobanks, and the team found that 59 percent of these were established after 2001.

Nearly 50 percent of these banks said that the main biomolecule that they store is DNA, 11 percent said RNA, 7 percent said protein, 20 percent said they do not store biomolecules, and 9 percent said ‘other’.

In total, these banks may house from tens of millions to over 50 million samples, the researchers found, and 53 percent of these specimens were stored to support research on particular diseases or disease types. By far, the largest portion of these is being used for cancer research, which is followed by biospecimens stored for neurological diseases like Alzheimer’s and HIV/AIDS.

As for the types of biological specimens these repositories store, 77 percent said they hold serum/plasma, 69 percent store solid tissues, 55 percent store whole blood, and 49 percent house peripheral blood cells or bone marrow. Around 7 percent of the biobanks store pathological body fluids, and around two or three percent have hair and toenail samples.

The rise of genome-focused research after the completion of the sequencing of the human genome a decade ago appears as if it may be a key driver in the biobank explosion. Since then, biobanks have been created to facilitate research generally, rather than to support studies of single diseases or to focus on one area of human biology.

“While there are likely multiple explanations for these results, it is possible that the changing landscape of genomic technology has facilitated a broadening of scope in research pursuits, so that biobanks are not as likely to limit their work to one disease,” the authors stated in the paper.

The expansion and use of new biobanks likely is “all about genomic information,” Henderson told GWDN.

“When we talk about specimens, and look at the numbers and kinds of specimens that people are saving, and the fact that the majority of our banks are cancer banks, and cancer research is fundamentally about DNA,” it is hard not to come to the conclusion that much of this growth is about genomics, she said.

Henderson also said the survey uncovered a “huge diversity” in the types of biobanks in the US.

“They get established for a variety of reasons, some accidental, some intentional, and they vary in size, in when they were established, how formal they are as organizations, what kind of specimens they hold, and where those specimens come from,” she said.

Biobanks also are diverse in their structural affiliations, although nearly 90 percent are embedded within other institutions, and nearly 80 percent of those embedded banks are located within academic institutions. Hospitals house around a quarter of these biobanks, and around 15 percent are part of a research institute.

While they house the samples that are helping to fuel genomics and molecular research, biobanks also can bring up ethical and policy questions that have caught the eye of policy-watchers at NHGRI.

Several issues that have been flagged by the institute’s Ethical, Legal, and Social Implications Research program are stirred up by the expansion of biobanks, such as questions about policies governing data sharing and security, privacy and the identifiability of genomic information, how and when to return research results and incidental findings, how governance structures function at genomic repositories, and informed consent issues caused by the multiple uses for samples by genome researchers.

“Given the diversity in biobank organizational characteristics, it is likely that management and governance policies will have to be tailored to fit the particular context. One size will not fit all,” Henderson said.

For example, she said, the biobanks in the survey showed a range of policies regarding who may access the data, with some enabling only the researchers who run the repository to access it, and others providing nearly universal access with no applicants denied.

There currently are few or no specific guidelines and laws that specifically govern biobanks and biorepositories, she explained.

A list of voluntary best practices for biospecimen resources published by the National Cancer Institute is probably the best available guidelines for biobanks to follow, Henderson explained, but there is not enough specificity in those or other rules or guidelines to apply them to the range of biobanks that are out there now.

“It’s not as is if there are no federal regulations that affect biobanks,” she said. “Certainly, human subject regulations do, and material transfer agreements and commercialization [rules] fall under certain federal regulatory guidance, but none are specific to biobanks.”

In some ways, she said, the biobanking and biorepository boom has created a “Wild West” landscape that will require further study, Henderson said. She and her fellow investigators now plan to begin to tack their research aims toward the ethical and regulatory issues that the proliferation of and multiple new uses for biobanks have brought about.

Matt Jones is a staff reporter for GenomeWeb Daily News. He covers public policy, legislation, and funding issues that affect researchers in the genomics field, as well as the operations of research institutes. E-mail him here or follow GWDN’s headlines at@DailyNewsGW.

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SOURCE: 

http://www.genomeweb.com/us-sees-boom-diverse-range-biobanks-regulations-are-lacking

ACMG Issues Guidelines on Sequencing for Dx, Screening Purposes

March 29, 2012

By a GenomeWeb staff reporter

NEW YORK (GenomeWeb News) – The American College of Medical Genetics last night released a policy statement and guidelines for the use of genomic sequencing for diagnostic genetic screening applications.

The guidelines cover how clinical whole-genome and whole-exome sequencing should be applied, distinguishing between cases where the technology is applied to diagnose a specific condition and when it is used as a screening purpose on asymptomatic individuals. It also asserted that the guidelines are applicable to sequencing for clinical purposes, not research.

In a statement, ACMG said that it recognizes that “genomic sequencing approaches can be of great value in the clinical evaluation of individuals with suspected germ-line genetic disorders,” and there are already “instances in which genomic sequencing approaches can and should contribute to clinical care.”

The organization also distinguished between returning results directly associated with the patient’s phenotype or clinical condition and secondary findings or results generated from screening asymptomatic individuals.

For secondary findings, or returning results to asymptomatic individuals, “it is critical that the standards for what is reportable be high to avoid burdening the health care system and consumers with what could be very large numbers of false positive results,” it wrote. By contrast, “a lower threshold for reporting is appropriate” for returning “diagnostic results that are clearly related to a patient’s phenotype or clinical condition.”

ACMG said whole-genome or whole-exome sequencing should be considered as a diagnostic test for individuals when the phenotype or family history data strongly implicate a genetic etiology, but the disorder is unknown and a specific genetic test is not available; when a patient presents with a defined genetic disorder with a high degree of genetic heterogeneity, making multiple single-gene tests less practical; when a patient has a likely genetic disorder, but available tests have failed at diagnosing the disorder; and when a fetus has a likely genetic disorder, but available tests have failed to diagnose it.

Prior to testing, ACMG recommends patients and families receive genetic counseling and be informed about the expected outcomes, likelihood of finding incidental results, and what types of results will be returned. Labs performing the tests should have clear policies related to disclosing secondary findings, and patients should also have the option of not receiving certain results.

Additionally, patients should be informed if a laboratory’s institutional review board has approved a protocol that allows variants of unknown significance to be used for further research, and patients should consent to this use of their data.

The test itself, and every component of it, including the bioinformatics and interpretation, should be performed in a lab directed by a board-certified individual with broad medical genetics and genomics training, ACMG said.

Regarding what results it recommends returning, ACMG said that test results could include variants known to be associated with the patient’s condition; novel variants whose “genetic, biological, and pathological features” indicate that they are likely involved with the patient’s phenotype; and secondary findings not associated with the patient’s condition, but that are known to be associated with a phenotype.

ACMG has different recommendations for whole-genome or whole-exome sequencing done not for diagnostic purposes, but as a screen of asymptomatic individuals. In these instances, it stresses that the threshold for determining which results should be returned should be “significantly higher” than when the technology is used for a specific diagnostic purpose.

Additionally, it said that individuals should be informed of the “virtual certainty of finding variants of unknown significance.”

While many in the field assume that everyone will eventually have their genomes sequenced at birth, the ACMG’s current position is that sequencing should not be used as a first-tier approach for newborn screening. Whole-genome or whole-exome sequencing should also not be used as a method for prenatal screening, it wrote.

However, whole-genome or whole-exome sequencing could be considered for preconception carrier screening to “focus on genetic variants known to be associated with significant phenotypes in homozygous or hemizygous progeny,” ACMG said.

ACMG acknowledged that the field is rapidly evolving and said that its recommendations would likely be revised over time.

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SOURCE:

http://www.genomeweb.com/sequencing/acmg-issues-guidelines-sequencing-dx-screening-purposes

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