Play Video
1
ENCODE: The Encyclopedia of DNA Elements
ENCODE: The Encyclopedia of DNA Elements
::2012/09/05::
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2
Understanding ENCODE
Understanding ENCODE
::2012/09/09::
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3
Encode - The Fog Of Love
Encode - The Fog Of Love
::2013/04/04::
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4
Encode - None
Encode - None
::2011/02/24::
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5
The Story of You: ENCODE and the human genome
The Story of You: ENCODE and the human genome
::2012/09/10::
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6
What the Encode project tells us about the human genome and
What the Encode project tells us about the human genome and 'junk DNA'
::2012/09/06::
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ENCODE: Encyclopedia Of DNA Elements
ENCODE: Encyclopedia Of DNA Elements
::2012/09/06::
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8
Hướng Dẫn Encode Bằng MeGUI [Bài 4/5]
Hướng Dẫn Encode Bằng MeGUI [Bài 4/5]
::2013/07/07::
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Hướng Dẫn Encode Bằng VirtualDubMod [ Bài 4/5 ]
::2012/05/26::
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10
DaVIP & Encode - High Technology (FULL VERSION)
DaVIP & Encode - High Technology (FULL VERSION)
::2010/04/21::
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11
TeamFormers: The Electric Boogaloo: The proper encode
TeamFormers: The Electric Boogaloo: The proper encode
::2012/11/15::
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12
Hướng dẫn encode bằng VirtualDub xuất định dạng H264 cực nét
Hướng dẫn encode bằng VirtualDub xuất định dạng H264 cực nét
::2014/02/28::
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13
Volor Flex & Encode - Altiplano
Volor Flex & Encode - Altiplano
::2013/08/15::
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14
Tutorial No.1 How to encode your new member?
Tutorial No.1 How to encode your new member?
::2013/08/03::
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15
Encode - Magic Points
Encode - Magic Points
::2011/02/24::
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ENCODE Project Update - Elise Feingold
ENCODE Project Update - Elise Feingold
::2014/09/16::
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Volor Flex & Encode - Altiplano ( Official Video )
Volor Flex & Encode - Altiplano ( Official Video )
::2012/12/04::
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ENCODE (Introducción)
ENCODE (Introducción)
::2013/05/06::
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How To ENCODE Like YTS or YIFY TORRENTS!! THE EASY WAY!
How To ENCODE Like YTS or YIFY TORRENTS!! THE EASY WAY!
::2014/05/21::
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Decoding ENCODE: #SciSun Hangout on Air Panel Discussion
Decoding ENCODE: #SciSun Hangout on Air Panel Discussion
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How to Encode Aim Global Products! Tutorial.
How to Encode Aim Global Products! Tutorial.
::2014/02/19::
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22
Hướng dẫn tạo Sub bằng Aegisub và encode MEGUI cho người mới bắt đầu
Hướng dẫn tạo Sub bằng Aegisub và encode MEGUI cho người mới bắt đầu
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23
ENCODE - Enciclopédia dos Elementos do DNA - Prof. Paulo Jubilut
ENCODE - Enciclopédia dos Elementos do DNA - Prof. Paulo Jubilut
::2012/09/06::
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ENCODE/DECODE  & CONVERT DATE/TIME
ENCODE/DECODE & CONVERT DATE/TIME
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How to Encode a Tab (or Function) in a 2D Barcode using the Barcode Generator
How to Encode a Tab (or Function) in a 2D Barcode using the Barcode Generator
::2011/04/18::
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สอนการ Encode แบบ งงๆ โดย arm963 The Anime Fansub
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How to Encode for Multiple Screens
How to Encode for Multiple Screens
::2014/07/30::
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Mind Encode - Plastikman
Mind Encode - Plastikman
::2013/11/08::
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How to Encode with HandBrake
How to Encode with HandBrake
::2014/03/26::
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How to Encode Barcode Data using the IDAutomation Online Font Encoder
How to Encode Barcode Data using the IDAutomation Online Font Encoder
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Plastikman Mind encode
Plastikman Mind encode
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Katharsys - The Scraper (Encode & Davip Remix) [Free Download]
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Dream.Encode.
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ENCODE: Encyclopedia of DNA Elements
ENCODE: Encyclopedia of DNA Elements
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Demystifying encodes and decodes of WebM
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DaVIP & Encode - High Technology
DaVIP & Encode - High Technology
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DaVIP & Encode - Vertigo
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::2013/04/20::
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Jonathan Wells, ENCODE & Intelligent Design
Jonathan Wells, ENCODE & Intelligent Design
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Viewing Ensembl Regulation & ENCODE Using the Matrix
Viewing Ensembl Regulation & ENCODE Using the Matrix
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Cinco respuestas sobre el proyecto ENCODE y el "ADN oscuro"
::2012/09/18::
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Roderic Guigó y ENCODE (Español)
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Video Tip of the Week: ENCODE enables smaller science
Video Tip of the Week: ENCODE enables smaller science
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How to Encode 2D Barcodes in Microsoft Excel using VBA Macros
How to Encode 2D Barcodes in Microsoft Excel using VBA Macros
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What does the sign of the second derivative encode? - Week 4 - Lecture 7 - Mooculus
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How to Encode a Horizontal Tab in a PDF417 in Microsoft Excel
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RESULTS [51 .. 101]
From Wikipedia, the free encyclopedia
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ENCODE
ENCODE logo.png
Content
Description Whole-genome database
Contact
Research center University of California Santa Cruz
Laboratory Center for Biomolecular Science and Engineering
Authors Brian J Raney[1]
Primary citation PMID 21037257
Release date 2010 (2010)
Access
Website encodeproject.org
Tools
Miscellaneous

The Encyclopedia of DNA Elements (ENCODE) is a public research project launched by the US National Human Genome Research Institute (NHGRI) in September 2003.[1][2][3][4][5]

Intended as a follow-up to the Human Genome Project (Genomic Research), the ENCODE project aims to identify all functional elements in the human genome.

The project involves a worldwide consortium of research groups, and data generated from this project can be accessed through public databases.

Motivation and significance[edit]

Humans are estimated to have approximately 20,000 protein-coding genes (collectively known as the exome), which account for only about 1.5% of DNA in the human genome. The primary goal of the ENCODE project is to determine the role of the remaining component of the genome, much of which was traditionally regarded as "junk" (i.e. DNA that is not transcribed).

Approximately 90% of single-nucleotide polymorphisms in the human genome (that have been linked to various diseases by genome-wide association studies) are found outside of protein-coding regions.[6]

The activity and expression of protein-coding genes can be modulated by the regulome - a variety of DNA elements, such as promoter, transcriptional regulatory sequences and regions of chromatin structure and histone modification. It is thought that changes in the regulation of gene activity can disrupt protein production and cell processes and result in disease (ENCODE Project Background). Determining the location of these regulatory elements and how they influence gene transcription could reveal links between variations in the expression of certain genes and the development of disease.[7]

ENCODE is intended as a comprehensive resource to allow the scientific community to better understand how the genome can affect human health, and to "stimulate the development of new therapies to prevent and treat these diseases".[2]

To date, the project has facilitated the identification of novel DNA regulatory elements, providing new insights into the organization and regulation of our genes and genome, and how differences in DNA sequence could influence disease.[6] One main accomplishment described by the Consortium has been that 80% of the human genome is now "associated with at least one biochemical function".[8][9] Much of this functional non-coding DNA is involved in the regulation of the expression of coding genes.[8] Furthermore the expression of each coding gene is controlled by multiple regulatory sites located both near and distant from the gene. These results demonstrate that gene regulation is far more complex than was previously believed.[10]

The ENCODE Project[edit]

ENCODE is implemented in three phases: the pilot phase, the technology development phase and the production phase.

Along the pilot phase, the ENCODE Consortium evaluated strategies for identifying various types of genomic elements. The goal of the pilot phase was to identify a set of procedures that, in combination, could be applied cost-effectively and at high-throughput to accurately and comprehensively characterize large regions of the human genome. The pilot phase had to reveal gaps in the current set of tools for detecting functional sequences, and was also thought to reveal whether some methods used by that time were inefficient or unsuitable for large-scale utilization. Some of these problems had to be addressed in the ENCODE technology development phase (being executed concurrently with the pilot phase), which aimed to devise new laboratory and computational methods that would improve our ability to identify known functional sequences or to discover new functional genomic elements. The results of the first two phases determined the best path forward for analysing the remaining 99% of the human genome in a cost-effective and comprehensive production phase.[2]

The ENCODE Phase I Project: The Pilot Project[edit]

The pilot phase tested and compared existing methods to rigorously analyse a defined portion of the human genome sequence. It was organized as an open consortium and brought together investigators with diverse backgrounds and expertise to evaluate the relative merits of each of a diverse set of techniques, technologies and strategies. The concurrent technology development phase of the project aimed to develop new high throughput methods to identify functional elements. The goal of these efforts was to identify a suite of approaches that would allow the comprehensive identification of all the functional elements in the human genome. Through the ENCODE pilot project, National Human Genome Research Institute (NHGRI) assessed the abilities of different approaches to be scaled up for an effort to analyse the entire human genome and to find gaps in the ability to identify functional elements in genomic sequence.

The ENCODE pilot project process involved close interactions between computational and experimental scientists to evaluate a number of methods for annotating the human genome. A set of regions representing approximately 1% (30 Mb) of the human genome was selected as the target for the pilot project and was analyzed by all ENCODE pilot project investigators. All data generated by ENCODE participants on these regions was rapidly released into public databases.[4][11]

Target Selection[edit]

For use in the ENCODE pilot project, defined regions of the human genome - corresponding to 30Mb, roughly 1% of the total human genome - were selected. These regions served as the foundation on which to test and evaluate the effectiveness and efficiency of a diverse set of methods and technologies for finding various functional elements in human DNA.

Prior to embarking upon the target selection, it was decided that 50% of the 30Mb of sequence would be selected manually while the remaining sequence would be selected randomly. The two main criteria for manually selected regions were: 1) the presence of well-studied genes or other known sequence elements, and 2) the existence of a substantial amount of comparative sequence data. A total of 14.82Mb of sequence was manually selected using this approach, consisting of 14 targets that range in size from 500kb to 2Mb.

The remaining 50% of the 30Mb of sequence were composed of thirty, 500kb regions selected according to a stratified random-sampling strategy based on gene density and level of non-exonic conservation. The decision to use these particular criteria was made in order to ensure a good sampling of genomic regions varying widely in their content of genes and other functional elements. The human genome was divided into three parts - top 20%, middle 30%, and bottom 50% - along each of two axes: 1) gene density and 2) level of non-exonic conservation with respect to the orthologous mouse genomic sequence (see below), for a total of nine strata. From each stratum, three random regions were chosen for the pilot project. For those strata underrepresented by the manual picks, a fourth region was chosen, resulting in a total of 30 regions. For all strata, a "backup" region was designated for use in the event of unforeseen technical problems.

In greater detail, the stratification criteria were as follows:

  • Gene density: The gene density score of a region was the percentage of bases covered either by genes in the Ensembl database, or by human mRNA best BLAT (BLAST-like alignment tool) alignments in the UCSC Genome Browser database.
  • Non-exonic conservation: The region was divided into non-overlapping subwindows of 125 bases. Subwindows that showed less than 75% base alignment with mouse sequence were discarded. For the remaining subwindows, the percentage with at least 80% base identity to mouse, and which did not correspond to Ensembl genes, GenBank mRNA BLASTZ alignments, Fgenesh++ gene predictions, TwinScan gene predictions, spliced EST alignments, or repeated sequences (DNA)], was used as the non-exonic conservation score.

The above scores were computed within non-overlapping 500 kb windows of finished sequence across the genome, and used to assign each window to a stratum.[12]

Pilot Phase Results[edit]

The pilot phase was successfully finished and the results were published in June 2007 in Nature[4] and in a special issue of Genome Research;[13] the results published in the first paper mentioned advanced the collective knowledge about human genome function in several major areas, included in the following highlights:[4]

  • The human genome is pervasively transcribed, such that the majority of its bases are associated with at least one primary transcript and many transcripts link distal regions to established protein-coding loci.
  • Many novel non-protein-coding transcripts have been identified, with many of these overlapping protein-coding loci and others located in regions of the genome previously thought to be transcriptionally silent.
  • Numerous previously unrecognized transcription start sites have been identified, many of which show chromatin structure and sequence-specific protein-binding properties similar to well-understood promoters.
  • Regulatory sequences that surround transcription start sites are symmetrically distributed, with no bias towards upstream regions.
  • chromatin accessibility and histone modification patterns are highly predictive of both the presence and activity of transcription start sites.
  • Distal DNaseI hypersensitive sites have characteristic histone modification patterns that reliably distinguish them from promoters; some of these distal sites show marks consistent with insulator function.
  • DNA replication timing is correlated with chromatin structure.
  • A total of 5% of the bases in the genome can be confidently identified as being under evolutionary constraint in mammals; for approximately 60% of these constrained bases, there is evidence of function on the basis of the results of the experimental assays performed to date.
  • Although there is general overlap between genomic regions identified as functional by experimental assays and those under evolutionary constraint, not all bases within these experimentally defined regions show evidence of constraint.
  • Different functional elements vary greatly in their sequence variability across the human population and in their likelihood of residing within a structurally variable region of the genome.
  • Surprisingly, many functional elements are seemingly unconstrained across mammalian evolution. This suggests the possibility of a large pool of neutral elements that are biochemically active but provide no specific benefit to the organism. This pool may serve as a 'warehouse' for natural selection, potentially acting as the source of lineage-specific elements and functionally conserved but non-orthologous elements between species.

The ENCODE Phase II Project: The Production Phase Project[edit]

Image of ENCODE data in the UCSC Genome Browser. This shows several tracks containing information on gene regulation. The gene on the left (ATP2B4) is transcribed in a wide variety of cells. The gene on the right is only transcribed in a few types of cells, including embryonic stem cells.

In September 2007, National Human Genome Research Institute (NHGRI) began funding the production phase of the ENCODE project. In this phase, the goal was to analyze the entire genome and to conduct "additional pilot-scale studies".[14]

As in the pilot project, the production effort is organized as an open consortium. In October 2007, NHGRI awarded grants totaling more than $80 million over four years.[15] The production phase also includes a Data Coordination Center, a Data Analysis Center, and a Technology Development Effort.[16] At that time the project evolved into a truly global enterprise, involving 440 scientists from 32 laboratories worldwide. Once pilot phase was completed, the project “scaled up” in 2007, profiting immensely from new-generation sequencing machines. And the data was, indeed, big; researchers generated around 15 terabytes of raw data.

By 2010, over 1,000 genome-wide data sets had been produced by the ENCODE project. Taken together, these data sets show which regions are transcribed into RNA, which regions are likely to control the genes that are used in a particular type of cell, and which regions are associated with a wide variety of proteins. The primary assays used in ENCODE are ChIP-seq, DNase I Hypersensitivity, RNA-seq, and assays of DNA methylation.

Production Phase Results[edit]

In September 2012, the project released a much more extensive set of results, in 30 papers published simultaneously in several journals, including six in Nature, six in Genome Biology and a special issue with 18 publications of Genome Research.[17]

The authors described the production and the initial analysis of 1,640 data sets designed to annotate functional elements in the entire human genome, integrating results from diverse experiments within cell types, related experiments involving 147 different cell types, and all ENCODE data with other resources, such as candidate regions from genome-wide association studies (GWAS) and evolutionary constrained regions. Together, these efforts revealed important features about the organization and function of the human genome, which were summarized in an overview paper as follows:[8]

  1. The vast majority (80.4%) of the human genome participates in at least one biochemical RNA and/or chromatin associated event in at least one cell type. Much of the genome lies close to a regulatory event: 95% of the genome lies within 8kb of a DNA-protein interaction (as assayed by bound ChIP-seq motifs or DNaseI footprints), and 99% is within 1.7kb of at least one of the biochemical events measured by ENCODE.
  2. Primate-specific elements as well as elements without detectable mammalian constraint show, in aggregate, evidence of negative selection; thus some of them are expected to be functional.
  3. Classifying the genome into seven chromatin states suggests an initial set of 399,124 regions with enhancer-like features and 70,292 regions with promoters-like features, as well hundreds of thousands of quiescent regions. High-resolution analyses further subdivide the genome into thousands of narrow states with distinct functional properties.
  4. It is possible to quantitatively correlate RNA sequence production and processing with both chromatin marks and transcription factor (TF) binding at promoters, indicating that promoter functionality can explain the majority of RNA expression variation.
  5. Many non-coding variants in individual genome sequences lie in ENCODE- annotated functional regions; this number is at least as large as those that lie in protein coding genes.
  6. SNPs associated with disease by GWAS are enriched within non-coding functional elements, with a majority residing in or near ENCODE-defined regions that are outside of protein coding genes. In many cases, the disease phenotypes can be associated with a specific cell type or TF.

The most striking finding was that the fraction of human DNA that is biologically active is considerably higher than even the most optimistic previous estimates. In an overview paper, the ENCODE Consortium reported that its members were able to assign biochemical functions to over 80% of the genome.[8] Much of this was found to be involved in controlling the expression levels of coding DNA, which makes up less than 1% of the genome.

The most important new elements of the "encyclopedia" include:

  • A comprehensive map of DNase 1 hypersensitive sites, which are markers for regulatory DNA that is typically located adjacent to genes and allows chemical factors to influence their expression. The map identified nearly 3 million sites of this type, including nearly all that were previously known and many that are novel.[18]
  • A lexicon of short DNA sequences that form recognition motifs for DNA-binding proteins. Approximately 8.4 million such sequences were found, comprising a fraction of the total DNA roughly twice the size of the exome. Thousands of transcription promoters were found to make use of a single stereotyped 50-base-pair footprint.[19]
  • A preliminary sketch of the architecture of the network of human transcription factors, that is, factors that bind to DNA in order to promote or inhibit the expression of genes. The network was found to be quite complex, with factors that operate at different levels as well as numerous feedback loops of various types.[20]
  • A measurement of the fraction of the human genome that is capable of being transcribed into RNA. This fraction was estimated to add up to more than 75% of the total DNA, a much higher value than previous estimates. The project also began to characterize the types of RNA transcripts that are generated at various locations.[21]

Data Management and Analysis[edit]

Capturing, storing, integrating, and displaying the diverse data generated is challenging. The ENCODE Data Coordination Center (DCC) organizes and displays the data generated by the labs in the consortium, and ensures that the data meets specific quality standards when it is released to the public. Before a lab submits any data, the DCC and the lab draft a data agreement that defines the experimental parameters and associated metadata. The DCC validates incoming data to ensure consistency with the agreement. It then loads the data onto a test server for preliminary inspection, and coordinates with the labs to organize the data into a consistent set of tracks. When the tracks are ready, the DCC Quality Assurance team performs a series of integrity checks, verifies that the data is presented in a manner consistent with other browser data, and perhaps most importantly, verifies that the metadata and accompanying descriptive text are presented in a way that is useful to our users. The data is released on the public UCSC Genome Browser website only after all of these checks have been satisfied. In parallel, data is analyzed by the ENCODE Data Analysis Center, a consortium of analysis teams from the various production labs plus other researchers. These teams develop standardized protocols to analyze data from novel assays, determine best practices, and produce a consistent set of analytic methods such as standardized peak callers and signal generation from alignment pile-ups.[22]

The National Human Genome Research Institute (NHGRI) has identified ENCODE as a "community resource project". This important concept was defined at an international meeting held in Ft. Lauderdale in January 2003 as a research project specifically devised and implemented to create a set of data, reagents, or other material whose primary utility will be as a resource for the broad scientific community. Accordingly, the ENCODE data release policy stipulates that data, once verified, will be deposited into public databases and made available for all to use without restriction.[22]

Future Perspectives[edit]

To date, ENCODE has sampled 119 of 1,800 known TFs and general components of the transcriptional machinery on a limited number of cell types and 13 of more than 60 currently known histone or DNA modifications across 147 cell types. DNaseI, FAIRE and extensive RNA assays across subcellular fractionations have been undertaken on many cell types, but overall these data reflect a minor fraction of the potential functional information encoded in the human genome. An important future goal will be to enlarge this dataset to additional factors, modifications and cell types, complementing the other related projects in this area (e.g., Roadmap Epigenomics Project and International Human Epigenome (HEP) Consortium). These projects will constitute foundational resources for human genomics, allowing a deeper interpretation of the organization of gene and regulatory information and the mechanisms of regulation and thereby provide important insights in human health and disease.[8]

The ENCODE Consortium[edit]

The ENCODE Consortium is composed primarily of scientists who were funded by US National Human Genome Research Institute (NHGRI). Other participants contributing to the project are brought up into the Consortium or Analysis Working Group.

The pilot phase consisted of eight research groups and twelve groups participating in the ENCODE Technology Development Phase (ENCODE Pilot Project: Participants and Projects). After 2007, the number of participants grew up to 440 scientists from 32 laboratories worldwide as the pilot phase was officially over. At the moment the consortium consists of different centers which perform different tasks (ENCODE Participants and Projects):

  1. ENCODE Production Centers
  2. ENCODE Data Coordination Center
  3. ENCODE Data Analysis Center
  4. ENCODE Computational Analysis Awards
  5. ENCODE Technology Development Effort

Controversy[edit]

Although the consortium claims they are far from finished with the ENCODE project, many reactions to the slew of papers, their web and iPad app presentations and the news coverage that accompanied the release were favorable. The Nature editors and ENCODE authors "... collaborated over many months to make the biggest splash possible and capture the attention of not only the research community but also of the public at large."[23] The ENCODE project's claim that 80% of the human genome has biochemical function[8] was rapidly picked up by the popular press who described the results of the project as leading to the death of junk DNA.[24][25] However the conclusion that most of the genome is functional was severely criticized on the grounds that ENCODE project used a far too liberal definition of functional, namely anything that is transcribed must be functional. The criticism goes to both press officers and scientists for establishing that every virus, transposon, and dead gene in the human genome is essential for our collective health and survival. This conclusion was arrived at despite the widely accepted view that many DNA elements such as pseudogenes that are transcribed are nevertheless non-functional. Furthermore the ENCODE project has emphasized sensitivity over specificity leading to the detection of many false positives.[26][27][28] Somewhat arbitrary choice of cell lines and transcription factors as well as lack of appropriate control experiments were additional major criticisms of ENCODE as random DNA mimics ENCODE-like 'functional' behavior.[29]

The project has also been criticized for its high cost (~$400 million in total) and favoring big science which takes money away from highly productive investigator-initiated research.[30] The pilot ENCODE project cost an estimated $55 million; the scale-up was about $130 million and the US National Human Genome Research Institute NHGRI could award up to $123 million for the next phase. Some researchers argue that a solid return on that investment has yet to be seen. There have been attempts to scour the literature for the papers in which ENCODE plays a significant part and since 2012 there have been 300 papers, 110 of which come from labs without ENCODE funding. An additional problem is that ENCODE is not a unique name dedicated to the ENCODE project exclusively, so the word ‘encode’ comes up in many genetics and genomics literature.[6]

Another major critique is that the results do not justify the amount of time spent on the project and that the project itself is essentially unfinishable. Although often compared to Human Genome Project (HGP) and even termed as the HGP next step, the HGP had a clear endpoint which ENCODE currently lacks.

The authors seem to sympathize with the scientific concerns and at the same time try to justify their efforts by giving interviews and explaining ENCODE details not just to the scientific public, but also to mass media. They also claim that it took more than half a century from the realization that DNA is the hereditary material of life to the human genome sequence, so that their plan for the next century would be to really understand the sequence itself.[6]

modENCODE project[edit]

The Model Organism ENCyclopedia Of DNA Elements (modENCODE) project is a continuation of the original ENCODE project targeting the identification of functional elements in selected model organism genomes, specifically, Drosophila melanogaster and Caenorhabditis elegans.[31] The extension to model organisms permits biological validation of the computational and experimental findings of the ENCODE project, something that is difficult or impossible to do in humans.[31]

Funding for the modENCODE project was announced by the National Institutes of Health (NIH) in 2007 and included several different research institutions in the US.[32][33]

In late 2010, the modENCODE consortium unveiled its first set of results with publications on annotation and integrative analysis of the worm and fly genomes in Science.[34][35] Data from these publications is available from the modENCODE web site.[36]

At the moment, modENCODE is run as a Research Network and the consortium is formed by 11 primary projects, divided between worm and fly. The projects spans the following:

  • Gene structure
  • mRNA and ncRNA expression profiling
  • Transcription factor binding sites
  • Histone modifications and replacement
  • Chromatin structure
  • DNA replication initiation and timing
  • Copy number variation.[37]

FactorBook[edit]

The analysis of transcription factor binding data generated by the ENCODE project is currently available in the web-accessible repository FactorBook.[38] Essentially, Factorbook.org is a Wiki-based database for transcription factor-binding data generated by the ENCODE consortium. In the first release, Factorbook contains:

  • 457 ChIP-seq datasets on 119 TFs in a number of human cell lines
  • The average profiles of histone modifications and nucleosome positioning around the TF-binding regions
  • Sequence motifs enriched in the regions and the distance and orientation preferences between motif sites.[39]

See also[edit]

References[edit]

  1. ^ a b Raney BJ, Cline MS, Rosenbloom KR, Dreszer TR, Learned K, Barber GP, Meyer LR, Sloan CA, Malladi VS, Roskin KM, Suh BB, Hinrichs AS, Clawson H, Zweig AS, Kirkup V, Fujita PA, Rhead B, Smith KE, Pohl A, Kuhn RM, Karolchik D, Haussler D, Kent, WJ (January 2011). "ENCODE whole-genome data in the UCSC genome browser (2011 update)". Nucleic Acids Res. 39 (Database issue): D871–5. doi:10.1093/nar/gkq1017. PMC 3013645. PMID 21037257. 
  2. ^ a b c The ENCODE Project Consortium (2004). "The ENCODE (ENCyclopedia Of DNA Elements) Project". Science. 
  3. ^ ENCODE Project Consortium (2011). Becker PB, ed. "A User's Guide to the Encyclopedia of DNA Elements (ENCODE)". PLoS Biology 9 (4): e1001046. doi:10.1371/journal.pbio.1001046. PMC 3079585. PMID 21526222.  edit
  4. ^ a b c d ENCODE Project Consortium, Birney E, Stamatoyannopoulos JA, Dutta A, Guigó R, Gingeras TR, Margulies EH, Weng Z, Snyder M, Dermitzakis ET, et al. (2007). "Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project". Nature 447 (7146): 799–816. Bibcode:2007Natur.447..799B. doi:10.1038/nature05874. PMC 2212820. PMID 17571346.  edit
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