Encyclopedia Of DNA Elements Project Research Articles

Discovering Gene Regulatory Elements Using Coverage-Based Heuristics.

Data mining algorithms and sequencing methods (such as RNA-seq and ChIP-seq) are being combined to discover genomic regulatory motifs that relate to a variety of phenotypes. However, motif discovery algorithms often produce very long lists of putative transcription factor binding sites, hindering the discovery of phenotype-related regulatory elements by making it difficult to select a manageable set of candidate motifs for experimental validation. To address this issue, the authors introduce the motif selection problem and provide coverage-based search heuristics for its solution. Analysis of 203 ChIP-seq experiments from the ENCyclopedia of DNA Elements project shows that our algorithms produce motifs that have high sensitivity and specificity and reveals new insights about the regulatory code of the human genome. The greedy algorithm performs the best, selecting a median of two motifs per ChIP-seq transcription factor group while achieving a median sensitivity of 77 percent.

An Efficient Method for Electroporation of Small Interfering RNAs into ENCODE Project Tier 1 GM12878 and K562 Cell Lines.

The Encyclopedia of DNA Elements (ENCODE) Project aims to identify all functional sequence elements in the human genome sequence by use of high-throughput DNA/cDNA sequencing approaches. To aid the standardization, comparison, and integration of data sets produced from different technologies and platforms, the ENCODE Consortium selected several standard human cell lines to be used by the ENCODE Projects. The Tier 1 ENCODE cell lines include GM12878, K562, and H1 human embryonic stem cell lines. GM12878 is a lymphoblastoid cell line, transformed with the Epstein-Barr virus, that was selected by the International HapMap Project for whole genome and transcriptome sequencing by use of the Illumina platform. K562 is an immortalized myelogenous leukemia cell line. The GM12878 cell line is attractive for the ENCODE Projects, as it offers potential synergy with the International HapMap Project. Despite the vast amount of sequencing data available on the GM12878 cell line through the ENCODE Project, including transcriptome, chromatin immunoprecipitation-sequencing for histone marks, and transcription factors, no small interfering siRNA-mediated knockdown studies have been performed in the GM12878 cell line, as cationic lipid-mediated transfection methods are inefficient for lymphoid cell lines. Here, we present an efficient and reproducible method for transfection of a variety of siRNAs into the GM12878 and K562 cell lines, which subsequently results in targeted protein depletion.

Proteogenomics Dashboard for the Human Proteome Project

dasHPPboard is a novel proteomics-based dashboard that collects and reports the experiments produced by the Spanish Human Proteome Project consortium (SpHPP) and aims to help HPP to map the entire human proteome. We have followed the strategy of analog genomics projects like the Encyclopedia of DNA Elements (ENCODE), which provides a vast amount of data on human cell lines experiments. The dashboard includes results of shotgun and selected reaction monitoring proteomics experiments, post-translational modifications information, as well as proteogenomics studies. We have also processed the transcriptomics data from the ENCODE and Human Body Map (HBM) projects for the identification of specific gene expression patterns in different cell lines and tissues, taking special interest in those genes having little proteomic evidence available (missing proteins). Peptide databases have been built using single nucleotide variants and novel junctions derived from RNA-Seq data that can be used in search engines for sample-specific protein identifications on the same cell lines or tissues. The dasHPPboard has been designed as a tool that can be used to share and visualize a combination of proteomic and transcriptomic data, providing at the same time easy access to resources for proteogenomics analyses. The dasHPPboard can be freely accessed at: http://sphppdashboard.cnb.csic.es.

A novel motif-discovery algorithm to identify co-regulatory motifs in large transcription factor and microRNA co-regulatory networks in human.

Interplays between transcription factors (TFs) and microRNAs (miRNAs) in gene regulation are implicated in various physiological processes. It is thus important to identify biologically meaningful network motifs involving both types of regulators to understand the key co-regulatory mechanisms underlying the cellular identity and function. However, existing motif finders do not scale well for large networks and are not designed specifically for co-regulatory networks. In this study, we propose a novel algorithm CoMoFinder to accurately and efficiently identify composite network motifs in genome-scale co-regulatory networks. We define composite network motifs as network patterns involving at least one TF, one miRNA and one target gene that are statistically significant than expected. Using two published disease-related co-regulatory networks, we show that CoMoFinder outperforms existing methods in both accuracy and robustness. We then applied CoMoFinder to human TF-miRNA co-regulatory network derived from The Encyclopedia of DNA Elements project and identified 44 recurring composite network motifs of size 4. The functional analysis revealed that genes involved in the 44 motifs are enriched for significantly higher number of biological processes or pathways comparing with non-motifs. We further analyzed the identified composite bi-fan motif and showed that gene pairs involved in this motif structure tend to physically interact and are functionally more similar to each other than expected. CoMoFinder is implemented in Java and available for download at http://www.cs.utoronto.ca/∼yueli/como.html.

Using the ENCODE Resource for Functional Annotation of Genetic Variants.

This article illustrates the use of the Encyclopedia of DNA Elements (ENCODE) resource to generate or refine hypotheses from genomic data on disease and other phenotypic traits. First, the goals and history of ENCODE and related epigenomics projects are reviewed. Second, the rationale for ENCODE and the major data types used by ENCODE are briefly described, as are some standard heuristics for their interpretation. Third, the use of the ENCODE resource is examined. Standard use cases for ENCODE, accessing the ENCODE resource, and accessing data from related projects are discussed. Although the focus of this article is the use of ENCODE data, some of the same approaches can be used with data from other projects.

Genetics of juvenile idiopathic arthritis: new tools bring new approaches.

In juvenile idiopathic arthritis (JIA), there are now more than 25 regions represented by single nucleotide polymorphisms that show strong genetic associations. The causal variants and corresponding functions have not yet been defined for the majority of these regions. Here, we review current JIA association findings and the recent progress in the annotation of noncoding portion of the human genome as well as the new technologies necessary to apply this knowledge to JIA association findings. An international collaboration was able to amass sufficient numbers of JIA and control samples to identify significantly robust genetic associations for JIA. The Encyclopedia of DNA Elements project and the National Institutes of Health (NIH) Roadmap Epigenetics Program have now annotated more than 80% of the noncoding genome, important in understanding the impact of risk loci, the majority of which fall outside of protein coding regions. Recent technological advances in high throughput sequencing, chromatin structure determination, transcription factor and enhancer binding site mapping and genome editing will likely provide a basis for understanding JIA genetic risk. Understanding the role of genetic variation in the cause of JIA will provide insight for disease mechanism and may explain disease heterogeneity between JIA subtypes and between autoimmune diseases in general.

Important role of single nucleotide polymorphisms in the study of complex diseases

Single nucleotide polymorphisms (SNPs) have been very widely used in the study of diseases and characters since the completion of the Human Genome Project. SNPs are mostly used as mere genetic markers in studying complex disease. Geneticists began to focus on the direct relationship between SNPs and complex diseases after the "Encyclopedia Of DNA Elements Project". SNPs can pay a regulative role alone, while the collected SNPs in genome can significantly affect the biological characters and disease development.

Conceptual and empirical challenges of ascribing functions to transposable elements.

Media attention and the subsequent scientific backlash engendered by the claim by spokespeople for the Encyclopedia of DNA Elements (ENCODE) project that 80% of the human genome has a biochemical function highlight the need for a clearer understanding of function concepts in biology. This article provides an overview of two major function concepts that have been developed in the philosophy of science--the causal role concept and the selected effects concept--and their relevance to ENCODE. Unlike in some previous critiques, the ENCODE project is not considered problematic here because it employed a causal role definition of function (which is relatively common in genetics) but because of how this concept was misused. In addition, several unique challenges that arise when dealing with transposable elements (TEs) but that were ignored by ENCODE are highlighted. These include issues surrounding TE-level versus organism-level selection, the origins versus the persistence of elements, and accidental versus functional organism-level benefits. Finally, some key questions are presented that should be addressed in any study aiming to ascribe functions to major portions of large eukaryotic genomes, the majorities of which are made up of transposable elements.

Asymmetric evolution of human transcription factor regulatory networks.

Changes in cis or trans regulatory regions are the major driving forces that underlie the evolution of gene expression. Transcription factors (TFs) are the main trans factors involved in transcriptional regulation. Here, we studied the divergence of upstream and downstream regulatory networks between duplicate TFs in light of the Encyclopedia of DNA Elements project. We found that the divergence of upstream regulatory networks was generally smaller than the divergence of downstream regulatory networks. Further analysis showed that the downstream regulatory circuits of duplicate TFs evolve faster in the early stage than the late stage after gene duplication. Upstream regulatory circuits are generally more conserved than downstream regulatory circuits in the early stage and in small TF families. Our results indicate the asymmetric evolution of upstream and downstream regulatory circuits between duplicate TFs, which suggest that after gene duplication, human TF families tend to evolve asymmetrically between coding regions and promoter regions.

Spatially conserved regulatory elements identified within human and mouse Cd247 gene using high-throughput sequencing data from the ENCODE project.

The Cd247 gene encodes for a transmembrane protein important for the expression and assembly of TCR/CD3 complex on the surface of T lymphocytes. Down-regulation of CD247 has functional consequences in systemic autoimmunity and has been shown to be associated with Type 1 Diabetes in NOD mouse. In this study, we have utilized the wealth of high-throughput sequencing data produced during the Encyclopedia of DNA Elements (ENCODE) project to identify spatially conserved regulatory elements within the Cd247 gene from human and mouse. We show the presence of two transcription factor binding sites, supported by histone marks and ChIP-seq data, that specifically have features of an enhancer and a promoter, respectively. We also identified a putative long non-coding RNA from the characteristically long first intron of the Cd247 gene. The long non-coding RNA annotation is supported by manual annotations from the GENCODE project in human and our expression quantification analysis performed in NOD and B6 mice using qRT-PCR. Furthermore, 17 of the 23 SNPs already known to be implicated with T1D were observed within the long non-coding RNA region in mouse. The spatially conserved regulatory elements identified in this study have the potential to enrich our understanding of the role of Cd247 gene in autoimmune diabetes.

Defining functional DNA elements in the human genome.

With the completion of the human genome sequence, attention turned to identifying and annotating its functional DNA elements. As a complement to genetic and comparative genomics approaches, the Encyclopedia of DNA Elements Project was launched to contribute maps of RNA transcripts, transcriptional regulator binding sites, and chromatin states in many cell types. The resulting genome-wide data reveal sites of biochemical activity with high positional resolution and cell type specificity that facilitate studies of gene regulation and interpretation of noncoding variants associated with human disease. However, the biochemically active regions cover a much larger fraction of the genome than do evolutionarily conserved regions, raising the question of whether nonconserved but biochemically active regions are truly functional. Here, we review the strengths and limitations of biochemical, evolutionary, and genetic approaches for defining functional DNA segments, potential sources for the observed differences in estimated genomic coverage, and the biological implications of these discrepancies. We also analyze the relationship between signal intensity, genomic coverage, and evolutionary conservation. Our results reinforce the principle that each approach provides complementary information and that we need to use combinations of all three to elucidate genome function in human biology and disease.

Epigenetics, chromatin and genome organization: recent advances from the ENCODE project

The organization of the genome into functional units, such as enhancers and active or repressed promoters, is associated with distinct patterns of DNA and histone modifications. The Encyclopedia of DNA Elements (ENCODE) project has advanced our understanding of the principles of genome, epigenome and chromatin organization, identifying hundreds of thousands of potential regulatory regions and transcription factor binding sites. Part of the ENCODE consortium, GENCODE, has annotated the human genome with novel transcripts including new noncoding RNAs and pseudogenes, highlighting transcriptional complexity. Many disease variants identified in genome-wide association studies are located within putative enhancer regions defined by the ENCODE project. Understanding the principles of chromatin and epigenome organization will help to identify new disease mechanisms, biomarkers and drug targets, particularly as ongoing epigenome mapping projects generate data for primary human cell types that play important roles in disease.

Finding genomic function for genetic associations in nicotine addiction research: The ENCODE project's role in future pharmacogenomic analysis

Tobacco-related behaviors and the underlying addiction to nicotine are complex tangles of genetic and environmental factors. Efforts to understand the genetic component of these traits have identified sites in the genome (single nucleotide polymorphisms, or SNPs) that might account for some part of the role of genetics in nicotine addiction. Encouragingly, some of these candidate SNPs remain significant in meta-analyses. However, genetic associations cannot be fully assessed, regardless of statistical significance, without an understanding of the functional consequences of the alleles present at these SNPs. The proper experimental test for allelic function can be very difficult to define, representing a roadblock in translating genetic results into treatment to prevent smoking and other nicotine-related behaviors. This roadblock can be navigated in part with a new web-based tool, the Encyclopedia of DNA Elements (ENCODE). ENCODE is a compilation of searchable data on several types of biochemical functions or “marks” across the genome. These data can be queried for the co-localization of a candidate SNP and a biochemical mark. The presence of a SNP within a marked region of DNA enables the generation of better-informed hypotheses to test possible functional roles of alleles at a candidate SNP. Two examples of such co-localizations are presented. One example reveals ENCODE's ability to relate a candidate SNP's function with a gene very far from the physical location of the SNP. The second example reveals a new potential function of the SNP, rs4105144, that has been genetically associated with the number of cigarettes smoked per day. Details for accessing the ENCODE data for this SNP are provided to serve as a tutorial. By serving as a bridge between genetic associations and biochemical function, ENCODE has the power to propel progress in untangling the genetic aspects of nicotine addiction — a major public health concern.

Practical Guidelines for the Comprehensive Analysis of ChIP-seq Data

Mapping the chromosomal locations of transcription factors, nucleosomes, histone modifications, chromatin remodeling enzymes, chaperones, and polymerases is one of the key tasks of modern biology, as evidenced by the Encyclopedia of DNA Elements (ENCODE) Project. To this end, chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is the standard methodology. Mapping such protein-DNA interactions in vivo using ChIP-seq presents multiple challenges not only in sample preparation and sequencing but also for computational analysis. Here, we present step-by-step guidelines for the computational analysis of ChIP-seq data. We address all the major steps in the analysis of ChIP-seq data: sequencing depth selection, quality checking, mapping, data normalization, assessment of reproducibility, peak calling, differential binding analysis, controlling the false discovery rate, peak annotation, visualization, and motif analysis. At each step in our guidelines we discuss some of the software tools most frequently used. We also highlight the challenges and problems associated with each step in ChIP-seq data analysis. We present a concise workflow for the analysis of ChIP-seq data in Figure 1 that complements and expands on the recommendations of the ENCODE and modENCODE projects. Each step in the workflow is described in detail in the following sections.

Computational prediction of transcription factor binding sites based on an integrative approach incorporating genomic and epigenomic features

Transcription factor binding sites (TFBSs) are often predicted by sequence-based methods that use a position weight matrix or consensus sequences. However, the degeneracy of TFBSs makes the prediction of them very challenging. Recent completion of the encyclopedia of DNA elements project provides many useful additional information enabling researchers to tackle these difficulties from a noble point of view. In this paper we developed an integrative TFBS prediction method incorporating genomic as well as epigenomic features, such as DNA methylation, histone modification and chromatin accessibility. We found that (i) an integration of various features facilitates more accurate TFBS prediction, (ii) the proximity range of −500 to 500 nt relative to the transcription start site of a gene resulted in slightly more accurate prediction than the other ranges, and (iii) the proximity of an epigenomic feature contributes more than the other properties of epigenomic or genomic features to the accurate prediction of TFBSs. This study demonstrates that epigenomic features play a critical role in an integrative approach for predicting TFBSs.

Advances in Exercise, Fitness, and Performance Genomics in 2012

A small number of excellent articles on exercise genomics issues were published in 2012. A new PYGM knock-in mouse model will provide opportunities to investigate the exercise intolerance and very low activity level of people with McArdle disease. New reports on variants in ACTN3 and ACE have increased the level of uncertainty regarding their true role in skeletal muscle metabolism and strength traits. The evidence continues to accumulate on the positive effects of regular physical activity on body mass index or adiposity in individuals at risk of obesity as assessed by their FTO genotype or by the number of risk alleles they carry at multiple obesity-susceptibility loci. The serum levels of triglycerides and the risk of hypertriglyceridemia were shown to be influenced by the interactions between a single nucleotide polymorphism (SNP) in the NOS3 gene and physical activity level. Allelic variation at nine SNPs was shown to account for the heritable component of the changes in submaximal exercise heart rate induced by the HERITAGE Family Study exercise program. SNPs at the RBPMS, YWHAQ, and CREB1 loci were found to be particularly strong predictors of the changes in submaximal exercise heart rate. The 2012 review ends with comments on the importance of relying more on experimental data, the urgency of identifying panels of genomic predictors of the response to regular exercise and particularly of adverse responses, and the exciting opportunities offered by recent advances in our understanding of the global architecture of the human genome as reported by the Encyclopedia of DNA Elements project.

The ENCODE project: implications for psychiatric genetics

The ENCyclopedia Of DNA Elements (ENCODE) project is a public research consortium that aims to identify all functional elements of the human genome sequence. The project comprised 1640 data sets, from 147 different cell type and the findings were released in a coordinated set of 34 publications across several journals. The ENCODE publications report that 80.4% of the human genome displays some functionality. These data have important implications for interpreting results from large-scale genetics studies. We reviewed some of the key findings from the ENCODE publications and discuss how they can influence or inform further investigations into the genetic factors contributing to neuropsychiatric disorders.

ENCODE and its first impractical application

ENCODE and its first impractical application

Role of Long Non-coding Ribonucleic Acid in Gastrointestinal Cancer

With the improvement of high-throughput genomic technology such as microarray and next-generation sequencing over the last ten to twenty year, we have come to know that the portion of the genome responsible for protein coding constitutes just approximately 1.5%. The remaining 98.5% of the genome not responsible for protein coding have been regarded as 'junk DNA'. More recently, however, 'Encyclopedia of DNA elements project' revealed that most of the junk DNA were transcribed to RNA regardless of being translated into proteins. In addition, many reports support that a lot of these non-coding RNAs play a role in gene regulation. In fact, there are various functioning short non-coding RNAs including rRNA, tRNA, small interfering RNA, and micro RNA. Mechanisms of these RNAs are relatively well-known. Until recently, however, little is known about long non-coding RNAs which consist of 200 nucleotides or more. In this article, we will review the representative long non-coding RNAs which have been reported to be related to gastrointestinal cancers and to play a certain role in its pathogenesis.

Decoding ENCODE for Cancer

The ENCODE (Encyclopedia of DNA Elements) project has delivered a first systematic look at non-protein-coding stretches of the human genome, analyzing regions of gene transcription, transcription factor association, chromatin structure, and histone modification across 147 cell lines.