A comparative encyclopedia of DNA elements in the mouse genome

The laboratory mouse shares the majority of its protein-coding genes with humans, making it the premier model organism in biomedical research, yet the two mammals differ in significant ways. To gain greater insights into both shared and species-specific transcriptional and cellular regulatory programs in the mouse, the Mouse ENCODE Consortium has mapped transcription, DNase I hypersensitivity, transcription factor binding, chromatin modifications and replication domains throughout the mouse genome in diverse cell and tissue types. By comparing with the human genome, we not only confirm substantial conservation in the newly annotated potential functional sequences, but also find a large degree of divergence of sequences involved in transcriptional regulation, chromatin state and higher order chromatin organization. Our results illuminate the wide range of evolutionary forces acting on genes and their regulatory regions, and provide a general resource for research into mammalian biology and mechanisms of human diseases

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

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

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

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

Genetic regulatory signatures underlying islet gene expression and type 2 diabetes

The majority of genetic variants associated with type 2 diabetes (T2D) are located outside of genes in noncoding regions that may regulate gene expression in disease-relevant tissues, like pancreatic islets. Here, we present the largest integrated analysis to date of high-resolution, high-throughput human islet molecular profiling data to characterize the genome (DNA), epigenome (DNA packaging), and transcriptome (gene expression). We find that T2D genetic variants are enriched in regions of the genome where transcription Regulatory Factor X (RFX) is predicted to bind in an islet-specific manner. Genetic variants that increase T2D risk are predicted to disrupt RFX binding, providing a molecular mechanism to explain how the genome can influence the epigenome, modulating gene expression and ultimately T2D risk

Transcription Factor Occupancy in Differentiating Skeletal Muscle

With recent advances in high-throughput sequencing, mapping of genome-wide transcription factor occupancy has become feasible. To advance the understanding of skeletal muscle differentiation specifically and transcriptional regulation in general, I determined the genome-wide occupancy map for myogenin in differentiating C2C12 myocyte cells. I then analyzed the myogenin map for underlying sequence content and the association between occupied elements and expression trajectories of adjacent genes. Having determined that myogenin primarily associates with expressed genes, I performed a similar analysis on occupancy maps of other transcription factors active during skeletal muscle differentiation, including an extensive analysis of co-occupancy. This analysis provided strong motif evidence for protein-protein interactions as the primary driving force in the formation of Myogenin / Mef2 and MyoD / AP-1 complexes at jointly-occupied sites. Finally, factor occupancy analysis was extended to include bHLH transcription factors in tissues other than skeletal muscle. The cross-tissue analysis led to the emergence of a motif structure used by bHLH TFs to encode either tissue-specific or "general" (public) access in a variety of lineages

An Examination of Codewords with Optimal Merit Factor

We examine the codewords with best possible merit factor (minimum sum of squares of periodic autocorrelations) for a variety of lengths. Many di#erent approaches were tried in an attempt to find construction methods for such codewords, or for codewords with good but non-optimal merit factors. # The authors thank Hew lett-Packard for their generous support during the summer of 1998, and Dr. James Davis, University of Richmond, for his extensive support and assistance. 1 Introduction 1 1.1 Periodic Autocorrelations and Merit Factors for Binary Sequences Our general objective this summer was to find construction methods for binary codewords with low autocorrelations. Specifically, we wanted to choose the codewords with the best merit factors for a variety of sequence lengths without resorting to exhaustive search. Initially, we thought that previous work [Bernasconi] would allow for an interesting avenue for investigation, but after acquiring a copy of the paper we decided that furth..

Genetic regulatory signatures underlying islet gene expression and type 2 diabetes.

Genome-wide association studies (GWAS) have identified \u3e100 independent SNPs that modulate the risk of type 2 diabetes (T2D) and related traits. However, the pathogenic mechanisms of most of these SNPs remain elusive. Here, we examined genomic, epigenomic, and transcriptomic profiles in human pancreatic islets to understand the links between genetic variation, chromatin landscape, and gene expression in the context of T2D. We first integrated genome and transcriptome variation across 112 islet samples to produce dense cis-expression quantitative trait loci (cis-eQTL) maps. Additional integration with chromatin-state maps for islets and other diverse tissue types revealed that cis-eQTLs for islet-specific genes are specifically and significantly enriched in islet stretch enhancers. High-resolution chromatin accessibility profiling using assay for transposase-accessible chromatin sequencing (ATAC-seq) in two islet samples enabled us to identify specific transcription factor (TF) footprints embedded in active regulatory elements, which are highly enriched for islet cis-eQTL. Aggregate allelic bias signatures in TF footprints enabled us de novo to reconstruct TF binding affinities genetically, which support the high-quality nature of the TF footprint predictions. Interestingly, we found that T2D GWAS loci were strikingly and specifically enriched in islet Regulatory Factor X (RFX) footprints. Remarkably, within and across independent loci, T2D risk alleles that overlap with RFX footprints uniformly disrupt the RFX motifs at high-information content positions. Together, these results suggest that common regulatory variations have shaped islet TF footprints and the transcriptome and that a confluent RFX regulatory grammar plays a significant role in the genetic component of T2D predisposition. Proc Natl Acad Sci U S A 2017 Feb 28; 114(9):2301-2306

A Comparative Encyclopedia of DNA Elements in the Mouse Genome

Summary As the premier model organism in biomedical research, the laboratory mouse shares the majority of protein-coding genes with humans, yet the two mammals differ in significant ways. To gain greater insights into both shared and species-specific transcriptional and cellular regulatory programs in the mouse, the Mouse ENCODE Consortium has mapped transcription, DNase I hypersensitivity, transcription factor binding, chromatin modifications, and replication domains throughout the mouse genome in diverse cell and tissue types. By comparing with the human genome, we not only confirm substantial conservation in the newly annotated potential functional sequences, but also find a large degree of divergence of other sequences involved in transcriptional regulation, chromatin state and higher order chromatin organization. Our results illuminate the wide range of evolutionary forces acting on genes and their regulatory regions, and provide a general resource for research into mammalian biology and mechanisms of human diseases