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.

Whole-genome sequencing identifies a recurrent functional synonymous mutation in melanoma.

Synonymous mutations, which do not alter the protein sequence, have been shown to affect protein function [Sauna ZE, Kimchi-Sarfaty C (2011) Nat Rev Genet 12(10):683-691]. However, synonymous mutations are rarely investigated in the cancer genomics field. We used whole-genome and -exome sequencing to identify somatic mutations in 29 melanoma samples. Validation of one synonymous somatic mutation in BCL2L12 in 285 samples identified 12 cases that harbored the recurrent F17F mutation. This mutation led to increased BCL2L12 mRNA and protein levels because of differential targeting of WT and mutant BCL2L12 by hsa-miR-671-5p. Protein made from mutant BCL2L12 transcript bound p53, inhibited UV-induced apoptosis more efficiently than WT BCL2L12, and reduced endogenous p53 target gene transcription. This report shows selection of a recurrent somatic synonymous mutation in cancer. Our data indicate that silent alterations have a role to play in human cancer, emphasizing the importance of their investigation in future cancer genome studies.

Prediction-based approaches to characterize bidirectional promoters in the mammalian genome.

BACKGROUND: Machine learning approaches are emerging as a way to discriminate various classes of functional elements. Previous attempts to create Regulatory Potential (RP) scores to discriminate functional DNA from nonfunctional DNA included using Markov models trained to identify sequences from promoters and enhancers from ancestral repeats. We proposed that knowledge gleaned from those methods could be further refined using a multiple class predictor to separate classes of promoter elements from enhancers or nonfunctional DNA. RESULTS: We extended our previous work, which identified over 5,000 candidate bidirectional promoters in the human genome, to map the orthologous promoter regions in the mouse genome. Our algorithm measured the robustness of evidence provided by the spliced EST annotations and incorporated evidence from annotations of UCSC Known Genes and GenBank mRNA. In preparation for de novo prediction of this promoter type, we examined characteristic features of the dataset as a whole. For instance, bidirectional promoters score very highly among all functional elements for Regulatory Potential Scores. This result was unexpected due to the limited sequence conservation found in these noncoding regions. We demonstrate that bidirectional promoters can be classified apart from other genomic features including non-bidirectional promoters, i.e. those promoters having no nearby upstream genes. Furthermore bidirectional promoters consistently score at the level of very highly conserved functional elements in the genome- developmental enhancers. The high scores are due to sequence-based characteristics within the promoters, not the surrounding exons. These results indicate that high-scoring RP regions can be deconvoluted into various functional classes of genomic elements. Using a multiple class predictor we are able to discriminate bidirectional promoters from enhancers, non-bidirectional promoters, and non-promoter regions on the basis of RP scores and CpG islands. CONCLUSIONS: We examine orthology at bidirectional promoters, use discriminatory machine learning approaches to differentiate multiple types of promoters from other functional and nonfunctional features in the genome and begin the process of deconvoluting classes of functional regions that score well with RP scores. These types of approaches precede supervised learning techniques to discover unannotated promoter regions.

Diversity of core promoter elements comprising human bidirectional promoters.

BACKGROUND: Bidirectional promoters lie between adjacent genes, which are transcribed from opposite strands of DNA. The functional mechanisms underlying the activation of bidirectional promoters are currently uncharacterised. To define the core promoter elements of bidirectional promoters in human, we mapped motifs for TATA, INR, BRE, DPE, INR, as well as CpG-islands. RESULTS: We found a consistently high correspondence between C+G content, CpG-island presence and an average expression level increasing the median level for all genes in bidirectional promoters. These CpG-rich promoters showed discrete initiation patterns rather than broad regions of transcription initiation, as are typically seen for CpG-island promoters. CpG-islands encompass both TSSs within bidirectional promoters, providing an explanation for the symmetrical co-expression patterns of many of these genes. In contrast, TATA motifs appear to be asymmetrically positioned at one TSS or the other. CONCLUSION: Our findings demonstrate that bidirectional promoters utilize a variety of core promoter elements to initiate transcription. CpG-islands dominate the regulatory landscape of this group of promoters.

Comprehensive annotation of bidirectional promoters identifies co-regulation among breast and ovarian cancer genes.

A "bidirectional gene pair" comprises two adjacent genes whose transcription start sites are neighboring and directed away from each other. The intervening regulatory region is called a "bidirectional promoter." These promoters are often associated with genes that function in DNA repair, with the potential to participate in the development of cancer. No connection between these gene pairs and cancer has been previously investigated. Using the database of spliced-expressed sequence tags (ESTs), we identified the most complete collection of human transcripts under the control of bidirectional promoters. A rigorous screen of the spliced EST data identified new bidirectional promoters, many of which functioned as alternative promoters or regulated novel transcripts. Additionally, we show a highly significant enrichment of bidirectional promoters in genes implicated in somatic cancer, including a substantial number of genes implicated in breast and ovarian cancers. The repeated use of this promoter structure in the human genome suggests it could regulate co-expression patterns among groups of genes. Using microarray expression data from 79 human tissues, we verify regulatory networks among genes controlled by bidirectional promoters. Subsets of these promoters contain similar combinations of transcription factor binding sites, including evolutionarily conserved ETS factor binding sites in ERBB2, FANCD2, and BRCA2. Interpreting the regulation of genes involved in co-expression networks, especially those involved in cancer, will be an important step toward defining molecular events that may contribute to disease.

The ENCODEdb portal: simplified access to ENCODE Consortium data.

The Encyclopedia of DNA Elements (ENCODE) project aims to identify and characterize all functional elements in a representative chromosomal sample comprising 1% of the human genome. Data generated by members of The ENCODE Project Consortium are housed in a number of public databases, such as the UCSC Genome Browser, NCBI's Gene Expression Omnibus (GEO), and EBI's ArrayExpress. As such, it is often difficult for biologists to gather all of the ENCODE data from a particular genomic region of interest and integrate them with relevant information found in other public databases. The ENCODEdb portal was developed to address this problem. ENCODEdb provides a unified, single point-of-access to data generated by the ENCODE Consortium, as well as to data from other source databases that lie within ENCODE regions; this provides the user a complete view of all known data in a particular region of interest. ENCODEdb Genomic Context searches allow for the retrieval of information on functional elements annotated within ENCODE regions, including mRNA, EST, and STS sequences; single nucleotide polymorphisms, and UniGene clusters. Information is also retrieved from GEO, OMIM, and major genome sequence browsers. ENCODEdb Consortium Data searches allow users to perform compound queries on array-based ENCODE data available both from GEO and from the UCSC Genome Browser. Results are retrieved from a specific genomic area of interest and can be further manipulated in a variety of contexts, including the UCSC Genome Browser and the Galaxy large-scale genome analysis platform. The ENCODEdb portal is freely accessible at http://research.nhgri.nih.gov/ENCODEdb.