Simon Minovitsky

In vivo enhancer analysis of human conserved non-coding sequences.

Identifying the sequences that direct the spatial and temporal expression of genes and defining their function in vivo remains a significant challenge in the annotation of vertebrate genomes. One major obstacle is the lack of experimentally validated training sets. In this study, we made use of extreme evolutionary sequence conservation as a filter to identify putative gene regulatory elements, and characterized the in vivo enhancer activity of a large group of non-coding elements in the human genome that are conserved in human–pufferfish, Takifugu (Fugu) rubripes, or ultraconserved in human–mouse–rat. We tested 167 of these extremely conserved sequences in a transgenic mouse enhancer assay. Here we report that 45% of these sequences functioned reproducibly as tissue-specific enhancers of gene expression at embryonic day 11.5. While directing expression in a broad range of anatomical structures in the embryo, the majority of the 75 enhancers directed expression to various regions of the developing nervous system. We identified sequence signatures enriched in a subset of these elements that targeted forebrain expression, and used these features to rank all ∼3,100 non-coding elements in the human genome that are conserved between human and Fugu. The testing of the top predictions in transgenic mice resulted in a threefold enrichment for sequences with forebrain enhancer activity. These data dramatically expand the catalogue of human gene enhancers that have been characterized in vivo, and illustrate the utility of such training sets for a variety of biological applications, including decoding the regulatory vocabulary of the human genome.

VISTA Enhancer Browser—a database of tissue-specific human enhancers

Despite the known existence of distant-acting cis-regulatory elements in the human genome, only a small fraction of these elements has been identified and experimentally characterized in vivo. This paucity of enhancer collections with defined activities has thus hindered computational approaches for the genome-wide prediction of enhancers and their functions. To fill this void, we utilize comparative genome analysis to identify candidate enhancer elements in the human genome coupled with the experimental determination of their in vivo enhancer activity in transgenic mice [L. A. Pennacchio et al. (2006) Nature, in press]. These data are available through the VISTA Enhancer Browser (). This growing database currently contains over 250 experimentally tested DNA fragments, of which more than 100 have been validated as tissue-specific enhancers. For each positive enhancer, we provide digital images of whole-mount embryo staining at embryonic day 11.5 and an anatomical description of the reporter gene expression pattern. Users can retrieve elements near single genes of interest, search for enhancers that target reporter gene expression to a particular tissue, or download entire collections of enhancers with a defined tissue specificity or conservation depth. These experimentally validated training sets are expected to provide a basis for a wide range of downstream computational and functional studies of enhancer function.

The Genome Portal of the Department of Energy Joint Genome Institute

The Department of Energy (DOE) Joint Genome Institute (JGI) is a national user facility with massive-scale DNA sequencing and analysis capabilities dedicated to advancing genomics for bioenergy and environmental applications. Beyond generating tens of trillions of DNA bases annually, the Institute develops and maintains data management systems and specialized analytical capabilities to manage and interpret complex genomic data sets, and to enable an expanding community of users around the world to analyze these data in different contexts over the web. The JGI Genome Portal (http://genome.jgi.doe.gov) provides a unified access point to all JGI genomic databases and analytical tools. A user can find all DOE JGI sequencing projects and their status, search for and download assemblies and annotations of sequenced genomes, and interactively explore those genomes and compare them with other sequenced microbes, fungi, plants or metagenomes using specialized systems tailored to each particular class of organisms. We describe here the general organization of the Genome Portal and the most recent addition, MycoCosm (http://jgi.doe.gov/fungi), a new integrated fungal genomics resource.

Combinatorial regulation of endothelial gene expression by ets and forkhead transcription factors

Vascular development begins when mesodermal cells differentiate into endothelial cells, which then form primitive vessels. It has been hypothesized that endothelial-specific gene expression may be regulated combinatorially, but the transcriptional mechanisms governing specificity in vascular gene expression remain incompletely understood. Here, we identify a 44 bp transcriptional enhancer that is sufficient to direct expression specifically and exclusively to the developing vascular endothelium. This enhancer is regulated by a composite cis-acting element, the FOX:ETS motif, which is bound and synergistically activated by Forkhead and Ets transcription factors. We demonstrate that coexpression of the Forkhead protein FoxC2 and the Ets protein Etv2 induces ectopic expression of vascular genes in Xenopus embryos, and that combinatorial knockdown of the orthologous genes in zebrafish embryos disrupts vascular development. Finally, we show that FOX:ETS motifs are present in many known endothelial-specific enhancers and that this motif is an efficient predictor of endothelial enhancers in the human genome.

RegTransBase—a database of regulatory sequences and interactions in a wide range of prokaryotic genomes

RegTransBase is a manually curated database of regulatory interactions in prokaryotes that captures the knowledge in public scientific literature using a controlled vocabulary. Although several databases describing interactions between regulatory proteins and their binding sites are already being maintained, they either focus mostly on the model organisms Escherichia coli and Bacillus subtilis or are entirely computationally derived. RegTransBase describes a large number of regulatory interactions reported in many organisms and contains the following types of experimental data: the activation or repression of transcription by an identified direct regulator, determining the transcriptional regulatory function of a protein (or RNA) directly binding to DNA (RNA), mapping or prediction of a binding site for a regulatory protein and characterization of regulatory mutations. Currently, RegTransBase content is derived from about 3000 relevant articles describing over 7000 experiments in relation to 128 microbes. It contains data on the regulation of about 7500 genes and evidence for 6500 interactions with 650 regulators. RegTransBase also contains manually created position weight matrices (PWM) that can be used to identify candidate regulatory sites in over 60 species. RegTransBase is available at .

The splicing regulatory element, UGCAUG, is phylogenetically and spatially conserved in introns that flank tissue-specific alternative exons

Previous studies have identified UGCAUG as an intron splicing enhancer that is frequently located adjacent to tissue-specific alternative exons in the human genome. Here, we show that UGCAUG is phylogenetically and spatially conserved in introns that flank brain-enriched alternative exons from fish to man. Analysis of sequence from the mouse, rat, dog, chicken and pufferfish genomes revealed a strongly statistically significant association of UGCAUG with the proximal intron region downstream of brain-enriched alternative exons. The number, position and sequence context of intronic UGCAUG elements were highly conserved among mammals and in chicken, but more divergent in fish. Control datasets, including constitutive exons and non-tissue-specific alternative exons, exhibited a much lower incidence of closely linked UGCAUG elements. We propose that the high sequence specificity of the UGCAUG element, and its unique association with tissue-specific alternative exons, mark it as a critical component of splicing switch mechanism(s) designed to activate a limited repertoire of splicing events in cell type-specific patterns. We further speculate that highly conserved UGCAUG-binding protein(s) related to the recently described Fox-1 splicing factor play a critical role in mediating this specificity.

A correlation with exon expression approach to identify cis-regulatory elements for tissue-specific alternative splicing

Correlation of motif occurrences with gene expression intensity is an effective strategy for elucidating transcriptional cis-regulatory logic. Here we demonstrate that this approach can also identify cis-regulatory elements for alternative pre-mRNA splicing. Using data from a human exon microarray, we identified 56 cassette exons that exhibited higher transcript-normalized expression in muscle than in other normal adult tissues. Intron sequences flanking these exons were then analyzed to identify candidate regulatory motifs for muscle-specific alternative splicing. Correlation of motif parameters with gene-normalized exon expression levels was examined using linear regression and linear splines on RNA words and degenerate weight matrices, respectively. Our unbiased analysis uncovered multiple candidate regulatory motifs for muscle-specific splicing, many of which are phylogenetically conserved among vertebrate genomes. The most prominent downstream motifs were binding sites for Fox1- and CELF-related splicing factors, and a branchpoint-like element acuaac; pyrimidine-rich elements resembling PTB-binding sites were most significant in upstream introns. Intriguingly, our systematic study indicates a paucity of novel muscle-specific elements that are dominant in short proximal intronic regions. We propose that Fox and CELF proteins play major roles in enforcing the muscle-specific alternative splicing program, facilitating expression of unique isoforms of cytoskeletal proteins critical to muscle cell function.

SNP-VISTA: An interactive SNP visualization tool

BackgroundRecent advances in sequencing technologies promise to provide a better understanding of the genetics of human disease as well as the evolution of microbial populations. Single Nucleotide Polymorphisms (SNPs) are established genetic markers that aid in the identification of loci affecting quantitative traits and/or disease in a wide variety of eukaryotic species. With todays technological capabilities, it has become possible to re-sequence a large set of appropriate candidate genes in individuals with a given disease in an attempt to identify causative mutations. In addition, SNPs have been used extensively in efforts to study the evolution of microbial populations, and the recent application of random shotgun sequencing to environmental samples enables more extensive SNP analysis of co-occurring and co-evolving microbial populations. The program is available at http://genome.lbl.gov/vista/snpvista[1].ResultsWe have developed and present two modifications of an interactive visualization tool, SNP-VISTA, to aid in the analyses of the following types of data: A. Large-scale re-sequence data of disease-related genes for discovery of associated and/or causative alleles (GeneSNP-VISTA). B. Massive amounts of ecogenomics data for studying homologous recombination in microbial populations (EcoSNP-VISTA). The main features and capabilities of SNP-VISTA are: 1) mapping of SNPs to gene structure; 2) classification of SNPs, based on their location in the gene, frequency of occurrence in samples and allele composition; 3) clustering, based on user-defined subsets of SNPs, highlighting haplotypes as well as recombinant sequences; 4) integration of protein evolutionary conservation visualization; and 5) display of automatically calculated recombination points that are user-editable.ConclusionThe main strength of SNP-VISTA is its graphical interface and use of visual representations, which support interactive exploration and hence better understanding of large-scale SNP data by the user.