Richard Humbert

Systematic Localization of Common Disease-Associated Variation in Regulatory DNA

Predictions of Genetic Disease Many genome-wide association studies (GWAS) have identified loci and variants associated with disease, but the ability to predict disease on the basis of these genetic variants remains small. Maurano et al. (p. 1190; see the Perspective by Schadt and Chang; see the cover) characterize the location of GWAS variants in the genome with respect to their proximity to regulatory DNA [marked by deoxyribonuclease I (DNase I) hypersensitive sites] by tissue type, disease, and enrichments in physiologically relevant transcription factor binding sites and networks. They found many noncoding disease associations in regulatory DNA, indicating tissue and developmental-specific regulatory roles for many common genetic variants and thus enabling links to be made between gene regulation and adult-onset disease. Genetic variants that have been associated with diseases are concentrated in regulatory regions of the genome. Genome-wide association studies have identified many noncoding variants associated with common diseases and traits. We show that these variants are concentrated in regulatory DNA marked by deoxyribonuclease I (DNase I) hypersensitive sites (DHSs). Eighty-eight percent of such DHSs are active during fetal development and are enriched in variants associated with gestational exposure–related phenotypes. We identified distant gene targets for hundreds of variant-containing DHSs that may explain phenotype associations. Disease-associated variants systematically perturb transcription factor recognition sequences, frequently alter allelic chromatin states, and form regulatory networks. We also demonstrated tissue-selective enrichment of more weakly disease-associated variants within DHSs and the de novo identification of pathogenic cell types for Crohn’s disease, multiple sclerosis, and an electrocardiogram trait, without prior knowledge of physiological mechanisms. Our results suggest pervasive involvement of regulatory DNA variation in common human disease and provide pathogenic insights into diverse disorders.

The accessible chromatin landscape of the human genome.

DNase I hypersensitive sites (DHSs) are markers of regulatory DNA and have underpinned the discovery of all classes of cis-regulatory elements including enhancers, promoters, insulators, silencers and locus control regions. Here we present the first extensive map of human DHSs identified through genome-wide profiling in 125 diverse cell and tissue types. We identify ∼2.9 million DHSs that encompass virtually all known experimentally validated cis-regulatory sequences and expose a vast trove of novel elements, most with highly cell-selective regulation. Annotating these elements using ENCODE data reveals novel relationships between chromatin accessibility, transcription, DNA methylation and regulatory factor occupancy patterns. We connect ∼580,000 distal DHSs with their target promoters, revealing systematic pairing of different classes of distal DHSs and specific promoter types. Patterning of chromatin accessibility at many regulatory regions is organized with dozens to hundreds of co-activated elements, and the transcellular DNase I sensitivity pattern at a given region can predict cell-type-specific functional behaviours. The DHS landscape shows signatures of recent functional evolutionary constraint. However, the DHS compartment in pluripotent and immortalized cells exhibits higher mutation rates than that in highly differentiated cells, exposing an unexpected link between chromatin accessibility, proliferative potential and patterns of human variation.

An expansive human regulatory lexicon encoded in transcription factor footprints

Regulatory factor binding to genomic DNA protects the underlying sequence from cleavage by DNase I, leaving nucleotide-resolution footprints. Using genomic DNase I footprinting across 41 diverse cell and tissue types, we detected 45 million transcription factor occupancy events within regulatory regions, representing differential binding to 8.4 million distinct short sequence elements. Here we show that this small genomic sequence compartment, roughly twice the size of the exome, encodes an expansive repertoire of conserved recognition sequences for DNA-binding proteins that nearly doubles the size of the human cis–regulatory lexicon. We find that genetic variants affecting allelic chromatin states are concentrated in footprints, and that these elements are preferentially sheltered from DNA methylation. High-resolution DNase I cleavage patterns mirror nucleotide-level evolutionary conservation and track the crystallographic topography of protein–DNA interfaces, indicating that transcription factor structure has been evolutionarily imprinted on the human genome sequence. We identify a stereotyped 50-base-pair footprint that precisely defines the site of transcript origination within thousands of human promoters. Finally, we describe a large collection of novel regulatory factor recognition motifs that are highly conserved in both sequence and function, and exhibit cell-selective occupancy patterns that closely parallel major regulators of development, differentiation and pluripotency.

BEDOPS: high-performance genomic feature operations

UNLABELLED The large and growing number of genome-wide datasets highlights the need for high-performance feature analysis and data comparison methods, in addition to efficient data storage and retrieval techniques. We introduce BEDOPS, a software suite for common genomic analysis tasks which offers improved flexibility, scalability and execution time characteristics over previously published packages. The suite includes a utility to compress large inputs into a lossless format that can provide greater space savings and faster data extractions than alternatives. AVAILABILITY http://code.google.com/p/bedops/ includes binaries, source and documentation.

Developmental Fate and Cellular Maturity Encoded in Human Regulatory DNA Landscapes

Cellular-state information between generations of developing cells may be propagated via regulatory regions. We report consistent patterns of gain and loss of DNase I-hypersensitive sites (DHSs) as cells progress from embryonic stem cells (ESCs) to terminal fates. DHS patterns alone convey rich information about cell fate and lineage relationships distinct from information conveyed by gene expression. Developing cells share a proportion of their DHS landscapes with ESCs; that proportion decreases continuously in each cell type as differentiation progresses, providing a quantitative benchmark of developmental maturity. Developmentally stable DHSs densely encode binding sites for transcription factors involved in autoregulatory feedback circuits. In contrast to normal cells, cancer cells extensively reactivate silenced ESC DHSs and those from developmental programs external to the cell lineage from which the malignancy derives. Our results point to changes in regulatory DNA landscapes as quantitative indicators of cell-fate transitions, lineage relationships, and dysfunction.

High-throughput localization of functional elements by quantitative chromatin profiling

Identification of functional, noncoding elements that regulate transcription in the context of complex genomes is a major goal of modern biology. Localization of functionality to specific sequences is a requirement for genetic and computational studies. Here, we describe a generic approach, quantitative chromatin profiling, that uses quantitative analysis of in vivo chromatin structure over entire gene loci to rapidly and precisely localize cis-regulatory sequences and other functional modalities encoded by DNase I hypersensitive sites. To demonstrate the accuracy of this approach, we analyzed ∼300 kilobases of human genome sequence from diverse gene loci and cleanly delineated functional elements corresponding to a spectrum of classical cis-regulatory activities including enhancers, promoters, locus control regions and insulators as well as novel elements. Systematic, high-throughput identification of functional elements coinciding with DNase I hypersensitive sites will substantially expand our knowledge of transcriptional regulation and should simplify the search for noncoding genetic variation with phenotypic consequences.

Mouse regulatory DNA landscapes reveal global principles of cis-regulatory evolution

To study the evolutionary dynamics of regulatory DNA, we mapped >1.3 million deoxyribonuclease I–hypersensitive sites (DHSs) in 45 mouse cell and tissue types, and systematically compared these with human DHS maps from orthologous compartments. We found that the mouse and human genomes have undergone extensive cis-regulatory rewiring that combines branch-specific evolutionary innovation and loss with widespread repurposing of conserved DHSs to alternative cell fates, and that this process is mediated by turnover of transcription factor (TF) recognition elements. Despite pervasive evolutionary remodeling of the location and content of individual cis-regulatory regions, within orthologous mouse and human cell types the global fraction of regulatory DNA bases encoding recognition sites for each TF has been strictly conserved. Our findings provide new insights into the evolutionary forces shaping mammalian regulatory DNA landscapes. Mouse-to-human genomic comparisons illuminate conserved transcriptional programs despite regulatory rewiring. Rewiring the gene regulatory landscape DNAse I hypersensitive sites (DHSs) correlate with genomic locations that control where messenger RNA is to be produced. DHSs differ, depending on the cell type, developmental stage, and species. Viestra et al. compared mouse and human genome-wide DHS maps. Approximately one-third of the DHSs are conserved between the species, which separated approximately 550 million years ago. Most DHSs fell into tissue-specific cohorts; however, these were generally not conserved between the human and mouse. It seems that the majority of DHSs evolve because of changes in the sequence that gradually change how the region is regulated. Science, this issue p. 1007

Paraoxonase Genotypes, Lipoprotein Lipase Activity, and HDL

Paraxonase, an enzyme associated with the high density lipoprotein (HDL) particle, hydrolyzes paraoxon, the active metabolite of the insecticide parathion. Several studies have shown that paraxonase levels in humans have a distribution characteristic of two alleles, one with low activity and the other with high activity. Paraoxonase also has arylesterase activity, which does not exhibit activity polymorphism and can therefore serve as an estimate of enzyme protein. Although the ability of paraoxon to irreversibly inhibit lipoprotein lipase (LPL) has been exploited experimentally for many years, the role of plasma paraoxonase in lipoprotein metabolism is unknown. Seventy-two normal individuals were examined for paraoxonase genotypes, plasma paraoxonase and arylesterase activities, postheparin LPL and hepatic lipase (HL) activities, and lipoprotein levels to determine whether (1) paraoxonase activity or genotype determines lipoprotein levels via an effect on LPL or HL activity or (2) variation in LPL and HL activities determines HDL levels and indirectly affects paraoxonase activity and protein levels in plasma. In the entire group, paraoxonase activity was related to arylesterase activity and genotype. Whereas arylesterase activity was correlated with HDL cholesterol (HDL-C) and apolipoproteinA-I (apoA-I) levels, neither arylesterase nor paraoxonase was correlated with LPL or HL activity. Furthermore, LPL activity was positively correlated and HL inversely correlated with HDL cholesterol and apoA-I levels, whereas LPL was inversely correlated with triglyceride levels. The paraoxonase genotypes of the study group were 30 individuals homozygous for the low-activity allele, 38 heterozygotes, and 4 individuals homozygous for the high-activity allele. Paraoxonase genotype accounted for approximately .75 of the variation in paraoxonase activity. Paraoxonase activity was linearly related to arylesterase activity within each subgroup. No difference in either LPL or HL activity was seen as a function of paraoxonase genotype, nor were differences seen in plasma triglyceride or HDL-C by genotype by ANOVA. The relation between LPL and HL and components of HDL in the paraoxonase genotypic subgroups in general reflected the associations seen in the group as a whole. Multivariate analysis showed that LPL, HL, and arylesterase, a measure of paraoxonase mass, were independent predictors of HDL cholesterol, while paraoxonase genotype or activity was not. Thus, variation in LPL and HL appears to be significantly related to HDL cholesterol and apoA-I levels. The levels of HDL are a major correlate of paraoxonase protein levels, while paraoxonase genotype is the major predictor of plasma paraoxonase activity.

A thermodynamic approach to PCR primer design

We developed a primer design method, Pythia, in which state of the art DNA binding affinity computations are directly integrated into the primer design process. We use chemical reaction equilibrium analysis to integrate multiple binding energy calculations into a conservative measure of polymerase chain reaction (PCR) efficiency, and a precomputed index on genomic sequences to evaluate primer specificity. We show that Pythia can design primers with success rates comparable with those of current methods, but yields much higher coverage in difficult genomic regions. For example, in RepeatMasked sequences in the human genome, Pythia achieved a median coverage of 89% as compared with a median coverage of 51% for Primer3. For parameter settings yielding sensitivities of 81%, our method has a recall of 97%, compared with the Primer3 recall of 48%. Because our primer design approach is based on the chemistry of DNA interactions, it has fewer and more physically meaningful parameters than current methods, and is therefore easier to adjust to specific experimental requirements. Our software is freely available at http://pythia.sourceforge.net.

Gammaretroviral Vector Integration Occurs Overwhelmingly Within and Near DNase Hypersensitive Sites

Concerns surrounding the oncogenic potential of recombinant gammaretroviral vectors has spurred a great deal of interest in vector integration site (VIS) preferences. Although gammaretroviral vectors exhibit a modest preference for integration near transcription start sites (TSS) of active genes, such associations only account for about a third of all VIS. Previous studies suggested a correlation between gammaretroviral VIS and DNase hypersensitive sites (DHS), which mark chromatin regions associated with cis-regulatory elements. In order to study this issue directly, we assessed the correlation between 167 validated gammaretroviral VIS and a deep genome-wide map of DHS, both determined in the same cell line (the human fibrosarcoma HT1080). The DHS map was developed by sequencing individual DNase I cleavage sites using massively parallel sequencing technologies. These studies revealed an overwhelming preference for integrations associated with DHS, with a median distance of only 238 bp between individual VIS and the nearest DHS for the experimental dataset, compared to 3 kb for a random dataset and 577 to 1457 bp for two unrelated cell lines (p<0.001). Indeed, nearly 84% of all VIS were found to be located within 1 kb of a DHS (p=10(-43)). Further, this correlation was statistically independent from the association with TSS. The preference for DHS far exceeds that seen for other hallmarks of gammaretroviral VIS, including TSS, and may help explain several aspects of gammaretroviral vector biology, including the mechanism of VIS selection, as well as the relative frequency and underlying biology of gammaretroviral vector-mediated genotoxicity.