Showing papers by "Broad Institute published in 2006"

Principal components analysis corrects for stratification in genome-wide association studies

Abstract: Population stratification—allele frequency differences between cases and controls due to systematic ancestry differences—can cause spurious associations in disease studies. We describe a method that enables explicit detection and correction of population stratification on a genome-wide scale. Our method uses principal components analysis to explicitly model ancestry differences between cases and controls. The resulting correction is specific to a candidate marker’s variation in frequency across ancestral populations, minimizing spurious associations while maximizing power to detect true associations. Our simple, efficient approach can easily be applied to disease studies with hundreds of thousands of markers. Population stratification—allele frequency differences between cases and controls due to systematic ancestry differences—can cause spurious associations in disease studies 1‐8 . Because the effects of stratification vary in proportion to the number of samples 9 , stratification will be an increasing problem in the large-scale association studies of the future, which will analyze thousands of samples in an effort to detect common genetic variants of weak effect. The two prevailing methods for dealing with stratification are genomic control and structured association 9‐14 . Although genomic control and structured association have proven useful in a variety of contexts, they have limitations. Genomic control corrects for stratification by adjusting association statistics at each marker by a uniform overall inflation factor. However, some markers differ in their allele frequencies across ancestral populations more than others. Thus, the uniform adjustment applied by genomic control may be insufficient at markers having unusually strong differentiation across ancestral populations and may be superfluous at markers devoid of such differentiation, leading to a loss in power. Structured association uses a program such as STRUCTURE 15 to assign the samples to discrete subpopulation clusters and then aggregates evidence of association within each cluster. If fractional membership in more than one cluster is allowed, the method cannot currently be applied to genome-wide association studies because of its intensive computational cost on large data sets. Furthermore, assignments of individuals to clusters are highly sensitive to the number of clusters, which is not well defined 14,16 .

Population structure and eigenanalysis

Abstract: Current methods for inferring population structure from genetic data do not provide formal significance tests for population differentiation. We discuss an approach to studying population structure (principal components analysis) that was first applied to genetic data by Cavalli-Sforza and colleagues. We place the method on a solid statistical footing, using results from modern statistics to develop formal significance tests. We also uncover a general “phase change” phenomenon about the ability to detect structure in genetic data, which emerges from the statistical theory we use, and has an important implication for the ability to discover structure in genetic data: for a fixed but large dataset size, divergence between two populations (as measured, for example, by a statistic like FST) below a threshold is essentially undetectable, but a little above threshold, detection will be easy. This means that we can predict the dataset size needed to detect structure.

A Genome-Wide Association Study Identifies IL23R as an Inflammatory Bowel Disease Gene

Abstract: The inflammatory bowel diseases Crohn's disease and ulcerative colitis are common, chronic disorders that cause abdominal pain, diarrhea, and gastrointestinal bleeding. To identify genetic factors that might contribute to these disorders, we performed a genome-wide association study. We found a highly significant association between Crohn's disease and the IL23R gene on chromosome 1p31, which encodes a subunit of the receptor for the proinflammatory cytokine interleukin-23. An uncommon coding variant (rs11209026, c.1142G>A, p.Arg381Gln) confers strong protection against Crohn's disease, and additional noncoding IL23R variants are independently associated. Replication studies confirmed IL23R associations in independent cohorts of patients with Crohn's disease or ulcerative colitis. These results and previous studies on the proinflammatory role of IL-23 prioritize this signaling pathway as a therapeutic target in inflammatory bowel disease.

Reactive oxygen species have a causal role in multiple forms of insulin resistance.

Abstract: Insulin resistance is a cardinal feature of type 2 diabetes and is characteristic of a wide range of other clinical and experimental settings. Little is known about why insulin resistance occurs in so many contexts. Do the various insults that trigger insulin resistance act through a common mechanism? Or, as has been suggested, do they use distinct cellular pathways? Here we report a genomic analysis of two cellular models of insulin resistance, one induced by treatment with the cytokine tumour-necrosis factor-alpha and the other with the glucocorticoid dexamethasone. Gene expression analysis suggests that reactive oxygen species (ROS) levels are increased in both models, and we confirmed this through measures of cellular redox state. ROS have previously been proposed to be involved in insulin resistance, although evidence for a causal role has been scant. We tested this hypothesis in cell culture using six treatments designed to alter ROS levels, including two small molecules and four transgenes; all ameliorated insulin resistance to varying degrees. One of these treatments was tested in obese, insulin-resistant mice and was shown to improve insulin sensitivity and glucose homeostasis. Together, our findings suggest that increased ROS levels are an important trigger for insulin resistance in numerous settings.

GenePattern 2.0.

Abstract: Stephen J Chapman1,2, Chiea C Khor1, Fredrik O Vannberg1, Nicholas A Maskell2, Christopher WH Davies3, Emma L Hedley2, Shelley Segal4, Catrin E Moore4, Kyle Knox5, Nicholas P Day6, Stephen H Gillespie7, Derrick W Crook5, Robert JO Davies2 & Adrian VS Hill1 1The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK. 2Oxford Centre for Respiratory Medicine, Churchill Hospital Site, Oxford Radcliffe Hospital, Oxford OX3 7LJ, UK. 3Department of Respiratory Medicine, Royal Berkshire Hospital, Reading RG1 5AN, UK. 4Department of Paediatrics, John Radcliffe Hospital, Oxford OX3 9DU, UK. 5Department of Microbiology, John Radcliffe Hospital, Oxford OX3 9DU, UK. 6Centre for Clinical Vaccinology and Tropical Medicine, Oxford OX3 9DU, UK. 7Centre for Medical Microbiology, Department of Infection, University College London, London NW1 2BU, UK. e-mail: adrian.hill@well.ox.ac.uk

Transformation from committed progenitor to leukaemia stem cell initiated by MLL-AF9.

Abstract: Leukaemias and other cancers possess a rare population of cells capable of the limitless self-renewal necessary for cancer initiation and maintenance. Eradication of these cancer stem cells is probably a critical part of any successful anti-cancer therapy, and may explain why conventional cancer therapies are often effective in reducing tumour burden, but are only rarely curative. Given that both normal and cancer stem cells are capable of self-renewal, the extent to which cancer stem cells resemble normal tissue stem cells is a critical issue if targeted therapies are to be developed. However, it remains unclear whether cancer stem cells must be phenotypically similar to normal tissue stem cells or whether they can retain the identity of committed progenitors. Here we show that leukaemia stem cells (LSC) can maintain the global identity of the progenitor from which they arose while activating a limited stem-cell- or self-renewal-associated programme. We isolated LSC from leukaemias initiated in committed granulocyte macrophage progenitors through introduction of the MLL-AF9 fusion protein encoded by the t(9;11)(p22;q23). The LSC were capable of transferring leukaemia to secondary recipient mice when only four cells were transferred, and possessed an immunophenotype and global gene expression profile very similar to that of normal granulocyte macrophage progenitors. However, a subset of genes highly expressed in normal haematopoietic stem cells was re-activated in LSC. LSC can thus be generated from committed progenitors without widespread reprogramming of gene expression, and a leukaemia self-renewal-associated signature is activated in the process. Our findings define progression from normal progenitor to cancer stem cell, and suggest that targeting a self-renewal programme expressed in an abnormal context may be possible.

BRAF mutation predicts sensitivity to MEK inhibition

Abstract: The kinase pathway comprising RAS, RAF, mitogen-activated protein kinase kinase (MEK) and extracellular signal regulated kinase (ERK) is activated in most human tumours, often through gain-of-function mutations of RAS and RAF family members. Using small-molecule inhibitors of MEK and an integrated genetic and pharmacologic analysis, we find that mutation of BRAF is associated with enhanced and selective sensitivity to MEK inhibition when compared to either 'wild-type' cells or cells harbouring a RAS mutation. This MEK dependency was observed in BRAF mutant cells regardless of tissue lineage, and correlated with both downregulation of cyclin D1 protein expression and the induction of G1 arrest. Pharmacological MEK inhibition completely abrogated tumour growth in BRAF mutant xenografts, whereas RAS mutant tumours were only partially inhibited. These data suggest an exquisite dependency on MEK activity in BRAF mutant tumours, and offer a rational therapeutic strategy for this genetically defined tumour subtype.

MPLW515L is a novel somatic activating mutation in myelofibrosis with myeloid metaplasia.

Abstract: Background The JAK2V617F allele has recently been identified in patients with polycythemia vera (PV), essential thrombocytosis (ET), and myelofibrosis with myeloid metaplasia (MF). Subsequent analysis has shown that constitutive activation of the JAK-STAT signal transduction pathway is an important pathogenetic event in these patients, and that enzymatic inhibition of JAK2V617F may be of therapeutic benefit in this context. However, a significant proportion of patients with ET or MF are JAK2V617F-negative. We hypothesized that activation of the JAK-STAT pathway might also occur as a consequence of activating mutations in certain hematopoietic-specific cytokine receptors, including the erythropoietin receptor (EPOR), the thrombopoietin receptor (MPL), or the granulocyte-colony stimulating factor receptor (GCSFR).

Chromosome Conformation Capture Carbon Copy (5C): A massively parallel solution for mapping interactions between genomic elements

Abstract: Physical interactions between genetic elements located throughout the genome play important roles in gene regulation and can be identified with the Chromosome Conformation Capture (3C) methodology. 3C converts physical chromatin interactions into specific ligation products, which are quantified individually by PCR. Here we present a high-throughput 3C approach, 3C-Carbon Copy (5C), that employs microarrays or quantitative DNA sequencing using 454-technology as detection methods. We applied 5C to analyze a 400-kb region containing the human beta-globin locus and a 100-kb conserved gene desert region. We validated 5C by detection of several previously identified looping interactions in the beta-globin locus. We also identified a new looping interaction in K562 cells between the beta-globin Locus Control Region and the gamma-beta-globin intergenic region. Interestingly, this region has been implicated in the control of developmental globin gene switching. 5C should be widely applicable for large-scale mapping of cis- and trans- interaction networks of genomic elements and for the study of higher-order chromosome structure.

Insights from the genome of the biotrophic fungal plant pathogen Ustilago maydis

Abstract: Ustilago maydis is a ubiquitous pathogen of maize and a well-established model organism for the study of plant-microbe interactions. This basidiomycete fungus does not use aggressive virulence strategies to kill its host. U. maydis belongs to the group of biotrophic parasites (the smuts) that depend on living tissue for proliferation and development. Here we report the genome sequence for a member of this economically important group of biotrophic fungi. The 20.5-million-base U. maydis genome assembly contains 6,902 predicted protein-encoding genes and lacks pathogenicity signatures found in the genomes of aggressive pathogenic fungi, for example a battery of cell-wall-degrading enzymes. However, we detected unexpected genomic features responsible for the pathogenicity of this organism. Specifically, we found 12 clusters of genes encoding small secreted proteins with unknown function. A significant fraction of these genes exists in small gene families. Expression analysis showed that most of the genes contained in these clusters are regulated together and induced in infected tissue. Deletion of individual clusters altered the virulence of U. maydis in five cases, ranging from a complete lack of symptoms to hypervirulence. Despite years of research into the mechanism of pathogenicity in U. maydis, no 'true' virulence factors had been previously identified. Thus, the discovery of the secreted protein gene clusters and the functional demonstration of their decisive role in the infection process illuminate previously unknown mechanisms of pathogenicity operating in biotrophic fungi. Genomic analysis is, similarly, likely to open up new avenues for the discovery of virulence determinants in other pathogens.

Positive Natural Selection in the Human Lineage

Abstract: Positive natural selection is the force that drives the increase in prevalence of advantageous traits, and it has played a central role in our development as a species. Until recently, the study of natural selection in humans has largely been restricted to comparing individual candidate genes to theoretical expectations. The advent of genome-wide sequence and polymorphism data brings fundamental new tools to the study of natural selection. It is now possible to identify new candidates for selection and to reevaluate previous claims by comparison with empirical distributions of DNA sequence variation across the human genome and among populations. The flood of data and analytical methods, however, raises many new challenges. Here, we review approaches to detect positive natural selection, describe results from recent analyses of genome-wide data, and discuss the prospects and challenges ahead as we expand our understanding of the role of natural selection in shaping the human genome.

A practical recipe for stable isotope labeling by amino acids in cell culture (SILAC).

Abstract: Stable isotope labeling by amino acids in cell culture (SILAC) is a simple, robust, yet powerful approach in mass spectrometry (MS)-based quantitative proteomics. SILAC labels cellular proteomes through normal metabolic processes, incorporating non-radioactive, stable isotope-containing amino acids in newly synthesized proteins. Growth medium is prepared where natural ("light") amino acids are replaced by "heavy" SILAC amino acids. Cells grown in this medium incorporate the heavy amino acids after five cell doublings and SILAC amino acids have no effect on cell morphology or growth rates. When light and heavy cell populations are mixed, they remain distinguishable by MS, and protein abundances are determined from the relative MS signal intensities. SILAC provides accurate relative quantification without any chemical derivatization or manipulation and enables development of elegant functional assays in proteomics. In this protocol, we describe how to apply SILAC and the use of nano-scale liquid chromatography coupled to electrospray ionization mass spectrometry for protein identification and quantification. This procedure can be completed in 8 days.

A high resolution HLA and SNP haplotype map for disease association studies in the extended human MHC

Abstract: The proteins encoded by the classical HLA class I and class II genes in the major histocompatibility complex (MHC) are highly polymorphic and are essential in self versus non-self immune recognition. HLA variation is a crucial determinant of transplant rejection and susceptibility to a large number of infectious and autoimmune diseases. Yet identification of causal variants is problematic owing to linkage disequilibrium that extends across multiple HLA and non-HLA genes in the MHC. We therefore set out to characterize the linkage disequilibrium patterns between the highly polymorphic HLA genes and background variation by typing the classical HLA genes and >7,500 common SNPs and deletion-insertion polymorphisms across four population samples. The analysis provides informative tag SNPs that capture much of the common variation in the MHC region and that could be used in disease association studies, and it provides new insight into the evolutionary dynamics and ancestral origins of the HLA loci and their haplotypes.

Common deletion polymorphisms in the human genome.

Abstract: The locations and properties of common deletion variants in the human genome are largely unknown. We describe a systematic method for using dense SNP genotype data to discover deletions and its application to data from the International HapMap Consortium to characterize and catalogue segregating deletion variants across the human genome. We identified 541 deletion variants (94% novel) ranging from 1 kb to 745 kb in size; 278 of these variants were observed in multiple, unrelated individuals, 120 in the homozygous state. The coding exons of ten expressed genes were found to be commonly deleted, including multiple genes with roles in sex steroid metabolism, olfaction and drug response. These common deletion polymorphisms typically represent ancestral mutations that are in linkage disequilibrium with nearby SNPs, meaning that their association to disease can often be evaluated in the course of SNP-based whole-genome association studies.

A common genetic variant is associated with adult and childhood obesity.

Abstract: Obesity is a heritable trait and a risk factor for many common diseases such as type 2 diabetes, heart disease, and hypertension. We used a dense whole-genome scan of DNA samples from the Framingham Heart Study participants to identify a common genetic variant near the INSIG2 gene associated with obesity. We have replicated the finding in four separate samples composed of individuals of Western European ancestry, African Americans, and children. The obesity-predisposing genotype is present in 10% of individuals. Our study suggests that common genetic polymorphisms are important determinants of obesity.

Common variation in three genes, including a noncoding variant in CFH , strongly influences risk of age-related macular degeneration

Abstract: Age-related macular degeneration (AMD) is a common, late-onset disease with seemingly typical complexity: recurrence ratios for siblings of an affected individual are three- to sixfold higher than in the general population, and family-based analysis has resulted in only modestly significant evidence for linkage. In a case-control study drawn from a US-based population of European descent, we have identified a previously unrecognized common, noncoding variant in CFH, the gene encoding complement factor H, that substantially increases the influence of this locus on AMD, and we have strongly replicated the associations of four other previously reported common alleles in three genes (P values ranging from 10−6 to 10−70). Despite excellent power to detect epistasis, we observed purely additive accumulation of risk from alleles at these genes. We found no differences in association of these loci with major phenotypic categories of advanced AMD. Genotypes at these five common SNPs define a broad spectrum of interindividual disease risk and explain about half of the classical sibling risk of AMD in our study population.

TMPRSS2:ERG fusion-associated deletions provide insight into the heterogeneity of prostate cancer

Abstract: Prostate cancer is a common and clinically heterogeneous disease with marked variability in progression. The recent identification of gene fusions of the 5'-untranslated region of TMPRSS2 (21q22.3) with the ETS transcription factor family members, either ERG (21q22.2), ETV1 (7p21.2), or ETV4 (17q21), suggests a mechanism for overexpression of the ETS genes in the majority of prostate cancers. In the current study using fluorescence in situ hybridization (FISH), we identified the TMPRSS2:ERG rearrangements in 49.2% of 118 primary prostate cancers and 41.2% of 18 hormone-naive lymph node metastases. The FISH assay detected intronic deletions between ERG and TMPRSS2 resulting in TMPRSS2:ERG fusion in 60.3% (35 of 58) of the primary TMPRSS2:ERG prostate cancers and 42.9% (3 of 7) of the TMPRSS2:ERG hormone-naive lymph node metastases. A significant association was observed between TMPRSS2:ERG rearranged tumors through deletions and higher tumor stage and the presence of metastatic disease involving pelvic lymph nodes. Using 100K oligonucleotide single nucleotide polymorphism arrays, a homogeneous deletion site between ERG and TMPRSS2 on chromosome 21q22.2-3 was identified with two distinct subclasses distinguished by the start point of the deletion at either 38.765 or 38.911 Mb. This study confirms that TMPRSS2:ERG is fused in approximately half of the prostate cancers through deletion of genomic DNA between ERG and TMPRSS2. The deletion as cause of TMPRSS2:ERG fusion is associated with clinical features for prostate cancer progression compared with tumors that lack the TMPRSS2:ERG rearrangement.

A common genetic variant in the NOS1 regulator NOS1AP modulates cardiac repolarization.

Abstract: Extremes of the electrocardiographic QT interval, a measure of cardiac repolarization, are associated with increased cardiovascular mortality. We identified a common genetic variant influencing this quantitative trait through a genome-wide association study on 200 subjects at the extremes of a population-based QT interval distribution of 3,966 subjects from the KORA cohort in Germany, with follow-up screening of selected markers in the remainder of the cohort. We validated statistically significant findings in two independent samples of 2,646 subjects from Germany and 1,805 subjects from the US Framingham Heart Study. This genome-wide study identified NOS1AP (CAPON), a regulator of neuronal nitric oxide synthase, as a new target that modulates cardiac repolarization. Approximately 60% of subjects of European ancestry carry at least one minor allele of the NOS1AP genetic variant, which explains up to 1.5% of QT interval variation.

Bayesian Estimation of Concordance among Gene Trees

Abstract: Multigene sequence data have great potential for elucidating important and interesting evolutionary processes, but statistical methods for extracting information from such data remain limited. Although various biological processes may cause different genes to have different genealogical histories (and hence different tree topologies), we also may expect that the number of distinct topologies among a set of genes is relatively small compared with the number of possible topologies. Therefore evidence about the tree topology for one gene should influence our inferences of the tree topology on a different gene, but to what extent? In this paper, we present a new approach for modeling and estimating concordance among a set of gene trees given aligned molecular sequence data. Our approach introduces a one-parameter probability distribution to describe the prior distribution of concordance among gene trees. We describe a novel 2-stage Markov chain Monte Carlo (MCMC) method that first obtains independent Bayesian posterior probability distributions for individual genes using standard methods. These posterior distributions are then used as input for a second MCMC procedure that estimates a posterior distribution of gene-to-tree maps (GTMs). The posterior distribution of GTMs can then be summarized to provide revised posterior probability distributions for each gene (taking account of concordance) and to allow estimation of the proportion of the sampled genes for which any given clade is true (the sample-wide concordance factor). Further, under the assumption that the sampled genes are drawn randomly from a genome of known size, we show how one can obtain an estimate, with credibility intervals, on the proportion of the entire genome for which a clade is true (the genome-wide concordance factor). We demonstrate the method on a set of 106 genes from 8 yeast species.

Repeated morphological evolution through cis -regulatory changes in a pleiotropic gene

Abstract: The independent evolution of morphological similarities is widespread. For simple traits, such as overall body colour, repeated transitions by means of mutations in the same gene may be common. However, for more complex traits, the possible genetic paths may be more numerous; the molecular mechanisms underlying their independent origins and the extent to which they are constrained to follow certain genetic paths are largely unknown. Here we show that a male wing pigmentation pattern involved in courtship display has been gained and lost multiple times in a Drosophila clade. Each of the cases we have analysed (two gains and two losses) involved regulatory changes at the pleiotropic pigmentation gene yellow. Losses involved the parallel inactivation of the same cis-regulatory element (CRE), with changes at a few nucleotides sufficient to account for the functional divergence of one element between two sibling species. Surprisingly, two independent gains of wing spots resulted from the co-option of distinct ancestral CREs. These results demonstrate how the functional diversification of the modular CREs of pleiotropic genes contributes to evolutionary novelty and the independent evolution of morphological similarities.

Deuterostome phylogeny reveals monophyletic chordates and the new phylum Xenoturbellida

Abstract: Deuterostomes comprise vertebrates, the related invertebrate chordates (tunicates and cephalochordates) and three other invertebrate taxa: hemichordates, echinoderms and Xenoturbella. The relationships between invertebrate and vertebrate deuterostomes are clearly important for understanding our own distant origins. Recent phylogenetic studies of chordate classes and a sea urchin have indicated that urochordates might be the closest invertebrate sister group of vertebrates, rather than cephalochordates, as traditionally believed. More remarkable is the suggestion that cephalochordates are closer to echinoderms than to vertebrates and urochordates, meaning that chordates are paraphyletic. To study the relationships among all deuterostome groups, we have assembled an alignment of more than 35,000 homologous amino acids, including new data from a hemichordate, starfish and Xenoturbella. We have also sequenced the mitochondrial genome of Xenoturbella. We support the clades Olfactores (urochordates and vertebrates) and Ambulacraria (hemichordates and echinoderms). Analyses using our new data, however, do not support a cephalochordate and echinoderm grouping and we conclude that chordates are monophyletic. Finally, nuclear and mitochondrial data place Xenoturbella as the sister group of the two ambulacrarian phyla. As such, Xenoturbella is shown to be an independent phylum, Xenoturbellida, bringing the number of living deuterostome phyla to four.

Minimizing the risk of reporting false positives in large-scale RNAi screens

Abstract: Large-scale RNA interference (RNAi)-based analyses, very much as other ‘omic’ approaches, have inherent rates of false positives and negatives. The variability in the standards of care applied to validate results from these studies, if left unchecked, could eventually begin to undermine the credibility of RNAi as a powerful functional approach. This Commentary is an invitation to an open discussion started among various users of RNAi to set forth accepted standards that would insure the quality and accuracy of information in the large datasets coming out of genome-scale screens.

Genome-scale loss-of-function screening with a lentiviral RNAi library.

Abstract: The discovery that RNA interference (RNAi) is functional in mammalian cells led us to form The RNAi Consortium (TRC) with the goal of enabling large-scale loss-of-function screens through the development of genome-scale RNAi libraries and methodologies for their use. These resources form the basis of a loss-of-function screening platform created at the Broad Institute. Our human and mouse libraries currently contain >135,000 lentiviral clones targeting 27,000 genes. Initial screening efforts have demonstrated that these libraries and methods are practical and powerful tools for high-throughput lentivirus RNAi screens.