William Cookson

Merlin — Rapid analysis of dense genetic maps using sparse gene flow trees

Efforts to find disease genes using high-density single-nucleotide polymorphism (SNP) maps will produce data sets that exceed the limitations of current computational tools. Here we describe a new, efficient method for the analysis of dense genetic maps in pedigree data that provides extremely fast solutions to common problems such as allele-sharing analyses and haplotyping. We show that sparse binary trees represent patterns of gene flow in general pedigrees in a parsimonious manner, and derive a family of related algorithms for pedigree traversal. With these trees, exact likelihood calculations can be carried out efficiently for single markers or for multiple linked markers. Using an approximate multipoint calculation that ignores the unlikely possibility of a large number of recombinants further improves speed and provides accurate solutions in dense maps with thousands of markers. Our multipoint engine for rapid likelihood inference (Merlin) is a computer program that uses sparse inheritance trees for pedigree analysis; it performs rapid haplotyping, genotype error detection and affected pair linkage analyses and can handle more markers than other pedigree analysis packages.

A large-scale, consortium-based genomewide association study of asthma

BACKGROUND Susceptibility to asthma is influenced by genes and environment; implicated genes may indicate pathways for therapeutic intervention. Genetic risk factors may be useful in identifying subtypes of asthma and determining whether intermediate phenotypes, such as elevation of the total serum IgE level, are causally linked to disease. METHODS We carried out a genomewide association study by genotyping 10,365 persons with physician-diagnosed asthma and 16,110 unaffected persons, all of whom were matched for ancestry. We used random-effects pooled analysis to test for association in the overall study population and in subgroups of subjects with childhood-onset asthma (defined as asthma developing before 16 years of age), later-onset asthma, severe asthma, and occupational asthma. RESULTS We observed associations of genomewide significance between asthma and the following single-nucleotide polymorphisms: rs3771166 on chromosome 2, implicating IL1RL1/IL18R1 (P=3×10(−9)); rs9273349 on chromosome 6, implicating HLA-DQ (P=7×10(−14)); rs1342326 on chromosome 9, flanking IL33 (P=9×10(−10)); rs744910 on chromosome 15 in SMAD3 (P=4×10(−9)); and rs2284033 on chromosome 22 in IL2RB (P=1.1×10(−8)). Association with the ORMDL3/GSDMB locus on chromosome 17q21 was specific to childhood-onset disease (rs2305480, P=6×10(−23)). Only HLA-DR showed a significant genomewide association with the total serum IgE concentration, and loci strongly associated with IgE levels were not associated with asthma. CONCLUSIONS Asthma is genetically heterogeneous. A few common alleles are associated with disease risk at all ages. Implicated genes suggest a role for communication of epithelial damage to the adaptive immune system and activation of airway inflammation. Variants at the ORMDL3/GSDMB locus are associated only with childhood-onset disease. Elevation of total serum IgE levels has a minor role in the development of asthma. (Funded by the European Commission and others.)

Genetic variants regulating ORMDL3 expression contribute to the risk of childhood asthma.

Asthma is caused by a combination of poorly understood genetic and environmental factors. We have systematically mapped the effects of single nucleotide polymorphisms (SNPs) on the presence of childhood onset asthma by genome-wide association. We characterized more than 317,000 SNPs in DNA from 994 patients with childhood onset asthma and 1,243 non-asthmatics, using family and case-referent panels. Here we show multiple markers on chromosome 17q21 to be strongly and reproducibly associated with childhood onset asthma in family and case-referent panels with a combined P value of P < 10-12. In independent replication studies the 17q21 locus showed strong association with diagnosis of childhood asthma in 2,320 subjects from a cohort of German children (P = 0.0003) and in 3,301 subjects from the British 1958 Birth Cohort (P = 0.0005). We systematically evaluated the relationships between markers of the 17q21 locus and transcript levels of genes in Epstein–Barr virus (EBV)-transformed lymphoblastoid cell lines from children in the asthma family panel used in our association study. The SNPs associated with childhood asthma were consistently and strongly associated (P < 10-22) in cis with transcript levels of ORMDL3, a member of a gene family that encodes transmembrane proteins anchored in the endoplasmic reticulum. The results indicate that genetic variants regulating ORMDL3 expression are determinants of susceptibility to childhood asthma.

A General Test of Association for Quantitative Traits in Nuclear Families

High-resolution mapping is an important step in the identification of complex disease genes. In outbred populations, linkage disequilibrium is expected to operate over short distances and could provide a powerful fine-mapping tool. Here we build on recently developed methods for linkage-disequilibrium mapping of quantitative traits to construct a general approach that can accommodate nuclear families of any size, with or without parental information. Variance components are used to construct a test that utilizes information from all available offspring but that is not biased in the presence of linkage or familiality. A permutation test is described for situations in which maximum-likelihood estimates of the variance components are biased. Simulation studies are used to investigate power and error rates of this approach and to highlight situations in which violations of multivariate normality assumptions warrant the permutation test. The relationship between power and the level of linkage disequilibrium for this test suggests that the method is well suited to the analysis of dense maps. The relationship between power and family structure is investigated, and these results are applicable to study design in complex disease, especially for late-onset conditions for which parents are usually not available. When parental genotypes are available, power does not depend greatly on the number of offspring in each family. Power decreases when parental genotypes are not available, but the loss in power is negligible when four or more offspring per family are genotyped. Finally, it is shown that, when siblings are available, the total number of genotypes required in order to achieve comparable power is smaller if parents are not genotyped.

A genome-wide association study of global gene expression

We have created a global map of the effects of polymorphism on gene expression in 400 children from families recruited through a proband with asthma. We genotyped 408,273 SNPs and identified expression quantitative trait loci from measurements of 54,675 transcripts representing 20,599 genes in Epstein-Barr virus–transformed lymphoblastoid cell lines. We found that 15,084 transcripts (28%) representing 6,660 genes had narrow-sense heritabilities (H2) > 0.3. We executed genome-wide association scans for these traits and found peak lod scores between 3.68 and 59.1. The most highly heritable traits were markedly enriched in Gene Ontology descriptors for response to unfolded protein (chaperonins and heat shock proteins), regulation of progression through the cell cycle, RNA processing, DNA repair, immune responses and apoptosis. SNPs that regulate expression of these genes are candidates in the study of degenerative diseases, malignancy, infection and inflammation. We have created a downloadable database to facilitate use of our findings in the mapping of complex disease loci.

GOLD—Graphical Overview of Linkage Disequilibrium

SUMMARY We describe a software package that provides a graphical summary of linkage disequilibrium in human genetic data. It allows for the analysis of family data and is well suited to the analysis of dense genetic maps. AVAILABILITY http://www.well.ox.ac.uk/asthma/GOLD CONTACT: goncalo@well.ox.ac.uk

Exposure to Environmental Microorganisms and Childhood Asthma

BACKGROUND Children who grow up in environments that afford them a wide range of microbial exposures, such as traditional farms, are protected from childhood asthma and atopy. In previous studies, markers of microbial exposure have been inversely related to these conditions. METHODS In two cross-sectional studies, we compared children living on farms with those in a reference group with respect to the prevalence of asthma and atopy and to the diversity of microbial exposure. In one study--PARSIFAL (Prevention of Allergy-Risk Factors for Sensitization in Children Related to Farming and Anthroposophic Lifestyle)--samples of mattress dust were screened for bacterial DNA with the use of single-strand conformation polymorphism (SSCP) analyses to detect environmental bacteria that cannot be measured by means of culture techniques. In the other study--GABRIELA (Multidisciplinary Study to Identify the Genetic and Environmental Causes of Asthma in the European Community [GABRIEL] Advanced Study)--samples of settled dust from childrens rooms were evaluated for bacterial and fungal taxa with the use of culture techniques. RESULTS In both studies, children who lived on farms had lower prevalences of asthma and atopy and were exposed to a greater variety of environmental microorganisms than the children in the reference group. In turn, diversity of microbial exposure was inversely related to the risk of asthma (odds ratio for PARSIFAL, 0.62; 95% confidence interval [CI], 0.44 to 0.89; odds ratio for GABRIELA, 0.86; 95% CI, 0.75 to 0.99). In addition, the presence of certain more circumscribed exposures was also inversely related to the risk of asthma; this included exposure to species in the fungal taxon eurotium (adjusted odds ratio, 0.37; 95% CI, 0.18 to 0.76) and to a variety of bacterial species, including Listeria monocytogenes, bacillus species, corynebacterium species, and others (adjusted odds ratio, 0.57; 95% CI, 0.38 to 0.86). CONCLUSIONS Children living on farms were exposed to a wider range of microbes than were children in the reference group, and this exposure explains a substantial fraction of the inverse relation between asthma and growing up on a farm. (Funded by the Deutsche Forschungsgemeinschaft and the European Commission.).

Disordered Microbial Communities in Asthmatic Airways

Background A rich microbial environment in infancy protects against asthma [1], [2] and infections precipitate asthma exacerbations [3]. We compared the airway microbiota at three levels in adult patients with asthma, the related condition of COPD, and controls. We also studied bronchial lavage from asthmatic children and controls. Principal Findings We identified 5,054 16S rRNA bacterial sequences from 43 subjects, detecting >70% of species present. The bronchial tree was not sterile, and contained a mean of 2,000 bacterial genomes per cm2 surface sampled. Pathogenic Proteobacteria, particularly Haemophilus spp., were much more frequent in bronchi of adult asthmatics or patients with COPD than controls. We found similar highly significant increases in Proteobacteria in asthmatic children. Conversely, Bacteroidetes, particularly Prevotella spp., were more frequent in controls than adult or child asthmatics or COPD patients. Significance The results show the bronchial tree to contain a characteristic microbiota, and suggest that this microbiota is disturbed in asthmatic airways.

Reagent and laboratory contamination can critically impact sequence-based microbiome analyses

BackgroundThe study of microbial communities has been revolutionised in recent years by the widespread adoption of culture independent analytical techniques such as 16S rRNA gene sequencing and metagenomics. One potential confounder of these sequence-based approaches is the presence of contamination in DNA extraction kits and other laboratory reagents.ResultsIn this study we demonstrate that contaminating DNA is ubiquitous in commonly used DNA extraction kits and other laboratory reagents, varies greatly in composition between different kits and kit batches, and that this contamination critically impacts results obtained from samples containing a low microbial biomass. Contamination impacts both PCR-based 16S rRNA gene surveys and shotgun metagenomics. We provide an extensive list of potential contaminating genera, and guidelines on how to mitigate the effects of contamination.ConclusionsThese results suggest that caution should be advised when applying sequence-based techniques to the study of microbiota present in low biomass environments. Concurrent sequencing of negative control samples is strongly advised.

Mapping complex disease traits with global gene expression

Variation in gene expression is an important mechanism underlying susceptibility to complex disease. The simultaneous genome-wide assay of gene expression and genetic variation allows the mapping of the genetic factors that underpin individual differences in quantitative levels of expression (expression QTLs; eQTLs). The availability of systematically generated eQTL information could provide immediate insight into a biological basis for disease associations identified through genome-wide association (GWA) studies, and can help to identify networks of genes involved in disease pathogenesis. Although there are limitations to current eQTL maps, understanding of disease will be enhanced with novel technologies and international efforts that extend to a wide range of new samples and tissues.