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Biomedical subjects

Richard Mott

Publications and source records attributed to Richard Mott.

At least 19 recordsLinked to original sources

Genetic and environmental effects on complex traits in mice.

The interaction between genotype and environment is recognized as an important source of experimental variation when complex traits are measured in the mouse, but the magnitude of that interaction has not often been measured. From a study of 2448 genetically heterogeneous mice, we report the heritability of 88 complex traits that include models of human disease (asthma, type 2 diabetes mellitus, obesity, and anxiety) as well as immunological, biochemical, and hematological phenotypes. We show that environmental and physiological covariates are involved in an unexpectedly large number of significant interactions with genetic background. The 15 covariates we examined have a significant effect on behavioral and physiological tests, although they rarely explain >10% of the variation. We found that interaction effects are more frequent and larger than the main effects: half of the interactions explained >20% of the variance and in nine cases exceeded 50%. Our results indicate that assays of gene function using mouse models should take into account interactions between gene and environment.

Animals↗

Genome-wide genetic association of complex traits in heterogeneous stock mice.

Difficulties in fine-mapping quantitative trait loci (QTLs) are a major impediment to progress in the molecular dissection of complex traits in mice. Here we show that genome-wide high-resolution mapping of multiple phenotypes can be achieved using a stock of genetically heterogeneous mice. We developed a conservative and robust bootstrap analysis to map 843 QTLs with an average 95% confidence interval of 2.8 Mb. The QTLs contribute to variation in 97 traits, including models of human disease (asthma, type 2 diabetes mellitus, obesity and anxiety) as well as immunological, biochemical and hematological phenotypes. The genetic architecture of almost all phenotypes was complex, with many loci each contributing a small proportion to the total variance. Our data set, freely available at http://gscan.well.ox.ac.uk, provides an entry point to the functional characterization of genes involved in many complex traits.

Animals↗

Genomic clusters, putative pathogen recognition molecules, and antimicrobial genes are induced by infection of C. elegans with M. nematophilum.

The interaction between the nematode Caenorhabditis elegans and a Gram-positive bacterial pathogen, Microbacterium nematophilum, provides a model for an innate immune response in nematodes. This pathogen adheres to the rectal and post-anal cuticle of the worm, causing slowed growth, constipation, and a defensive swelling response of rectal hypodermal cells. To explore the genomic responses that the worm activates after pathogenic attack we used microarray analysis of transcriptional changes induced after 6-h infection, comparing virulent with avirulent infection. We defined 89 genes with statistically significant expression changes of at least twofold, of which 68 were up-regulated and 21 were down-regulated. Among the former, those encoding C-type lectin domains were the most abundant class. Many of the 89 genes exhibit genomic clustering, and we identified one large cluster of 62 genes, of which most were induced in response to infection. We tested 41 of the induced genes for involvement in immunity using mutants or RNAi, finding that six of these are required for the swelling response and five are required more generally for defense. Our results indicate that C-type lectins and other putative pathogen-recognition molecules are important for innate immune defense in C. elegans. We also found significant induction of genes encoding lysozymes, proteases, and defense-related proteins, as well as various domains of unknown function. The genes induced during infection by M. nematophilum appear largely distinct from genes induced by other pathogens, suggesting that C. elegans mounts pathogen-specific responses to infection.

Animals↗

An integrated system for genetic analysis.

BACKGROUND: Large-scale genetic mapping projects require data management systems that can handle complex phenotypes and detect and correct high-throughput genotyping errors, yet are easy to use. DESCRIPTION: We have developed an Integrated Genotyping System (IGS) to meet this need. IGS securely stores, edits and analyses genotype and phenotype data. It stores information about DNA samples, plates, primers, markers and genotypes generated by a genotyping laboratory. Data are structured so that statistical genetic analysis of both case-control and pedigree data is straightforward. CONCLUSION: IGS can model complex phenotypes and contain genotypes from whole genome association studies. The database makes it possible to integrate genetic analysis with data curation. The IGS web site http://bioinformatics.well.ox.ac.uk/project-igs.shtml contains further information.

Chromosome Mapping↗

A protocol for high-throughput phenotyping, suitable for quantitative trait analysis in mice.

Whole-genome genetic association studies in outbred mouse populations represent a novel approach to identifying the molecular basis of naturally occurring genetic variants, the major source of quantitative variation between inbred strains of mice. Measuring multiple phenotypes in parallel on each mouse would make the approach cost effective, but protocols for phenotyping on a large enough scale have not been developed. In this article we describe the development and deployment of a protocol to collect measures on three models of human disease (anxiety, type II diabetes, and asthma) as well as measures of mouse blood biochemistry, immunology, and hematology. We report that the protocol delivers highly significant differences among the eight inbred strains (A/J, AKR/J, BALBc/J, CBA/J, C3H/HeJ, C57BL/6 J, DBA/2 J, and LP/J), the progenitors of a genetically heterogeneous stock (HS) of mice. We report the successful collection of multiple phenotypes from 2000 outbred HS animals. The phenotypes measured in the protocol form the basis of a large-scale investigation into the genetic basis of complex traits in mice designed to examine interactions between genes and between genes and environment, as well as the main effects of genetic variants on phenotypes.

Animals↗

A high-resolution single nucleotide polymorphism genetic map of the mouse genome.

High-resolution genetic maps are required for mapping complex traits and for the study of recombination. We report the highest density genetic map yet created for any organism, except humans. Using more than 10,000 single nucleotide polymorphisms evenly spaced across the mouse genome, we have constructed genetic maps for both outbred and inbred mice, and separately for males and females. Recombination rates are highly correlated in outbred and inbred mice, but show relatively low correlation between males and females. Differences between male and female recombination maps and the sequence features associated with recombination are strikingly similar to those observed in humans. Genetic maps are available from http://gscan.well.ox.ac.uk/#genetic_map and as supporting information to this publication.

Animals↗

Simulating the collaborative cross: power of quantitative trait loci detection and mapping resolution in large sets of recombinant inbred strains of mice.

It has been suggested that the collaborative cross, a large set of recombinant inbred strains derived from eight inbred mouse strains, would be a powerful resource for the dissection of complex phenotypes. Here we use simulation to investigate the power of the collaborative cross to detect and map small genetic effects. We show that for a fixed population of 1000 individuals, 500 RI lines bred using a modified version of the collaborative cross design are adequate to map a single additive locus that accounts for 5% of the phenotypic variation to within 0.96 cM. In the presence of strong epistasis more strains can improve detection, but 500 lines still provide sufficient resolution to meet most goals of the collaborative cross. However, even with a very large panel of RILs, mapping resolution may not be sufficient to identify single genes unambiguously. Our results are generally applicable to the design of RILs in other species.

Animals↗

Screening for recently selected alleles by analysis of human haplotype similarity.

There is growing interest in the use of haplotype-based methods for detecting recent selection. Here, we describe a method that uses a sliding window to estimate similarity among the haplotypes associated with any given single-nucleotide polymorphism (SNP) allele. We used simulations of natural selection to provide estimates of the empirical power of the method to detect recently selected alleles and found it to be comparable in power to the popular long-range haplotype test and more powerful than methods based on nucleotide diversity. We then applied the method to a recently selected allele--the sickle mutation at the HBB locus--and found it to have a signal of selection that was significantly stronger than that of simulated models both with and without strong selection. Using this method, we also evaluated >4,000 SNPs on chromosome 20, indicating the applicability of the method to regional data sets.

Alleles↗

SW-ARRAY: a dynamic programming solution for the identification of copy-number changes in genomic DNA using array comparative genome hybridization data.

Comparative genome hybridization (CGH) to DNA microarrays (array CGH) is a technique capable of detecting deletions and duplications in genomes at high resolution. However, array CGH studies of the human genome noting false negative and false positive results using large insert clones as probes have raised important concerns regarding the suitability of this approach for clinical diagnostic applications. Here, we adapt the Smith-Waterman dynamic-programming algorithm to provide a sensitive and robust analytic approach (SW-ARRAY) for detecting copy-number changes in array CGH data. In a blind series of hybridizations to arrays consisting of the entire tiling path for the terminal 2 Mb of human chromosome 16p, the method identified all monosomies between 267 and 1567 kb with a high degree of statistical significance and accurately located the boundaries of deletions in the range 267-1052 kb. The approach is unique in offering both a nonparametric segmentation procedure and a nonparametric test of significance. It is scalable and well-suited to high resolution whole genome array CGH studies that use array probes derived from large insert clones as well as PCR products and oligonucleotides.

Algorithms↗

Genomewide analysis of the host response to malaria in Kenyan children.

Malaria is a global problem, and there is a critical need for further understanding of the disease process. When malarial parasites invade and develop within the bloodstream, they stimulate a profound host response whose main clinical sign is fever. To explore this response, we measured host gene expression in whole blood from Kenyan children hospitalized with either acute malaria or other febrile illnesses. Genomewide analysis of expression identified 2 principal gene-expression profiles related to neutrophil and erythroid activity. In addition to these general acute responses, a third gene-expression profile was associated with host parasitemia; mediators of erythrophagocytosis and cellular stress were notable components of this response. The delineation of subjects on the basis of patterns of gene expression provides a molecular perspective of the host response to malaria and further functional insight into the underlying processes of pathogenesis.

Child↗

Candidate-gene screening and association analysis at the autism-susceptibility locus on chromosome 16p: evidence of association at GRIN2A and ABAT.

Autism is a highly heritable neurodevelopmental disorder whose underlying genetic causes have yet to be identified. To date, there have been eight genome screens for autism, two of which identified a putative susceptibility locus on chromosome 16p. In the present study, 10 positional candidate genes that map to 16p11-13 were examined for coding variants: A2BP1, ABAT, BFAR, CREBBP, EMP2, GRIN2A, MRTF-B, SSTR5, TBX6, and UBN1. Screening of all coding and regulatory regions by denaturing high-performance liquid chromatography identified seven nonsynonymous changes. Five of these mutations were found to cosegregate with autism, but the mutations are not predicted to have deleterious effects on protein structure and are unlikely to represent significant etiological variants. Selected variants from candidate genes were genotyped in the entire International Molecular Genetics Study of Autism Consortium collection of 239 multiplex families and were tested for association with autism by use of the pedigree disequilibrium test. Additionally, genotype frequencies were compared between 239 unrelated affected individuals and 192 controls. Patterns of linkage disequilibrium were investigated, and the transmission of haplotypes across candidate genes was tested for association. Evidence of single-marker association was found for variants in ABAT, CREBBP, and GRIN2A. Within these genes, 12 single-nucleotide polymorphisms (SNPs) were subsequently genotyped in 91 autism trios (one affected individual and two unaffected parents), and the association was replicated within GRIN2A (Fisher's exact test, P<.0001). Logistic regression analysis of SNP data across GRIN2A and ABAT showed a trend toward haplotypic differences between cases and controls.

4-Aminobutyrate Transaminase↗

Strategies for mapping and cloning quantitative trait genes in rodents.

Over the past 15 years, more than 2,000 quantitative trait loci (QTLs) have been identified in crosses between inbred strains of mice and rats, but less than 1% have been characterized at a molecular level. However, new resources, such as chromosome substitution strains and the proposed Collaborative Cross, together with new analytical tools, including probabilistic ancestral haplotype reconstruction in outbred mice, Yin-Yang crosses and in silico analysis of sequence variants in many inbred strains, could make QTL cloning tractable. We review the potential of these strategies to identify genes that underlie QTLs in rodents.

Animals↗

Genetic dissection of a behavioral quantitative trait locus shows that Rgs2 modulates anxiety in mice.

Here we present a strategy to determine the genetic basis of variance in complex phenotypes that arise from natural, as opposed to induced, genetic variation in mice. We show that a commercially available strain of outbred mice, MF1, can be treated as an ultrafine mosaic of standard inbred strains and accordingly used to dissect a known quantitative trait locus influencing anxiety. We also show that this locus can be subdivided into three regions, one of which contains Rgs2, which encodes a regulator of G protein signaling. We then use quantitative complementation to show that Rgs2 is a quantitative trait gene. This combined genetic and functional approach should be applicable to the analysis of any quantitative trait.

Animals↗

Quantitative high-throughput analysis of transcription factor binding specificities.

We present a general high-throughput approach to accurately quantify DNA-protein interactions, which can facilitate the identification of functional genetic polymorphisms. The method tested here on two structurally distinct transcription factors (TFs), NF-kappaB and OCT-1, comprises three steps: (i) optimized selection of DNA variants to be tested experimentally, which we show is superior to selecting variants at random; (ii) a quantitative protein-DNA binding assay using microarray and surface plasmon resonance technologies; (iii) prediction of binding affinity for all DNA variants in the consensus space using a statistical model based on principal coordinates analysis. For the protein-DNA binding assay, we identified a polyacrylamide/ester glass activation chemistry which formed exclusive covalent bonds with 5'-amino-modified DNA duplexes and hindered non-specific electrostatic attachment of DNA. Full accessibility of the DNA duplexes attached to polyacrylamide-modified slides was confirmed by the high degree of data correlation with the electromobility shift assay (correlation coefficient 93%). This approach offers the potential for high-throughput determination of TF binding profiles and predicting the effects of single nucleotide polymorphisms on TF binding affinity. New DNA binding data for OCT-1 are presented.

Acrylic Resins↗

The Collaborative Cross, a community resource for the genetic analysis of complex traits.

The goal of the Complex Trait Consortium is to promote the development of resources that can be used to understand, treat and ultimately prevent pervasive human diseases. Existing and proposed mouse resources that are optimized to study the actions of isolated genetic loci on a fixed background are less effective for studying intact polygenic networks and interactions among genes, environments, pathogens and other factors. The Collaborative Cross will provide a common reference panel specifically designed for the integrative analysis of complex systems and will change the way we approach human health and disease.

Animals↗

Replication timing of the human genome.

We have developed a directly quantitative method utilizing genomic clone DNA microarrays to assess the replication timing of sequences during the S phase of the cell cycle. The genomic resolution of the replication timing measurements is limited only by the genomic clone size and density. We demonstrate the power of this approach by constructing a genome-wide map of replication timing in human lymphoblastoid cells using an array with clones spaced at 1 Mb intervals and a high-resolution replication timing map of 22q with an array utilizing overlapping sequencing tile path clones. We show a positive correlation, both genome-wide and at a high resolution, between replication timing and a range of genome parameters including GC content, gene density and transcriptional activity.

Base Composition↗

Recognizing the fold of a protein structure.

This paper reports a graph-theoretic program, GRATH, that rapidly, and accurately, matches a novel structure against a library of domain structures to find the most similar ones. GRATH generates distributions of scores by comparing the novel domain against the different types of folds that have been classified previously in the CATH database of structural domains. GRATH uses a measure of similarity that details the geometric information, number of secondary structures and number of residues within secondary structures, that any two protein structures share. Although GRATH builds on well established approaches for secondary structure comparison, a novel scoring scheme has been introduced to allow ranking of any matches identified by the algorithm. More importantly, we have benchmarked the algorithm using a large dataset of 1702 non-redundant structures from the CATH database which have already been classified into fold groups, with manual validation. This has facilitated introduction of further constraints, optimization of parameters and identification of reliable thresholds for fold identification. Following these benchmarking trials, the correct fold can be identified with the top score with a frequency of 90%. It is identified within the ten most likely assignments with a frequency of 98%. GRATH has been implemented to use via a server (http://www.biochem.ucl.ac.uk/cgi-bin/cath/Grath.pl). GRATH's speed and accuracy means that it can be used as a reliable front-end filter for the more accurate, but computationally expensive, residue based structure comparison algorithm SSAP, currently used to classify domain structures in the CATH database. With an increasing number of structures being solved by the structural genomics initiatives, the GRATH server also provides an essential resource for determining whether newly determined structures are related to any known structures from which functional properties may be inferred.

Algorithms↗