Prof Richard F Mott
| Research Area: | Bioinformatics & Stats (inc. Modelling and Computational Biology) |
|---|---|
| Technology Exchange: | Bioinformatics, Computational biology, SNP typing, Statistical genetics and Transcript profiling |
| Keywords: | QTL, bioinformatics, disease mapping and comparative genomics |
| Web Links: |
The Bioinformatics and Statistical Genetics group functions to support the disease gene cloning projects within the Wellcome Trust Centre for Human Genetics, and to maintain independent research in development of methods, algorithms and software for mapping multifactorial trait loci.
The group has current research foci in the areas of comparative genomics, ancestral haplotype construction, database development, QTL linkage and association methods, variability in patterns of linkage disequilibrium, microarray analysis and multivariate modelling of quantitative traits.
My own research focusses on the analysis of complex traits in mouse models of human disease, and in other model organisms
| Name | Department | Institution | Country |
|---|---|---|---|
| Prof Jonathan Flint | Wellcome Trust Centre for Human Genetics | Oxford University | UK |
| Prof Chris Holmes | Department of Statistics, | University of Oxford | UK |
| Nicholas Harberd | University of Oxford | UK | |
| Paula Kover | University of Manchester | UK | |
| Fuad Iraqi | Tel Aviv University | Israel | |
| Irina Udalova | Imperial College, London | UK | |
| Janet Thornton | European Bioinformatics Institute | UK |
2006. Genome-wide genetic association of complex traits in heterogeneous stock mice. Nat Genet, 38 (8), pp. 879-887. Read abstract | Read more
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. Hide abstract
2005. Using progenitor strain information to identify quantitative trait nucleotides in outbred mice. Genetics, 171 (2), pp. 673-681. Read abstract | Read more
We have developed a fast and economical strategy for dissecting the genetic architecture of quantitative trait loci at a molecular level. The method uses two pieces of information: mapping data from crosses that involve more than two inbred strains and sequence variants in the progenitor strains within the interval containing a quantitative trait locus (QTL). By testing whether the strain distribution pattern in the progenitor strains is consistent with the observed genetic effect of the QTL we can assign a probability that any sequence variant is a quantitative trait nucleotide (QTN). It is not necessary to genotype the animals except at a skeleton of markers; the genotypes at all other polymorphisms are estimated by a multipoint analysis. We apply the method to a 4.8-Mb region on mouse chromosome 1 that contains a QTL influencing anxiety segregating in a heterogeneous stock and show that, under the assumption that a single QTN is present and lies in a region conserved between the human and mouse genomes, it is possible to reduce the number of variants likely to be the quantitative trait nucleotide from many thousands to <20. Hide abstract
2004. Genetic dissection of a behavioral quantitative trait locus shows that Rgs2 modulates anxiety in mice. Nat Genet, 36 (11), pp. 1197-1202. Read abstract | Read more
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. Hide abstract
2004. Unexpected complexity in the haplotypes of commonly used inbred strains of laboratory mice. Proc Natl Acad Sci U S A, 101 (26), pp. 9734-9739. Read abstract | Read more
Investigation of sequence variation in common inbred mouse strains has revealed a segmented pattern in which regions of high and low variant density are intermixed. Furthermore, it has been suggested that allelic strain distribution patterns also occur in well defined blocks and consequently could be used to map quantitative trait loci (QTL) in comparisons between inbred strains. We report a detailed analysis of polymorphism distribution in multiple inbred mouse strains over a 4.8-megabase region containing a QTL influencing anxiety. Our analysis indicates that it is only partly true that the genomes of inbred strains exist as a patchwork of segments of sequence identity and difference. We show that the definition of haplotype blocks is not robust and that methods for QTL mapping may fail if they assume a simple block-like structure. Hide abstract
2004. Quantitative high-throughput analysis of transcription factor binding specificities. Nucleic Acids Res, 32 (4), pp. e44. Read abstract | Read more
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. Hide abstract
1999. Approximate statistics of gapped alignments. J Comput Biol, 6 (1), pp. 91-112. Read abstract | Read more
A heuristic approximation to the score distribution of gapped alignments in the logarithmic domain is presented. The method applies to comparisons between random, unrelated protein sequences, using standard score matrices and arbitrary gap penalties. It is shown that gapped alignment behavior is essentially governed by a single parameter, alpha, depending on the penalty scheme and sequence composition. This treatment also predicts the position of the transition point between logarithmic and linear behavior. The approximation is tested by simulation and shown to be accurate over a range of commonly used substitution matrices and gap-penalties. Hide abstract
1997. EST_GENOME: a program to align spliced DNA sequences to unspliced genomic DNA. Comput Appl Biosci, 13 (4), pp. 477-478.
1997. Instability of highly expanded CAG repeats in mice transgenic for the Huntington's disease mutation. Nat Genet, 15 (2), pp. 197-200. Read abstract | Read more
Six inherited neurodegenerative diseases are caused by a CAG/polyglutamine expansion, including spinal and bulbar muscular atrophy (SBMA), Huntington's disease (HD), spinocerebellar ataxia type 1 (SCA1), dentatorubral pallidoluysian atrophy (DRPLA) Machado-Joseph disease (MJD or SCA3) and SCA2. Normal and expanded HD allele sizes of 6-39 and 35-121 repeats have been reported, and the allele distributions for the other diseases are comparable. Intergenerational instability has been described in all cases, and repeats tend to be more unstable on paternal transmission. This may present as larger increases on paternal inheritance as in HD, or as a tendency to increase on male and decrease on female transmission as in SCA1 (ref. 15). Somatic repeat instability is also apparent and appears most pronounced in the CNS. The major exception is the cerebellum, which in HD, DRPLA, SCA1 and MJD has a smaller repeat relative to the other brain regions tested. Of non-CNS tissues, instability was observed in blood, liver, kidney and colon. A mouse model of CAG repeat instability would be helpful in unravelling its molecular basis although an absence of CAG repeat instability in transgenic mice has so far been reported. These studies include (CAG) in the androgen receptor cDNA, (CAG) in the HD cDNA, (CAG) in the SCA1 cDNA, (CAG) in the SCA3 cDNA and as an isolated (CAG) tract. Hide abstract
