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Prof Richard Mott
210A Darwin Building
UCL Genetics Institute
UCL Department of Genetics, Evolution & Environment
Tel: 020 3108 4005
Prof Richard Mott profile picture
  • Weldon Professor of Computational and Statistical Genetics
  • Genetics, Evolution & Environment
  • Div of Biosciences
  • Faculty of Life Sciences

When an undergraduate I read Mathematics at Cambridge, followed by an MSc in Biometry at Reading University. I gained my PhD in 1989, on the Statistics of DNA Sequence Homologies, which was supervised by Tom Kirkwood (MRC NIMR London) and Robert Curnow (Reading). This was followed by  post-doc at NIMR on protein sequence alignment.

In 1991 I moved fields to work on physical genome mapping with Hans Lehrach, ICRF London (now CRUK). I developed software for constructing some of the first physical maps (Mott et al, 1993), including those of S. pombe (Maier at al, 1992, Hoheisel et al 1993), and helped build the human physical map used to clone Huntingtin (Baxendale et al, 1993). I moved to the Sanger Centre in 1995 to create the CAFtools sequence assembly software (Dear et al, 1998 Genome Research) for the Human Genome Project, used extensively to automate the production of finished sequence. I also devised one of the first algorithms for spliced alignment of ESTs to genomic DNA (Mott 1997 CABIOS). In 1997 I moved to SmithKline Beecham Pharmaceuticals; with Roger Tribe (Warwick), I devised a novel approach to the statistics of gapped protein sequence alignments (Mott and Tribe 1999 J Comp Biol, Mott 2000 J Mol Biol) and generalised it to non-affine gap penalties (Mott 1999 Bioinformatics).

In 1999 I joined the Wellcome Trust Centre for Human Genetics, Oxford, eventually becoming Professor by Research. There I made various contributions to the computational analysis of biological data, e.g. protein sequence similarities (Mott 2000), protein subcellular localisation (Mott et al, 2002 Genome Research), DNA- protein binding (Udalova et al, 2002 PNAS), SNP tagging (Ackerman et al, 2004), genetic mapping (Mott and Flint 2002, Valdar et al, 2003), replication timing (Wodefine et al, 2004 Hum Mol Genetics) and mouse genome assembly (Waterston et al, 2003 Nature). However, most of my research work was in analysis of complex traits in rodent models (Valdar et al, 2006, Baud et al, 2013); I developed the HAPPY software (Mott et al 2000 PNAS, Yalcin et al 2005 Genetics), characterised the haplotype structure of the mouse genome (Yalcin et al, 2004 PNAS) and helped identify one of the first quantitative trait genes for behaviour (Yalcin et al, 2004 Nature Genetics)

I also co-led the effort to breed the mouse collaborative cross (Durrant et al, 2011 Genome Research) and collaborated in the sequencing of inbred mouse strains (Keane et al, 2011 Nature, Agam et al, 2011 Nature). I developed similar programs in the  plant Arabidopsis thaliana (Kover et al, 2009 PLoS Genetics, Gan et al, 2011 Nature). My most recent major work has been an analysis of parent of origin effects in mice (Mott et al, 2014 Cell). I am also a member of the CONVERGE consortium which identified the first replicated genetic loci associated with major depression (Na et al 2015 Nature).

Since 2015 I have been Weldon Professor of Computational Genetics at University College London.

Research Summary

I have worked on many aspects of bioinformatics and statistical genetics, but much of my research since 2000 has concerned the statistical genetic analysis of populations - either animal or plant - descended from multiple inbred founders, often called Multi-Parent Populations (MPPs). MPP chromosomes are mosaics of the founders, and this observation can be used to investigate the genetic architecture of complex traits. These centre around how genetic variation at a locus is associated with a phenotype - for example whether it is caused by single or by multiple linked variants (Baud et al 2013 Nat Genet), and whether the parent-of-origin of an allele modulates its phenotypic effect (Mott et al 2015 Cell). To do this, I developed an analysis framework based on decomposing the genomes of individuals into probabilistic mosaics of the population founders (Mott et al 2000, PNAS, Yalcin et al 2005 Genetics, Durrant et al 2010 Genetics). 

With collaborators, I developed genetic reference MPPs, that are ideal for genetic analysis using this framework. These include the Collaborative Cross mouse reference population (Durrrant et al 2011 Genome Research, Aylor et al 2011 Genome Research) and the Arabidopsis thaliana MAGIC lines (Kover et al 2009 PLoS Genetics) and the wheat NIAB DIVERSE MAGIC. I have also applied these methods to the study of quantitative genetics in heterogeneous stock mice (Valdar et al 2006 Nature Genetics) and rats (Baud et al 2013 Nature Genetics). I collaborated in the sequencing of the founder genomes (Keane et al 2011 Nature, Gan et al 2011 Nature). I used these methods to dissect the genetic architecture of parent-of-origin effects (Mott et al 2014 Cell). Our recent review (Scott et al 2020 Heredity) surveys thee state of the art of crop MPPs.

In human genetics, with the CONVERGE consortium I helped analyse human case-control data leading to the first replicated discovery of loci associated with major depressive disorder (Na et al 2015 Nature), and the link between mitochondria and depression (Na et al 2015 Current Biology).

My current research includes an analysis of structural variation based on treating structural variants as quantitative traits (Imprialou et al 2017, Genetics). I have two BBSRC research grants analysing MAGIC populations of wheat (BB/M011585/1 with NIAB, Cambridge, just completed), chickpea and rice (GCRF-funded BB/P024726/1 with ICRISAT, India and IRRI, Philippines). 

I have recently begun research into ancient crop genomes (Scott et al 2019, Nature Plants). We sequenced an ancient emmer wheat specimen from the UCL Petrie Museum of Egyptian Archaeology and show that, among other things, that wheat grown in Egypt 3,000 years ago carried same principle domestication alleles as does modern emmer wheat.

Recently I published a method for homomorphic genotype encryption (Mott et al 2020 Genetics) based on random orthogonal matrices as encryption keys.

I have further BBSRC funded research starting 2020 on non-additive quantitative genetics in Mammals (BBSRC BB/S017372/1, with Jiangxi Agricultural University, China) and on the genetic architecture of protein abundance in plants (BBSRC LoLa BB/T002182/1, with Rothamsted
and Cambridge.

Teaching Summary

I lecture on the courses 

BIOL0029 Computational Biology (2nd years) 

BIOL0034 Applications of Human Genetics (3rd years and Masters)

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