Background
One to two percent of all children are born with a developmental disorder, such as a learning disability or a heart defect, as a result of errors in embryogenesis and early neurodevelopment. These disorders make a major contribution to paediatric hospital admissions and mortality. Surgical repair of congenital heart defects has decreased mortality rates considerably, but as a result of passing on faulty genes from one generation to the next, the prevalence of congenital heart disease is increasing. Accurate diagnosis is essential to inform patient management, prognosis and medical care, and give families the opportunity for prenatal diagnosis.
Many of these disorders are genetic in origin and the increasing resolution of genomic technologies has enabled substantial increases in diagnosis rates in recent years. Nevertheless, most children with developmental disorders do not currently receive a genetic diagnosis.
The advent of cost-efficient genome sequencing technologies raises the prospect of discovering many currently unknown disease genes and increasing diagnosis rates dramatically. However, our ability to discover millions of genetic variants in every genome, is running far ahead of our ability to accurately identify individual disease-causing variants. This interpretation gap is the fundamental challenge in human genetics today.
Research
Over the past five years we have focused on characterising genomic structural variation in human populations and its role in disease. During the next five years we are expanding our focus to all forms of genetic variation made accessible by new sequencing technologies, and to translate our better understanding into improved clinical diagnosis rates. We find that a deep appreciation of population variation is key to interpreting the pathogenicity of variants seen in patients.
In collaboration with UK and international clinicians, over the next five years, we are investigating the genetic causes of developmental disorders in over 15,000 children and their families. The scale of this research enables us to identify genetic variants that can cause a variety of different developmental disorders. In addition to a general interest in diverse developmental disorders, our group has a specific goal to elucidate the genetic architecture of congenital heart disease.
Many developmental disorders are caused by one or more of the 50-100 new mutations that arise in each genome every generation. The mutation rates of the handful of different molecular processes that generate this variation can be thought of as quantitative traits, like height, that vary among members of the population as a result of genetic and environmental factors. We also know that mutation rates can vary dramatically on the basis of age and sex. For example, it has been proposed that, on average, the majority (more than 80 per cent) of new mutations arise in the sperm of the father, with only a minority (less than 20 per cent) coming from the egg of the mother. Despite the clinical importance of achieving a fuller understanding of the factors influencing mutation rates, little is known about how and why mutation rates vary from gamete to gamete and from individual to individual. Through novel statistical analyses of genome sequences of parents and children we are increasing our comprehension of how these fundamental mutation processes operate, and how they underpin the variation we see in patients in the clinic and in the population as a whole.
Resources
CNV Project - aims to characterise structural variation in the human genome, and integrate this knowledge into disease and population genetic studies
Collaborations
- UK10K - aims to uncover the role of rare genetic variants in health and disease by studying the genetic code of 10,000 people in fine detail
- Genetic Origins of Congenital Heart Disease study - aims to understand the genetic basis of congenital heart disease in children and adults
Selected publications
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Characterising and predicting haploinsufficiency in the human genome.
PLoS genetics 2010;6;10;e1001154
PUBMED: 20976243; PMC: 2954820; DOI: 10.1371/journal.pgen.1001154
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Mutation spectrum revealed by breakpoint sequencing of human germline CNVs.
Nature genetics 2010;42;5;385-91
PUBMED: 20364136; PMC: 3428939; DOI: 10.1038/ng.564
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Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls.
Nature 2010;464;7289;713-20
PUBMED: 20360734; PMC: 2892339; DOI: 10.1038/nature08979
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Origins and functional impact of copy number variation in the human genome.
Nature 2010;464;7289;704-12
PUBMED: 19812545; PMC: 3330748; DOI: 10.1038/nature08516
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Large, rare chromosomal deletions associated with severe early-onset obesity.
Nature 2010;463;7281;666-70
PUBMED: 19966786; PMC: 3108883; DOI: 10.1038/nature08689
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A robust statistical method for case-control association testing with copy number variation.
Nature genetics 2008;40;10;1245-52
PUBMED: 18776912; PMC: 2784596; DOI: 10.1038/ng.206
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Germline rates of de novo meiotic deletions and duplications causing several genomic disorders.
Nature genetics 2008;40;1;90-5
PUBMED: 18059269; PMC: 2669897; DOI: 10.1038/ng.2007.40
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Relative impact of nucleotide and copy number variation on gene expression phenotypes.
Science (New York, N.Y.) 2007;315;5813;848-53
PUBMED: 17289997; PMC: 2665772; DOI: 10.1126/science.1136678
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Global variation in copy number in the human genome.
Nature 2006;444;7118;444-54
PUBMED: 17122850; PMC: 2669898; DOI: 10.1038/nature05329
Team
Team members
Members
- Stephen Clayton
- Bioinformatician
Stephen Clayton
- Bioinformatician
I studied Biochemistry at the University of York and went on to do a MRes in Bioinformatics.
Research
I am developing pipelines and tools for the DDD project.

Dr Matthew Hurles