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Published on: June 15, 2011
De novo mutations in regulatory elements in neurodevelopmental disorders
Patrick J Short1, Jeremy F McRae1, Giuseppe Gallone1
1Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK.
De novo mutations in regulatory elements, particularly in fetal brain-active regions, are a significant cause of neurodevelopmental disorders. This study estimates their contribution in patients lacking coding variants.
Area of Science:
- Genetics
- Developmental Biology
- Genomic Regulation
Background:
- Previously, 42% of severe developmental disorder cases were linked to de novo mutations in coding sequences.
- The role of de novo mutations in regulatory elements remains largely unexplored.
- Regulatory elements control gene expression and are crucial for development.
Purpose of the Study:
- To investigate the contribution of de novo mutations in regulatory elements to developmental disorders.
- To identify specific types of regulatory elements enriched for mutations in affected individuals.
- To estimate the prevalence and impact of these mutations in neurodevelopmental disorders.
Main Methods:
- Analysis of de novo mutations in three classes of putative regulatory elements in nearly 8,000 patients.
- Assessment of evolutionary conservation and functional activity (fetal brain-active elements).
- Statistical analysis to determine enrichment and estimate mutation rates.
Main Results:
- De novo mutations in highly conserved, fetal brain-active elements are significantly enriched in neurodevelopmental disorders.
- A twofold enrichment of recurrently mutated elements was observed.
- An estimated 1-3% of patients without coding variants carry pathogenic de novo mutations in these regulatory elements.
Conclusions:
- De novo mutations in regulatory elements, especially conserved fetal brain-active ones, are an important genetic cause of neurodevelopmental disorders.
- This finding expands the understanding of genetic underpinnings beyond coding regions.
- Combining functional and evolutionary data is crucial for identifying regulatory causes of genetic disorders.
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