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Updated: Aug 23, 2025
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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
Published on: June 23, 2012
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Influences of rare copy-number variation on human complex traits
Margaux L A Hujoel1, Maxwell A Sherman2, Alison R Barton3
1Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Cell
|October 28, 2022
Summary
Researchers developed a new computational method to detect copy-number variants (CNVs) in the human genome. This approach identified numerous CNV-trait associations, revealing insights into gene dosage sensitivity and complex human traits.
Area of Science:
- Genomics
- Human Genetics
- Bioinformatics
Background:
- The human genome has numerous copy-number variants (CNVs), but their phenotypic effects are largely unknown.
- Previous methods, limited by SNP-array data, could only detect larger CNVs.
Purpose of the Study:
- To develop a more sensitive computational method for detecting CNVs.
- To analyze the associations between CNVs and quantitative traits using a large biobank cohort.
Main Methods:
- Developed a novel computational approach utilizing haplotype sharing within biobank cohorts.
- Applied the method to UK Biobank data to identify CNVs and analyze their associations with 56 quantitative traits.
Main Results:
- The new method significantly increased the detection of rare gene inactivation events caused by genomic structural variation.
- Identified 269 independent associations between CNVs and quantitative traits (p < 5 × 10⁻⁸).
- Identified putative target genes for nearly half of the loci, providing insights into gene dosage sensitivity.
Conclusions:
- Haplotype-informed analysis offers a powerful approach to sensitively detect CNVs.
- This method enhances understanding of the genetic basis of human complex traits and gene-trait relationships.
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