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Utilization of a SNP microarray to detect uniparental disomy: Implications and outcomes
Alexandra Arreola1, Gloria Haskell1, Inder Gadi1
1Center for Molecular Biology and Pathology, Labcorp, Research Triangle Park, NC.
Summary
Single-nucleotide polymorphism (SNP) microarray analysis effectively detects uniparental disomy (UPD) using Mendelian Inheritance Error (MIE) values in trios and heterozygous SNP percentages in duos. This method aids in diagnosing genetic conditions related to UPD.
Area of Science:
- Genetics
- Genomic analysis
- Molecular diagnostics
Background:
- Uniparental disomy (UPD) is a condition where an individual inherits two copies of a chromosome from only one parent.
- Accurate detection of UPD is crucial for diagnosing various genetic disorders.
- Single-nucleotide polymorphism (SNP) microarray analysis offers a potential method for UPD detection.
Purpose of the Study:
- To evaluate the effectiveness of SNP microarray analysis in identifying UPD.
- To assess the utility of SNP microarray in both trio and duo family study designs.
- To establish diagnostic criteria for UPD detection using SNP microarray data.
Main Methods:
- Established Mendelian Inheritance Error (MIE) values to differentiate UPD from biparental inheritance in 124 patients.
- Utilized trio data (proband and both parents) and duo data (proband and one parent).
- Calculated the percentage of heterozygous (AB) SNPs contributed by the parent in duo analyses.
Main Results:
- In trios, distinct MIE ranges identified UPD (MIE ≈ 0.02) versus biparental inheritance (MIE ≈ 8.76).
- In duos, a heterozygous SNP percentage (AB%) of approximately 52.0% indicated biparental inheritance.
- In duos, an AB% of approximately 97.2% was consistent with UPD, demonstrating the method's utility.
Conclusions:
- SNP microarray analysis is a valuable tool for detecting UPD.
- Specific MIE ranges and AB% calculations reliably distinguish UPD from biparental inheritance.
- The diagnostic yield for UPD testing can be limited by the detection of large homozygous regions in routine microarray analysis, impacting clinical practice.
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