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Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
Published on: January 9, 2020
SNP haplotype mapping in a small ALS family
Katherine A Dick Krueger1, Shoji Tsuji, Yoko Fukuda
1Department of Genetics, University of Minnesota, Minneapolis, Minnesota, United States of America.
This study validates using high-density SNP arrays with haploid cells to map single-gene disorders in small families. This approach enhances genetic analysis, identifying candidate regions for diseases like amyotrophic lateral sclerosis (ALS).
Area of Science:
- Genetics
- Genomics
- Molecular Biology
Background:
- Identifying genes for monogenic disorders is crucial for understanding human disease mechanisms.
- A trend away from studying single-gene disorders exists due to challenges in mapping small families.
- New tools are needed to effectively map remaining single-gene disorders.
Purpose of the Study:
- To experimentally validate the use of high-density single nucleotide polymorphism (SNP) arrays and haploid cell lines for defining genome-wide haplotypes.
- To assess the accuracy of SNP arrays in predicting chromosomal haplotypes.
- To demonstrate the utility of these methods for mapping single-gene disorders in small families, using amyotrophic lateral sclerosis (ALS) as a prototype.
Main Methods:
- Generation of haploid cell line panels.
- Performing a 5 centimorgan (cM) short tandem repeat polymorphism (STRP) genome scan.
- Experimental determination of haplotypes for entire chromosomes.
- Comparison of experimentally derived haplotypes with in silico haplotypes predicted from SNP arrays using diploid DNA.
Main Results:
- High-density SNP arrays accurately predict chromosomal haplotypes.
- Haplotype information significantly enhances genetic analysis in small families.
- The methods precisely identified 12 candidate intervals shared by all 5 affected individuals in the ALS family.
Conclusions:
- Readily available tools, including SNP arrays and haploid cell lines, can maximize genetic information for mapping single-gene disorders.
- This approach provides a valuable first step for genetic mapping in small families.
- The validated methods offer a powerful strategy to overcome limitations in studying previously unmapped Mendelian disorders.
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