Abstract
Homozygosity mapping is a powerful procedure that is capable of detecting recessive disease-causing genes in a few patients from families with a history of inbreeding. We report here a homozygosity mapping algorithm for high-density single nucleotide polymorphism arrays that is able to (i) correct genotyping errors, (ii) search for autozygous segments genome-wide through regions with runs of homozygous SNPs, (iii) check the validity of the inbreeding history, and (iv) calculate the probability of the disease-causing gene being located in the regions identified. The genotyping error correction restored an average of 94.2% of the total length of all regions with run of homozygous SNPs, and 99.9% of the total length of them that were longer than 2 cM. At the end of the analysis, we would know the probability that regions identified contain a disease-causing gene, and we would be able to determine how much effort should be devoted to scrutinizing the regions. We confirmed the power of this algorithm using 6 patients with Siiyama-type α1-antitrypsin deficiency, a rare autosomal recessive disease in Japan. Our procedure will accelerate the identification of disease-causing genes using high-density SNP array data.
Highlights
Identification of the genetic factors underlying disease causation provides crucial information for disease prevention and treatment
The usable implementation should (i) correct genotyping errors because thousands of single-nucleotide polymorphism (SNP) are mistyped per high-density SNP array, adversely affecting the homozygosity mapping analysis; (ii) search for autozygous segment (AS) genome-wide; (iii) check the validity of the inbreeding history, which is vital for homozygosity mapping but is often erroneous, and (iv) calculate the probability of the disease-causing gene being located in the regions identified
Strategy Our aim was to establish an algorithm for homozygosity mapping that uses SNP genotyping data obtained by high-density arrays, is equipped by a powerful genotyping error correction algorithm, detects ASs genomewide, allows investigation into the family inbreeding history, and is able to calculate the probability that the identified regions contain the target gene
Summary
Identification of the genetic factors underlying disease causation provides crucial information for disease prevention and treatment. Homozygosity mapping [3] enables the detection of recessive disease-causing genes in a few patients from families with a history of inbreeding; this mapping technique is especially useful for the detection of rare genes With this technique, chromosomal segments in which all polymorphic markers are homozyogous are considered autozygous segment (AS) [4]. The usable implementation should (i) correct genotyping errors because thousands of SNPs are mistyped per high-density SNP array, adversely affecting the homozygosity mapping analysis; (ii) search for ASs genome-wide; (iii) check the validity of the inbreeding history, which is vital for homozygosity mapping but is often erroneous, and (iv) calculate the probability of the disease-causing gene being located in the regions identified. At the end of the analysis, we would know the probability that regions identified contain a disease-causing gene, and we would be able to determine how much effort should be devoted to scrutinizing the regions
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