HomSI: a homozygous stretch identifier from next-generation sequencing data

Area of Science:

• Genomics
• Medical Genetics
• Bioinformatics

Background:

• Consanguineous families exhibit increased homozygosity, leading to a higher prevalence of recessive genetic diseases.
• Homozygosity mapping is a key technique for identifying disease genes in these families.
• Traditional methods involve SNP arrays for homozygosity and subsequent gene sequencing.

Purpose of the Study:

• To develop a novel computational tool for identifying homozygous regions using next-generation sequencing (NGS) data.
• To offer an efficient alternative to traditional homozygosity mapping methods.

Main Methods:

• Developed a new software tool that processes variant call format (*.vcf) files from deep sequencing data.
• The tool identifies homozygous genomic regions within the input data.

Main Results:

• The developed tool successfully identifies the majority of homozygous regions previously detected by microarray single nucleotide polymorphism (SNP) genotype data.
• This approach integrates homozygous region identification and mutation detection into a single sequencing experiment.

Conclusions:

• The novel tool provides an efficient method for identifying homozygous regions from deep sequencing data.
• This advancement can streamline the discovery of recessive disease genes in consanguineous populations.