Whole genome identity-by-descent determination

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• High-throughput genotyping assays generate single nucleotide polymorphism (SNP) data for genetic studies.
• Pedigree datasets use unphased genotype data to infer haplotypes based on Mendelian inheritance.
• Haplotype analysis is crucial for locating chromosomal regions in genetic linkage studies.

Purpose of the Study:

• To develop a flexible whole genome haplotyping algorithm accommodating ungenotyped founders in pedigrees.
• To efficiently determine all distinct haplotype allele identity-by-descent (IBD) sharings, irrespective of the total number of haplotyping solutions.
• To provide a computational tool (iBDD) for advanced genome-wide genetic studies.

Main Methods:

• Developed a cubic time whole genome haplotyping algorithm minimizing zero-recombination haplotype blocks.
• Implemented an algorithm to determine distinct haplotype allele IBD sharings in linear time relative to the number of solutions.
• Utilized a computer program, iBDD, for the haplotyping and IBD sharing analysis.

Main Results:

• The algorithm successfully relaxed pedigree structure requirements to include ungenotyped founders.
• Despite trillions of potential haplotyping solutions, only thousands of distinct haplotype allele IBD sharings were identified.
• The iBDD program efficiently returned all distinct IBD sharings for downstream analysis.

Conclusions:

• The iBDD algorithm provides a robust method for haplotyping and IBD sharing analysis in complex pedigrees.
• This approach significantly enhances the feasibility of genome-wide genetic linkage and association studies.
• iBDD offers a scalable solution for handling vast amounts of genetic data and complex family structures.