Genomic estimates of Identity-By-Descent relationships in large scale data sets

Area of Science:

• Animal Genetics
• Quantitative Genetics
• Bioinformatics

Background:

• Genomic relationships and inbreeding are typically estimated using genetic drift (GRM), homozygosity (ROH), or Identity-By-Descent (IBD).
• A genomic IBD-based relationship matrix (Gla) uses linkage analysis to distinguish parental inheritances, replacing pedigree-based probabilities.
• Accurate estimation of genomic relationships is crucial for effective animal breeding and genetic management.

Purpose of the Study:

• To develop a fast approximate algorithm (FGla) for estimating the G la matrix in large pedigrees using dense marker genotypes.
• To compare the FGla-derived G la matrix with traditional methods (A, GRM, F ROH) in simulated and real cattle data.
• To assess the accuracy and unbiasedness of the FGla algorithm for genomic relationship and inbreeding estimation.

Main Methods:

• Developed FGla, a computationally efficient multipoint linkage analysis algorithm for estimating G la.
• Utilized dense marker genotypes to identify and impute parental inheritances of chromosomal segments.
• Employed the Viterbi algorithm for imputation and random sampling for any remaining unknown inheritances, averaging out errors with a large number of markers.

Main Results:

• FGla accurately estimated G la coefficients, with accuracy increasing from 0.971 to 0.998 with denser genotyping.
• The G la matrix provided approximately unbiased relationships in the Best Linear Unbiased Prediction (BLUP) sense.
• FGla relationships were found to be unbiased and used the same base population as the pedigree-based A matrix.

Conclusions:

• FGla is a computationally efficient and unbiased algorithm for estimating IBD-based genomic relationships and inbreeding coefficients.
• The G la matrix is well-suited for genomic management of inbreeding and genomic optimal contribution selection.
• G la-based selection is neutral with respect to allele frequency changes, offering advantages for long-term genetic gain.