Submitted to: Genetic Selection Evolution
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/25/2025
Publication Date: N/A
Citation: N/A

Interpretive Summary: The scaling of genomic inbreeding was revised to account for X chromosome differences between males and females and to better match the scale of genomic- to pedigree-based inbreeding. Also, the impact of different allelic frequencies was measured. The computational efficiency of the whole procedure was improved to keep up with the massive increase of incoming genotypes. As a result, genomic inbreeding values of males and females are now more comparable to each other and to pedigree inbreeding. The computation has been improved to more rapidly process the larger numbers of genotypes expected in the future.

Technical Abstract: Background Breeders for many decades used pedigrees to limit increases in inbreeding, but genomic measures of relationship and inbreeding can provide more precise control. Previous calculations of pedigree inbreeding (F_ped), genomic inbreeding (F_gen), pedigree expected future inbreeding (EFI_ped), and genomic expected future inbreeding (EFI_gen) ignored the influence of the X-chromosome when estimating relationships. However, excluding the X-chromosome can cause an increase in inbreeding by mating two individuals with the same X-chromosome. Because the X-specific region has 3.0% of the 79,060 markers used in U.S. genomic evaluation and those markers are coded as 100% homozygous in males, homozygosity of females appeared to be 3% less than for males. Allele frequency also has an impact on computing F_gen. Programs to compute pedigree and genomic measures were revised to improve speed and memory use as well as to better account for the X-chromosome. Results Revised software reduced computational time from 33 hours to 13 minutes for F_ped and EFI_ped with 88 million animals in the pedigree and from 19 hours to 28 minutes for F_gen and EFI_gen. for 3,280,753 genotyped animals of 5 breeds. With the X-chromosome excluded, correlations were high between Fgen computed using either an allele frequency of 0.5 or a base population frequency for most but not all breeds; mean F_gen was higher for males than for females. After adjusting F_gen for the X-chromosome using an allele frequency of 0.5, correlations across breeds and sex increased, and X-adjusted F_gen was more similar to F_ped. Mean correlation with F_ped across breeds was 0.67 for Fgen with an allele frequency of 0.5, 0.67 for X-adjusted F_gen, and 0.54 for F_gen with base population allele frequency; corresponding EFI correlations were 0.83, 0.83, and 0.84. Correlation of haplotype-based inbreeding with F_ped was 0.64. Conclusions Revision of inbreeding software allowed simpler and more accurate comparison of genomic and pedigree relationships and much faster computation. Use of the X-chromosome in estimating genomic inbreeding measures did not affect the correlation between sexes but did improve mean differences. Breeds with smaller populations were more sensitive to the use of different allele frequencies.