The effect of rare alleles on estimated genomic relationships from whole genome sequence data

Abstract

Background: Relationships between individuals and inbreeding coefficients are commonly used for breeding decisions, but may be affected by the type of data used for their estimation. The proportion of variants with low Minor Allele Frequency (MAF) is larger in whole genome sequence (WGS) data compared to Single Nucleotide Polymorphism (SNP) chips. Therefore, WGS data provide true relationships between individuals and may influence breeding decisions and prioritisation for conservation of genetic diversity in livestock. This study identifies differences between relationships and inbreeding coefficients estimated using pedigree, SNP or WGS data for 118 Holstein bulls from the 1000 Bull genomes project. To determine the impact of rare alleles on the estimates we compared three scenarios of MAF restrictions: variants with a MAF higher than 5%, variants with a MAF higher than 1% and variants with a MAF between 1% and 5%.

Results: We observed significant differences between estimated relationships and, although less significantly, inbreeding coefficients from pedigree, SNP or WGS data, and between MAF restriction scenarios. Computed correlations between pedigree and genomic relationships, within groups with similar relationships, ranged from negative to moderate for both estimated relationships and inbreeding coefficients, but were high between estimates from SNP and WGS (0.49 to 0.99). Estimated relationships from genomic information exhibited higher variation than from pedigree. Inbreeding coefficients analysis showed that more complete pedigree records lead to higher correlation between inbreeding coefficients from pedigree and genomic data. Finally, estimates and correlations between additive genetic (A) and genomic (G) relationship matrices were lower, and variances of the relationships were larger when accounting for allele frequencies than without accounting for allele frequencies.

Conclusions: Using pedigree data or genomic information, and including or excluding variants with a MAF below 5% showed significant differences in relationship and inbreeding coefficient estimates. Estimated relationships and inbreeding coefficients are the basis for selection decisions. Therefore, it can be expected that using WGS instead of SNP can affect selection decision. Inclusion of rare variants will give access to the variation they carry, which is of interest for conservation of genetic diversity.

Figure 1

Distribution plot of the number of variants per class of MAF. Histograms of the number of segregating variants in each Minor Allele Frequency category (116 bins) from 1% to 50%, with density curve. The histogram on the left represents the distribution of variants from the Bovine 50 K SNP chip. The histogram on the right represents the distribution of variants from whole genome sequence (WGS) data.

Figure 2

Linear regressions plots for A , SNP and WGS against each other ( Yang method ) . Plots of linear regressions of A estimated relationships from pedigree (A _ped), G estimated relationships for Single Nucleotide Polymorphism (G _SNP) and whole genome sequence (G _WGS) data using the Yang method. Each linear regression was performed for the scenarios with Minor Allele Frequency (MAF) ≥ 5% (5+), ≥ 1% (1+) and between 1% and 5% (1_5). The first row represents the plots for scenario +5, the second for +1 and the third for 1_5. The first column shows the linear regression plots of G _SNP on A _ped. The second column shows the linear regression plots of G _WGS on A _ped. The third shows the linear regression plots of G _WGS on G _SNP. In black is the regression line for an exact linear model (intercept=0, slope=1) and in red is the actual overall regression line. On the top left corner, the overall correlation coefficient for each linear regression appears.

Figure 3

Linear regressions plots for A, SNP and WGS against each other (based on similarities). Plots of linear regression of A estimated relationships from pedigree (A _ped), G estimated relationships for Single Nucleotide Polymorphism (G _SNP) and whole genome sequence (G _WGS) data, based on similarities. Each linear regression was performed for the scenarios with Minor Allele Frequency (MAF) ≥ 5% (5+), ≥ 1% (1+) and between 1% and 5% (1_5). The first row represents the plots for scenario +5, the second for +1 and the third for 1_5. The first column shows the linear regression plots of G _SNP on A _ped. The second column shows the linear regression plots of G _WGS on A _ped. The third shows the linear regression plots of G _WGS on G _SNP. In black is the regression line for an exact linear model (intercept=0, slope=1) and in red is the actual overall regression line. On the top left corner, the overall correlation coefficient for each linear regression appears.