Theoretical and empirical comparisons of expected and realized relationships for the X-chromosome

Abstract

Background: X-chromosomal loci present different inheritance patterns compared to autosomal loci and must be modeled accordingly. Sexual chromosomes are not systematically considered in whole-genome relationship matrices although rules based on genealogical or marker information have been derived. Loci on the X-chromosome could have a significant contribution to the additive genetic variance, in particular for some traits such as those related to reproduction. Thus, accounting for the X-chromosome relationship matrix might be informative to better understand the architecture of complex traits (e.g., by estimating the variance associated to this chromosome) and to improve their genomic prediction. For such applications, previous studies have shown the benefits of combining information from genotyped and ungenotyped individuals. Results: In this paper, we start by presenting rules to compute a genomic relationship matrix (GRM) for the X-chromosome (G X) without making any assumption on dosage compensation, and based on coding of gene content with 0/1 for males and 0/1/2 for females. This coding adjusts naturally to previously derived pedigree-based relationships (S) for the X-chromosome. When needed, we propose to accommodate and estimate dosage compensation and genetic heterogeneity across sexes via multiple trait models. Using a Holstein dairy cattle dataset, including males and females, we then empirically illustrate that realized relationships (G X) matches expectations (S). However, G X presents high deviations from S. G X has also a lower dimensionality compared to the autosomal GRM. In particular, individuals are frequently identical along the entire chromosome. Finally, we confirm that the heritability of gene content for markers on the X-chromosome that are estimated by using S is 1, further demonstrating that S and G X can be combined. For the pseudo-autosomal region, we demonstrate that the expected relationships vary according to position because of the sex-gradient. We end by presenting the rules to construct the 'H matrix' by combining both relationship matrices. Conclusions: This work shows theoretically and empirically that a pedigree-based relationship matrix built with rules specifically developed for the X-chromosome (S) matches the realized GRM for the X-chromosome. Therefore, applications that combine expected relationships and genotypes for markers on the X-chromosome should use S and G X .

Genotype-by-environment interactions for reproduction, body composition, and growth traits in maternal-line pigs based on single-step genomic reaction norms

“…Thus, in this study, we also used the RNM coupled with the matrix. Since inheritance patterns differ between the autosomes and the X chromosome, specific approaches (such as different genotyping coding rules) must be used to include SSCX SNPs in the construction of genomic-based relationship matrices [ 28 , 64 , 65 ]. In addition to the dosage compensation effect in females [ 30 ], the different number of copies of the X chromosome between males and females complicates the calculation of individual relationships.…”

High male specific contribution of the X-chromosome to individual global recombination rate in dairy cattle

“…Although the marker-based estimation of the percentage of genetic variance accounted by the X-chromosome was large (19.9%), it was lower than the pedigree-based estimation (29.9%). This difference might be due to the differences between expected and realized relationships that are larger when these are estimated for a single chromosome, such as the X-chromosome, rather than with all the autosomes [ 30 ]. Even higher deviations between expected and realized relationships were observed when comparisons were done exclusively for males and the for X-chromosome [ 30 ].…”

“…This difference might be due to the differences between expected and realized relationships that are larger when these are estimated for a single chromosome, such as the X-chromosome, rather than with all the autosomes [ 30 ]. Even higher deviations between expected and realized relationships were observed when comparisons were done exclusively for males and the for X-chromosome [ 30 ]. Use of realized relationships are expected to provide better estimators.…”

“…Contrasting results were obtained in females with the same approach as the contribution of the X-chromosome to female GRR was almost null. This discrepancy could be due to technical aspects, such as lower power in females where we have fewer records despite a larger number of parents, or such as the pedigree-based relationships A and S being more similar in females than in males (e.g., higher correlations between elements of the relationship matrices) (e.g., [ 30 ]), making it more difficult to disentangle the two effects. Nevertheless, the power was large enough to identify the variants present on the autosomes and affecting both male and female GRR [ 8 ].…”

“…The genetic variance associated with the X-chromosome (the X-specific part) was estimated by extending the LMM as follows: where s is the vector of random additive genetic effects associated with the X-chromosome and normally distributed, i.e. s ~ N (0, S ), where is the additive genetic variance associated with the X-chromosome and S is the additive relationship matrix for the X-chromosome estimated from pedigree as in Fernando and Grossman [ 42 ], and reconstructed with codes developed in Druet and Legarra [ 30 ]. We realized a likelihood ratio test (LRT) comparing the two models to determine whether was significantly different from 0.…”