Evaluation of heritability partitioning approaches in livestock populations.

BACKGROUND: Heritability partitioning approaches estimate the contribution of different functional classes, such as coding or regulatory variants, to the genetic variance. This information allows a better understanding of the genetic architecture of complex traits, including complex diseases, but can also help improve the accuracy of genomic selection in livestock species. However, methods have mainly been tested on human genomic data, whereas livestock populations have specific characteristics, such as high levels of relatedness, small effective population size or long-range levels of linkage disequilibrium. RESULTS: Here, we used data from 14,762 cows, imputed at the whole-genome sequence level for 11,537,240 variants, to simulate traits in a typical livestock population and evaluate the accuracy of two state-of-the-art heritability partitioning methods, GREML and a Bayesian mixture model. In simulations where a single functional class had increased contribution to heritability, we observed that the estimators were unbiased but had low precision. When causal variants were enriched in variants with low (< 0.05) or high (> 0.20) minor allele frequency or low (below 1st quartile) or high (above 3rd quartile) linkage disequilibrium scores, it was necessary to partition the genetic variance into multiple classes defined on the basis of allele frequencies or LD scores to obtain unbiased results. When multiple functional classes had variable contributions to heritability, estimators showed higher levels of variation and confounding between certain categories was observed. In addition, estimators from small categories were particularly imprecise. However, the estimates and their ranking were still informative about the contribution of the classes. We also demonstrated that using methods that estimate the contribution of a single category at a time, a commonly used approach, results in an overestimation. Finally, we applied the methods to phenotypes for muscular development and height and estimated that, on average, variants in open chromatin regions had a higher contribution to the genetic variance (> 45%), while variants in coding regions had the strongest individual effects (> 25-fold enrichment on average). Conversely, variants in intergenic or intronic regions showed lower levels of enrichment (0.2 and 0.6-fold on average, respectively). CONCLUSIONS: Heritability partitioning approaches should be used cautiously in livestock populations, in particular for small categories. Two-component approaches that fit only one functional category at a time lead to biased estimators and should not be used.

Genetic and genomic analysis of Belgian Blue's susceptibility for psoroptic mange.

BACKGROUND: Psoroptic mange, caused by Psoroptes ovis mites, is affecting Belgian Blue cattle's welfare and production potential. The Belgian Blue cattle-known for its high degree of muscling, low feed conversion ratio and high beef quality-is highly susceptible for this disease. RESULTS: In this study, we phenotyped 1975 Belgian Blue cattle from more than 100 different groups on commercial beef farms for their psoroptic mange susceptibility. Substantial individual differences were observed within these management groups, with lesion extent differences up to ± 15%. Animal models showed that estimated heritabilities were low for lesion extent and severe lesion extent (0.07 and 0.09, respectively) and 0.12 for the number of mites. A genome wide association study for mange susceptibility revealed signals on BTA6, BTA11, BTA15 and BTA24. In these regions, candidate genes GBA3, RAG2, and TRAF6 were identified. CONCLUSIONS: Despite the challenges in phenotyping for psoroptic mange due to the timing of screening, the continuous evolution of lesions and different management conditions, we successfully conducted a study on the genetic susceptibility to psoroptic mange in Belgian Blue cattle. Our results clearly indicate that psoroptic mange is under polygenic control and the underlying candidate genes should be studied more thoroughly. This is the first study providing candidate genes for this complex disease. These results are already valuable for Belgian Blue breeding, however, further research is needed to unravel the architecture of this disease and to identify causal mutations.

GWAS reveals determinants of mobilization rate and dynamics of an active endogenous retrovirus of cattle.

Five to ten percent of mammalian genomes is occupied by multiple clades of endogenous retroviruses (ERVs), that may count thousands of members. New ERV clades arise by retroviral infection of the germline followed by expansion by reinfection and/or retrotransposition. ERV mobilization is a source of deleterious variation, driving the emergence of ERV silencing mechanisms, leaving "DNA fossils". Here we show that the ERVK[2-1-LTR] clade is still active in the bovine and a source of disease-causing alleles. We develop a method to measure the rate of ERVK[2-1-LTR] mobilization, finding an average of 1 per ~150 sperm cells, with >10-fold difference between animals. We perform a genome-wide association study and identify eight loci affecting ERVK[2-1-LTR] mobilization. We provide evidence that polymorphic ERVK[2-1-LTR] elements in four of these loci cause the association. We generate a catalogue of full length ERVK[2-1-LTR] elements, and show that it comprises 15% of C-type autonomous elements, and 85% of D-type non-autonomous elements lacking functional genes. We show that >25% of the variance of mobilization rate is determined by the number of C-type elements, yet that de novo insertions are dominated by D-type elements. We propose that D-type elements act as parasite-of-parasite gene drives that may contribute to the observed demise of ERV elements.