Massive detection of cryptic recessive genetic defects in dairy cattle mining millions of life histories.

BACKGROUND: Dairy cattle breeds are populations of limited effective size, subject to recurrent outbreaks of recessive defects that are commonly studied using positional cloning. However, this strategy, based on the observation of animals with characteristic features, may overlook a number of conditions, such as immune or metabolic genetic disorders, which may be confused with pathologies of environmental etiology. RESULTS: We present a data mining framework specifically designed to detect recessive defects in livestock that have been previously missed due to a lack of specific signs, incomplete penetrance, or incomplete linkage disequilibrium. This approach leverages the massive data generated by genomic selection. Its basic principle is to compare the observed and expected numbers of homozygotes for sliding haplotypes in animals with different life histories. Within three cattle breeds, we report 33 new loci responsible for increased risk of juvenile mortality and present a series of validations based on large-scale genotyping, clinical examination, and functional studies for candidate variants affecting the NOA1, RFC5, and ITGB7 genes. In particular, we describe disorders associated with NOA1 and RFC5 mutations for the first time in vertebrates. CONCLUSIONS: The discovery of these many new defects will help to characterize the genetic basis of inbreeding depression, while their management will improve animal welfare and reduce losses to the industry.

Investigating the impact of paternal age, paternal heat stress, and estimation of non-genetic paternal variance on dairy cow phenotype.

BACKGROUND: Linear models that are commonly used to predict breeding values in livestock species consider paternal influence solely as a genetic effect. However, emerging evidence in several species suggests the potential effect of non-genetic semen-mediated paternal effects on offspring phenotype. This study contributes to such research by analyzing the extent of non-genetic paternal effects on the performance of Holstein, Montbéliarde, and Normande dairy cows. Insemination data, including semen Batch Identifier (BI, a combination of bull identification and collection date), was associated with various traits measured in cows born from the insemination. These traits encompassed stature, milk production (milk, fat, and protein yields), udder health (somatic cell score and clinical mastitis), and female fertility (conception rates of heifers and cows). We estimated (1) the effects of age at collection and heat stress during spermatogenesis, and (2) the variance components associated with BI or Weekly aggregated BI (WBI). RESULTS: Overall, the non-genetic paternal effect estimates were small and of limited biological importance. However, while heat stress during spermatogenesis did not show significant associations with any of the traits studied in daughters, we observed significant effects of bull age at semen collection on the udder health of daughters. Indeed, cows born from bulls collected after 1500 days of age had higher somatic cell scores compared to those born from bulls collected at a younger age (less than 400 days old) in both Holstein and Normande breeds (+ 3% and + 5% of the phenotypic mean, respectively). In addition, across all breeds and traits analyzed, the estimates of non-genetic paternal variance were consistently low, representing on average 0.13% and 0.09% of the phenotypic variance for BI and WBI, respectively (ranging from 0 to 0.7%). These estimates did not significantly differ from zero, except for milk production traits (milk, fat, and protein yields) in the Holstein breed and protein yield in the Montbéliarde breed when WBI was considered. CONCLUSIONS: Our findings indicate that non-genetic paternal information transmitted through semen does not substantially influence the offspring phenotype in dairy cattle breeds for routinely measured traits. This lack of substantial impact may be attributed to limited transmission or minimal exposure of elite bulls to adverse conditions.

A recurrent de novo missense mutation in COL1A1 causes osteogenesis imperfecta type II and preterm delivery in Normande cattle.

BACKGROUND: Nine male and eight female calves born to a Normande artificial insemination bull named "Ly" were referred to the French National Observatory of Bovine Abnormalities for multiple fractures, shortened gestation, and stillbirth or perinatal mortality. RESULTS: Using Illumina BovineSNP50 array genotypes from affected calves and 84 half-sib controls, the associated locus was mapped to a 6.5-Mb interval on chromosome 19, assuming autosomal inheritance with germline mosaicism. Subsequent comparison of the whole-genome sequences of one case and 5116 control genomes, followed by genotyping in the affected pedigree, identified a de novo missense substitution within the NC1 domain of the COL1A1 gene (Chr19 g.36,473,965G > A; p.D1412N) as unique candidate variant. Interestingly, the affected residue was completely conserved among 243 vertebrate orthologs, and the same substitution in humans has been reported to cause type II osteogenesis imperfecta (OI), a connective tissue disorder that is characterized primarily by bone deformity and fragility. Moreover, three COL1A1 mutations have been described to cause the same syndrome in cattle. Necropsy, computed tomography, radiology, and histology confirmed the diagnosis of type II OI, further supporting the causality of this variant. In addition, a detailed analysis of gestation length and perinatal mortality in 1387 offspring of Ly and more than 160,000 progeny of 63 control bulls allowed us to statistically confirm in a large pedigree the association between type II OI and preterm delivery, which is probably due to premature rupture of fetal membranes and has been reported in several isolated cases of type II OI in humans and cattle. Finally, analysis of perinatal mortality rates and segregation distortion supported a low level of germ cell mosaicism in Ly, with an estimate of 4.5% to 7.7% of mutant sperm and thus 63 to 107 affected calves born. These numbers contrast with the 17 cases reported and raise concerns about the underreporting of congenital defects to heredo-surveillance platforms, even for textbook genetic syndromes. CONCLUSIONS: In conclusion, we describe a large animal model for a recurrent substitution in COL1A1 that is responsible for type II OI in humans. More generally, this study highlights the utility of such datasets and large half-sib families available in livestock species to characterize sporadic genetic defects.

Large-scale detection and characterization of interchromosomal rearrangements in normozoospermic bulls using massive genotype and phenotype data sets.

In this paper, we developed a highly sensitive approach to detect interchromosomal rearrangements in cattle by searching for abnormal linkage disequilibrium patterns between markers located on different chromosomes in large paternal half-sib families genotyped as part of routine genomic evaluations. We screened 5571 families of artificial insemination sires from 15 breeds and revealed 13 putative interchromosomal rearrangements, 12 of which were validated by cytogenetic analysis and long-read sequencing. These consisted of one Robertsonian fusion, 10 reciprocal translocations, and the first case of insertional translocation reported in cattle. Taking advantage of the wealth of data available in cattle, we performed a series of complementary analyses to define the exact nature of these rearrangements, investigate their origins, and search for factors that may have favored their occurrence. We also evaluated the risks to the livestock industry and showed significant negative effects on several traits in the sires and in their balanced or aneuploid progeny compared with wild-type controls. Thus, we present the most comprehensive and thorough screen for interchromosomal rearrangements compatible with normal spermatogenesis in livestock species. This approach is readily applicable to any population that benefits from large genotype data sets, and will have direct applications in animal breeding. Finally, it also offers interesting prospects for basic research by allowing the detection of smaller and rarer types of chromosomal rearrangements than GTG banding, which are interesting models for studying gene regulation and the organization of genome structure.