A large population study to assess the magnitude of prenatal programming in dairy cattle.

The performance of an adult dairy cow may be influenced by events that occur before her birth. The present study investigated potential effects of 2 prenatal groups of factors, Assisted Reproductive Techniques (ART) and maternal characteristics (e.g., dam parity), on offspring performance during their first lactation, in populations of 2 dairy cow breeds: French Holstein and Montbéliarde. The different ART studied included the type of semen (conventional or X-sorted) used for Artificial Insemination (AI) and the technology of conception used (AI, embryo transfer, or in vitro fertilization). Three maternal characteristics were considered: (1) the dam age at first calving, (2) dam parity number, and (3) indicators of dam udder health during gestation (somatic cell score and events of clinical mastitis). First, we investigated whether heifer survival from 3d to 18 mo old was associated with any of the prenatal factors considered. We then estimated the associations of these prenatal factors with 8 traits of commercial interest: (1) stature, (2-4) milk, fat, and protein yields, (5) somatic cell score, (6) clinical mastitis, and (7-8) heifer and cow conception rate, all measured on genotyped cows. Linear models were used for this study with the prenatal factors as covariates in the model, and for the 8 traits, phenotypes were adjusted for their corresponding genomic estimated breeding value. The results indicated that the survival rate of heifers born from embryo transfer was significantly higher than that of heifers born from AI (probably due to preferential management practices), while the other prenatal factors did not explain differences in heifer survival. Among the Montbéliarde cows born from AI, those born from X-sorted semen showed a lightly but significantly lower milk yield than those born without X-sorting of the semen (-52 kg of milk in the first lactation). Among the Holstein cows, those born from embryo transfer presented significantly lower milk performance than cows born from AI. Regarding the maternal characteristics, none or very weak associations were found between the dam age at first calving and the offspring performance in both breeds. Dam parity, on the other hand, was associated with offspring performance for milk, fat, and protein yield in both breeds, however not in the same direction. In the Holstein breed, an increase in dam parity was favorable for offspring performance for milk, fat, and protein yield, whereas in the Montbéliarde breed, an increase in dam parity was associated with lower milk and protein yield and no association was found for fat yield. The udder health of the dam during gestation was not or only weakly associated with the traits studied in the offspring. Although some significant associations were identified due to the large sample size, the effects were modest, typically less than 1% of the phenotypic mean, and were not consistently observed across the 2 breeds.

A missense mutation in the FZD7 gene is associated with dilution of the red areas of the coat in Montbéliarde cattle.

Recently, a new genetically autosomal recessive color phenotype emerged in the red pied bovine Montbéliarde breed. It is characterized by a dilution of the red areas of the coat and was denominated 'milca'. A genome-wide homozygosity scan of 106 cases followed by haplotype analysis revealed a candidate region within BTA2 between positions 89.95 and 91.63 Mb. Analysis of whole-genome sequence data generated from milca animals identified a strong candidate variant within the coding region of the Frizzled-7 gene (FZD7). This gene encodes for a G-protein coupled receptor for Wnt signaling proteins. The variant induces a glycine to alanine substitution in the second extracellular loop, p.(Gly414Ala). Cross-species amino acid alignments revealed that this glycine is conserved among orthologs and most paralogs, suggesting that it plays an important role in FZD function. In addition, genotyping data revealed that the mutant allele is restricted to the Montbéliarde breed, at a 3.7% frequency. All homozygous cows for the mutant allele exhibited the milca phenotype whereas all heterozygotes had no coat color defects. In conclusion, this study strongly suggests that, in cattle, a mutation of FZD7 alone is sufficient to cause a coat color phenotype without any strong other adverse effect.

Short communication: A splice site mutation in CENPU is associated with recessive embryonic lethality in Holstein cattle.

A genome scan for homozygous haplotype deficiency coupled with whole-genome sequence data analysis is a very effective method to identify embryonic lethal mutations in cattle. Among other factors, the power of the approach depends on the availability of a greater amount of genotyping and sequencing data. In the present study, we analyzed the largest known panel of Illumina BovineSNP50 (Illumina Inc., San Diego, CA) genotypes, comprising 401,896 Holstein animals, and we report the mapping of a new embryonic lethal haplotype on chromosome 27, called HH7. We fine mapped the locus in a 2.0-Mb interval using an identical-by-descent approach and analyzed genome sequence data from 4 carrier and 143 noncarrier Holstein bulls to identify the causative mutation. We detected a strong candidate variant in the gene encoding centromere protein U (CENPU), a centromere component essential for proper chromosome segregation during mitosis. The mutant allele is a deletion of 4 nucleotides located at position +3 to +6 bp after the splicing donor site of exon 11. Cross-species nucleotide alignment revealed that the nucleotide at position +3 is entirely conserved among vertebrates, suggesting that it plays an important role in the regulation of CENPU splicing. For verification, we genotyped the candidate variant in 232,775 Holstein individuals and did not observe any homozygotes, whereas 16 were expected (Poisson P-value = 1.1 × 10-7; allele frequency = 0.8%). In addition, genotyping of 250,602 animals from 19 additional breeds revealed that the mutant allele is restricted to animals of Holstein descent. Finally, we estimated the effect of the candidate variant on 2 fertility traits in at-risk mating (i.e., between carrier bulls and daughters of carrier bulls) versus non-risk mating. In agreement with a recessive lethal inheritance pattern, we observed a marked reduction in both conception rate and 56-d nonreturn rate in heifers and cows. The effect on 56-d nonreturn rate suggests that a substantial proportion of homozygous mutants die before 35 d after insemination, which is consistent with the early embryonic death previously reported in CENPU-/- mouse embryos. In conclusion, we demonstrate that with more than 400,000 genotypes, we can map very rare recessive lethal mutations segregating at a frequency below 1% in the population. We recommend performing new analyses regularly as data are accumulating.

A missense mutation (p.Tyr452Cys) in the CAD gene compromises reproductive success in French Normande cattle.

We scanned the genome of 77,815 Normande cattle with different Illumina SNP chips (Illumina Inc., San Diego, CA) to map recessive embryonic lethal mutations using homozygous haplotype deficiency. We detected 2 novel haplotypes on chromosomes 11 and 24 but did not confirm 6 previously reported haplotypes. The one on chromosome 11 showed a marked reduction in conception rates and moderate decrease in nonreturn rate in at-risk versus control mating, supporting late embryonic mortality. After fine mapping and analyzing whole-genome sequences, we prioritized a missense mutation in CAD (g.72399397T>C; p.Tyr452Cys)-a gene encoding a protein (carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase) essential for de novo pyrimidine biosynthesis-as a candidate causal variant. This transition mutation replaces a tyrosine residue, which is perfectly conserved among living organisms, with a cysteine residue in the carbamoyl-phosphate synthetase 2 domain of the protein. A single animal was confirmed to be homozygous for the mutation based on Sanger sequencing. However, large-scale genotyping of the candidate variant with the Illumina EuroG10k BeadChip revealed an absence of live homozygotes in a panel of 33,323 Normande animals and an absence of carriers in 348,593 animals from 19 other cattle breeds. These results support recessive embryonic lethality with nearly complete penetrance, as was previously reported in CAD mutants in several eukaryote species. The only homozygous cow had extremely poor udder conformation, suggesting a potential role of CAD in udder development, but no effect was detected when comparing daughter yield deviations of 250 heterozygous bulls with that of 2,912 homozygotes for the ancestral allele. Together, our results showed the importance of large-scale screening for homozygous haplotype deficiency with hundreds of thousands of animals, validating results with an independent data set, and considering unexpected live homozygotes, to avoid both false-positive and false-negative discoveries. These discoveries will be used primarily in mating decisions to avoid at-risk mating. In addition, we recommend including CAD in the breeding objectives of Normande cattle.

Use of meta-analyses and joint analyses to select variants in whole genome sequences for genomic evaluation: An application in milk production of French dairy cattle breeds.

As a result of the 1000 Bull Genome Project, it has become possible to impute millions of variants, with many of these potentially causative for traits of interest, for thousands of animals that have been genotyped with medium-density chips. This enormous source of data opens up very interesting possibilities for the inclusion of these variants in genomic evaluations. However, for computational reasons, it is not possible to include all variants in genomic evaluation procedures. One potential approach could be to select the most relevant variants based on the results of genome-wide association studies (GWAS); however, the identification of causative mutations is still difficult with this method, partly because of weak imputation accuracy for rare variants. To address this problem, this study assesses the ability of different approaches based on multi-breed GWAS (joint and meta-analyses) to identify single-nucleotide polymorphisms (SNP) for use in genomic evaluation in the 3 main French dairy cattle breeds. A total of 6,262 Holstein bulls, 2,434 Montbéliarde bulls, and 2,175 Normande bulls with daughter yield deviations for 5 milk production traits were imputed for 27 million variants. Within-breed and joint (including all 3 breeds) GWAS were performed and 3 models of meta-analysis were tested: fixed effect, random effect, and Z-score. Comparison of the results of within- and multi-breed GWAS showed that most of the quantitative trait loci identified using within-breed approaches were also found with multi-breed methods. However, the most significant variants identified in each region differed depending on the method used. To determine which approach highlighted the most predictive SNP for each trait, we used a marker-assisted best unbiased linear prediction model to evaluate lists of SNP generated by the different GWAS methods; each list contained between 25 and 2,000 candidate variants per trait, which were identified using a single within- or multi-breed GWAS approach. Among all the multi-breed methods tested in this study, variant selection based on meta-analysis (fixed effect) resulted in the most-accurate genomic evaluation (+1 to +3 points compared with other multi-breed approaches). However, the accuracies of genomic evaluation were always better when variants were selected using the results of within-breed GWAS. As has generally been found in studies of quantitative trait loci, these results suggest that part of the genetic variance of milk production traits is breed specific in Holstein, Montbéliarde, and Normande cattle.

Rapid Discovery of De Novo Deleterious Mutations in Cattle Enhances the Value of Livestock as Model Species.

In humans, the clinical and molecular characterization of sporadic syndromes is often hindered by the small number of patients and the difficulty in developing animal models for severe dominant conditions. Here we show that the availability of large data sets of whole-genome sequences, high-density SNP chip genotypes and extensive recording of phenotype offers an unprecedented opportunity to quickly dissect the genetic architecture of severe dominant conditions in livestock. We report on the identification of seven dominant de novo mutations in CHD7, COL1A1, COL2A1, COPA, and MITF and exploit the structure of cattle populations to describe their clinical consequences and map modifier loci. Moreover, we demonstrate that the emergence of recessive genetic defects can be monitored by detecting de novo deleterious mutations in the genome of bulls used for artificial insemination. These results demonstrate the attractiveness of cattle as a model species in the post genomic era, particularly to confirm the genetic aetiology of isolated clinical case reports in humans.

Genetic tools to improve reproduction traits in dairy cattle.

Fertility is a major concern in the dairy cattle industry and has been the subject of numerous studies over the past 20 years. Surprisingly, most of these studies focused on rough female phenotypes and, despite their important role in reproductive success, male- and embryo-related traits have been poorly investigated. In recent years, the rapid and important evolution of technologies in genetic research has led to the development of genomic selection. The generalisation of this method in combination with the achievements of the AI industry have led to the constitution of large databases of genotyping and sequencing data, as well as refined phenotypes and pedigree records. These resources offer unprecedented opportunities in terms of fundamental and applied research. Here we present five such examples with a focus on reproduction-related traits: (1) detection of quantitative trait loci (QTL) for male fertility and semen quality traits; (2) detection of QTL for refined phenotypes associated with female fertility; (3) identification of recessive embryonic lethal mutations by depletion of homozygous haplotypes; (4) identification of recessive embryonic lethal mutations by mining whole-genome sequencing data; and (5) the contribution of high-density single nucleotide polymorphism chips, whole-genome sequencing and imputation to increasing the power of QTL detection methods and to the identification of causal variants.

Genomic prediction in French Charolais beef cattle using high-density single nucleotide polymorphism markers.

The objective of the study was to develop a genomic evaluation for French beef cattle breeds and assess accuracy and bias of prediction for different genomic selection strategies. Based on a reference population of 2,682 Charolais bulls and cows, genotyped or imputed to a high-density SNP panel (777K SNP), we tested the influence of different statistical methods, marker densities (50K versus 777K), and training population sizes and structures on the quality of predictions. Four different training sets containing up to 1,979 animals and a unique validation set of 703 young bulls only known on their individual performances were formed. BayesC method had the largest average accuracy compared to genomic BLUP or pedigree-based BLUP. No gain of accuracy was observed when increasing the density of markers from 50K to 777K. For a BayesC model and 777K SNP panels, the accuracy calculated as the correlation between genomic predictions and deregressed EBV (DEBV) divided by the square root of heritability was 0.42 for birth weight, 0.34 for calving ease, 0.45 for weaning weight, 0.52 for muscular development, and 0.27 for skeletal development. Half of the training set constituted animals having only their own performance recorded, whose contribution only represented 5% of the accuracy. Using DEBV as a response brought greater accuracy than using EBV (+5% on average). Considering a residual polygenic component strongly reduced bias for most of the traits. The optimal percentage of polygenic variance varied across traits. Among the methodologies tested to implement genomic selection in the French Charolais beef cattle population, the most accurate and less biased methodology was to analyze DEBV under a BayesC strategy and a residual polygenic component approach. With this approach, a 50K SNP panel performed as well as a 777K panel.

Efficiency of multi-breed genomic selection for dairy cattle breeds with different sizes of reference population.

Single-breed genomic selection (GS) based on medium single nucleotide polymorphism (SNP) density (~50,000; 50K) is now routinely implemented in several large cattle breeds. However, building large enough reference populations remains a challenge for many medium or small breeds. The high-density BovineHD BeadChip (HD chip; Illumina Inc., San Diego, CA) containing 777,609 SNP developed in 2010 is characterized by short-distance linkage disequilibrium expected to be maintained across breeds. Therefore, combining reference populations can be envisioned. A population of 1,869 influential ancestors from 3 dairy breeds (Holstein, Montbéliarde, and Normande) was genotyped with the HD chip. Using this sample, 50K genotypes were imputed within breed to high-density genotypes, leading to a large HD reference population. This population was used to develop a multi-breed genomic evaluation. The goal of this paper was to investigate the gain of multi-breed genomic evaluation for a small breed. The advantage of using a large breed (Normande in the present study) to mimic a small breed is the large potential validation population to compare alternative genomic selection approaches more reliably. In the Normande breed, 3 training sets were defined with 1,597, 404, and 198 bulls, and a unique validation set included the 394 youngest bulls. For each training set, estimated breeding values (EBV) were computed using pedigree-based BLUP, single-breed BayesC, or multi-breed BayesC for which the reference population was formed by any of the Normande training data sets and 4,989 Holstein and 1,788 Montbéliarde bulls. Phenotypes were standardized by within-breed genetic standard deviation, the proportion of polygenic variance was set to 30%, and the estimated number of SNP with a nonzero effect was about 7,000. The 2 genomic selection (GS) approaches were performed using either the 50K or HD genotypes. The correlations between EBV and observed daughter yield deviations (DYD) were computed for 6 traits and using the different prediction approaches. Compared with pedigree-based BLUP, the average gain in accuracy with GS in small populations was 0.057 for the single-breed and 0.086 for multi-breed approach. This gain was up to 0.193 and 0.209, respectively, with the large reference population. Improvement of EBV prediction due to the multi-breed evaluation was higher for animals not closely related to the reference population. In the case of a breed with a small reference population size, the increase in correlation due to multi-breed GS was 0.141 for bulls without their sire in reference population compared with 0.016 for bulls with their sire in reference population. These results demonstrate that multi-breed GS can contribute to increase genomic evaluation accuracy in small breeds.