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.

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.

Searching for homozygous haplotype deficiency in Manech Tête Rousse dairy sheep revealed a nonsense variant in the MMUT gene affecting newborn lamb viability.

BACKGROUND: Recessive deleterious variants are known to segregate in livestock populations, as in humans, and some may be lethal in the homozygous state. RESULTS: We used phased 50 k single nucleotide polymorphism (SNP) genotypes and pedigree data to scan the genome of 6845 Manech Tête Rousse dairy sheep to search for deficiency in homozygous haplotypes (DHH). Five Manech Tête Rousse deficient homozygous haplotypes (MTRDHH1 to 5) were identified, with a homozygous deficiency ranging from 84 to 100%. These haplotypes are located on Ovis aries chromosome (OAR)1 (MTRDHH2 and 3), OAR10 (MTRDHH4), OAR13 (MTRDHH5), and OAR20 (MTRDHH1), and have carrier frequencies ranging from 7.8 to 16.6%. When comparing at-risk matings between DHH carriers to safe matings between non-carriers, two DHH (MTRDHH1 and 2) were linked with decreased insemination success and/or increased stillbirth incidence. We investigated the MTRDHH1 haplotype, which substantially increased stillbirth rate, and identified a single nucleotide variant (SNV) inducing a premature stop codon (p.Gln409*) in the methylmalonyl-CoA mutase (MMUT) gene by using a whole-genome sequencing approach. We generated homozygous lambs for the MMUT mutation by at-risk mating between heterozygous carriers, and most of them died within the first 24 h after birth without any obvious clinical symptoms. Reverse transcriptase-qPCR and western blotting on post-mortem liver and kidney biological samples showed a decreased expression of MMUT mRNA in the liver and absence of a full-length MMUT protein in the mutant homozygous lambs. CONCLUSIONS: We identified five homozygous deficient haplotypes that are likely to harbor five independent deleterious recessive variants in sheep. One of these was detected in the MMUT gene, which is associated with lamb lethality in the homozygous state. A specific management of these haplotypes/variants in the MTR dairy sheep selection program would help enhance the overall fertility and lamb survival.

Genetic parameters, GWAS and selection perspective on gestation length in 16 French cattle breeds.

In this paper, we present a comprehensive study of gestation length (GL) in 16 cattle breeds by using large genotype and animal record databases. Data included over 20 million gestations since 2000 and genotypes from one million calves. The study addressed the GL variability within and between breeds, estimation of its direct and maternal heritability coefficients, association with fitness and several economic traits, and QTL detection. The breed average GL varied from 279.7 to 294.4 d, in Holstein and Blonde d'Aquitaine breeds, respectively. Standard deviations per breed were similar and ranged from 5.2 to 5.8 d. Direct heritability (i.e., for GL defined as a trait of the calf) was moderate to high (h2 = 0.40 to 0.67), whereas the maternal heritability was low (0.04 to 0.06). Extreme breeding values for GL were strongly associated with a higher mortality during the first 2 d of life and were associated with milk production of dams for dairy breeds and precocity of females. Finally, several QTL were detected affecting GL with cumulated effects up to a few days, and at least 2 QTL were found to be shared between different breeds. Our study highlights the risks that would be associated with selection toward a reduced gestation length. Further genomic studies are needed to identify the causal variants, and their association with juvenile mortality and other economic traits.

X-linked genes influence various complex traits in dairy cattle.

BACKGROUND: The search for quantitative trait loci (QTL) affecting traits of interest in mammals is frequently limited to autosomes, with the X chromosome excluded because of its hemizygosity in males. This study aimed to assess the importance of the X chromosome in the genetic determinism of 11 complex traits related to milk production, milk composition, mastitis resistance, fertility, and stature in 236,496 cows from three major French dairy breeds (Holstein, Montbéliarde, and Normande) and three breeds of regional importance (Abondance, Tarentaise, and Vosgienne). RESULTS: Estimates of the proportions of heritability due to autosomes and X chromosome (h²X) were consistent among breeds. On average over the 11 traits, h²X=0.008 and the X chromosome explained ~ 3.5% of total genetic variance. GWAS was performed within-breed at the sequence level (~ 200,000 genetic variants) and then combined in a meta-analysis. QTL were identified for most breeds and traits analyzed, with the exception of Tarentaise and Vosgienne and two fertility traits. Overall, 3, 74, 59, and 71 QTL were identified in Abondance, Montbéliarde, Normande, and Holstein, respectively, and most were associated with the most-heritable traits (milk traits and stature). The meta-analyses, which assessed a total of 157 QTL for the different traits, highlighted new QTL and refined the positions of some QTL found in the within-breed analyses. Altogether, our analyses identified a number of functional candidate genes, with the most notable being GPC3, MBNL3, HS6ST2, and DMD for dairy traits; TMEM164, ACSL4, ENOX2, HTR2C, AMOT, and IRAK1 for udder health; MAMLD1 and COL4A6 for fertility; and NRK, ESX1, GPR50, GPC3, and GPC4 for stature. CONCLUSIONS: This study demonstrates the importance of the X chromosome in the genetic determinism of complex traits in dairy cattle and highlights new functional candidate genes and variants for these traits. These results could potentially be extended to other species as many X-linked genes are shared among mammals.

Sequence-based GWAS meta-analyses for beef production traits.

BACKGROUND: Combining the results of within-population genome-wide association studies (GWAS) based on whole-genome sequences into a single meta-analysis (MA) is an accurate and powerful method for identifying variants associated with complex traits. As part of the H2020 BovReg project, we performed sequence-level MA for beef production traits. Five partners from France, Switzerland, Germany, and Canada contributed summary statistics from sequence-based GWAS conducted with 54,782 animals from 15 purebred or crossbred populations. We combined the summary statistics for four growth, nine morphology, and 15 carcass traits into 16 MA, using both fixed effects and z-score methods. RESULTS: The fixed-effects method was generally more informative to provide indication on potentially causal variants, although we combined substantially different traits in each MA. In comparison with within-population GWAS, this approach highlighted (i) a larger number of quantitative trait loci (QTL), (ii) QTL more frequently located in genomic regions known for their effects on growth and meat/carcass traits, (iii) a smaller number of genomic variants within the QTL, and (iv) candidate variants that were more frequently located in genes. MA pinpointed variants in genes, including MSTN, LCORL, and PLAG1 that have been previously associated with morphology and carcass traits. We also identified dozens of other variants located in genes associated with growth and carcass traits, or with a function that may be related to meat production (e.g., HS6ST1, HERC2, WDR75, COL3A1, SLIT2, MED28, and ANKAR). Some of these variants overlapped with expression or splicing QTL reported in the cattle Genotype-Tissue Expression atlas (CattleGTEx) and could therefore regulate gene expression. CONCLUSIONS: By identifying candidate genes and potential causal variants associated with beef production traits in cattle, MA demonstrates great potential for investigating the biological mechanisms underlying these traits. As a complement to within-population GWAS, this approach can provide deeper insights into the genetic architecture of complex traits in beef cattle.

Identification of homozygous haplotypes carrying putative recessive lethal mutations that compromise fertility traits in French Lacaune dairy sheep.

BACKGROUND: Homozygous recessive deleterious mutations can cause embryo/fetal or neonatal lethality, or genetic defects that affect female fertility and animal welfare. In livestock populations under selection, the frequency of such lethal mutations may increase due to inbreeding, genetic drift, and/or the positive pleiotropic effects of heterozygous carriers on selected traits. RESULTS: By scanning the genome of 19,102 Lacaune sheep using 50 k single nucleotide polymorphism (SNP) phased genotypes and pedigree data, we identified 11 Lacaune deficient homozygous haplotypes (LDHH1 to LDHH11) showing a highly significant deficit of homozygous animals ranging from 79 to 100%. These haplotypes located on chromosomes 3, 4, 13, 17 and 18, spanned regions from 1.2 to 3.0 Mb long with a frequency of heterozygous carriers between 3.7 and 12.1%. When we compared at-risk matings (between carrier rams and daughters of carrier rams) and safe matings, seven of the 11 haplotypes were associated with a significant alteration of two fertility traits, a reduced success of artificial insemination (LDHH1, 2, 8 and 9), and/or an increased stillbirth rate (LDHH3, 6, 8, 9, and 10). The 11 haplotypes were also tested for a putative selective advantage of heterozygous carrier rams based on their daughter yield deviation for six dairy traits (milk, fat and protein yields, fat and protein contents and lactation somatic cell score). LDHH1, 3, 4, 5, 7, 9 and 11 were associated with positive effects on at least one selected dairy trait, in particular milk yield. For each haplotype, the most probable candidate genes were identified based on their roles in lethality of mouse knock-out models and in mammalian genetic disorders. CONCLUSIONS: Based on a reverse genetic strategy, we identified at least 11 haplotypes with homozygous deficiency segregating in French Lacaune dairy sheep. This strategy represents a first tool to limit at-risk matings in the Lacaune dairy selection scheme. We assume that most of the identified LDHH are in strong linkage disequilibrium with a recessive lethal mutation that affects embryonic or juvenile survival in sheep but is yet to be identified.

Confirmed effects of candidate variants for milk production, udder health, and udder morphology in dairy cattle.

BACKGROUND: Over the last years, genome-wide association studies (GWAS) based on imputed whole-genome sequences (WGS) have been used to detect quantitative trait loci (QTL) and highlight candidate genes for important traits. However, in general this approach does not allow to validate the effects of candidate mutations or determine if they are truly causative for the trait(s) in question. To address these questions, we applied a two-step, within-breed GWAS approach on 15 traits (5 linked with milk production, 2 with udder health, and 8 with udder morphology) in Montbéliarde (MON), Normande (NOR), and Holstein (HOL) cattle. We detected the most-promising candidate variants (CV) using imputed WGS of 2515 MON, 2203 NOR, and 6321 HOL bulls, and validated their effects in three younger populations of 23,926 MON, 9400 NOR, and 51,977 HOL cows. RESULTS: Bull sequence-based GWAS detected 84 QTL: 13, 10, and 30 for milk production traits; 3, 0, and 2 for somatic cell score (SCS); and 8, 2 and 16 for udder morphology traits, in MON, NOR, and HOL respectively. Five genomic regions with effects on milk production traits were shared among the three breeds whereas six (2 for production and 4 for udder morphology and health traits) had effects in two breeds. In 80 of these QTL, 855 CV were highlighted based on the significance of their effects and functional annotation. The subsequent GWAS on MON, NOR, and HOL cows validated 8, 9, and 23 QTL for production traits; 0, 0, and 1 for SCS; and 4, 1, and 8 for udder morphology traits, respectively. In 47 of the 54 confirmed QTL, the CV identified in bulls had more significant effects than single nucleotide polymorphisms (SNPs) from the standard 50K chip. The best CV for each validated QTL was located in a gene that was functionally related to production (36 QTL) or udder (9 QTL) traits. CONCLUSIONS: Using this two-step GWAS approach, we identified and validated 54 QTL that included CV mostly located within functional candidate genes and explained up to 6.3% (udder traits) and 37% (production traits) of the genetic variance of economically important dairy traits. These CV are now included in the chip used to evaluate French dairy cattle and can be integrated into routine genomic evaluation.

Gene networks for three feed efficiency criteria reveal shared and specific biological processes.

BACKGROUND: French beef producers suffer from the decrease in profitability of their farms mainly because of the continuous increase in feed costs. Selection for feed efficiency in beef cattle represents a relevant solution to face this problem. However, feed efficiency is a complex trait that can be assessed by three major criteria: residual feed intake (RFI), residual gain (RG) and feed efficiency ratio (FE), which involve different genetic determinisms. An analysis that combines phenotype and whole-genome sequence data provides a unique framework for genomic studies. The aim of our study was to identify the gene networks and the biological processes that are responsible for the genetic determinism that is shared between these three feed efficiency criteria. RESULTS: A population of 1477 French Charolais young bulls was phenotyped for feed intake (FI), average daily gain (ADG) and final weight (FW) to estimate RFI, RG and FE. A subset of 789 young bulls was genotyped on the BovineSNP50 single nucleotide polymorphism (SNP) array and imputed at the sequence level using RUN6 of the 1000 Bull Genomes Project. We conducted a genome-wide association study (GWAS) to estimate the individual effect of 8.5 million SNPs and applied an association weight matrix (AWM) approach to analyse the results, one for each feed efficiency criterion. The results highlighted co-association networks including 626 genes for RFI, 426 for RG and 564 for FE. Enrichment assessment revealed the biological processes that show the strongest association with RFI, RG and FE, i.e. digestive tract (salivary, gastric and mucin secretion) and metabolic processes (cellular and cardiovascular). Energetic functions were more associated with RFI and FE and cardio-vascular and cellular processes with RG. Several hormones such as apelin, glucagon, insulin, aldosterone, the gonadotrophin releasing hormone and the thyroid hormone were also identified, and these should be tested in future studies as candidate biomarkers for feed efficiency. CONCLUSIONS: The combination of network and pathway analyses at the sequence level led to the identification of both common and specific mechanisms that are involved in RFI, RG and FE, and to a better understanding of the genetic determinism underlying these three criteria. The effects of the genes involved in each of the identified processes need to be tested in genomic evaluations to confirm the potential gain in reliability of using functional variants to select animals for feed efficiency.

The impact of genomic selection on genetic diversity and genetic gain in three French dairy cattle breeds.

BACKGROUND: In France, implementation of genomic evaluations in dairy cattle breeds started in 2009 and this has modified the breeding schemes drastically. In this context, the goal of our study was to understand the impact of genomic selection on the genetic diversity of bulls from three French dairy cattle breeds born between 2005 and 2015 (Montbéliarde, Normande and Holstein) and the factors that are involved. METHODS: We compared annual genetic gains, inbreeding rates based on runs of homozygosity (ROH) and pedigree data, and mean ROH length within breeds, before and after the implementation of genomic selection. RESULTS: Genomic selection induced an increase in mean annual genetic gains of 50, 71 and 33% for Montbéliarde, Normande and Holstein bulls, respectively, and in parallel, the generation intervals were reduced by a factor of 1.7, 1.9 and 2, respectively. We found no significant change in inbreeding rate for the two national breeds, Montbéliarde and Normande, and a significant increase in inbreeding rate for the Holstein international breed, which is now as high as 0.55% per year based on ROH and 0.49% per year based on pedigree data (equivalent to a rate of 1.36 and 1.39% per generation, respectively). The mean ROH length was longer for bulls from the Holstein breed than for those from the other two breeds. CONCLUSIONS: With the implementation of genomic selection, the annual genetic gain increased for bulls from the three major French dairy cattle breeds. At the same time, the annual loss of genetic diversity increased for Holstein bulls, possibly because of the massive use of a few elite bulls in this breed, but not for Montbéliarde and Normande bulls. The increase in mean ROH length in Holstein may reflect the occurrence of recent inbreeding. New strategies in breeding schemes, such as female donor stations and embryo transfer, and recent implementation of genomic evaluations in small regional breeds should be studied carefully in order to ensure the sustainability of breeding schemes in the future.

An initiator codon mutation in SDE2 causes recessive embryonic lethality in Holstein cattle.

Researching depletions in homozygous genotypes for specific haplotypes among the large cohorts of animals genotyped for genomic selection is a very efficient strategy to map recessive lethal mutations. In this study, by analyzing real or imputed Illumina BovineSNP50 (Illumina Inc., San Diego, CA) genotypes from more than 250,000 Holstein animals, we identified a new locus called HH6 showing significant negative effects on conception rate and nonreturn rate at 56 d in at-risk versus control mating. We fine-mapped this locus in a 1.1-Mb interval and analyzed genome sequence data from 12 carrier and 284 noncarrier Holstein bulls. We report the identification of a strong candidate mutation in the gene encoding SDE2 telomere maintenance homolog (SDE2), a protein essential for genomic stability in eukaryotes. This A-to-G transition changes the initiator ATG (methionine) codon to ACG because the gene is transcribed on the reverse strand. Using RNA sequencing and quantitative reverse-transcription PCR, we demonstrated that this mutation does not significantly affect SDE2 splicing and expression level in heterozygous carriers compared with control animals. Initiation of translation at the closest in-frame methionine codon would truncate the SDE2 precursor by 83 amino acids, including the cleavage site necessary for its activation. Finally, no homozygote for the G allele was observed in a large population of nearly 29,000 individuals genotyped for the mutation. The low frequency (1.3%) of the derived allele in the French population and the availability of a diagnostic test on the Illumina EuroG10K SNP chip routinely used for genomic evaluation will enable rapid and efficient selection against this deleterious mutation.

Within-breed and multi-breed GWAS on imputed whole-genome sequence variants reveal candidate mutations affecting milk protein composition in dairy cattle.

BACKGROUND: Genome-wide association studies (GWAS) were performed at the sequence level to identify candidate mutations that affect the expression of six major milk proteins in Montbéliarde (MON), Normande (NOR), and Holstein (HOL) dairy cattle. Whey protein (α-lactalbumin and ß-lactoglobulin) and casein (αs1, αs2, ß, and κ) contents were estimated by mid-infrared (MIR) spectrometry, with medium to high accuracy (0.59 ≤ R2 ≤ 0.92), for 848,068 test-day milk samples from 156,660 cows in the first three lactations. Milk composition was evaluated as average test-day measurements adjusted for environmental effects. Next, we genotyped a subset of 8080 cows (2967 MON, 2737 NOR, and 2306 HOL) with the BovineSNP50 Beadchip. For each breed, genotypes were first imputed to high-density (HD) using HD single nucleotide polymorphisms (SNPs) genotypes of 522 MON, 546 NOR, and 776 HOL bulls. The resulting HD SNP genotypes were subsequently imputed to the sequence level using 27 million high-quality sequence variants selected from Run4 of the 1000 Bull Genomes consortium (1147 bulls). Within-breed, multi-breed, and conditional GWAS were performed. RESULTS: Thirty-four distinct genomic regions were identified. Three regions on chromosomes 6, 11, and 20 had very significant effects on milk composition and were shared across the three breeds. Other significant effects, which partially overlapped across breeds, were found on almost all the autosomes. Multi-breed analyses provided a larger number of significant genomic regions with smaller confidence intervals than within-breed analyses. Combinations of within-breed, multi-breed, and conditional analyses led to the identification of putative causative variants in several candidate genes that presented significant protein-protein interactions enrichment, including those with previously described effects on milk composition (SLC37A1, MGST1, ABCG2, CSN1S1, CSN2, CSN1S2, CSN3, PAEP, DGAT1, AGPAT6) and those with effects reported for the first time here (ALPL, ANKH, PICALM). CONCLUSIONS: GWAS applied to fine-scale phenotypes, multiple breeds, and whole-genome sequences seems to be effective to identify candidate gene variants. However, although we identified functional links between some candidate genes and milk phenotypes, the causality between candidate variants and milk protein composition remains to be demonstrated. Nevertheless, the identification of potential causative mutations that underlie milk protein composition may have immediate applications for improvements in cheese-making.

A missense mutation in PFAS (phosphoribosylformylglycinamidine synthase) is likely causal for embryonic lethality associated with the MH1 haplotype in Montbéliarde dairy cattle.

A candidate mutation in the sex hormone binding globulin gene was proposed in 2013 to be responsible for the MH1 recessive embryonic lethal locus segregating in the Montbéliarde breed. In this follow-up study, we excluded this candidate variant because healthy homozygous carriers were observed in large-scale genotyping data generated in the framework of the genomic selection program. We fine mapped the MH1 locus in a 702-kb interval and analyzed genome sequence data from the 1,000 bull genomes project and 54 Montbéliarde bulls (including 14 carriers and 40 noncarriers). We report the identification of a strong candidate mutation in the gene encoding phosphoribosylformylglycinamidine synthase (PFAS), a protein involved in de novo purine synthesis. This mutation, located in a class I glutamine amidotransferase-like domain, results in the substitution of an arginine residue that is entirely conserved among eukaryotes by a cysteine (p.R1205C). No homozygote for the cysteine-encoding allele was observed in a large population of more than 25,000 individuals despite a 6.7% allelic frequency and 122 expected homozygotes under neutrality assumption. Genotyping of 18 embryos collected from heterozygous parents as well as analysis on nonreturn rates suggested that most homozygous carriers died between 7 and 35 d postinsemination. The identification of this strong candidate mutation will enable the accurate testing of the reproducers and the efficient selection against this lethal recessive embryonic defect in the Montbéliarde breed.

Construction of a large collection of small genome variations in French dairy and beef breeds using whole-genome sequences.

BACKGROUND: In recent years, several bovine genome sequencing projects were carried out with the aim of developing genomic tools to improve dairy and beef production efficiency and sustainability. RESULTS: In this study, we describe the first French cattle genome variation dataset obtained by sequencing 274 whole genomes representing several major dairy and beef breeds. This dataset contains over 28 million single nucleotide polymorphisms (SNPs) and small insertions and deletions. Comparisons between sequencing results and SNP array genotypes revealed a very high genotype concordance rate, which indicates the good quality of our data. CONCLUSIONS: To our knowledge, this is the first large-scale catalog of small genomic variations in French dairy and beef cattle. This resource will contribute to the study of gene functions and population structure and also help to improve traits through genotype-guided selection.

Multi-omics data integration for the identification of biomarkers for bull fertility.

Bull fertility is an important economic trait, and the use of subfertile semen for artificial insemination decreases the global efficiency of the breeding sector. Although the analysis of semen functional parameters can help to identify infertile bulls, no tools are currently available to enable precise predictions and prevent the commercialization of subfertile semen. Because male fertility is a multifactorial phenotype that is dependent on genetic, epigenetic, physiological and environmental factors, we hypothesized that an integrative analysis might help to refine our knowledge and understanding of bull fertility. We combined -omics data (genotypes, sperm DNA methylation at CpGs and sperm small non-coding RNAs) and semen parameters measured on a large cohort of 98 Montbéliarde bulls with contrasting fertility levels. Multiple Factor Analysis was conducted to study the links between the datasets and fertility. Four methodologies were then considered to identify the features linked to bull fertility variation: Logistic Lasso, Random Forest, Gradient Boosting and Neural Networks. Finally, the features selected by these methods were annotated in terms of genes, to conduct functional enrichment analyses. The less relevant features in -omics data were filtered out, and MFA was run on the remaining 12,006 features, including the 11 semen parameters and a balanced proportion of each type of-omics data. The results showed that unlike the semen parameters studied the-omics datasets were related to fertility. Biomarkers related to bull fertility were selected using the four methodologies mentioned above. The most contributory CpGs, SNPs and miRNAs targeted genes were all found to be involved in development. Interestingly, fragments derived from ribosomal RNAs were overrepresented among the selected features, suggesting roles in male fertility. These markers could be used in the future to identify subfertile bulls in order to increase the global efficiency of the breeding sector.

High-density marker imputation accuracy in sixteen French cattle breeds.

BACKGROUND: Genotyping with the medium-density Bovine SNP50 BeadChip® (50K) is now standard in cattle. The high-density BovineHD BeadChip®, which contains 777,609 single nucleotide polymorphisms (SNPs), was developed in 2010. Increasing marker density increases the level of linkage disequilibrium between quantitative trait loci (QTL) and SNPs and the accuracy of QTL localization and genomic selection. However, re-genotyping all animals with the high-density chip is not economically feasible. An alternative strategy is to genotype part of the animals with the high-density chip and to impute high-density genotypes for animals already genotyped with the 50K chip. Thus, it is necessary to investigate the error rate when imputing from the 50K to the high-density chip. METHODS: Five thousand one hundred and fifty three animals from 16 breeds (89 to 788 per breed) were genotyped with the high-density chip. Imputation error rates from the 50K to the high-density chip were computed for each breed with a validation set that included the 20% youngest animals. Marker genotypes were masked for animals in the validation population in order to mimic 50K genotypes. Imputation was carried out using the Beagle 3.3.0 software. RESULTS: Mean allele imputation error rates ranged from 0.31% to 2.41% depending on the breed. In total, 1980 SNPs had high imputation error rates in several breeds, which is probably due to genome assembly errors, and we recommend to discard these in future studies. Differences in imputation accuracy between breeds were related to the high-density-genotyped sample size and to the genetic relationship between reference and validation populations, whereas differences in effective population size and level of linkage disequilibrium showed limited effects. Accordingly, imputation accuracy was higher in breeds with large populations and in dairy breeds than in beef breeds. More than 99% of the alleles were correctly imputed if more than 300 animals were genotyped at high-density. No improvement was observed when multi-breed imputation was performed. CONCLUSION: In all breeds, imputation accuracy was higher than 97%, which indicates that imputation to the high-density chip was accurate. Imputation accuracy depends mainly on the size of the reference population and the relationship between reference and target populations.

Predicting male fertility from the sperm methylome: application to 120 bulls with hundreds of artificial insemination records.

BACKGROUND: Conflicting results regarding alterations to sperm DNA methylation in cases of spermatogenesis defects, male infertility and poor developmental outcomes have been reported in humans. Bulls used for artificial insemination represent a relevant model in this field, as the broad dissemination of bull semen considerably alleviates confounding factors and enables the precise assessment of male fertility. This study was therefore designed to assess the potential for sperm DNA methylation to predict bull fertility. RESULTS: A unique collection of 100 sperm samples was constituted by pooling 2-5 ejaculates per bull from 100 Montbéliarde bulls of comparable ages, assessed as fertile (n = 57) or subfertile (n = 43) based on non-return rates 56 days after insemination. The DNA methylation profiles of these samples were obtained using reduced representation bisulfite sequencing. After excluding putative sequence polymorphisms, 490 fertility-related differentially methylated cytosines (DMCs) were identified, most of which were hypermethylated in subfertile bulls. Interestingly, 46 genes targeted by DMCs are involved in embryonic and fetal development, sperm function and maturation, or have been related to fertility in genome-wide association studies; five of these were further analyzed by pyrosequencing. In order to evaluate the prognostic value of fertility-related DMCs, the sperm samples were split between training (n = 67) and testing (n = 33) sets. Using a Random Forest approach, a predictive model was built from the methylation values obtained on the training set. The predictive accuracy of this model was 72% on the testing set and 72% on individual ejaculates collected from an independent cohort of 20 bulls. CONCLUSION: This study, conducted on the largest set of bull sperm samples so far examined in epigenetic analyses, demonstrated that the sperm methylome is a valuable source of male fertility biomarkers. The next challenge is to combine these results with other data on the same sperm samples in order to improve the quality of the model and better understand the interplay between DNA methylation and other molecular features in the regulation of fertility. This research may have potential applications in human medicine, where infertility affects the interaction between a male and a female, thus making it difficult to isolate the male factor.

Sequence-based GWAS and post-GWAS analyses reveal a key role of SLC37A1, ANKH, and regulatory regions on bovine milk mineral content.

The mineral composition of bovine milk plays an important role in determining its nutritional and cheese-making value. Concentrations of the main minerals predicted from mid-infrared spectra produced during milk recording, combined with cow genotypes, provide a unique opportunity to decipher the genetic determinism of these traits. The present study included 1 million test-day predictions of Ca, Mg, P, K, Na, and citrate content from 126,876 Montbéliarde cows, of which 19,586 had genotype data available. All investigated traits were highly heritable (0.50-0.58), with the exception of Na (0.32). A sequence-based genome-wide association study (GWAS) detected 50 QTL (18 affecting two to five traits) and positional candidate genes and variants, mostly located in non-coding sequences. In silico post-GWAS analyses highlighted 877 variants that could be regulatory SNPs altering transcription factor (TF) binding sites or located in non-coding RNA (mainly lncRNA). Furthermore, we found 47 positional candidate genes and 45 TFs highly expressed in mammary gland compared to 90 other bovine tissues. Among the mammary-specific genes, SLC37A1 and ANKH, encoding proteins involved in ion transport were located in the most significant QTL. This study therefore highlights a comprehensive set of functional candidate genes and variants that affect milk mineral content.