S. Fritz

Estimation of genetic parameters and genome scan for 15 semen characteristics traits of Holstein bulls

A QTL detection experiment was performed in French dairy cattle to search for QTL related to male fertility. Ten families, involving a total of 515 bulls, were phenotyped for ejaculated volume and sperm concentration, number of spermatozoa, motility, velocity, percentage of motile spermatozoa after thawing and abnormal spermatozoa. A set of 148 microsatellite markers were used to realize a genome scan. First, genetic parameters were estimated for all traits. Semen production traits were found to have moderate heritabilities (from 0.15 to 0.30) while some of the semen quality traits such as motility had high heritabilities (close to 0.60). Genetic correlations among traits showed negative relationships between volume and concentration and between volume and most quality traits such as motility or abnormal sperm while correlations between concentration and these traits were rather favourable. Percentages of abnormal sperm were negatively related to quality traits, especially with motility and velocity of spermatozoa. Three QTL related to abnormal sperm frequencies were significant at p < 0.01. In total, 11 QTL (p < 0.05) were detected. However, the number of QTL detected was within the range of expected false positives. Because of the lack of power to find QTL in this design further analyses are required to confirm these QTL.

Application of Bayesian least absolute shrinkage and selection operator (LASSO) and BayesCπ methods for genomic selection in French Holstein and Montbéliarde breeds.

Recently, the amount of available single nucleotide polymorphism (SNP) marker data has considerably increased in dairy cattle breeds, both for research purposes and for application in commercial breeding and selection programs. Bayesian methods are currently used in the genomic evaluation of dairy cattle to handle very large sets of explanatory variables with a limited number of observations. In this study, we applied 2 bayesian methods, BayesCπ and bayesian least absolute shrinkage and selection operator (LASSO), to 2 genotyped and phenotyped reference populations consisting of 3,940 Holstein bulls and 1,172 Montbéliarde bulls with approximately 40,000 polymorphic SNP. We compared the accuracy of the bayesian methods for the prediction of 3 traits (milk yield, fat content, and conception rate) with pedigree-based BLUP, genomic BLUP, partial least squares (PLS) regression, and sparse PLS regression, a variable selection PLS variant. The results showed that the correlations between observed and predicted phenotypes were similar in BayesCπ (including or not pedigree information) and bayesian LASSO for most of the traits and whatever the breed. In the Holstein breed, bayesian methods led to higher correlations than other approaches for fat content and were similar to genomic BLUP for milk yield and to genomic BLUP and PLS regression for the conception rate. In the Montbéliarde breed, no method dominated the others, except BayesCπ for fat content. The better performances of the bayesian methods for fat content in Holstein and Montbéliarde breeds are probably due to the effect of the DGAT1 gene. The SNP identified by the BayesCπ, bayesian LASSO, and sparse PLS regression methods, based on their effect on the different traits of interest, were located at almost the same position on the genome. As the bayesian methods resulted in regressions of direct genomic values on daughter trait deviations closer to 1 than for the other methods tested in this study, bayesian methods are suggested for genomic evaluations of French dairy cattle.

A comparison of partial least squares (PLS) and sparse PLS regressions in genomic selection in French dairy cattle.

Genomic selection involves computing a prediction equation from the estimated effects of a large number of DNA markers based on a limited number of genotyped animals with phenotypes. The number of observations is much smaller than the number of independent variables, and the challenge is to find methods that perform well in this context. Partial least squares regression (PLS) and sparse PLS were used with a reference population of 3,940 genotyped and phenotyped French Holstein bulls and 39,738 polymorphic single nucleotide polymorphism markers. Partial least squares regression reduces the number of variables by projecting independent variables onto latent structures. Sparse PLS combines variable selection and modeling in a one-step procedure. Correlations between observed phenotypes and phenotypes predicted by PLS and sparse PLS were similar, but sparse PLS highlighted some genome regions more clearly. Both PLS and sparse PLS were more accurate than pedigree-based BLUP and generally provided lower correlations between observed and predicted phenotypes than did genomic BLUP. Furthermore, PLS and sparse PLS required similar computing time to genomic BLUP for the study of 6 traits.

An ABC estimate of pedigree error rate: application in dog, sheep and cattle breeds

On the basis of correlations between pairwise individual genealogical kinship coefficients and allele sharing distances computed from genotyping data, we propose an approximate Bayesian computation (ABC) approach to assess pedigree file reliability through gene-dropping simulations. We explore the features of the method using simulated data sets and show precision increases with the number of markers. An application is further made with five dog breeds, four sheep breeds and one cattle breed raised in France and displaying various characteristics and population sizes, using microsatellite or SNP markers. Depending on the breeds, pedigree error estimations range between 1% and 9% in dog breeds, 1% and 10% in sheep breeds and 4% in cattle breeds.

Whole-genome scan to detect quantitative trait loci associated with milk protein composition in 3 French dairy cattle breeds

In the context of the PhénoFinLait project, a genome-wide analysis was performed to detect quantitative trait loci (QTL) that affect milk protein composition estimated using mid-infrared spectrometry in the Montbéliarde (MO), Normande (NO), and Holstein (HO) French dairy cattle breeds. The 6 main milk proteins (α-lactalbumin, β-lactoglobulin, and αS1-, αS2-, β-, and κ-caseins) expressed as grams per 100g of milk (% of milk) or as grams per 100g of protein (% of protein) were estimated in 848,068 test-day milk samples from 156,660 cows. Genotyping was performed for 2,773 MO, 2,673 NO, and 2,208 HO cows using the Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA). Individual test-day records were adjusted for environmental effects and then averaged per cow to define the phenotypes analyzed. Quantitative trait loci detection was performed within each breed using a linkage disequilibrium and linkage analysis approach. A total of 39 genomic regions distributed on 20 of the 29 Bos taurus autosomes (BTA) were significantly associated with milk protein composition at a genome-wide level of significance in at least 1 of the 3 breeds. The 9 most significant QTL were located on BTA2 (133 Mbp), BTA6 (38, 47, and 87 Mbp), BTA11 (103 Mbp), BTA14 (1.8 Mbp), BTA20 (32 and 58 Mbp), and BTA29 (8 Mbp). The BTA6 (87 Mbp), BTA11, and BTA20 (58 Mbp) QTL were found in all 3 breeds, and they had highly significant effects on κ-casein, β-lactoglobulin, and α-lactalbumin, expressed as a percentage of protein, respectively. Each of these QTL explained between 13% (BTA14) and 51% (BTA11) of the genetic variance of the trait. Many other QTL regions were also identified in at least one breed. They were located on 14 additional chromosomes (1, 3, 4, 5, 7, 15, 17, 19, 21, 22, 24, 25, 26, and 27), and they explained 2 to 8% of the genetic variance of 1 or more protein composition traits. Concordance analyses, performed between QTL status and sequence-derived polymorphisms from 13 bulls, revealed previously known causal polymorphisms in LGB (BTA11) and GHR (BTA20 at 32 Mbp) and excluded some other previously described mutations. These results constitute a first step in identifying causal mutations and using routinely collected mid-infrared predictions in future genomic selection programs to improve bovine milk protein composition.

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

BackgroundIn 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.ResultsIn 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.ConclusionsTo 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.

Sire effect on early and late embryonic death in French Holstein cattle

We investigated the effect of maternal sire on early pregnancy failure (between D0, day of insemination and D90) in their progeny during the first and second lactations (n=3508) in the Holstein breed. The estimated breeding value (EBV) for cow fertility of 12 bulls (reliability⩾0.95) was used to create the following three groups: low, medium and high EBV (EBV from -0.7 to 1 expressed as genetic standard deviation relative to the mean of the breed). In their daughters (93 to 516 per bull), progesterone measurement was carried out on the day of artificial insemination (AI; D0) to check whether the cows were in the follicular phase and on D18 to 25 to assess non-fertilisation-early embryonic mortality (NF-EEM). Late embryonic mortality (LEM) and early foetal death (FD) were determined by ultrasonography on D45 and D90 and by the return to oestrus after the first AI. Frequencies of NF-EEM, LEM, FD and pregnancy were 33.3%, 11.7%, 1.4% and 48.5% and incidences were 35.1, 19.0, 2.7 and 51.1, respectively. Sire EBV was significantly related to the incidences of pregnancy failure between D0 and D90, fertilisation failure-early embryonic mortality (FF-EEM) and LEM but not to the incidence of FD between D45 and D90 of pregnancy. The relative risk (RR) of FF-EEM was significantly higher (RR=1.2; P<0.05) for the progeny group of low EBV bulls when compared with high EBV bulls. The same effect was observed when comparing LEM of the progeny groups from the low EBV bulls to those from moderate and high EBV bulls (RR, respectively, of 1.3 and 1.4; P<005). The incidence of FF-EEM was significantly higher when cows were inseminated before 80 days postpartum compared with later, and for the extreme values of the difference between milk fat and protein content measured during the first 3 months of lactation. FF-EEM was also significantly related to the year of observation. The incidence of LEM was higher for the highest producing cows and was influenced by interaction between milk yield×lactation rank and milk yield×milk protein content. In conclusion, this study showed large differences in early pregnancy failure between progeny groups and highlights the interest of accurate characterisation of embryonic death in order to identify potential candidate genes for female fertility.

A Generalized Caprine-like Hypoplasia Syndrome is localized within a 6-cM interval on bovine chromosome 13 in the Montbeliarde breed.

Caprine-like Generalized Hypoplasia Syndrome (or SHGC) is a new hereditary disorder described in the Montbéliarde breed. We report here the characterization of this new disease, based on the visual examination of animals affected by SHGC, and on physiological and biochemical studies undertaken on samples of both SHGC and normal animals. Biological samples for more than 150 affected calves and their parents have been collected over the past 4 years within the framework of the Bovine Genetic Disease Observatory. First, pedigree analyses showed that the mode of inheritance is most probably autosomal recessive. Then, a genome scan with 113 animals and 140 microsatellite markers revealed a single locus within a 35-cM region on bovine chromosome 13. Genotypes of 261 animals for 18 new microsatellite markers from the region confirmed the localization of the disorder to a 6-cM interval. Finally, based on the analysis of haplotypes in 463 Montbéliarde sires, we estimated the frequency of the SHGC mutated allele in the population and could propose a strategy for the systematic eradication of this disorder in the near future.

Progressive ataxia of Charolais cattle highlights a role of KIF1C in sustainable myelination

Hereditary spastic paraplegias (HSPs) are clinically and genetically heterogeneous human neurodegenerative diseases. Amongst the identified genetic causes, mutations in genes encoding motor proteins such as kinesins have been involved in various HSP clinical isoforms. Mutations in KIF1C are responsible for autosomal recessive spastic paraplegia type 58 (SPG58) and spastic ataxia 2 (SPAX2). Bovines also develop neurodegenerative diseases, some of them having a genetic aetiology. Bovine progressive ataxia was first described in the Charolais breed in the early 1970s in England and further cases in this breed were subsequently reported worldwide. We can now report that progressive ataxia of Charolais cattle results from a homozygous single nucleotide polymorphism in the coding region of the KIF1C gene. In this study, we show that the mutation at the heterozygous state is associated with a better score for muscular development, explaining its balancing selection for several decades, and the resulting high frequency (13%) of the allele in the French Charolais breed. We demonstrate that the KIF1C bovine mutation leads to a functional knock-out, therefore mimicking mutations in humans affected by SPG58/SPAX2. The functional consequences of KIF1C loss of function in cattle were also histologically reevaluated. We showed by an immunochemistry approach that demyelinating plaques were due to altered oligodendrocyte membrane protrusion, and we highlight an abnormal accumulation of actin in the core of demyelinating plaques, which is normally concentrated at the leading edge of oligodendrocytes during axon wrapping. We also observed that the lesions were associated with abnormal extension of paranodal sections. Moreover, this model highlights the role of KIF1C protein in preserving the structural integrity and function of myelin, since the clinical signs and lesions arise in young-adult Charolais cattle. Finally, this model provides useful information for SPG58/SPAX2 disease and other demyelinating lesions.

Genome-wide association study for milking speed in French Holstein cows

Using a combination of data from the BovineSNP50 BeadChip SNP array (Illumina, San Diego, CA) and a EuroGenomics (Amsterdam, the Netherlands) custom single nucleotide polymorphism (SNP) chip with SNP pre-selected from whole genome sequence data, we carried out an association study of milking speed in 32,491 French Holstein dairy cows. Milking speed was measured by a score given by the farmer. Phenotypes were yield deviations as obtained from the French evaluation system. They were analyzed with a linear mixed model for association studies. We identified SNP on 22 chromosomes significantly associated with milking speed. As clinical mastitis and somatic cell score have an unfavorable genetic correlation with milking speed, we tested whether the most significant SNP on these 22 chromosomes associated with milking speed were also associated with clinical mastitis or somatic cell score. Nine hundred seventy-one genome-wide significant SNP were associated with milking speed. Of these, 86 were associated with clinical mastitis and 198 with somatic cell score. The most significant association signals for milking speed were observed on chromosomes 7, 8, 10, 14, and 18. The most significant signal was located on chromosome 14 (ZFAT gene). Eleven novel milking speed quantitative trait loci (QTL) were observed on chromosomes 7, 10, 11, 14, 18, 25, and 26. Twelve candidate SNP for milking speed mapped directly within genes. Of these, 10 were QTL lead SNP, which mapped within the genes HMHA1, POLR2E, GNB5, KLHL29, ZFAT, KCNB2, CEACAM18, CCL24, and LHPP. Limited pleiotropy was observed between milking speed QTL and clinical mastitis.