The regular decrease of female fertility over time is a major concern in modern dairy cattle industry. Only half of this decrease is explained by indirect response to selection on milk production, ...suggesting the existence of other factors such as embryonic lethal genetic defects. Genomic regions harboring recessive deleterious mutations were detected in three dairy cattle breeds by identifying frequent haplotypes (>1%) showing a deficit in homozygotes among Illumina Bovine 50k Beadchip haplotyping data from the French genomic selection database (47,878 Holstein, 16,833 Montbéliarde, and 11,466 Normande animals). Thirty-four candidate haplotypes (p<10(-4)) including previously reported regions associated with Brachyspina, CVM, HH1, and HH3 in Holstein breed were identified. Haplotype length varied from 1 to 4.8 Mb and frequencies from 1.7 up to 9%. A significant negative effect on calving rate, consistent in heifers and in lactating cows, was observed for 9 of these haplotypes in matings between carrier bulls and daughters of carrier sires, confirming their association with embryonic lethal mutations. Eight regions were further investigated using whole genome sequencing data from heterozygous bull carriers and control animals (45 animals in total). Six strong candidate causative mutations including polymorphisms previously reported in FANCI (Brachyspina), SLC35A3 (CVM), APAF1 (HH1) and three novel mutations with very damaging effect on the protein structure, according to SIFT and Polyphen-2, were detected in GART, SHBG and SLC37A2 genes. In conclusion, this study reveals a yet hidden consequence of the important inbreeding rate observed in intensively selected and specialized cattle breeds. Counter-selection of these mutations and management of matings will have positive consequences on female fertility in dairy cattle.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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.
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.
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.
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.
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 β-lactoglobulin) and casein (αs1, αs2, β, and κ) contents were estimated by mid-infrared (MIR) spectrometry, with medium to high accuracy (0.59 ≤ R
≤ 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.
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).
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.
Milk quality in dairy cattle is routinely assessed via analysis of mid-infrared (MIR) spectra; this approach can also be used to predict the milk's cheese-making properties (CMP) and composition. ...When this method of high-throughput phenotyping is combined with efficient imputations of whole-genome sequence data from cows' genotyping data, it provides a unique and powerful framework with which to carry out genomic analyses. The goal of this study was to use this approach to identify genes and gene networks associated with milk CMP and composition in the Montbéliarde breed.
Milk cheese yields, coagulation traits, milk pH and contents of proteins, fatty acids, minerals, citrate, and lactose were predicted from MIR spectra. Thirty-six phenotypes from primiparous Montbéliarde cows (1,442,371 test-day records from 189,817 cows) were adjusted for non-genetic effects and averaged per cow. 50 K genotypes, which were available for a subset of 19,586 cows, were imputed at the sequence level using Run6 of the 1000 Bull Genomes Project (comprising 2333 animals). The individual effects of 8.5 million variants were evaluated in a genome-wide association study (GWAS) which led to the detection of 59 QTL regions, most of which had highly significant effects on CMP and milk composition. The results of the GWAS were further subjected to an association weight matrix and the partial correlation and information theory approach and we identified a set of 736 co-associated genes. Among these, the well-known caseins, PAEP and DGAT1, together with dozens of other genes such as SLC37A1, ALPL, MGST1, SEL1L3, GPT, BRI3BP, SCD, GPAT4, FASN, and ANKH, explained from 12 to 30% of the phenotypic variance of CMP traits. We were further able to identify metabolic pathways (e.g., phosphate and phospholipid metabolism and inorganic anion transport) and key regulator genes, such as PPARA, ASXL3, and bta-mir-200c that are functionally linked to milk composition.
By using an approach that integrated GWAS with network and pathway analyses at the whole-genome sequence level, we propose candidate variants that explain a substantial proportion of the phenotypic variance of CMP traits and could thus be included in genomic evaluation models to improve milk CMP in Montbéliarde cows.
Size of the reference population and reliability of phenotypes are crucial factors influencing the reliability of genomic predictions. It is therefore useful to combine closely related populations. ...Increased accuracies of genomic predictions depend on the number of individuals added to the reference population, the reliability of their phenotypes, and the relatedness of the populations that are combined.
This paper assesses the increase in reliability achieved when combining four Holstein reference populations of 4000 bulls each, from European breeding organizations, i.e. UNCEIA (France), VikingGenetics (Denmark, Sweden, Finland), DHV-VIT (Germany) and CRV (The Netherlands, Flanders). Each partner validated its own bulls using their national reference data and the combined data, respectively.
Combining the data significantly increased the reliability of genomic predictions for bulls in all four populations. Reliabilities increased by 10%, compared to reliabilities obtained with national reference populations alone, when they were averaged over countries and the traits evaluated. For different traits and countries, the increase in reliability ranged from 2% to 19%.
Genomic selection programs benefit greatly from combining data from several closely related populations into a single large reference population.
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.
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.
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.
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.
We herein study genetic recombination in three cattle populations from France, New Zealand, and the Netherlands. We identify 2,395,177 crossover (CO) events in 94,516 male gametes, and 579,996 CO ...events in 25,332 female gametes. The average number of COs was found to be larger in males (23.3) than in females (21.4). The heritability of global recombination rate (GRR) was estimated at 0.13 in males and 0.08 in females, with a genetic correlation of 0.66 indicating that shared variants are influencing GRR in both sexes. A genome-wide association study identified seven quantitative trait loci (QTL) for GRR. Fine-mapping following sequence-based imputation in 14,401 animals pinpointed likely causative coding (5) and noncoding (1) variants in genes known to be involved in meiotic recombination (HFM1, MSH4, RNF212, MLH3, MSH5) for 5/7 QTL, and noncoding variants (3) in RNF212B for 1/7 QTL. This suggests that this RNF212 paralog might also be involved in recombination. Most of the identified mutations had significant effects in both sexes, with three of them each accounting for ∼10% of the genetic variance in males.
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.
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.
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.
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).
Estimates of the proportions of heritability due to autosomes and X chromosome (h²
) were consistent among breeds. On average over the 11 traits, h²
=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.
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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Bovine paratuberculosis is a contagious disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP), with adverse effects on animal welfare and serious economic consequences. Published ...results on host genetic resistance to MAP are inconsistent, mainly because of difficulties in characterizing the infection status of cows. The objectives of this study were to identify quantitative trait loci (QTL) for resistance to MAP in Holstein and Normande cows with an accurately defined status for MAP.
From MAP-infected herds, cows without clinical signs of disease were subjected to at least four repeated serum ELISA and fecal PCR tests over time to determine both infected and non-infected statuses. Clinical cases were confirmed using PCR. Only cows that had concordant results for all tests were included in further analyses. Positive and control cows were matched within herd according to their birth date to ensure a same level of exposure to MAP. Cows with accurate phenotypes, i.e. unaffected (control) or affected (clinical or non-clinical cases), were genotyped with the Illumina BovineSNP50 BeadChip. Genotypes were imputed to whole-genome sequences using the 1000 Bull Genomes reference population (run6). A genome-wide association study (GWAS) of MAP status of 1644 Holstein and 649 Normande cows, using either two (controls versus cases) or three classes of phenotype (controls, non-clinical and clinical cases), revealed three regions, on Bos taurus (BTA) chromosomes 12, 13, and 23, presenting significant effects in Holstein cows, while only one of those was identified in Normande cows (BTA23). The most significant effect was found on BTA13, in a short 8.5-kb region. Conditional analyses revealed that only one causal variant may be responsible for the effects observed on each chromosome with the ABCC4 (BTA12), CBFA2T2 (BTA13), and IER3 (BTA23) genes as good functional candidates.
A sequence-based GWAS on cows for which resistance to MAP was accurately defined, was able to identify candidate variants located in genes that were functionally related to resistance to MAP; these explained up to 28% of the genetic variance of the trait. These results are very encouraging for efforts towards implementation of a breeding strategy aimed at improving resistance to paratuberculosis in Holstein cows.
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