Association analysis for udder index and milking speed with imputed whole-genome sequence variants in Nordic Holstein cattle

Genome-Wide Association Study for Body Conformation Traits and Fitness in Czech Holsteins

The aim of this study was a genome-wide association study (GWAS) on conformation traits using 25,486 genotyped Czech Holsteins, with 35,227 common SNPs for each genotype. Linear trait records were collected between 1995 and 2020. The Interbull information from Multiple Across Country Evaluation (MACE) was included for bulls that mostly had daughter records in a foreign country. When using the Bonferroni correction, the number of SNPs that were either significant or approached the significance threshold was low-dairy capacity composite on BTA4, feet and legs composite BTA21, total score BTA10, stature BTA24, body depth BTA6, angularity BTA20, fore udder attachment BTA10. Without the Bonferroni correction, the total number of significant or near of significance SNPs was 32. The SNPs were localized on BTA1,2,4,5,6,7,8,18,22,25,26,28 for dairy capacity composite, BTA15,21 for feet and legs composite, BTA10 for total score, BTA24 stature, BTA6,23 body depth, BTA20 angularity, BTA2 rump angle, BTA9,10 rear legs rear view, BTA2,19 rear legs side view, BTA10 fore udder attachment, BTA2 udder depth, BTA10 rear udder height, BTA12 central alignment, BTA24 rear teat placement, BTA8,29 rear udder width. The results provide biological information for the improvement of body conformation and fitness in the Holstein population.

Genome-Wide Genomic and Functional Association Study for Workability and Calving Traits in Holstein Cattle

The goal of our study was to identify the SNPs, metabolic pathways (KEGG), and gene ontology (GO) terms significantly associated with calving and workability traits in dairy cattle. We analysed direct (DCE) and maternal (MCE) calving ease, direct (DSB) and maternal (MSB) stillbirth, milking speed (MSP), and temperament (TEM) based on a Holstein-Friesian dairy cattle population consisting of 35,203 individuals. The number of animals, depending on the trait, ranged from 22,301 bulls for TEM to 30,603 for DCE. We estimated the SNP effects (based on 46,216 polymorphisms from Illumina BovineSNP50 BeadChip Version 2) using a multi-SNP mixed model. The SNP positions were mapped to genes and the GO terms/KEGG pathways of the corresponding genes were assigned. The estimation of the GO term/KEGG pathway effects was based on a mixed model using the SNP effects as dependent variables. The number of significant SNPs comprised 59 for DCE, 25 for DSB and MSP, 17 for MCE and MSB, and 7 for TEM. Significant KEGG pathways were found for MSB (2), TEM (2), and MSP (1) and 11 GO terms were significant for MSP, 10 for DCE, 8 for DSB and TEM, 5 for MCE, and 3 for MSB. From the perspective of a better understanding of the genomic background of the phenotypes, traits with low heritabilities suggest that the focus should be moved from single genes to the metabolic pathways or gene ontologies significant for the phenotype.

Genome-wide associations for heat stress response suggest potential candidate genes underlying milk fatty acid composition in dairy cattle

Contents of milk fatty acids (FA) display remarkable alterations along climatic gradients. Detecting candidate genes underlying such alterations might be beneficial for the exploration of climate sensitivity in dairy cattle. Consequently, we aimed on the definition of FA heat stress indicators, considering FA breeding values in response to temperature-humidity index (THI) alterations. Indicators were used in GWAS, in ongoing gene annotations and for the estimation of chromosome-wide variance components. The phenotypic data set consisted of 39,600 test-day milk FA records from 5,757 first-lactation Holstein dairy cows kept in 16 large-scale German cooperator herds. The FA traits were C18:0, polyunsaturated fatty acids (PUFA), saturated fatty acids (SFA), and unsaturated fatty acids (UFA). After genotype quality control, 40,523 SNP markers from 3,266 cows and 930 sires were considered. Meteorological data from the weather station in closest herd distance were used for the calculation of maximum hourly daily THI, which were allocated to 10 different THI classes. The same FA from 3 stages of lactation were considered as different, but genetically correlated traits. Consequently, a 3-trait reaction norm model was used to estimate genetic parameters and breeding values for FA along THI classes, considering either pedigree (A) or genomic (G) relationship matrices. De-regressed proofs and genomic estimated breeding values at the intermediate THI class 5 and at the extreme THI class 10 were used as pseudophenotypes in ongoing genomic analyses for thermoneutral (TNC) and heat stress conditions (HSC), respectively. The differences in de-regressed proofs and in genomic estimated breeding values from both THI classes were pseudophenotypes for heat stress response (HSR). Genetic correlations between the same FA under TNC and HSC were smallest in the first lactation stage and ranged from 0.20 for PUFA to 0.87 for SFA when modeling with the A matrix, and from 0.35 for UFA to 0.86 for SFA when modeling with the G matrix. In the first lactation stage, larger additive genetic variances under HSC compared with TNC indicate climate sensitivity for C18:0, PUFA, and UFA. Climate sensitivity was also reflected by pronounced chromosome-wide genetic variances for HSR of PUFA and UFA in the first stage of lactation. For all FA under TNC, HSC, and HSR, quite large genetic variance proportions were explained by BTA14. In GWAS, 30 SNP (within or close to 38 potential candidate genes) overlapped for HSR of the different FA. One unique potential candidate gene (AMFR) was detected for HSR of PUFA, 15 for HSR of SFA (ADGRB1, DENND3, DUSP16, EFR3A, EMP1, ENSBTAG00000003838, EPS8, MGP, PIK3C2G, STYK1, TMEM71, GSG1, SMARCE1, CCDC57, and FASN) and 3 for HSR of UFA (ENSBTAG00000048091, PAEP, and EPPK1). The identified unique genes play key roles in milk FA synthesis and are associated with disease resistance in dairy cattle. The results suggest consideration of FA in combination with climatic responses when inferring genetic mechanisms of heat stress in dairy cows.

Genome-wide association study with imputed whole-genome sequence variants including large deletions for female fertility in 3 Nordic dairy cattle breeds

Fertility is an economically important trait in livestock. Poor fertility in dairy cattle can be due to loss-of-function variants affecting any essential gene that causes early embryonic mortality in homozygotes. To identify fertility-associated quantitative trait loci, we performed single-marker association analyses for 8 fertility traits in Holstein, Jersey, and Nordic Red Dairy cattle using imputed whole-genome sequence variants including SNPs, indels, and large deletion. We then performed stepwise selection of independent markers from GWAS loci using conditional and joint association analyses. From single-marker analyses for fertility traits, we reported genome-wide significant associations of 30,384 SNPs, 178 indels, and 3 deletions in Holstein; 23,481 SNPs, 189 indels, and 13 deletions in Nordic Red; and 17 SNPs in Jersey cattle. Conditional and joint association analyses identified 37 and 23 independent associations in Holstein and Nordic Red Dairy cattle, respectively. Fertility-associated GWAS loci were enriched for developmental and cellular processes (Gene Ontology enrichment, false discovery rate < 0.05). For these quantitative trait loci regions (top marker and 500 kb of surrounding regions), we proposed several candidate genes with functional annotations corresponding to embryonic lethality and various fertility-related phenotypes in mouse and cattle. The inclusion of these top markers in future releases of the custom SNP chip used for genomic evaluations will enable their validation in independent populations and improve the accuracy of genomic predictions.

Assessing the genetic background and genomic relatedness of red cattle populations originating from Northern Europe

Background

Local cattle breeds need special attention, as they are valuable reservoirs of genetic diversity. Appropriate breeding decisions and adequate genomic management of numerically smaller populations are required for their conservation. At this point, the analysis of dense genome-wide marker arrays provides encompassing insights into the genomic constitution of livestock populations. We have analyzed the genetic characterization of ten cattle breeds originating from Germany, The Netherlands and Denmark belonging to the group of red dairy breeds in Northern Europe. The results are intended to provide initial evidence on whether joint genomic breeding strategies of these populations will be successful.

Results

Traditional Danish Red and Groningen White-Headed were the most genetically differentiated breeds and their populations showed the highest levels of inbreeding. In contrast, close genetic relationships and shared ancestry were observed for the populations of German Red and White Dual-Purpose, Dutch Meuse-Rhine-Yssel, and Dutch Deep Red breeds, reflecting their common histories. A considerable amount of gene flow from Red Holstein to German Angler and to German Red and White Dual-Purpose was revealed, which is consistent with frequent crossbreeding to improve productivity of these local breeds. In Red Holstein, marked genomic signatures of selection were reported on chromosome 18, suggesting directed selection for important breeding goal traits. Furthermore, tests for signatures of selection between Red Holstein, Red and White Dual-Purpose, and Meuse-Rhine-Yssel uncovered signals for all investigated pairs of populations. The corresponding genomic regions, which were putatively under different selection pressures, harboured various genes which are associated with traits such as milk and beef production, mastitis and female fertility.

Conclusions

This study provides comprehensive knowledge on the genetic constitution and genomic connectedness of divergent red cattle populations in Northern Europe. The results will help to design and optimize breeding strategies. A joint genomic evaluation including some of the breeds studied here seems feasible.

A Systematic Review of Genomic Regions and Candidate Genes Underlying Behavioral Traits in Farmed Mammals and Their Link with Human Disorders

Simple Summary

This study is a comprehensive review of genomic regions associated with animal behavior in farmed mammals (beef and dairy cattle, pigs, and sheep) which contributes to a better understanding of the biological mechanisms influencing the target indicator trait and to gene expression studies by suggesting genes likely controlling the trait, and it will be useful in optimizing genomic predictions of breeding values incorporating biological information. Behavioral mechanisms are complex traits, genetically controlled by multiple genes spread across the whole genome. The majority of the genes identified in cattle, pigs, and sheep in association with a plethora of behavioral measurements (e.g., temperament, terrain use, milking speed, tail biting, and sucking reflex) are likely controlling stimuli reception (e.g., olfactory), internal recognition of stimuli (e.g., neuroactive ligand–receptor interaction), and body response to a stimulus (e.g., blood pressure, fatty acidy metabolism, hormone signaling, and inflammatory pathways). Six genes were commonly identified between cattle and pigs. About half of the genes for behavior identified in farmed mammals were also identified in humans for behavioral, mental, and neuronal disorders. Our findings indicate that the majority of the genes identified are likely controlling animal behavioral outcomes because their biological functions as well as potentially differing allele frequencies between two breed groups (subjectively) clustered based on their temperament characteristics.

Abstract

The main objectives of this study were to perform a systematic review of genomic regions associated with various behavioral traits in the main farmed mammals and identify key candidate genes and potential causal mutations by contrasting the frequency of polymorphisms in cattle breeds with divergent behavioral traits (based on a subjective clustering approach). A total of 687 (cattle), 1391 (pigs), and 148 (sheep) genomic regions associated with 37 (cattle), 55 (pigs), and 22 (sheep) behavioral traits were identified in the literature. In total, 383, 317, and 15 genes overlap with genomic regions identified for cattle, pigs, and sheep, respectively. Six common genes (e.g., NR3C2, PITPNM3, RERG, SPNS3, U6, and ZFAT) were found for cattle and pigs. A combined gene-set of 634 human genes was produced through identified homologous genes. A total of 313 out of 634 genes have previously been associated with behavioral, mental, and neurologic disorders (e.g., anxiety and schizophrenia) in humans. Additionally, a total of 491 candidate genes had at least one statistically significant polymorphism (p-value < 0.05). Out of those, 110 genes were defined as having polymorphic regions differing in greater than 50% of exon regions. Therefore, conserved genomic regions controlling behavior were found across farmed mammal species and humans.

Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review

Genomics comprises a set of current and valuable technologies implemented as selection tools in dairy cattle commercial breeding programs. The intensive progeny testing for production and reproductive traits based on genomic breeding values (GEBVs) has been crucial to increasing dairy cattle productivity. The knowledge of key genes and haplotypes, including their regulation mechanisms, as markers for productivity traits, may improve the strategies on the present and future for dairy cattle selection. Genome-wide association studies (GWAS) such as quantitative trait loci (QTL), single nucleotide polymorphisms (SNPs), or single-step genomic best linear unbiased prediction (ssGBLUP) methods have already been included in global dairy programs for the estimation of marker-assisted selection-derived effects. The increase in genetic progress based on genomic predicting accuracy has also contributed to the understanding of genetic effects in dairy cattle offspring. However, the crossing within inbred-lines critically increased homozygosis with accumulated negative effects of inbreeding like a decline in reproductive performance. Thus, inaccurate-biased estimations based on empirical-conventional models of dairy production systems face an increased risk of providing suboptimal results derived from errors in the selection of candidates of high genetic merit-based just on low-heritability phenotypic traits. This extends the generation intervals and increases costs due to the significant reduction of genetic gains. The remarkable progress of genomic prediction increases the accurate selection of superior candidates. The scope of the present review is to summarize and discuss the advances and challenges of genomic tools for dairy cattle selection for optimizing breeding programs and controlling negative inbreeding depression effects on productivity and consequently, achieving economic-effective advances in food production efficiency. Particular attention is given to the potential genomic selection-derived results to facilitate precision management on modern dairy farms, including an overview of novel genome editing methodologies as perspectives toward the future.

Genomic information allows for more accurate breeding values for milkability in dual-purpose Italian Simmental cattle

Milkability is a trait related to the milking efficiency of an animal, and it is a component of the herd profitability. Due to its economic importance, milkability is currently included in the selection index of the Italian Simmental cattle breed with a weight of 7.5%. This lowly heritable trait is measured on a subjective scale from 1 to 3 (1 = slow, 3 = fast), and genetic evaluations are performed by pedigree-based BLUP. Genomic information is now available for some animals in the Italian Simmental population, and its inclusion in the genetic evaluation system could increase accuracy of breeding values and genetic progress for milkability. The aim of this study was to test the feasibility and advantages of having a genomic evaluation for this trait in the Italian Simmental population. Phenotypes were available for 131,308 cows. A total of 9,526 animals had genotypes for 42,152 loci; among the genotyped animals, 2,455 were cows with phenotypes, and the other were their relatives. The youngest cows with both phenotypes and genotypes (n = 900) were identified as selection candidates. Variance components and heritability were estimated using pedigree information, whereas genetic and genomic evaluations were carried out using BLUP and single-step genomic BLUP (ssGBLUP), respectively. In addition, a weighted ssGBLUP was assessed using genomic regions from a genome-wide association study. Evaluation models were validated using theoretical and realized accuracies. The estimated heritability for milkability was 0.12 ± 0.01. The mean theoretical accuracies for selection candidates were 0.43 ± 0.08 (BLUP) and 0.53 ± 0.06 (ssGBLUP). The mean realized accuracies based on linear regression statistics were 0.29 (BLUP) and 0.40 (ssGBLUP). No genomic regions were significantly associated with milkability, thus no improvements in accuracy were observed when using weighted ssGBLUP. Results indicated that genomic information could improve the accuracy of breeding values and increase genetic progress for milkability in Italian Simmental.

Using imputed whole-genome sequence variants to uncover candidate mutations and genes affecting milking speed and temperament in Holstein cattle

Milking speed (MS) and temperament (MT) are 2 workability traits of great importance in dairy cattle production and breeding. This is mainly due to an increased intensification of the worldwide production systems and greater adoption of precision technologies with less human-cattle interaction. Both MS and MT are heritable traits and thus, genomic selection is a promising tool to expedite their genetic progress. However, the genetic architecture and biological mechanisms underlying the phenotypic expression of these traits remain underexplored. In this study, we investigated the association of >5.7 million imputed whole-genome sequence variants with MT and MS in 4,381 and 4,219 North American Holstein cattle, respectively. The statistical analyses were performed using a mixed linear model fitting a polygenic effect. We detected 40 and 35 significant SNPs independently associated with MT and MS, respectively, which were distributed across 26 chromosomes. Eight candidate genes (GRIN3A, KCNJ3, BOSTAUV1R417, BOSTAUV1R419, MAP2K5, KCTD3, GAP43, and LSAMP) were suggested to play an important role in MT as they are involved in biologically relevant pathways, such as glutamatergic synapse, vomeronasal receptor and oxytocin signaling. Within their coding and upstream sequences, we used an independent data set to further detect or validate significantly differentiated SNP between cattle breeds with known differences in MT. There were fewer candidate genes potentially implicated in MS, but immunity-related genes (e.g., BOLA-NC1 and LOC512672), also identified in other populations, were validated in this study. The significant SNP and novel candidate genes identified contribute to a better understanding of the biological mechanisms underlying both traits in dairy cattle. This information will also be useful for the optimization of prediction of genomic breeding values by giving greater weights to SNP located in the genomic regions identified.

Genome-wide association study for mammary structure in Canadian Angus cows

Functional and enduring mammary structure is pivotal for producer profitability, and animal health and welfare in beef production. Genetic evaluations for teat and udder score in Canadian Angus cattle have previously been developed. The aim of this study was to identify genomic regions associated with teat and udder structure in Canadian Angus cows thereby enhancing knowledge of the biological architecture of these traits. Thus, we performed a weighted single-step genome wide association study (WssGWAS) to identify candidate genes for teat and udder score in 1,582 Canadian Angus cows typed with the GeneSeek^® Genomic Profiler Bovine 130K SNP array. Genomically enhanced estimated breeding values (GEBVs) were converted to SNP marker effects using unequal variances for markers to calculate weights for each SNP over three iterations. At the genome wide level, we detected windows of 20 consecutive SNPs that explained more than 0.5% of the variance observed in these traits. A total of 35 and 28 windows were identified for teat and udder score, respectively, with two SNP windows in common for both traits. Using Ensembl, the SNP windows were used to search for candidate genes and quantitative trait loci (QTL). A total of 94 and 71 characterized genes were identified in the regions for teat and udder score, respectively. Of these, 7 genes were common for both traits. Gene network and enrichment analysis, using Ingenuity Pathway Analysis (IPA), signified key pathways unique to each trait. Genes of interest were associated with immune response and wound healing, adipose tissue development and morphology, and epithelial and vascular development and morphology. Genetic architecture from this GWAS confirms that teat and udder score are distinct, polygenic traits involving varying and complex biological pathways, and that genetic selection for improved teat and udder score is possible.

Multi-trait meta-analyses reveal 25 quantitative trait loci for economically important traits in Brown Swiss cattle

Background

Little is known about the genetic architecture of economically important traits in Brown Swiss cattle because only few genome-wide association studies (GWAS) have been carried out in this breed. Moreover, most GWAS have been performed for single traits, thus not providing detailed insights into potentially existing pleiotropic effects of trait-associated loci.

Results

To compile a comprehensive catalogue of large-effect quantitative trait loci (QTL) segregating in Brown Swiss cattle, we carried out association tests between partially imputed genotypes at 598,016 SNPs and daughter-derived phenotypes for more than 50 economically important traits, including milk production, growth and carcass quality, body conformation, reproduction and calving traits in 4578 artificial insemination bulls from two cohorts of Brown Swiss cattle (Austrian-German and Swiss populations). Across-cohort multi-trait meta-analyses of the results from the single-trait GWAS revealed 25 quantitative trait loci (QTL; P < 8.36 × 10^− 8) for economically relevant traits on 17 Bos taurus autosomes (BTA). Evidence of pleiotropy was detected at five QTL located on BTA5, 6, 17, 21 and 25. Of these, two QTL at BTA6:90,486,780 and BTA25:1,455,150 affect a diverse range of economically important traits, including traits related to body conformation, calving, longevity and milking speed. Furthermore, the QTL at BTA6:90,486,780 seems to be a target of ongoing selection as evidenced by an integrated haplotype score of 2.49 and significant changes in allele frequency over the past 25 years, whereas either no or only weak evidence of selection was detected at all other QTL.

Conclusions

Our findings provide a comprehensive overview of QTL segregating in Brown Swiss cattle. Detected QTL explain between 2 and 10% of the variation in the estimated breeding values and thus may be considered as the most important QTL segregating in the Brown Swiss cattle breed. Multi-trait association testing boosts the power to detect pleiotropic QTL and assesses the full spectrum of phenotypes that are affected by trait-associated variants.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-6066-6) contains supplementary material, which is available to authorized users.

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.