Genomic associations with somatic cell score in first-lactation Holstein cows

GWABLUP: genome-wide association assisted best linear unbiased prediction of genetic values

BACKGROUND

Since the very beginning of genomic selection, researchers investigated methods that improved upon SNP-BLUP (single nucleotide polymorphism best linear unbiased prediction). SNP-BLUP gives equal weight to all SNPs, whereas it is expected that many SNPs are not near causal variants and thus do not have substantial effects. A recent approach to remedy this is to use genome-wide association study (GWAS) findings and increase the weights of GWAS-top-SNPs in genomic predictions. Here, we employ a genome-wide approach to integrate GWAS results into genomic prediction, called GWABLUP.

RESULTS

GWABLUP consists of the following steps: (1) performing a GWAS in the training data which results in likelihood ratios; (2) smoothing the likelihood ratios over the SNPs; (3) combining the smoothed likelihood ratio with the prior probability of SNPs having non-zero effects, which yields the posterior probability of the SNPs; (4) calculating a weighted genomic relationship matrix using the posterior probabilities as weights; and (5) performing genomic prediction using the weighted genomic relationship matrix. Using high-density genotypes and milk, fat, protein and somatic cell count phenotypes on dairy cows, GWABLUP was compared to GBLUP, GBLUP (topSNPs) with extra weights for GWAS top-SNPs, and BayesGC, i.e. a Bayesian variable selection model. The GWAS resulted in six, five, four, and three genome-wide significant peaks for milk, fat and protein yield and somatic cell count, respectively. GWABLUP genomic predictions were 10, 6, 7 and 1% more reliable than those of GBLUP for milk, fat and protein yield and somatic cell count, respectively. It was also more reliable than GBLUP (topSNPs) for all four traits, and more reliable than BayesGC for three of the traits. Although GWABLUP showed a tendency towards inflation bias for three of the traits, this was not statistically significant. In a multitrait analysis, GWABLUP yielded the highest accuracy for two of the traits. However, for SCC, which was relatively unrelated to the yield traits, including yield trait GWAS-results reduced the reliability compared to a single trait analysis.

CONCLUSIONS

GWABLUP uses GWAS results to differentially weigh all the SNPs in a weighted GBLUP genomic prediction analysis. GWABLUP yielded up to 10% and 13% more reliable genomic predictions than GBLUP for single and multitrait analyses, respectively. Extension of GWABLUP to single-step analyses is straightforward.

Genetic parameters of colostrum and calf serum antibodies in Swedish dairy cattle

Background

A sufficient IgG content in the colostrum is essential for the newborn calf, as it provides passive immunity which substantially affects the probability of survival during rearing. Failure of passive transfer (FPT) occurs when a calf does not absorb enough antibodies from the colostrum and is defined by an IgG concentration in calf serum lower than 10 g/L. Apart from delayed access to colostrum, FPT can be due to a low production of IgG in the mother or poor IgG absorption by the calf. The aim of this study was to estimate the genetic background of antibody levels and indicator traits for antibodies in the colostrum and calf serum, and their correlation with milk production.

Results

Colostrum data were available for 1340 dairy cows with at least one calving and calf serum data were available for 886 calves from these cows. Indicator traits for antibody concentrations were estimated using refractometry (a digital Brix refractometer for colostrum and an optical refractometer for serum), and enzyme-linked immunosorbent assays (ELISA) were used to determine the levels of total IgG and natural antibodies (NAb) of various antibody isotypes in the colostrum and calf serum. Colostrum traits had heritabilities ranging from 0.16 to 0.31 with repeatabilities ranging from 0.21 to 0.55. Brix percentages had positive genetic correlations with all colostrum antibody traits including total IgG (0.68). Calf serum antibody concentrations had heritabilities ranging from 0.25 to 0.59, with a significant maternal effect accounting for 17 to 27% of the variance. When later in life calves produced their first lactation, the lactation average somatic cell score was found to be negatively correlated with NAb levels in calf serum.

Conclusions

Our results suggest that antibody levels in the colostrum and calf serum can be increased by means of selection.

Selection for environmental variance of litter size in rabbits involves genes in pathways controlling animal resilience

Background

Environmental variance (V_E) is partially under genetic control, which means that the V_E of individuals that share the same environment can differ because they have different genotypes. Previously, a divergent selection experiment for V_E of litter size (LS) during 13 generations in rabbit yielded a successful response and revealed differences in resilience between the divergent lines. The aim of the current study was to identify signatures of selection in these divergent lines to better understand the molecular mechanisms and pathways that control V_E of LS and animal resilience. Three methods (F_ST, ROH and varLD) were used to identify signatures of selection in a set of 473 genotypes from these rabbit lines (377) and a base population (96). A whole-genome sequencing (WGS) analysis was performed on 54 animals to detect genes with functional mutations.

Results

By combining signatures of selection and WGS data, we detected 373 genes with functional mutations in their transcription units, among which 111 had functions related to the immune system, stress response, reproduction and embryo development, and/or carbohydrate and lipid metabolism. The genes TTC23L, FBXL20, GHDC, ENSOCUG00000031631, SLC18A1, CD300LG, MC2R, and ENSOCUG00000006264 were particularly relevant, since each one carried a functional mutation that was fixed in one of the rabbit lines and absent in the other line. In the 3ʹUTR region of the MC2R and ENSOCUG00000006264 genes, we detected a novel insertion/deletion (INDEL) variant.

Conclusions

Our findings provide further evidence in favour of V_E as a measure of animal resilience. Signatures of selection were identified for V_E of LS in genes that have a functional mutation in their transcription units and are mostly implicated in the immune response and stress response pathways. However, the real implications of these genes for V_E and animal resilience will need to be assessed through functional analyses.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00653-y.

Improvement of Disease Resistance in Livestock: Application of Immunogenomics and CRISPR/Cas9 Technology

Disease occurrence adversely affects livestock production and animal welfare, and have an impact on both human health and public perception of food-animals production. Combined efforts from farmers, animal scientists, and veterinarians have been continuing to explore the effective disease control approaches for the production of safe animal-originated food. Implementing the immunogenomics, along with genome editing technology, has been considering as the key approach for safe food-animal production through the improvement of the host genetic resistance. Next-generation sequencing, as a cutting-edge technique, enables the production of high throughput transcriptomic and genomic profiles resulted from host-pathogen interactions. Immunogenomics combine the transcriptomic and genomic data that links to host resistance to disease, and predict the potential candidate genes and their genomic locations. Genome editing, which involves insertion, deletion, or modification of one or more genes in the DNA sequence, is advancing rapidly and may be poised to become a commercial reality faster than it has thought. The clustered regulatory interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) [CRISPR/Cas9] system has recently emerged as a powerful tool for genome editing in agricultural food production including livestock disease management. CRISPR/Cas9 mediated insertion of NRAMP1 gene for producing tuberculosis resistant cattle, and deletion of CD163 gene for producing porcine reproductive and respiratory syndrome (PRRS) resistant pigs are two groundbreaking applications of genome editing in livestock. In this review, we have highlighted the technological advances of livestock immunogenomics and the principles and scopes of application of CRISPR/Cas9-mediated targeted genome editing in animal breeding for disease resistance.

Genome-Wide Identification of Discriminative Genetic Variations in Beef and Dairy Cattle via an Information-Theoretic Approach

Analyzing the associations between genotypic changes and phenotypic traits on a genome-wide scale can contribute to understanding the functional roles of distinct genetic variations during breed development. We performed a whole-genome analysis of Angus and Jersey cattle breeds using conditional mutual information, which is an information-theoretic method estimating the conditional independency among multiple factor variables. The proposed conditional mutual information-based approach allows breed-discriminative genetic variations to be explicitly identified from tens of millions of SNP (single nucleotide polymorphism) positions on a genome-wide scale while minimizing the usage of prior knowledge. Using this data-driven approach, we identified biologically relevant functional genes, including breed-specific variants for cattle traits such as beef and dairy production. The identified lipid-related genes were shown to be significantly associated with lipid and triglyceride metabolism, fat cell differentiation, and muscle development. In addition, we confirmed that milk-related genes are involved in mammary gland development, lactation, and mastitis-associated processes. Our results provide the distinct properties of Angus and Jersey cattle at a genome-wide level. Moreover, this study offers important insights into discovering unrevealed genetic variants for breed-specific traits and the identification of genetic signatures of diverse cattle breeds with respect to target breed-specific properties.

Uncovering Sub-Structure and Genomic Profiles in Across-Countries Subpopulations of Angus Cattle

Highlighting genomic profiles for geographically distinct subpopulations of the same breed may provide insights into adaptation mechanisms to different environments, reveal genomic regions divergently selected, and offer initial guidance to joint genomic analysis. Here, we characterized similarities and differences between the genomic patterns of Angus subpopulations, born and raised in Canada (N = 382) and Brazil (N = 566). Furthermore, we systematically scanned for selection signatures based on the detection of autozygosity islands common between the two subpopulations, and signals of divergent selection, via FST and varLD tests. The principal component analysis revealed a sub-structure with a close connection between the two subpopulations. The averages of genomic relationships, inbreeding coefficients, and linkage disequilibrium at varying genomic distances were rather similar across them, suggesting non-accentuated differences in overall genomic diversity. Autozygosity islands revealed selection signatures common to both subpopulations at chromosomes 13 (63.77-65.25 Mb) and 14 (22.81-23.57 Mb), which are notably known regions affecting growth traits. Nevertheless, further autozygosity islands along with FST and varLD tests unravel particular sites with accentuated population subdivision at BTAs 7 and 18 overlapping with known QTL and candidate genes of reproductive performance, thermoregulation, and resistance to infectious diseases. Our findings indicate overall genomic similarity between Angus subpopulations, with noticeable signals of divergent selection in genomic regions associated with the adaptation in different environments.

Identification of functional mutations associated with environmental variance of litter size in rabbits

Background

Environmental variance (V_E) is partly under genetic control and has recently been proposed as a measure of resilience. Unravelling the genetic background of the V_E of complex traits could help to improve resilience of livestock and stabilize their production across farming systems. The objective of this study was to identify genes and functional mutations associated with variation in V_E of litter size (LS) in rabbits. To achieve this, we combined the results of a genome-wide association study (GWAS) and a whole-genome sequencing (WGS) analysis using data from two divergently selected rabbit lines for high and low V_E of LS. These lines differ in terms of biomarkers of immune response and mortality. Moreover, rabbits with a lower V_E of LS were found to be more resilient to infections than animals with a higher V_E of LS.

Results

By using two GWAS approaches (single-marker regression and Bayesian multiple-marker regression), we identified four genomic regions associated with V_E of LS, on chromosomes 3, 7, 10, and 14. We detected 38 genes in the associated genomic regions and, using WGS, we identified 129 variants in the splicing, UTR, and coding (missense and frameshift effects) regions of 16 of these 38 genes. These genes were related to the immune system, the development of sensory structures, and stress responses. All of these variants (except one) segregated in one of the rabbit lines and were absent (n = 91) or fixed in the other one (n = 37). The fixed variants were in the HDAC9, ITGB8, MIS18A, ENSOCUG00000021276 and URB1 genes. We also identified a 1-bp deletion in the 3′UTR region of the HUNK gene that was fixed in the low V_E line and absent in the high V_E line.

Conclusions

This is the first study that combines GWAS and WGS analyses to study the genetic basis of V_E. The new candidate genes and functional mutations identified in this study suggest that the V_E of LS is under the control of functions related to the immune system, stress response, and the nervous system. These findings could also explain differences in resilience between rabbits with homogeneous and heterogeneous V_E of litter size.

Three Novel Players: PTK2B, SYK, and TNFRSF21 Were Identified to Be Involved in the Regulation of Bovine Mastitis Susceptibility via GWAS and Post-transcriptional Analysis

Bovine mastitis is a common inflammatory disease caused by multiple factors in early lactation or dry period. Genome wide association studies (GWAS) can provide a convenient and effective strategy for understanding the biological basis of mastitis and better prevention. 2b-RADseq is a high-throughput sequencing technique that offers a powerful method for genome-wide genetic marker development and genotyping. In this study, single nucleotide polymorphisms (SNPs) of the immune-regulated gene correlative with mastitis were screened and identified by two stage association analysis via GWAS-2b-RADseq in Chinese Holstein cows. We have screened 10,058 high quality SNPs from 7,957,920 tags and calculated their allele frequencies. Twenty-seven significant SNPs were co-labeled in two GWAS analysis models [Bayesian (P < 0.001) and Logistic regression (P < 0.01)], and only three SNPs (rs75762330, C > T, PIC = 0.2999; rs88640083, A > G, PIC = 0.1676; rs20438858, G > A, PIC = 0.3366) were annotated to immune-regulated genes (PTK2B, SYK, and TNFRSF21). Identified three SNPs are located in non-coding regions with low or moderate genetic polymorphisms. However, independent sample population validation (Case-control study) data showed that three important SNPs (rs75762330, P < 0.025, OR > 1; rs88640083, P < 0.005, OR > 1; rs20438858, P < 0.001, OR < 1) were significantly associated with clinical mastitis trait. Importantly, PTK2B and SYK expression was down-regulated in both peripheral blood leukocytes (PBLs) of clinical mastitis cows and in vitro LPS (E. coli)-stimulated bovine mammary epithelial cells, while TNFRSF21 was up-regulated. Under the same conditions, expression of Toll-like receptor 4 (TLR4), AKT1, and pro-inflammatory factors (IL-1β and IL-8) were also up-regulated. Interestingly, network analysis indicated that PTK2B and SYK are co-expressed in innate immune signaling pathway of Chinese Holstein. Taken together, these results provided strong evidence for the study of SNPs in bovine mastitis, and revealed the role of SYK, PTK2B, and TNFRSF21 in bovine mastitis susceptibility/tolerance.

Identification of QTLs for low somatic cell count in Murrah buffaloes

Mastitis, the most frequent and costly disease in buffalo, is the major cause of morbidity. The somatic cell count, an indirect indicator of susceptibility/resistance to mastitis, is a low heritable trait and thus a perfect candidate for marker assisted selection. Half sib families (12) were created and the somatic cell count was recorded at 3 stages of lactation during the first lactation of the 2,422 daughters belonging to 12 sires. Partial genome scan was carried out using interval mapping with different algorithms. The QTLs obtained for each half sib family were further subjected to meta analysis to identify chromosomal regions associated with somatic cell count on 8 chromosomes of buffalo. Four metaQTL regions were identified on chromosomes BBU1q, BBU8, and BBU10; 3 metaQTL regions on BBU2q, BBU9 and BBU15; 2 metaQTL regions on BBU6 and 1 on BBU7 of buffalo. Comparative genomics was used for finding out genes underlying the metaQTL regions; 1,065 genes were underlying the metaQTL regions in buffaloes assuming buffalo–cattle–human synteny. Genes (78) mapped to immune response. These genes are supposedly important candidate genes for further analysis. Gene ontology and network analysis was carried out on these genes. The genes identified belonged to immune response and defense mechanism. The QTL markers identified in the present analysis can be used in the breeding programs of buffalo to select the bulls, which are less susceptible to mastitis.

Milk somatic cells, factors influencing their release, future prospects, and practical utility in dairy animals: An overview

Milk somatic cells (SCs) are a mixture of milk-producing cells and immune cells. These cells are secreted in milk during the normal course of milking and are used as an index for estimating mammary health and milk quality of dairy animals worldwide. Milk SC is influenced by cow productivity, health, parity, lactation stage, and breed of an animal. Any change in environmental conditions, poor management practices, and also stressful conditions significantly increases the amount of SC coming in milk. Better hygiene and proper nutrition help in reducing milk SC. Milk with low SC means better milk products with a longer shelf life. The present review describes the role of SCs (both secretory and immune) in milk, their role in maintaining the integrity of the mammary gland, and factors affecting their release in milk. This information may help to reduce milk somatic cell counts (SCCs) and to establish differential SCC standards.

Genetic parameters for semen quality and quantity traits in five pig lines

We aimed to estimate genetic parameters for semen quality and quantity traits as well as for within-boar variation of these traits to evaluate their inclusion in breeding goals. Genetic parameters were estimated within line using a multiple-trait (4 × 4) repeatability animal model fitted for 5 pig lines, considering 4 semen traits: sperm motility (MOT), sperm progressive motility (PROMOT), log-transformed number of sperm cells per ejaculate (lnN), and total morphological abnormalities (ABN). The within-boar variation of these traits was analyzed based on a multiple-trait (2 × 2) approach for SD and average (AVG) and a single-trait analysis for CV. The average heritabilities across the 5 lines estimated by multiple-trait analysis were 0.18 ± 0.07 (MOT), 0.22 ± 0.08 (PROMOT), 0.16 ± 0.04 (lnN), and 0.20 ± 0.04 (ABN). The average genetic correlations were favorable between MOT and PROMOT (0.86 ± 0.10), between MOT and ABN (-0.66 ± 0.25), and between PROMOT and ABN (-0.65 ± 0.25). As determined by within-boar variation analysis, AVG exhibited the greatest heritabilities followed by SD and CV, respectively, for the traits MOT and ABN. For PROMOT, average SD heritability was lower than CV heritability, whereas for lnN, they were the same. The average genetic correlations between AVG and SD were favorable for MOT (-0.60 ± 0.13), PROMOT (-0.79 ± 0.14), and ABN (0.78 ± 0.17). The moderate heritabilities indicate the possibility of effective selection of boars based on semen traits. Average and SD are proposed as appropriate traits for selection regarding uniformity.

Validating genome-wide associated signals for clinical mastitis in German Holstein cattle

A validation study for six genomic regions previously identified by a genome-wide association study for somatic cell score was conducted with data of clinical mastitis in German Holstein cattle. Out of 10 tested SNPs, five on chromosomes 6, 13 and 19 were significantly associated with clinical mastitis (P < 0.05). Three SNPs on chromosomes 6 and 19 had the same direction of effect as those previously reported in the initial genome-wide association study for somatic cell score. The other two SNPs on chromosome 13 had opposite effects. As well as validating associations within known QTL from previous studies, e.g. chromosomes 6 and 19, novel loci on chromosome 13 were confirmed. Promising candidate genes are, for example: deoxycytidine kinase, immunoglobulin J chain, vitamin D binding protein, forkhead box K2, sodium/hydrogen exchanger 8 and cytoplasmic nuclear factor of activated T-cells 2. Our confirmation study provides additional evidence for the functional role of the linked genomic regions to immune response. This information can be used as a basis for further functional studies for those potential genes.

The Use of "Omics" in Lactation Research in Dairy Cows

“Omics” is the application of genomics, transcriptomics, proteomics, and metabolomics in biological research. Over the years, tremendous amounts of biological information has been gathered regarding the changes in gene, mRNA and protein expressions as well as metabolites in different physiological conditions and regulations, which has greatly advanced our understanding of the regulation of many physiological and pathophysiological processes. The aim of this review is to comprehensively describe the advances in our knowledge regarding lactation mainly in dairy cows that were obtained from the “omics” studies. The “omics” technologies have continuously been preferred as the technical tools in lactation research aiming to develop new nutritional, genetic, and management strategies to improve milk production and milk quality in dairy cows.

Genome-wide association study in Chinese Holstein cows reveal two candidate genes for somatic cell score as an indicator for mastitis susceptibility

Backgrounds

Bovine mastitis is a typical inflammatory disease causing seriously economic loss. Genome-wide association study (GWAS) can be a powerful method to promote marker assistant selection of this kind of complex disease. The present study aimed to analyze and identify single nucleotide polymorphisms (SNPs) and candidate genes that associated with mastitis susceptibility traits in Chinese Holstein.

Results

Forty eight SNPs were identified significantly associated with mastitis resistance traits in Chinese Holstein cows, which are mainly located on the BTA 14. A total of 41 significant SNPs were linked to 31 annotated bovine genes. Gene Ontology and pathway enrichment revealed 5 genes involved in 32 pathways, in which, TRAPPC9 and ARHGAP39 genes participate cell differentiation and developmental pathway together. The six common genome-wide significant SNPs are found located within TRAPPC9 and flanking ARHGAP39 genes.

Conclusions

Our data identified the six SNPs significantly associated with SCS EBVs, which suggest that their linked two genes (TRAPPC9 and ARHGAP39) are novel candidate genes of mastitis susceptibility in Holsteins.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0263-3) contains supplementary material, which is available to authorized users.

Genotype by environment interactions on culling rates and 305-day milk yield of Holstein cows in 3 US regions

The objective of this study was to investigate genotype by environment interactions for culling rates and milk production in large and small dairy herds in 3 US regions, using genotypes, pedigree, and phenotypes. Single nucleotide polymorphism (SNP) marker variances were also estimated in these different environments. Culling rates including cow mortality were based on 6 Dairy Herd Improvement termination codes reported by dairy producers. Separate data sets for culling rates and 305-d milk yield were created for large and small dairy herds in the US regions of the Southeast (SE), Southwest (SW), and Northeast (NE) for the first 3 lactation cows that calved between 1999 and 2008. Genomic information from 42,503 SNP markers on 34,506 bulls was included in the analysis to predict genomic estimated breeding value (GEBV) of culling rates and 305-d milk yield with a single-step genomic BLUP using a bivariate threshold-linear model. Cow replacement rates in large SE and NE herds were higher. Heritability estimates of culling rates ranged from 0.03 to 0.11, but the differences were small between large and small herds and among the 3 US regions. Genetic correlations between culling rates and 305-d milk yield were medium to high for cows sold for poor production and reproduction problems. Correlations of GEBV for culling rates among the 3 US regions ranged from 0.34 to 0.92 and were lower between the SW and the other regions, especially in small herds. Correlations of GEBV between large and small herds ranged from 0.44 to 0.90 and were lower in the SW. These results indicate genotype by environment interactions of cow culling rate between the US regions and between large and small herds. Correlations of top 30 SNP marker effects for culling rates between 2 US regions ranged from 0.64 to 0.98 and were higher than those of more SNP marker effects except for a culling reason "sold for dairy purpose." Those correlations between large and small herds ranged from 0.67 to 0.98. High correlations of top SNP marker effects on culling reasons between the US regions and between large and small herds suggest that major markers can be useful for selection in different environments. The SNP variance shown in a marker gene segment on chromosome 14 was strongly associated with milk production in large and small herds in the NE but not in the SE and SW. Marker genes on chromosome 14 also showed a strong association with cow culling rates due to poor production and mortality in large herds in the NE.

Bovine mastitis: frontiers in immunogenetics

Mastitis is one of the most prevalent and costly diseases in the dairy industry with losses attributable to reduced milk production, discarded milk, early culling, veterinary services, and labor costs. Typically, mastitis is an inflammation of the mammary gland most often, but not limited to, bacterial infection, and is characterized by the movement of leukocytes and serum proteins from the blood to the site of infection. It contributes to compromised milk quality and the potential spread of antimicrobial resistance if antibiotic treatment is not astutely applied. Despite the implementation of management practises and genetic selection approaches, bovine mastitis control continues to be inadequate. However, some novel genetic strategies have recently been demonstrated to reduce mastitis incidence by taking advantage of a cow's natural ability to make appropriate immune responses against invading pathogens. Specifically, dairy cattle with enhanced and balanced immune responses have a lower occurrence of disease, including mastitis, and they can be identified and selected for using the high immune response (HIR) technology. Enhanced immune responsiveness is also associated with improved response to vaccination, increased milk, and colostrum quality. Since immunity is an important fitness trait, beneficial associations with longevity and reproduction are also often noted. This review highlights the genetic regulation of the bovine immune system and its vital contributions to disease resistance. Genetic selection approaches currently used in the dairy industry to reduce the incidence of disease are reviewed, including the HIR technology, genomics to improve disease resistance or immune response, as well as the Immunity(+)™ sire line. Improving the overall immune responsiveness of cattle is expected to provide superior disease resistance, increasing animal welfare and food quality while maintaining favorable production levels to feed a growing population.

A genome-wide association study reveals dominance effects on number of teats in pigs

Dominance has been suggested as one of the genetic mechanisms explaining heterosis. However, using traditional quantitative genetic methods it is difficult to obtain accurate estimates of dominance effects. With the availability of dense SNP (Single Nucleotide Polymorphism) panels, we now have new opportunities for the detection and use of dominance at individual loci. Thus, the aim of this study was to detect additive and dominance effects on number of teats (NT), specifically to investigate the importance of dominance in a Landrace-based population of pigs. In total, 1,550 animals, genotyped for 32,911 SNPs, were used in single SNP analysis. SNPs with a significant genetic effect were tested for their mode of gene action being additive, dominant or a combination. In total, 21 SNPs were associated with NT, located in three regions with additive (SSC6, 7 and 12) and one region with dominant effects (SSC4). Estimates of additive effects ranged from 0.24 to 0.29 teats. The dominance effect of the QTL located on SSC4 was negative (−0.26 teats). The additive variance of the four QTLs together explained 7.37% of the total phenotypic variance. The dominance variance of the four QTLs together explained 1.82% of the total phenotypic variance, which corresponds to one-fourth of the variance explained by additive effects. The results suggest that dominance effects play a relevant role in the genetic architecture of NT. The QTL region on SSC7 contains the most promising candidate gene: VRTN. This gene has been suggested to be related to the number of vertebrae, a trait correlated with NT.

Single nucleotide polymorphism and haplotype effects associated with somatic cell score in German Holstein cattle

Background

To better understand the genetic determination of udder health, we performed a genome-wide association study (GWAS) on a population of 2354 German Holstein bulls for which daughter yield deviations (DYD) for somatic cell score (SCS) were available. For this study, we used genetic information of 44 576 informative single nucleotide polymorphisms (SNPs) and 11 725 inferred haplotype blocks.

Results

When accounting for the sub-structure of the analyzed population, 16 SNPs and 10 haplotypes in six genomic regions were significant at the Bonferroni threshold of P ≤ 1.14 × 10^-6. The size of the identified regions ranged from 0.05 to 5.62 Mb. Genomic regions on chromosomes 5, 6, 18 and 19 coincided with known QTL affecting SCS, while additional genomic regions were found on chromosomes 13 and X. Of particular interest is the region on chromosome 6 between 85 and 88 Mb, where QTL for mastitis traits and significant SNPs for SCS in different Holstein populations coincide with our results. In all identified regions, except for the region on chromosome X, significant SNPs were present in significant haplotypes. The minor alleles of identified SNPs on chromosomes 18 and 19, and the major alleles of SNPs on chromosomes 6 and X were favorable for a lower SCS. Differences in somatic cell count (SCC) between alternative SNP alleles reached 14 000 cells/mL.

Conclusions

The results support the polygenic nature of the genetic determination of SCS, confirm the importance of previously reported QTL, and provide evidence for the segregation of additional QTL for SCS in Holstein cattle. The small size of the regions identified here will facilitate the search for causal genetic variations that affect gene functions.

Unraveling the genetic architecture of environmental variance of somatic cell score using high-density single nucleotide polymorphism and cow data from experimental farms

In recent years, it has been shown that not only is the phenotype under genetic control, but also the environmental variance. Very little, however, is known about the genetic architecture of environmental variance. The main objective of this study was to unravel the genetic architecture of the mean and environmental variance of somatic cell score (SCS) by identifying genome-wide associations for mean and environmental variance of SCS in dairy cows and by quantifying the accuracy of genome-wide breeding values. Somatic cell score was used because previous research has shown that the environmental variance of SCS is partly under genetic control and reduction of the variance of SCS by selection is desirable. In this study, we used 37,590 single nucleotide polymorphism (SNP) genotypes and 46,353 test-day records of 1,642 cows at experimental research farms in 4 countries in Europe. We used a genomic relationship matrix in a double hierarchical generalized linear model to estimate genome-wide breeding values and genetic parameters. The estimated mean and environmental variance per cow was used in a Bayesian multi-locus model to identify SNP associated with either the mean or the environmental variance of SCS. Based on the obtained accuracy of genome-wide breeding values, 985 and 541 independent chromosome segments affecting the mean and environmental variance of SCS, respectively, were identified. Using a genomic relationship matrix increased the accuracy of breeding values relative to using a pedigree relationship matrix. In total, 43 SNP were significantly associated with either the mean (22) or the environmental variance of SCS (21). The SNP with the highest Bayes factor was on chromosome 9 (Hapmap31053-BTA-111664) explaining approximately 3% of the genetic variance of the environmental variance of SCS. Other significant SNP explained less than 1% of the genetic variance. It can be concluded that fewer genomic regions affect the environmental variance of SCS than the mean of SCS, but genes with large effects seem to be absent for both traits.