Characterization of a QTL region affecting clinical mastitis and protein yield on BTA6

A genomic assessment of the correlation between milk production traits and claw and udder health traits in Holstein dairy cattle

Claw diseases and mastitis represent the most important disease traits in dairy cattle with increasing incidences and a frequently mentioned connection to milk yield. Yet, many studies aimed to detect the genetic background of both trait complexes via fine-mapping of quantitative trait loci. However, little is known about genomic regions that simultaneously affect milk production and disease traits. For this purpose, several tools to detect local genetic correlations have been developed. In this study, we attempted a detailed analysis of milk production and disease traits as well as their interrelationship using a sample of 34,497 50K genotyped German Holstein cows with milk production and claw and udder disease traits records. We performed a pedigree-based quantitative genetic analysis to estimate heritabilities and genetic correlations. Additionally, we generated GWAS summary statistics, paying special attention to genomic inflation, and used these data to identify shared genomic regions, which affect various trait combinations. The heritability on the liability scale of the disease traits was low, between 0.02 for laminitis and 0.19 for interdigital hyperplasia. The heritabilities for milk production traits were higher (between 0.27 for milk energy yield and 0.48 for fat-protein ratio). Global genetic correlations indicate the shared genetic effect between milk production and disease traits on a whole genome level. Most of these estimates were not significantly different from zero, only mastitis showed a positive one to milk (0.18) and milk energy yield (0.13), as well as a negative one to fat-protein ratio (-0.07). The genomic analysis revealed significant SNPs for milk production traits that were enriched on Bos taurus autosome 5, 6, and 14. For digital dermatitis, we found significant hits, predominantly on Bos taurus autosome 5, 10, 22, and 23, whereas we did not find significantly trait-associated SNPs for the other disease traits. Our results confirm the known genetic background of disease and milk production traits. We further detected 13 regions that harbor strong concordant effects on a trait combination of milk production and disease traits. This detailed investigation of genetic correlations reveals additional knowledge about the localization of regions with shared genetic effects on these trait complexes, which in turn enables a better understanding of the underlying biological pathways and putatively the utilization for a more precise design of breeding schemes.

Distinguishing pleiotropy from linked QTL between milk production traits and mastitis resistance in Nordic Holstein cattle

BACKGROUND

Production and health traits are central in cattle breeding. Advances in next-generation sequencing technologies and genotype imputation have increased the resolution of gene mapping based on genome-wide association studies (GWAS). Thus, numerous candidate genes that affect milk yield, milk composition, and mastitis resistance in dairy cattle are reported in the literature. Effect-bearing variants often affect multiple traits. Because the detection of overlapping quantitative trait loci (QTL) regions from single-trait GWAS is too inaccurate and subjective, multi-trait analysis is a better approach to detect pleiotropic effects of variants in candidate genes. However, large sample sizes are required to achieve sufficient power. Multi-trait meta-analysis is one approach to deal with this problem. Thus, we performed two multi-trait meta-analyses, one for three milk production traits (milk yield, protein yield and fat yield), and one for milk yield and mastitis resistance.

RESULTS

For highly correlated traits, the power to detect pleiotropy was increased by multi-trait meta-analysis compared with the subjective assessment of overlapping of single-trait QTL confidence intervals. Pleiotropic effects of lead single nucleotide polymorphisms (SNPs) that were detected from the multi-trait meta-analysis were confirmed by bivariate association analysis. The previously reported pleiotropic effects of variants within the DGAT1 and MGST1 genes on three milk production traits, and pleiotropic effects of variants in GHR on milk yield and fat yield were confirmed. Furthermore, our results suggested that variants in KCTD16, KCNK18 and ENSBTAG00000023629 had pleiotropic effects on milk production traits. For milk yield and mastitis resistance, we identified possible pleiotropic effects of variants in two genes, GC and DGAT1.

CONCLUSIONS

Multi-trait meta-analysis improves our ability to detect pleiotropic interactions between milk production traits and identifies variants with pleiotropic effects on milk production traits and mastitis resistance. In particular, this should contribute to better understand the biological mechanisms that underlie the unfavorable genetic correlation between milk yield and mastitis.

Dissecting closely linked association signals in combination with the mammalian phenotype database can identify candidate genes in dairy cattle

BACKGROUND

Genome-wide association studies (GWAS) have been successfully implemented in cattle research and breeding. However, moving from the associations to identify the causal variants and reveal underlying mechanisms have proven complicated. In dairy cattle populations, we face a challenge due to long-range linkage disequilibrium (LD) arising from close familial relationships in the studied individuals. Long range LD makes it difficult to distinguish if one or multiple quantitative trait loci (QTL) are segregating in a genomic region showing association with a phenotype. We had two objectives in this study: 1) to distinguish between multiple QTL segregating in a genomic region, and 2) use of external information to prioritize candidate genes for a QTL along with the candidate variants.

RESULTS

We observed fixing the lead SNP as a covariate can help to distinguish additional close association signal(s). Thereafter, using the mammalian phenotype database, we successfully found candidate genes, in concordance with previous studies, demonstrating the power of this strategy. Secondly, we used variant annotation information to search for causative variants in our candidate genes. The variant information successfully identified known causal mutations and showed the potential to pinpoint the causative mutation(s) which are located in coding regions.

CONCLUSIONS

Our approach can distinguish multiple QTL segregating on the same chromosome in a single analysis without manual input. Moreover, utilizing information from the mammalian phenotype database and variant effect predictor as post-GWAS analysis could benefit in candidate genes and causative mutations finding in cattle. Our study not only identified additional candidate genes for milk traits, but also can serve as a routine method for GWAS in dairy cattle.

Dissecting closely linked association signals in combination with the mammalian phenotype database can identify candidate genes in dairy cattle

Background

Genome-wide association studies (GWAS) have been successfully implemented in cattle research and breeding. However, moving from the associations to identifying the causal variants and revealing underlying mechanisms have proven complicated. In dairy cattle populations, we face a challenge due to long-range linkage disequilibrium (LD) arising from close familial relationships in the studied individuals. Long range LD makes it difficult to distinguish if one or multiple quantitative trait loci (QTL) are segregating in a genomic region showing association with a phenotype. We had two objectives in this study: 1) to distinguish between multiple QTL segregating in a genomic region, and 2) use of external information to prioritize candidate genes for a QTL along with the candidate variant.

Results

We observed fixing the lead SNP as a covariate can help to distinguish additional close association signal(s). Thereafter, using the mammalian phenotype database, we successfully found candidate genes, in concordance with previous studies, demonstrating the power of this strategy. Secondly, we used variant annotation information to search for causative variants in our candidate genes. The variant information successfully identified known causal mutations and showed the potential to pinpoint the causative mutation(s) which are located in coding regions.

Conclusions

Our approach can distinguish multiple QTL segregating on the same chromosome in a single analysis without manual input. Moreover, utilizing information from the mammalian phenotype database and variant effect predictor as post-GWAS analysis could benefit in candidate genes and causative mutations finding in cattle. Our study not only identified additional candidate genes for milk traits, but also can serve as a routine method for GWAS in dairy cattle.

Electronic supplementary material

The online version of this article (10.1186/s12863-018-0620-0) contains supplementary material, which is available to authorized users.

Genome-Wide Association Study for Susceptibility to and Recoverability From Mastitis in Danish Holstein Cows

Because mastitis is very frequent and unavoidable, adding recovery information into the analysis for genetic evaluation of mastitis is of great interest from economical and animal welfare point of view. Here we have performed genome-wide association studies (GWAS) to identify associated single nucleotide polymorphisms (SNPs) and investigate the genetic background not only for susceptibility to – but also for recoverability from mastitis. Somatic cell count records from 993 Danish Holstein cows genotyped for a total of 39378 autosomal SNP markers were used for the association analysis. Single SNP regression analysis was performed using the statistical software package DMU. Substitution effect of each SNP was tested with a t-test and a genome-wide significance level of P-value < 10^-4 was used to declare significant SNP-trait association. A number of significant SNP variants were identified for both traits. Many of the SNP variants associated either with susceptibility to – or recoverability from mastitis were located in or very near to genes that have been reported for their role in the immune system. Genes involved in lymphocyte developments (e.g., MAST3 and STAB2) and genes involved in macrophage recruitment and regulation of inflammations (PDGFD and PTX3) were suggested as possible causal genes for susceptibility to – and recoverability from mastitis, respectively. However, this is the first GWAS study for recoverability from mastitis and our results need to be validated. The findings in the current study are, therefore, a starting point for further investigations in identifying causal genetic variants or chromosomal regions for both susceptibility to – and recoverability from mastitis.

Population structure and genomic inbreeding in nine Swiss dairy cattle populations

BACKGROUND

Domestication, breed formation and intensive selection have resulted in divergent cattle breeds that likely exhibit their own genomic signatures. In this study, we used genotypes from 27,612 autosomal single nucleotide polymorphisms to characterize population structure based on 9214 sires representing nine Swiss dairy cattle populations: Brown Swiss (BS), Braunvieh (BV), Original Braunvieh (OB), Holstein (HO), Red Holstein (RH), Swiss Fleckvieh (SF), Simmental (SI), Eringer (ER) and Evolèner (EV). Genomic inbreeding (F ROH) and signatures of selection were determined by calculating runs of homozygosity (ROH). The results build the basis for a better understanding of the genetic development of Swiss dairy cattle populations and highlight differences between the original populations (i.e. OB, SI, ER and EV) and those that have become more popular in Switzerland as currently reflected by their larger populations (i.e. BS, BV, HO, RH and SF).

RESULTS

The levels of genetic diversity were highest and lowest in the SF and BS breeds, respectively. Based on F ST values, we conclude that, among all pairwise comparisons, BS and HO (0.156) differ more than the other pairs of populations. The original Swiss cattle populations OB, SI, ER, and EV are clearly genetically separated from the Swiss cattle populations that are now more common and represented by larger numbers of cows. Mean levels of F ROH ranged from 0.027 (ER) to 0.091 (BS). Three of the original Swiss cattle populations, ER (F ROH: 0.027), OB (F ROH: 0.029), and SI (F ROH: 0.039), showed low levels of genomic inbreeding, whereas it was much higher in EV (F ROH: 0.074). Private signatures of selection for the original Swiss cattle populations are reported for BTA4, 5, 11 and 26.

CONCLUSIONS

The low levels of genomic inbreeding observed in the original Swiss cattle populations ER, OB and SI compared to the other breeds are explained by a lesser use of artificial insemination and greater use of natural service. Natural service results in more sires having progeny at each generation and thus this breeding practice is likely the major reason for the remarkable levels of genetic diversity retained within these populations. The fact that the EV population is regionally restricted and its small census size of herd-book cows explain its high level of genomic inbreeding.

Fine mapping of a QTL on bovine chromosome 6 using imputed full sequence data suggests a key role for the group-specific component (GC) gene in clinical mastitis and milk production

BACKGROUND

Clinical mastitis is an inflammation of the mammary gland and causes significant costs to dairy production. It is unfavourably genetically correlated to milk production, and, thus, knowledge of the mechanisms that underlie these traits would be valuable to improve both of them simultaneously through breeding. A quantitative trait locus (QTL) that affects both clinical mastitis and milk production has recently been fine-mapped to around 89 Mb on bovine chromosome 6 (BTA6), but identification of the gene that underlies this QTL was not possible due to the strong linkage disequilibrium between single nucleotide polymorphisms (SNPs) within this region. Our aim was to identify the gene and, if possible, the causal polymorphism(s) responsible for this QTL through association analysis of high-density SNPs and imputed full sequence data in combination with analyses of transcript and protein levels of the identified candidate gene.

RESULTS

Associations between SNPs and the studied traits were strongest for SNPs that were located within and immediately upstream of the group-specific component (GC) gene. This gene encodes the vitamin D-binding protein (DBP) and has multiple roles in immune defense and milk production. A 12-kb duplication that was identified downstream of this gene covered its last exon and segregated with the QTL allele that is associated with increased mastitis susceptibility and milk production. However, analyses of GC mRNA levels on the available samples revealed no differences in expression between animals having or lacking this duplication. Moreover, we detected no differences in the concentrations of DBP and its ligand vitamin D between the animals with different GC genotypes that were available for this study.

CONCLUSIONS

Our results suggest GC as the gene that underlies the QTL for clinical mastitis and milk production. However, since only healthy animals were sampled for transcription and expression analyses, we could not draw any final conclusion on the absence of quantitative differences between animals with different genotypes. Future studies should investigate GC RNA expression and protein levels in cows with different genotypes during an infection.

An alternative experimental case-control design for genetic association studies on bovine mastitis

The possibility of using genetic control strategies to increase disease resistance to infectious diseases relies on the identification of markers to include in the breeding plans. Possible incomplete exposure of mastitis-free (control) animals, however, is a major issue to find relevant markers in genetic association studies for infectious diseases. Usually, designs based on elite dairy sires are used in association studies, but an epidemiological case-control strategy, based on cows repeatedly field-tested could be an alternative for disease traits. To test this hypothesis, genetic association results obtained in the present work from a cohort of Italian Holstein cows tested for mastitis over time were compared with those from a previous genome-wide scan on Italian Holstein sires genotyped with 50k single nucleotide polymorphisms for de-regressed estimated breeding values for somatic cell counts (SCCs) on Bos taurus autosome (BTA6) and BTA14. A total of 1121 cows were selected for the case-control approach (cases=550, controls=571), on a combination of herd level of SCC incidence and of within herd individual level of SCC. The association study was conducted on nine previously identified markers, six on BTA6 and four on BTA14, using the R statistical environment with the 'qtscore' function of the GenABEL package, on high/low adjusted linear score as a binomial trait. The results obtained in the cow cohort selected on epidemiological information were in agreement with those obtained from the previous sire genome-wide association study (GWAS). Six out of the nine markers showed significant association, four on BTA14 (rs109146371, rs109234250, rs109421300, rs109162116) and two on BTA6 (rs110527224 and rs42766480). Most importantly, using mastitis as a case study, the current work further validated the alternative use of historical field disease data in case-control designs for genetic analysis of infectious diseases in livestock.

Genome-wide association study using high-density single nucleotide polymorphism arrays and whole-genome sequences for clinical mastitis traits in dairy cattle

Mastitis is a mammary disease that frequently affects dairy cattle. Despite considerable research on the development of effective prevention and treatment strategies, mastitis continues to be a significant issue in bovine veterinary medicine. To identify major genes that affect mastitis in dairy cattle, 6 chromosomal regions on Bos taurus autosome (BTA) 6, 13, 16, 19, and 20 were selected from a genome scan for 9 mastitis phenotypes using imputed high-density single nucleotide polymorphism arrays. Association analyses using sequence-level variants for the 6 targeted regions were carried out to map causal variants using whole-genome sequence data from 3 breeds. The quantitative trait loci (QTL) discovery population comprised 4,992 progeny-tested Holstein bulls, and QTL were confirmed in 4,442 Nordic Red and 1,126 Jersey cattle. The targeted regions were imputed to the sequence level. The highest association signal for clinical mastitis was observed on BTA 6 at 88.97 Mb in Holstein cattle and was confirmed in Nordic Red cattle. The peak association region on BTA 6 contained 2 genes: vitamin D-binding protein precursor (GC) and neuropeptide FF receptor 2 (NPFFR2), which, based on known biological functions, are good candidates for affecting mastitis. However, strong linkage disequilibrium in this region prevented conclusive determination of the causal gene. A different QTL on BTA 6 located at 88.32 Mb in Holstein cattle affected mastitis. In addition, QTL on BTA 13 and 19 were confirmed to segregate in Nordic Red cattle and QTL on BTA 16 and 20 were confirmed in Jersey cattle. Although several candidate genes were identified in these targeted regions, it was not possible to identify a gene or polymorphism as the causal factor for any of these regions.

A genome-wide association study for somatic cell score using the Illumina high-density bovine beadchip identifies several novel QTL potentially related to mastitis susceptibility

Mastitis is an inflammation-driven disease of the bovine mammary gland that occurs in response to physical damage or infection and is one of the most costly production-related diseases in the dairy industry worldwide. We performed a genome-wide association study (GWAS) to identify genetic loci associated with somatic cell score (SCS), an indicator trait of mammary gland inflammation. A total of 702 Holstein-Friesian bulls were genotyped for 777,962 single nucleotide polymorphisms (SNPs) and associated with SCS phenotypes. The SCS phenotypes were expressed as daughter yield deviations (DYD) based on a large number of progeny performance records. A total of 138 SNPs on 15 different chromosomes reached genome-wide significance (corrected p-value ≤ 0.05) for association with SCS (after correction for multiple testing). We defined 28 distinct QTL regions and a number of candidate genes located in these QTL regions were identified. The most significant association (p-value = 1.70 × 10⁻⁷) was observed on chromosome 6. This QTL had no known genes annotated within it, however, the Ensembl Genome Browser predicted the presence of a small non-coding RNA (a Y RNA gene) in this genomic region. This Y RNA gene was 99% identical to human RNY4. Y RNAs are a rare type of non-coding RNA that were originally discovered due to their association with the autoimmune disease, systemic lupus erythematosus. Examining small-RNA sequencing (RNAseq) data being generated by us in multiple different mastitis-pathogen challenged cell-types has revealed that this Y RNA is expressed (but not differentially expressed) in these cells. Other QTL regions identified in this study also encoded strong candidate genes for mastitis susceptibility. A QTL region on chromosome 13, for example, was found to contain a cluster of β-defensin genes, a gene family with known roles in innate immunity. Due to the increased SNP density, this study also refined the boundaries for several known QTL for SCS and mastitis.

Gene polymorphisms: the keys for marker assisted selection and unraveling core regulatory pathways for mastitis resistance

One of the most frequent mammary diseases impacting lactating animals is mastitis, an inflammation of the mammary gland most commonly caused by bacterial infection. The severity of mastitis is greatly influenced by the invading organism and the subsequent immune response which must recognize the foreign organism, recruit immune cells, eliminate the invading pathogen, and resolve the inflammatory response. The speed, strength, and duration of this response and subsequent disease susceptibility are critically tied to the genetic background of an animal. However, the genetic contribution has been difficult to identify due to the complex interactions that must occur for effective disease resistance. Recent studies have utilized polymorphisms to better define the genes and chromosomal regions that contribute to mastitis resistance. This review will examine these studies with primary emphasis in bovine systems, as the most work regarding mastitis has been conducted in this species.

Molecular characterization of a long range haplotype affecting protein yield and mastitis susceptibility in Norwegian Red cattle

Background

Previous fine mapping studies in Norwegian Red cattle (NRC) in the region 86-90.4 Mb on Bos taurus chromosome 6 (BTA6) has revealed a quantitative trait locus (QTL) for protein yield (PY) around 88 Mb and a QTL for clinical mastitis (CM) around 90 Mb. The close proximity of these QTLs may partly explain the unfavorable genetic correlation between these two traits in NRC. A long range haplotype covering this region was introduced into the NRC population through the importation of a Holstein-Friesian bull (1606 Frasse) from Sweden in the 1970s. It has been suggested that this haplotype has a favorable effect on milk protein content but an unfavorable effect on mastitis susceptibility. Selective breeding for milk production traits is likely to have increased the frequency of this haplotype in the NRC population.

Results

Association mapping for PY and CM in NRC was performed using genotypes from 556 SNPs throughout the region 86-97 Mb on BTA6 and daughter-yield-deviations (DYDs) from 2601 bulls made available from the Norwegian dairy herd recording system. Highest test scores for PY were found for single-nucleotide polymorphisms (SNPs) within and surrounding the genes CSN2 and CSN1S2, coding for the β-casein and α_S2-casein proteins. High coverage re-sequencing by high throughput sequencing technology enabled molecular characterization of a long range haplotype from 1606 Frasse encompassing these two genes. Haplotype analysis of a large number of descendants from this bull indicated that the haplotype was not markedly disrupted by recombination in this region. The haplotype was associated with both increased milk protein content and increased susceptibility to mastitis, which might explain parts of the observed genetic correlation between PY and CM in NRC. Plausible causal polymorphisms affecting PY were detected in the promoter region and in the 5'-flanking UTR of CSN1S2. These polymorphisms could affect transcription or translation of CSN1S2 and thereby affect the amount of α_S2-casein in milk.

Highest test scores for CM were found in the region 89-91 Mb on BTA6, very close to a cluster of genes coding for CXC chemokines. Expression levels of some of these CXC chemokines have previously been shown to increase in bovine mammary gland cell lines after exposure to bacterial cell wall components.

Conclusion

Molecular characterization of the long range haplotype from the Holstein-Friesian bull 1606 Frasse, imported into NRC in the 1970s, revealed polymorphisms that could affect transcription or translation of the casein gene CSN1S2. Sires with this haplotype had daughters with significantly elevated milk protein content and selection for milk production traits is likely to have increased the frequency of this haplotype in the NRC population. The haplotype was also associated with increased mastitis susceptibility, which might explain parts of the genetic correlation between PY and CM in NRC.

Genome wide scan for somatic cell counts in holstein bulls

Background

Mastitis is the most costly disease for dairy production, and control of the disease is often difficult, due to its multi-factorial nature. Susceptibility to mastitis is under partial genetic control and the industry uses indirect selection for decreased concentrations of somatic cells in milk to reduce mastitis.

Methods

A genome-wide scan was performed to identify genomic regions associated with deregressed estimated breeding values (EBVs) for somatic cell counts (SCC) in Holstein bulls. In total 1183 proven bulls of the Italian of Holstein population, were genotyped with the BovineSNP50 BeadChip (Illumina, San Diego, CA) and a whole genome association analysis was performed using the R package GenABEL.

Results

Two chromosomal regions showed association with SCC, a region on chromosome 14 with high significance (P < 5x10^-6) and a region on chromosome 6 with moderate significance (P < 5x10^-5).

Conclusions

Two regions with effects on SCC have been identified with good statistical support. A further study of these candidate regions will be performed to verify the results and identify the causal mutations.

Quantitative trait loci for clinical mastitis on chromosomes 2, 6, 14 and 20 in Norwegian Red cattle

Mastitis is the most frequent and costly disease in dairy production and solutions leading to a reduction in the incidence of mastitis are highly demanded. Here a genome-wide association study was performed to identify polymorphisms affecting susceptibility to mastitis. Genotypes for 17 349 SNPs distributed across the 29 bovine autosomal chromosomes from a total of 2589 sires with 1 389 776 daughters with records on clinical mastitis were included in the analysis. Records of occurrence of clinical mastitis were divided into seven time periods in the first three lactations in order to identify quantitative trait loci affecting mastitis susceptibility in particular phases of lactation. The most convincing results from the association mapping were followed up and validated by a combined linkage disequilibrium and linkage analysis. The study revealed quantitative trait loci affecting occurrence of clinical mastitis in the periparturient period on chromosomes 2, 6 and 20 and a quantitative trait locus affecting occurrence of clinical mastitis in late lactation on chromosome 14. None of the quantitative trait loci for clinical mastitis detected in the study seemed to affect lactation average of somatic cell score. The SNPs highly associated with clinical mastitis lie near both the gene encoding interleukin 8 on chromosome 6 and the genes encoding the two interleukin 8 receptors on chromosome 2.