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

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.

Prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis

Next-generation sequencing technology has provided resources to easily explore and identify candidate single-nucleotide polymorphisms (SNPs) and variants. However, there remains a challenge in identifying and inferring the causal SNPs from sequence data. A problem with different methods that predict the effect of mutations is that they produce false positives. In this hypothesis, we provide an overview of methods known for identifying causal variants and discuss the challenges, fallacies, and prospects in discerning candidate SNPs. We then propose a three-point classification strategy, which could be an additional annotation method in identifying causalities.

The patterns of genomic variances and covariances across genome for milk production traits between Chinese and Nordic Holstein populations

BACKGROUND

With the development of SNP chips, SNP information provides an efficient approach to further disentangle different patterns of genomic variances and covariances across the genome for traits of interest. Due to the interaction between genotype and environment as well as possible differences in genetic background, it is reasonable to treat the performances of a biological trait in different populations as different but genetic correlated traits. In the present study, we performed an investigation on the patterns of region-specific genomic variances, covariances and correlations between Chinese and Nordic Holstein populations for three milk production traits.

RESULTS

Variances and covariances between Chinese and Nordic Holstein populations were estimated for genomic regions at three different levels of genome region (all SNP as one region, each chromosome as one region and every 100 SNP as one region) using a novel multi-trait random regression model which uses latent variables to model heterogeneous variance and covariance. In the scenario of the whole genome as one region, the genomic variances, covariances and correlations obtained from the new multi-trait Bayesian method were comparable to those obtained from a multi-trait GBLUP for all the three milk production traits. In the scenario of each chromosome as one region, BTA 14 and BTA 5 accounted for very large genomic variance, covariance and correlation for milk yield and fat yield, whereas no specific chromosome showed very large genomic variance, covariance and correlation for protein yield. In the scenario of every 100 SNP as one region, most regions explained <0.50% of genomic variance and covariance for milk yield and fat yield, and explained <0.30% for protein yield, while some regions could present large variance and covariance. Although overall correlations between two populations for the three traits were positive and high, a few regions still showed weakly positive or highly negative genomic correlations for milk yield and fat yield.

CONCLUSIONS

The new multi-trait Bayesian method using latent variables to model heterogeneous variance and covariance could work well for estimating the genomic variances and covariances for all genome regions simultaneously. Those estimated genomic parameters could be useful to improve the genomic prediction accuracy for Chinese and Nordic Holstein populations using a joint reference data in the future.

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.

Using Sequence Variants in Linkage Disequilibrium with Causative Mutations to Improve Across-Breed Prediction in Dairy Cattle: A Simulation Study

Sequence data are expected to increase the reliability of genomic prediction by containing causative mutations directly, especially in cases where low linkage disequilibrium between markers and causative mutations limits prediction reliability, such as across-breed prediction in dairy cattle. In practice, the causative mutations are unknown, and prediction with only variants in perfect linkage disequilibrium with the causative mutations is not realistic, leading to a reduced reliability compared to knowing the causative variants. Our objective was to use sequence data to investigate the potential benefits of sequence data for the prediction of genomic relationships, and consequently reliability of genomic breeding values. We used sequence data from five dairy cattle breeds, and a larger number of imputed sequences for two of the five breeds. We focused on the influence of linkage disequilibrium between markers and causative mutations, and assumed that a fraction of the causative mutations was shared across breeds and had the same effect across breeds. By comparing the loss in reliability of different scenarios, varying the distance between markers and causative mutations, using either all genome wide markers from commercial SNP chips, or only the markers closest to the causative mutations, we demonstrate the importance of using only variants very close to the causative mutations, especially for across-breed prediction. Rare variants improved prediction only if they were very close to rare causative mutations, and all causative mutations were rare. Our results show that sequence data can potentially improve genomic prediction, but careful selection of markers is essential.

Detection of quantitative trait loci for maternal traits using high-density genotypes of Blonde d'Aquitaine beef cattle

Background

The genetic determinism of the calving and suckling performance of beef cows is little known whereas these maternal traits are of major economic importance in beef cattle production systems. This paper aims to identify QTL regions and candidate genes that affect maternal performance traits in the Blonde d’Aquitaine breed. Three calving performance traits were studied: the maternal effect on calving score from field data, the calving score and pelvic opening recorded in station for primiparous cows. Three other traits related to suckling performance were also analysed: the maternal effect on weaning weight from field data, milk yield and the udder swelling score recorded in station for primiparous cows. A total of 2,505 animals were genotyped from various chip densities and imputed in high density chips for 706,791 SNP. The number of genotyped animals with phenotypes ranged from 1,151 to 2,284, depending on the trait considered.

Results

QTL detections were performed using a Bayes C approach. Evidence for a QTL was based on Bayes Factor values. Putative candidate genes were proposed for the QTL with major evidence for one of the six traits and for the QTL shared by at least two of the three traits underlying either calving or suckling performance. Nine candidate genes were proposed for calving performance among the nine highlighted QTL regions. The neuroregulin gene on chromosome 27 was notably identified as a very likely candidate gene for maternal calving performance. As for suckling abilities, seven candidate genes were identified among the 15 highlighted QTL. In particular, the Group-Specific Component gene on chromosome 6, which encodes vitamin D binding protein, is likely to have a major effect on maternal weaning weight in the Blonde d’Aquitaine breed. This gene had already been linked to milk production and clinical mastitis in dairy cattle.

Conclusion

In the near future, these QTL findings and the preliminary proposals of candidate genes which act on the maternal performance of beef cows should help to identify putative causal mutations based on sequence data from different cattle breeds.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-016-0397-y) contains supplementary material, which is available to authorized users.

Genome-wide association study for longevity with whole-genome sequencing in 3 cattle breeds

Longevity is an important economic trait in dairy production. Improvements in longevity could increase the average number of lactations per cow, thereby affecting the profitability of the dairy cattle industry. Improved longevity for cows reduces the replacement cost of stock and enables animals to achieve the highest production period. Moreover, longevity is an indirect indicator of animal welfare. Using whole-genome sequencing variants in 3 dairy cattle breeds, we carried out an association study and identified 7 genomic regions in Holstein and 5 regions in Red Dairy Cattle that were associated with longevity. Meta-analyses of 3 breeds revealed 2 significant genomic regions, located on chromosomes 6 (META-CHR6-88MB) and 18 (META-CHR18-58MB). META-CHR6-88MB overlaps with 2 known genes: neuropeptide G-protein coupled receptor (NPFFR2; 89,052,210-89,059,348 bp) and vitamin D-binding protein precursor (GC; 88,695,940-88,739,180 bp). The NPFFR2 gene was previously identified as a candidate gene for mastitis resistance. META-CHR18-58MB overlaps with zinc finger protein 717 (ZNF717; 58,130,465-58,141,877 bp) and zinc finger protein 613 (ZNF613; 58,115,782-58,117,110 bp), which have been associated with calving difficulties. Information on longevity-associated genomic regions could be used to find causal genes/variants influencing longevity and exploited to improve the reliability of genomic prediction.

Genome-wide association study for endocrine fertility traits using single nucleotide polymorphism arrays and sequence variants in dairy cattle

Endocrine fertility traits, which are defined from progesterone concentration levels in milk, are interesting indicators of dairy cow fertility because they more directly reflect the cows own reproductive physiology than classical fertility traits, which are more biased by farm management decisions. The aim of this study was to detect quantitative trait loci (QTL) for 7 endocrine fertility traits in dairy cows by performing a genome-wide association study with 85k single nucleotide polymorphisms (SNP), and then fine-map targeted QTL regions, using imputed sequence variants. Two classical fertility traits were also analyzed for QTL with 85k SNP. The association between a SNP and a phenotype was assessed by single-locus regression for each SNP, using a linear mixed model that included a random polygenic effect. A total of 2,447 Holstein Friesian cows with 5,339 lactations with both phenotypes and genotypes were used for association analysis. Heritability estimates ranged from 0.09 to 0.15 for endocrine fertility traits and 0.03 to 0.10 for classical fertility traits. The genome-wide association study identified 17 QTL regions for endocrine fertility traits on Bos taurus autosomes (BTA) 2, 3, 8, 12, 15, 17, 23, and 25. The highest number (5) of QTL regions from the genome-wide association study was identified for the endocrine trait "proportion of samples with luteal activity." Overlapping QTL regions were found between endocrine traits on BTA 2, 3, and 17. For the classical trait calving to first service, 3 QTL regions were identified on BTA 3, 15, and 23, and an overlapping region was identified on BTA 23 with endocrine traits. Fine-mapping target regions for the endocrine traits on BTA 2 and 3 using imputed sequence variants confirmed the QTL from the genome-wide association study, and identified several associated variants that can contribute to an index of markers for genetic improvement of fertility. Several potential candidate genes underlying endocrine fertility traits were also identified in the target regions and are discussed. However, due to high linkage disequilibrium, it was not possible to specify genes or polymorphisms as causal factors for any of the regions.

A 0.5-Mbp deletion on bovine chromosome 23 is a strong candidate for stillbirth in Nordic Red cattle

Background

A whole-genome association study of 4631 progeny-tested Nordic Red dairy cattle bulls using imputed next-generation sequencing data revealed a major quantitative trait locus (QTL) that affects birth index (BI) on Bos taurus autosome (BTA) 23. We analyzed this QTL to identify which of the component traits of BI are affected and understand its molecular basis.

Results

A genome-wide scan of BI in Nordic Red dairy cattle detected major QTL on BTA6, 14 and 23. The strongest associated single nucleotide polymorphism (SNP) on BTA23 was located at 13,313,896 bp with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$- \log_{10} ({\text{p}}) = 50.63$$\end{document}-log10(p)=50.63. Analyses of component traits showed that the QTL had a large effect on stillbirth. Based on the 10 most strongly associated SNPs with stillbirth, we constructed a haplotype. Among this haplotype’s alleles, HAP_QTL had a large negative effect on stillbirth. No animals were found to be homozygous for HAP_QTL. Analysis of stillbirth records that were categorized by carrier status for HAP_QTL of the sire and maternal grandsire suggested that this haplotype had a recessive mode of inheritance. Illumina BovineHD BeadChip genotypes and genotype intensity data indicated a chromosomal deletion between 12.28 and 12.81 Mbp on BTA23. An independent set of Illumina Bovine50k BeadChip genotypes identified a recessive lethal haplotype that spanned the deleted region.

Conclusions

A deleted region of approximately 500 kb that spans three genes on BTA23 was identified and is a strong candidate QTL with a large effect on BI by increasing stillbirth.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-016-0215-z) contains supplementary material, which is available to authorized users.

Identification of QTL on Chromosome 18 Associated with Non-Coagulating Milk in Swedish Red Cows

Non-coagulating (NC) milk, defined as milk not coagulating within 40 min after rennet-addition, can have a negative influence on cheese production. Its prevalence is estimated at 18% in the Swedish Red (SR) cow population. Our study aimed at identifying genomic regions and causal variants associated with NC milk in SR cows, by doing a GWAS using 777k SNP genotypes and using imputed sequences to fine map the most promising genomic region. Phenotypes were available from 382 SR cows belonging to 21 herds in the south of Sweden, from which individual morning milk was sampled. NC milk was treated as a binary trait, receiving a score of one in case of non-coagulation within 40 min. For all 382 SR cows, 777k SNP genotypes were available as well as the combined genotypes of the genetic variants of αs1-β-κ-caseins. In addition, whole-genome sequences from the 1000 Bull Genome Consortium (Run 3) were available for 429 animals of 15 different breeds. From these sequences, 33 sequences belonged to SR and Finish Ayrshire bulls with a large impact in the SR cow population. Single-marker analyses were run in ASReml using an animal model. After fitting the casein loci, 14 associations at -Log10(P-value) > 6 identified a promising region located on BTA18. We imputed sequences to the 382 genotyped SR cows using Beagle 4 for half of BTA18, and ran a region-wide association study with imputed sequences. In a seven mega base-pairs region on BTA18, our strongest association with NC milk explained almost 34% of the genetic variation in NC milk. Since it is possible that multiple QTL are in strong LD in this region, 59 haplotypes were built, genetically differentiated by means of a phylogenetic tree, and tested in phenotype-genotype association studies. Haplotype analyses support the existence of one QTL underlying NC milk in SR cows. A candidate gene of interest is the VPS35 gene, for which one of our strongest association is an intron SNP in this gene. The VPS35 gene belongs to the mammary gene sets of pre-parturient and of lactating cows.

Meta-Analysis of Transcriptional Responses to Mastitis-Causing Escherichia coli

Bovine mastitis is a widespread disease in dairy cows, and is often caused by bacterial mammary gland infection. Mastitis causes reduced milk production and leads to excessive use of antibiotics. We present meta-analysis of transcriptional profiles of bovine mastitis from 10 studies and 307 microarrays, allowing identification of much larger sets of affected genes than any individual study. Combining multiple studies provides insight into the molecular effects of Escherichia coli infection in vivo and uncovers differences between the consequences of E. coli vs. Staphylococcus aureus infection of primary mammary epithelial cells (PMECs). In udders, live E. coli elicits inflammatory and immune defenses through numerous cytokines and chemokines. Importantly, E. coli infection causes downregulation of genes encoding lipid biosynthesis enzymes that are involved in milk production. Additionally, host metabolism is generally suppressed. Finally, defensins and bacteria-recognition genes are upregulated, while the expression of the extracellular matrix protein transcripts is silenced. In PMECs, heat-inactivated E. coli elicits expression of ribosomal, cytoskeletal and angiogenic signaling genes, and causes suppression of the cell cycle and energy production genes. We hypothesize that heat-inactivated E. coli may have prophylactic effects against mastitis. Heat-inactivated S. aureus promotes stronger inflammatory and immune defenses than E. coli. Lipopolysaccharide by itself induces MHC antigen presentation components, an effect not seen in response to E. coli bacteria. These results provide the basis for strategies to prevent and treat mastitis and may lead to the reduction in the use of antibiotics.

A multi-trait meta-analysis with imputed sequence variants reveals twelve QTL for mammary gland morphology in Fleckvieh cattle

Background

The availability of whole-genome sequence data from key ancestors in bovine populations provides an exhaustive catalogue of polymorphic sites that segregate within and across cattle breeds. Sequence variants identified from the sequenced genome of key ancestors can be imputed into animals that have been genotyped using medium- and high-density genotyping arrays. Association analysis with imputed sequences, particularly when applied to multiple traits simultaneously, is a very powerful approach to detect candidate causal variants that underlie complex phenotypes.

Results

We used whole-genome sequence data from 157 key ancestors of the German Fleckvieh cattle population to impute 20,561,798 sequence variants into 10,363 animals that had (partly imputed) genotypes based on 634,109 single nucleotide polymorphisms (SNPs). Rare variants were more frequent among the sequence-derived than the array-derived genotypes. Association studies with imputed sequence variants were performed using seven correlated udder conformation traits as response variables. The calculation of an approximate multi-trait test statistic enabled us to detect 12 quantitative trait loci (QTL) (P < 2.97 × 10⁻⁹) that affect different morphological features of the mammary gland. Among the tested variants, the most significant associations were found for imputed sequence variants at 11 QTL, whereas the top association signal was observed for an array-derived variant at a QTL on bovine chromosome 14. Seven QTL were associated with multiple phenotypes. Most QTL were located in non-coding regions of the genome but in close proximity of candidate genes that could be involved in mammary gland morphology (SP5, GC, NPFFR2, CRIM1, RXFP2, TBX5, RBM19 and ADAM12).

Conclusions

Using imputed sequence variants in association analyses allows the detection of QTL at maximum resolution. Multi-trait approaches can reveal QTL that are not detected in single-trait association studies. Most QTL for udder conformation traits were located in non-coding regions of the genome, which suggests that mutations in regulatory sequences are the major determinants of variation in mammary gland morphology in cattle.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-016-0190-4) contains supplementary material, which is available to authorized users.

Validation of PDE9A Gene Identified in GWAS Showing Strong Association with Milk Production Traits in Chinese Holstein

Phosphodiesterase9A (PDE9A) is a cyclic guanosine monophosphate (cGMP)-specific enzyme widely expressed among the tissues, which is important in activating cGMP-dependent signaling pathways. In our previous genome-wide association study, a single nucleotide polymorphism (SNP) (BTA-55340-no-rs(b)) located in the intron 14 of PDE9A, was found to be significantly associated with protein yield. In addition, we found that PDE9A was highly expressed in mammary gland by analyzing its mRNA expression in different tissues. The objectives of this study were to identify genetic polymorphisms of PDE9A and to determine the effects of these variants on milk production traits in dairy cattle. DNA sequencing identified 11 single nucleotide polymorphisms (SNPs) and six SNPs in 5' regulatory region were genotyped to test for the subsequent association analyses. After Bonferroni correction for multiple testing, all these identified SNPs were statistically significant for one or more milk production traits (p < 0.0001~0.0077). Interestingly, haplotype-based association analysis revealed similar effects on milk production traits (p < 0.01). In follow-up RNA expression analyses, two SNPs (c.-1376 G>A, c.-724 A>G) were involved in the regulation of gene expression. Consequently, our findings provide confirmatory evidences for associations of PDE9A variants with milk production traits and these identified SNPs may serve as genetic markers to accelerate Chinese Holstein breeding program.

Genetic dissection of milk yield traits and mastitis resistance quantitative trait loci on chromosome 20 in dairy cattle

Intense selection to increase milk yield has had negative consequences for mastitis incidence in dairy cattle. Due to low heritability of mastitis resistance and an unfavorable genetic correlation with milk yield, a reduction in mastitis through traditional breeding has been difficult to achieve. Here, we examined quantitative trait loci (QTL) that segregate for clinical mastitis and milk yield on Bos taurus autosome 20 (BTA20) to determine whether both traits are affected by a single polymorphism (pleiotropy) or by multiple closely linked polymorphisms. In the latter but not the former situation, undesirable genetic correlation could potentially be broken by selecting animals that have favorable variants for both traits. First, we performed a within-breed association study using a haplotype-based method in Danish Holstein cattle (HOL). Next, we analyzed Nordic Red dairy cattle (RDC) and Danish Jersey cattle (JER) with the goal of determining whether these QTL identified in Holsteins were segregating across breeds. Genotypes for 12,566 animals (5,966 HOL, 5,458 RDC, and 1,142 JER) were determined by using the Illumina Bovine SNP50 BeadChip (50K; Illumina, San Diego, CA), which identifies 1,568 single nucleotide polymorphisms on BTA20. Data were combined, phased, and clustered into haplotype states, followed by within- and across-breed haplotype-based association analyses using a linear mixed model. Association signals for both clinical mastitis and milk yield peaked in the 26- to 40-Mb region on BTA20 in HOL. Single-variant association analyses were carried out in the QTL region using whole sequence level variants imputed from references of 2,036 HD genotypes (BovineHD BeadChip; Illumina) and 242 whole-genome sequences. The milk QTL were also segregating in RDC and JER on the BTA20-targeted region; however, an indication of differences in the causal factor(s) was observed across breeds. A previously reported F279Y mutation (rs385640152) within the growth hormone receptor gene showed strong association with milk, fat, and protein yields. In HOL, the highest peaks for milk yield and susceptibility to mastitis were separated by over 3.5 Mb (3.8 Mb by haplotype analysis, 3.6 Mb by single nucleotide polymorphism analysis), suggesting separate genetic variants for the traits. Further analysis yielded 2 candidate mutations for the mastitis QTL, at 33,642,072 bp (rs378947583) in an intronic region of the caspase recruitment domain protein 6 gene and 35,969,994 bp (rs133596506) in an intronic region of the leukemia-inhibitory factor receptor gene. These findings suggest that it may be possible to separate these beneficial and detrimental genetic factors through targeted selective breeding.

Genome-wide association study for female fertility in Nordic Red cattle

Background

The Nordic Red Cattle (NRC) consists of animls belonging to the Danish Red, Finnish Ayrshire, and Swedish Red breeds. Compared to the Holstein breed, NRC animals are smaller, have a shorter calving interval, lower mastitis incidence and lower rates of stillborn calves, however they produce less milk, fat and protein. Female fertility is an important trait for the dairy cattle farmer. Selection decisions in female fertilty in NRC are based on the female fertility index (FTI). FTI is a composite index including a number of sub-indices describing aspects of female fertility in dairy cattle. The sub-traits of FTI are: number of inseminations per conception (AIS) in cows (C) and heifers (H), the length in days of the interval from calving to first insemination (ICF) in cows, days from first to last insemination (IFL) in cows and heifers, and 56-day non-return rate (NRR) in cows and heifers. The aim of this study was first to identify QTL for FTI by conducting a genome scan for variants associated with fertility index using imputed whole genome sequence data based on 4207 Nordic Red sires, and subsequently analyzing which of the sub-traits were affected by each FTI QTL by associating them with the sub-traits.

Results

A total 17,388 significant SNP markers (−log₁₀(P) > 8.25) were detected for FTI distributed over 25 chromosomes. The chromosomes with the most significant markers were tested for associations with the underlying sub-traits: BTA1 (822 SNP), BTA2 (220 SNP), BTA3 (83 SNP), BTA5 (195 SNP), two regions on BTA6 (503 SNP), BTA13 (980 SNP), BTA15 (23 SNP), BTA20 (345 SNP), and BTA24 (104 SNP). The fertility traits underlying the FTI peak area were: BTA1 (IFLC, IFLH), BTA2 (AISH, IFLH, NRRH), BTA3 (AISH, NRRH), BTA5 (AISC, AISH, IFLH), BTA6 (region 1: AISH, NRRH; region 2: AISH, IFLH), BTA13 (IFLH, IFLC), BTA15 (IFLC, NRRH), and BTA24 (AISH, IFLH). For BTA20 all sub-traits had SNP markers with a –log₁₀(P) > 10. Furthermore the genes assigned to the most significant SNP for FTI were located on BTA6 (GPR125), BTA13 (ANKRD60), BTA15 (GRAMD1B), and BTA24 (ZNF521).

Conclusion

This study 1) shows that many markers within FTI QTL regions were significantly associated with both AISH and IFLH, and 2) identified candidate genes for FTI located on BTA6 (GPR125), BTA13 (ANKRD60), BTA15 (GRAMD1B), and BTA24 (ZNF521). It is not known how the genes/variants identified in this study regulate female fertility, however the majority of these genes were involved in protein binding, 3) a SNP in a QTL region for FTI on BTA20 was previously validated in three cattle breeds.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0269-x) contains supplementary material, which is available to authorized users.

Association analysis for udder health based on SNP-panel and sequence data in Danish Holsteins

BACKGROUND

The sensitivity of genome-wide association studies for the detection of quantitative trait loci (QTL) depends on the density of markers examined and the statistical models used. This study compares the performance of three marker densities to refine six previously detected QTL regions for mastitis traits: 54 k markers of a medium-density SNP (single nucleotide polymorphism) chip (MD), imputed 777 k markers of a high-density SNP chip (HD), and imputed whole-genome sequencing data (SEQ). Each dataset contained data for 4496 Danish Holstein cattle. Comparisons were performed using a linear mixed model (LM) and a Bayesian variable selection model (BVS).

RESULTS

After quality control, 587, 7825, and 78 856 SNPs in the six targeted regions remained for MD, HD, and SEQ data, respectively. In general, the association patterns between SNPs and traits were similar for the three marker densities when tested using the same statistical model. With the LM model, 120 (MD), 967 (HD), and 7209 (SEQ) SNPs were significantly associated with mastitis, whereas with the BVS model, 43 (MD), 131 (HD), and 1052 (SEQ) significant SNPs (Bayes factor > 3.2) were observed. A total of 26 (MD), 75 (HD), and 465 (SEQ) significant SNPs were identified by both models. In addition, one, 16, and 33 QTL peaks for MD, HD, and SEQ data were detected according to the QTL intensity profile of SNP bins by post-analysis of the BVS model.

CONCLUSIONS

The power to detect significant associations increased with increasing marker density. The BVS model resulted in clearer boundaries between linked QTL than the LM model. Using SEQ data, the six targeted regions were refined to 33 candidate QTL regions for udder health. The comparison between these candidate QTL regions and known genes suggested that NPFFR2, SLC4A4, DCK, LIFR, and EDN3 may be considered as candidate genes for mastitis susceptibility.

Identification of genomic regions associated with female fertility in Danish Jersey using whole genome sequence data

BACKGROUND

Female fertility is an important trait in cattle breeding programs. In the Nordic countries selection is based on a fertility index (FTI). The fertility index is a weighted combination of four female fertility traits estimated breeding values for number of inseminations per conception (AIS), 56-day non-return rate (NRR), number of days from first to last insemination (IFL), and number of days between calving and first insemination (ICF). The objective of this study was to identify associations between sequence variants and fertility traits in Jersey cattle based on 1,225 Jersey sires from Denmark with official breeding values for female fertility traits. The association analyses were carried out in two steps: first the cattle genome was scanned for quantitative trait loci using a sire model for FTI using imputed whole genome sequence variants; second the significant quantitative trait locus regions were re-analyzed using a linear mixed model (animal model) for both FTI and its component traits AIS, NRR, IFL and ICF. The underlying traits were analyzed separately for heifers (first parity cows) and cows (later parity cows) for AIS, NRR, and IFL.

RESULTS

In the first step 6 QTL were detected for FTI: one QTL on each of BTA7, BTA20, BTA23, BTA25, and two QTL on BTA9 (QTL9-1 and QTL9-2). In the second step, ICF showed association with the QTL regions on BTA7, QTL9-2 QTL2 on BTA9, and BTA25, AIS for cows on BTA20 and BTA23, AIS for heifers on QTL9-2 on BTA9, IFL for cows on BTA20, BTA23 and BTA25, IFL for heifers on BTA7 and QTL9-2 on BTA9, NRR for heifers on BTA7 and BTA23, and NRR for cows on BTA23.

CONCLUSION

The genome wide association study presented here revealed 6 genomic regions associated with FTI. Screening these 6 QTL regions for the underlying female fertility traits revealed that different female fertility traits showed associations with different subsets of the individual FTI QTL peaks. The result of this study contributed to a better insight into the genetic control of FTI in the Danish Jersey.

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.

Loci associated with adult stature also affect calf birth survival in cattle

Background

Understanding the underlying pleiotropic relationships among quantitative traits is necessary in order to predict correlated responses to artificial selection. The availability of large-scale next-generation sequence data in cattle has provided an opportunity to examine whether pleiotropy is responsible for overlapping QTL in multiple economic traits. In the present study, we examined QTL affecting cattle stillbirth, calf size, and adult stature located in the same genomic region.

Results

A genome scan using imputed whole genome sequence variants revealed one QTL with large effects on the service sire calving index (SCI), and body conformation index (BCI) at the same location (~39 Mb) on chromosome 6 in Nordic Red cattle. The targeted region was analyzed for SCI and BCI component traits. The QTL peak included LCORL and NCAPG genes, which had been reported to influence fetal growth and adult stature in several species. The QTL exhibited large effects on calf size and stature in Nordic Red cattle. Two deviant haplotypes (HAP1 and HAP2) were resolved which increased calf size at birth, and affected adult body conformation. However, the haplotypes also resulted in increased calving difficulties and calf mortality due to increased calf size at birth. Haplotype locations overlapped, however linkage disequilibrium (LD) between the sites was low, suggesting that two independent mutations were responsible for similar effects. The difference in prevalence between the two haplotypes in Nordic Red subpopulations suggested independent origins in different populations.

Conclusions

Results of our study identified QTL with large effects on body conformation and service sire calving traits on chromosome 6 in cattle. We present robust evidence that variation at the LCORL and NCAPG locus affects calf size at birth and adult stature. We suggest the two deviant haplotypes within the QTL were due to two independent mutations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0202-3) contains supplementary material, which is available to authorized users.

Short communication: Validation of 4 candidate causative trait variants in 2 cattle breeds using targeted sequence imputation

Most association studies for pinpointing trait-associated variants are performed within breed. The availability of sequence data from key ancestors of several cattle breeds now enables immediate assessment of the frequency of trait-associated variants in populations different from the mapping population and their imputation into large validation populations. The objective of this study was to validate the effects of 4 putatively causative variants on milk production traits, male fertility, and stature in German Fleckvieh and Holstein-Friesian animals using targeted sequence imputation. We used whole-genome sequence data of 456 animals to impute 4 missense mutations in DGAT1, GHR, PRLR, and PROP1 into 10,363 Fleckvieh and 8,812 Holstein animals. The accuracy of the imputed genotypes exceeded 95% for all variants. Association testing with imputed variants revealed consistent antagonistic effects of the DGAT1 p.A232K and GHR p.F279Y variants on milk yield and protein and fat contents, respectively, in both breeds. The allele frequency of both polymorphisms has changed considerably in the past 20 yr, indicating that they were targets of recent selection for milk production traits. The PRLR p.S18N variant was associated with yield traits in Fleckvieh but not in Holstein, suggesting that it may be in linkage disequilibrium with a mutation affecting yield traits rather than being causal. The reported effects of the PROP1 p.H173R variant on milk production, male fertility, and stature could not be confirmed. Our results demonstrate that population-wide imputation of candidate causal variants from sequence data is feasible, enabling their rapid validation in large independent populations.

Quantitative trait loci markers derived from whole genome sequence data increases the reliability of genomic prediction

This study investigated the effect on the reliability of genomic prediction when a small number of significant variants from single marker analysis based on whole genome sequence data were added to the regular 54k single nucleotide polymorphism (SNP) array data. The extra markers were selected with the aim of augmenting the custom low-density Illumina BovineLD SNP chip (San Diego, CA) used in the Nordic countries. The single-marker analysis was done breed-wise on all 16 index traits included in the breeding goals for Nordic Holstein, Danish Jersey, and Nordic Red cattle plus the total merit index itself. Depending on the trait's economic weight, 15, 10, or 5 quantitative trait loci (QTL) were selected per trait per breed and 3 to 5 markers were selected to tag each QTL. After removing duplicate markers (same marker selected for more than one trait or breed) and filtering for high pairwise linkage disequilibrium and assaying performance on the array, a total of 1,623 QTL markers were selected for inclusion on the custom chip. Genomic prediction analyses were performed for Nordic and French Holstein and Nordic Red animals using either a genomic BLUP or a Bayesian variable selection model. When using the genomic BLUP model including the QTL markers in the analysis, reliability was increased by up to 4 percentage points for production traits in Nordic Holstein animals, up to 3 percentage points for Nordic Reds, and up to 5 percentage points for French Holstein. Smaller gains of up to 1 percentage point was observed for mastitis, but only a 0.5 percentage point increase was seen for fertility. When using a Bayesian model accuracies were generally higher with only 54k data compared with the genomic BLUP approach, but increases in reliability were relatively smaller when QTL markers were included. Results from this study indicate that the reliability of genomic prediction can be increased by including markers significant in genome-wide association studies on whole genome sequence data alongside the 54k SNP set.