Genetic determinants of hair and eye colours in the Scottish and Danish populations

Background

The Bovine HapMap Consortium has generated assay panels to genotype ~30,000 single nucleotide polymorphisms (SNPs) from 501 animals sampled from 19 worldwide taurine and indicine breeds, plus two outgroup species (Anoa and Water Buffalo). Within the larger set of SNPs we targeted 101 high density regions spanning up to 7.6 Mb with an average density of approximately one SNP per 4 kb, and characterized the linkage disequilibrium (LD) and haplotype block structure within individual breeds and groups of breeds in relation to their geographic origin and use.

Results

From the 101 targeted high-density regions on bovine chromosomes 6, 14, and 25, between 57 and 95% of the SNPs were informative in the individual breeds. The regions of high LD extend up to ~100 kb and the size of haplotype blocks ranges between 30 bases and 75 kb (10.3 kb average). On the scale from 1–100 kb the extent of LD and haplotype block structure in cattle has high similarity to humans. The estimation of effective population sizes over the previous 10,000 generations conforms to two main events in cattle history: the initiation of cattle domestication (~12,000 years ago), and the intensification of population isolation and current population bottleneck that breeds have experienced worldwide within the last ~700 years. Haplotype block density correlation, block boundary discordances, and haplotype sharing analyses were consistent in revealing unexpected similarities between some beef and dairy breeds, making them non-differentiable. Clustering techniques permitted grouping of breeds into different clades given their similarities and dissimilarities in genetic structure.

Conclusion

This work presents the first high-resolution analysis of haplotype block structure in worldwide cattle samples. Several novel results were obtained. First, cattle and human share a high similarity in LD and haplotype block structure on the scale of 1–100 kb. Second, unexpected similarities in haplotype block structure between dairy and beef breeds make them non-differentiable. Finally, our findings suggest that ~30,000 uniformly distributed SNPs would be necessary to construct a complete genome LD map in Bos taurus breeds, and ~580,000 SNPs would be necessary to characterize the haplotype block structure across the complete cattle genome.     

Genome-wide scan for bovine twinning rate QTL using linkage disequilibrium

Twinning is a complex trait with negative impacts on health and reproduction, which cause economic loss in dairy production. Several twinning rate quantitative trait loci (QTL) have been detected in previous studies, but confidence intervals for QTL location are broad and many QTL are unreplicated. To identify genomic regions or genes associated with twinning rate, QTL analysis based on linkage combined with linkage disequilibrium (LLD) and individual marker associations was conducted across the genome using high-throughput single nucleotide polymorphism (SNP) genotypes. A total of 9919 SNP markers were genotyped with 200 sires and sons in 19 half-sib North American Holstein dairy cattle families. After SNPs were genotyped, informative markers were selected for genome-wide association tests and QTL searches. Evidence for twinning rate QTL was found throughout the genome. Thirteen markers significantly associated with twinning rate were detected on chromosomes 2, 5 and 14 ( P  < 2.3 × 10⁻⁵). Twenty-six regions on fourteen chromosomes were identified by LLD analysis at P  < 0.0007. Seven previously reported ovulation or twinning rate QTL were supported by results of single marker association or LLD analyses. Single marker association analysis and LLD mapping were complementary tools for the identification of putative QTL in this genome scan.     

Haplotype evolution and linkage disequilibrium: A simulation study

We simulated the evolution of a three-site haplotype system, two restriction fragment length polymorphisms flanking one short tandem repeat polymorphism, under five different demographic scenarios, three with constant population size and two with population growth. The simulation was designed to observe the effects of population history, recombination fraction, and mutation rate on allele and haplotype frequencies, haplotype diversity, frequency of ancestral alleles, and linkage disequilibrium. The known ancestral haplotypes were often found at low frequencies and even became extinct after 5, 000 generations, especially with small effective population sizes. The original linkage disequilibrium was eroded and even reversed.     

Genome-wide analysis in endangered populations: a case study in Barbaresca sheep

Analysis of genomic data is becoming increasingly common in the livestock industry and the findings have been an invaluable resource for effective management of breeding programs in small and endangered populations. In this paper, with the goal of highlighting the potential of genomic analysis for small and endangered populations, genome-wide levels of linkage disequilibrium, measured as the squared correlation coefficient of allele frequencies at a pair of loci, effective population size, runs of homozygosity (ROH) and genetic diversity parameters, were estimated in Barbaresca sheep using Illumina OvineSNP50K array data. Moreover, the breed’s genetic structure and its relationship with other breeds were investigated. Levels of pairwise linkage disequilibrium decreased with increasing distance between single nucleotide polymorphisms. An average correlation coefficient <0.25 was found for markers located up to 50 kb apart. Therefore, these results support the need to use denser single nucleotide polymorphism panels for high power association mapping and genomic selection efficiency in future breeding programs. The estimate of past effective population size ranged from 747 animals 250 generations ago to 28 animals five generations ago, whereas the contemporary effective population size was 25 animals. A total of 637 ROH were identified, most of which were short (67%) and ranged from 1 to 10 Mb. The genetic analyses revealed that the Barbaresca breed tended to display lower variability than other Sicilian breeds. Recent inbreeding was evident, according to the ROH analysis. All the investigated parameters showed a comparatively narrow genetic base and indicated an endangered status for Barbaresca. Multidimensional scaling, model-based clustering, measurement of population differentiation, neighbor networks and haplotype sharing distinguished Barbaresca from other breeds, showed a low level of admixture with the other breeds considered in this study, and indicated clear genetic differences compared with other breeds. Attention should be given to the conservation of Barbaresca due to its critical conservation status. In this context, genomic information may have a crucial role in management of small and endangered populations.     

Relative extended haplotype homozygosity signals across breeds reveal dairy and beef specific signatures of selection

Background

A number of methods are available to scan a genome for selection signatures by evaluating patterns of diversity within and between breeds. Among these, “extended haplotype homozygosity” (EHH) is a reliable approach to detect genome regions under recent selective pressure. The objective of this study was to use this approach to identify regions that are under recent positive selection and shared by the most representative Italian dairy and beef cattle breeds.

Results

A total of 3220 animals from Italian Holstein (2179), Italian Brown (775), Simmental (493), Marchigiana (485) and Piedmontese (379) breeds were genotyped with the Illumina BovineSNP50 BeadChip v.1. After standard quality control procedures, genotypes were phased and core haplotypes were identified. The decay of linkage disequilibrium (LD) for each core haplotype was assessed by measuring the EHH. Since accurate estimates of local recombination rates were not available, relative EHH (rEHH) was calculated for each core haplotype. Genomic regions that carry frequent core haplotypes and with significant rEHH values were considered as candidates for recent positive selection. Candidate regions were aligned across to identify signals shared by dairy or beef cattle breeds. Overall, 82 and 87 common regions were detected among dairy and beef cattle breeds, respectively. Bioinformatic analysis identified 244 and 232 genes in these common genomic regions. Gene annotation and pathway analysis showed that these genes are involved in molecular functions that are biologically related to milk or meat production.

Conclusions

Our results suggest that a multi-breed approach can lead to the identification of genomic signatures in breeds of cattle that are selected for the same production goal and thus to the localisation of genomic regions of interest in dairy and beef production.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0113-9) contains supplementary material, which is available to authorized users.     

Expression,SNV identification,linkage disequilibrium,and combined genotype association analysis of the muscle-specific gene CSRP3 in Chinese cattle

The cysteine and glycine-rich protein 3 (CSRP3) plays an important role in the myofiber differentiation. Here, we identified five SNVs in all exon and intron regions of the CSRP3 gene using DNA sequencing, PCR-RFLP and forced-PCR-RFLP methods in 554 cattle. Four of the five SNVs were significantly associated with growth performance and carcass traits of the cattle. In addition, we evaluated haplotype frequency and linkage disequilibrium coefficient of five sequence variants. The result of haplotype analysis demonstrated 28 haplotypes present in Qinchuan and two haplotypes in Chinese Holstein. Only haplotypes 1 and 8 were being shared by two populations, haplotype 14 had the highest haplotype frequency in Qinchuan (17.4%) and haplotype 8 had the highest haplotype frequency in Chinese Holstein (94.4%). Statistical analyses of combined genotypes indicated that some combined genotypes were significantly or highly significantly associated with growth and carcass traits in the Qinchuan cattle population. qPCR analyses also showed that bovine CSRP3 gene was exclusively expressed in longissimus dorsi muscle and heart tissues. The data support the high potential of the CSRP3 as a marker gene for the improvement of growth performance and carcass traits in selection programs.     

Novel Muscle-Specific Genes TCAP,TNNI1, and FHL1 in Cattle: SNVs,Linkage Disequilibrium,Combined Genotypes,Association Analysis of Growth Performance,and Carcass Quality Traits and Expression Studies

TCAP, TNNI1, and FHL1 regulate muscle growth and development. In this study, four single nucleotide variants (SNVs) were discovered in almost all of the exon and intron regions of the TCAP, TNNI1, and FHL1 genes using DNA pooled sequencing, polymerase chain reaction (PCR)-RFLP, and forced-PCR-RFLP methods in 576 cattle. Four SNVs were significantly associated with the growth performance and carcass quality traits of the cattle. In addition, the haplotype, haplotype frequency, and linkage disequilibrium coefficient of three sequence variants were also evaluated in the cattle population. Haplotype analysis demonstrated that eight haplotypes were present in the Qinchuan cattle population and no haplotypes were present in the Chinese Holstein population; haplotype 1 had the highest frequency in the Qinchuan (42.7%) population. Statistical analyses of 12 combined genotypes indicated that some were significantly associated with the growth performance and carcass quality traits of the Qinchuan cattle population. Moreover, the quantitative real-time polymerase chain reaction results demonstrated that the bovine TCAP, TNNI1, and FHL1 genes were exclusively expressed in muscle tissue. These data support the high potentials of the TCAP, TNNI1, and FHL1 as marker genes to improve the growth performance and carcass quality traits of Qinchuan cattle or other animals selection programs.     

Consistency of linkage disequilibrium between Chinese and Nordic Holsteins and genomic prediction for Chinese Holsteins using a joint reference population

Background

In China, the reference population of genotyped Holstein cattle is relatively small with to date, 80 bulls and 2091 cows genotyped with the Illumina 54 K chip. Including genotyped Holstein cattle from other countries in the reference population could improve the accuracy of genomic prediction of the Chinese Holstein population. This study investigated the consistency of linkage disequilibrium between adjacent markers between the Chinese and Nordic Holstein populations, and compared the reliability of genomic predictions based on the Chinese reference population only or the combined Chinese and Nordic reference populations.

Methods

Genomic estimated breeding values of Chinese Holstein cattle were predicted using a single-trait GBLUP model based on the Chinese reference dataset, and using a two-trait GBLUP model based on a joint reference dataset that included both the Chinese and Nordic Holstein data.

Results

The extent of linkage disequilibrium was similar in the Chinese and Nordic Holstein populations and the consistency of linkage disequilibrium between the two populations was very high, with a correlation of 0.97. Genomic prediction using the joint versus the Chinese reference dataset increased reliabilities of genomic predictions of Chinese Holstein bulls in the test data from 0.22, 0.15 and 0.11 to 0.51, 0.47 and 0.36 for milk yield, fat yield and protein yield, respectively. Using five-fold cross-validation, reliabilities of genomic predictions of Chinese cows increased from 0.15, 0.12 and 0.15 to 0.26, 0.17 and 0.20 for milk yield, fat yield and protein yield, respectively.

Conclusions

The linkage disequilibrium between the two populations was very consistent and using the combined Nordic and Chinese reference dataset substantially increased reliabilities of genomic predictions for Chinese Holstein cattle.     

Accuracy of marker-assisted selection with single markers and marker haplotypes in cattle

A key question for the implementation of marker-assisted selection (MAS) using markers in linkage disequilibrium with quantitative trait loci (QTLs) is how many markers surrounding each QTL should be used to ensure the marker or marker haplotypes are in sufficient linkage disequilibrium (LD) with the QTL. In this paper we compare the accuracy of MAS using either single markers or marker haplotypes in an Angus cattle data set consisting of 9323 genome-wide single nucleotide polymorphisms (SNPs) genotyped in 379 Angus cattle. The extent of LD in the data set was such that the average marker-marker r2 was 0.2 at 200 kb. The accuracy of MAS increased as the number of markers in the haplotype surrounding the QTL increased, although only when the number of markers in the haplotype was 4 or greater did the accuracy exceed that achieved when the SNP in the highest LD with the QTL was used. A large number of phenotypic records (>1000) were required to accurately estimate the effects of the haplotypes.     

A genome‐wide scan for signatures of recent selection in Holstein cattle

The data from the newly available 50 K SNP chip was used for tagging the genome‐wide footprints of positive selection in Holstein–Friesian cattle. For this purpose, we employed the recently described Extended Haplotype Homozygosity test, which detects selection by measuring the characteristics of haplotypes within a single population. To assess formally the significance of these results, we compared the combination of frequency and the Relative Extended Haplotype Homozygosity value of each core haplotype with equally frequent haplotypes across the genome. A subset of the putative regions showing the highest significance in the genome‐wide EHH tests was mapped. We annotated genes to identify possible influence they have in beneficial traits by using the Gene Ontology database. A panel of genes, including FABP3, CLPN3, SPERT, HTR2A5, ABCE1, BMP4 and PTGER2, was detected, which overlapped with the most extreme P‐values. This panel comprises some interesting candidate genes and QTL, representing a broad range of economically important traits such as milk yield and composition, as well as reproductive and behavioural traits. We also report high values of linkage disequilibrium and a slower decay of haplotype homozygosity for some candidate regions harbouring major genes related to dairy quality. The results of this study provide a genome‐wide map of selection footprints in the Holstein genome, and can be used to better understand the mechanisms of selection in dairy cattle breeding.     

Linkage disequilibrium predicts physical distance in the adenomatous polyposis coli region.

To test the reliability of linkage-disequilibrium analysis for gene mapping, we compared physical distance and linkage disequilibrium among seven polymorphisms in the adenomatous polyposis coli (APC) region on chromosome 5. Three of them lie within the APC gene, and two lie within the nearby MCC (mutated in colon cancer) gene. One polymorphism lies between the two genes, and one is likely to be 5' of MCC. Five of these polymorphisms are newly reported. All polymorphisms were typed in the CEPH kindreds, yielding 179-205 unrelated two-locus haplotypes. Linkage disequilibrium between each pair of polymorphisms is highly correlated with physical distance in this 550-kb region (correlation coefficient -.80, P < .006). This result is replicated in both the Utah and non-Utah CEPH kindreds. There is a tendency for greater disequilibrium among pairs of polymorphisms located within the same gene than among other pairs of polymorphisms. Trigenic, quadrigenic, three-locus, and four-locus disequilibrium measures were also estimated, but these measures revealed much less disequilibrium than did the two-locus disequilibrium measures. A review of 19 published disequilibrium studies, including this one, shows that linkage disequilibrium nearly always correlates significantly with physical distance in genomic regions > 50-60 kb but that it does not do so in smaller genomic regions. We show that this agrees with theoretical predictions. This finding helps to resolve controversies regarding the use of disequilibrium for inferring gene order. Disequilibrium mapping is unlikely to predict gene order correctly in regions < 50-60 kb in size but can often be applied successfully in regions of 50-500 kb or so in size. It is convenient that this is the range in which other mapping techniques, including chromosome walking and linkage mapping, become difficult.     

Selection of haplotype variables from a high-density marker map for genomic prediction

Background

Using haplotype blocks as predictors rather than individual single nucleotide polymorphisms (SNPs) may improve genomic predictions, since haplotypes are in stronger linkage disequilibrium with the quantitative trait loci than are individual SNPs. It has also been hypothesized that an appropriate selection of a subset of haplotype blocks can result in similar or better predictive ability than when using the whole set of haplotype blocks. This study investigated genomic prediction using a set of haplotype blocks that contained the SNPs with large effects estimated from an individual SNP prediction model. We analyzed protein yield, fertility and mastitis of Nordic Holstein cattle, and used high-density markers (about 770k SNPs). To reach an optimum number of haplotype variables for genomic prediction, predictions were performed using subsets of haplotype blocks that contained a range of 1000 to 50 000 main SNPs.

Results

The use of haplotype blocks improved the prediction reliabilities, even when selection focused on only a group of haplotype blocks. In this case, the use of haplotype blocks that contained the 20 000 to 50 000 SNPs with the highest effect was sufficient to outperform the model that used all individual SNPs as predictors (up to 1.3 % improvement in prediction reliability for mastitis, compared to individual SNP approach), and the achieved reliabilities were similar to those using all haplotype blocks available in the genome data (from 0.6 % lower to 0.8 % higher reliability).

Conclusions

Haplotype blocks used as predictors can improve the reliability of genomic prediction compared to the individual SNP model. Furthermore, the use of a subset of haplotype blocks that contains the main SNP effects from genomic data could be a feasible approach to genomic prediction in dairy cattle, given an increase in density of genotype data available. The predictive ability of the models that use a subset of haplotype blocks was similar to that obtained using either all haplotype blocks or all individual SNPs, with the benefit of having a much lower computational demand.     

An efficient haplotyping method with DNA pools

Determination of haplotype frequencies (the joint distribution of genetic markers) in large population samples is a powerful tool for association studies. This is due to their greater extent of polymorphism since any two bi-allelic single nucleotide polymorphisms (SNPs) generate a potential four-allele genetic marker. Therefore, a haplotype may capture a given functional polymorphism with higher statistical power than its SNP components. The statistical estimation of haplotype frequencies, usually employed in linkage disequilibrium studies, requires individual genotyping for each SNP in the haplotype, thus making it an expensive process. In this study, we describe a new method for direct measurement of haplotype frequencies in DNA pools by allele-specific, long-range haplotype amplification. The proposed method allows the efficient determination of haplotypes composed of two SNPs in close vicinity (up to 20 kb).     

Linkage disequilibrium and historical effective population size in the Thoroughbred horse

Many genomic methodologies rely on the presence and extent of linkage disequilibrium (LD) between markers and genetic variants underlying traits of interest, but the extent of LD in the horse has yet to be comprehensively characterized. In this study, we evaluate the extent and decay of LD in a sample of 817 Thoroughbreds. Horses were genotyped for over 50,000 single nucleotide polymorphism (SNP) markers across the genome, with 34,848 autosomal SNPs used in the final analysis. Linkage disequilibrium, as measured by the squared correlation coefficient (r(2)), was found to be relatively high between closely linked markers (>0.6 at 5 kb) and to extend over long distances, with average r(2) maintained above non-syntenic levels for single nucleotide polymorphisms (SNPs) up to 20 Mb apart. Using formulae which relate expected LD to effective population size (N(e)), and assuming a constant actual population size, N(e) was estimated to be 100 in our population. Values of historical N(e), calculated assuming linear population growth, suggested a decrease in N(e) since the distant past, reaching a minimum twenty generations ago, followed by a subsequent increase until the present time. The qualitative trends observed in N(e) can be rationalized by current knowledge of the history of the Thoroughbred breed, and inbreeding statistics obtained from published pedigree analyses are in agreement with observed values of N(e). Given the high LD observed and the small estimated N(e), genomic methodologies such as genomic selection could feasibly be applied to this population using the existing SNP marker set.     

The effect of using genealogy-based haplotypes for genomic prediction

Background

Genomic prediction uses two sources of information: linkage disequilibrium between markers and quantitative trait loci, and additive genetic relationships between individuals. One way to increase the accuracy of genomic prediction is to capture more linkage disequilibrium by regression on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information.

Methods

A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (π) of the haplotype covariates had zero effect, i.e. a Bayesian mixture method.

Results

About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some cases, decreased the bias of prediction. With the Bayesian method, accuracy of prediction was less sensitive to parameter π when fitting haplotypes compared to fitting markers.

Conclusions

Use of haplotypes based on genealogy can slightly increase the accuracy of genomic prediction. Improved methods to cluster the haplotypes constructed from local genealogy could lead to additional gains in accuracy.     

Dominant Sequences of Human Major Histocompatibility Complex Conserved Extended Haplotypes from HLA-DQA2 to DAXX

We resequenced and phased 27 kb of DNA within 580 kb of the MHC class II region in 158 population chromosomes, most of which were conserved extended haplotypes (CEHs) of European descent or contained their centromeric fragments. We determined the single nucleotide polymorphism and deletion-insertion polymorphism alleles of the dominant sequences from HLA-DQA2 to DAXX for these CEHs. Nine of 13 CEHs remained sufficiently intact to possess a dominant sequence extending at least to DAXX, 230 kb centromeric to HLA-DPB1. We identified the regions centromeric to HLA-DQB1 within which single instances of eight “common” European MHC haplotypes previously sequenced by the MHC Haplotype Project (MHP) were representative of those dominant CEH sequences. Only two MHP haplotypes had a dominant CEH sequence throughout the centromeric and extended class II region and one MHP haplotype did not represent a known European CEH anywhere in the region. We identified the centromeric recombination transition points of other MHP sequences from CEH representation to non-representation. Several CEH pairs or groups shared sequence identity in small blocks but had significantly different (although still conserved for each separate CEH) sequences in surrounding regions. These patterns partly explain strong calculated linkage disequilibrium over only short (tens to hundreds of kilobases) distances in the context of a finite number of observed megabase-length CEHs comprising half a population''s haplotypes. Our results provide a clearer picture of European CEH class II allelic structure and population haplotype architecture, improved regional CEH markers, and raise questions concerning regional recombination hotspots.     

Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction

Background

The purpose of this work was to study the impact of both the size of genomic reference populations and the inclusion of a residual polygenic effect on dairy cattle genetic evaluations enhanced with genomic information.

Methods

Direct genomic values were estimated for German Holstein cattle with a genomic BLUP model including a residual polygenic effect. A total of 17,429 genotyped Holstein bulls were evaluated using the phenotypes of 44 traits. The Interbull genomic validation test was implemented to investigate how the inclusion of a residual polygenic effect impacted genomic estimated breeding values.

Results

As the number of reference bulls increased, both the variance of the estimates of single nucleotide polymorphism effects and the reliability of the direct genomic values of selection candidates increased. Fitting a residual polygenic effect in the model resulted in less biased genome-enhanced breeding values and decreased the correlation between direct genomic values and estimated breeding values of sires in the reference population.

Conclusions

Genetic evaluation of dairy cattle enhanced with genomic information is highly effective in increasing reliability, as well as using large genomic reference populations. We found that fitting a residual polygenic effect reduced the bias in genome-enhanced breeding values, decreased the correlation between direct genomic values and sire''s estimated breeding values and made genome-enhanced breeding values more consistent in mean and variance as is the case for pedigree-based estimated breeding values.