Genomic inbreeding estimation in small populations: evaluation of runs of homozygosity in three local dairy cattle breeds

In the local breeds with small population size, one of the most important problems is the increase of inbreeding coefficient (F). High levels of inbreeding lead to reduced genetic diversity and inbreeding depression. The availability of high-density single nucleotide polymorphism (SNP) arrays has facilitated the quantification of F by genomic markers in farm animals. Runs of homozygosity (ROH) are contiguous lengths of homozygous genotypes and represent an estimate of the degree of autozygosity at genome-wide level. The current study aims to quantify the genomic F derived from ROH (F_ROH) in three local dairy cattle breeds. F_ROH values were compared with F estimated from the genomic relationship matrix (F_GRM), based on the difference between observed v. expected number of homozygous genotypes (F_HOM) and the genomic homozygosity of individual i (F_{MOL i}). The molecular coancestry coefficient (f_{MOL ij}) between individuals i and j was also estimated. Individuals of Cinisara (71), Modicana (72) and Reggiana (168) were genotyped with the 50K v2 Illumina BeadChip. Genotypes from 96 animals of Italian Holstein cattle breed were also included in the analysis. We used a definition of ROH as tracts of homozygous genotypes that were >4 Mb. Among breeds, 3661 ROH were identified. Modicana showed the highest mean number of ROH per individual and the highest value of F_ROH, whereas Reggiana showed the lowest ones. Differences among breeds existed for the ROH lengths. The individuals of Italian Holstein showed high number of short ROH segments, related to ancient consanguinity. Similar results showed the Reggiana with some extreme animals with segments covering 400 Mb and more of genome. Modicana and Cinisara showed similar results between them with the total length of ROH characterized by the presence of large segments. High correlation was found between F_HOM and F_ROH ranged from 0.83 in Reggiana to 0.95 in Cinisara and Modicana. The correlations among F_ROH and other estimated F coefficients were generally lower ranged from 0.45 (F_{MOL i}−F_ROH) in Cinisara to 0.17 (F_GRM−F_ROH) in Modicana. On the basis of our results, recent inbreeding was observed in local breeds, considering that 16 Mb segments are expected to present inbreeding up to three generations ago. Our results showed the necessity of implementing conservation programs to control the rise of inbreeding and coancestry in the three Italian local dairy cattle breeds.     

Genome‐wide variability and selection signatures in Italian island cattle breeds

In the present study, a sample of 88 animals belonging to four local (Modicana, Sarda, Sardo‐Bruna and Sardo‐Modicana) and one cosmopolitan (Italian Brown Swiss) cattle breeds were genotyped with a medium density SNP beadchip and compared to investigate their genetic diversity and the existence of selection signatures. A total of 43 012 SNPs distributed across all 29 autosomal chromosomes were retained after data quality control. Basic population statistics, Wright fixation index and runs of homozygosity (ROH) analyses confirmed that the Italian Brown Swiss genome was shaped mainly by selection, as underlined by the low values of heterozygosity and minor allele frequency. As expected, local cattle exhibited a large within‐breed genetic heterogeneity. The F_ST comparison revealing the largest number of significant SNPs was Sardo‐Bruna vs. Sardo‐Modicana, whereas the smallest was observed for Italian Brown Swiss vs. Sardo‐Modicana. Modicana exhibited the largest number of detected ROHs, whereas the smallest was observed for Sardo‐Modicana. Signatures of selection were detected in genomic regions that harbor genes involved in milk production traits for Italian Brown Swiss and fitness traits for local breeds. According to the results of multi‐dimensional scaling and the admixture analysis the Sardo‐Bruna is more similar to the Sarda than to the Italian Brown Swiss breed. Moreover, the Sardo‐Modicana is genetically closer to the Modicana than to the Sarda breed. Results of the present work confirm the usefulness of single nucleotide polymorphisms in deciphering the genetic architecture of livestock breeds.     

Preselection statistics and Random Forest classification identify population informative single nucleotide polymorphisms in cosmopolitan and autochthonous cattle breeds

Commercial single nucleotide polymorphism (SNP) arrays have been recently developed for several species and can be used to identify informative markers to differentiate breeds or populations for several downstream applications. To identify the most discriminating genetic markers among thousands of genotyped SNPs, a few statistical approaches have been proposed. In this work, we compared several methods of SNPs preselection (Delta, F_st and principal component analyses (PCA)) in addition to Random Forest classifications to analyse SNP data from six dairy cattle breeds, including cosmopolitan (Holstein, Brown and Simmental) and autochthonous Italian breeds raised in two different regions and subjected to limited or no breeding programmes (Cinisara, Modicana, raised only in Sicily and Reggiana, raised only in Emilia Romagna). From these classifications, two panels of 96 and 48 SNPs that contain the most discriminant SNPs were created for each preselection method. These panels were evaluated in terms of the ability to discriminate as a whole and breed-by-breed, as well as linkage disequilibrium within each panel. The obtained results showed that for the 48-SNP panel, the error rate increased mainly for autochthonous breeds, probably as a consequence of their admixed origin lower selection pressure and by ascertaining bias in the construction of the SNP chip. The 96-SNP panels were generally more able to discriminate all breeds. The panel derived by PCA-chrom (obtained by a preselection chromosome by chromosome) could identify informative SNPs that were particularly useful for the assignment of minor breeds that reached the lowest value of Out Of Bag error even in the Cinisara, whose value was quite high in all other panels. Moreover, this panel contained also the lowest number of SNPs in linkage disequilibrium. Several selected SNPs are located nearby genes affecting breed-specific phenotypic traits (coat colour and stature) or associated with production traits. In general, our results demonstrated the usefulness of Random Forest in combination to other reduction techniques to identify population informative SNPs.     

Genome‐wide assessment of diversity and differentiation between original and modern Brown cattle populations

Identifying genomic regions involved in the differences between breeds can provide information on genes that are under the influence of both artificial and natural selection. The aim of this study was to assess the genetic diversity and differentiation among four different Brown cattle populations (two original vs. two modern populations) and to characterize the distribution of runs of homozygosity (ROH) islands using the Illumina Bovine SNP50 BeadChip genotyping data. After quality control, 34 735 SNPs and 106 animals were retained for the analyses. Larger heterogeneity was highlighted for the original populations. Patterns of genetic differentiation, multidimensional scaling, and the neighboring joining tree distinguished the modern from the original populations. The F_ST‐outlier identified several genes putatively involved in the genetic differentiation between the two groups, such as stature and growth, behavior, and adaptability to local environments. The ROH islands within both the original and the modern populations overlapped with QTL associated with relevant traits. In modern Brown (Brown Swiss and Italian Brown), ROH islands harbored candidate genes associated with milk production traits, in evident agreement with the artificial selection conducted to improve this trait in these populations. In original Brown (Original Braunvieh and Braunvieh), we identified candidate genes related with fat deposition, confirming that breeding strategies for the original Brown populations aimed to produce dual‐purpose animals. Our study highlighted the presence of several genomic regions that vary between Brown populations, in line with their different breeding histories.     

Comparative selection signature analyses identify genomic footprints in Reggiana cattle,the traditional breed of the Parmigiano-Reggiano cheese production system

Reggiana is an autochthonous cattle breed reared mainly in the province of Reggio Emilia, located in the North of Italy. Reggiana cattle (originally a triple-purpose population largely diffused in the North of Italy) are characterised by a typical solid red coat colour. About 2500 cows of this breed are currently registered to its herd book. Reggiana is now considered a dual-purpose breed even if it is almost completely dedicated to the production of a mono-breed branded Protected Designation of Origin Parmigiano-Reggiano cheese, which is the main driver of the sustainable conservation of this local genetic resource. In this study, we provided the first overview of genomic footprints that characterise Reggiana and define the diversity of this local cattle breed. A total of 168 Reggiana sires (all bulls born over 35 years for which semen was available) and other 3321 sires from 3 cosmopolitan breeds (Brown, Holstein and Simmental) were genotyped with the Illumina BovineSNP50 panel. ADMIXTURE analysis suggested that Reggiana breed might have been influenced, at least in part, by the other three breeds included in this study. Selection signatures in the Reggiana genome were identified using three statistical approaches based on allele frequency differences among populations or on properties of haplotypes segregating in the populations (fixation index (F_ST); integrated haplotype score; cross-population extended haplotype homozygosity). We identified several regions under peculiar selection in the Reggiana breed, particularly on bovine chromosome (BTA) 6 in the KIT gene region, that is known to be involved in coat colour pattern distribution, and within the region of the LAP3, NCAPG and LCORL genes, that are associated with stature, conformation and carcass traits. Another already known region that includes the PLAG1 gene (BTA14), associated with conformation traits, showed a selection signature in the Reggiana cattle. On BTA18, a signal of selection included the MC1R gene that causes the red coat colour in cattle. Other selection sweeps were in regions, with high density of quantitative trait loci for milk production traits (on BTA20) and in several other large regions that might have contributed to shape and define the Reggiana genome (on BTA17 and BTA29). All these results, overall, indicate that the Reggiana genome might still contain several signs of its multipurpose and non-specialised utilisation, as already described for other local cattle populations, in addition to footprints derived by its ancestral origin and by its adaptation to the specialised Parmigiano-Reggiano cheese production system.     

Runs of homozygosity reveal genome‐wide autozygosity in Italian sheep breeds

The availability of dense single nucleotide polymorphism (SNP) assays allows for the determination of autozygous segments based on runs of consecutive homozygous genotypes (ROH). The aim of the present study was to investigate the occurrence and distribution of ROH in 21 Italian sheep breeds using medium‐density SNP genotypes in order to characterize autozygosity and identify genomic regions that frequently appeared in ROH within individuals, namely ROH islands. After filtering, the final number of animals and SNPs retained for analyses were 502 and 46 277 respectively. A total of 12 302 ROH were identified. The mean number of ROH per breed ranged from 10.58 (Comisana) to 44.54 (Valle del Belice). The average length of ROH across breeds was 4.55 Mb and ranged from 3.85 Mb (Biellese) to 5.51 Mb (Leccese). Valle del Belice showed the highest value of inbreeding on the basis of ROH (F_ROH = 0.099), whereas Comisana showed the lowest (F_ROH = 0.016), and high standard deviation values revealed high variability in autozygosity levels within each breed. Differences also existed in the length of ROH. Analysis of the distribution of ROH according to their size showed that, for all breeds, the majority of the detected ROH were <10 Mb in length, with a few long ROH >25 Mb. The levels of ROH that we estimated here reflect the inbreeding history of the investigated sheep breeds. These results also highlight that ancient and recent inbreeding have had an impact on the genome of the Italian sheep breeds and suggest that several animals have experienced recent autozygosity events. Comisana and Bergamasca appeared as the less consanguineous breeds, whereas Barbaresca, Leccese and Valle del Belice showed ROH patterns typically produced by recent inbreeding. Moreover, within the genomic regions most commonly associated with ROH, several candidate genes were detected.     

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.     

Analysis of runs of homozygosity and their relationship with inbreeding in five cattle breeds farmed in Italy

Increased inbreeding is an inevitable consequence of selection in livestock populations. The analysis of high‐density single nucleotide polymorphisms (SNPs) facilitates the identification of long and uninterrupted runs of homozygosity (ROH) that can be used to identify chromosomal regions that are identical by descent. In this work, the distribution of ROH of different lengths in five Italian cattle breeds is described. A total of 4095 bulls from five cattle breeds (2093 Italian Holstein, 749 Italian Brown, 364 Piedmontese, 410 Marchigiana and 479 Italian Simmental) were genotyped at 54K SNP loci. ROH were identified and used to estimate molecular inbreeding coefficients (F_ROH), which were compared with inbreeding coefficients estimated from pedigree information (F_PED) and using the genomic relationship matrix (F_GRM). The average number of ROH per animal ranged from 54 ± 7.2 in Piedmontese to 94.6 ± 11.6 in Italian Brown. The highest number of short ROH (related to ancient consanguinity) was found in Piedmontese, followed by Simmental. The Italian Brown and Holstein had a higher proportion of longer ROH distributed across the whole genome, revealing recent inbreeding. The F_PED were moderately correlated with F_ROH > 1 Mb (0.662, 0.700 and 0.669 in Italian Brown, Italian Holstein and Italian Simmental respectively) but poorly correlated with F_GRM (0.134, 0.128 and 0.448 for Italian Brown, Italian Holstein and Italian Simmental respectively). The inclusion of ROH > 8 Mb in the inbreeding calculation improved the correlation of F_ROH with F_PED and F_GRM. ROH are a direct measure of autozygosity at the DNA level and can overcome approximations and errors resulting from incomplete pedigree data. In populations with high linkage disequilibrium (LD) and recent inbreeding (e.g. Italian Holstein and Italian Brown), a medium‐density marker panel, such as the one used here, may provide a good estimate of inbreeding. However, in populations with low LD and ancient inbreeding, marker density would have to be increased to identify short ROH that are identical by descent more precisely.     

Searching new signals for production traits through gene‐based association analysis in three Italian cattle breeds

Genome‐wide association studies (GWAS) have been widely applied to disentangle the genetic basis of complex traits. In cattle breeds, classical GWAS approaches with medium‐density marker panels are far from conclusive, especially for complex traits. This is due to the intrinsic limitations of GWAS and the assumptions that are made to step from the association signals to the functional variations. Here, we applied a gene‐based strategy to prioritize genotype–phenotype associations found for milk production and quality traits with classical approaches in three Italian dairy cattle breeds with different sample sizes (Italian Brown n = 745; Italian Holstein n = 2058; Italian Simmental n = 477). Although classical regression on single markers revealed only a single genome‐wide significant genotype–phenotype association, for Italian Holstein, the gene‐based approach identified specific genes in each breed that are associated with milk physiology and mammary gland development. As no standard method has yet been established to step from variation to functional units (i.e., genes), the strategy proposed here may contribute to revealing new genes that play significant roles in complex traits, such as those investigated here, amplifying low association signals using a gene‐centric approach.     

Genomic characterization of Pinzgau cattle: genetic conservation and breeding perspectives

A genome-wide scan of Slovak Pinzgau cattle was prepared for the first time in order to estimate their genetic diversity at a more detailed level compared to previously published studies. The aim of this study was to describe the genetic diversity based on the runs of homozygosity (ROH_s), linkage disequilibrium (LD) and effective population size (N_eLD) using genome-wide data. Moreover, Bayesian clustering algorithms and multivariate methods were used to detect the population structure, potential admixture level and relationship between Austrian and Slovak Pinzgau cattle with respect to a large meta-population consisting of 15 European cattle breeds. The proportion of ROH segments ranged from 0.43 to 1.91% in Slovak Pinzgau, depending on the minimum size of an ROH. The genomic inbreeding coefficients were higher than the pedigree ones possibly due to the limited number of available generations in pedigree data. The observed N_eLD was close to the limit value characterizing the endangerment status, based both on genomic and pedigree data. Population structure within analyzed breeds based on the Wright’s F_ST index, Nei’s genetic distances, and unsupervised as well as supervised analysis has been established. Overall, these analyses clearly distinguished populations based on their origin. A detailed analysis of the introgression of each breed into the Pinzgau breeds prepared using a Bayesian approach showed that the contribution of Holstein cattle in Austrian as well as Slovak Pinzgau was larger than contribution of beef breeds. A possible reason is the recent usage of Holstein sires to increase milk production. There are considerable differences between well-defined regions that clearly distinguish Austrian and Slovak Pinzgau, despite their close common history. Generally, the breeding program of Austrian Pinzgau is more focused on meat production than Slovak Pinzgau, which was clearly reflected in the obtained autozygosity islands. Considering the genetic establishment of Slovak Pinzgau population the genetic potential of the breed is insufficiently used. On a long term, more global breeding program including very close populations will be more efficient providing higher genetic progress and diversity. Established methodology how to distinguish genealogically close populations on high-throughput molecular information based of Slovak and Austrian Pinzgau can be proposed as general for analysis of differences in all highly related breeds.     

Identification of genomic regions associated with inbreeding depression in Holstein and Jersey dairy cattle

Background

Inbreeding reduces the fitness of individuals by increasing the frequency of homozygous deleterious recessive alleles. Some insight into the genetic architecture of fitness, and other complex traits, can be gained by using single nucleotide polymorphism (SNP) data to identify regions of the genome which lead to reduction in performance when identical by descent (IBD). Here, we compared the effect of genome-wide and location-specific homozygosity on fertility and milk production traits in dairy cattle.

Methods

Genotype data from more than 43 000 SNPs were available for 8853 Holstein and 4138 Jersey dairy cows that were part of a much larger dataset that had pedigree records (338 696 Holstein and 64 049 Jersey animals). Measures of inbreeding were based on: (1) pedigree data; (2) genotypes to determine the realised proportion of the genome that is IBD; (3) the proportion of the total genome that is homozygous and (4) runs of homozygosity (ROH) which are stretches of the genome that are homozygous.

Results

A 1% increase in inbreeding based either on pedigree or genomic data was associated with a decrease in milk, fat and protein yields of around 0.4 to 0.6% of the phenotypic mean, and an increase in calving interval (i.e. a deterioration in fertility) of 0.02 to 0.05% of the phenotypic mean. A genome-wide association study using ROH of more than 50 SNPs revealed genomic regions that resulted in depression of up to 12.5 d and 260 L for calving interval and milk yield, respectively, when completely homozygous.

Conclusions

Genomic measures can be used instead of pedigree-based inbreeding to estimate inbreeding depression. Both the diagonal elements of the genomic relationship matrix and the proportion of homozygous SNPs can be used to measure inbreeding. Longer ROH (>3 Mb) were found to be associated with a reduction in milk yield and captured recent inbreeding independently and in addition to overall homozygosity. Inbreeding depression can be reduced by minimizing overall inbreeding but maybe also by avoiding the production of offspring that are homozygous for deleterious alleles at specific genomic regions that are associated with inbreeding depression.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-014-0071-7) contains supplementary material, which is available to authorized users.     

Application of Selection Mapping to Identify Genomic Regions Associated with Dairy Production in Sheep

In Europe, especially in Mediterranean areas, the sheep has been traditionally exploited as a dual purpose species, with income from both meat and milk. Modernization of husbandry methods and the establishment of breeding schemes focused on milk production have led to the development of “dairy breeds.” This study investigated selective sweeps specifically related to dairy production in sheep by searching for regions commonly identified in different European dairy breeds. With this aim, genotypes from 44,545 SNP markers covering the sheep autosomes were analysed in both European dairy and non-dairy sheep breeds using two approaches: (i) identification of genomic regions showing extreme genetic differentiation between each dairy breed and a closely related non-dairy breed, and (ii) identification of regions with reduced variation (heterozygosity) in the dairy breeds using two methods. Regions detected in at least two breeds (breed pairs) by the two approaches (genetic differentiation and at least one of the heterozygosity-based analyses) were labeled as core candidate convergence regions and further investigated for candidate genes. Following this approach six regions were detected. For some of them, strong candidate genes have been proposed (e.g. ABCG2, SPP1), whereas some other genes designated as candidates based on their association with sheep and cattle dairy traits (e.g. LALBA, DGAT1A) were not associated with a detectable sweep signal. Few of the identified regions were coincident with QTL previously reported in sheep, although many of them corresponded to orthologous regions in cattle where QTL for dairy traits have been identified. Due to the limited number of QTL studies reported in sheep compared with cattle, the results illustrate the potential value of selection mapping to identify genomic regions associated with dairy traits in sheep.     

Whole-Genome Analyses of Korean Native and Holstein Cattle Breeds by Massively Parallel Sequencing

A main goal of cattle genomics is to identify DNA differences that account for variations in economically important traits. In this study, we performed whole-genome analyses of three important cattle breeds in Korea—Hanwoo, Jeju Heugu, and Korean Holstein—using the Illumina HiSeq 2000 sequencing platform. We achieved 25.5-, 29.6-, and 29.5-fold coverage of the Hanwoo, Jeju Heugu, and Korean Holstein genomes, respectively, and identified a total of 10.4 million single nucleotide polymorphisms (SNPs), of which 54.12% were found to be novel. We also detected 1,063,267 insertions–deletions (InDels) across the genomes (78.92% novel). Annotations of the datasets identified a total of 31,503 nonsynonymous SNPs and 859 frameshift InDels that could affect phenotypic variations in traits of interest. Furthermore, genome-wide copy number variation regions (CNVRs) were detected by comparing the Hanwoo, Jeju Heugu, and previously published Chikso genomes against that of Korean Holstein. A total of 992, 284, and 1881 CNVRs, respectively, were detected throughout the genome. Moreover, 53, 65, 45, and 82 putative regions of homozygosity (ROH) were identified in Hanwoo, Jeju Heugu, Chikso, and Korean Holstein respectively. The results of this study provide a valuable foundation for further investigations to dissect the molecular mechanisms underlying variation in economically important traits in cattle and to develop genetic markers for use in cattle breeding.     

Runs of homozygosity and distribution of functional variants in the cattle genome

Background

Recent developments in sequencing technology have facilitated widespread investigations of genomic variants, including continuous stretches of homozygous genomic regions. For cattle, a large proportion of these runs of homozygosity (ROH) are likely the result of inbreeding due to the accumulation of elite alleles from long-term selective breeding programs. In the present study, ROH were characterized in four cattle breeds with whole genome sequence data and the distribution of predicted functional variants was detected in ROH regions and across different ROH length classes.

Results

On average, 19.5 % of the genome was located in ROH across four cattle breeds. There were an average of 715.5 ROH per genome with an average size of ~750 kbp, ranging from 10 (minimum size considered) to 49,290 kbp. There was a significant correlation between shared short ROH regions and regions putatively under selection (p < 0.001). By investigating the relationship between ROH and the predicted deleterious and non-deleterious variants, we gained insight into the distribution of functional variation in inbred (ROH) regions. Predicted deleterious variants were more enriched in ROH regions than predicted non-deleterious variants, which is consistent with observations in the human genome. We also found that increased enrichment of deleterious variants was significantly higher in short (<100 kbp) and medium (0.1 to 3 Mbp) ROH regions compared with long (>3 Mbp) ROH regions (P < 0.001), which is different than what has been observed in the human genome.

Conclusions

This study illustrates the distribution of ROH and functional variants within ROH in cattle populations. These patterns are different from those in the human genome but consistent with the natural history of cattle populations, which is confirmed by the significant correlation between shared short ROH regions and regions putatively under selection. These findings contribute to understanding the effects of inbreeding and probably selection in shaping the distribution of functional variants in the cattle genome.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1715-x) contains supplementary material, which is available to authorized users.     

The Genome Response to Artificial Selection: A Case Study in Dairy Cattle

Dairy cattle breeds have been subjected over the last fifty years to intense artificial selection towards improvement of milk production traits. In this study, we performed a whole genome scan for differentiation using 42,486 SNPs in the three major French dairy cattle breeds (Holstein, Normande and Montbéliarde) to identify the main physiological pathways and regions which were affected by this selection. After analyzing the population structure, we estimated F_ST within and across the three breeds for each SNP under a pure drift model. We further considered two different strategies to evaluate the effect of selection at the genome level. First, smoothing F_ST values over each chromosome with a local variable bandwidth kernel estimator allowed identifying 13 highly significant regions subjected to strong and/or recent positive selection. Some of them contained genes within which causal variants with strong effect on milk production traits (GHR) or coloration (MC1R) have already been reported. To go further in the interpretation of the observed signatures of selection we subsequently concentrated on the annotation of differentiated genes defined according to the F_ST value of SNPs localized close or within them. To that end we performed a comprehensive network analysis which suggested a central role of somatotropic and gonadotropic axes in the response to selection. Altogether, these observations shed light on the antagonism, at the genome level, between milk production and reproduction traits in highly producing dairy cows.     

Signatures of selection in five Italian cattle breeds detected by a 54K SNP panel

In this study we used a medium density panel of SNP markers to perform population genetic analysis in five Italian cattle breeds. The BovineSNP50 BeadChip was used to genotype a total of 2,935 bulls of Piedmontese, Marchigiana, Italian Holstein, Italian Brown and Italian Pezzata Rossa breeds. To determine a genome-wide pattern of positive selection we mapped the F _st values against genome location. The highest F _st peaks were obtained on BTA6 and BTA13 where some candidate genes are located. We identified selection signatures peculiar of each breed which suggest selection for genes involved in milk or meat traits. The genetic structure was investigated by using a multidimensional scaling of the genetic distance matrix and a Bayesian approach implemented in the STRUCTURE software. The genotyping data showed a clear partitioning of the cattle genetic diversity into distinct breeds if a number of clusters equal to the number of populations were given. Assuming a lower number of clusters beef breeds group together. Both methods showed all five breeds separated in well defined clusters and the Bayesian approach assigned individuals to the breed of origin. The work is of interest not only because it enriches the knowledge on the process of evolution but also because the results generated could have implications for selective breeding programs.     

Effect of Artificial Selection on Runs of Homozygosity in U.S. Holstein Cattle

The intensive selection programs for milk made possible by mass artificial insemination increased the similarity among the genomes of North American (NA) Holsteins tremendously since the 1960s. This migration of elite alleles has caused certain regions of the genome to have runs of homozygosity (ROH) occasionally spanning millions of continuous base pairs at a specific locus. In this study, genome signatures of artificial selection in NA Holsteins born between 1953 and 2008 were identified by comparing changes in ROH between three distinct groups under different selective pressure for milk production. The ROH regions were also used to estimate the inbreeding coefficients. The comparisons of genomic autozygosity between groups selected or unselected since 1964 for milk production revealed significant differences with respect to overall ROH frequency and distribution. These results indicate selection has increased overall autozygosity across the genome, whereas the autozygosity in an unselected line has not changed significantly across most of the chromosomes. In addition, ROH distribution was more variable across the genomes of selected animals in comparison to a more even ROH distribution for unselected animals. Further analysis of genome-wide autozygosity changes and the association between traits and haplotypes identified more than 40 genomic regions under selection on several chromosomes (Chr) including Chr 2, 7, 16 and 20. Many of these selection signatures corresponded to quantitative trait loci for milk, fat, and protein yield previously found in contemporary Holsteins.     

Improved precision of QTL mapping using a nonlinear Bayesian method in a multi-breed population leads to greater accuracy of across-breed genomic predictions

Background

Genomic selection is increasingly widely practised, particularly in dairy cattle. However, the accuracy of current predictions using GBLUP (genomic best linear unbiased prediction) decays rapidly across generations, and also as selection candidates become less related to the reference population. This is likely caused by the effects of causative mutations being dispersed across many SNPs (single nucleotide polymorphisms) that span large genomic intervals. In this paper, we hypothesise that the use of a nonlinear method (BayesR), combined with a multi-breed (Holstein/Jersey) reference population will map causative mutations with more precision than GBLUP and this, in turn, will increase the accuracy of genomic predictions for selection candidates that are less related to the reference animals.

Results

BayesR improved the across-breed prediction accuracy for Australian Red dairy cattle for five milk yield and composition traits by an average of 7% over the GBLUP approach (Australian Red animals were not included in the reference population). Using the multi-breed reference population with BayesR improved accuracy of prediction in Australian Red cattle by 2 – 5% compared to using BayesR with a single breed reference population. Inclusion of 8478 Holstein and 3917 Jersey cows in the reference population improved accuracy of predictions for these breeds by 4 and 5%. However, predictions for Holstein and Jersey cattle were similar using within-breed and multi-breed reference populations. We propose that the improvement in across-breed prediction achieved by BayesR with the multi-breed reference population is due to more precise mapping of quantitative trait loci (QTL), which was demonstrated for several regions. New candidate genes with functional links to milk synthesis were identified using differential gene expression in the mammary gland.

Conclusions

QTL detection and genomic prediction are usually considered independently but persistence of genomic prediction accuracies across breeds requires accurate estimation of QTL effects. We show that accuracy of across-breed genomic predictions was higher with BayesR than with GBLUP and that BayesR mapped QTL more precisely. Further improvements of across-breed accuracy of genomic predictions and QTL mapping could be achieved by increasing the size of the reference population, including more breeds, and possibly by exploiting pleiotropic effects to improve mapping efficiency for QTL with small effects.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-014-0074-4) contains supplementary material, which is available to authorized users.