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Signatures of contemporary selection in the Israeli Holstein dairy cattle

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Abstract

Strong selection in the Israeli Holstein dairy cattle population over the last three decades should have left clear signatures of selection. Two experimental approaches were applied to detect evidence of contemporary selection based on the 54K BeadChip genotypes of ~1000 Israeli Holstein bulls: (i) the long-range haplotype test, which searches for structural evidence resulting from selective sweep, and (ii) direct analysis of the changes in haplotypes frequencies over time combined with linkage disequilibrium blocks haplotype-based association analysis. Ten traits were analyzed: the PD07 Israeli selection index, milk, milk fat, % fat, milk protein, % protein, somatic cell score, female fertility, milk production persistency and herd life. The long-range haplotype test detected ~15% of the 3288 haplotypes that showed significant positive frequency trends (P < 0.05) and was significantly correlated with the substitution effects of the haplotypes and the selection intensities for the different traits. Thirty signatures of recent selection, which correspond to both approaches and affect the Israeli PD07 selection index, were identified on 17 of the 29 autosomes. The second experimental approach also was used to estimate the selection intensity of the different traits. The correlation between the selection intensities for the traits analyzed, derived from changes in haplotype frequencies in the population of bulls, and those derived from trait-based analysis of the cow population was 0.93 over all traits. Thus, the changes in haplotypes frequencies in the bulls' population accurately estimate genetic trends in the general cow population and can be used to detect signatures of recent selection.

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... Depending on the number of breeds analyzed, we classify the studies as those that focus on: (i) a single breed (Qanbari et al., 2010(Qanbari et al., , 2014Glick et al., 2012;Boitard and Rocha, 2013;Lee et al., 2013b;Lim et al., 2013;Pan et al., 2013); (ii) a pair-wise comparison of closely-related populations with divergent production characteristics (mostly beef vs. dairy breeds, e.g., Hayes et al., 2009;Wiener et al., 2011;Hosokawa et al., 2012;Pintus et al., 2014) and (iii) several breeds, from three ) to 19 breeds (Bovine HapMap Consortium, 2009), of the same or different production characteristics, and for which both across-and within-population analyses are performed. Overall, the selection sweeps considered in this review involved 37 breeds (including 17 beef breeds, 14 dairy breeds, and six dual-purpose breeds), and four different beef-vs.-dairy ...
... The reports reviewed here have applied different but complementary statistics to detect selection signatures (Table 1). We classify the studies in the following categories: (i) studies that have estimated differences in allele frequencies by contrasting pair of breeds through F ST (or related statistics) or by differences in allelic frequencies Hayes et al., 2009;Wiener et al., 2011;Hosokawa et al., 2012;Mancini et al., 2014;Pintus et al., 2014;Porto-Neto et al., 2014; the across-breed results of Stella et al., 2010); (ii) studies based on extended regions of low diversity or the calculation of extended haplotype homozygosity (EHH) or variants of this statistic such as Relative Extended Haplotype Homozygosity (REHH), the long-range haplotype (LRH) test, and integrated Haplotype Homozygosity Score (iHS) (Qanbari et al., 2010;Glick et al., 2012;Lim et al., 2013;Pan et al., 2013;Ramey et al., 2013;Rothammer et al., 2013); and (iii) studies based on the allele frequency spectrum, in which regions with outlying allele frequency patterns within (Boitard and Rocha, 2013;Druet et al., 2013; the withinbreed results of Stella et al., 2010). The studies based on F ST and related statistics (category i) detect diversifying selection between breeds. ...
... Glick et al., 2012 ...
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This review compiles the results of 21 genomic studies of European Bos taurus breeds and thus provides a general picture of the selection signatures in taurine cattle identified by genome-wide selection-mapping scans. By performing a comprehensive summary of the results reported in the literature, we compiled a list of 1049 selection sweeps described across 37 cattle breeds (17 beef breeds, 14 dairy breeds, and 6 dual-purpose breeds), and four different beef-vs.-dairy comparisons, which we subsequently grouped into core selective sweep (CSS) regions, defined as consecutive signals within 1 Mb of each other. We defined a total of 409 CSSs across the 29 bovine autosomes, 232 (57%) of which were associated with a single-breed (Single-breed CSSs), 134 CSSs (33%) were associated with a limited number of breeds (Two-to-Four-breed CSSs) and 39 CSSs (9%) were associated with five or more breeds (Multi-breed CSSs). For each CSS, we performed a candidate gene survey that identified 291 genes within the CSS intervals (from the total list of 5183 BioMart-extracted genes) linked to dairy and meat production, stature, and coat color traits. A complementary functional enrichment analysis of the CSS positional candidates highlighted other genes related to pathways underlying behavior, immune response, and reproductive traits. The Single-breed CSSs revealed an over-representation of genes related to dairy and beef production, this was further supported by over-representation of production-related pathway terms in these regions based on a functional enrichment analysis. Overall, this review provides a comparative map of the selection sweeps reported in European cattle breeds and presents for the first time a characterization of the selection sweeps that are found in individual breeds. Based on their uniqueness, these breed-specific signals could be considered as "divergence signals," which may be useful in characterizing and protecting livestock genetic diversity.
... Therefore, core haplotypes with extreme P-values in the distribution, that is, − Log10 (P) higher than 2 (P <0.01), were considered to be significant. However, according to Glick et al. (2012), REHH can serve as evidence of recent selection only for haplotypes present at relatively high frequency in the population. As a consequence, only core haplotypes with a frequency ⩾0.25 were considered to be relevant, since inferior values could be indicative of recombination events (Sabeti et al., 2002). ...
... In general, the authors found high values of LD and slow decay of haplotype homozygosity, indicating the validity of the approach for the identification of selection signatures. Glick et al. (2012) used the LRH test together with direct analysis of changes in haplotype frequencies over time to provide evidence of selection in a population of Holstein-Israeli cattle. The positive correlation of 0.34 between the two approaches demonstrated that the LRH test was able to detect haplotypes that suffered significant and recent changes in their frequency, indicating signatures of selection. ...
... The larger number of regions indicative of positive selection identified by these authors, who used an SNP chip of the same density and the same significance criteria for the REHH test as in the present study, suggests more diverse (for different economically important traits) and intense selection in dairy cattle when compared with Quarter Horse racing, one of the most recently domesticated large animal species (Aberle and Distl, 2004). According to Glick et al. (2012), an increase of selection intensity should result in changes in the number of loci that respond to selection and faster changes in haplotype frequencies which, in turn, increase REHH values. For better visualization of the distribution of putative selection signatures across the genome, the transformed P-values of the REHH test were plotted against the position of the haplotypes on the ECA (Figure 1). ...
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Selection of Quarter Horses for different purposes has led to the formation of lines, including racing and cutting horses. The objective of this study was to identify genomic regions divergently selected in racing line of Quarter Horses in relation to cutting line applying relative extended haplotype homozygosity (REHH) analysis, an extension of extended haplotype homozygosity (EHH) analysis, and the fixation index (F ST) statistic. A total of 188 horses of both sexes, born between 1985 and 2009 and registered at the Brazilian Association of Quarter Horse Breeders, including 120 of the racing line and 68 of the cutting line, were genotyped using single nucleotide polymorphism arrays. On the basis of 27 genomic regions identified as selection signatures by REHH and F ST statistics, functional annotations of genes were made in order to identify those that could have been important during formation of the racing line and that could be used subsequently for the development of selection tools. Genes involved in muscle growth (n=8), skeletal growth (n=10), muscle energy metabolism (n=15), cardiovascular system (n=14) and nervous system (n=23) were identified, including the FKTN, INSR, GYS1, CLCN1, MYLK, SYK, ANG, CNTFR and HTR2B.
... Nonetheless, it is likely that some of the apparent selection signatures detected in our study may represent false positive results. However, since many of the selection signatures that we detected are consistent with other reports on selection signatures in independent cattle populations [9,34,[37][38][39][40][41] and since, overall, they confirm the results of genome-wide association studies for the same traits [42][43][44], we consider that the number of false positive results in our study is small. Applying a stricter FDR would inevitably reduce the number of true positive selection signatures detected. ...
... Genome-wide analyses of selection signatures were reported for several international Holstein populations including Chinese [37], German [9,34] and Israeli [40] Holsteins. Several of the genes that we identified here confirm previously documented selection signatures in Holstein cattle populations, such as ACTC1 [9], FABP3 [34], RORA [34], GHR [34] and LACTB [34]. ...
... Of particular interest is the region on BTA20 that was detected by the iHS method as having a strong selection signature in Holstein-Friesian cattle (Fig. 1) and [See Additional file: 2 Figure S2]. This result confirms selection signatures reported in a population of Israeli Holstein cows [40] and to a lesser extent in German Holstein cows [34]. This region on BTA20 between 20 and 40 Mb harbors many genes including GDNF, WDR70, NUP155, GHR, ITGA2, LOC100847619, ITGA1, PELO, NDUFS4, FST, LOC100847646, LOC782165, MOCS2, ITGA2, NIM1, ZNF131, LOC100848437, LOC100336494, LOC785615, LOC785744, LOC100139184, LOC100848479, LOC783463, LOC527137, SEPP1, CCDC152, LOC100848533, PARP8, EMB and LOC785429. ...
Article
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Artificial selection for economically important traits in cattle is expected to have left distinctive selection signatures on the genome. Access to high-density genotypes facilitates the accurate identification of genomic regions that have undergone positive selection. These findings help to better elucidate the mechanisms of selection and to identify candidate genes of interest to breeding programs. Information on 705 243 autosomal single nucleotide polymorphisms (SNPs) in 3122 dairy and beef male animals from seven cattle breeds (Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental) were used to detect selection signatures by applying two complementary methods, integrated haplotype score (iHS) and global fixation index (FST). To control for false positive results, we used false discovery rate (FDR) adjustment to calculate adjusted iHS within each breed and the genome-wide significance level was about 0.003. Using the iHS method, 83, 92, 91, 101, 85, 101 and 86 significant genomic regions were detected for Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental cattle, respectively. None of these regions was common to all seven breeds. Using the FST approach, 704 individual SNPs were detected across breeds. Annotation of the regions of the genome that showed selection signatures revealed several interesting candidate genes i.e. DGAT1, ABCG2, MSTN, CAPN3, FABP3, CHCHD7, PLAG1, JAZF1, PRKG2, ACTC1, TBC1D1, GHR, BMP2, TSG1, LYN, KIT and MC1R that play a role in milk production, reproduction, body size, muscle formation or coat color. Fifty-seven common candidate genes were found by both the iHS and global FST methods across the seven breeds. Moreover, many novel genomic regions and genes were detected within the regions that showed selection signatures; for some candidate genes, signatures of positive selection exist in the human genome. Multilevel bioinformatic analyses of the detected candidate genes suggested that the PPAR pathway may have been subjected to positive selection. This study provides a high-resolution bovine genomic map of positive selection signatures that are either specific to one breed or common to a subset of the seven breeds analyzed. Our results will contribute to the detection of functional candidate genes that have undergone positive selection in future studies.
... A possible explanation is that linkage relationships and the segregating quantitative trait loci change over time (Moser et al., 2009). Glick et al. (2012) found that out of the15,485 haplotypes with population frequencies between 5% and 95% in the population of Israeli Holstein bulls born since 1984, 930 haplotypes (6%) underwent significant changes in allelic frequencies, resulting in frequencies of either <10% or >90% for the bulls born between 2004 and 2008. ...
... Thus both the GEBV and PA detected the same QTL. However, as noted previously (Glick et al., 2012) the QTL segregating in the validation bulls are not the same as those segregating in the training population. In order to improve GEBV, it is necessary to include markers linked to QTL that are not segregating in the training set. ...
Article
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Several studies have shown that computation of genomic estimated breeding values (GEBV) with accuracies significantly greater than parent average (PA) estimated breeding values (EBVs) requires genotyping of at least several thousand progeny-tested bulls. For all published analyses, GEBV computed from the selected samples of markers have lower or equal accuracy than GEBV derived on the basis of all valid single nucleotide polymorphisms (SNPs). In the current study, we report on four new methods for selection of markers. Milk, fat, protein, somatic cell score, fertility, persistency, herd life and the Israeli selection index were analyzed. The 972 Israeli Holstein bulls genotyped with EBV for milk production traits computed from daughter records in 2012 were assigned into a training set of 844 bulls with progeny test EBV in 2008, and a validation set of 128 young bulls. Numbers of bulls in the two sets varied slightly among the nonproduction traits. In EFF12, SNPs were first selected for each trait based on the effects of each marker on the bulls' 2012 EBV corrected for effective relationships, as determined by the SNP matrix. EFF08 was the same as EFF12, except that the SNPs were selected on the basis of the 2008 EBV. In DIFmax, the SNPs with the greatest differences in allelic frequency between the bulls in the training and validation sets were selected, whereas in DIFmin the SNPs with the smallest differences were selected. For all methods, the numbers of SNPs retained varied over the range of 300 to 6000. For each trait, except fertility, an optimum number of markers between 800 and 5000 was obtained for EFF12, based on the correlation between the GEBV and current EBV of the validation bulls. For all traits, the difference between the correlation of GEBV and current EBV and the correlation of the PA and current EBV was >0.25. EFF08 was inferior to EFF12, and was generally no better than PA EBV. DIFmax always outperformed DIFmin and generally outperformed EFF08 and PA. Furthermore, GEBV based on DIFmax were generally less biased than PA. It is likely that other methods of SNP selection could improve upon these results.
... It was expected that the genomic autozygosity in this latter group would be significantly lower than animals under selection, and thus present a unique opportunity to characterize ROH status and distribution due to breed development prior to the intense selection for milk that took place in the latter half of the 20 th century. This within breed comparison of genome autozygosity differs considerably from previous reports using a more contemporary sampling of elite commercial Holstein sires outside of NA to find selection signatures [16,17]. In addition, the two groups under selection in this study were produced in different environments, but had substantial overlap in ancestry due to common AI sires used to boost milk production. ...
... Signatures of selection have been identified using many different methods in diverse cattle breeds [15,[31][32][33][34], whereas, only a few studies focused on selection occurring during the last few decades in cattle [15,17]. The high-ROH genomic regions in NA Holsteins were consistent with signatures of selection detected by EHH with high core haplotype frequency (>0.25) in German Holsteins [16]. ...
Article
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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.
... To identify genomic regions corresponding to natural selection, new approaches have been suggested using large scale genetic markers (Nielsen et al., 2007). In Holstein cattle, signatures of artificial selection have been identified by examining the decay of extended haplotype homozygosity (EHH) (Qanbari et al., 2010; Elferink et al., 2012; Glick et al., 2012) or F ST (Barendse et al., 2009; Flori et al., 2009 ) with other cattle breeds. Common signatures of selection have been reported in Holstein-Friesians and those are expected to be detected in addition to the unique signatures of selection in cattle sampled from East Africa. ...
... Indeed, the pattern of the most frequent haplotype resembles greatly that found in Holsteins and Friesians, except two regions on BTA 10 and 13. The selection signature on BTA 10 was reported in German, Dutch, and U.S. Holsteins (Qanbari et al., 2010; Elferink et al., 2012; Kim et al., 2013), but not in Israeli Friesians (Glick et al., 2012). The frequency of the most common haplotype at 30 Mb on BTA 13 has increased during the last few decades in the U.S. Holsteins, and was associated with milk yield (Kim et al., 2013 ). ...
Article
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Dairy cattle in East Africa imported from the U.S. and Europe have been adapted to new environments. In small local farms, cattle have generally been maintained by crossbreeding that could increase survivability under a severe environment. Eventually, genomic ancestry of a specific breed will be nearly fixed in genomic regions of local breeds or crossbreds when it is advantageous for survival or production in harsh environments. To examine this situation, 25 Friesians and 162 local cattle produced by crossbreeding of dairy breeds in Kenya were sampled and genotyped using 50K SNPs. Using principal component analysis, the admixed local cattle were found to consist of several imported breeds, including Guernsey, Norwegian Red, and Holstein. To infer the influence of parental breeds on genomic regions, local ancestry mapping was performed based on the similarity of haplotypes. As a consequence, it appears that no genomic region has been under the complete influence of a specific parental breed. Nonetheless, the ancestry of Holstein-Friesians was substantial in most genomic regions (>80%). Furthermore, we examined the frequency of the most common haplotypes from parental breeds that have changed substantially in Kenyan crossbreds during admixture. The frequency of these haplotypes from parental breeds, which were likely to be selected in temperate regions, has deviated considerably from expected frequency in eleven genomic regions. Additionally, extended haplotype homozygosity based methods were applied to identify the regions responding to recent selection in crossbreds, called candidate regions, resulting in seven regions that appeared to be affected by Holstein-Friesians. However, some signatures of selection were less dependent on Holsteins-Friesians, suggesting evidence of adaptation in East Africa. The analysis of local ancestry is a useful approach to understand the detailed genomic structure and may reveal regions of the genome required for specialized adaptation
... The combination of genome-wide associations and signatures of selection based on the same set of SNPs help facilitate our ability to unravel loci influencing complex traits [43,44]. A previous study [45], which is concordant with our results, reported that the changes in haplotypes frequencies in sires accurately estimated genetic trends in the commercial cow population and could be applied to detect signatures of recent selection in Israeli Holsteins. Considering the candidate regions under selection and at the same time accounting for increased milk yield have provided the genomic status of the contemporary population of US Jerseys, suggesting the fundamental genotypic parameters available for the future breeding plans balancing productivity and diversity. ...
Article
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Genome signatures of artificial selection in U.S. Jersey cattle were identified by examining changes in haplotype homozygosity for a resource population of animals born between 1953 and 2007. Genetic merit of this population changed dramatically during this period for a number of traits, especially milk yield. The intense selection underlying these changes was achieved through extensive use of artificial insemination (AI), which also increased consanguinity of the population to a few superior Jersey bulls. As a result, allele frequencies are shifted for many contemporary animals, and in numerous cases to a homozygous state for specific genomic regions. The goal of this study was to identify those selection signatures that occurred after extensive use of AI since the 1960 , using analyses of shared haplotype segments or Runs of Homozygosity. When combined with animal birth year information, signatures of selection associated with economically important traits were identified and compared to results from an extended haplotype homozygosity analysis.. Overall, our results reveal that more recent selection increased autozygosity across the entire genome, but some specific regions increased more than others. A genome-wide scan identified more than 15 regions with a substantial change in autozygosity. Haplotypes found to be associated with increased milk, fat and protein yield in U.S. Jersey cattle also consistently increased in frequency. The analyses used in this study was able to detect directional selection over the last few decades when individual production records for Jersey animals were available.
... For example, although the polymorphism for ABCG2 is present in many different populations, allelic frequencies across populations differ dramatically (Ron et al., 2006). Similarly, Glick et al. (2012) and Weller et al. (2014) demonstrated that the markers with the greatest effects on traits of interest change over time, due to changes in allelic frequencies. ...
Article
The objectives were to investigate the accuracy of genomic evaluations obtained for a small dairy cattle population (Israeli Holsteins) via joint evaluation with a larger population (Dutch Holsteins), and to evaluate the use of pedigree data from foreign bulls computed by Interbull without daughter records in Israel. The training population included 4,010 Dutch bulls and 713 Israeli bulls. The validation population included 185 Israeli bulls with daughter records for milk production traits and slightly fewer bulls for the nonproduction traits. Milk, fat, and protein yields, somatic cell score, longevity, female fertility, direct and maternal calving ease, direct and maternal stillbirth, and the Israeli breeding index were analyzed. The genomic prediction model was based on the Bayesian multi-QTL model of Meuwissen and Goddard, where the effects of dense single nucleotide polymorphisms across the whole genome are fitted directly, without the use of haplotypes or identical-by-descent probabilities. Correlations of May 2014 estimated breeding values (EBV14) with genomic EBV (GEBV) were higher than the correlations of EBV14 with parent averages (PA) computed from the June 2009 evaluation for all traits. For the Israel selection index, the difference between EBV14 and GEBV correlation on the one hand and EBV14 and PA computed using Interbull data on the other hand was 15 percentage points. For protein, the difference between the corresponding correlations was 14 percentage points. Generally, correlations of EBV14 with PA based on Israeli EBV only were similar to correlations of EBV14 with PA including Interbull evaluations. Relative to EBV14, milk production traits were biased upwards for both GEBV and PA, but the bias was greater for PA. The Y-intercepts of regressions of EBV14 were significantly different from zero for regression on GEBV for all 3 milk production traits and the Israeli selection index. This was not the case for regression of EBV14 on PA. The regression line intersected with the line of unbiased estimation near the EBV of the bulls with highest values. Because only bulls with high evaluations are of interest for selection, GEBV for these bulls were less biased compared with that of bulls with lower evaluations. The difference in mean EBV14 between bulls born during 2007-2008 selected by GEBV and PA was 65 units. If half of all inseminations are by young bulls, then the annual genetic gain obtained by implementation of genomic evaluation will be 8 units per year (65/8). Because annual gain is currently 107 units, this is a gain of 7%. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
... As the mutation is deleterious under modern management, it is possible that its frequency will decrease with time in this breed. Signatures of selection for production traits have also been reported in domestic cattle and swine (e.g., Glick et al. 2012;Rubin et al. 2012). However, this is the first evidence of a functional allele under selection in the domestic horse. ...
Article
A dominantly inherited gain-of-function mutation in the glycogen synthase (GYS1) gene, resulting in excess skeletal muscle glycogen, has been identified in more than 30 horse breeds. This mutation is associated with the disease Equine Polysaccharide Storage Myopathy Type 1, yet persists at high frequency in some breeds. Under historical conditions of daily work and limited feed, excess muscle glycogen may have been advantageous, driving the increase in frequency of this allele. Fine-scale DNA sequencing in 80 horses and genotype assays in 279 horses revealed a paucity of haplotypes carrying the mutant allele when compared with the wild-type allele. Additionally, we found increased linkage disequilibrium, measured by relative extended haplotype homozygosity, in haplotypes carrying the mutation compared with haplotypes carrying the wild-type allele. Coalescent simulations of Belgian horse populations demonstrated that the high frequency and extended haplotype associated with the GYS1 mutation were unlikely to have arisen under neutrality or due to population demography. In contrast, in Quarter Horses, elevated relative extended haplotype homozygosity was associated with multiple haplotypes and may be the result of recent population expansion or a popular sire effect. These data suggest that the GYS1 mutation underwent historical selection in the Belgian, but not in the Quarter Horse.
... [60,69,93,122,193] REHH Relative EHH: Detects evidence of recent selection on relatively high frequency haplotypes within a population by comparing the EHH of the tested core haplotype to that of other core haplotypes present at a locus to correct for local variation in recombination rates [191]. [69,122,156,170,173] XP-EHH Across Population EHH: Detects selective sweeps by comparing EHH across populations in which selected alleles (at core haplotypes) have risen to near fixation in one but not all populations [194]. [50,80,125,128] iHS Integrated Haplotype-homozygosity Score: Detects evidence of recent positive selection at a locus based on the differential levels of LD surrounding a positively selected (derived) allele (at intermediate frequencies) compared to the background (ancestral) allele at the same position within a population [73]. ...
Article
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Since domestication, significant genetic improvement has been achieved for many traits of commercial importance in cattle, including adaptation, appearance and production. In response to such intense selection pressures, the bovine genome has undergone changes at the underlying regions of functional genetic variants, which are termed "selection signatures". This article reviews 64 recent (2009-2015) investigations testing genomic diversity for departure from neutrality in worldwide cattle populations. In particular, we constructed a meta-assembly of 16,158 selection signatures for individual breeds and their archetype groups (European, African, Zebu and composite) from 56 genome-wide scans representing 70,743 animals of 90 pure and crossbred cattle breeds. Meta-selection-scores (MSS) were computed by combining published results at every given locus, within a sliding window span. MSS were adjusted for common samples across studies and were weighted for significance thresholds across and within studies. Published selection signatures show extensive coverage across the bovine genome, however, the meta-assembly provides a consensus profile of 263 genomic regions of which 141 were unique (113 were breed-specific) and 122 were shared across cattle archetypes. The most prominent peaks of MSS represent regions under selection across multiple populations and harboured genes of known major effects (coat color, polledness and muscle hypertrophy) and genes known to influence polygenic traits (stature, adaptation, feed efficiency, immunity, behaviour, reproduction, beef and dairy production). As the first meta-assembly of selection signatures, it offers novel insights about the hotspots of selective sweeps in the bovine genome, and this method could equally be applied to other species.
... They supported their conclusions by within-breed haplotype homozygosity measures, assuming homozygosity levels as the final result of selection leading to haplotype fixation in those regions. However, as artificial selection can be conceived as a continuous process, its effects probably may be better evaluated by studying the additive substitution effects deriving from allele accumulation over time detectable from past time windows, as we proposed in our study and before by Glick et al. (2012). These authors reported a high correlation between selection intensity for milk production and reproduction traits by comparing changes in haplotype frequencies in a population of about 1000 Israeli Holstein bulls (genotyped with the Illumina BovineSNP50 BeadChip array) over a period spanning about five bull generations and those derived by trait-based analysis of the cow population. ...
Article
In this study, we investigated at the genome-wide level if 20 years of artificial directional selection based on boar genetic evaluation obtained with a classical BLUP animal model shaped the genome of the Italian Large White pig breed. The most influential boars of this breed (n = 192), born from 1992 (the beginning of the selection program of this breed) to 2012, with an estimated breeding value reliability of >0.85, were genotyped with the Illumina Porcine SNP60 BeadChip. After grouping the boars in eight classes according to their year of birth, filtered single nucleotide polymorphisms (SNPs) were used to evaluate the effects of time on genotype frequency changes using multinomial logistic regression models. Of these markers, 493 had a PBonferroni < 0.10. However, there was an increasing number of SNPs with a decreasing level of allele frequency changes over time, representing a continuous profile across the genome. The largest proportion of the 493 SNPs was on porcine chromosome (SSC) 7, SSC2, SSC8 and SSC18 for a total of 204 haploblocks. Functional annotations of genomic regions, including the 493 shifted SNPs, reported a few Gene Ontology terms that might underly the biological processes that contributed to increase performances of the pigs over the 20 years of the selection program. The obtained results indicated that the genome of the Italian Large White pigs was shaped by a directional selection program derived by the application of methodologies assuming the infinitesimal model that captured a continuous trend of allele frequency changes in the boar population.
... However, even for traits that have been recorded for several generations, it is doubtful that these historical records should be included in routine genomic evaluations for several reasons. As demonstrated by Glick et al. (2012) and Weller et al. (2014b), the frequencies of the important segregating genes change over time. In Israeli Holsteins, the frequency of the DGAT1 allele that increases fat concentration and quantity increased from 0.02 to 0.13 over 9 yr, and the allele of ABCG2 that increases protein concentration increased from 0.62 to 0.78 over 12 yr (Weller et al., 2003;Cohen-Zinder et al., 2005). ...
Article
Genomic evaluation has been successfully implemented in the United States, Canada, Great Britain, Ireland, New Zealand, Australia, France, the Netherlands, Germany, and the Scandinavian countries. Adoption of this technology in the major dairy producing countries has led to significant changes in the worldwide dairy industry. Gradual elimination of the progeny test system has led to a reduction in the number of sires with daughter records and fewer genetic ties between years. As genotyping costs decrease, the number of cows genotyped will continue to increase, and these records will become the basic data used to compute genomic evaluations, most likely via application of "single-step" methodologies. Although genomic selection has been successful in increasing rates of genetic gain, we still know very little about the genetic architecture of quantitative variation. Apparently, a very large number of genes affect nearly all economic traits, in accordance with the infinitesimal model for quantitative traits. Less emphasis in selection goals will be placed on milk production traits, and more on health, reproduction, and efficiency traits and on environmentally friendly production with reduced waste and gas emission. Genetic variance for economic traits is maintained by the increase in frequency of rare alleles, new mutations, and changes in selection goals and management. Thus, it is unlikely that a selection plateau will be reached in the near future.
... Although HO in Israel have been a closed population for many decades, they have had a similar breeding goal to other Holstein populations, with the highest weight on milk production out of all the Interbull member countries. They have only recently included fertility in the breeding index, PD07 (Glick et al., 2012) while Norwegian Red has been selected for a broad breeding goal with emphasis on health and fertility since the 1970s. Genetic improvement has been obtained for low-heritability traits like mastitis, ketosis (Heringstad et al., 2007) and female fertility (A-Ranberg et al., 2003). ...
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Norwegian Red bulls, selected in Norway, have been used for crossbreeding with Israeli Holstein on commercial farms. The aim of this project was to investigate Norwegian Red×Israeli Holstein (NRX) performance to see how the daughters perform in a different environment than the one their sires were selected in. This was done by comparing health and fertility of NRX with their Israeli Holstein (HO) counterparts. The data consisted of 71 911 HO records and 10 595 NRX records from 33 855 cows in 23 Israeli dairy herds. Calving events took place between 2006 and 2016. Five postpartum disorders (mean frequency in HO v . NRX, %) recorded by veterinarians were analyzed: anestrus (37.4 v . 41.2), metritis (40.1 v . 28.6), ketosis (11.9 v . 7.1), lameness (7.1 v . 3.1) and retained placenta (6.2 v . 4.0). The incidence of abortions was also analyzed; HO had a mean frequency of 9.9% and NRX 8.2%. These traits were defined as binary traits, with ‘1’ indicating that the disorder was present and a treatment took place at least once, or ‘0’ if the cow did not show signs of that disorder. Days open (i.e. the number of days from calving to conception), body condition score (BCS) recorded on a 1 to 5 scale and changes in BCS from calving to peak lactation were also analyzed. A logistic model was used for the health traits, while days open and BCS were analyzed with linear models. The model included breed group, herd-year of calving, birth year and parity as fixed effects. There was a significantly higher risk (odds ratio for HO v . NRX in parentheses) of ketosis (1.46), metritis (1.78), lameness (2.07), retained placenta (1.41) and abortion (1.13) in HO compared with NRX. Israeli Holstein heifers and cows in parity 3 to 6 had fewer cases of anestrus than NRX but no differences were found between the groups in parities 1 and 2. Body condition score was higher for NRX than HO and there was less change in BCS from calving to peak lactation in NRX compared with HO. Likewise, NRX had fewer days open than HO. Results indicate that crossbreeding can produce cows with better fertility that are less susceptible to postpartum disorders.
... Moreover, strong selection signature (|iHS| > 3.623, as highest 1% of all |iHS| values at genome-wide level) was detected in this region, especially in the overlapped ROH segment (Fig 2D). In a recent study, significant correlation between the EHH-based selection signature and actual trend in haplotype frequencies was demonstrated [42]. Similarly, we inferred that Artificial selection increased body weight but induced increase of runs of homozygosity in Hanwoo cattle strong selection signature based on EHH could be the evidence of recent artificial selection contributing to change of ROH. ...
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Artificial selection has been demonstrated to have a rapid and significant effect on the phenotype and genome of an organism. However, most previous studies on artificial selection have focused solely on genomic sequences modified by artificial selection or genomic sequences associated with a specific trait. In this study, we generated whole genome sequencing data of 126 cattle under artificial selection, and 24,973,862 single nucleotide variants to investigate the relationship among artificial selection, genomic sequences and trait. Using runs of homozygosity detected by the variants, we showed increase of inbreeding for decades, and at the same time demonstrated a little influence of recent inbreeding on body weight. Also, we could identify ~0.2 Mb runs of homozygosity segment which may be created by recent artificial selection. This approach may aid in development of genetic markers directly influenced by artificial selection, and provide insight into the process of artificial selection.
... This could be explained by the fact that F ROH k for this region was already high in 1986, which suggests that selection for this region occurred already before the Holsteinisation (the large-scale introduction of HF into national dairy industries in the 1970s and early 1980s). The latter could also explain why this region was identified as a selection signature in various countries [36,62,64]. ...
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Background: In recent decades, Holstein-Friesian (HF) selection schemes have undergone profound changes, including the introduction of optimal contribution selection (OCS; around 2000), a major shift in breeding goal composition (around 2000) and the implementation of genomic selection (GS; around 2010). These changes are expected to have influenced genetic diversity trends. Our aim was to evaluate genome-wide and region-specific diversity in HF artificial insemination (AI) bulls in the Dutch-Flemish breeding program from 1986 to 2015. Methods: Pedigree and genotype data (~ 75.5 k) of 6280 AI-bulls were used to estimate rates of genome-wide inbreeding and kinship and corresponding effective population sizes. Region-specific inbreeding trends were evaluated using regions of homozygosity (ROH). Changes in observed allele frequencies were compared to those expected under pure drift to identify putative regions under selection. We also investigated the direction of changes in allele frequency over time. Results: Effective population size estimates for the 1986-2015 period ranged from 69 to 102. Two major breakpoints were observed in genome-wide inbreeding and kinship trends. Around 2000, inbreeding and kinship levels temporarily dropped. From 2010 onwards, they steeply increased, with pedigree-based, ROH-based and marker-based inbreeding rates as high as 1.8, 2.1 and 2.8% per generation, respectively. Accumulation of inbreeding varied substantially across the genome. A considerable fraction of markers showed changes in allele frequency that were greater than expected under pure drift. Putative selected regions harboured many quantitative trait loci (QTL) associated to a wide range of traits. In consecutive 5-year periods, allele frequencies changed more often in the same direction than in opposite directions, except when comparing the 1996-2000 and 2001-2005 periods. Conclusions: Genome-wide and region-specific diversity trends reflect major changes in the Dutch-Flemish HF breeding program. Introduction of OCS and the shift in breeding goal were followed by a drop in inbreeding and kinship and a shift in the direction of changes in allele frequency. After introduction of GS, rates of inbreeding and kinship increased substantially while allele frequencies continued to change in the same direction as before GS. These results provide insight in the effect of breeding practices on genomic diversity and emphasize the need for efficient management of genetic diversity in GS schemes.
... When commercial SNP chips became available also for non-model animals, the research was quickly expanded within animal breeding. Selection signatures based on SNP markers were discovered in dairy cattle (Flori et al., 2009;Qanbari et al., 2010;Stella et al., 2010;Glick et al., 2012;Ramey et al., 2013;Pérez O'Brien et al., 2014;Pintus et al., 2014;Randhawa et al., 2014). ...
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The characterization of livestock genetic diversity has experienced extensive changes with the availability of dense nucleotide markers. Among the various forms of markers, the single nucleotide polymorphisms (SNP) have arguably the largest influence. A wide range of indicators for the assessment of genetic diversity was developed, or the existing methods were improved, enabling us to make informed decisions on the management of livestock populations. This review discusses the selected aspects of diversity assessment, with special attention to the SNP based methods. One of the core concepts in genomics of diversity is the linkage disequilibrium (LD), as it was shaped by demographic events during the development of breeds and species. These events, either natural or artificial, left detectable signals within the livestock genomes. Further changes were induced by human activity when mating related animals, leading to fixing or improving the desired traits in the breed, but reducing their genetic variability. The assessment of relatedness is also pivotal to construct meaningful mating plans and to avoid the negative consequences of inbreeding depression that might be detrimental especially in small, endangered populations. Both LD and relatedness are of interest on their own, as well as in their follow-up applications deriving overall measures of effective population size.
... Large F ST statistics imply divergent selection for alternate alleles within different breeds suggesting that there may be several mutations in NBEA that have been strongly historically selected in some breeds and that are currently under selection in others. None of the putative sweep regions detected in the Holsteins were concordant with regions detected to be responding to recent selection in Israeli Holsteins [92]. Rather than reflecting differences in the origin of the founders of the US and Israeli Holstein populations [93], this more likely reflects the fact that our study focused on the identification of loci where selection had driven the desirable allele to fixation, whereas the Israeli study focused on the identification of loci currently responding to strong selection. ...
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The domestication and subsequent selection by humans to create breeds and biological types of cattle undoubtedly altered the patterning of variation within their genomes. Strong selection to fix advantageous large-effect mutations underlying domesticability, breed characteristics or productivity created selective sweeps in which variation was lost in the chromosomal region flanking the selected allele. Selective sweeps have now been identified in the genomes of many animal species including humans, dogs, horses, and chickens. Here, we attempt to identify and characterise regions of the bovine genome that have been subjected to selective sweeps. Two datasets were used for the discovery and validation of selective sweeps via the fixation of alleles at a series of contiguous SNP loci. BovineSNP50 data were used to identify 28 putative sweep regions among 14 diverse cattle breeds. Affymetrix BOS 1 prescreening assay data for five breeds were used to identify 85 regions and validate 5 regions identified using the BovineSNP50 data. Many genes are located within these regions and the lack of sequence data for the analysed breeds precludes the nomination of selected genes or variants and limits the prediction of the selected phenotypes. However, phenotypes that we predict to have historically been under strong selection include horned-polled, coat colour, stature, ear morphology, and behaviour. The bias towards common SNPs in the design of the BovineSNP50 assay led to the identification of recent selective sweeps associated with breed formation and common to only a small number of breeds rather than ancient events associated with domestication which could potentially be common to all European taurines. The limited SNP density, or marker resolution, of the BovineSNP50 assay significantly impacted the rate of false discovery of selective sweeps, however, we found sweeps in common between breeds which were confirmed using an ultra-high-density assay scored in a small number of animals from a subset of the breeds. No sweep regions were shared between indicine and taurine breeds reflecting their divergent selection histories and the very different environmental habitats to which these sub-species have adapted.
... Allele frequency change is the most fundamental change due to selection [4,5], and a genomic region subjected to selection typically has a long-range pattern of linkage disequilibrium (LD) due to hitchhiking between the selection target and the neighboring variants [6][7][8]. Selection signature analysis based on allele frequency differences and long-range LD patterns of genome regions have identified a large number of genomic regions affected by selection from within-breed analysis of Holsteins [9][10][11][12][13][14] or from comparative analysis between Holsteins and other cattle breeds [15][16][17][18][19]. However, the relationship between genome changes and the decreased fertility and immunity in Holstein cattle remained unknown. ...
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Background The availability of a unique unselected Holstein line since 1964 provided a direct comparison between selected and unselected Holstein genomes whereas large Holstein samples provided unprecedented statistical power for identifying high-confidence SNP effects. Utilizing these unique resources, we aimed to identify genome changes affected by selection since 1964. Results Direct comparison of genome-wide SNP markers between a Holstein line unselected since 1964 and contemporary Holsteins showed that the 40 years of artificial selection since 1964 resulted in genome landscape changes. Among the regions affected by selection, the regions containing 198 genes with fertility functions had a larger negative correlation than that of all SNPs between the SNP effects on milk yield and daughter pregnancy rate. These results supported the hypothesis that hitchhiking of genetic selection for milk production by negative effects of fertility genes contributed to the unintended declines in fertility since 1964. The genome regions subjected to selection also contained 67 immunity genes, the bovine MHC region of Chr23 with significantly decreased heterozygosity in contemporary Holsteins, and large gene clusters including T-cell receptor and immunoglobulin genes. Conclusions This study for the first time provided direct evidence that genetic selection for milk production affected fertility and immunity genes and that the hitchhiking of genetic selection for milk production by negative fertility effects contributed to the fertility declines since 1964, and identified a large number of candidate fertility and immunity genes affected by selection. The results provided novel understanding about genome changes due to artificial selection and their impact on fertility and immunity genes and could facilitate developing genetic methods to reverse the declines in fertility and immunity in Holstein cattle.
... (1) because accuracies of GEBV were lower than those obtained with a GBLUP based on 50K SNP (probably due to a good cover of the genome) and (2) because significant segregating QTL change over time (due to fixation of positive alleles with high frequencies, and increase of frequency of positive alleles with low frequencies (Glick et al., 2012), a model that combines a genomic relationship matrix based on a classical 50K chip and a list of selected putative QTL, as proposed by Van Raden et al. (2017), could be investigated. Instead of sharing GEBV data, as is widespread now, this study demonstrates the possibility of exchanging data on SNP effects. ...
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As a result of the 1000 Bull Genome Project, it has become possible to impute millions of variants, with many of these potentially causative for traits of interest, for thousands of animals that have been genotyped with medium-density chips. This enormous source of data opens up very interesting possibilities for the inclusion of these variants in genomic evaluations. However, for computational reasons, it is not possible to include all variants in genomic evaluation procedures. One potential approach could be to select the most relevant variants based on the results of genome-wide association studies (GWAS); however, the identification of causative mutations is still difficult with this method, partly because of weak imputation accuracy for rare variants. To address this problem, this study assesses the ability of different approaches based on multi-breed GWAS (joint and meta-analyses) to identify single-nucleotide polymorphisms (SNP) for use in genomic evaluation in the 3 main French dairy cattle breeds. A total of 6,262 Holstein bulls, 2,434 Montbéliarde bulls, and 2,175 Normande bulls with daughter yield deviations for 5 milk production traits were imputed for 27 million variants. Within-breed and joint (including all 3 breeds) GWAS were performed and 3 models of meta-analysis were tested: fixed effect, random effect, and Z-score. Comparison of the results of within- and multi-breed GWAS showed that most of the quantitative trait loci identified using within-breed approaches were also found with multi-breed methods. However, the most significant variants identified in each region differed depending on the method used. To determine which approach highlighted the most predictive SNP for each trait, we used a marker-assisted best unbiased linear prediction model to evaluate lists of SNP generated by the different GWAS methods; each list contained between 25 and 2,000 candidate variants per trait, which were identified using a single within- or multi-breed GWAS approach. Among all the multi-breed methods tested in this study, variant selection based on meta-analysis (fixed effect) resulted in the most-accurate genomic evaluation (+1 to +3 points compared with other multi-breed approaches). However, the accuracies of genomic evaluation were always better when variants were selected using the results of within-breed GWAS. As has generally been found in studies of quantitative trait loci, these results suggest that part of the genetic variance of milk production traits is breed specific in Holstein, Montbéliarde, and Normande cattle.
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Domestication and selection are the major driving forces responsible for the determinative genetic variability in livestock. These selection patterns create unique genetic signatures within the genome. BovineSNP50 chip data from 236 animals (seven indicine and five taurine cattle breeds) were analyzed in the present study. We implemented three complementary approaches viz. iHS (Integrated haplotype score), ROH (Runs of homozygosity), and FST, to detect selection signatures. A total of 179, 56, and 231 regions revealed 518, 277, and 267 candidate genes identified by iHS, ROH, and FST methods, respectively. We found several candidate genes (e.g., NCR3, ARID5A, HIST1H2BN, DEFB4, DEFB7, HSPA1L, HSPA1B, and DNAJB4) related to production traits and the adaptation of indigenous breeds to local environmental constraints such as heat stress and disease susceptibility. However, further studies are warranted to refine the findings using a larger sample size, whole-genome sequencing, and/or high density genotyping.
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The aim of this study was to detect selection signatures considering cows from the German Holstein (GH) and the local dual-purpose black and white (DSN) population, as well as from generated sub-populations. The 4654 GH and 261 DSN cows were genotyped with the BovineSNP50 Genotyping BeadChip. The geographical herd location was used as an environmental descriptor to create the East-DSN and West-DSN sub-populations. In addition, two further sub-populations of GH cows were generated, using the extreme values for solutions of residual effects of cows for the claw disorder dermatitis digitalis. These groups represented the most susceptible and most resistant cows. We used cross-population extended haplotype homozygosity methodology (XP-EHH) to identify the most recent selection signatures. Furthermore, we calculated Wright's fixation index (FST ). Chromosomal segments for the top 0.1 percentile of negative or positive XP-EHH scores were studied in detail. For gene annotations, we used the Ensembl database and we considered a window of 250 kbp downstream and upstream of each core SNP corresponding to peaks of XP-EHH. In addition, functional interactions among potential candidate genes were inferred via gene network analyses. The most outstanding XP-EHH score was on chromosome 12 (at 77.34 Mb) for DSN and on chromosome 20 (at 36.29-38.42 Mb) for GH. Selection signature locations harbored QTL for several economically important milk and meat quality traits, reflecting the different breeding goals for GH and DSN. The average FST value between GH and DSN was quite low (0.068), indicating shared founders. For group stratifications according to cow health, several identified potential candidate genes influence disease resistance, especially to dermatitis digitalis.
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Panigrahi, M., Kumar, S., Deb, S.M., Mitra, A., Sharma, A. and Bujarbaruah, K.M. 2009. Lack of polymorphism in partial insulin like growth factor 1 (IGF1) and insulin like growth factor binding protein 3 (IGFBP3) genes of mithun. J. Appl. Anim. Res., 36: 41?44. A 396 bp fragment encompassing exon 5 of Insulin like growth factor 1 (IGF1) gene and 652 bp fragment encompassing exon 2?3 of Insulin like growth factor binding protein 3 (IGFBP3) gene were digested by HindIII and NlaIII restriction enzymes, respectively, in 90 mithun (Bos frontalis). The PCR-RFLP analysis showed the absence of polymorphism in these fragments in the animals screened. HindIII restriction enzyme produced two fragments of 269 and 127 bp in exon-5 of IGF 1. Similarly NlaIII restriction enzyme produced two fragments of 551 and 101 bp in exon 2?3 ofIGFBP3 gene. Two single nucleotide differences in IGF1 while six such differences in IGFBP3 gene existed in mithun sequences when compared to cattle. The sequence of the amplicons, which were the first reports on these genes in mithun, were submitted to GenBank (Accession numbers EF686016 and EF686017, respectively).
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The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A different approach to problems of multiple significance testing is presented. It calls for controlling the expected proportion of falsely rejected hypotheses – the false discovery rate. This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise. Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power. A simple sequential Bonferroni-type procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial. The use of the new procedure and the appropriateness of the criterion are illustrated with examples.
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An efficient algorithm for genomic selection of moderately sized populations based on single nucleotide polymorphism chip technology is described. A total of 995 Israeli Holstein bulls with genetic evaluations based on daughter records were genotyped for either the BovineSNP50 BeadChip or the BovineSNP50 v2 BeadChip. Milk, fat, protein, somatic cell score, female fertility, milk production persistency and herd-life were analyzed. The 400 markers with the greatest effects on each trait were first selected based on individual analysis of each marker with the genetic evaluations of the bulls as the dependent variable. The effects of all 400 markers were estimated jointly using a 'cow model,' estimated from the data truncated to exclude lactations with freshening dates after September 2006. Genotype probabilities for each locus were computed for all animals with missing genotypes. In Method I, genetic evaluations were computed by analysis of the truncated data set with the sum of the marker effects subtracted from each record. Genomic estimated breeding values for the young bulls with genotypes, but without daughter records, were then computed as their parent averages combined with the sum of each animal's marker effects. Method II genomic breeding values were computed based on regressions of estimated breeding values of bulls with daughter record on their parent averages, sum of marker effects and birth year. Method II correlations of the current breeding values of young bulls without daughter records in the truncated data set were higher than the correlations of the current breeding values with the parent averages for fat and protein production, persistency and herd-life. Bias of evaluations, estimated as a difference between the mean of current breeding values of the young bulls and their genomic evaluations, was reduced for milk production traits, persistency and herd-life. Bias for milk production traits was slightly negative, as opposed to the positive bias of parent averages. Correlations of Method II with the means of daughter records adjusted for fixed effects were higher than parent averages for fat, protein, fertility, persistency and herd-life. Reducing the number of markers included in the analysis from 400 to 300 did not reduce correlations of genomic breeding values for protein with current breeding values, but did slightly reduce correlations with means of daughter records. Method II has the advantages as compared with the method of VanRaden in that genotypes of cows can be readily incorporated into the Method II analysis, and it is more effective for moderately sized populations.
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'Selection signatures' delimit regions of the genome that are, or have been, functionally important and have therefore been under either natural or artificial selection. In this study, two different and complementary methods--integrated Haplotype Homozygosity Score (|iHS|) and population differentiation index (FST)--were applied to identify traces of decades of intensive artificial selection for traits of economic importance in modern cattle. We scanned the genome of a diverse set of dairy and beef breeds from Germany, Canada and Australia genotyped with a 50 K SNP panel. Across breeds, a total of 109 extreme |iHS| values exceeded the empirical threshold level of 5% with 19, 27, 9, 10 and 17 outliers in Holstein, Brown Swiss, Australian Angus, Hereford and Simmental, respectively. Annotating the regions harboring clustered |iHS| signals revealed a panel of interesting candidate genes like SPATA17, MGAT1, PGRMC2 and ACTC1, COL23A1, MATN2, respectively, in the context of reproduction and muscle formation. In a further step, a new Bayesian FST-based approach was applied with a set of geographically separated populations including Holstein, Brown Swiss, Simmental, North American Angus and Piedmontese for detecting differentiated loci. In total, 127 regions exceeding the 2.5 per cent threshold of the empirical posterior distribution were identified as extremely differentiated. In a substantial number (56 out of 127 cases) the extreme FST values were found to be positioned in poor gene content regions which deviated significantly (p < 0.05) from the expectation assuming a random distribution. However, significant FST values were found in regions of some relevant genes such as SMCP and FGF1. Overall, 236 regions putatively subject to recent positive selection in the cattle genome were detected. Both |iHS| and FST suggested selection in the vicinity of the Sialic acid binding Ig-like lectin 5 gene on BTA18. This region was recently reported to be a major QTL with strong effects on productive life and fertility traits in Holstein cattle. We conclude that high-resolution genome scans of selection signatures can be used to identify genomic regions contributing to within- and inter-breed phenotypic variation.
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Domestication of livestock species and a long history of migrations, selection and adaptation have created an enormous variety of breeds. Conservation of these genetic resources relies on demographic characterization, recording of production environments and effective data management. In addition, molecular genetic studies allow a comparison of genetic diversity within and across breeds and a reconstruction of the history of breeds and ancestral populations. This has been summarized for cattle, yak, water buffalo, sheep, goats, camelids, pigs, horses, and chickens. Further progress is expected to benefit from advances in molecular technology.
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The genomics revolution has spurred the undertaking of HapMap studies of numerous species, allowing for population genomics to increase the understanding of how selection has created genetic differences between subspecies populations. The objectives of this study were to (1) develop an approach to detect signatures of selection in subsets of phenotypically similar breeds of livestock by comparing single nucleotide polymorphism (SNP) diversity between the subset and a larger population, (2) verify this method in breeds selected for simply inherited traits, and (3) apply this method to the dairy breeds in the International Bovine HapMap (IBHM) study. The data consisted of genotypes for 32,689 SNPs of 497 animals from 19 breeds. For a given subset of breeds, the test statistic was the parametric composite log likelihood (CLL) of the differences in allelic frequencies between the subset and the IBHM for a sliding window of SNPs. The null distribution was obtained by calculating CLL for 50,000 random subsets (per chromosome) of individuals. The validity of this approach was confirmed by obtaining extremely large CLLs at the sites of causative variation for polled (BTA1) and black-coat-color (BTA18) phenotypes. Across the 30 bovine chromosomes, 699 putative selection signatures were detected. The largest CLL was on BTA6 and corresponded to KIT, which is responsible for the piebald phenotype present in four of the five dairy breeds. Potassium channel-related genes were at the site of the largest CLL on three chromosomes (BTA14, -16, and -25) whereas integrins (BTA18 and -19) and serine/arginine rich splicing factors (BTA20 and -23) each had the largest CLL on two chromosomes. On the basis of the results of this study, the application of population genomics to farm animals seems quite promising. Comparisons between breed groups have the potential to identify genomic regions influencing complex traits with no need for complex equipment and the collection of extensive phenotypic records and can contribute to the identification of candidate genes and to the understanding of the biological mechanisms controlling complex traits.
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Genomic selection (GS) uses molecular breeding values (MBV) derived from dense markers across the entire genome for selection of young animals. The accuracy of MBV prediction is important for a successful application of GS. Recently, several methods have been proposed to estimate MBV. Initial simulation studies have shown that these methods can accurately predict MBV. In this study we compared the accuracies and possible bias of five different regression methods in an empirical application in dairy cattle. Genotypes of 7,372 SNP and highly accurate EBV of 1,945 dairy bulls were used to predict MBV for protein percentage (PPT) and a profit index (Australian Selection Index, ASI). Marker effects were estimated by least squares regression (FR-LS), Bayesian regression (Bayes-R), random regression best linear unbiased prediction (RR-BLUP), partial least squares regression (PLSR) and nonparametric support vector regression (SVR) in a training set of 1,239 bulls. Accuracy and bias of MBV prediction were calculated from cross-validation of the training set and tested against a test team of 706 young bulls. For both traits, FR-LS using a subset of SNP was significantly less accurate than all other methods which used all SNP. Accuracies obtained by Bayes-R, RR-BLUP, PLSR and SVR were very similar for ASI (0.39-0.45) and for PPT (0.55-0.61). Overall, SVR gave the highest accuracy.All methods resulted in biased MBV predictions for ASI, for PPT only RR-BLUP and SVR predictions were unbiased. A significant decrease in accuracy of prediction of ASI was seen in young test cohorts of bulls compared to the accuracy derived from cross-validation of the training set. This reduction was not apparent for PPT. Combining MBV predictions with pedigree based predictions gave 1.05 - 1.34 times higher accuracies compared to predictions based on pedigree alone. Some methods have largely different computational requirements, with PLSR and RR-BLUP requiring the least computing time. The four methods which use information from all SNP namely RR-BLUP, Bayes-R, PLSR and SVR generate similar accuracies of MBV prediction for genomic selection, and their use in the selection of immediate future generations in dairy cattle will be comparable. The use of FR-LS in genomic selection is not recommended.
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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.
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Identifying recent positive selection signatures in domesticated animals could provide information on genome response to strong directional selection from domestication and artificial selection. With the completion of the cattle genome, private companies are now providing large numbers of polymorphic markers for probing variation in domestic cattle (Bos taurus). We analysed over 7,500 polymorphic single nucleotide polymorphisms (SNP) in beef (Angus) and dairy (Holstein) cattle and outgroup species Bison, Yak and Banteng in an indirect test of inbreeding and positive selection in Domestic cattle. Outgroup species: Bison, Yak and Banteng, were genotyped with high levels of success (90%) and used to determine ancestral and derived allele states in domestic cattle. Frequency spectrums of the derived alleles in Angus and Holstein were examined using Fay and Wu's H test. Significant divergences from the predicted frequency spectrums expected under neutrality were identified. This appeared to be the result of combined influences of positive selection, inbreeding and ascertainment bias for moderately frequent SNP. Approximately 10% of all polymorphisms identified as segregating in B. taurus were also segregating in Bison, Yak or Banteng; highlighting a large number of polymorphisms that are ancient in origin. These results suggest that a large effective population size (N(e)) of approximately 90,000 or more existed in B. taurus since they shared a common ancestor with Bison, Yak and Banteng ~1-2 million years ago (MYA). More recently N(e) decreased sharply probably associated with domestication. This may partially explain the paradox of high levels of polymorphism in Domestic cattle and the relatively small recent N(e) in this species. The period of inbreeding caused Fay and Wu's H statistic to depart from its expectation under neutrality mimicking the effect of selection. However, there was also evidence for selection, because high frequency derived alleles tended to cluster near each other on the genome.
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Haplotype-based methods offer a powerful approach to disease gene mapping, based on the association between causal mutations and the ancestral haplotypes on which they arose. As part of The SNP Consortium Allele Frequency Projects, we characterized haplotype patterns across 51 autosomal regions (spanning 13 megabases of the human genome) in samples from Africa, Europe, and Asia. We show that the human genome can be parsed objectively into haplotype blocks: sizable regions over which there is little evidence for historical recombination and within which only a few common haplotypes are observed. The boundaries of blocks and specific haplotypes they contain are highly correlated across populations. We demonstrate that such haplotype frameworks provide substantial statistical power in association studies of common genetic variation across each region. Our results provide a foundation for the construction of a haplotype map of the human genome, facilitating comprehensive genetic association studies of human disease.
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Milk, fat, and protein production, somatic cell score (SCS), and female fertility in the Israeli Holstein dairy cattle population were analyzed using a multitrait animal model (AM) with parities 1 through 5 as separate traits. Female fertility was measured as the inverse of the number of inseminations to conception in percent. Variance components were estimated using both the repeatability AM and multitrait AM. The multitrait heritabilities for individual parities were greater than the heritabilities from the repeatability AM, and heritabilities decreased with an increase in parity number. Heritabilities were higher for production traits, lower for SCS, and lowest for female fertility. The genetic correlations were higher than the environmental correlations. Genetic correlations between parities decreased with an increase in the difference in parity number, but all were greater than 0.5. The environmental correlations were higher for production traits, lower for SCS, and close to zero for female fertility. In the analysis of the complete milk recorded population, genetic trends from the repeatability and multitrait models were very similar. The genetic trend for SCS was economically unfavorable until 1993, and favorable since then. The genetic trend for female fertility was close to zero, but the annual environmental trend was -0.2%. The multitrait lactation model is an attractive compromise between repeatability lactation models, which do not account for maturing trends across parities, and test-day models, which are much more demanding computationally.
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We previously localized a quantitative trait locus (QTL) on chromosome 6 affecting milk fat and protein concentration to a 4-cM confidence interval, centered on the microsatellite BM143. We characterized the genes and sequence variation in this region and identified common haplotypes spanning five polymorphic sites in the genes IBSP, SPP1, PKD2, and ABCG2 for two sires heterozygous for this QTL. Expression of SPP1 and ABCG2 in the bovine mammary gland increased from parturition through lactation. SPP1 and all the coding exons of ABCG2 and PKD2 were sequenced for these two sires. The single nucleotide change capable of encoding a substitution of tyrosine-581 to serine (Y581S) in the ABCG2 transporter was the only polymorphism corresponding to the segregation status of all 3 heterozygous and 15 homozygous sires for the QTL in the Israeli and U.S. Holstein populations. The allele substitution fixed effects on the genetic evaluations of 335 Israeli sires were -341 kg milk, +0.16% fat, and +0.13% protein (F-value = 200). No other polymorphism gave significant effect for fat and protein concentration in models that also included Y581S. The allele substitution effects on the genetic evaluations of 670 cows, daughters of two heterozygous sires, were -226 kg milk, 0.09% fat, and 0.08% protein (F-value = 394), with partial dominance towards the 581S homozygotes. We therefore propose that Y581S in ABCG2 is the causative site for this QTL.
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A scheme is described for the genetic improvement of milk yield in a large population of dairy cows, based on half-sister selection of young bulls, as an alternative to the normal procedure of progeny testing. The results indicate that the suggested scheme would lead t o an eventual rate of genetic progress very similar to the progeny testing scheme. However, the annual cost of the new scheme is less than a progeny testing scheme, largely because the ‘laying off’ of candidate bulls, to await selection, is completely eliminated. In addition, improvement of the dairy cows shows up sooner in the new scheme; by the 10th year from the start the cumulative genetic improvement is four times greater than for progeny testing.
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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.
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A number of cattle breeds have become highly specialized for milk or beef production, following strong artificial selection for these traits. In this paper, we compare allele frequencies from 9323 single nucleotide polymorphism (SNP) markers genotyped in dairy and beef cattle breeds averaged in sliding windows across the genome, with the aim of identifying divergently selected regions of the genome between the production types. The value of the method for identifying selection signatures was validated by four sources of evidence. First, differences in allele frequencies between dairy and beef cattle at individual SNPs were correlated with the effects of those SNPs on production traits. Secondly, large differences in allele frequencies generally occurred in the same location for two independent data sets (correlation 0.45) between sliding window averages. Thirdly, the largest differences in sliding window average difference in allele frequencies were found on chromosome 20 in the region of the growth hormone receptor gene, which carries a mutation known to have an effect on milk production traits in a number of dairy populations. Finally, for the chromosome tested, the location of selection signatures between dairy and beef cattle was correlated with the location of selection signatures within dairy cattle.
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The ability to detect recent natural selection in the human population would have profound implications for the study of human history and for medicine. Here, we introduce a framework for detecting the genetic imprint of recent positive selection by analysing long-range haplotypes in human populations. We first identify haplotypes at a locus of interest (core haplotypes). We then assess the age of each core haplotype by the decay of its association to alleles at various distances from the locus, as measured by extended haplotype homozygosity (EHH). Core haplotypes that have unusually high EHH and a high population frequency indicate the presence of a mutation that rose to prominence in the human gene pool faster than expected under neutral evolution. We applied this approach to investigate selection at two genes carrying common variants implicated in resistance to malaria: G6PD and CD40 ligand. At both loci, the core haplotypes carrying the proposed protective mutation stand out and show significant evidence of selection. More generally, the method could be used to scan the entire genome for evidence of recent positive selection.
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Persistency was defined as the predicted milk production 180 d after peak divided by peak production (in %). Heritability of persistency in a multitrait analysis including parities 1 through 5 increased from 0.16 to 0.27 from first through third parity, and then declined through fifth parity. Genetic correlations for persistency between consecutive parities were all > 0.8. First-parity genetic correlations of the traits included in the Israeli selection index with persistency were all < 0.1, except for fertility and herdlife, which were 0.20 and 0.25; whereas second-parity genetic correlations of persistency with the 3 milk production traits were all > 0.34, and the genetic correlation with fertility was only 0.10. The genetic correlation between second-parity persistency and herdlife was 0.58. Persistency in the Israeli Holstein population was analyzed by the multitrait animal model. The genetic trend since 1985 for the multiparity index was 0.22% persistency/yr, even though there was no direct selection on persistency.
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Many quantitative trait loci (QTL) affecting economic traits in livestock have now been identified. However, the confidence interval (CI) of individual QTL as determined by linkage analysis often spans tens of map units, containing hundreds of genes. Linkage disequilibrium (LD) mapping can reduce the CI to individual map units, but this reduced interval will still contain tens of genes. Methods suitable for model animals to find and validate specific quantitative trait nucleotides (QTN) underlying the QTL cannot be easily applied to livestock species because of their long generation intervals, the cost of maintaining each animal and the difficulty of producing transgenics or 'knock-outs'. Considering these limitations, we review successful approaches for identifying QTN in livestock and outline a schematic strategy for QTN determination and verification. In addition to linkage and LD mapping, the methods include positional cloning, selection of candidate genes, DNA sequencing and statistical analyses. Concordance determination and functional assays are the critical tests for validation of a QTN; we provide a generalized formula for the probability of concordance by chance. Three genes that meet the burden of proof for QTN identification--DGAT1 in cattle, IGF2 in swine and GDF8 in sheep--are discussed in detail. The genetic and economic ramifications of identified QTN and the horizon for selection and introgression are also considered.
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Whole-genome association studies present many new statistical and computational challenges due to the large quantity of data obtained. One of these challenges is haplotype inference; methods for haplotype inference designed for small data sets from candidate-gene studies do not scale well to the large number of individuals genotyped in whole-genome association studies. We present a new method and software for inference of haplotype phase and missing data that can accurately phase data from whole-genome association studies, and we present the first comparison of haplotype-inference methods for real and simulated data sets with thousands of genotyped individuals. We find that our method outperforms existing methods in terms of both speed and accuracy for large data sets with thousands of individuals and densely spaced genetic markers, and we use our method to phase a real data set of 3,002 individuals genotyped for 490,032 markers in 3.1 days of computing time, with 99% of masked alleles imputed correctly. Our method is implemented in the Beagle software package, which is freely available.
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The extent and pattern of linkage disequilibrium (LD) between closely spaced markers contain information about population history, including past population size and selection history. Selection signatures can be identified by comparing the LD surrounding a putative selected allele at a locus to the putative non-selected allele. In livestock populations, locations of selection signatures identified in this way should be correlated with QTL affecting production traits, as the populations have been under strong artificial selection for these traits. We used a dense SNP map of bovine chromosome 6 to characterize the pattern of LD on this chromosome in Norwegian Red cattle, a breed which has been strongly selected for milk production. The pattern of LD was generally consistent with strong selection in regions containing QTL affecting milk production traits, including a strong selection signature in a region containing a mutation known to affect milk production. The results demonstrate that in livestock populations, the origin of selection signatures will often be QTL for livestock production traits, and illustrate the value of selection signatures in uncovering new mutations with potential effects on quantitative traits.
The genome response to arti-ficial selection: a case study in dairy cattle The structure of haplotype blocks in the human genome
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Falconer D.S. (1964) Introduction to Quantitative Genetics, p. 206. Oliver and Boyd LTD, Edinburgh and London. Flori L., Fritz S.B., JaffreIzic F., Boussaha M., Gut I., Heath S., Foulley J.-L. & Gautier M. (2009) The genome response to arti-ficial selection: a case study in dairy cattle. PLoS ONE 4, e6595. Gabriel S.B., Schaffner S.F., Nguyen H. et al. (2002) The structure of haplotype blocks in the human genome. Science 296, 2225– 9.
Application of site and haplo-type-frequency based approaches for detecting selection signa-tures in cattle From QTL to QTN identification in livestock– winning by points rather than knock-out: a review
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Qanbari S., Gianola D., Hayes B., Schenkel F., Miller S., Moore S., Thaller G. & Simianer H. (2011) Application of site and haplo-type-frequency based approaches for detecting selection signa-tures in cattle. BMC Genomics 12, 318. Ron M. & Weller J. (2007) From QTL to QTN identification in livestock– winning by points rather than knock-out: a review. Ani-mal Genetics 38, 429–39.
Genetic trends-average breeding value of cows Controlling the false discov-ery rate: a practical and powerful approach to multiple testing
  • Anon
Anon. (2009) Genetic trends-average breeding value of cows. In: The Dairy Industry in Israel 2009 (Eds D. Hojman, Y. Malul & T. Avrech), p. 33. Israel Dairy Board and Israel Cattle Breeders Association, Caesaria, Israel. Benjamini Y. & Hochberg Y. (1995) Controlling the false discov-ery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological) 57, 289–300.
Genetic trends-average breeding value of cows In: The Dairy Industry in Israel
  • Anon
Anon. (2009) Genetic trends-average breeding value of cows. In: The Dairy Industry in Israel 2009 (Eds D. Hojman, Y. Malul & T. Avrech), p. 33. Israel Dairy Board and Israel Cattle Breeders Association, Caesaria, Israel.
Israel Dairy Board and Israel Cattle Breeders Association
  • Anon
Anon. (2009) Genetic trends-average breeding value of cows. In: The Dairy Industry in Israel 2009 (Eds D. Hojman, Y. Malul & T. Avrech), p. 33. Israel Dairy Board and Israel Cattle Breeders Association, Caesaria, Israel.