Linkage disequilibrium in the North American Holstein population

Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cows

BACKGROUND

Over the last decades, it was subject of many studies to investigate the genomic connection of milk production and health traits in dairy cattle. Thereby, incorporating functional information in genomic analyses has been shown to improve the understanding of biological and molecular mechanisms shaping complex traits and the accuracies of genomic prediction, especially in small populations and across-breed settings. Still, little is known about the contribution of different functional and evolutionary genome partitioning subsets to milk production and dairy health. Thus, we performed a uni- and a bivariate analysis of milk yield (MY) and eight health traits using a set of ~34,497 German Holstein cows with 50K chip genotypes and ~17 million imputed sequence variants divided into 27 subsets depending on their functional and evolutionary annotation. In the bivariate analysis, eight trait-combinations were observed that contrasted MY with each health trait. Two genomic relationship matrices (GRM) were included, one consisting of the 50K chip variants and one consisting of each set of subset variants, to obtain subset heritabilities and genetic correlations. In addition, 50K chip heritabilities and genetic correlations were estimated applying merely the 50K GRM.

RESULTS

In general, 50K chip heritabilities were larger than the subset heritabilities. The largest heritabilities were found for MY, which was 0.4358 for the 50K and 0.2757 for the subset heritabilities. Whereas all 50K genetic correlations were negative, subset genetic correlations were both, positive and negative (ranging from -0.9324 between MY and mastitis to 0.6662 between MY and digital dermatitis). The subsets containing variants which were annotated as noncoding related, splice sites, untranslated regions, metabolic quantitative trait loci, and young variants ranked highest in terms of their contribution to the traits` genetic variance. We were able to show that linkage disequilibrium between subset variants and adjacent variants did not cause these subsets` high effect.

CONCLUSION

Our results confirm the connection of milk production and health traits in dairy cattle via the animals` metabolic state. In addition, they highlight the potential of including functional information in genomic analyses, which helps to dissect the extent and direction of the observed traits` connection in more detail.

A Multibreed Genome-Wide Association Study for Cattle Leukocyte Telomere Length

Telomeres are terminal DNA regions of chromosomes that prevent chromosomal fusion and degradation during cell division. In cattle, leukocyte telomere length (LTL) is associated with longevity, productive lifespan, and disease susceptibility. However, the genetic basis of LTL in this species is less studied than in humans. In this study, we utilized the whole-genome resequencing data of 239 animals from 17 cattle breeds for computational leukocyte telomere length estimation and subsequent genome-wide association study of LTL. As a result, we identified 42 significant SNPs, of which eight were found in seven genes (EXOC6B, PTPRD, RPS6KC1, NSL1, AGBL1, ENSBTAG00000052188, and GPC1) when using covariates for two major breed groups (Turano-Mongolian and European). Association analysis with covariates for breed effect detected 63 SNPs, including 13 in five genes (EXOC6B, PTPRD, RPS6KC1, ENSBTAG00000040318, and NELL1). The PTPRD gene, demonstrating the top signal in analysis with breed effect, was previously associated with leukocyte telomere length in cattle and likely is involved in the mechanism of alternative lengthening of telomeres. The single nucleotide variants found could be tested for marker-assisted selection to improve telomere-length-associated traits.

Longitudinal genome-wide association studies of milk production traits in Holstein cattle using whole-genome sequence data imputed from medium-density chip data

Longitudinal traits, such as milk production traits in dairy cattle, are featured by having phenotypic values at multiple time points, which change dynamically over time. In this study, we first imputed SNP chip (50-100K) data to whole-genome sequence (WGS) data in a Chinese Holstein population consisting of 6,470 cows. The imputation accuracies were 0.88 to 0.97 on average after quality control. We then performed longitudinal GWAS in this population based on a random regression test-day model using the imputed WGS data. The longitudinal GWAS revealed 16, 39, and 75 quantitative trait locus regions associated with milk yield, fat percentage, and protein percentage, respectively. We estimated the 95% confidence intervals (CI) for these quantitative trait locus regions using the logP drop method and identified 581 genes involved in these CI. Further, we focused on the CI that covered or overlapped with only 1 gene or the CI that contained an extremely significant top SNP. Twenty-eight candidate genes were identified in these CI. Most of them have been reported in the literature to be associated with milk production traits, such as DGAT1, HSF1, MGST1, GHR, ABCG2, ADCK5, and CSN1S1. Among the unreported novel genes, some also showed good potential as candidate genes, such as CCSER1, CUX2, SNTB1, RGS7, OSR2, and STK3, and are worth being further investigated. Our study provided not only new insights into the candidate genes for milk production traits, but also a general framework for longitudinal GWAS based on random regression test-day model using WGS data.

Genetic variants of IFIH1 and DHX58 affect the chronicity of hepatitis C in the Chinese Han population

Hepatitis C remains a major public health problem in the world. The host immune system plays a key role in viral clearance. This study aimed to investigate the connection between retinoic acid-inducible gene I-like (RIG-I-like) receptor gene polymorphism and hepatitis C chronicity in the Chinese Han population. The current study genotyped three SNPs (IFIH1 rs10930046 and DHX58 rs2074158, rs2074160) to assess their association with the chronicity of hepatitis C virus (HCV) infection among 1,590 participants (590 spontaneous HCV clearance cases and 1,000 persistent infection patients). Our research shows that DHX58 rs2074158-G allele (dominant model: adjusted OR = 1.53, 95% CI [1.20-1.95], P = 0.001; additive model: adjusted OR = 1.50, 95% CI [1.27-1.78], P < 0.001) and IFIH1 rs10930046-C allele (additive model: adjusted OR = 1.26, 95% CI [1.07-1.49], P = 0.005) were associated with chronic hepatitis C (CHC). And the risk of CHC increased in people carrying more unfavorable genotypes (rs2074158-AG/GG or rs10930046-CC), with the chronic rates for genotypes number from zero to two in 60.69%, 57.33%, and 85.93%, respectively (adjusted OR = 3.64, 95% CI [2.18-6.08]; P < 0.001). Genetic polymorphism of IFIH1 and DHX58 may be related to CHC in the Chinese Han population. Furthermore, the risk of CHC increases as the number of unfavorable genotypes carried by the HCV-infected person increases. IFIH1 rs10930046, DHX58 rs2074158, age, ALT, and AST levels were all independent predictors of CHC.

A Genome-Wide Association Study for Tolerance to Paratuberculosis Identifies Candidate Genes Involved in DNA Packaging, DNA Damage Repair, Innate Immunity, and Pathogen Persistence

Although the genetic susceptibility to diseases has been extensively studied, the genetic loci and the primary molecular and cellular mechanisms that control disease tolerance are still largely unknown. Bovine paratuberculosis (PTB) is an enteritis caused by Mycobacterium avium subsp. paratuberculosis (MAP). PTB affects cattle worldwide and represents a major issue on animal health. In this study, the associations between host genetic and PTB tolerance were investigated using the genotypes from 277 Spanish Holstein cows with two distinct phenotypes: cases) infected animals with positive PCR and bacteriological culture results but without lesions in gut tissues (N= 24), and controls) animals with negative PCR and culture results but with PTB-associated lesions (N= 253). DNA from peripheral blood of the study population was genotyped with the Bovine EuroG MD Bead Chip, and the corresponding genotypes were imputed to whole-genome sequencing (WGS) data. A genome-wide association study was performed using the WGS data and the defined phenotypes in a case-control approach. A total of 142 single nucleotide polymorphisms (SNPs) were associated (false discovery rate ≤ 0.05, P values between 1.5 × 10^-7 and 5.7 × 10^-7) with tolerance (heritability= 0.55). The 40 SNPs with P-values < 5 × 10^-7 defined 9 QTLs and 98 candidate genes located on BTA4, BTA9, BTA16, BTA25, and BTA26. Some of the QTLs identified in this study overlap with QTLs previously associated with PTB, bovine tuberculosis, mastitis, somatic cell score, bovine diarrhea virus persistent infection, tick resistance, and length of productive life. Two candidate genes with important roles in DNA damage response (ERCC4 and RMI2) were identified on BTA25. Functional analysis using the 98 candidate genes revealed a significant enrichment of the DNA packaging process (TNP2/PRMI1/PRM2/PRM3). In addition, the TNF-signaling (bta04668; TRAF5/CREB5/CASP7/CHUK) and the toxoplasmosis (bta05145; TGFβ2/CHUK/CIITA/SOCS1) pathways were significantly enriched. Interestingly, the nuclear Factor NF-κβ Inhibitor Kinase Alpha (CHUK), a key molecule in the regulation of the NF-κB pathway, was enriched in both pathways. Taken together, our results define a distinct immunogenetic profile in the PTB-tolerant animals designed to control bacterial growth, modulate inflammation, limit tissue damage and increase repair, thus reducing the severity of the disease.

Genetic structure analysis in several populations of cattle using SNP genotypes

Parameters such as effective population size (Ne), runs of homozygosity (ROH), and inbreeding based on ROH (FROH) can give new insight into the level of genetic diversity for the population under selection. This research aimed to measure the extent of linkage disequilibrium (LD), effective population size (Ne), Haplotype Block Structure, and runs of homozygosity (ROHs) in several populations of cattle using SNP genotypes. In this study, that the average r² decreased with the increasing distance of SNP pairs. A general decrease in Ne can be seen for all four populations, indicating a loss of genetic diversity. The Iranian Holstein had the lowest level of genomic inbreeding at an ROH of 1, 5, 10 Mb, while the French Holstein had the highest. The maximum number of ROH is seen at a distance of less than 1 Mb, and the lowest number of ROH is seen at a distance of 10 Mb. The number of ROH decreases with increasing distance due to the increased recombination rate. This is a concern as an increase in inbreeding leads to a reduction in the effective population size, which was also evident in the study populations.

The breeding structure for the small ruminant resources in India

Intense selection for a few desired traits has resulted in reduction of the effective population size (Ne) in most of the plant and livestock populations across the world. The objective of the research was to assess the impact of Ne on the genetic architecture of the population in a simulated data with variable Ne for general population under selection. Along with this, the estimate of Ne and its ratio to adult breeding population (N_B) in the census data of small ruminants of India were also investigated. Results indicated that the average inbreeding ([Formula: see text]) decreases with increase in Ne; similarly, increase in [Formula: see text] per generation was highest in population with lowest Ne. Correlation of estimated breeding value (EBV) with true breeding value (TBV) was not much affected with effective population size. An effective number of chromosome segments (Me) in the populations under selection were significantly affected by magnitude of Ne, with linear positive relation between Ne and Me. Results on livestock census data revealed that all the sheep and goat breeds have sufficiently large Ne based on derived and actual census data. The median for ratio of effective population size to adult census size in sheep breeds was 0.120 and for goat breeds was 0.131. Karnah and Poonchi sheep shares the status of endangered breeds due to a smaller number of breeding female population and hence need attention for conservation. The Ne was large in sheep and goat due to less selection pressure as a result of low coverage of breed improvement programs, availability of large number of breeding males, and absence of artificial insemination (AI) in the field flocks. The estimates of Ne and its ratio to the adult census size (N_B) excluded several factors such as fluctuating population size and overlapping generations. Study revealed introspection from most of the industrial breeding programs on the issue of Ne for populations under selection. Similarly, in small ruminants, large Ne indicates huge genetic diversity and scope of improvement in the productivity in near future.

Exploration of fine-scale recombination rate variation in the domestic horse

Total genetic map length and local recombination landscapes typically vary within and across populations. As a first step to understanding the recombination landscape in the domestic horse, we calculated population recombination rates and identified likely recombination hotspots using approximately 1.8 million SNP genotypes for 485 horses from 32 distinct breeds. The resulting breed-averaged recombination map spans 2.36 Gb and accounts for 2939.07 cM. Recombination hotspots occur once per 23.8 Mb on average and account for ∼9% of the physical map length. Regions with elevated recombination rates in the entire cohort were enriched for genes in pathways involving interaction with the environment: immune system processes (specifically, MHC class I and class II genes), responses to stimuli, and serotonin receptor pathways. We found significant correlations between differences in local recombination rates and population differentiation quantified by F _ST Analysis of breed-specific maps revealed thousands of hotspot regions unique to particular breeds, as well as unique "coldspots," regions where a particular breed showed below-average recombination, whereas all other breeds had evidence of a hotspot. Finally, we identified relative enrichment (P = 5.88 × 10^-27) for the in silico-predicted recognition motif for equine PR/SET domain 9 (PRDM9) in recombination hotspots. These results indicate that selective pressures and PRDM9 function contribute to variation in recombination rates across the domestic horse genome.

Functional annotation and Bayesian fine-mapping reveals candidate genes for important agronomic traits in Holstein bulls

A hundred years of data collection in dairy cattle can facilitate powerful studies of complex traits. Cattle GWAS have identified many associated genomic regions. With increasing numbers of cattle sequenced, fine-mapping of causal variants is becoming possible. Here we imputed selected sequence variants to 27,214 Holstein bulls that have highly reliable phenotypes for 35 production, reproduction, and body conformation traits. We performed single-marker scans for the 35 traits and multi-trait tests of the three trait groups, revealing 282 candidate QTL for fine-mapping. We developed a Bayesian Fine-MAPping approach (BFMAP) to integrate fine-mapping with functional enrichment analysis. Our fine-mapping identified 69 promising candidate genes, including ABCC9, VPS13B, MGST1, SCD, MKL1, CSN1S1 for production, CHEK2, GC, KALRN for reproduction, and TMTC2, ARRDC3, ZNF613, CCND2, FGF6 for conformation traits. Collectively, these results demonstrated the utility of BFMAP, identified candidate genes, and enhanced our understanding of the genetic basis of cattle complex traits.

Complex Trait Prediction from Genome Data: Contrasting EBV in Livestock to PRS in Humans: Genomic Prediction

In this Review, we focus on the similarity of the concepts underlying prediction of estimated breeding values (EBVs) in livestock and polygenic risk scores (PRS) in humans. Our research spans both fields and so we recognize factors that are very obvious for those in one field, but less so for those in the other. Differences in family size between species is the wedge that drives the different viewpoints and approaches. Large family size achievable in nonhuman species accompanied by selection generates a smaller effective population size, increased linkage disequilibrium and a higher average genetic relationship between individuals within a population. In human genetic analyses, we select individuals unrelated in the classical sense (coefficient of relationship <0.05) to estimate heritability captured by common SNPs. In livestock data, all animals within a breed are to some extent "related," and so it is not possible to select unrelated individuals and retain a data set of sufficient size to analyze. These differences directly or indirectly impact the way data analyses are undertaken. In livestock, genetic segregation variance exposed through samplings of parental genomes within families is directly observable and taken for granted. In humans, this genomic variation is under-recognized for its contribution to variation in polygenic risk of common disease, in both those with and without family history of disease. We explore the equation that predicts the expected proportion of variance explained using PRS, and quantify how GWAS sample size is the key factor for maximizing accuracy of prediction in both humans and livestock. Last, we bring together the concepts discussed to address some frequently asked questions.

A genome-wide scan for diversifying selection signatures in selected horse breeds

The genetic differentiation of the current horse population was evolutionarily created by natural or artificial selection which shaped the genomes of individual breeds in several unique ways. The availability of high throughput genotyping methods created the opportunity to study this genetic variation on a genome-wide level allowing detection of genome regions divergently selected between separate breeds as well as among different horse types sharing similar phenotypic features. In this study, we used the population differentiation index (FST) that is generally used for measuring locus-specific allele frequencies variation between populations, to detect selection signatures among six horse breeds maintained in Poland. These breeds can be classified into three major categories, including light, draft and primitive horses, selected mainly in terms of type (utility), exterior, performance, size, coat color and appearance. The analysis of the most pronounced selection signals found in this study allowed us to detect several genomic regions and genes connected with processes potentially important for breed phenotypic differentiation and associated with energy homeostasis during physical effort, heart functioning, fertility, disease resistance and motor coordination. Our results also confirmed previously described association of loci on ECA3 (spanning LCORL and NCAPG genes) and ECA11 (spanning LASP1 gene) with the regulation of body size in our draft and primitive (small size) horses. The efficiency of the applied FST-based approach was also confirmed by the identification of a robust selection signal in the blue dun colored Polish Konik horses at the locus of TBX3 gene, which was previously shown to be responsible for dun coat color dilution in other horse breeds. FST-based method showed to be efficient in detection of diversifying selection signatures in the analyzed horse breeds. Especially pronounced signals were observed at the loci responsible for fixed breed-specific features. Several candidate genes under selection were proposed in this study for traits selected in separate breeds and horse types, however, further functional and comparative studies are needed to confirm and explain their effect on the observed genetic diversity of the horse breeds.

The contribution of myostatin (MSTN) and additional modifying genetic loci to race distance aptitude in Thoroughbred horses racing in different geographic regions

BACKGROUND

Race distance aptitude in Thoroughbred horses is highly heritable and is influenced largely by variation at the myostatin gene (MSTN).

OBJECTIVES

In addition to MSTN, we hypothesised that other modifying loci contribute to best race distance.

STUDY DESIGN

Using 3006 Thoroughbreds, including 835 'elite' horses, which were >3 years old, had race records and were sampled from Europe/Middle-East, Australia/New Zealand, North America and South Africa, we performed genome-wide association (GWA) tests and separately developed a genomic prediction algorithm to comprehensively catalogue additive genetic variation contributing to best race distance.

METHODS

48,896 single-nucleotide polymorphism (SNP) genotypes were generated from high-density SNP genotyping arrays. Heritability estimates, tests of GWA and genomic prediction models were derived for the phenotypes: average race distance, best race distance for elite, nonelite and all winning horses.

RESULTS

Heritability estimates were high ( h m 2  = 0.51, best race distance - elite; h m 2  = 0.42, best race distance - nonelite; h m 2  = 0.40, best race distance - all) and most of the variation was attributed to the MSTN gene. MSTN locus SNPs were the most strongly associated with the trait and included BIEC2-438999 (ECA18:66913090; P = 4.51 × 10^-110 , average race distance; P = 2.33 × 10^-42 , best race distance - elite). The genomic prediction algorithm enabled the inclusion of variation from all SNPs in a model that partitioned horses into short and long cohorts following assignment of MSTN genotype. Additional genes with minor contributions to best race distance were identified.

MAIN LIMITATIONS

The nongenetic influence of owner/trainer decisions on placement of horses in suitable races could not be controlled.

CONCLUSIONS

MSTN is the single most important genetic contributor to best race distance in the Thoroughbred. Employment of genetic prediction models will lead to more accurate placing of horses in races that are best suited to their inherited genetic potential for distance aptitude.

Genomic regions underlying susceptibility to bovine tuberculosis in Holstein-Friesian cattle

BACKGROUND

The significant social and economic loss as a result of bovine tuberculosis (bTB) presents a continuous challenge to cattle industries in the UK and worldwide. However, host genetic variation in cattle susceptibility to bTB provides an opportunity to select for resistant animals and further understand the genetic mechanisms underlying disease dynamics.

METHODS

The present study identified genomic regions associated with susceptibility to bTB using genome-wide association (GWA), regional heritability mapping (RHM) and chromosome association approaches. Phenotypes comprised de-regressed estimated breeding values of 804 Holstein-Friesian sires and pertained to three bTB indicator traits: i) positive reactors to the skin test with positive post-mortem examination results (phenotype 1); ii) positive reactors to the skin test regardless of post-mortem examination results (phenotype 2) and iii) as in (ii) plus non-reactors and inconclusive reactors to the skin tests with positive post-mortem examination results (phenotype 3). Genotypes based on the 50 K SNP DNA array were available and a total of 34,874 SNPs remained per animal after quality control.

RESULTS

The estimated polygenic heritability for susceptibility to bTB was 0.26, 0.37 and 0.34 for phenotypes 1, 2 and 3, respectively. GWA analysis identified a putative SNP on Bos taurus autosomes (BTA) 2 associated with phenotype 1, and another on BTA 23 associated with phenotype 2. Genomic regions encompassing these SNPs were found to harbour potentially relevant annotated genes. RHM confirmed the effect of these genomic regions and identified new regions on BTA 18 for phenotype 1 and BTA 3 for phenotypes 2 and 3. Heritabilities of the genomic regions ranged between 0.05 and 0.08 across the three phenotypes. Chromosome association analysis indicated a major role of BTA 23 on susceptibility to bTB.

CONCLUSION

Genomic regions and candidate genes identified in the present study provide an opportunity to further understand pathways critical to cattle susceptibility to bTB and enhance genetic improvement programmes aiming at controlling and eradicating the disease.

An across-breed genome wide association analysis of susceptibility to paratuberculosis in dairy cattle

Paratuberculosis is a chronic disease of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP). It occurs worldwide and causes a significant loss in the animal production industry. There is no cure for MAP infection and vaccination is problematic. Identification of genetics of susceptibility could be a useful adjunct for programs that focus on management, testing and culling of diseased animals. A case-control, genome-wide association study (GWAS) was conducted using Holstein and Jersey cattle in a combined analysis in order to identify markers and chromosomal regions associated with susceptibility to MAP infection across-breed. A mixed-model method (GRAMMAR-GC) implemented in the GenABEL R package and a Bayes C analysis implemented in GenSel software were used as alternative approaches to conduct GWAS analysis focused on single SNPs and chromosomal segments, respectively. After conducting quality control, 22 406 SNPs from 2157 individuals were available for the GRAMMAR-GC (Bayes C) analysis and 45 640 SNPs from 2199 individuals were available for the Bayes C analysis. One SNP located on BTA27 (8·6 Mb) was identified as moderately associated (P < 5 × 10-5, FDR = 0·44) in the GRAMMAR-GC analysis of the combined breed data. Nine 1 Mb windows located on BTA 2, 3 (3 windows), 6, 8, 25, 27 and 29 each explained ≥1% of the total proportion of genetic variance in the Bayes C analysis. In an analysis ignoring differences in linkage phase, two moderately significantly associated SNPs were identified; ARS-BFGL-NGS-19381 on BTA23 (32 Mb) and Hapmap40994-BTA-46361 on BTA19 (61 Mb). New common genomic regions and candidate genes have been identified from the across-breed analysis that might be involved in the immune response and susceptibility to MAP infection.

Predictive performance of genomic selection methods for carcass traits in Hanwoo beef cattle: impacts of the genetic architecture

Background

Hanwoo beef is known for its marbled fat, tenderness, juiciness and characteristic flavor, as well as for its low cholesterol and high omega 3 fatty acid contents. As yet, there has been no comprehensive investigation to estimate genomic selection accuracy for carcass traits in Hanwoo cattle using dense markers. This study aimed at evaluating the accuracy of alternative statistical methods that differed in assumptions about the underlying genetic model for various carcass traits: backfat thickness (BT), carcass weight (CW), eye muscle area (EMA), and marbling score (MS).

Methods

Accuracies of direct genomic breeding values (DGV) for carcass traits were estimated by applying fivefold cross-validation to a dataset including 1183 animals and approximately 34,000 single nucleotide polymorphisms (SNPs).

Results

Accuracies of BayesC, Bayesian LASSO (BayesL) and genomic best linear unbiased prediction (GBLUP) methods were similar for BT, EMA and MS. However, for CW, DGV accuracy was 7% higher with BayesC than with BayesL and GBLUP. The increased accuracy of BayesC, compared to GBLUP and BayesL, was maintained for CW, regardless of the training sample size, but not for BT, EMA, and MS. Genome-wide association studies detected consistent large effects for SNPs on chromosomes 6 and 14 for CW.

Conclusions

The predictive performance of the models depended on the trait analyzed. For CW, the results showed a clear superiority of BayesC compared to GBLUP and BayesL. These findings indicate the importance of using a proper variable selection method for genomic selection of traits and also suggest that the genetic architecture that underlies CW differs from that of the other carcass traits analyzed. Thus, our study provides significant new insights into the carcass traits of Hanwoo cattle.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-016-0283-0) contains supplementary material, which is available to authorized users.

Effective Population Size and Signatures of Selection Using Bovine 50K SNP Chips in Korean Native Cattle (Hanwoo)

Inferring the effective population size and the pattern of selection signatures is of interest both from an evolutionary perspective and to improve models for mapping of quantitative trait genes. We used DNA samples of 61 sires and 486 progeny of the Hanwoo, genotyped by the Illumina Bovine SNP50 BeadChip, to analyze the genetic structure. Our study showed a persistent decline in effective population size throughout the period considered, but suggested a marked decline at one distinctive time point (100th generation) and two sharp decline intervals (50th-25th generation and 25th-10th generation). This pattern can be explained by Hanwoo formation and the modern breeding program. Our results revealed 95 regions exhibiting the footprint of recent positive selection at a threshold level of 0.01. We found an overlap of the 11 core regions presenting top P-values and those that had previously been identified as harboring quantitative trait loci from other breeds. The information generated from this study can be used to better understand the mechanism of selection in Hanwoo breeding, and provide important implications for the design and application of association studies in the Hanwoo population.

Recent artificial selection in U.S. Jersey cattle impacts autozygosity levels of specific genomic regions

BACKGROUND

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.

RESULTS

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.

CONCLUSIONS

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.

Genome-wide scan of gastrointestinal nematode resistance in closed Angus population selected for minimized influence of MHC

Genetic markers associated with parasite indicator traits are ideal targets for study of marker assisted selection aimed at controlling infections that reduce herd use of anthelminthics. For this study, we collected gastrointestinal (GI) nematode fecal egg count (FEC) data from post-weaning animals of an Angus resource population challenged to a 26 week natural exposure on pasture. In all, data from 487 animals was collected over a 16 year period between 1992 and 2007, most of which were selected for a specific DRB1 allele to reduce the influence of potential allelic variant effects of the MHC locus. A genome-wide association study (GWAS) based on BovineSNP50 genotypes revealed six genomic regions located on bovine Chromosomes 3, 5, 8, 15 and 27; which were significantly associated (-log₁₀ p=4.3) with Box-Cox transformed mean FEC (BC-MFEC). DAVID analysis of the genes within the significant genomic regions suggested a correlation between our results and annotation for genes involved in inflammatory response to infection. Furthermore, ROH and selection signature analyses provided strong evidence that the genomic regions associated BC-MFEC have not been affected by local autozygosity or recent experimental selection. These findings provide useful information for parasite resistance prediction for young grazing cattle and suggest new candidate gene targets for development of disease-modifying therapies or future studies of host response to GI parasite infection.

A limited number of Y chromosome lineages is present in North American Holsteins

Holsteins are the most numerous dairy cattle breed in North America and the breed has undergone intensive selection for improving milk production and conformation. Theoretically, this intensive selection could lead to a reduction of the effective population size and reduced genetic diversity. The objective of this study was to investigate the effective population size of the Holstein Y chromosome and the effects of limited Y chromosome lineages on male reproduction and the future of the breed. Paternal pedigree information of 62,897 Holstein bulls born between 1950 and 2013 in North America and 220,872 bulls evaluated by multiple-trait across-country genetic evaluations of Interbull (Uppsala, Sweden) were collected and analyzed. The results indicated that the number of Y chromosome lineages in Holsteins has undergone a dramatic decrease during the past 50 years because of artificial selection and the application of artificial insemination (AI) technology. All current Holstein AI bulls in North America are the descendants of only 2 ancestors (Hulleman and Neptune H) born in 1880. These 2 ancestral Y-lineages are continued through 3 dominant pedigrees from the 1960s; namely, Pawnee Farm Arlinda Chief, Round Oak Rag Apple Elevation, and Penstate Ivanhoe Star, with a contribution of 48.78, 51.06, and 0.16% to the Holstein bull population in the 2010s, respectively. The Y-lineage of Penstate Ivanhoe Star is almost eliminated from the breed. The genetic variations in the 2 ancestral Y-lineages were evaluated among 257 bulls by determining the copy number variations (CNV) of 3 Y-linked gene families: PRAMEY, HSFY, and ZNF280BY, which are spread along the majority (95%) of the bovine Y chromosome male-specific region (MSY). No significant difference was found between the 2 ancestral Y-lineages, although large CNV were observed within each lineage. This study suggests minimal genetic diversity on the Y chromosome in Holsteins and provides a starting point for investigating the effect of the extremely limited number of Y-lineages on male reproduction and other traits important for the future of the Holstein breed.

Estimation of effective population size using single-nucleotide polymorphism (SNP) data in Jeju horse

This study was conducted to estimate the effective population size using SNPs data of 240 Jeju horses that had raced at the Jeju racing park. Of the total 61,746 genotyped autosomal SNPs, 17,320 (28.1%) SNPs (missing genotype rate of >10%, minor allele frequency of <0.05 and Hardy–Weinberg equilibrium test P-value of <10^–6) were excluded after quality control processes. SNPs on the X and Y chromosomes and genotyped individuals with missing genotype rate over 10% were also excluded, and finally, 44,426 (71.9%) SNPs were selected and used for the analysis. The measures of the LD, square of correlation coefficient (r²) between SNP pairs, were calculated for each allele and the effective population size was determined based on r² measures. The polymorphism information contents (PIC) and expected heterozygosity (HE) were 0.27 and 0.34, respectively. In LD, the most rapid decline was observed over the first 1 Mb. But r² decreased more slowly with increasing distance and was constant after 2 Mb of distance and the decline was almost linear with log-transformed distance. The average r² between adjacent SNP pairs ranged from 0.20 to 0.31 in each chromosome and whole average was 0.26, while the whole average r² between all SNP pairs was 0.02. We observed an initial pattern of decreasing N_e and estimated values were closer to 41 at 1 ~ 5 generations ago. The effective population size (41 heads) estimated in this study seems to be large considering Jeju horse’s population size (about 2,000 heads), but it should be interpreted with caution because of the technical limitations of the methods and sample size.

Genome-wide association study of susceptibility to infection by Mycobacterium avium subspecies paratuberculosis in Holstein cattle

Paratuberculosis, or Johne's disease, is a chronic, granulomatous, gastrointestinal tract disease of cattle and other ruminants caused by the bacterium Mycobacterium avium, subspecies paratuberculosis (MAP). Control of Johne's disease is based on programs of testing and culling animals positive for infection with MAP while concurrently modifying management to reduce the likelihood of infection. The current study is motivated by the hypothesis that genetic variation in host susceptibility to MAP infection can be dissected and quantifiable associations with genetic markers identified. For this purpose, a case-control, genome-wide association study was conducted using US Holstein cattle phenotyped for MAP infection using a serum ELISA and/or fecal culture test. Cases included cows positive for either serum ELISA, fecal culture or both. Controls consisted of animals negative for the serum ELISA test or both serum ELISA and fecal culture when both were available. Controls were matched by herd and proximal birth date with cases. A total of 856 cows (451 cases and 405 controls) were used in initial discovery analyses, and an additional 263 cows (159 cases and 104 controls) from the same herds were used as a validation data set. Data were analyzed in a single marker analysis controlling for relatedness of individuals (GRAMMAR-GC) and also in a Bayesian analysis in which multiple marker effects were estimated simultaneously (GenSel). For the latter, effects of non-overlapping 1 Mb marker windows across the genome were estimated. Results from the two discovery analyses were generally concordant; however, discovery results were generally not well supported in analysis of the validation data set. A combined analysis of discovery and validation data sets provided strongest support for SNPs and 1 Mb windows on chromosomes 1, 2, 6, 7, 17 and 29.

Linkage disequilibrium and haplotype block structure in a composite beef cattle breed

Background

The development of linkage disequilibrium (LD) maps and the characterization of haplotype block structure at the population level are useful parameters for guiding genome wide association (GWA) studies, and for understanding the nature of non-linear association between phenotypes and genes. The elucidation of haplotype block structure can reduce the information of several single nucleotide polymorphisms (SNP) into the information of a haplotype block, reducing the number of SNPs in a coherent way for consideration in GWA and genomic selection studies.

Results

The maximum average LD, measured by r² varied between 0.33 to 0.40 at a distance of < 2.5 kb, and the minimum average values of r² varied between 0.05 to 0.07 at distances ranging from 400 to 500 kb, clearly showing that the average r² reduced with the increase in SNP pair distances. The persistence of LD phase showed higher values at shorter genomic distances, decreasing with the increase in physical distance, varying from 0.96 at a distance of < 2.5 kb to 0.66 at a distance from 400 to 500 kb. A total of 78% of all SNPs were clustered into haplotype blocks, covering 1,57 Mb of the total autosomal genome size.

Conclusions

This study presented the first high density linkage disequilibrium map and haplotype block structure for a composite beef cattle population, and indicates that the high density SNP panel over 700 k can be used for genomic selection implementation and GWA studies for Canchim beef cattle.

Linkage Disequilibrium Estimation of Chinese Beef Simmental Cattle Using High-density SNP Panels

Linkage disequilibrium (LD) plays an important role in genomic selection and mapping quantitative trait loci (QTL). In this study, the pattern of LD and effective population size (N_e) were investigated in Chinese beef Simmental cattle. A total of 640 bulls were genotyped with IlluminaBovinSNP50BeadChip and IlluminaBovinHDBeadChip. We estimated LD for each autosomal chromosome at the distance between two random SNPs of <0 to 25 kb, 25 to 50 kb, 50 to 100 kb, 100 to 500 kb, 0.5 to 1 Mb, 1 to 5 Mb and 5 to 10 Mb. The mean values of r² were 0.30, 0.16 and 0.08, when the separation between SNPs ranged from 0 to 25 kb to 50 to 100 kb and then to 0.5 to 1 Mb, respectively. The LD estimates decreased as the distance increased in SNP pairs, and increased with the increase of minor allelic frequency (MAF) and with the decrease of sample sizes. Estimates of effective population size for Chinese beef Simmental cattle decreased in the past generations and N_e was 73 at five generations ago.

Accuracy of imputation to whole-genome sequence data in Holstein Friesian cattle

Background

The use of whole-genome sequence data can lead to higher accuracy in genome-wide association studies and genomic predictions. However, to benefit from whole-genome sequence data, a large dataset of sequenced individuals is needed. Imputation from SNP panels, such as the Illumina BovineSNP50 BeadChip and Illumina BovineHD BeadChip, to whole-genome sequence data is an attractive and less expensive approach to obtain whole-genome sequence genotypes for a large number of individuals than sequencing all individuals. Our objective was to investigate accuracy of imputation from lower density SNP panels to whole-genome sequence data in a typical dataset for cattle.

Methods

Whole-genome sequence data of chromosome 1 (1737 471 SNPs) for 114 Holstein Friesian bulls were used. Beagle software was used for imputation from the BovineSNP50 (3132 SNPs) and BovineHD (40 492 SNPs) beadchips. Accuracy was calculated as the correlation between observed and imputed genotypes and assessed by five-fold cross-validation. Three scenarios S40, S60 and S80 with respectively 40%, 60%, and 80% of the individuals as reference individuals were investigated.

Results

Mean accuracies of imputation per SNP from the BovineHD panel to sequence data and from the BovineSNP50 panel to sequence data for scenarios S40 and S80 ranged from 0.77 to 0.83 and from 0.37 to 0.46, respectively. Stepwise imputation from the BovineSNP50 to BovineHD panel and then to sequence data for scenario S40 improved accuracy per SNP to 0.65 but it varied considerably between SNPs.

Conclusions

Accuracy of imputation to whole-genome sequence data was generally high for imputation from the BovineHD beadchip, but was low from the BovineSNP50 beadchip. Stepwise imputation from the BovineSNP50 to the BovineHD beadchip and then to sequence data substantially improved accuracy of imputation. SNPs with a low minor allele frequency were more difficult to impute correctly and the reliability of imputation varied more. Linkage disequilibrium between an imputed SNP and the SNP on the lower density panel, minor allele frequency of the imputed SNP and size of the reference group affected imputation reliability.

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.

Transcriptome analysis and SNP identification in SCC of horn in (Bos indicus) Indian cattle

Single Nucleotide Polymorphisms (SNPs) have become the marker of choice for genome wide association studies. In order to provide the best genome coverage for the analysis of disease, production and performance traits, a large number of relatively evenly distributed SNPs are needed. The main objective of present work was to identify large numbers of gene-associated SNPs using high-throughput sequencing in squamous cell carcinoma of horn. RNA-seq analysis was conducted on 2 tissues viz. Horn Cancer (HC) and Horn Normal (HN) in Kankrej breed of cattle. A total of 909,362 reads with average read length of 405 bp for HC and 583,491 reads with average read length of 411 bp for HN were obtained. We found 9532 and 7065 SNPs as well as 1771 and 1172 Indels in HC and HN, respectively, from which, 7889 SNPs and 1736 Indels were uniquely present in HC, 5886 SNPs and 1146 Indels were uniquely present in HN and reported first time in Bos indicus, whereas the rest are already reported in Bos taurus dbSNP database. The gene-associated SNPs and Indels were high in upregulated genes of HC as compared to HN. Analysis of differentially expressed genes was identified, these genes are involved in regulation of cell proliferation, apoptosis, gene transcription, cell survival and metabolism through various metabolic pathways. The result of transcriptome expression profiling was validated using Real Time quantitative PCR in nine randomly selected genes. We identified numbers aberrant signaling pathways responsible for carcinogenesis in HC which are also commonly altered in squamous cell carcinoma (SCC) of lung in human being. We conclude that a large number of altered genes and dysfunction of multiple pathways are involved in the development of Horn Cancer. The present findings contribute to theoretical information for further screening of genes and identification of markers for early diagnosis of HC as well as SNPs identified in this report provide a much needed resource for genetic studies in B. indicus and shall contribute to the development of a high density SNP array. Validation and testing of these SNPs using SNP arrays will form the material basis for gene associated SNPs in HC.

Genome-wide linkage disequilibrium in the Blonde d'Aquitaine cattle breed

We present here the first genome-wide characterization of linkage disequilibrium (LD) in the French Blonde d'Aquitaine (BLA) breed, a well-muscled breed renowned for producing high-yielding beef carcasses. To assess the pattern and extent of LD, we used a sample of 30 unrelated bulls and 36 923 single nucleotide polymorphisms (SNPs) covering all cattle autosomes. The squared correlation of the alleles at two loci (r(2) ) was used as a measure of LD. The analysis of adjacent marker pairs revealed that the level of LD decreases rapidly with physical distance between SNPs. Overall mean r(2) was 0.205 (±0.262). Strong LD (r(2)  > 0.8) and useful LD (measured as r(2 ) > 0.2) were observed within genomic regions of up to 720 and 724 kb, respectively. We analysed the genetic structure of the BLA population and found stratification. The observed genetic sub-structuring is consistent with the known recent demographic history that occurred during BLA breed formation. Our results indicate that LD mapping of phenotypic traits in the BLA population is feasible; however, because of this sub-structuring, special care is needed to reduce the likelihood of false-positive associations between marker loci and traits of interest.

Inferring demography from runs of homozygosity in whole-genome sequence, with correction for sequence errors

Whole-genome sequence is potentially the richest source of genetic data for inferring ancestral demography. However, full sequence also presents significant challenges to fully utilize such large data sets and to ensure that sequencing errors do not introduce bias into the inferred demography. Using whole-genome sequence data from two Holstein cattle, we demonstrate a new method to correct for bias caused by hidden errors and then infer stepwise changes in ancestral demography up to present. There was a strong upward bias in estimates of recent effective population size (Ne) if the correction method was not applied to the data, both for our method and the Li and Durbin (Inference of human population history from individual whole-genome sequences. Nature 475:493-496) pairwise sequentially Markovian coalescent method. To infer demography, we use an analytical predictor of multiloci linkage disequilibrium (LD) based on a simple coalescent model that allows for changes in Ne. The LD statistic summarizes the distribution of runs of homozygosity for any given demography. We infer a best fit demography as one that predicts a match with the observed distribution of runs of homozygosity in the corrected sequence data. We use multiloci LD because it potentially holds more information about ancestral demography than pairwise LD. The inferred demography indicates a strong reduction in the Ne around 170,000 years ago, possibly related to the divergence of African and European Bos taurus cattle. This is followed by a further reduction coinciding with the period of cattle domestication, with Ne of between 3,500 and 6,000. The most recent reduction of Ne to approximately 100 in the Holstein breed agrees well with estimates from pedigrees. Our approach can be applied to whole-genome sequence from any diploid species and can be scaled up to use sequence from multiple individuals.

Population parameters incorporated into genome-wide tagSNP selection

Single nucleotide polymorphisms (SNPs) are the most widespread source of variation in genomes. While the very large number of SNPs allows for a very precise description of genetic variation, it impedes data processing and significantly increases analysis time. Many of the SNPs located close to each other frequently carry the same or similar information. This problem can be solved by selecting the most informative SNPs (tagSNPs) using linkage disequilibrium information by identifying a set of tagSNPs representative for a chromosome fragment. The goal of this study is to check whether the genetic structure of a population, expressed by relationship and inbreeding coefficients, affects tagSNP selection. Six subsets of 450 bulls are selected out of the 1228 Polish Holstein-Friesian bulls genotyped by the Illumina BovineSNP50 Bead Chip. TagSNPs are selected for each of the subsets, as well as for the whole data set. The average reduction of the SNP number is 77.2% and is very similar in each sub-population. Differences in tagSNP selection between sub-populations are small. On average, 93.88% of the tagSNPs overlap between subsets. The study showed that differences in the genetic structure of the reference population have little influence on tagSNP selection.

Inferring quantitative trait pathways associated with bull fertility from a genome-wide association study

Whole-genome association studies typically focus on genetic markers with the strongest evidence of association. However, single markers often explain only a small component of the genetic variance and hence offer a limited understanding of the trait under study. As such, the objective of this study was to perform a pathway-based association analysis in Holstein dairy cattle in order to identify relevant pathways involved in bull fertility. The results of a single-marker association analysis, using 1,755 bulls with sire conception rate data and genotypes for 38,650 single nucleotide polymorphisms (SNPs), were used in this study. A total of 16,819 annotated genes, including 2,767 significantly associated with bull fertility, were used to interrogate a total of 662 Gene Ontology (GO) terms and 248 InterPro (IP) entries using a test of proportions based on the cumulative hypergeometric distribution. After multiple-testing correction, 20 GO categories and one IP entry showed significant overrepresentation of genes statistically associated with bull fertility. Several of these functional categories such as small GTPases mediated signal transduction, neurogenesis, calcium ion binding, and cytoskeleton are known to be involved in biological processes closely related to male fertility. These results could provide insight into the genetic architecture of this complex trait in dairy cattle. In addition, this study shows that quantitative trait pathways inferred from single-marker analyses could enhance our interpretations of the results of genome-wide association studies.

Genome-wide association study identifies candidate markers for bull fertility in Holstein dairy cattle

The decline in the reproductive efficiency of dairy cattle has become a challenging problem worldwide. Female fertility is now taken into account in breeding goals while generally less attention is given to male fertility. The objective of this study was to perform a genome-wide association study in Holstein bulls to identify genetic variants significantly related to sire conception rate (SCR), a new phenotypic evaluation of bull fertility. The analysis included 1755 sires with SCR data and 38,650 single nucleotide polymorphisms (SNPs) spanning the entire bovine genome. Associations between SNPs and SCR were analyzed using a mixed linear model that included a random polygenic effect and SNP genotype either as a linear covariate or as a categorical variable. A multiple testing correction approach was used to account for the correlation between SNPs because of linkage disequilibrium. After genome-wide correction, eight SNPs showed significant association with SCR. Some of these SNPs are located close to or in the middle of genes with functions related to male fertility, such as the sperm acrosome reaction, chromatin remodeling during the spermatogenesis, and the meiotic process during male germ cell maturation. Some SNPs showed marked dominance effects, which provide more evidence for the relevance of non-additive effects in traits closely related to fitness such as fertility. The results could contribute to the identification of genes and pathways associated with male fertility in dairy cattle.

Genome-wide association identifies multiple genomic regions associated with susceptibility to and control of ovine lentivirus

BACKGROUND

Like human immunodeficiency virus (HIV), ovine lentivirus (OvLV) is macrophage-tropic and causes lifelong infection. OvLV infects one quarter of U.S. sheep and induces pneumonia and body condition wasting. There is no vaccine to prevent OvLV infection and no cost-effective treatment for infected animals. However, breed differences in prevalence and proviral concentration have indicated a genetic basis for susceptibility to OvLV. A recent study identified TMEM154 variants in OvLV susceptibility. The objective here was to identify additional loci associated with odds and/or control of OvLV infection.

METHODOLOGY/PRINCIPAL FINDINGS

This genome-wide association study (GWAS) included 964 sheep from Rambouillet, Polypay, and Columbia breeds with serological status and proviral concentration phenotypes. Analytic models accounted for breed and age, as well as genotype. This approach identified TMEM154 (nominal P=9.2×10(-7); empirical P=0.13), provided 12 additional genomic regions associated with odds of infection, and provided 13 regions associated with control of infection (all nominal P<1 × 10(-5)). Rapid decline of linkage disequilibrium with distance suggested many regions included few genes each. Genes in regions associated with odds of infection included DPPA2/DPPA4 (empirical P=0.006), and SYTL3 (P=0.051). Genes in regions associated with control of infection included a zinc finger cluster (ZNF192, ZSCAN16, ZNF389, and ZNF165; P=0.001), C19orf42/TMEM38A (P=0.047), and DLGAP1 (P=0.092).

CONCLUSIONS/SIGNIFICANCE

These associations provide targets for mutation discovery in sheep susceptibility to OvLV. Aside from TMEM154, these genes have not been associated previously with lentiviral infection in any species, to our knowledge. Further, data from other species suggest functional hypotheses for future testing of these genes in OvLV and other lentiviral infections. Specifically, SYTL3 binds and may regulate RAB27A, which is required for enveloped virus assembly of human cytomegalovirus. Zinc finger transcription factors have been associated with positive selection for repression of retroviral replication. DLGAP1 binds and may regulate DLG1, a known regulator of HIV infectivity.

The value of cows in reference populations for genomic selection of new functional traits

Today, almost all reference populations consist of progeny tested bulls. However, older progeny tested bulls do not have reliable estimated breeding values (EBV) for new traits. Thus, to be able to select for these new traits, it is necessary to build a reference population. We used a deterministic prediction model to test the hypothesis that the value of cows in reference populations depends on the availability of phenotypic records. To test the hypothesis, we investigated different strategies of building a reference population for a new functional trait over a 10-year period. The trait was either recorded on a large scale (30 000 cows per year) or on a small scale (2000 cows per year). For large-scale recording, we compared four scenarios where the reference population consisted of 30 sires; 30 sires and 170 test bulls; 30 sires and 2000 cows; or 30 sires, 2000 cows and 170 test bulls in the first year with measurements of the new functional trait. In addition to varying the make-up of the reference population, we also varied the heritability of the trait (h2 = 0.05 v. 0.15). The results showed that a reference population of test bulls, cows and sires results in the highest accuracy of the direct genomic values (DGV) for a new functional trait, regardless of its heritability. For small-scale recording, we compared two scenarios where the reference population consisted of the 2000 cows with phenotypic records or the 30 sires of these cows in the first year with measurements of the new functional trait. The results showed that a reference population of cows results in the highest accuracy of the DGV whether the heritability is 0.05 or 0.15, because variation is lost when phenotypic data on cows are summarized in EBV of their sires. The main conclusions from this study are: (i) the fewer phenotypic records, the larger effect of including cows in the reference population; (ii) for small-scale recording, the accuracy of the DGV will continue to increase for several years, whereas the increases in the accuracy of the DGV quickly decrease with large-scale recording; (iii) it is possible to achieve accuracies of the DGV that enable selection for new functional traits recorded on a large scale within 3 years from commencement of recording; and (iv) a higher heritability benefits a reference population of cows more than a reference population of bulls.

Linkage disequilibrium in Angus, Charolais, and Crossbred beef cattle

Linkage disequilibrium (LD) and the persistence of its phase across populations are important for genomic selection as well as fine scale mapping of quantitative trait loci (QTL). However, knowledge of LD in beef cattle, as well as the persistence of LD phase between crossbreds (C) and purebreds, is limited. The objective of this study was to understand the patterns of LD in Angus (AN), Charolais (CH), and C beef cattle based on 31,073, 32,088, and 33,286 SNP in each population, respectively. Amount of LD decreased rapidly from 0.29 to 0.23 to 0.19 in AN, 0.22 to 0.16 to 0.12 in CH, 0.21 to 0.15 to 0.11 in C, when the distance range between markers changed from 0-30 kb to 30-70 kb and then to 70-100 kb, respectively. Breeds and chromosomes had significant effects (P < 0.001) on LD decay. There was significant interaction between breeds and chromosomes (P < 0.001). Correlations of LD phase were high between C and AN (0.84), C and CH (0.81), as well as between AN and CH (0.77) for distances less than or equal to 70 kb. These dropped when the distance increased. Estimated effective population sizes for AN and CH were 207 and 285, respectively, for 10 generations ago. Given a useful LD of at least 0.3 between pairs of SNPs, the LD phase between any pair of the three breed groups was highly persistent. The current SNP density would allow the capture of approximately 49% of useful LD between SNP and marker QTL in AN, and 38% in CH. A higher density SNP panel or redesign of the current panel is needed to achieve more of useful LD for the purpose of genomic selection beef cattle.

Linkage disequilibrium and inbreeding estimation in Spanish Churra sheep

Background

Genomic technologies, such as high-throughput genotyping based on SNP arrays, have great potential to decipher the genetic architecture of complex traits and provide background information concerning genome structure in domestic animals, including the extent of linkage disequilibrium (LD) and haplotype blocks. The objective of this study was to estimate LD, the population evolution (past effective population size) and the level of inbreeding in Spanish Churra sheep.

Results

A total of 43,784 SNPs distributed in the ovine autosomal genome was analyzed in 1,681 Churra ewes. LD was assessed by measuring r² between all pairs of loci. For SNPs up to 10 kb apart, the average r² was 0.329; for SNPs separated by 200–500 kb the average r² was 0.061. When SNPs are separated by more than 50 Mbp, the average r² is the same as between non-syntenic SNP pairs (0.003). The effective population size has decreased through time, faster from 1,000 to 100 years ago and slower since the selection scheme started (15–25 generations ago). In the last generation, four years ago, the effective population size was estimated to be 128 animals. Inbreeding coefficients, although differed depending on the estimation approaches, were generally low and showed the same trend, which indicates that since 2003, inbreeding has been slightly increasing in the studied resource population.

Conclusions

The extent of LD in Churra sheep persists over much more limited distances than reported in dairy cattle and seems to be similar to other ovine populations. Churra sheep show a wide genetic base, with a long-term viable effective population size that has been slightly decreasing since selection scheme began in 1986. The genomic dataset analyzed provided useful information for identifying low-level inbreeding in the sample, whereas based on the parameters reported here, a higher marker density than that analyzed here will be needed to successfully conduct accurate mapping of genes underlying production traits and genomic selection prediction in this sheep breed. Although the Ovine Assembly development is still in a draft stage and future refinements will provide a more accurate physical map that will improve LD estimations, this work is a first step towards the understanding of the genetic architecture in sheep.

[Chinese Holstein Cattle effective population size estimated from whole genome linkage disequilibrium]

Effective populations size (Ne) is an important population parameter that helps to explain genetic variation, population evolution and understanding of the genetic architecture underlying complex traits. With the availability of high-dense SNP panels, more and more researches focus on estimating of Ne using linkage disequilibrium (LD) between SNPs. In this study, we estimated the effective population size from 2093 Chinese Holstein Cattle genotyped with Illumina BovineSNP50 BeadChip. After removal of individual with call rate lt; 95%, SNPs with call rate lt; 95%, minor allele frequency lt; 5% and Hardy-Weinberg Equilibrium test with Plt;0.0001, 1 968 individuals with 38 796 SNPs were remained. Eight kinds of SNP pairs with the distances 0.1, 0.2, 0.5, 1, 2, 5, 10, and 15 Mb were respectively chosen to estimate the effective population size of Chinese Holstein cattle from 4 generations ago. It is demonstrated from the results of this study that the effective population size of Chinese Holstein is decreased in the past generations, and the corresponding effective population size at ~4 generations ago is only around 45.

Maximum likelihood estimation of linkage disequilibrium in half-sib families

Maximum likelihood methods for the estimation of linkage disequilibrium between biallelic DNA-markers in half-sib families (half-sib method) are developed for single and multifamily situations. Monte Carlo computer simulations were carried out for a variety of scenarios regarding sire genotypes, linkage disequilibrium, recombination fraction, family size, and number of families. A double heterozygote sire was simulated with recombination fraction of 0.00, linkage disequilibrium among dams of δ=0.10, and alleles at both markers segregating at intermediate frequencies for a family size of 500. The average estimates of δ were 0.17, 0.25, and 0.10 for Excoffier and Slatkin (1995), maternal informative haplotypes, and the half-sib method, respectively. A multifamily EM algorithm was tested at intermediate frequencies by computer simulation. The range of the absolute difference between estimated and simulated δ was between 0.000 and 0.008. A cattle half-sib family was genotyped with the Illumina 50K BeadChip. There were 314,730 SNP pairs for which the sire was a homo-heterozygote with average estimates of r2 of 0.115, 0.067, and 0.111 for half-sib, Excoffier and Slatkin (1995), and maternal informative haplotypes methods, respectively. There were 208,872 SNP pairs for which the sire was double heterozygote with average estimates of r2 across the genome of 0.100, 0.267, and 0.925 for half-sib, Excoffier and Slatkin (1995), and maternal informative haplotypes methods, respectively. Genome analyses for all possible sire genotypes with 829,042 tests showed that ignoring half-sib family structure leads to upward biased estimates of linkage disequilibrium. Published inferences on population structure and evolution of cattle should be revisited after accommodating existing half-sib family structure in the estimation of linkage disequilibrium.

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation

Background

Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction.

Methods

Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values.

Results

Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied.

Conclusions

These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy.

Accuracy of genomic selection in simulated populations mimicking the extent of linkage disequilibrium in beef cattle

Background

The success of genomic selection depends mainly on the extent of linkage disequilibrium (LD) between markers and quantitative trait loci (QTL), the number of animals in the training set (TS) and the heritability (h²) of the trait. The extent of LD depends on the genetic structure of the population and the density of markers. The aim of this study was to calculate accuracy of direct genomic estimated breeding values (DGEBV) using best linear unbiased genomic prediction (GBLUP) for different marker densities, heritabilities and sizes of the TS in simulated populations that mimicked previously reported extent and pattern of LD in beef cattle.

Results

The accuracy of DGEBV increased significantly (p < 0.05) with the increase in the number of bulls in the TS (480, 960 or 1920), trait h² (0.10, 0.25 or 0.40) and marker densities (40 k or 800 k). Increasing the number of animals in the TS by 4-fold and using their phenotypes to estimate marker effects was not sufficient to maintain or increase the accuracy of DGEBV obtained using estimated breeding values (EBVs) when the trait h² was lower than 0.40 for both marker densities. Comparing to expected accuracies of parent average (PA), the gains by using DGEBV would be of 27%, 13% and 10% for trait h² equal to 0.10, 0.25 and 0.40, respectively, considering the scenario with 40 k markers and 1920 bulls in TS.

Conclusions

As reported in dairy cattle, the size of the TS and the extent of LD have major impact on the accuracy of DGEBV. Based on the findings of this simulation study, large TS, as well as dense marker panels, aiming to increase the level of LD between markers and QTL, will likely be needed in beef cattle for successful implementation of genomic selection.