F.S. Schenkel

Invited review: reliability of genomic predictions for North American Holstein bulls.

Genetic progress will increase when breeders examine genotypes in addition to pedigrees and phenotypes. Genotypes for 38,416 markers and August 2003 genetic evaluations for 3,576 Holstein bulls born before 1999 were used to predict January 2008 daughter deviations for 1,759 bulls born from 1999 through 2002. Genotypes were generated using the Illumina BovineSNP50 BeadChip and DNA from semen contributed by US and Canadian artificial-insemination organizations to the Cooperative Dairy DNA Repository. Genomic predictions for 5 yield traits, 5 fitness traits, 16 conformation traits, and net merit were computed using a linear model with an assumed normal distribution for marker effects and also using a nonlinear model with a heavier tailed prior distribution to account for major genes. The official parent average from 2003 and a 2003 parent average computed from only the subset of genotyped ancestors were combined with genomic predictions using a selection index. Combined predictions were more accurate than official parent averages for all 27 traits. The coefficients of determination (R(2)) were 0.05 to 0.38 greater with nonlinear genomic predictions included compared with those from parent average alone. Linear genomic predictions had R(2) values similar to those from nonlinear predictions but averaged just 0.01 lower. The greatest benefits of genomic prediction were for fat percentage because of a known gene with a large effect. The R(2) values were converted to realized reliabilities by dividing by mean reliability of 2008 daughter deviations and then adding the difference between published and observed reliabilities of 2003 parent averages. When averaged across all traits, combined genomic predictions had realized reliabilities that were 23% greater than reliabilities of parent averages (50 vs. 27%), and gains in information were equivalent to 11 additional daughter records. Reliability increased more by doubling the number of bulls genotyped than the number of markers genotyped. Genomic prediction improves reliability by tracing the inheritance of genes even with small effects.

QMSim: A large scale genome simulator for livestock

SUMMARY QMSim was designed to simulate large-scale genotyping data in multiple and complex livestock pedigrees. The simulation is basically carried out in two steps. In the first step, a historical population is simulated to establish mutation-drift equilibrium, and in the second step, recent population structures are generated, which can be very complex. A wide variety of genome architectures, ranging from infinitesimal model to single-locus model, can be simulated. The program is efficient in terms of computing time and memory requirements. AVAILABILITY Executable versions of QMSim for Windows and Linux are freely available at http://www.aps.uoguelph.ca/~msargol/qmsim/.

A Genome Scan to Detect Quantitative Trait Loci for Economically Important Traits in Holstein Cattle Using Two Methods and a Dense Single Nucleotide Polymorphism Map

Genome scans for detection of bovine quantitative trait loci (QTL) were performed via variance component linkage analysis and linkage disequilibrium single-locus regression (LDRM). Four hundred eighty-four Holstein sires, of which 427 were from 10 grandsire families, were genotyped for 9,919 single nucleotide polymorphisms (SNP) using the Affymetrix MegAllele GeneChip Bovine Mapping 10K SNP array. A hybrid of the grand-daughter and selective genotyping designs was applied. Four thousand eight hundred fifty-six of the 9,919 SNP were located to chromosomes in base-pairs and formed the basis for the analyses. The mean polymorphism information content of the SNP was 0.25. The SNP centimorgan position was interpolated from their base-pair position using a microsatellite framework map. Estimated breeding values were used as observations, and the following traits were analyzed: 305-d lactation milk, fat, and protein yield; somatic cell score; herd life; interval of calving to first service; and age at first service. The variance component linkage analysis detected 102 potential QTL, whereas LDRM analysis found 144 significant SNP associations after accounting for a 5% false discovery rate. Twenty potential QTL and 49 significant SNP associations were in close proximity to QTL cited in the literature. Both methods found significant regions on Bos taurus autosome (BTA) 3, 5, and 16 for milk yield; BTA 14 and 19 for fat yield; BTA 1, 3, 16, and 28 for protein yield; BTA 2 and 13 for calving to first service; and BTA 14 for age at first service. Both approaches were effective in detecting potential QTL with a dense SNP map. The LDRM was well suited for a first genome scan due to its approximately 8 times lower computational demands. Further fine mapping should be applied on the chromosomal regions of interest found in this study.

Selection of single-nucleotide polymorphisms and quality of genotypes used in genomic evaluation of dairy cattle in the United States and Canada

Nearly 57,000 single-nucleotide polymorphisms (SNP) genotyped with the Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA) were investigated to determine usefulness of the associated SNP for genomic prediction. Genotypes were obtained for 12,591 bulls and cows, and SNP were selected based on 5,503 bulls with genotypes from a larger set of SNP. The following SNP were deleted: 6,572 that were monomorphic, 3,213 with scoring problems (primarily because of poor definition of clusters and excess number of clusters), and 3,649 with a minor allele frequency of <2%. Number of SNP for each minor allele frequency class (> or =2%) was fairly uniform (777 to 1,004). For 5 contiguous SNP assigned to chromosome 7, no bulls were heterozygous, which indicated that those SNP are actually on the nonpseudoautosomal portion of the X chromosome. Another 178 SNP that were not assigned to a chromosome but that had many fewer heterozygotes than expected were also assigned to the X chromosome. Existence of Hardy-Weinberg equilibrium was investigated by comparing observed with expected heterozygosity. For 11 SNP, the observed percentage of heterozygous individuals differed from the expected by >15%; therefore, those SNP were deleted. For 2,628 SNP, the genotype at another SNP was highly correlated (i.e., genotypes were identical for >99.5% of bulls), and those were deleted. After edits, 40,874 SNP remained. A parent-progeny conflict was declared when the genotypes were alternate homozygotes. Mean number of conflicts was 2.3 when pedigree was correct and 2,411 when it was incorrect. The sire was genotyped for >93% of animals. Maternal grandsire genotype was similarly checked; however, because alternate homozygotes could be valid, a conflict threshold of 16% was used to indicate a need for further investigation. Genotyping consistency was investigated for 21 bulls genotyped twice with differences primarily from SNP that were not scored in one of the genotypes. Concordance for readable SNP was extremely high (99.96-100%). Thousands of SNP that were polymorphic in Holsteins were monomorphic in Jerseys or Brown Swiss, which indicated that breed-specific SNP sets are required or that all breeds need to be considered in the SNP selection process. Genotypes from the Illumina BovineSNP50 BeadChip are of high accuracy and provide the basis for genomic evaluations in the United States and Canada.

Assessing feed efficiency in beef steers through feeding behavior, infrared thermography and glucocorticoids*

A better understanding of the factors regulating feed efficiency and their potential as predictors of feed efficiency in cattle is needed. Therefore, the potential of three classes of traits, namely, feeding behavior characteristics: daily time at feeder (TF; min/day), time per meal (TM; min), meal size (MS; g DM), eating rate (ER; g DM/min), number of daily meals (NM) and daily visits to the feeder (VF); infrared (IR) thermography traits (°C): eye (EY), cheek (CK), snout (SN), ribs (RB) and hind area (HA); and glucocorticoid levels: fecal cortisol metabolites (FCM; ng/g) and plasma cortisol (PC; ng/ml) as predictors of efficiency were evaluated in 91 steers (436 ± 37 kg) over 2 years (Y1 = 46; Y2 = 45). Additionally, the individual traits of each of these three classes were combined to define three single traits. Individual daily feed intake of a corn silage and high-moisture corn-based diet was measured using an automated feeding system. Body weight and thermographs were taken every 28 days over a period of 140 days. Four productive performance traits were calculated: daily dry matter intake (DMI), average daily gain (ADG), feed to gain ratio (F : G) and residual feed intake (RFI). Steers were also classified into three RFI categories (low-, medium- and high-RFI). Among the feeding behavior characteristics, MS and ER were correlated with all efficiency traits (range: 0.26 to 0.75). Low-RFI (more efficient steers) had smaller MS, lower ER and fewer VF in comparison to high-RFI steers. Less efficient steers (high-RFI) performed more VF during the nocturnal period than more efficient steers. More efficient steers had lower CK and SN temperatures than less efficient steers (28.1°C v. 29.2°C and 30.0°C v. 31.2°C), indicating greater energetic efficiency for low-RFI steers. In terms of glucocorticoids, PC was not correlated with efficiency traits. In contrast, more efficient steers had higher FCM in comparison to less efficient steers (51.1 v. 31.2 ng/g), indicating that a higher cortisol baseline is related to better feed efficiency. The overall evaluation of the three classes of traits revealed that feeding behavior, IR thermography and glucocorticoids accounted for 18%, 59% and 7% of the total variation associated with RFI, respectively. These classes of traits have usefulness in the indirect assessment of feed efficiency in cattle. Among them, IR thermography was the most promising alternative to screen cattle for this feed efficiency. These findings might have application in selection programs and in the better understanding of the biological basis associated with productive performance.

A principal component regression based genome wide analysis approach reveals the presence of a novel QTL on BTA7 for MAP resistance in holstein cattle.

Bovine Johnes disease (JD), caused by Mycobacterium avium spp. paratuberculosis (MAP), causes significant losses to the dairy and beef cattle industries. Effective vaccination or therapeutic strategies against this disease are currently unavailable and infected animals either get culled or die due to clinical disease. An alternative strategy to manage the disease is to selectively breed animals with enhanced resistance to MAP infection. Therefore, the objective of this study was to identify genetic loci putatively associated with MAP infection in a resource population consisting of Holstein cattle using a genome-wide association approach. The BovineSNP50 BeadChip, containing 54,001 single nucleotide polymorphisms (SNPs), was used to genotype 232 animals with known MAP infection status. Since, traditional case-control analytical techniques are based on single-marker analysis and do not account for the existence of linkage disequilibrium (LD) between markers, we used a novel principal component regression approach, where each SNP was fit in a logistic regression model, along with principal components of other SNPs on the same chromosome showing association with the trait, as covariates. Such an approach allowed us to account for the LD that exists between multiple markers showing an association on the same chromosome. Our analysis revealed the presence of at least 12 genomic regions on BTA1, 5, 6, 7, 10, 11 and 14 that were associated with the MAP infection status of our resource population. A brief description of these genomic regions, and a discussion of the analysis used in this study, have been presented.

Genome-wide association study for birth weight in Nellore cattle points to previously described orthologous genes affecting human and bovine height

BackgroundBirth weight (BW) is an economically important trait in beef cattle, and is associated with growth- and stature-related traits and calving difficulty. One region of the cattle genome, located on Bos primigenius taurus chromosome 14 (BTA14), has been previously shown to be associated with stature by multiple independent studies, and contains orthologous genes affecting human height. A genome-wide association study (GWAS) for BW in Brazilian Nellore cattle (Bos primigenius indicus) was performed using estimated breeding values (EBVs) of 654 progeny-tested bulls genotyped for over 777,000 single nucleotide polymorphisms (SNPs).ResultsThe most significant SNP (rs133012258, PGC = 1.34 × 10-9), located at BTA14:25376827, explained 4.62% of the variance in BW EBVs. The surrounding 1 Mb region presented high identity with human, pig and mouse autosomes 8, 4 and 4, respectively, and contains the orthologous height genes PLAG1, CHCHD7, MOS, RPS20, LYN, RDHE2 (SDR16C5) and PENK. The region also overlapped 28 quantitative trait loci (QTLs) previously reported in literature by linkage mapping studies in cattle, including QTLs for birth weight, mature height, carcass weight, stature, pre-weaning average daily gain, calving ease, and gestation length.ConclusionsThis study presents the first GWAS applying a high-density SNP panel to identify putative chromosome regions affecting birth weight in Nellore cattle. These results suggest that the QTLs on BTA14 associated with body size in taurine cattle (Bos primigenius taurus) also affect birth weight and size in zebu cattle (Bos primigenius indicus).

Health recording in Canadian Holsteins: Data and genetic parameters

The objective of this study was to investigate if health data recorded by Canadian dairy producers can be used for genetic selection. Eight diseases are recorded by producers on a voluntary basis: mastitis, displaced abomasum, ketosis, milk fever, retained placenta, metritis, cystic ovaries, and lameness. Between 40 to 60% of all herds had to be excluded by editing procedures for each trait, assuming unreliable health recording. All analyses were carried out for first-lactation Holstein cows. The majority of disease cases occurred in the first month of lactation. Mean disease frequencies were 12.6, 3.7, 4.5, 4.6, 10.8, 8.2, and 9.2% for mastitis, displaced abomasum, ketosis, retained placenta, metritis, cystic ovaries, and lameness, respectively. Milk fever was very rare in first-lactation cows with a frequency of only 0.20%, and was, therefore, not considered in the analyses. Univariate and bivariate linear animal models were fitted. Heritabilities for mastitis, displaced abomasum, ketosis, retained placenta, metritis, cystic ovaries, and lameness were 0.02, 0.06, 0.03, 0.03, 0.02, 0.03, and 0.01, respectively. Genetic correlations between diseases were mostly positive. The strongest genetic correlations were found between displaced abomasum and ketosis (0.64) and between retained placenta and metritis (0.62). The remaining genetic correlations ranged from -0.22 (between metritis and lameness) to 0.49 (between mastitis and lameness). In agreement with the genetic correlations, the largest phenotypic correlations were found between displaced abomasum and ketosis (0.27) and retained placenta and metritis (0.14). All other phenotypic correlations were low and close to zero (0.00 to 0.06). Pearson correlations between breeding values for health traits and other routinely evaluated traits were computed, which revealed noticeable favorable relationships to direct herd life and fertility. In addition, a moderate favorable association was found between mastitis and somatic cell score. Mastitis is the most promising trait to be included in routine genetic evaluation, because it is the most recorded disease and has a high frequency and positive genetic correlations to all other health traits. Although, about 40% of all Canadian dairy producers participate in the health-recording system, a large proportion of the data are lost after data validation. Thus, dairy producers should be encouraged to keep accurate and complete health data.

Genome-Wide Mapping of Loci Explaining Variance in Scrotal Circumference in Nellore Cattle

The reproductive performance of bulls has a high impact on the beef cattle industry. Scrotal circumference (SC) is the most recorded reproductive trait in beef herds, and is used as a major selection criterion to improve precocity and fertility. The characterization of genomic regions affecting SC can contribute to the identification of diagnostic markers for reproductive performance and uncover molecular mechanisms underlying complex aspects of bovine reproductive biology. In this paper, we report a genome-wide scan for chromosome segments explaining differences in SC, using data of 861 Nellore bulls (Bos indicus) genotyped for over 777,000 single nucleotide polymorphisms. Loci that excel from the genome background were identified on chromosomes 4, 6, 7, 10, 14, 18 and 21. The majority of these regions were previously found to be associated with reproductive and body size traits in cattle. The signal on chromosome 14 replicates the pleiotropic quantitative trait locus encompassing PLAG1 that affects male fertility in cattle and stature in several species. Based on intensive literature mining, SP4, MAGEL2, SH3RF2, PDE5A and SNAI2 are proposed as novel candidate genes for SC, as they affect growth and testicular size in other animal models. These findings contribute to linking reproductive phenotypes to gene functions, and may offer new insights on the molecular biology of male fertility.

Genome-Wide Association for Growth Traits in Canchim Beef Cattle

Studies are being conducted on the applicability of genomic data to improve the accuracy of the selection process in livestock, and genome-wide association studies (GWAS) provide valuable information to enhance the understanding on the genetics of complex traits. The aim of this study was to identify genomic regions and genes that play roles in birth weight (BW), weaning weight adjusted for 210 days of age (WW), and long-yearling weight adjusted for 420 days of age (LYW) in Canchim cattle. GWAS were performed by means of the Generalized Quasi-Likelihood Score (GQLS) method using genotypes from the BovineHD BeadChip and estimated breeding values for BW, WW, and LYW. Data consisted of 285 animals from the Canchim breed and 114 from the MA genetic group (derived from crossings between Charolais sires and ½ Canchim + ½ Zebu dams). After applying a false discovery rate correction at a 10% significance level, a total of 4, 12, and 10 SNPs were significantly associated with BW, WW, and LYW, respectively. These SNPs were surveyed to their corresponding genes or to surrounding genes within a distance of 250 kb. The genes DPP6 (dipeptidyl-peptidase 6) and CLEC3B (C-type lectin domain family 3 member B) were highlighted, considering its functions on the development of the brain and skeletal system, respectively. The GQLS method identified regions on chromosome associated with birth weight, weaning weight, and long-yearling weight in Canchim and MA animals. New candidate regions for body weight traits were detected and some of them have interesting biological functions, of which most have not been previously reported. The observation of QTL reports for body weight traits, covering areas surrounding the genes (SNPs) herein identified provides more evidence for these associations. Future studies targeting these areas could provide further knowledge to uncover the genetic architecture underlying growth traits in Canchim cattle.