PSVIII-38 Genomic prediction for tick resistance in Angus cattle

Abstract The main objective of this study was to evaluate the feasibility of single-step genomic BLUP (ssGBLUP) for genetic evaluation of tick resistance in Angus cattle in Brazil. Additionally, we investigated population parameters, namely effect population size (Ne) and inbreeding (F) based on pedigree (PED) and genomic (GEN) information. Half-body tick counts were recorded up to three times in the same animal, totaling 2291 records. To normalize the distribution, records were log-transformed prior to the analysis. From 7073 animals in the pedigree, 1299 were genotyped with 3 different SNP chips of density 50k, 77k, and 150k. After imputation and quality control, 61,066 SNP remained. A repeatability animal model was used to estimate variance components, traditional EBV, and genomic EBV (GEBV). Validation was carried out for young genotyped animals, with no phenotypes in the reduced data but at least one record in the complete data, using two different approaches: 1) predictive ability as the correlation between phenotypes adjusted for fixed effects and (G)EBV; 2) a method based on linear regressions that is called LR, which uses correlations between (G)EBV in the complete and reduced data as a measure of consistency between subsequent evaluations. Heritability for tick counts was 0.18 ± 0.03. Based on PED and GEN, Ne was 254 and 199, whereas F was 0.016 and 0.003, respectively. Predictive ability for tick counts was 0.11 for EBV and 0.14 for GEBV, which is considered low. Conversely, when LR validation was used, the relative increase in accuracy by adding extra phenotypic information was 0.49 for EBV and 0.61 for GEBV. Even though tick counts has low heritability, our study indicates that genomic selection can help to improve prediction accuracy and, therefore, to increase tick resistance in this Angus population.

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Development of genomic predictions for Angus cattle in Brazil incorporating genotypes from related American sires

Journal of Animal Science ◽

10.1093/jas/skac009 ◽

2022 ◽

Author(s):

Gabriel Soares Campos ◽

Fernando Flores Cardoso ◽

Claudia Cristina Gulias Gomes ◽

Robert Domingues ◽

Luciana Correia de Almeida Regitano ◽

...

Keyword(s):

Reference Population ◽

Single Step ◽

Linear Regression Method ◽

Effective Population ◽

Genetic Progress ◽

Angus Cattle ◽

Improvement Programs ◽

Snp Panels ◽

Estimate Variance ◽

Genomic Predictions

Abstract Genomic prediction has become the new standard for genetic improvement programs, and currently, there is a desire to implement this technology for the evaluation of Angus cattle in Brazil. Thus, the main objective of this study was to assess the feasibility of evaluating young Brazilian Angus (BA) bulls and heifers for 12 routinely recorded traits using single-step genomic BLUP (ssGBLUP) with and without genotypes from American Angus (AA) sires. The second objective was to obtain estimates of effective population size (Ne) and linkage disequilibrium (LD) in the Brazilian Angus population. The dataset contained phenotypic information for up to 277,661 animals belonging to the Promebo® breeding program, pedigree for 362,900, of which 1,386 were genotyped for 50k, 77k, and 150k SNP panels. After imputation and quality control, 61,666 SNP were available for the analyses. In addition, genotypes from 332 American Angus (AA) sires widely used in Brazil were retrieved from the AA Association database to be used for genomic predictions. Bivariate animal models were used to estimate variance components, traditional EBV, and genomic EBV (GEBV). Validation was carried out with the linear regression method (LR) using young-genotyped animals born between 2013 and 2015 without phenotypes in the reduced dataset and with records in the complete dataset. Validation animals were further split into progeny of BA and AA sires to evaluate if their progenies would benefit by including genotypes from AA sires. The Ne was 254 based on pedigree and 197 based on LD, and the average LD (±SD) and distance between adjacent SNPs across all chromosomes was 0.27 (±0.27) and 40743.68 bp, respectively. Prediction accuracies with ssGBLUP outperformed BLUP for all traits, improving accuracies by, on average, 16% for BA young bulls and heifers. The GEBV prediction accuracies ranged from 0.37 (total maternal for weaning weight and tick count) to 0.54 (yearling precocity) across all traits, and dispersion (LR coefficients) fluctuated between 0.92 and 1.06. Inclusion of genotyped sires from the AA improved GEBV accuracies by 2%, on average, compared to using only the BA reference population. Our study indicated that genomic information could help to improve GEBV accuracies and hence genetic progress in the Brazilian Angus population. The inclusion of genotypes from American Angus sires heavily used in Brazil just marginally increased the GEBV accuracies for selection candidates.

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213 Genomic selection of carcass quality traits in crossbred pigs using a reference population

Journal of Animal Science ◽

10.1093/jas/skz258.082 ◽

2019 ◽

Vol 97 (Supplement_3) ◽

pp. 41-41

Author(s):

Matteo Bergamaschi ◽

Christian Maltecca ◽

Clint Schwab ◽

Justin Fix ◽

Francesco Tiezzi

Keyword(s):

Fixed Effects ◽

Carcass Traits ◽

Predictive Ability ◽

Reference Population ◽

Single Step ◽

Carcass Quality ◽

Quality Traits ◽

Single Gender ◽

Training Set ◽

Crossbred Pigs

Abstract The objective of this work was to evaluate the predictive ability of different models applied to carcass traits in crossbred pigs. The pigs were divided in 2 finishing flows: A=36,110 and B=95,041 animals, and were progeny of 386 sires (almost entirely genotyped with the 60k SNP chip). In flow A, individuals were housed into single-sire single-gender pens, and split-marketing on a pen basis was applied. In flow B, individuals were kept in standard commercial conditions and split-marketing on an individuals basis was applied. A dataset containing individual records of three carcass traits: back-fat (BF), loin depth (LD), and carcass daily gain (CACG) was used. Data from flow A were divided into training and validation sets on the basis of contemporary groups (8 in training and 1 in testing). Variance components and solutions were obtained using the BLUPF90 suite of programs. Models included fixed effects (dam line, sow parity, sex, cross fostering, and contemporary group) and random effects (additive genetic, batch, litter, and residual). Models tested were univariate vs multivariate and pedigree vs single-step. The addition of flow B records to the training set was evaluated, by including or excluding these records. Heritabilities were 0.68±0.023 for BF, 0.47±0.018 for LD, and 0.55±0.023 for CACG. CACG gain was correlated with BF (0.43±0.029) and LD (0.39±0.03). Low genetic correlation was found between BF and LD (0.17±0.034). Prediction accuracies were 0.39±0.05, 0.17±0.06, and 0.13±0.03 for BF, LD, and CACG respectively. The mean accuracy of BF, LD, and CG increased (~6%) when records from flow B were included in the training set, whereas the increase of accuracy between models (univariate vs multivariate) was not significant. The inclusion of sire genotypes did not improve prediction accuracy significantly. Based on these results, the prediction of carcass quality traits in crossbred pigs is possible.

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Multiple Country and Breed Genomic Prediction of Tick Resistance in Beef Cattle

Frontiers in Immunology ◽

10.3389/fimmu.2021.620847 ◽

2021 ◽

Vol 12 ◽

Author(s):

Fernando Flores Cardoso ◽

Oswald Matika ◽

Appolinaire Djikeng ◽

Ntanganedzeni Mapholi ◽

Heather M. Burrow ◽

...

Keyword(s):

Beef Cattle ◽

Genetic Correlation ◽

Predictive Ability ◽

Tick Control ◽

Factors Affecting ◽

Partial Data ◽

Wide Range ◽

Tick Counts ◽

Over Dispersion ◽

Tick Resistance

Ticks cause substantial production losses for beef and dairy cattle. Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped/phenotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. For NG and TC additional phenotyping will be required to obtain accurate GEBV.

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Use of genomic information to exploit genotype-by-environment interactions for body weight of broiler chicken in bio-secure and production environments

Genetics Selection Evolution ◽

10.1186/s12711-019-0493-3 ◽

2019 ◽

Vol 51 (1) ◽

Cited By ~ 1

Author(s):

Thinh T. Chu ◽

John W. M. Bastiaansen ◽

Peer Berg ◽

Hélène Romé ◽

Danye Marois ◽

...

Keyword(s):

Body Weight ◽

Genetic Correlations ◽

Single Step ◽

Pedigree Information ◽

Genomic Information ◽

Genotype By Environment Interactions ◽

Genotype By Environment ◽

Increase In Accuracy ◽

Close Relatives ◽

Estimate Variance

Abstract Background The increase in accuracy of prediction by using genomic information has been well-documented. However, benefits of the use of genomic information and methodology for genetic evaluations are missing when genotype-by-environment interactions (G × E) exist between bio-secure breeding (B) environments and commercial production (C) environments. In this study, we explored (1) G × E interactions for broiler body weight (BW) at weeks 5 and 6, and (2) the benefits of using genomic information for prediction of BW traits when selection candidates were raised and tested in a B environment and close relatives were tested in a C environment. Methods A pedigree-based best linear unbiased prediction (BLUP) multivariate model was used to estimate variance components and predict breeding values (EBV) of BW traits at weeks 5 and 6 measured in B and C environments. A single-step genomic BLUP (ssGBLUP) model that combined pedigree and genomic information was used to predict EBV. Cross-validations were based on correlation, mean difference and regression slope statistics for EBV that were estimated from full and reduced datasets. These statistics are indicators of population accuracy, bias and dispersion of prediction for EBV of traits measured in B and C environments. Validation animals were genotyped and non-genotyped birds in the B environment only. Results Several indications of G × E interactions due to environmental differences were found for BW traits including significant re-ranking, heterogeneous variances and different heritabilities for BW measured in environments B and C. The genetic correlations between BW traits measured in environments B and C ranged from 0.48 to 0.54. The use of combined pedigree and genomic information increased population accuracy of EBV, and reduced bias of EBV prediction for genotyped birds compared to the use of pedigree information only. A slight increase in accuracy of EBV was also observed for non-genotyped birds, but the bias of EBV prediction increased for non-genotyped birds. Conclusions The G × E interaction was strong for BW traits of broilers measured in environments B and C. The use of combined pedigree and genomic information increased population accuracy of EBV substantially for genotyped birds in the B environment compared to the use of pedigree information only.

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PSXII-9 Modeling genetic differences of combined broiler chicken populations in single-step GBLUP

Journal of Animal Science ◽

10.1093/jas/skab235.464 ◽

2021 ◽

Vol 99 (Supplement_3) ◽

pp. 254-254

Author(s):

Matias Bermann ◽

Daniela Lourenco ◽

Vivian Breen ◽

Rachel Hawken ◽

Fernando Brito Lopes ◽

...

Keyword(s):

Fixed Effects ◽

Broiler Chicken ◽

Predictive Ability ◽

Single Step ◽

Fixed Effect ◽

Model Specification ◽

Breeding Values ◽

Chicken Population ◽

Estimated Breeding Values ◽

Genomic Predictions

Abstract The objectives of this study were to model the inclusion of a group of external birds into a local broiler chicken population for the purpose of genomic evaluations and evaluating the behavior of two accuracy estimators under different model specifications. The pedigree was composed by 242,413 birds and genotypes were available for 107,216 birds. A five-trait model that included one growth, two yield, and two efficiency traits was used for the analyses. The strategies to model the introduction of external birds were to include a fixed effect representing the origin of parents and to use UPG or metafounders. Genomic estimated breeding values (GEBV) were obtained with single-step GBLUP (ssGBLUP) using the Algorithm for Proven and Young (APY). Bias, dispersion, and accuracy of GEBV for the validation birds, i.e., from the most recent generation, were computed. The bias and dispersion were estimated with the LR-method, whereas accuracy was estimated by the LR-method and predictive ability. Models with fixed UPG and estimated inbreeding or random UPG resulted in similar GEBV. The inclusion of an extra fixed effect in the model made the GEBV unbiased and reduced the inflation, while models without such an effect were significantly biased. Genomic predictions with metafounders were slightly biased and inflated due to the unbalanced number of observations assigned to each metafounder. When combining local and external populations, the greatest accuracy and smallest bias can be obtained by adding an extra fixed effect to account for the origin of parents plus UPG with estimated inbreeding or random UPG. To estimate the accuracy, the LR-method is more consistent among models, whereas predictive ability greatly depends on the model specification, that is, on the fixed effects included in the model. When changing model specification, the largest variation for the LR-method was 20%, while for predictive ability was 110%.

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Estimation of direct and maternal genetic parameters for weaning weight in Hungarian Simmental cattle

Acta Agraria Debreceniensis ◽

10.34101/actaagrar/2/9305 ◽

2021 ◽

pp. 17-22

Author(s):

Afees Abiola Ajasa ◽

Imre Füller ◽

Barnabás Vágó ◽

István Komlósi ◽

János Posta

Keyword(s):

Fixed Effects ◽

Genetic Parameters ◽

Additive Genetic Variance ◽

Random Effect ◽

Ratio Test ◽

Genetic Covariance ◽

Weaning Weight ◽

Simmental Cattle ◽

Estimate Variance ◽

Best Fit

The aim of the current research was to estimate variance components and genetic parameters of weaning weight in Hungarian Simmental cattle. Weaning weight records were obtained from the Association of Hungarian Simmental Breeders. The dataset comprised of 44,278 animals born from 1975 to 2020. The data was analyzed using the restricted maximum likelihood methodology of the Wombat software. We fitted a total of six models to the weaning weight data of Hungarian Simmental cattle. Models ranged from a simple model with animals as the only random effect to a model that had maternal environmental effects as additional random effects as well as direct maternal genetic covariance. Fixed effects in the model comprised of herd, birth year, calving order and sex. Likelihood ratio test was used to determine the best fit model for the data. Results indicated that allowing for direct-maternal genetic covariance increases the direct and maternal effect dramatically. The best fit model had direct and maternal genetic effects as the only random effect with non-zero direct-maternal genetic correlation. Direct heritability, maternal heritability and direct maternal correlation of the best fit model was 0.57, 0.16 and -0.78 respectively. The result indicates that problem of (co-)sampling variation occurs when attempting to partition additive genetic variance into direct and maternal components.

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Applying the Metafounders Approach for Genomic Evaluation in a Multibreed Beef Cattle Population

Frontiers in Genetics ◽

10.3389/fgene.2020.556399 ◽

2020 ◽

Vol 11 ◽

Author(s):

Vinícius Silva Junqueira ◽

Paulo Sávio Lopes ◽

Daniela Lourenco ◽

Fabyano Fonseca e Silva ◽

Fernando Flores Cardoso

Keyword(s):

Beef Cattle ◽

Variance Components ◽

Genetic Relationships ◽

A Priori ◽

Predictive Ability ◽

Single Step ◽

Pedigree Information ◽

Phenotypic Variance ◽

Genomic Information ◽

The Impact

Pedigree information is incomplete by nature and commonly not well-established because many of the genetic ties are not known a priori or can be wrong. The genomic era brought new opportunities to assess relationships between individuals. However, when pedigree and genomic information are used simultaneously, which is the case of single-step genomic BLUP (ssGBLUP), defining the genetic base is still a challenge. One alternative to overcome this challenge is to use metafounders, which are pseudo-individuals that describe the genetic relationship between the base population individuals. The purpose of this study was to evaluate the impact of metafounders on the estimation of breeding values for tick resistance under ssGBLUP for a multibreed population composed by Hereford, Braford, and Zebu animals. Three different scenarios were studied: pedigree-based model (BLUP), ssGBLUP, and ssGBLUP with metafounders (ssGBLUPm). In ssGBLUPm, a total of four different metafounders based on breed of origin (i.e., Hereford, Braford, Zebu, and unknown) were included for the animals with missing parents. The relationship coefficient between metafounders was in average 0.54 (ranging from 0.34 to 0.96) suggesting an overlap between ancestor populations. The estimates of metafounder relationships indicate that Hereford and Zebu breeds have a possible common ancestral relationship. Inbreeding coefficients calculated following the metafounder approach had less negative values, suggesting that ancestral populations were large enough and that gametes inherited from the historical population were not identical. Variance components were estimated based on ssGBLUPm, ssGBLUP, and BLUP, but the values from ssGBLUPm were scaled to provide a fair comparison with estimates from the other two models. In general, additive, residual, and phenotypic variance components in the Hereford population were smaller than in Braford across different models. The addition of genomic information increased heritability for Hereford, possibly because of improved genetic relationships. As expected, genomic models had greater predictive ability, with an additional gain for ssGBLUPm over ssGBLUP. The increase in predictive ability was greater for Herefords. Our results show the potential of using metafounders to increase accuracy of GEBV, and therefore, the rate of genetic gain in beef cattle populations with partial levels of missing pedigree information.

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Selection of cattle for tick resistance, and the effect of herds of different susceptibility on Boophilus populations

Australian Journal of Agricultural Research ◽

10.1071/ar9620974 ◽

1962 ◽

Vol 13 (5) ◽

pp. 974 ◽

Cited By ~ 32

Author(s):

PR Wilkinson

Keyword(s):

Tick Infestation ◽

Tick Control ◽

Boophilus Microplus ◽

Skin Thickness ◽

Adult Females ◽

Cattle Ticks ◽

In Parenthesis ◽

Tick Counts ◽

Tick Resistance ◽

Selection Of

Weekly counts of Boophilus microplus (Canestrini) on 30 Australian Illawarra Shorthorn heifers enabled the cattle to be ranked in order of tick infestation, with highly significant correlations between counts of two observers and between counts of one observer on different occasions. In May 1960, when the heifers were 1½–2 years old, 12 were selected as relatively tick-resistant and 12 as relatively tick-susceptible. Each of these groups was divided at random into herds of six, and the four herds were then allotted randomly to separate paddocks, each onequarter of the area previously grazed. A herd was sprayed with 0.5% DDT emulsion when its average count of ticks (adult females over 5 mm in length) on one side of the animals exceeded 40. During the ensuing tick season, from October 5, 1960, to June 7, 1961, the sums of average weekly tick counts, and the numbers of sprayings (in parenthesis) were: susceptible herds 4853 (5) and 5962 (6): resistant herds 718 (0) and 1073 (1). Counts of tick larvae on defined body areas showed that, in the summer after segregation, resistant herds carried fewer larvae than the susceptible herds, apparently because fewer mature ticks fell from the resistant cattle in the preceding spring and winter. As a consequence of this, counts of adult ticks were comparatively lower after than before segregation. There was little or no 'spring rise' of tick infestation on the resistant herds. There was no significant correlation between tick resistance and coat score, sweat gland dimensions, or total skin thickness, but a correlation of -0.53 with follicle depth was significant at the 1% level. There was no evidence of adaptation of cattle ticks to the resistant animals, either in the field experiment or in observations on stalled cattle. The experiment draws attention to the appreciable proportion of tick-resistant animals within the Australian Illawarra Shorthorn breed, which has largely been overlooked in past discussions on tick-resistant breeds of cattle. It also suggests a technique for estimating the improvement in tick control that may be obtained by a given degree of selection within any breed, for any given environment.

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Determinants of Gender Differences in Change in Pay among Job-Switching Executives

ILR Review ◽

10.1177/0019793920930712 ◽

2020 ◽

pp. 001979392093071

Author(s):

Boris Groysberg ◽

Paul Healy ◽

Eric Lin

Keyword(s):

Gender Differences ◽

Women Executives ◽

Fixed Effects ◽

Supply And Demand ◽

Relative Increase ◽

Global Search ◽

Men And Women ◽

Explanatory Factors ◽

Pay Differences ◽

Performance Based Compensation

The authors investigate what determines differences in change in pay between men and women executives who move to new employers. Using proprietary data of 2,034 executive placements from a global search firm, the authors observe narrower pay differences between men and women after job moves. The unconditional gap shrinks from 21.5% in the prior employer to 15% in the new employer. After controlling for typical explanatory factors, the residual gap falls by almost 30%, from 8.5% at the prior employer to 6.1% in the new placement. This change reflects a relative increase in performance-based compensation for women and a lower level of unexplained pay inequality generally in external placements. Controlling for individual fixed effects, observed women have higher pay raises than do men. Finally, the authors find suggestive evidence that pay differences may also be moderated by differences in the supply and demand for women executives.

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Resistance to the cattle tick, Boophilus microplus in a herd of Australian Illawarra Shorthorn cattle: Its assessment and heritability

Australian Journal of Agricultural Research ◽

10.1071/ar9700163 ◽

1970 ◽

Vol 21 (1) ◽

pp. 163 ◽

Cited By ~ 73

Author(s):

RH Wharton ◽

KBW Utech ◽

HG Turner

Keyword(s):

Reference Value ◽

Mature Female ◽

Boophilus Microplus ◽

Supplementary Information ◽

Cattle Tick ◽

The Mean ◽

Tick Counts ◽

The Right ◽

High Level ◽

Tick Resistance

An Australian Illawarra Shorthorn herd of 24 cows was mated in three consecutive years with an AIS bull. The cows and their progeny were rated for tick resistance at frequent intervals from August 1959 to December 1965 by counting the numbers of semiengorged female ticks on the right side. The mean of log counts for all counts on a particular animal was adopted as the reference value for its degree of susceptibility. The ranking of cattle generally showed a high level of consistency with mean repeatability of counts (r = 0.47, P < 0.01). Discrimination between animals was more reliable (P < 0.01) in summer (r = 0.52) than in winter (r = 0.27). The repeatability of tick counts increased with mean count, from r = 0.27 when the mean count was 3 to r = 0.67 when it was 100. The reliability of counts on the cows decreased with age and with lactation. Supplementary information on a larger herd showed no effect of pregnancy on mean count or on discrimination between susceptible and resistant animals, but showed that there was a partial breakdown of resistance during lactation. In calves infested naturally, no effects of age or sex on tick counts or their repeatability were detected, though male calves yielded significantly larger numbers of ticks than females when infested artificially. The mean yield of mature female ticks on the cows following two artificial infestations with known numbers of larvae ranged from 0.2 to 27.4% of the potential. Natural and artificial assessments of susceptibility were closely correlated. The rank of the bull was similar to that of the more resistant cows. Mean estimates of the heritability of tick resistance based on single counts were 39 % from dam-calf correlations and 49 % from full-sib correlations. Estimates based on summer counts only were 42 and 64% respectively. These results provide strong encouragement for selecting for tick resistance.

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