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4. Efficient large-scale single-step evaluations and indirect genomic prediction of genotyped selection candidates

Author

Vandenplas, Jeremie, ten Napel, Jan, Darbaghshahi, Saeid Naderi, Evans, Ross, Calus, Mario P.L., Veerkamp, Roel, Cromie, Andrew, Mäntysaari, Esa A., Strandén, Ismo, Vandenplas, Jeremie, ten Napel, Jan, Darbaghshahi, Saeid Naderi, Evans, Ross, Calus, Mario P.L., Veerkamp, Roel, Cromie, Andrew, Mäntysaari, Esa A., and Strandén, Ismo

Abstract

Background: Single-step genomic best linear unbiased prediction (ssGBLUP) models allow the combination of genomic, pedigree, and phenotypic data into a single model, which is computationally challenging for large genotyped populations. In practice, genotypes of animals without their own phenotype and progeny, so-called genotyped selection candidates, can become available after genomic breeding values have been estimated by ssGBLUP. In some breeding programmes, genomic estimated breeding values (GEBV) for these animals should be known shortly after obtaining genotype information but recomputing GEBV using the full ssGBLUP takes too much time. In this study, first we compare two equivalent formulations of ssGBLUP models, i.e. one that is based on the Woodbury matrix identity applied to the inverse of the genomic relationship matrix, and one that is based on marker equations. Second, we present computationally-fast approaches to indirectly compute GEBV for genotyped selection candidates, without the need to do the full ssGBLUP evaluation. Results: The indirect approaches use information from the latest ssGBLUP evaluation and rely on the decomposition of GEBV into its components. The two equivalent ssGBLUP models and indirect approaches were tested on a six-trait calving difficulty model using Irish dairy and beef cattle data that include 2.6 million genotyped animals of which about 500,000 were considered as genotyped selection candidates. When using the same computational approaches, the solving phase of the two equivalent ssGBLUP models showed similar requirements for memory and time per iteration. The computational differences between them were due to the preprocessing phase of the genomic information. Regarding the indirect approaches, compared to GEBV obtained from single-step evaluations including all genotypes, indirect GEBV had correlations higher than 0.99 for all traits while showing little dispersion and level bias. Conclusions: In conclusion, ssGBLUP predic

Published
2023

7. Additional file 1 of Efficient large-scale single-step evaluations and indirect genomic prediction of genotyped selection candidates

Author

Vandenplas, Jeremie, ten Napel, Jan, Darbaghshahi, Saeid Naderi, Evans, Ross, Calus, Mario P. L., Veerkamp, Roel, Cromie, Andrew, Mäntysaari, Esa A., and Strandén, Ismo

Abstract

Additional file 1: Table S1. Pearson correlations, regression coefficients, and level bias for direct and maternal GEBV computed from the full ssSNPBLUP versus from the indirect prediction approaches for 251,332 genotyped selection candidates with both parents genotyped. Table S2. Pearson correlations, regression coefficients, and level bias for direct and maternal GEBV computed from the full ssSNPBLUP versus from the indirect prediction approaches for 155,675 genotyped selection candidates with only one genotyped parent. Table S3. Pearson correlations, regression coefficients, and level bias for direct and maternal GEBV computed from the full ssSNPBLUP versus from the indirect prediction approaches for 50,164 genotyped selection candidates with no genotyped parents. Table S4. Pearson correlations, regression coefficients, and level bias for direct and maternal GEBV computed from the full ssGTABLUP versus from the indirect prediction approaches for 251,332 genotyped selection candidates with both parents genotyped. Table S5. Pearson correlations, regression coefficients, and level bias for direct and maternal GEBV computed from the full ssGTABLUP versus from the indirect prediction approaches for 155,675 genotyped selection candidates with only one genotyped parent. Table S6. Pearson correlations, regression coefficients, and level bias for direct and maternal GEBV computed from the full ssGTABLUP versus from the indirect prediction approaches for 50,164 genotyped selection candidates with no genotyped parents.

Published
2023
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8. Re-ranking in International Beef Cattle Evaluations due toignoring Direct-Maternal Genetic Correlations Between Countries

Author

Bonifazi, R., Vandenplas, J., ten Napel, J., Cromie, Andrew, Veerkamp, R.F., Calus, M.P.L., Bonifazi, R., Vandenplas, J., ten Napel, J., Cromie, Andrew, Veerkamp, R.F., and Calus, M.P.L.

Abstract

Many traits of economical relevance in beef cattle are influenced in their phenotypic expression by the dam. Genetic evaluations of maternally affected traits require to model direct, maternal and direct-maternal genetic (co)variances next to non-genetic effects. In Interbeef beef cattle international evaluations, direct-maternal genetic correlations (rdm) may be different both within countries (rdm_WC) and between countries (rdm_BC). rdm_WC for growth traits up to weaning are often reported to be negative and significantly different from zero. As rdm_BC are difficult to estimate, these are currently assumed to be equal to zero in Interbeef evaluations. The objective of this study was to evaluate the impact of using estimated values for rdm_BC instead of assuming them to be zero, on international estimated breeding values (IEBV). We implemented two scenarios that differed only in the modelling of rdm_BC: A) the current Interbeef evaluation with assumes rdm_BC to be 0 and fits estimated rdm_WC, and B) an Interbeef evaluation in which both estimated rdm_WC and rdm_BC were fitted. Weaning weight phenotypes and pedigree information were available for more than 3 million Limousin beef cattle males and females, born between 1972 and 2017, and distributed across ten European countries. We evaluated the impact of ignoring rdm_BC on different groups of animals by comparing animals’ direct and maternal IEBV between scenarios A and B. Ignoring rdm_BC resulted in no re-ranking for direct IEBV, and limited re-ranking for maternal IEBV. Less re-ranking in maternal IEBV was observed with increasing reliability. Moreover, ignoring rdm_BC resulted in no re-ranking for publishable sires, i.e. of sires with IEBV that can be exchanged across countries. Our study suggests that the current practice of ignoring rdm_BC has limited impact on Interbeef evaluations when rdm_BC are close to 0 on average (ranging from +0.14 to -0.14) as is the case for weaning weight.

Published
2022

9. Additional file 1 of International single-step SNPBLUP beef cattle evaluations for Limousin weaning weight

Author

Bonifazi, Renzo, Calus, Mario P. L., ten Napel, Jan, Veerkamp, Roel F., Michenet, Alexis, Savoia, Simone, Cromie, Andrew, and Vandenplas, Jérémie

Abstract

Additional file 1: Table S1. Number of phenotypes (N), minimum, mean, maximum, and phenotypic standard deviation ( $${\sigma }_{P}$$ σ P ) of males and females per country. Table S2. List of environmental effects in the national model of each country. Table S3. Direct and maternal genetic covariances (below diagonal), genetic variances (diagonal) and genetic correlations (above diagonal) within and across countries. Table S4. National genetic, environmental and residual (co)variances. Table S5. Level bias ( $${\widehat{\Delta }}_{p}$$ Δ ^ p ), dispersion bias ( $${\widehat{b}}_{p}$$ b ^ p ) and accuracy of partial EBV ( $${\widehat{acc}}_{p}$$ acc ^ p ) of direct and maternal EBV for animals with phenotypes and no genotypes born from 2014 onwards, in each scenario and for each country. Table S6. Increases in population accuracy ( $$inc\_acc$$ i n c _ a c c ) of moving from each scenario to ssSNPBLUPINT for direct and maternal EBV for animals with phenotypes and no genotypes born from 2014 onwards for each country. Table S7. Countries sending the genotypes for Common Bulls (CB) and Common Maternal Grand-Sires (CMGS). Table S8. Level bias ( $${\widehat{\Delta }}_{p}$$ Δ ^ p ), dispersion bias ( $${\widehat{b}}_{p}$$ b ^ p ) and accuracy of partial EBV ( $${\widehat{acc}}_{p}$$ acc ^ p ) of direct and maternal EBV for the focal group, in each scenario and for each country. Standard errors reported within parenthesis.

Published
2022
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10. Additional file 4 of International single-step SNPBLUP beef cattle evaluations for Limousin weaning weight

Author

Bonifazi, Renzo, Calus, Mario P. L., ten Napel, Jan, Veerkamp, Roel F., Michenet, Alexis, Savoia, Simone, Cromie, Andrew, and Vandenplas, Jérémie

Abstract

Additional file 4: Figure S3. Direct and maternal EBV realized Mendelian sampling (RMS) trends in each countrya expressed in genetic standard deviation (GSD) for genotyped and non-genotyped animalsb computed with pedigree-based BLUP international (PBLUPINT) and single-step SNP-BLUP international (ssSNPBLUPINT) models. aCZE Czech Republic, DFS Denmark, Finland and Sweden, IRL Ireland, DEU Germany, CHE Switzerland. bGenotyped animals: animals with genotype that appear in the pseudo-national pedigree (with or without phenotype in the country). Non-genotyped animals: animals that appear in the pseudo-national pedigree without genotype and with phenotype in the country.

Published
2022
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11. Additional file 2 of International single-step SNPBLUP beef cattle evaluations for Limousin weaning weight

Author

Bonifazi, Renzo, Calus, Mario P. L., ten Napel, Jan, Veerkamp, Roel F., Michenet, Alexis, Savoia, Simone, Cromie, Andrew, and Vandenplas, Jérémie

Abstract

Additional file 2: File S1. Findhap instruction file. File S2. International pedigree-based BLUP MiXBLUP instruction file. File S3. International single-step SNPBLUP MiXBLUP instruction file.

Published
2022
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12. Additional file 3 of International single-step SNPBLUP beef cattle evaluations for Limousin weaning weight

Author

Bonifazi, Renzo, Calus, Mario P. L., ten Napel, Jan, Veerkamp, Roel F., Michenet, Alexis, Savoia, Simone, Cromie, Andrew, and Vandenplas, Jérémie

Abstract

Additional file 3: Figure S1. Plot of pedigree-based (x-axis) and genomic-based (y-axis) relationships between genotyped animals. The red dots indicate the relationships of the 41 genotypes removed due to pedigree incompatibilities. Figure S2. Differences in genetic trends between ssSNPBLUPINT and PBLUPINT per country for sires with at least 10 recorded offspring in the country (only birth years with at least 5 sires are included).

Published
2022
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15. Corrigendum to 'Relationships between metabolic profiles and gene expression in liver and leukocytes of dairy cows in early lactation' (J. Dairy Sci. 104:3596–3616)

Author

Wathes, D. Claire, Cheng, Zhangrui, Salavati, Mazdak, Buggiotti, Laura, Tang, L., Ferris, C., Hostens, M., Crowe, M. A., McLoughlin, Niamh, Fahey, Alan, Matthews, Elizabeth, Santoro, Andreia, Byrne, Colin, Rudd, Pauline, O'Flaherty, Roisin, Hallinan, Sinead, Fouladi, Ali, Pollott, Geoff, Werling, Dirk, Bernardo, Beatriz Sanz, Wylie, Alistair, Bell, Matt, Vaneetvelde, Mieke, Hermans, Kristof, Opsomer, Geert, Moerman, Sander, De Koster, Jenne, Bogaert, Hannes, Vandepitte, Jan, Vandevelde, Leila, Vanranst, Bonny, Hoglund, Johanna, Dahl, Susanne, Ostergaard, Soren, Rothmann, Janne, Krogh, Mogens, Meyer, Else, Gaillard, Charlotte, Ettema, Jehan, Rousing, Tine, Signorelli, Federica, Napolitano, Francesco, Moioli, Bianca, Crisa, Alessandra, Buttazzoni, Luca, McClure, Jennifer, Matthews, Daragh, Kearney, Francis, Cromie, Andrew, McClure, Matt, Klaus, Ingvartsen, Takeda, H., and FAH GZ herkauwer

Subjects
Genetics, Animal Science and Zoology, Food Science
Published
2021

17. Corrigendum to “Relationships between metabolic profiles and gene expression in liver and leukocytes of dairy cows in early lactation” (J. Dairy Sci. 104:3596–3616)

Author

FAH GZ herkauwer, Wathes, D. Claire, Cheng, Zhangrui, Salavati, Mazdak, Buggiotti, Laura, Tang, L., Ferris, C., Hostens, M., Crowe, M. A., McLoughlin, Niamh, Fahey, Alan, Matthews, Elizabeth, Santoro, Andreia, Byrne, Colin, Rudd, Pauline, O'Flaherty, Roisin, Hallinan, Sinead, Fouladi, Ali, Pollott, Geoff, Werling, Dirk, Bernardo, Beatriz Sanz, Wylie, Alistair, Bell, Matt, Vaneetvelde, Mieke, Hermans, Kristof, Opsomer, Geert, Moerman, Sander, De Koster, Jenne, Bogaert, Hannes, Vandepitte, Jan, Vandevelde, Leila, Vanranst, Bonny, Hoglund, Johanna, Dahl, Susanne, Ostergaard, Soren, Rothmann, Janne, Krogh, Mogens, Meyer, Else, Gaillard, Charlotte, Ettema, Jehan, Rousing, Tine, Signorelli, Federica, Napolitano, Francesco, Moioli, Bianca, Crisa, Alessandra, Buttazzoni, Luca, McClure, Jennifer, Matthews, Daragh, Kearney, Francis, Cromie, Andrew, McClure, Matt, Klaus, Ingvartsen, Takeda, H., FAH GZ herkauwer, Wathes, D. Claire, Cheng, Zhangrui, Salavati, Mazdak, Buggiotti, Laura, Tang, L., Ferris, C., Hostens, M., Crowe, M. A., McLoughlin, Niamh, Fahey, Alan, Matthews, Elizabeth, Santoro, Andreia, Byrne, Colin, Rudd, Pauline, O'Flaherty, Roisin, Hallinan, Sinead, Fouladi, Ali, Pollott, Geoff, Werling, Dirk, Bernardo, Beatriz Sanz, Wylie, Alistair, Bell, Matt, Vaneetvelde, Mieke, Hermans, Kristof, Opsomer, Geert, Moerman, Sander, De Koster, Jenne, Bogaert, Hannes, Vandepitte, Jan, Vandevelde, Leila, Vanranst, Bonny, Hoglund, Johanna, Dahl, Susanne, Ostergaard, Soren, Rothmann, Janne, Krogh, Mogens, Meyer, Else, Gaillard, Charlotte, Ettema, Jehan, Rousing, Tine, Signorelli, Federica, Napolitano, Francesco, Moioli, Bianca, Crisa, Alessandra, Buttazzoni, Luca, McClure, Jennifer, Matthews, Daragh, Kearney, Francis, Cromie, Andrew, McClure, Matt, Klaus, Ingvartsen, and Takeda, H.

Published
2021

19. Genome‐wide association for milk production and lactation curve parameters in Holstein dairy cows

Author

Atashi, Hadi, Salavati, Mazdak, De Koster, Jenne, Ehrlich, Jim, Crowe, Mark, Opsomer, Geert, McLoughlin, Niamh, Fahey, Alan, Matthews, Elizabeth, Santoro, Andreia, Byrne, Colin, Rudd, Pauline, O'Flaherty, Roisin, Hallinan, Sinead, Wathes, Claire, Cheng, Zhangrui, Fouladi, Ali, Pollott, Geoff, Werling, Dirk, Bernardo, Beatriz Sanz, Wylie, Alistair, Bell, Matt, Van Eetvelde, Mieke, Hermans, Kristof, Moerman, Sander, Bogaert, Hannes, Vandepitte, Jan, Vande Velde, Leila, Van Ranst, Bonifacius, Hoglund, Johanna, Dahl, Susanne, Ostergaard, Soren, Rothmann, Janne, Krogh, Mogens, Meyer, Else, Gaillard, Charlotte, Ettema, Jehan, Rousing, Tine, Signorelli, Federica, Napolitano, Francesco, Moioli, Bianca, Crisa, Alessandra, Buttazzoni, Luca, McClure, Jennifer, Matthews, Daragh, Kearney, Francis, Cromie, Andrew, McClure, Matt, Zhang, Shujun, Chen, Xing, Chen, Huanchun, Zhao, Junlong, Yang, Liguo, Hua, Guohua, Tan, Chen, Wang, Guiqiang, Bonneau, Michel, Pompozzi, Andrea, Pearn, Armin, Evertson, Arnold, Kosten, Linda, Fogh, Anders, Andersen, Thomas, Lucey, Matthew, Elsik, Chris, Conant, Gavin, Taylor, Jerry, Gengler, Nicolas, Georges, Michel, Colinet, Frederic, Pamplona, Marilou Ramos, Hammami, Hedi, Bastin, Catherine, Takeda, Haruko, Laine, Aurelie, Van Laere, Anne-Sophie, Schulze, Martin, Vera, Sergio Palma, Ferris, Conrad, Marchitelli, Cinzia, and Hostens, Miel

Subjects
Candidate gene, Genotype, QTL, CATTLE, PREDICTIONS, Genome-wide association study, Biology, Best linear unbiased prediction, Quantitative trait locus, Protein lipidation, Polymorphism, Single Nucleotide, milk yield, Animal science, Food Animals, Pregnancy, Lactation, Genetic variation, medicine, Animals, Veterinary Sciences, PERSISTENCY, genome‐wide association study, QUANTITATIVE TRAIT LOCI, Genome, GENETIC-PARAMETERS, genome-wide association study, Holstein, General Medicine, Original Articles, SOMATIC-CELL SCORE, Dairying, Parity, medicine.anatomical_structure, Milk, Phenotype, YIELD, Yield (chemistry), Cattle, Female, Original Article, SHAPE, Animal Science and Zoology, ENRICHMENT, lactation curve
Abstract

The aim of this study was to identify genomic regions associated with 305‐day milk yield and lactation curve parameters on primiparous (n = 9,910) and multiparous (n = 11,158) Holstein cows. The SNP solutions were estimated using a weighted single‐step genomic BLUP approach and imputed high‐density panel (777k) genotypes. The proportion of genetic variance explained by windows of 50 consecutive SNP (with an average of 165 Kb) was calculated, and regions that accounted for more than 0.50% of the variance were used to search for candidate genes. Estimated heritabilities were 0.37, 0.34, 0.17, 0.12, 0.30 and 0.19, respectively, for 305‐day milk yield, peak yield, peak time, ramp, scale and decay for primiparous cows. Genetic correlations of 305‐day milk yield with peak yield, peak time, ramp, scale and decay in primiparous cows were 0.99, 0.63, 0.20, 0.97 and −0.52, respectively. The results identified three windows on BTA14 associated with 305‐day milk yield and the parameters of lactation curve in primi‐ and multiparous cows. Previously proposed candidate genes for milk yield supported by this work include GRINA, CYHR1, FOXH1, TONSL, PPP1R16A, ARHGAP39, MAF1, OPLAH and MROH1, whereas newly identified candidate genes are MIR2308, ZNF7, ZNF34, SLURP1, MAFA and KIFC2 (BTA14). The protein lipidation biological process term, which plays a key role in controlling protein localization and function, was identified as the most important term enriched by the identified genes.

Published
2020

20. Potential of milk mid-infrared spectra to predict nitrogen use efficiency of individual dairy cows in early lactation

Author

Grelet, C., Froidmont, E., Foldager, L., Salavati, M., Hostens, Miel, Ferris, C. P., Ingvartsen, K. L., Crowe, M. A., Sorensen, M. T., Pierna, J. A. Fernandez, Vanlierde, A., Gengler, N., Dehareng, F., Crowe, Mark, Fahey, Alan, Carter, Fiona, Matthews, Elizabeth, Santoro, Andreia, Byrne, Colin, Rudd, Pauline, O'Flaherty, Roisin, Hallinan, Sinead, Wathes, Claire, Salavati, Mazdak, Cheng, Zhangrui, Fouladi, Ali, Pollott, Geoff, Werling, Dirk, Bernardo, Beatriz Sanz, Ferris, Conrad, Wylie, Alistair, Bell, Matt, Van Eetvelde, Mieke, Hermans, Kristof, Opsomer, Geert, Moerman, Sander, De Koster, Jenne, Bogaert, Hannes, Vandepitte, Jan, Vande Velde, Leila, Van Ranst, Bonifacius, Ingvartsen, Klaus, Sorensen, Martin Tang, Hoglund, Johanna, Dahl, Susanne, Ostergaard, Soren, Rothmann, Janne, Krogh, Mogens, Meyer, Else, Foldager, Leslie, Gaillard, Charlotte, Ettema, Jehan, Rousing, Tine, Larsen, Torben, de Oliveira, Victor H. Silva, Marchitelli, Cinzia, Signorelli, Federica, Napolitano, Francesco, Moioli, Bianca, Crisa, Alessandra, Buttazzoni, Luca, McClure, Jennifer, Matthews, Daragh, Kearney, Francis, Cromie, Andrew, McClure, Matt, Zhang, Shujun, Chen, Xing, Chen, Huanchun, Zhao, Junlong, Yang, Liguo, Hua, Guohua, Tan, Chen, Wang, Guigiang, Bonneau, Michel, Sciarretta, Marlene, Pearn, Armin, Evertson, Arnold, Kosten, Linda, Fogh, Anders, Andersen, Thomas, Lucy, Matthew, Elsik, Chris, Conant, Gavin, Taylor, Jerry, Triant, Deborah, Gengler, Nicolas, Georges, Michel, Colinet, Frederic, Pamplona, Marilou Ramos, Hammami, Hedi, Bastin, Catherine, Takeda, Haruko, Laine, Aurelie, Van Laere, Anne-Sophie, Mota, Rodrigo, Darbagshahi, Saied Naderi, Dehareng, Frederic, Grelet, Clement, Vanlierde, Amelie, Froidmont, Eric, Becker, Frank, Schulze, Martin, and Vera, Sergio Palma

Subjects
nutrition, FARMS, POLLUTION, Fourier-transform mid-infrared spectrometry, DIETARY-PROTEIN, modeling, Veterinary Sciences, STANDARDIZATION, PERFORMANCE, environment
Abstract

Improving nitrogen use efficiency (NUE) at both the individual cow and the herd level has become a key target in dairy production systems, for both environmental and economic reasons. Cost-effective and large-scale phenotyping methods are required to improve NUE through genetic selection and by feeding and management strategies. The aim of this study was to evaluate the possibility of using mid-infrared (MIR) spectra of milk to predict individual dairy cow NUE during early lactation. Data were collected from 129 Holstein cows, from calving until 50 d in milk, in 3 research herds (Denmark, Ireland, and the UK). In 2 of the herds, diets were designed to challenge cows metabolically, whereas a diet reflecting local management practices was offered in the third herd. Nitrogen intake (kg/d) and nitrogen excreted in milk (kg/d) were calculated daily. Nitrogen use efficiency was calculated as the ratio between nitrogen in milk and nitrogen intake, and expressed as a percentage. Individual daily values for NUE ranged from 9.7 to 81.7%, with an average of 36.9% and standard deviation of 10.4%. Milk MIR spectra were recorded twice weekly and were standardized into a common format to avoid bias between apparatus or sampling periods. Regression models predicting NUE using milk MIR spectra were developed on 1,034 observations using partial least squares or support vector machines regression methods. The models were then evaluated through (1) a cross-validation using 10 subsets, (2) a cow validation excluding 25% of the cows to be used as a validation set, and (3) a diet validation excluding each of the diets one by one to be used as validation sets. The best statistical performances were obtained when using the support vector machines method. Inclusion of milk yield and lactation number as predictors, in combination with the spectra, also improved the calibration. In cross-validation, the best model predicted NUE with a coefficient of determination of cross-validation of 0.74 and a relative error of 14%, which is suitable to discriminate between low- and high-NUE cows. When performing the cow validation, the relative error remained at 14%, and during the diet validation the relative error ranged from 12 to 34%. In the diet validation, the models showed a lack of robustness, demonstrating difficulties in predicting NUE for diets and for samples that were not represented in the calibration data set. Hence, a need exists to integrate more data in the models to cover a maximum of variability regarding breeds, diets, lactation stages, management practices, seasons, MIR instruments, and geographic regions. Although the model needs to be validated and improved for use in routine conditions, these preliminary results showed that it was possible to obtain information on NUE through milk MIR spectra. This could potentially allow large-scale predictions to aid both further genetic and genomic studies, and the development of farm management tools.

Published
2020

21. Evidence for genetic variance in resistance to tuberculosis in Great Britain and Irish Holstein-Friesian populations

Author

Bermingham Mairead L, Brotherstone Susan, Berry Donagh P, More Simon J, Good Margaret, Cromie Andrew R, White Ian MS, Higgins Isabella M, Coffey Mike, Downs Sara H, Glass Elizabeth J, Bishop Stephen C, Mitchell Andy P, Clifton-Hadley Richard S, and Woolliams John A

Subjects
Medicine, Science
Abstract

Abstract Background Here, we jointly summarise scientific evidence for genetic variation in resistance to infection with Mycobacterium bovis, the primary agent of bovine tuberculosis (TB), provided by two recent and separate studies of Holstein-Friesian dairy cow populations in Great Britain (GB) and Ireland. Methods The studies quantified genetic variation within archived data from field and abattoir surveillance control programmes within each country. These data included results from the single intradermal comparative tuberculin test (SICTT), abattoir inspection for TB lesions and laboratory confirmation of disease status. Threshold animal models were used to estimate variance components for responsiveness to the SICTT and abattoir confirmed M. bovis infection. The link functions between the observed 0/1 scale and the liability scale were the complementary log-log in the GB, and logit link function in the Irish population. Results and discussion The estimated heritability of susceptibility to TB, as judged by responsiveness to the SICTT, was 0.16 (0.012) and 0.14 (0.025) in the GB and Irish populations, respectively. For abattoir or laboratory confirmation of infection, estimates were 0.18 (0.044) and 0.18 (0.041) from the GB and the Irish populations, respectively. Conclusions Estimates were all significantly different from zero and indicate that exploitable variation exists among GB and Irish Holstein Friesian dairy cows for resistance to TB. Epidemiological analysis suggests that factors such as variation in exposure or imperfect sensitivity and specificity would have resulted in underestimation of the true values.

Published
2011
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25. Comparison of the transcriptome in circulating leukocytes in early lactation between primiparous and multiparous cows provides evidence for age-related changes.

Author

Buggiotti, Laura, Cheng, Zhangrui, Salavati, Mazdak, Wathes, Claire D., the Genotype plus Environment Consortium, Fahey, Alan, Crisà, Alessandra, Fouladi, Ali, Wylie, Alistair, Vanlierde, Amelie, Fogh, Anders, Santoro, Andreia, Cromie, Andrew, Van Laere, Anne-Sophie, Pearn, Armin, Evertson, Arnold, Laine, Aurelie, Bernardo, Beatriz Sanz, Moioli, Bianca, and Vanranst, Bonny

Subjects
LACTATION, TRANSCRIPTOMES, COWS, LACTATION in cattle, LEUCOCYTES, DNA replication, ZINC-finger proteins
Abstract

Background: Previous studies have identified many immune pathways which are consistently altered in humans and model organisms as they age. Dairy cows are often culled at quite young ages due to an inability to cope adequately with metabolic and infectious diseases, resulting in reduced milk production and infertility. Improved longevity is therefore a desirable trait which would benefit both farmers and their cows. This study analysed the transcriptome derived from RNA-seq data of leukocytes obtained from Holstein cows in early lactation with respect to lactation number. Results: Samples were divided into three lactation groups for analysis: i) primiparous (PP, n = 53), ii) multiparous in lactations 2–3 (MP 2–3, n = 121), and iii) MP in lactations 4–7 (MP > 3, n = 55). Leukocyte expression was compared between PP vs MP > 3 cows with MP 2–3 as background using DESeq2 followed by weighted gene co-expression network analysis (WGCNA). Seven modules were significantly correlated (r ≥ 0.25) to the trait lactation number. Genes from the modules which were more highly expressed in either the PP or MP > 3 cows were pooled, and the gene lists subjected to David functional annotation cluster analysis. The top three clusters from modules more highly expressed in the PP cows all involved regulation of gene transcription, particularly zinc fingers. Another cluster included genes encoding enzymes in the mitochondrial beta-oxidation pathway. Top clusters up-regulated in MP > 3 cows included the terms Glycolysis/Gluconeogenesis, C-type lectin, and Immunity. Differentially expressed candidate genes for ageing previously identified in the human blood transcriptome up-regulated in PP cows were mainly associated with T-cell function (CCR7, CD27, IL7R, CAMK4, CD28), mitochondrial ribosomal proteins (MRPS27, MRPS9, MRPS31), and DNA replication and repair (WRN). Those up-regulated in MP > 3 cows encoded immune defence proteins (LYZ, CTSZ, SREBF1, GRN, ANXA5, ADARB1). Conclusions: Genes and pathways associated with lactation number in cows were identified for the first time to date, and we found that many were comparable to those known to be associated with ageing in humans and model organisms. We also detected changes in energy utilization and immune responses in leukocytes from older cows. [ABSTRACT FROM AUTHOR]

Published
2021
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31. In vitro characterisation of fresh and frozen sex-sorted bull spermatozoa

Author

Department of Agriculture, Food and the Marine, Holden, Shauna A., Murphy, Craig, Moreno, Juan F, Butler, Stephen T, Cromie, Andrew R., Lonergan, Patrick, Fair, Seán, Department of Agriculture, Food and the Marine, Holden, Shauna A., Murphy, Craig, Moreno, Juan F, Butler, Stephen T, Cromie, Andrew R., Lonergan, Patrick, and Fair, Seán

Abstract

peer-reviewed, This study sought to compare the in vitro characteristics of fresh and frozen non-sorted (NS) and sex-sorted (SS) bull spermatozoa. Experiment 1: Holstein–Friesian ejaculates (n = 10 bulls) were split across four treatments and processed: (1) NS fresh at 3 × 106 spermatozoa, (2) X-SS frozen at 2 × 106 spermatozoa, (3) X-SS fresh at 2 × 106 spermatozoa and (4) X-SS fresh at 1 × 106 spermatozoa. NS frozen controls of 20 × 106 spermatozoa per straw were sourced from previously frozen ejaculates (n = 3 bulls). Experiment 2: Aberdeen Angus ejaculates (n = 4 bulls) were split across four treatments and processed as: (1) NS fresh 3 × 106 spermatozoa, (2) Y-SS fresh at 1 × 106 spermatozoa, (3) Y-SS fresh at 2 × 106 spermatozoa and (4) X-SS fresh at 2 × 106 spermatozoa. Controls were sourced as per Experiment 1. In vitro assessments for progressive linear motility, acrosomal status and oxidative stress were carried out on Days 1, 2 and 3 after sorting (Day 0 = day of sorting. In both experiments SS fresh treatments had higher levels of agglutination in comparison to the NS fresh (P < 0.001), NS frozen treatments had the greatest PLM (P < 0.05) and NS spermatozoa exhibited higher levels of superoxide anion production compared with SS spermatozoa (P < 0.05). Experiment 1 found both fresh and frozen SS treatments had higher levels of viable acrosome-intact spermatozoa compared with the NS frozen treatments (P < 0.01)., ACCEPTED, peer-reviewed

Published
2017

32. A dual targeted β-defensin and exome sequencing approach to identify, validate and functionally characterise genes associated with bull fertility

Author

Whiston, Ronan, primary, Finlay, Emma K., additional, McCabe, Matthew S., additional, Cormican, Paul, additional, Flynn, Paul, additional, Cromie, Andrew, additional, Hansen, Peter J., additional, Lyons, Alan, additional, Fair, Sean, additional, Lonergan, Patrick, additional, O’ Farrelly, Cliona, additional, and Meade, Kieran G., additional

Published
2017
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34. Predicted carcass meat yield and primal cut yields in cattle divergent in genetic merit for a terminal index.

Author

Connolly, Stephen M, Cromie, Andrew R, Sleator, Roy D, and Berry, Donagh P

Subjects
CATTLE carcasses, BEEF cattle, MEAT industry, PHENOTYPES, FOOD production
Abstract

Several studies have clearly demonstrated the favorable impact of genetic selection on increasing beef cattle performance within the farm gate. Few studies, however, have attempted to quantify the value of genetic selection to downstream sectors of the beef industry, such as the meat processing sector. The objective of the current study was to characterize detailed carcass attributes of animals divergent in genetic merit for a terminal index as well as individual measures of genetic merit for carcass weight, conformation, and fat. The data used consisted of 53,674 young bulls and steers slaughtered between the years 2010 and 2013 in multiple Irish processing plants. All animals had a genetic evaluation as well as phenotypic measures of carcass characteristics. A terminal index, based on pedigree index for calving performance, feed intake, and carcass traits, calculated from the Irish national genetic evaluations, was obtained for each animal. Animals were categorized into four terminal index groups based on genetic merit estimates derived prior to the expression of the carcass phenotype by the animal. The association between genetic merit for terminal index with predicted phenotypic carcass red meat yield, carcass fat, carcass bone, and carcass composition, as well as between genetic merit for carcass weight, conformation, and fat with predicted phenotypic carcass red meat yield and composition were all quantified using linear mixed models. A greater terminal index value was associated with, on average, heavier phenotypic weights of each wholesale cut category. A greater terminal index value was also associated with a greater weight of meat and bone, but reduced carcass fat. Relative to animals in the lowest 25% genetic merit group, animals in the highest 25% genetic merit group had, on average, a greater predicted yield of very high value cuts (4.52 kg), high value cuts (13.13 kg), medium value cuts (6.06 kg), low value cuts (13.25 kg) as well as more total meat yield (37 kg). The results from the present study clearly signify a benefit to meat processers from breeding programs for terminal characteristics; coupled with the previously documented benefits to the producer, the benefits of breeding programs across the entire food production chain are obvious. [ABSTRACT FROM AUTHOR]

Published
2019
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36. Imputation of microsatellite alleles from dense SNP genotypes for parentage verification across multiple Bos taurus and Bos indicus breeds

Author

McClure, Matthew C, primary, Sonstegard, Tad S, additional, Wiggans, George R, additional, Van Eenennaam, Alison L, additional, Weber, Kristina L, additional, Penedo, Cecilia T, additional, Berry, Donagh P, additional, Flynn, John, additional, Garcia, Jose F, additional, Carmo, Adriana S, additional, Regitano, Luciana C A, additional, Albuquerque, Milla, additional, Silva, Marcos V G B, additional, Machado, Marco A, additional, Coffey, Mike, additional, Moore, Kirsty, additional, Boscher, Marie-Yvonne, additional, Genestout, Lucie, additional, Mazza, Raffaele, additional, Taylor, Jeremy F, additional, Schnabel, Robert D, additional, Simpson, Barry, additional, Marques, Elisa, additional, McEwan, John C, additional, Cromie, Andrew, additional, Coutinho, Luiz L, additional, Kuehn, Larry A, additional, Keele, John W, additional, Piper, Emily K, additional, Cook, Jim, additional, Williams, Robert, additional, and Van Tassell, Curtis P, additional

Published
2013
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37. Understanding genetic indices for dairy and beef cattle (Part I).

Author

Cromie, Andrew

Subjects
*DAIRY cattle genetics, *BEEF cattle, *CATTLE genetics, *ANIMAL breeding, *DWARFISM, *CHROMOSOME abnormalities, *QUANTITATIVE genetics, *GENETICS
Abstract

Think back to your training on genetics. What did it consist of? Single genes, such as coat colour and dwarfism, lethal recessives such as BLAD and CVM and chromosomal aberrations, such as freemartins. How much was there on the benefits of quantitative genetic variation in a trait and how this information could be used to improve future profits from breeding? Probably not a lot, but then again the role and value of genetics as a tool to influence farm profit has changed dramatically over the past few years, particularly since the introduction of the Economic Breeding Index (EBI) in dairy cattle and Suckler Beef Value (SBV) in beef cattle. INSET: CONTINUING EDUCATION: READER QUESTIONS AND ANSWERS. [ABSTRACT FROM AUTHOR]

Published
2011

38. Prediction of Trained Panel Sensory Scores for Beef with Non-Invasive Raman Spectroscopy.

Author

Cafferky, Jamie, Cama-Moncunill, Raquel, Sweeney, Torres, Allen, Paul, Cromie, Andrew, and Hamill, Ruth M.

Subjects
RAMAN spectroscopy, BEEF quality, STEAK (Beef), MUSCLE aging, CHEMOMETRICS, FORECASTING, ERECTOR spinae muscles
Abstract

The objective of this study was to investigate Raman spectroscopy as a tool for the prediction of sensory quality in beef. Raman spectra were collected from M. longissimus thoracis et lumborum (LTL) muscle on a thawed steak frozen 48 h post-mortem. Another steak was removed from the muscle and aged for 14 days before being assessed for 12 sensory traits by a trained panel. The most accurate coefficients of determination of cross validation (R2CV) calibrated within the current study were for the trained sensory panel textural scores; particularly tenderness (0.46), chewiness (0.43), stringiness (0.35) and difficulty to swallow (0.33), with practical predictions also achieved for metallic flavour (0.52), fatty after-effect (0.44) and juiciness (0.36). In general, the application of mathematical spectral pre-treatments to Raman spectra improved the predictive accuracy of chemometric models developed. This study provides calibrations for valuable quality traits derived from a trained sensory panel in a non-destructive manner, using Raman spectra collected at a time-point compatible with meat management systems. [ABSTRACT FROM AUTHOR]

Published
2022
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39. A dual targeted β-defensin and exome sequencing approach to identify, validate and functionally characterise genes associated with bull fertility

Author

Irish Department of Agriculture, Food and the Marine, Whiston, Ronan, Finlay, Emma K., McCabe, Matthew S., Cormican, Paul, Flynn, Paul, Cromie, Andrew R., Hansen, Peter J., Lyons, Alan, Fair, Seán, Lonergan, Patrick, O'Farrelly, Cliona, Meade, Kieran G., Irish Department of Agriculture, Food and the Marine, Whiston, Ronan, Finlay, Emma K., McCabe, Matthew S., Cormican, Paul, Flynn, Paul, Cromie, Andrew R., Hansen, Peter J., Lyons, Alan, Fair, Seán, Lonergan, Patrick, O'Farrelly, Cliona, and Meade, Kieran G.

Abstract

peer-reviewed, Bovine fertility remains a critical issue underpinning the sustainability of the agricultural sector. Phenotypic records collected on >7,000 bulls used in artificial insemination (AI) were used to identify 160 reliable and divergently fertile bulls for a dual strategy of targeted sequencing (TS) of fertilityrelated β-defensin genes and whole exome sequencing (WES). A haplotype spanning multiple β-defensin genes and containing 94 SNPs was significantly associated with fertility and functional analysis confirmed that sperm from bulls possessing the haplotype showed significantly enhanced binding to oviductal epithelium. WES of all exons in the genome in 24 bulls of high and low fertility identified 484 additional SNPs significantly associated with fertility. After validation, the most significantly associated SNP was located in the FOXJ3 gene, a transcription factor which regulates sperm function in mice. This study represents the first comprehensive characterisation of genetic variation in bovine β-defensin genes and functional analysis supports a role for β-defensins in regulating bull sperm function. This first application of WES in AI bulls with divergent fertility phenotypes has identified a novel role for the transcription factor FOXJ3 in the regulation of bull fertility. Validated genetic variants associated with bull fertility could prove useful for improving reproductive outcomes in cattle.

40. The impact of storage temperature and sperm number on the fertility of liquid-stored bull semen.

Author

Murphy C, Holden SA, Murphy EM, Cromie AR, Lonergan P, and Fair S

Abstract

In Ireland, liquid bull semen is stored at unregulated ambient temperatures, typically at 5×106 spermatozoa per dose, and inseminated within 2.5 days of collection. In Experiment 1, the effect of storage temperature (5, 15, 22, 32°C and fluctuations (Flux) between these temperatures) on progressive motility, viability, acrosomal status, DNA fragmentation and osmotic resistance was assessed. In Experiment 2, the field fertility of liquid semen at 5, 4 and 3×106 spermatozoa per dose, up to Day 2 after collection, was assessed in comparison to frozen-thawed semen at 20×106 spermatozoa per dose (n=35328 inseminations). In Experiment 1, storage at 15°C resulted in the highest progressive motility (PP6 spermatozoa per dose on Day 2 of storage was reduced in comparison to frozen-thawed semen (P<0.01). In conclusion, liquid semen is versatile between storage temperatures of 5 and 22°C, but demonstrates reduced fertility on Day 2 of storage at lower sperm numbers in comparison to frozen-thawed semen.

Published
2015
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