Main Research Projects (Current and Recent)
1. Increasing feed efficiency and reducing methane emissions through genomics: a new promising goal for the Canadian dairy industry (Large scale applied research project competition- Genome Canada, Schenkel (Co-applicant/Principle Investigator since January 2019), 2015 to 2020)
The overall goal of the project is to produce genomic predictions for Feed Efficiency (FE) and Methane Emissions (ME) that are ready for breeding application in Canada’s dairy cattle industry. These tools will enable producers to select cattle for improved FE and reduced ME, while still maintaining the high productivity, health and fertility of dairy cows.
2. Designing a reference population to accelerate genetic gains for novel traits in Canadian Holstein project (AAFC- Dairy cluster III Grant, Schenkel (Principal Investigator/Principle Investigator since January 2019), 2018 to 2022)
The main objective of this project is to generate tools to maximize the rate of genetic progress for novel traits by designing an enlarged female reference population for genomic prediction of novel traits with ssGBLUP and to investigate the incorporation of additional “-omics” data in Canadian dairy cattle breeding programs.
3. Understanding the impact of cutting-edge genomic technologies and novel phenotypes on breeding strategies for optimum sustainable genetic progress in Canadian dairy cattle project (AAFC- Dairy cluster III Grant, Schenkel (Co-applicant), 2018 to 2022)
The development of novel traits (e.g. feed efficiency, methane emission, etc.), new genotyping technologies (e.g. genotyping by sequencing), and novel tools (e.g. gene editing) applied in the dairy industry is advancing at an unprecedented rate. Wide-spread application of these new technologies will fundamentally change the accuracy of breeding values and the selection strategies used for genetic evaluation of dairy cattle. While these novel traits, technologies and tools are expected to further increase accuracy of genetic evaluations, the medium and long-term effects of their implementation into routine breeding programs at a population level are largely unknown. There is a clear need to assess current and prospective breeding strategies, and to compare the benefits of various strategies and tools for genetic improvement and selection. Ideally, the use of these new technologies will help ensure sustainability, genetic diversity, and will help to further improve production efficiency. The objective of this proposal is to analyze and compare the benefits of various strategies and novel tools for breed improvement.
4. Breeding livestock for climate resilience: the capacity to maintain production and fitness in a changing climate (Canada First Research Excellence Fund, Schenkel (Principle investigator), 2017 to 2019)
This project is part of the CFREF Food from Thought - Agricultural Systems for a Healthy Planet project led by the University of Guelph. The main goal of this project is to identify genes, as well as structural and regulatory regions of the genome of livestock species (with a focus on ruminant species such as beef and dairy cattle, sheep and goats), that are involved in adapting to different stressors triggered through climate change for allowing efficient selection for robust livestock tolerant to extreme temperatures and more productively efficient.
5. Implementation of genomic selection to improve productivity and health traits in Ontario dairy goats (Gov-OMAFRA Agreement Research Programs, Schenkel (Principal Investigator), 2017 to 2019)
The overarching objective of this project is to implement genomic selection in the dairy goat industry to promote faster genetic progress in production, conformation, reproduction and health traits in collaboration with Canadian Centre for Swine Improvement, leveraging from a previous genomic project. Specific objectives include increase the size of the reference population for the two major dairy goat breeds in Canada, named Alpine and Saanen; evaluate and validate prediction methods and corresponding genomic evaluation tools; achieve a better understanding of the genetic background of the traits of interest by estimating genetic parameters using genomic information and also performing GWAS studies; Increase the accuracies of genomic breeding values for various economically important traits by an increased reference population size and an optimized genomic evaluation model; transfer the genomic tools to Canadian Centre for Swine Improvement for the use by the dairy goat producers.
6. Genetic Improvement of Canadian Lamb Carcass Yield, Quality and Growth Traits (NSERC-CRD, Schenkel (Principal Investigator), 2016 to 2019)
In the Canadian lamb industry, carcass yield and quality traits are of considerable importance because these relate directly supply chain production efficiency, economic profitability and consumer choice of domestic products. This study seeks to examine genetic bases of carcass yield, fat depth and conformation in commercial lambs, and consider genetic relationships with early growth, ultrasound measurements and other economically important production and reproduction traits. The goal is to find optimal selection methods to improve carcass yield, quality and growth in commercial lamb breeding programs. This will be accomplished by analysing carcass processing data that were recorded over at least 2.5 years from commercial lambs that are part of the Canadian Sheep Genetic Evaluation System (CSGES) hosted at CGIL.
1. da Cruz, V. A., Brito, L. F., Schenkel, F., de Oliveira, H. R., Jafarikia, M., Zeny Feng (2019). Strategies for within-litter selection of piglets using ultra-low density SNP panels. Livestock Science, 220, 173-179, doi: 10.1016/j.livsci.2018.12.027.
2. Vargas*, G., Neves, H. H., Brito, L. F., Schenkel, F. S., Albuquerque, L. G., Roberto Carvalheiro (2019). Genetic and genomic analyses of testicular hypoplasia in Nellore cattle. PLoS ONE, 14 (1), e0211159, doi: 10.1371/journal.pone.0211159.
3. Oliveira*, H., Lourenco, D., Masuda, Y., Misztal, I., Tsuruta, S., Janusz Jamrozik; Luiz Brito; Fabyano Fonseca e Silva; Flavio Schenkel (2019). Application of single-step genomic evaluation using multiple-trait random regression test-day models in dairy cattle. Journal of Dairy Science, 102 (3), 2365–2377, doi: 10.3168/jds.2018-15466.
4. Rovere, G., de los Campos, G., Tempelman, R. J., Vazquez, A. I., Miglior, F., F. Schenkel, A. Cecchinato, G. Bittante, H. Toledo-Alvarado, and A. Fleming (2019). A landscape of the heritability of Fourier-Transform infrared spectral wavelengths of milk samples by parity and lactation stage in Holstein cows. Journal of Dairy Science, 102 (2), 1354-1363, doi: 10.3168/jds.2018-15109.
5. Guarini*, A., Lourenco, D., Brito, L., Sargolzaei, M., Baes, C., Miglior, Filippo, Misztal, Ignacy, and Schenkel, Flavio (2019). Genetics and genomics of reproductive disorders in Holstein cattle. Journal of Dairy Science, 102 (2), 1341–1353, doi: 10.3168/jds.2018-15038.
6. Fonseca*, P. A., Id-Lahoucine, S., Reverter, A., Medrano, J. F., Fortes, M. R., Joaquim Casellas, Filippo Miglior, Luiz Brito, Maria Raquel S. Carvalho, Flávio S. Schenkel, Loan T. Nguyen, Laercio Porto-Neto, Milton G. Thomas, and Angela Canovas (2019). Combining multi-OMICs information to identify key-regulator genes for pleiotropic effect on fertility and production traits in beef cattle. PLoS ONE., doi: 10.3168/jds.2018-15296.
7. Id-Lahoucine*, S., Canovas, A., Jaton, C., Miglior, F., Fonseca, P. A., Sargolzaei, Mehdi; Miller, Stephen ; Schenkel, Flavio; Medrano, Juan; Casellas, Joaquim. (2019). Implementation of Bayesian methods to identify SNP and haplotype regions with transmission ratio distortion across the whole genome: TRDscan v.1.0. Journal of Dairy Science., doi: 10.3168/jds.2018-15296.
8. Fonseca*, P. A., Dos Santos, F. C., Lam, S., Suárez-Vega, A., Miglior, F., F. Schenkel, Diniz, L.F.A., Id-Lahoucine, S., Carvalho, M.R.S., and Cánovas, A. (2018). Genetic mechanisms underlying spermatic and testicular traits within and among cattle breeds: Systematic review and prioritization of GWAS results. Journal of Animal Science, 96 (12), 4978–4999, doi: 10.1093/jas/sky382.
9. Do, D. N., Schenkel, F. S., Miglior, F., Zhao, X., & Ibeagha-Awemu, E. M. (2018). Genome wide association study identifies novel potential candidate genes for bovine milk cholesterol content. Scientific Reports, 8, 13239, doi: 10.1038/s41598-018-31427-0.
10. Vargas*, G., Schenkel, F., Brito, L. F., Neves, H. H., Munari, D. P., Arione A Boligon, and Roberto Carvalheiro (2018). Unravelling biological biotypes for growth, visual score and reproductive traits in Nellore cattle via principal component analysis. Livestock Science, 217, 37-43, doi: 10.1016/j.livsci.2018.09.010.
11. Brito, L. F., Mallikarjunappa, S., Sargolzaei, M., Koeck, A., Chesnais, J., F. S. Schenkel, K. G. Meade, F. Miglior, N. A. Karrow (2018). The genetic architecture of milk ELISA scores as an indicator of Johne's disease (paratuberculosis) in dairy cattle. Journal of Dairy Science, 101 (11), 10062–10075, doi: 10.3168/jds.2017-14250.
12. Massender*, E., Brito, L. F., Canovas, A., Baes, C. F., Kennedy, D., and F.S. Schenkel (2018). A genetic evaluation of growth, ultrasound, and carcass traits at alternative slaughter end points in crossbred heavy lambs. Journal of Animal Science., doi: 10.1093/jas/sky455.
13. Oliveira*, H. R., Brito, L. F., Silva, F. F., Lourenco, D. A.L., Jamrozik, J., and F. S. Schenkel (2018). Genomic prediction of lactation curves for milk, fat, protein and somatic cell score in dairy cattle. Journal of Dairy Science., doi: 10.3168/jds.2018-15159.
14. Stachowicz, K., Brito, L. F., Oliveira, H. R., Miller, S. P., & Schenkel, F. (2018). Assessing genetic diversity of various Canadian sheep breeds through pedigree analyses. Canadian Journal of Animal Science, 98 (4), 741-749, doi: 10.1139/CJAS-2017-0187.
15. Karimi*, Z., Sargolzaei, M., Robinson, J. A.B., & Schenkel, F. (2018). Assessing haplotype-based models for genomic evaluation in Holstein cattle. Canadian Journal of Animal Science, 98 (4), 750-759, doi: 10.1139/CJAS-2018-0009.
16. Do, D. N., Fleming, A., Schenkel, F., Miglior, F., Zhao, X., Ibeagha-Awemu, Eveline (2018). Genetic parameters of milk cholesterol content in Holstein cattle. Canadian Journal of Animal Science, 98 (4), 714-722, doi: 10.1139/CJAS-2018-0010.
17. Bore, R., Brito, L. F., Jafarikia, M., Bouquet, A., Maignel, L., Brian Sullivan, Flavio S. Schenkel (2018). Genomic data reveals large similarities among Canadian and French maternal pig lines. Canadian Journal of Animal Science, 98 (4), 809-817, doi: 10.1139/CJAS-2017-0103.
18. Forutan*, M., Mahyari, S. A., Baes, C., Melzer, N., Schenkel, F., and Mehdi Sargolzaei (2018). Inbreeding and runs of homozygosity before and after genomic selection in North American Holstein cattle. BMC Genomics, 19 (98)., doi: 10.1186/s12864-018-4453-z.
19. de Oliveira*, H. R., Silva, F. F., Brito, L. F., Guarini, A. R., Jamrozik, J., Flávio S. Schenkel (2018). Comparing de-regression methods for genomic prediction of test day traits in dairy cattle. Journal of Animal Breeding and Genetics, 135 (2), 97-106, doi: 0.1111/jbg.12317.
20. Kroezen, V., Schenkel, F., Miglior, F., Baes, C. F., & Squires, E. J. (2018). Candidate gene association analyses for ketosis resistance in Holsteins. Journal of Dairy Science, 101 (6), 5240-5249, doi: 10.3168/jds.2017-13374.
Flavio's education and academic timeline
Please visit our Centre for Genetic Improvement of Livestock (CGIL) webpage: http://cgil.uoguelph.ca/