Sammy E. Aggrey
Areas of Expertise
- Quantitative and Molecular Genetics/Bioinformatics
- University of British Columbia-Vancouver, BC, Canada-Ph.D.
- Canada’s Natural Science and Engineering Council Postdoctoral Fellow- McGill University
- Functional Genomics
- Growth and Skeletal Modeling
- Genetic covariance of fitness component
- Molecular basis of heat stress
- Dr. Arthur B. Karnuah
Undergraduate Teaching Responsibility
- POUL 3720 Poultry Breeding
Graduate Teaching Responsibility
- POUL8750 Quantitative Genetics
- POUL 8790 Breeding Strategies
- Interface between nutrition and functional genomics processes to provide molecular understanding of how dietary components affect feed utilization efficiency, growth and body composition using genome wide DNA/RNA sequencing, (Next generation sequencing-RNA-seq) micro-array and quantitative PCR technologies.
- Identification of quantitative trait loci (QTL) for growth, fatness and skeletal traits; mapping functional/candidate genes for growth and developmental traits and evaluating genetic markers for traits of economic importance (GWAS).
- Growth modeling/ Genetics-Nutrition Interactions
- Identification and prediction of microRNA and composite tandem repeats
- Genetic architecture of QTL regions
- Gene network modeling (Gene traffic networks algorithms
- Database and Pipeline for analyzing high throughput data
W. H. Muir and S. E. Aggrey, 2003. Poultry Genetics, Breeding and Biotechnology. CABI, U.K. 744pp.
Aggrey, S.E., 2007. Poultry Breeding and Genetics. 4pp In: Encyclopedia of Animal Science. W.G. Pond and A. W. Bell (Eds). Taylor and Francis, NY
Chen, C.Y., I Misztal, I. Aquilar, S. Tsuruta, T.H. Meuwissen, S.E. Aggrey, T. Wing and W.M. Muir, 2011. Genome-wide marker-assisted selection combining all pedigree phenotypic information with genotype data in one step: An example using broiler chickens. J. Anim. Science 89: 23-28.
Aggrey, S.E., A. B. Karnuah, B. Sebastian and N.B. Anthony, 2010. Genetic properties of feed efficiency parameters. Genetic Selection Evolution 42: 25 doi:10.1186/1297-9686-42-25
Byerly, M. S., J. Simon, L. A. Cogburn, E. Le Bihan-Duval, M. J. Duclos, S. E. Aggreyand T. E. Porter, 2010. Transcriptional profiling of the hypothalamus during development of adiposity in genetically selected fat and lean chickens. Physiological Genomics 42: 157-167.
Ankra-Badu, G.A., D. Shriner, E. Le Bihan-Duval, S. Mignon-Grasteau, F. Pitel, C. Beaumont, M. J. Duclos, J. Simon, T. E. Porter, A. Vignal, L. A. Cogburn, D. B. Allison, N. Yi and S. E. Aggrey, 2010. Mapping main, epistatic and sex-specific QTL for body composition in a chicken population divergently selected for low or high growth weight. BMC Genomics 11: 107.
Ankra-Badu, G.A., E. Le Bihan-Duval, F. Pitel, C. Beaumont, M.J. Duclos, J. Simon, W. Carre, T.E. Porter, A. Vignal, L.A. Cogburn and S.E. Aggrey, 2010. Quantitative trait loci for growth and skeletal traits in meat-type chicken. Animal Genetics 41:400-405.
Sebastian B., and S. E. Aggrey, 2008. Specificity and sensitivity of PROMIR, ERPIN and MIR-ABELA in predicting pre-microRNAs in the chicken genome. In-Silico Biol 8:1-5.
Aggrey, S.E., 2008. Accuracy of growth model parameters: Effects of frequency and duration of data collection, and missing information. Growth Dev. Aging 71: 45-54.
Carre, W., X. Wang, T. E. Porter, Y Nys, J. Tang, E. Bernberg, R. Morgan, J. Burnside,S. E. Aggrey, J. Simon and L. A. Cogburn, 2006. Chicken genomic resources: sequencing and annotation of 37,557 ESTs from single and multiple Tissue cDNA libraries and CAP3 assembly of a chicken gene index. Physiological Genomics 25:514-524.
For a full list of publications use Google Scholar, Pubmed or Web of Science.