Mehdi Sargolzaei

After earning MSc degree from Isfahan University of Technology in Iran, Dr. Sargolzaei completed his PhD at Niigata University in Japan. Both degrees were in animal genetics and breeding.
In 2006, he joined the Centre for Genetic Improvement of Livestock as a postdoc. He worked on a Genomic Selection project that resulted in official implementation of Genomic Evaluation for dairy cattle in Canada in 2009. Dr. Sargolzaei has developed several novel statistical methods and software tools aiming at analysing big genomic data. The driving force behind his software developments has been his keen interest in combining new statistical methods and advanced programming techniques to put theory in practice for analysing big genomic data.
Dr. Sargolzaei has worked as a researcher in dairy cattle industry since 2009, while keeping close tie with academia. He is currently working for Select Sires Inc., the largest dairy genetics company in North America, as Director of Genetic Research and Technology.

Dr. Sargolzaei's main areas of research are utilization of genomic information in livestock precision breeding, investigating new methodologies to increase accuracy of predicted genomic breeding values, immunogenomics, imputation and computational genomics.

Software

• snp1101 (For academic use please contact msargol@uoguelph.ca)
• FImpute v3 (Academic Version)
• QMSim v2
• CFC

• C. Bouwman, H. D. Daetwyler, A. J. Chamberlain, C. H. Ponce, M. Sargolzaei, ...... , M. E. Goddard, and B. J. Hayes. 2017. Meta-analysis of genome wide association studies for the stature of cattle reveals numerous common genes that regulate size in mammals. Nature Genetics, 50(3):362-367.
• Forutan M., S. A. Mahyari, C. Baes, N. Melzer, F. S. Schenkel, and M. Sargolzaei. 2017. Inbreeding and runs of homozygosity before and after genomic selection in North American Holstein cattle. BMC Genomics, 19:98.
• Chesnais, J., T. Cooper, G. Wiggans, M. Sargolzaei, J. Pryce and F. Miglior. 2015. Using genomics to enhance selection of novel traits in North American dairy cattle. Journal of Diary Science, 99:1-15.
• Sargolzaei, M., J. P. Chesnais and F. S. Schenkel. 2014. A new approach for efficient genotype imputation using information from relatives. BMC Genomics, 15:478.
• Thompson-Crispi, K. A., M. Sargolzaei, R. Ventura, M. Abo-Ismail, F. Miglior, F. S. Schenkel and B. A. Mallard. 2014. A genome-wide association study of immune response traits in Canadian Holstein cattle. BMC Genomics, 15:559.
• VanRaden, P. M., D. J. Null, M. Sargolzaei, G. R. Wiggans, M. E. Tooker, J. B. Cole, T. S. Sonstegard, E. E. Connor, M. Winters, J. B. C. H. M. van Kaam, B. J. Van Doormaal, M. A. Faust and G. A. Doak. 2012. Genomic imputation and evaluation using high density Holstein genotypes. Journal of Dairy Science, 96(1):668-678.
• Colleau, J. J. and M. Sargolzaei. 2011. MIM: An indirect method to assess inbreeding and coancestry in large incomplete pedigrees of selected dairy cattle. Journal of Animal Breeding and Genetics, 128(3):163-173.
• Sargolzaei, M. and F. S. Schenkel. 2009. QMSim: a large-scale genome simulator for livestock. Bioinformatics, 25: 680-681.
• Sargolzaei, M., F. S. Schenkel, G. B. Jansen and L. R. Schaeffer. 2008. Extent of linkage disequilibrium in Holstein cattle in North America. Journal of Dairy Science, 91: 2106-2117.
• Sargolzaei, M., H. Iwaisaki and J. J. Colleau. 2005. A fast algorithm for computing inbreeding coefficients in large populations. Journal of Animal Breeding and Genetics, 122: 325-331.