Sajjad Toghiani (PhD)

Research Geneticist

Profile

Sajjad is a Research Geneticist (Animals) at USDA in Animal Genomics and Improvement Laboratory with a background in animal breeding and genetics. His areas of interest are focused on the application of genomic information in livestock including genomic selection, genome-wide association studies, genotype imputation, and population genomics. His goals are to conduct research using cutting-edge genomic research in animal breeding to develop decision-making tools and improved algorithms to enhance animal health and welfare, environmental sustainability, and climate adaptability, and efficiently enhance productivity for producers.

Education

PhD University of Georgia (Athens, GA, USA)       2015-2018
College of Agricultural and Environmental Sciences
Department of Animal and Dairy Science
Majored in Animal Breeding and Genetics

MS University of Georgia (Athens, GA, USA)       2013-2015
College of Agricultural and Environmental Sciences
Department of Animal and Dairy Science
Majored in Animal Breeding and Genetics

MS Guilan University (Rasht, IRAN)             2005-2007
College of Agricultural Sciences
Department of Animal Science
Majored in Animal Breeding and Genetics

BS Shiraz University (Shiraz, IRAN)             2001-2005
College of Agricultural Sciences
Department of Animal Science
Majored in Animal Science

Professional Experience

USDA-ARS-AGIL – Beltsville, MD, USA
Research Geneticist (Animals)
January 2022 – Present

USDA-ARS-AGIL – Beltsville, MD, USA
Animal Scientist
March 2020 – January 2022

USDA-ARS-LRRL – Miles City, MT, USA
Postdoctoral Research Fellow as Geneticist
October 2018 – March 2020

Research Experience

University of Georgia , Graduate Research Assistant (PhD)
January 2015 – August 2018
PhD Dissertation: Implementing genomic selection method based on using Fst prioritized SNPs

University of Georgia , Graduate Research Assistant (M.S.)
January 2013 – December 2015
Master Thesis: Multi-generational imputation of SNP genotypes and accuracy of genomic selection

Iowa State University, Laboratory Research Assistant
September 2009 – January 2010

University of Guilan, Graduate Research Assistant (M.S.)
September 2005 – September 2007
Master Thesis: Estimation of genetic parameters for yield, fertility, and type traits in Iranian Holstein

Publications

Journal Publications and Conference Proceedings

• Déru, V., Tiezzi, F., VanRaden, P. M., Lozada-Soto, E. A., Toghiani, S., and Maltecca, C. (2024). Imputation accuracy from low to medium-density SNP chips for US crossbred dairy cattle. Journal of Dairy Science, 107(1), 398-411. https://doi.org/10.3168/jds.2023-23250
• VanRaden, P. M., Fok, G. C., Toghiani, S., Nicolazzi, E. L. (2023). Modeling identical twins and clones in genetic evaluations. Interbull Bulletin, (59), 26-27.
• Lozada-Soto, E. A., Gaddis, K. L. P., Tiezzi, F., Jiang, J., Ma, L., Toghiani, S., VanRaden, P. M., and Maltecca, C. (2023). Inbreeding depression for producer-recorded udder, metabolic, and reproductive diseases in US dairy cattle. Journal of Dairy Science. https://doi.org/10.3168/jds.2023-23909
• Nadri, S., Sadeghi-Sefidmazgi, A., Zamani, P., Ghorbani, G. R., and Toghiani, S. (2023). Implementation of Feed Efficiency in Iranian Holstein Breeding Program. Animals, 13(7), 1216. https://doi.org/10.3390/ani13071216
• Sumreddee, P., Ling, A., Toghiani, S., Hay, E. H., Hartono, E., Aggrey, S. E., and Rekaya, R. (2022). Estimation of old and new inbreeding and their effects on growth traits using pedigree and genomic information. In Proceedings of 12th World Congress on Genetics Applied to Livestock Production (WCGALP) pp. 952-955. Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-940-4_224
• Hay, E., Toghiani, S., Roberts, A. J., Paim, T., Kuehn, L. A., and Blackburn, H. D. (2022). Genetic architecture of a composite beef cattle population. In Proceedings of 12th World Congress on Genetics Applied to Livestock Production (WCGALP) pp. 826-829. Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-940-4_193
• Hay, E., Toghiani, S., Roberts, A. J., Paim, T., Kuehn, L. A., and Blackburn, H. D. (2022). Genetic architecture of a composite beef cattle population. Journal of Animal Science, 100(9), 1–13. https://doi.org/10.1093/jas/skac230
• Mahnani, A., Sadeghi-Sefidmazgi, A., Ansari-Mahyari, S., Ghiasi, H., and Toghiani, S. (2022). Genetic analysis of retained placenta and its association with reproductive disorder, production, and fertility traits of Iranian Holstein dairy cows. Theriogenology 189: 59-63. https://doi.org/10.1016/j.theriogenology.2022.04.008
• Toghiani, S., and VanRaden, P. (2021). National Index Correlations and Actual vs. Expected Use of Foreign Sires. Interbull Bulletin, (56), 52-59.
• Sumreddee, P., Hay, E. H., Toghiani, S., Roberts, A., Aggrey, S.E., and Rekaya, R. (2021). Grid search approach to discriminate between old and recent inbreeding using phenotypic, pedigree and genomic information. BMC genomics, 22(1), 1-17. https://doi.org/10.1186/s12864-021-07872-z
• Sumreddee, P., Toghiani, S., Hay, E. H., Roberts, A., Aggrey, S.E., and Rekaya, R. (2020). Runs of homozygosity and analysis of inbreeding depression. Journal of Animal Science, 98(12), skaa361. https://doi.org/10.1093/jas/skaa361
• Toghiani, S., Hay, E., Roberts, A., and Rekaya, R. (2020). Impact of cold stress on birth and weaning weight in a composite beef cattle breed. Livestock Science, 104053. https://doi.org/10.1017/S1751731120000531
• Toghiani, S., Hay, E., Fragomeni, B., Rekaya, R., and Roberts, A.J. (2020). Genotype by environment interaction in response to cold stress in a composite beef cattle breed. Animal-The International Journal of Animal Biosciences, 1-12. https://doi.org/10.1017/S1751731120000531
• Chang, L. Y., Toghiani, S., Hay, E. H., Aggrey, S. E., and Rekaya, R. (2019). A Weighted Genomic Relationship Matrix Based on Fixation Index (FST) Prioritized SNPs for Genomic Selection. Genes, 10(11),922. https://doi.org/10.3390/genes10110922
• Chang, L. Y., Toghiani, S., Aggrey, S. E., and Rekaya, R. (2019). Increasing accuracy of genomic selection in presence of high-density marker panels through the prioritization of relevant polymorphisms. BMC genetics, 20(1), 21. https://doi.org/10.1186/s12863-019-0720-5
• Aggrey, S. E., Toghiani, S., Chang, L. -Y., & Rekaya, R. (2019). Improving accuracy of genomic prediction using selected small sets of prioritized SNP markers. In Proc. 68th Annual Poultry Breeders Round Conference (pp. 1-10). St. Louis, MO.
• Sumreddee, P., Toghiani, S., Hay, E. H., Roberts, A., Aggrey, S.E., and Rekaya, R. (2018). Inbreeding depression in Line1 Hereford cattle population using pedigree and genomic information. Journal of Animal Science, 97(1), 1-18. https://doi.org/10.1093/jas/sky385
• Chang, L. Y., Toghiani, S., Ling, A., Aggrey, S. E., and Rekaya, R. (2018). High density marker panels, SNPs prioritizing and accuracy of genomic selection. BMC genetics, 19(1), 4. https://doi.org/10.1186/s12863-017-0595-2
• Toghiani, S., Hay, E., Sumreddee, P., Geary, T. W., Rekaya, R., and Roberts, A. J. (2017). Genomic prediction of continuous and binary fertility traits of females in a composite beef cattle breed. Journal of Animal Science, 95(11), 4787-4795. https://doi.org/10.2527/jas2017.1944
• Toghiani, S., Chang, L. Y., Ling, A., Aggrey, S. E., and Rekaya, R. (2017). Genomic differentiation as a tool for single nucleotide polymorphism prioritization for Genome wide association and phenotype prediction in livestock. Livestock Science, 205, 24-30. https://doi.org/10.1016/j.livsci.2017.09.007
• Chang, L. Y., Toghiani, S., Ling, A., Hay, E. H., Aggrey, S. E., and Rekaya, R. (2017). Analysis of multiple binary responses using a threshold model. Journal of Agricultural, Biological and Environmental Statistics, 22(4), 640-651. https://doi.org/10.1007/s13253-017-0305-6
• Toghiani, S., Aggrey, S. E., and Rekaya, R. (2016). Multi-generational imputation of single nucleotide polymorphism marker genotypes and accuracy of genomic selection. Animal-The International Journal of Animal Biosciences, 10(7), 1077-1085. https://doi.org/10.1017/S1751731115002906
• Toghiani, S. (2012). Genetic relationships between production traits and reproductive performance in Holstein dairy cows. Archives Animal Breeding, 55(5), 458-468. https://doi.org/10.5194/aab-55-458-2012
• Toghiani, S. (2011). Genetic parameters and correlations among linear type traits in the first lactation of Holstein Dairy cows. African Journal of Biotechnology, 10(9), 1507-1510.
• Toghiani Pozveh, S., Shadparvar, A. A., Shahrbabak, M. M., and Taromsari, M. D. (2009). Genetic analysis of reproduction traits and their relationship with conformation traits in Holstein cows. Livestock Science, 125(1), 84-87. https://doi.org/10.1016/j.livsci.2009.02.015

Poster Presentations

• Toghiani, S., Aggrey, S. E., and Rekaya, R. Fst based marker prioritization within QTL regions and its impact on genomic selection accuracy: Insights from a simulation study with high-density marker panels. The Allied Genetics Conference, Washington D.C., March 6 - 10, 2024.
• Toghiani, S., Aggrey, S. E., and Rekaya, R. A two-stage Fst prioritization approach in the presence of high-density marker panels: a simulation study. International Society for Animal Genetics (ISAG) Conference. Cape Town, South Africa, July 2 - 7, 2023.
• Lozada-Soto, E.A., Tiezzi, F., Jiang, J., Cole, J.B., Vanraden, P.M., Toghiani, S., and Maltecca, C. Effect of germplasm exchange strategies on genetic gain and diversity in dairy stud populations. Proc. The European Federation of Animal Science (EAAP) Congress. 2023; pp. 403.
• Sumreddee, P., Toghiani, S., Hay, E., Aggrey, S. E., and Rekaya, R. PSXII-29 Partitioning of Inbreeding Depression using Pedigree and Genomic Approaches. Journal of Animal Science, Volume 98, Issue Supplement_4, November 2020, Pages 247–248.
• Toghiani, S., Hay, E., Fragomeni, B., Rekaya, R., and Roberts, A. J. Genotype by environment interaction in response to cold stress in a composite beef cattle breed. Plant and Animal Genome XXVIII Conference, San Diego, CA, January 11 - 15, 2020.
• Sumreddee, P., Toghiani, S., Hay, E., Roberts, A., Aggrey, S. E., and Rekaya, R. Runs of homozygosity and analysis of inbreeding depression. Plant and Animal Genome XXVIII Conference. San Diego, CA, January 11 - 15, 2020.
• Chang, LY., S. Toghiani, S. Aggrey, and R. Rekaya. A weighted genomic relationship matrix based on Fst prioritized SNPs for genomic selection. American Society of Animal Science Annual Meeting, Austin, Texas, 2019.
• Rekaya, R., Toghiani, S., Sumreddee, P., Ling, A., and Aggrey, S. (2018). Multivariate genome wide association for continuous and discrete responses using multivariate Bernoulli prior. Journal of Animal Science, 96(suppl_3), 126-126.
• Sumreddee, P., Toghiani, S., Aggrey, S. E., and Rekaya, R. (2017).Joint genome-wide association analysis of continuous and discrete traits. Journal of Animal Science, 95(suppl_4), 104-105.
• Sumreddee, P., S. Toghiani, S. Aggrey, and R. Rekaya. Joint genome-wide association analysis of continuous and discrete traits. American Society of Animal Science Annual Meeting, Baltimore, Maryland, 2017.
• Toghiani, S., L. Chang, and R. Rekaya. Genome wide association in presence of high-density marker panels and genotyped causal variants. The Allied Genetics Conference, Orlando, Florida, 2016.
• Toghiani, S., and R. Rekaya. Multi-generational imputation of SNP genotypes and accuracy of genomic selection. Joint ADSA/ASAS Annual Meeting, Orlando, Florida, 2015.

Oral Presentations

• Toghiani, S., VanRaden, M., Gaddis, K. L., VandeHaar, M. J., and Tempelman, R. J. (2022). Phenotypic and genotypic impact of milk components and bodyweight composite on dry matter intake. In Journal of Dairy Science (Vol. 105, pp. 200-200).
• Toghiani, S., P. VanRaden. National Index Correlations and Expected vs. Actual Use of Foreign Sires. Interbull Virtual Conference, 2021, Leeuwarden, The Netherlands.
• Toghiani, S., Chang, L. Y., Hay, E. H., Roberts, A. J., Aggrey, S. E., and Rekaya, R. (2019). 330 A hybrid model for genomic selection using prioritized SNPs based on FST scores in the presence of non-genotyped animals. Journal of Animal Science, 97(Suppl 3), 51.
• Chang, L. Y., Toghiani, S., Aggrey, S. E., and Rekaya, R. (2017). Increasing accuracy of genomic selection in presence of high-density marker panels through the prioritization of relevant polymorphisms. Journal of Animal Science, 95(suppl_4), 91-92.
• Toghiani, S., Chang, L. Y., Aggrey, S. E., and Rekaya, R. (2017). A hybrid of prioritized SNP and polygenetic effect method for implementation of genomic selection. Journal of Animal Science, 95(supplement4), 92-92.
• Chang, L. Y., Toghiani, S., Aggrey, S. E., and Rekaya, R. (2016). High density marker panels, SNPs prioritizing and accuracy of genomic selection. Journal of Animal Science, 94(suppl_5), 141-142.
• Toghiani, S., Chang, L. Y., Aggrey, S. E., and Rekaya, R. (2016). SNP filtering using Fst and implications for genome wide association and phenotype prediction. Journal of Animal Science, 94(suppl_5), 143-143.

Book Chapters

• Toghiani, S. (2012). Quantitative Genetic Application in the Selection Process for Livestock Production. In J. Khalid (Ed.), Livestock Production (pp. Ch. 1). IntechOpen. https://doi.org/10.5772/51027

Editorial Activities

• Special issue Editor for Frontiers in Genetics – Livestock Genomics section: Reducing the Environmental Footprint of Livestock Through Genomic Selection.
• Editorial Board of Frontiers in Genetics as a Review Editor Livestock Genomics
• Special issue Editor for animals (MDPI) journal – Animal System and Management section: Animal Production in the Artificial Intelligence Era: Advances and Applications.

Honors and Awards

• USDA Employee Performance Award: Recipient of the monetary award in 2021 for contributing to the evaluation of international selection indices and the revision of the national selection index (NM$) to better account for feed intake associated with milk production and body weight traits in dairy cattle. Both research topics have been of wide interest to breeding companies, and national and international consumers of dairy products and primarily will benefit them for the foreseeable future.
• USDA-ARS Livestock and Range Research Laboratory (Miles City, MT) awarded a PhD Graduate Assistantship in 2016-2018
• Department of Animal and Dairy Science (University of Georgia) awarded a Master Graduate Assistantship in 2013-2015

Computer Skills

Programming: Fortran, SAS, R, Python, Unix shell scripting, Git and Github
Applications: MS Office (Word, Excel, PowerPoint, Outlook)
Analysis Tools: Plink (GWAS analysis software), Gensel (Bayesian method for GS/GWAS analysis), Blupf90 family (Genetic/Genomic evaluation), QMsim (QTL and marker simulator for livestock populations), FImpute (Genotype imputation tool),Bioconductor (Statistical and graphical methods for analyzing genomic data), Admixture (A tool to estimate individual ancestry from SNP genotype datasets)