Academic Profile

Biography

Education

Obihiro University of Agriculture and Veterinary Medicine (B.S.)
Obihiro University of Agriculture and Veterinary Medicine (M.S.)
University of Nebraska-Lincoln (Ph.D.)

Research Interests

Quantitative genetics in animals (animal breeding and genetic) analyzing phenotypic data, pedigree information, and/or genomic information to select animals such as dairy cattle, beef cattle, swine, poultry, fish, and bees for improvement of production, reproduction, and health.

Background (experiences)

Dairy cattle breeding, lactation physiology, computer programming, applied statistics (biostatistics), population genetics, quantitative genetics (animal breeding and genetics).

Data analyses: dairy cattle, beef cattle, pigs, chickens, fish, bees, horses, and dogs.

Recent Awards amd Activities

2019      “Technological Platform for Swine Breeding Programs”  Critiba, Brazil.
2019      “Asian Guide Dog Breeding Network Meeting” Guide Dog Association, Yokohama, Japan.
2021      “Efficient genetic progress for quantitative traits through genomic selection” International Symposium in Genetics in Aquaculture. Online.
2021      “Efficient genetic progress for quantitative traits through genomic selection” University of California-Davis, CA.
2022      "Programming and computer algorithms in animal breeding with focus on single-step GBLUP and reality of genomic selection" University of Georgia.
2023      “Industry-academia collaboration in animal breeding and genetics in aquaculture industry – more efficient genetic improvement” Ministry of Agriculture, Forestry, and Fisheries, Tokyo, Japan

Selected Recent Publications

Silva, R. M. O., J. Evenhuis, R. Vallejo, S. Tsuruta, G. Wiens, K. Martin., J. Parsons, Y. Palti, D. A. L. Lourenco, and T. Leeds. 2019. Variance and covariance estimates for resistance to bacterial cold water disease and columnaris disease in two rainbow trout breeding populations. J. Anim. Sci. 97:1124-1132.

Oliveira, H., D. Lourenco, Y. Masuda, I. Misztal, S. Tsuruta, J. Jamrozik, B. L. F. Fabyano, and F. Schenkel. 2019. Application of single-step genomic evaluation using multiple-trait random regression test-day models in dairy cattle J. Dairy Sci. 102:2365-2377.

Guarini, A. R., D. A. L. Lourenco, L. F. Brito, M. Sargolzaei, C. Baes, F. Miglior, S. Tsuruta, I. Misztal, and F. S. Schenkel. 2019. Use of a single-step approach for integrating MACE information into genomic evaluation of workability traits in Canadian Holstein cattle. J. Dairy Sci. 102:8175-8183.

Oliveira, H. R., D. A. L. Lourenco, Y. Masuda, I. Misztal, S. Tsuruta, J. Jamrozik, L. F. Brito, F. F. Silva, J. P. Cant, and F. S. Schenkel. 2019. Single-step genome-wide association and functional analysis for longitudinal traits of Canadian Ayrshire, Holstein and Jersey dairy cattle. J. Dairy Sci. 102: 9995-10011.

Maiorano, A. M., A. Assen, P. Bijma, C. Y. Chen, J. A. IIV. Silva, S. Tsuruta, I. Misztal, and D. A. L. Lourenco. 2019. Improving accuracy of maternal effects in genomic evaluations using pooled boar semen: a simulation study. J. Anim. Sci. 97:3237-3245.

Tsuruta, S., D. A. L. Lourenco, Y. Masuda, I. Misztal, and T. J. Lawlor. 2019. Controlling bias in genomic evaluations for young genotyped bulls. J. Dairy Sci. 102: 9956-9970.

Bosworth, W. Geoff, A. Garcia, S. Tsuruta, and D. Lourenco. 2020. Heritability and response to selection for carcass weight and growth in the Delta Select strain of channel catfish, Ictalurus punctatus. Aquaculture. 515:734507.

Garcia, A. L., Y. Masuda, S. Tsuruta, S. Miller, I. Misztal, and D. A. L. Lourenco. 2020. Indirect predictions with a large number of genotyped animals using the algorithm for proven and young. J. Anim. Sci. 98: skaa154.

Hidalgo, J, S. Tsuruta, D. Lourenco, Y. Masuda, Y. Huang, K. A. Gray, and I. Misztal. 2020. Changes in genetic parameters for fitness and growth traits in pigs under genomic selection. J. Anim. Sci. 98: skaa032

Mantovani, R., F. Folla, G. Pigozzi, S. Tsuruta, and C. Sartori. 2020. Genetics of Lifetime Reproductive Performance in Italian Heavy Draught Horse Mares. Animals. 10:1085.

Lourenco, D., A. Legarra, S. Tsuruta, Y. Masuda, I. Aguilar, and I. Misztal. 2020. Single-step genomic evaluations from theory to practice: using SNP chips and sequence data in blupf90. Genes. 11:790.

Jang, S., A. Garcia, S. Lee, S. Tsuruta, D. Lourenco. 2020. Genomic prediction for marbling score in Hanwoo cattle using sequence data. J. Anim. Sci. 98: https://doi.org/10.1093/jas/skaa278.022.

Misztal, I., S. Tsuruta, I. Pocrnic, and D. Lourenco. 2020. Core-dependent changes in genomic predictions using the algorithm for proven and young in single-step genomic best linear unbiased prediction. J. Anim. Sci. J. Anim. Sci. 98: skaa374.

Hidalgo, J., D. Lourenco, S. Tsuruta, Y. Masuda., S. Miller, M., Bermann, A. Garcia., and I. Misztal. 2021. Changes in genomic predictions when new information is added. J. Anim. Sci. 99: skaa004.

Tsuruta, S., T. J. Lawlor, D. A. L. Lourenco, and I. Misztal. 2021. Bias in genomic predictions by mating practices for linear type traits in a large-scale genomic evaluation. J. Dairy Sci. 104:662-677.

Cesarani, A., Y. Masuda, S. Tsuruta, E.L. Nicolazzi, P.M. VanRaden, D. Lourenco, and I. Misztal. 2021. Genomic predictions for yield traits in US Holsteins with unknown parent groups. J. Dairy Sci. 104:5843-5853.

Masuda, Y., S. Tsuruta, A. Legarra, M. Bermann, P. M. VanRaden, H. L. Bradford, and I. Misztal. 2021. Comparison of models for missing pedigree in single-step genomic prediction. J. Anim. Sci. 99: skab019.

Tsuruta, S., D. Lourenco, Y. Masuda., I. Misztal, and T. Lawlor. 2021. Short Communication: Reducing computational cost of large-scale genomic evaluation by using indirect genomic prediction. JDS Communications. 2:356-360..

Leite, N. G., E. F. Knol, A. L. S. Garcia, M. S. Lopes, L. Zak, S. Tsuruta, F. F. Silva, D. Lourenco. 2021. Investigating pig survival in different production phases using genomic models. J. Anim. Sci.99: skab217.

Hidalgo, J., D. Lourenco, S. Tsuruta, Y. Masuda, V. Breen, M. Bermann, and I. Misztal. 2021. Investigating the persistence of accuracy of genomic predictions over time in broilers. J. Anim. Sci. 99: skab239.

Kluska, S., Y. Masuda, F. Baldi, A. Legarra, S. Tsuruta, J. P. Eler, J. B. S. Ferraz, D. Lourenco. 2021. Metafounders may reduce bias in composite cattle genomic predictions. Frontiers in Genetics. Vol. 12. https://doi.org/10.3389/fgene.2021.678587.

Hollifield, M. K., D. Lourenco, S. Tsuruta, M. Bermann, J. Howard, and I. Misztal. 2021. Impact of including the cause of missing records on genetic evaluations for growth in commercial pigs. J. Anim. Sci. 99: skab226.

Masuda, Y., P. M. VanRaden, S. Tsuruta, D. A. L. Lourenco, and I. Misztal. 2021. Invited review: Unknown-parent groups and metafounders in single-step genomic BLUP. J. Dairy Sci. 105:923-939.

Galluzzo, F., J-T. van Kaam, R. Finocchiaro, M. Marusi, S. Tsuruta, and M. Cassandro. 2022. Short Communication: Estimation of milkability breeding values and variance components for Italian Holstein: a Bayesian approach. JDS Communications. https://doi.org/10.3168/jdsc.2021-0167.

Cesarani, A. D. Lourenco, S. Tsuruta, A. Legarra, E. Nicolazzi, P. VanRaden, and I. Misztal. 2022. Multibreed genomic evaluation for dairy cattle in the US using single-step GBLUP. J. Dairy Sci. https://doi.org/10.3168/jds.2021-21505.

Steyn, Y., T. Lawlor, Y. Masuda, S. Tsuruta, D. Lourenco, and I. Misztal. 2022. Identifying influential sires and distinct clusters of selection candidates based on genomic relationships to reduce inbreeding in the US Holstein. J. Dairy Sci. https://doi.org/10.3168/jds.2022-22143.

Steyn, Y., T. Lawlor, Y. Masuda, S. Tsuruta, A. Legarra, D. Lourenco, and I. Misztal. 2022. Non-parallel genome changes within sub-populations over time contribute to genetic diversity within the U.S. Holstein population. J. Dairy Sci. https://doi.org/10.3168/jds.2022-22143.

Leite, N. G., C. Y. Chen, S. Tsuruta, and D. Lourenco. 2022. Leveraging low-density crossbred genotypes to offset crossbred phenotypes and their impact on purebred predictions. J. Anim. Sci. https://doi.org/10.1093/jas/skac359.

Garcia, A., I. Aguilar, A. Legarra, S. Tsuruta, I. Misztal, and D. Lourenco. 2022. Theoretical accuracy for indirect predictions based on SNP effects from single-step GBLUP. Genet. Sel. Evol. https://doi.org/10.1186/s12711-022-00752-4.

Leite, N. G., E. F. Knol, S. Nuphaus, R. Vogelzang, S. Tsuruta, M. Wittmann, and D. Lourenco. 2023. Genetic base of swine inflammation and necrosis syndrome and its genetic association with skin damage and production traits. J. Anim. Sci. 101:skad067.

Garcia, A. L. S., S. Tsuruta, G. Gao, Y. Palti, D. Lourenco, and T. Leeds. 2023. Genomic selection models substantially improve the accuracy of genetic merit predictions for fillet yield and body weight in rainbow trout using a multi-trait model and multi-generation progeny testing. Genet. Sel. Evol. https://doi.org/10.1186/s12711-023-00782-6.

Leite,N. G., E. F. Knol, S. Tsuruta, S. Nuphaus, R. Vogelzang, and D. Lourenco. 2022. Using social interaction models for evaluating skin damage in gilts. Genet. Sel. Evol. 55:52.

McWhorter, Taylor; Sargolzaei, Mehdi; Sattler, Charles; Utt, Matt; Tsuruta, Shogo; Misztal, Ignacy; Lourenco, Daniela. 2023. Single-step genomic predictions for heat tolerance of production yields in U.S. Holsteins and Jerseys. J. Dairy Sci. https://doi.org/10.3168/jds.2022-23144.

Hidalgo, J., D. Lourenco, S. Tsuruta, Y. Masuda, V. Breen, M. Bermann, W. Herring, and I. Misztal. 2023. Efficient ways to combine data from broiler and layer chickens to account for sequential genomic selection. J. Anim. Sci.101: https://doi.org/10.1093/jas/skad177.

Tuliozi, B., R. Mantovani. I. Schoepf, S. Tsuruta, E. Mancin, and C. Sartori. 2023. Genetic correlations of direct and indirect genetic components of social dominance with fitness and morphology traits in cattle. Genet. Sel. Evol. 55: 84.

Jang, S., S. Tsuruta, N. G. Leite, I. Misztal, and D. Lourenco. 2023. Dimensionality of genomic information and its impact of genome-wide associations and variant selection for genomic prediction: a simulation study. Genet. Sel. Evol. 55:49.

Hidalgo, J., D. Lourenco, S. Tsuruta, Y. Masuda, V. Breen, M. Bermann, W. Herring, and I. Misztal. 2023. Derivation of indirect predictions using genomic recursions across generations in a broiler population. J. Anim. Sci. 101:1-9.

Leite, N. G., M. Berman, S. Tsuruta,  I. Misztal, and D. Lourenco. 2023. Marker effect p-value with the algorithm for proven and young for large genotyped populations. Genet. Sel. Evol. https://doi.org/10.1101/2023.10.15.562399.