Refereed Publications

Previous publication lists before 2013 and between 2014 and 2018 are also available.

2024

  • Tabet, J. M., D. Lourenco, F. Bussiman, M. Bermann, I. Misztal, P.M. VanRaden, Z.G. Vitezica, A. Legarra. 2024. All-breed single-step GBLUP evaluations for fertility traits in U.S. dairy cattle. Journal of Dairy Science. https://doi.org/10.3168/jds.2024-25281
  • Tabet, J. M., F. Bussiman, V. Breen, I. Misztal, D. Lourenco. 2024. Combining large broiler populations into a single genomic evaluation: dealing with genetic divergence. Journal of Animal Science. https://doi.org/10.1093/jas/skae360
  • Hidalgo, J., S. Tsuruta, D. Gonzalez, G. Oliveira, M. Sanchez, A. Kulkarni, C. Przybyla, G. Vargas, N. Vukasinovic, I. Misztal, D. Lourenco. 2024. Converting estimated breeding values from the observed to probability scale for health traits. Journal of Dairy Science. https://doi.org/10.3168/jds.2024-24767
  • Misztal, I., D. Lourenco. 2024. Potential negative effects of genomic selection. Journal of Animal Science. https://doi.org/10.1093/jas/skae155
  • Bermann, M., I. Aguilar, A. A. Munera, J. Bauer, J. Šplíchal, D. Lourenco, I. Misztal. 2024. Approximation of reliabilities for random-regression single-step genomic best linear unbiased predictor models. JDS Communications. https://doi.org/10.3168/jdsc.2023-0513
  • Richter, J., F. Bussiman, J. Hidalgo,  V. Breen, I. Misztal, D. Lourenco. 2024. Reviewing the definition of mortality in broiler chickens and its implications in genomic evaluations. Journal of Animal Science. https://doi.org/10.1093/jas/skae190
  • Ramos, P., A. Garcia, K. Retallik, M. Bermann, S. Tsuruta, I. Misztal, R. Veroneze, D. Lourenco. 2024. Comparing algorithms to approximate accuracies for single-step genomic best linear unbiased predictor. Journal of Animal Science. https://doi.org/10.1093/jas/skae195
  • Chen, C. Y, P. W. Knap, A. S. Bhatnagar, S. Tsuruta, D. Lourenco, I. Misztal, and J. W. Holl. 2024. Genetic parameters for pelvic organ prolapse in purebred and crossbred sows. Frontiers in Genetics. 15. https://doi.org/10.3389/fgene.2024.1441303
  • Pocrnic, I., D. Lourenco, I. Misztal. 2024. SNP profile for quantitative trait nucleotide in populations with small effective size and its impact on mapping and genomic predictions. Genetics. iyae103. https://doi.org/10.1093/genetics/iyae103
  • Misztal, I., D. Lourenco. 2024. Potential negative effects of genomic selection. Journal of Animal Science. skae155. https://doi.org/10.1093/jas/skae155
  • Londoño-Gil, M., R. López-Correa, I. Aguilar, C. U. Magnabosco, J. Hidalgo, F. Bussiman, F. Baldi, D. Lourenco. 2024. Strategies for genomic predictions of an indicine multi-breed population using single-step GBLUP. Journal of Animal Breeding and Genetics. 00, 1–14. https://doi.org/10.1111/jbg.12882
  • Bermann, M., I. Aguilar, A. A. Munera, J. Bauer, J. Šplíchal, D. Lourenco, I. Misztal. 2024. Approximation of reliabilities for random-regression single-step genomic best linear unbiased predictor models. JDS Communications. https://doi.org/10.3168/jdsc.2023-0513
  • Ramos, P. V. B., G. R. de Oliveira Menezes, D. A. da Silva, D. Lourenco, G. G. Santiago, R. A. A. Torres Júnior, F. F. e. Silva, P. S. Lopes, R. Veroneze. 2024. Genomic analysis of feed efficiency traits in beef cattle using random regression models. Journal of Animal Breeding and Genetics. 141, 291–303. https://doi.org/10.1111/jbg.12840
  • Hollifield, M. K., C. Y. Chen, E. Psota, J. Holl, D. Lourenco, I. Misztal. 2024. Estimating genetic parameters of digital behavior traits and their relationship with production traits in purebred pigs. Genetics Selection Evolution. 56:29. https://doi.org/10.1186/s12711-024-00902-w
  • Richter, J., J. Hidalgo, F. Bussiman, V. Breen, I. Misztal, D. Lourenco. 2024. Temporal dynamics of genetic parameters and SNP effects for performance and disorder traits in poultry undergoing genomic selection. Journal of Animal Science. skae097. https://doi.org/10.1093/jas/skae097
  • Hollifield, M. K., D. Lourenco, I. Misztal. 2024. Estimation of heritability with genomic information by method R.  Journal of Animal Breeding and Genetics. 00, 1–9. https://doi.org/10.1111/jbg.12863
  • Bermann, M., A. Legarra, A. A. Munera, I. Misztal, D. Lourenco. 2024. Confidence intervals for validation statistics with data truncation in genomic prediction. Genetics Selection Evolution. 56:18. https://doi.org/10.1186/s12711-024-00883-w

2023

  • Bermann, M., I. Aguilar, D. Lourenco, I. Misztal, A. Legarra. 2023. Reliabilities of estimated breeding values in models with metafounders. Genetics Selection Evolution. 55:6. https://doi.org/10.1186/s12711-023-00778-2
  • Bussiman, F., C. Y. Chen, J. Holl, M. Bermann, A. Legarra, I. Misztal, D. Lourenco. 2023. Boundaries for genotype, phenotype, and pedigree truncation in genomic evaluations in pigs. Journal of Animal Science. https://doi.org/10.1093/jas/skad273
  • Cesarani, A., M. Bermann, C. Dimauro, L. Degano, D. Vicario, D. Lourenco, N. P. P. Macciotta. 2023. Strategies for choosing core animals in the algorithm for proven and young and their impact on the accuracy of single-step genomic predictions in cattle. Animal. https://doi.org/10.1016/j.animal.2023.100766
  • Cesarani, A., F. C. Pause, J. Hidalgo, A. Garcia, L. Degano, D. Vicario, N. P. P. Macciotta, G. Stradali. 2023. Genetic background of semen parameters in Italian Simmental bulls. Italian Journal of Animal Science. https://doi.org/10.1080/1828051X.2022.2160665
  • Cesarani, A., D. Lourenco, M. Bermann, E. L. Nicolazzi, P. M. VanRanden, I. Misztal. 2023. Single-step genomic predictions for crossbred Holstein and Jersey cattle in the US. JDS Communications. https://doi.org/10.3168/jdsc.2023-0399
  • Garcia, A., S. Tsuruta, G. Gao, Y. Palti, D. Lourenco, 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. Genetics Selection Evolution. 55:11. https://doi.org/10.1186/s12711-023-00782-6
  • Hidalgo, J. D. Lourenco, S. Tsuruta, M. Bermann, V. Breen, I. Misztal. 2023. Derivation of indirect predictions using genomic recursions across generations in a broiler population. Journal of Animal Science. https://doi.org/10.1093/jas/skad355
  • Hidalgo, J., D. Lourenco, S. Tsuruta, M. Bermann, V. Breen, W. Herring, I. Misztal. 2023. Efficient ways to combine data from broiler and layer chickens to account for sequential genomic selection. Journal of Animal Science. https://doi.org/10.1093/jas/skad177
  • Hollifield, M. K., M. Bermann, D. Lourenco, I. Misztal. 2023. Exploring the statistical nature of independent chromosome segments. Livestock Science. https://doi.org/10.1016/j.livsci.2023.105207
  • Jang, S., R. Ros-Freixedes, J. M. Hickey, C.-Y. Chen, W. O. Herring, J. Holl, I. Misztal, and D. Lourenco. 2023. Multi-line ssGBLUP evaluation using preselected markers from whole-genome sequence data in pigs. Frontiers in Genetics. 14. https://doi.org/10.3389/fgene.2023.1163626
  • Jang, S., S. Tsuruta, I. Misztal, D. Lourenco. 2023. Dimensionality of genomic information and its impact on genome-wide associations and variant selection for genomic prediction: a simulation study. Genetics Selection Evolution. 55:49. https://doi.org/10.1186/s12711-023-00823-0
  • Jang, S., R. Ros-Freixedes, J. M. Hickey, C. Y. Chen, J. Holl, W. O. Herring, I. Misztal, D. Lourenco. 2023. Using pre-selected variants from large-scale whole-genome sequence data for single-step genomic predictions in pigs. Genetics Selection Evolution. 55:55. https://doi.org/10.1186/s12711-023-00831-0
  • Leite, N. G., E. F. Knol, S. Nuphaus, R. Vogelzang, S. Tsuruta, M. Wittmann, D. Lourenco. 2023. The genetic basis of swine inflammation and necrosis syndrome and its genetic association with post-weaning skin damage and production traits. Journal of Animal Science. https://doi.org/10.1093/jas/skad067
  • Leite, N. G., E. Knol, S. Tsuruta, S. Nuphaus, R. Vogelzang, D. Lourenco. 2023. Using social interaction models for genetic analysis of skin damage in gilts. Genetics Selection Evolution. 55:52. https://doi.org/10.1186/s12711-023-00816-z
  • McWhorter, T. M., M. Sargolzaei, C. G. Sattler, M. D. Utt, S. Tsuruta, I. Misztal, D. Lourenco. 2023. Single-step genomic predictions for heat tolerance of production yields in U.S. Holsteins and Jerseys. Journal of Dairy Science. https://doi.org/10.3168/jds.2022-23144
  • Ramos, P. V. B., G. R. de Oliveira Menezes, D. A. da Silva, D. Lourenco, G. G. Santiago, R. A. A. Torres Junior, F. F. E. Silva, P. S. Lopes, R. Veroneze. 2023. Genomic analysis of feed efficiency traits in beef cattle using random regression models. Journal of Animal Breeding and Genetics. https://doi.org/10.1111/jbg.12840
  • Steyn, Y., T. Lawlor, D. Lourenco, I. Misztal. 2023. The importance of historically popular sires on the accuracy of genomic predictions of young animals in the US Holstein population. JDS Communications. https://doi.org/10.3168/jdsc.2022-0299
  • Steyn, Y., T. Lawlor, Y. Masuda, S. Tsuruta, A. Legarra, D. Lourenco, I. Misztal. 2023. Nonparallel genome changes within subpopulations over time contributed to genetic diversity within the US Holstein population. Journal of Dairy Science. 106. https://doi.org/10.3168/jds.2022-21914
  • Warner, A., B. D. Heins, N. C. Hinkle, T. D. Pringle, S. E. Aggrey, R. Rekaya. 2023. Genetic parameters of subjective and image-based horn fly abundance phenotypes. Frontiers in Animal Science. 4. https://doi.org/https://doi.org/10.3389/fanim.2023.1284684

2022

  • Abdollahi-Arpanahi, R., D. Lourenco, I. Misztal. 2022. A comprehensive study on size and definition of the core group in the proven and young algorithm for single-step GBLUP. Genetics Selection Evolution. 54. https://doi.org/10.1186/s12711-022-00726-6 
  • Bermann, M., D. Lourenco, I. Misztal. 2022. Efficient approximation of reliabilities for single-step genomic best linear unbiased predictor models with the Algorithm for Proven and Young. Journal of Animal Science. https://doi.org/10.1093/jas/skab353
  • Bermann, M., D. Lourenco, N. S. Forneris, A. Legarra, I. Misztal. 2022. On the equivalence between marker effect models and breeding value models and direct genomic values with the Algorithm for Proven and Young. Genetics Selection Evolution. https://doi.org/10.1186/s12711-022-00741-7
  • Bermann, M., A. Cesarani, I. Misztal, D. Lourenco. 2022. Past, present, and future developments in single-step genomic models. Italian Journal of Animal Science. https://doi.org/10.1080/1828051X.2022.2053366
  • Callister, A., M. Bermann, S. Elms, B. Bradshaw, D. Lourenco, J. Brawner. 2022. Accounting for population structure in genomic predictions of Eucalyptus globulus. G3: Genes, Genomes, Genetics.  https://doi.org/10.1093/g3journal/jkac180
  • Campos, G. S., F. F. Cardoso, C. C. G. Gomes, R. Domingues, R. de Almeida Regitano, M. C. de Sent Oliveira, H. N. de Oliveira, R. Carvalheiro, L. G. Albuquerque, S. Miller, I. Misztal, D. Lourenco. 2022. Development of genomic predictions for Angus cattle in Brazil incorporating genotypes from related American sires. Journal of Animal Science. https://doi.org/10.1093/jas/skac009
  • Cesarani, A., D. Lourenco, S. Tsuruta, A. Legarra, E. L. Nicolazzi, P. M. VanRaden, I. Misztal. 2022. Multibreed genomic evaluation for production traits of dairy cattle in the United States using single-step genomic best linear unbiased predictor. Journal of Dairy Science. https://doi.org/10.3168/jds.2021-21505
  • Galluzzo, F., J.-T. van Kaam, R. Finocchiaro, M. Marusi, S. Tsuruta, M. Cassandro. 2022. Estimation of milkability breeding values and variance components for Italian Holstein. JDS Communications. https://doi.org/10.3168/jdsc.2021-0167
  • Garcia, A., I. Aguilar, A. Legarra, S. Tsuruta, I. Misztal, D. Lourenco. 2022. Theoretical accuracy for indirect predictions based on SNP effects from single-step GBLUP. Genetics Selection Evolution. 54. https://doi.org/10.1186/s12711-022-00752-4
  • Guinan, F. L., G. R. Wiggans, H. D. Norman, J. W. Durr, J. B. Cole, C. P. Van Tassell, I. Misztal, D. Lourenco. 2022. Changes in genetic trends in US dairy cattle since the implementation of genomic selection. Journal of Dairy Science. https://doi.org/10.3168/jds.2022-22205
  • Hollifield, M. K., M. Bermann, D. Lourenco, I. Misztal. 2022. Impact of blending the genomic relationship matrix with different levels of pedigree relationships or the identity matrix on genetic evaluations. JDS Communications. https://doi.org/10.3168/jdsc.2022-0229
  • Jang, S., D. Lourenco, S. Miller. 2022. Inclusion of Sire by Herd interaction effect in the genomic evaluation for weaning weight of American Angus. Journal of Animal Science. https://doi.org/10.1093/jas/skac057
  • Junqueira, V. S., D. Lourenco, Y. Masuda, F. F. Cardoso, P. S. Lopes, F. F. Silva, I. Misztal. 2022. Is single-step genomic REML with the algorithm for proven and young more computationally efficient when less generations of data are present? Journal of Animal Science. https://doi.org/10.1093/jas/skac082
  • Leite, N. G., C. Chen, W. O. Herring, J. Holl, S. Tsuruta, D. Lourenco, 2022. Leveraging low-density crossbred genotypes to offset crossbred phenotypes and their impact on purebred predictions. Journal of Animal Science. https://doi.org/10.1093/jas/skac359
  • McWhorter, T. M., M. Bermann, A.L.S. Garcia, A. Legarra, I. Aguilar, I. Misztal, D. Lourenco. 2022. Implication of the order of blending and tuning when computing the genomic relationship matrix in single-step GBLUP. Journal of Animal Breeding and Genetics. https://doi.org/10.1111/jbg.12734
  • Misztal, I., Y. Steyn, D. Lourenco. 2022. Genomic evaluation with multi breed and crossbred data. JDS Communications. https://doi.org/10.3168/jdsc.2021-0177
  • Misztal, I. 2022. Publishing and literature search in the online era. Journal of Animal Breeding and Genetics. https://doi.org/10.1111/jbg.12724
  • Steyn, Y., Y. Masuda, S. Tsuruta, D. Lourenco, I. Misztal, T. Lawlor. 2022. Identifying influential sires and distinct clusters of selection candidates based on genomic relationships to reduce inbreeding in the US Holstein. Journal of Dairy Science. https://doi.org/10.3168/jds.2022-22143
  • Warner, A., A. Ling, T. Krause, B. Heins, N. Hinkle, D. Pringle, S. E. Aggrey, R. Rekaya. 2022. Thrombin as a potential proxy to select for horn fly abundance in beef cattle. Animals. https://doi.org/10.3390/ani12212982

2021

  • Abdollahi-Arpanahi, R., D. Lourenco and I. Misztal. 2021. Detecting effective starting point of genomic selection by divergent trends from BLUP and ssGBLUP in pigs, beef cattle, and broilers. J. Anim. Sci. https://doi.org/10.1093/jas/skab243
  • Abdollahi-Arpanahi, R., D. Lourenco, A. Legarra, and I. Misztal. 2021. Dissecting genetic trends to understand breeding practices in livestock: a maternal pig line example. Genetics Selection Evolution. 53. https://doi.org/10.1186/s12711-021-00683-6
  • Al-Tobasei, R., A. Ali, A. Garcia, D. Lourenco, T. Leeds and M. Salem. 2021. Genomic predictions for fillet yield and firmness in rainbow trout using reduced-density SNP panels. BMC Genomics. 22:1-11. https://doi.org/10.1186/s12864-021-07404-9
  • Araujo, A.C., P. Carneiro, H.R. Oliveira, F.S. Schenkel, R. Veroneze, D.A.L. Lourenco and L.F. Brito. 2021. A comprehensive comparison of haplotype-based single-step genomic predictions in livestock populations with different genetic diversity levels: a simulation study. Frontiers in Genetics. Vol. 12. https://doi.org/10.3389/fgene.2021.729867
  • Bermann, M., D. Lourenco, and I. Misztal. 2021. Technical note: Automatic scaling in single-step genomic BLUP. J. Dairy Sci. 104:2027-2031. https://doi.org/10.3168/jds.2020-18969
  • Bermann, M., A. Legarra, M.K. Hollifield, Y. Masuda, D. Lourenco and I. Misztal. 2021. Validation of single‐step GBLUP genomic predictions from threshold models using the linear regression method: An application in chicken mortality. J. Anim. Breed. Genet. 138:4-13. https://doi.org/10.1111/jbg.12507
  • Bermann, M., D. Lourenco, V. Breen, R. Hawken, F. Brito Lopes and I. Misztal. 2021. Modeling genetic differences of combined broiler chicken populations in single-step GBLUP. J. Anim. Sci. 99:skab056. https://doi.org/10.1093/jas/skab056
  • Cesarani, A., A. Garcia, J. Hidalgo, L. Degano, D. Vicario, N. P. P. Macciotta, and D. Lourenco. 2021. Genomic information allows for more accurate breeding values for milkability in dual purpose Italian Simmental cattle. J. Dairy Sci. https://doi.org/10.3168/jds.2020-19838
  • 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 Holstein with unknown parent groups. J. Dairy Sci. https://doi.org/10.3168/jds.2020-19789
  • Cesarani, A., S. Biffani, A. Garcia, D. Lourenco, G. Bertolini, G. Neglia, I. Misztal, and N.P.P. Macciotta. 2021. Genomic investigation of milk production in Italian buffalo. Italian Journal of Animal Science 20, 539–547. https://doi.org/10.1080/1828051X.2021.1902404
  • Falchi, L., G. Gaspa, A. Cesarani, F. Correddu, L. Degano, D. Vicario, D. Lourenco and N. P. P. Macciotta. 2021. Investigation of β-hydroxybutyrate in early lactation of Simmental cows: Genetic parameters and genomic predictions. Journal of Animal Breeding and Genetics, 00, 1– 11. https://doi.org/10.1111/jbg.12637
  • Galoro Leite, N., E.F. Knol, A.L.S. Garcia, M.S. Lopes, L. Zak, F.F.E. Silva and D. Lourenco. 2021. Investigating pig survival in different production phases using genomic models. J. Anim. Sci. 99:skab217. https://doi.org/10.1093/jas/skab217
  • Hidalgo, J., D. Lourenco, S. Tsuruta, Y. Masuda, S. Miller, M. Bermann, A.L.S. Garcia, and I. Misztal. 2021. Changes in genomic predictions when new information is added. J. Anim. Sci. 99:skab004. https://doi.org/10.1093/jas/skab004
  • Hidalgo, J., D. Lourenco, S. Tsuruta, Y. Masuda, V. Breen, R. Hawken, M. Bermann and I. Misztal. 2021. Investigating the persistence of accuracy of genomic predictions over time in broilers. J. Anim. Sci. 99:skab239. https://doi.org/10.1093/jas/skab239
  • Hollifield, M.K., D. Lourenco, M. Bermann, J.T. Howard and I. Misztal. 2021. Determining stability of accuracy of genomic estimated breeding values in future generations in commercial pig populations. J. Anim. Sci. 99:skab085. https://doi.org/10.1093/jas/skab085
  • Hollifield, M.K., D. Lourenco, S. Tsuruta, M. Bermann, J.T. 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. https://doi.org/10.1093/jas/skab226
  • Kluska, S., Y. Masuda, J.B.S. Ferraz, S. Tsuruta, J.P. Eler, F. Baldi and 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
  • Ling, A.S., E.H. Hay, S.E. Aggrey and R. Rekaya. 2021. Dissection of the impact of prioritized QTL-linked and -unlinked SNP markers on the accuracy of genomic selection. BMC Genomics. 22:1-14. https://doi.org/10.1186/s12863-021-00979-y
  • Mancin, E., D.L. Lourenco, M. Bermann, R. Mantovani and I. Misztal. 2021. Accounting for population structure and phenotypes from relatives in association mapping. Frontiers in Genetics. Vol. 12. 10.3389/fgene.2021.642065
  • Masuda, Y., S. Tsuruta, M. Bermann, H.L. Bradford, and I. Misztal. 2021. Comparison of models for missing pedigree in single-step genomic prediction. J. Anim. Sci. 99:skab019. https://doi.org/10.1093/jas/skab019
  • 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. https://doi.org/10.3168/jds.2021-20293
  • Misztal, I., I. Aguilar, D. Lourenco, L. Ma, J. Steibel and M. Toro. 2021. Emerging issues in genomic selection. J. Anim. Sci. 99:skab092. https://doi.org/10.1093/jas/skab092
  • Shook, J. M., D. Lourenco, and A. K. Singh. 2021. PATRIOT: A Pipeline for Tracing Identity-by-Descent for Chromosome Segments to Improve Genomic Prediction in Self-Pollinating Crop Species. Frontiers in Plant Science 12(2095). https://doi.org/10.3389/fpls.2021.676269
  • Steyn, Y., D. A. L. Lourenco, C. Chen, B. D. Valente, J. Holl, W. O. Herring, and I. Misztal. 2021. Optimal definition of contemporary groups for crossbred pigs in a joint purebred and crossbred genetic evaluation. J. Anim. Sci. 99:skaa396. https://doi.org/10.1093/jas/skaa396
  • Steyn, Y., D. Gonzalez-Pena, Y.L. Bernal Rubio, N. Vukasinovic, S.K. DeNise, D.A.L. Lourenco and I. Misztal. 2021. Indirect genomic predictions for milk yield in crossbred Holstein-Jersey dairy cattle. J. Dairy Sci. 104:5728–573. https://doi.org/10.3168/jds.2020-19451
  • Sungkhapreecha, P., I. Misztal, J. Hidalgo, Y. Steyn, S. Buaban, M. Duangjinda, and W. Boonkum. 2021. Changes in genetic parameters for milk yield and heat tolerance in the Thai Holstein crossbred dairy population under different heat stress levels and over time. J. Dairy Sci. https://doi.org/10.3168/jds.2021-20151
  • Sungkhapreecha, P., I. Misztal, J. Hidalgo, D. Lourenco, S. Buaban, V. Chankitisakul and W. Boonkum. 2021. Validation of single-step genomic predictions using the linear regression method for milk yield and heat tolerance in a Thai-Holstein population. Veterinary World. 14(12): 3119-3125. https://doi.org/10.14202/vetworld.2021.3119-3125
  • Tonussi, R.L., M. Londoño-Gil, R.M. De Oliveira Silva, A.F.B. Magalhães, S.T. Amorim, S. Kluska, R. Espigolan, E. Peripolli, A.S.C. Pereira, R.B. Lôbo, I. Aguilar, D.A.L. Lourenço, and F. Baldi. 2021. Accuracy of genomic breeding values and predictive ability for postweaning liveweight and age at first calving in a Nellore cattle population with missing sire information. Tropical Animal Health and Production. 53. doi:10.1007/s11250-021-02879-w.
  • 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. 104:662-667. https://doi.org/10.3168/jds.2020-18668
  • Tsuruta, S., D.A.L. Lourenco, Y. Masuda, T.J. Lawlor, and I. Misztal. 2021. Reducing computational cost of large-scale genomic evaluation by using indirect genomic prediction. JDS Communications. https://doi.org/10.3168/jdsc.2021-0097
  • Yoshida, Y., F. Kawabata, S. Tabata, S.E. Aggrey, R. Rekaya, and H. Liu. 2021. Evolvement of taste sensitivity and taste buds in chickens during selective breeding. Poultry Sci.100:101-113. https://doi.org/10.1016/j.psj.2021.101113

2020

  • Ali, A., R. Al-Tobasei, D. A. L. Lourenco, T. Leeds, B. Kenney, and M. Salem. 2020. Genome-wide identification of loci associated with growth in rainbow trout. BMC Genomics. 21:1-16. https://doi.org/10.1186/s12864-020-6617-x
  • Bosworth, B., G. Waldbieser, A. Garcia, and D. A. L. Lourenco, 2020. Effect of pond‐or strip‐spawning on growth and carcass yield of channel catfish progeny, Ictalurus punctatus. J. World Aqua. Soc. 51:407-417. https://doi.org/10.1111/jwas.12659
  • Bosworth, B., G. Waldbieser, A. Garcia, S. Tsuruta, and D. A. L. 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. https://doi.org/10.1016/j.aquaculture.2019.734507
  • Cesarani, A., G. Gaspa, Y. Masuda, L. Degano, D. Vicario, D. A. Lourenco, and N. P. Macciotta. 2020. Variance components using genomic information for 2 functional traits in Italian Simmental cattle: Calving interval and lactation persistency. J. Dairy Sci. 103:5227-5233. https://doi.org/10.3168/jds.2019-17421
  • Cesarani, A., J. Hidalgo, A. Garcia, L. Degano, D. Vicario, Y. Masuda, I. Misztal, and D. A. L. Lourenco. 2020. Beef trait genetic parameters based on old and recent data and its implications for genomic predictions in Italian Simmental cattle. J. Anim. Sci. 98:skaa242. https://doi.org/10.1093/jas/skaa242
  • Duarte, J.L.G., A. S. Gori, X. Hubin, D. A. L. Lourenco, C. Charlier, I. Misztal, and T. Druet. 2020. Performances of Adaptive MultiBLUP, Bayesian regressions, and weighted-GBLUP approaches for genomic predictions in Belgian Blue beef cattle. BMC genomics. 21:1-18. https://doi.org/10.1186/s12864-020-06921-3
  • Fagundes, N. S., M. C. Milfort, S. M. Williams, M. J. Da Costa, A. L. Fuller, J.F. Menten, R. Rekaya, and S. E. Aggrey. 2020. Dietary methionine level alters growth, digestibility, and gene expression of amino acid transporters in meat-type chickens. Poultry Sci. 99:67-75. https://doi.org/10.3382/ps/pez588
  • Foutz, J.C., M. C. Milfort, A. L. Fuller, W. K. Kim, R. Rekaya, and S. E. Aggrey. 2020. Supplementation of diets with Brazil nut powder can meet dietary methionine requirement of organic broiler chickens. Organic Agriculture. 10: 359-367. https://doi.org/10.1007/s13165-019-00276-0
  • 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. https://doi.org/10.1093/jas/skaa154
  • Garcia-Baccino, C. A., D. A. L. Lourenco, S. Miller, R. J. Cantet. and Z. G. Vitezica. 2020. Estimating dominance genetic variances for growth traits in American Angus males using genomic models. J. Anim. Sci. 98:skz384. https://doi.org/10.1093/jas/skz384
  • Hidalgo, J., S. Tsuruta, D. A. L. 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. https://doi.org/10.1093/jas/skaa032
  • Junqueira, V.S., Lopes, P.S., Lourenco, D., Silva, F.F.E., Cardoso, F.F., 2020. Applying the Metafounders Approach for Genomic Evaluation in a Multibreed Beef Cattle Population. Frontiers in Genetics Vol. 11.  https://doi.org/10.3389/fgene.2020.556399
  • Lourenco, D. A. L., 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. https://doi.org/10.3390/genes11070790
  • McWhorter, T. M., J. L. Hutchison, H. D. Norman, J. B. Cole, G. C. Fok, D. A. L. Lourenco, P. M. VanRaden. 2020. Investigating conception rate for beef service sires bred to dairy cows. J. Dairy Sci. 103:10374-10382. https://doi.org/10.3168/jds.2020-18399
  • Misztal, I., D. A. L. Lourenco, and A. Legarra. 2020. Current status of genomic evaluation. J. Anim. Sci. 98:skaa101. https://doi.org/10.1093/jas/skaa101
  • Schneiders, G. H., J. C. Foutz, A. L. Fuller, J. Nelson, R. Rekaya, and S. E. Aggrey. 2020. The effect of increased temperature on viability, morphology, infectivity and development of Eimeria tenella. J. of Parasitology. 106(3):428-437. https://doi.org/10.1645/19-17
  • Schneiders, G.H., J. C. Foutz, M. C. Milfort, A. F. A. Ghareeb, A. L. Fuller, R. Rekaya, S. M. Williams, and S. E. Aggrey. 2020. Heat stress reduces sexual development and affects pathogenesis of Eimeria maxima in meat-type chickens. Scientific Reports. 10:10736. https://doi.org/10.1038/s41598-020-67330-w
  • Song, H., Q. Zhang, I. Misztal, and X. Ding. 2020. Genomic prediction of growth traits for pigs in the presence of genotype by environment interactions using single‐step genomic reaction norm model. J. Anim. Breed. Genet. 137:523-534. https://doi.org/10.1111/jbg.12499
  • Sumreddee, P., S. Toghiani, E. H. Hay, A. Roberts, S. E. Aggrey, and R. Rekaya. 2020. Runs of homozygosity and analysis of inbreeding depression. J. Anim. Sci. 98:skaa361. https://doi.org/10.1093/jas/skaa361
  • Toghiani, S., E. H. Hay, A. Roberts, and R. Rekaya. 2020. Impact of cold stress on birth and weaning weight in a composite beef cattle breed. Livestock Sci. 236:104053. https://doi.org/10.1016/j.livsci.2020.104053
  • Toghiani, S., E. Hay, B. Fragomeni, R. Rekaya, and A. J. Roberts. 2020. Genotype by environment interaction in response to cold stress in a composite beef cattle breed. Animal. 14(8):1576-1587. https://doi.org/10.1017/S1751731120000531
  • Valentino, P., S. Pegolo, G. Conte, A. Cesarani, N. P. P. Macciotta, B. Stefanon, P. A. Marsan, M. Mele, A. Cecchinato, and M. D’Andrea. 2020. Genomic prediction for latent variables related to milk fatty acid composition in Holstein, Simmental and Brown Swiss dairy cattle breeds. J. Anim. Breed. Genet. 00:1-14. https://doi.org/10.1111/jbg.12532
  • Vilar da Silva, F. Gonzalez-Ceron, E. W. Howerth, R. Rekaya, and S. E. Aggrey. 2020. Alteration of dietary cysteine affects activities of genes of the transsulturation and glutathione pathways, and development of skin tissues and feather follicles in chickens. Anim. Biotechnol. 31: 203-208. https://doi.org/10.1080/10495398.2019.1577253
  • Wang, Z., J. Zhou, B. Marshall, R. Rekaya, K. Ye, and H. Liu. 2020. SARS-CoV-2 receptor ACE2 is enriched in a subpopulation of mouse tongue epithelial cells in non-gustatory papillae, but not in taste buds or embryonic oral epithelium. ACS Pharmacol. Transl. Sci. 3(4):749-758. https://doi.org/10.1021/acsptsci.0c00062

2019

  • Aguilar, I. A. Legarra, F. Cardoso, Y. Masuda, D. A. L., and I. Misztal. 2019. Frequentist p-values for large-scale-single step genome-wide association, with an application to birth weight in American Angus cattle. Genet. Sel. Evol. 51:28. https://doi.org/10.1186/s12711-019-0469-3
  • Ali A., R. Al-Tobasei, D. A. L. Lourenco, T. D. Leeds, P. B. Kenney, and M. Salem. 2019. Genome-wide association study identifies genomic loci affecting fillet firmness and protein content in rainbow trout. Front. Genet. 10:386. https://doi.org/10.3389/fgene.2019.00386
  • Bradford, H. L., Y. Masuda, J. B. Cole, I. Misztal, and P. M. VanRaden. 2019. Modeling pedigree accuracy and uncertain parentage in single-step genomic evaluations of simulated and US Holstein datasets. J. Dairy Sci. 102:2308–2318. https://doi.org/10.3168/jds.2018-15419
  • Bradford, H. L., Y. Masuda, P. M. VanRaden, A. Legarra, and I. Misztal. 2019. Modeling missing pedigree in single-step genomic BLUP. J. Dairy Sci. 102:2336–2346. https://doi.org/10.3168/jds.2018-15434
  • Cesarani, A., I. Pocrnic, N. P. P. Macciotta, B. O. Fragomeni, and I. Misztal, and D. A. L. Lourenco. 2019. Bias in heritability estimates from genomic restricted maximum likelihood methods under different genotyping strategies. J. Anim. Breed. Genet. 136:40-50. https://doi.org/10.1111/jbg.12367
  • Fragomeni, B., Y. Masuda, H. L. Bradford, D. A. L. Lourenco, and I. Misztal. 2019. International bull evaluations by genomic best linear unbiased predictor with a prediction population. J. Dairy Sci. 102: 2330–2335. https://doi.org/10.3168/jds.2018-15554
  • Guarini, A. R., D. A. L. Lourenco, L. F. Brito, M. Sargolzaei, C. F. Baes, F. Miglior, I. Misztal, and F. S. Schenkel. 2019. Genetics and genomics of reproductive disorders in Canadian Holstein cattle. J. Dairy Sci. 102:1341-1353. https://doi.org/10.3168/jds.2018-15038
  • Guarini, A. R., D. A. L. Lourenco, L. F. Brito, M. Sargolzaei, C. F. Baes, F. Miglior, S. Tsuruta, I. Misztal, and F. S. Schenkel. 2019. Use of a single-step approach for integrating foreign information into national genomic evaluation in Holstein cattle. J. Dairy Sci. 102:8175-8183. https://doi.org/10.3168/jds.2018-15819
  • Guarini, A. R., M. Sargolzaei, L. F. Brito, V. Kroezen, D. A. L. Lourenco, C. F. Baes, F. Miglior, J. B. Cole, and F. S. Schenkel. 2019. Estimating the effect of the deleterious recessive haplotypes AH1 and AH2 on reproduction performance of Ayrshire cattle. J. Dairy Sci. 102:5315-5322. https://doi.org/10.3168/jds.2018-15366
  • Maiorano, A. M., A. Assen, P. Bijma, C. Y. Chen, J. A. Silva, W. O. Herring, S. Tsuruta, I. Misztal, and D. A. L. Lourenco. 2019. Improving accuracy of direct and maternal genetic effects in genomic evaluations using pooled boar semen: a simulation study. J. Anim. Sci. 97:3237-3245. https://doi.org/10.1093/jas/skz207
  • Oliveira, H. R., L. F. Brito, D. A. L. Lourenco, F. F. Silva, J. Jamrozik, L. R. Schaeffer, and F. S. Schenkel. 2019. Invited review: Advances and applications of random regression models: From quantitative genetics to genomics. J. Dairy Sci. 102:7664-7683. https://doi.org/10.3168/jds.2019-16265
  • Oliveira, H. R., L. F. Brito, M. Sargolzaei, F. F. Silva, J. Jamrozik, D. A. L. Lourenco, and F. S. Schenkel. 2019. Impact of including information from bulls and their daughters in the training population of multiple‐step genomic evaluations in dairy cattle: a simulation study. J. Anim. Breed. Genet. 136:441-452. https://doi.org/10.1111/jbg.12407
  • Oliveira H. R., L. F. Brito, F. F. Silva, D. A. L. Lourenco, J. Jamrozik, and F. S. Schenkel. 2019. Genomic prediction of lactation curves for milk, fat, protein, and somatic cell score in Holstein cattle. J. Dairy Sci. 102:452-463. https://doi.org/10.3168/jds.2018-15159
  • Oliveira, H. R., D. A. L. Lourenco, Y. Masuda, I. Misztal, S. Tsuruta, J. Jamrozik, L. F. Brito, F. F. Silva, and F. S. 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. https://doi.org/10.3168/jds.2018-15466
  • 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 for longitudinal traits of Canadian Ayrshire, Holstein, and Jersey dairy cattle. J. Dairy Sci. In Press. https://doi.org/10.3168/jds.2019-16821
  • Oliveira, H. R., J. P. Cant, L. F. Brito, F. L. B. Feitosa, T. C. S. Chud, P. A. S. Fonseca, J. Jamrozik, F. F. Silva, D. A. L. Lourenco, and F. S. Schenkel. 2019. Genome-wide association for milk production traits and somatic cell score in different lactation stages of Ayrshire, Holstein, and Jersey dairy cattle. J. Dairy Sci. 102:8159-8174. https://doi.org/10.3168/jds.2019-16451
  • Pocrnic, I., D. A. L. Lourenco, C. Y. Chen, W. O. Herring, and I. Misztal. 2019. Crossbred evaluations using single-step genomic BLUP and algorithm for proven and young with different sources of data. J. Anim. Sci. In Press. https://doi.org/10.1093/jas/skz042
  • Raulino-Domanski, F., M. Potrich, P. F. Freitas, F. C. Abdalla, E. N. Martins, D. A. L. Lourenco, and F. M. Costa-Maia. 2019. Optimized histological preparation of ovary for ovariole counting in africanized honey bee queens (Hymenoptera: Apidae). J. Insect Sci. 19:12. https://doi.org/10.1093/jisesa/iez013
  • Schneiders, G. H., J. C. Foutz, M. C. Milfort, A. F. A. Ghareeb, U. G. Sorhue, J. N. Richter, A. L. Fuller, S. M. Williams, R. Rekaya, and S. E. Aggrey. 2019. Ontogeny of intestinal permeability in chickens infected with Eimeria maxima: Implications for intestinal health. J. Adv. in Parasitol. 6(3):41.
  • Silva, R. M. O., J. P. Evenhuis, R. L. Vallejo, G. Gao, K. E. Martin, T. D. Leeds, Y. Palti, and D. A. L. Lourenco. 2019. Whole-genome mapping of quantitative trait loci and accuracy of genomic predictions for resistance to columnaris disease in two rainbow trout breeding populations. Genet. Sel. Evol. 51:42. https://doi.org/10.1186/s12711-019-0484-4
  • Stafuzza, N. B., R. M. O. Silva, B. O. Fragomeni, Y. Masuda, Y. Huang, K. Gray, and D. A. L. Lourenco. 2019. A genome-wide single nucleotide polymorphism and copy number variation analysis for number of piglets born alive. BMC Genomics. 20:321. https://doi.org/10.1186/s12864-019-5687-0

2018

  • Garcia, A. L. S., B. Bosworth, G. Waldbieser, I. Misztal, S. Tsuruta, D. A. L. Lourenco. 2018. Development of genomic predictions for harvest and carcass weight in channel catfish. Genet. Sel. Evol. 50:66. https://doi.org/10.1186/s12711-018-0435-5
  • Guarini, A. R., D. A. L. Lourenco, L. F. Brito, M. Sargolzaei, C. F. Baes, F. Miglior, I. Misztal, and F. S. Schenkel. 2018. Comparison of genomic predictions for lowly heritable traits using multi-step and single-step genomic best linear unbiased predictor in Holstein cattle. J. Dairy Sci. 101:8076-8086. https://doi.org/10.3168/jds.2017-14193
  • Junqueira, V.S., P.S. Lopes, M.D.V. Resende, F.F. Silva, D.A.L. Lourenco, M.J. Yokoo, F.F. Cardoso. 2018. Impact of embryo transfer phenotypic records on large-scale beef cattle genetic evaluations. R. Bras. Zootec. 47:e20170033. https://doi.org/10.1590/rbz4720170033
  • Maiorano, A.M., D.A.L. Lourenco, S. Tsuruta, A.M. Toro, N.B. Stafuzza, Y. Masuda, A. Vercesi Filho, J.N.S.G. Cyrillo, R.A. Curi, J.A.V. Silva. 2018. Assessing genetic architecture and signatures of selection of dual purpose Gir cattle populations using genomic information. PlosONE. 13(8):e0200694. https://doi.org/10.1371/journal.pone.0200694
  • Masuda, Y., P. M. VanRaden, I. Misztal, and T. J. Lawlor. 2018. Differing genetic trend estimates from traditional and genomic evaluations of genotyped animals as evidence of preselection bias in US Holsteins. J. Dairy Sci. 101:5194-5206. https://doi.org/10.3168/jds.2017-13310
  • Oliveira, D. P., D. A. L. Lourenco, S. Tsuruta, I. Misztal, D. J. A. Santos, F. R. de Araújo Neto, R. R. Aspilcueta-Borquis, F. Baldi, R. Carvalheiro, G. M. F. de Camargo, L. G. Albuquerque, and H. Tonhati. 2018. Reaction norm for yearling weight in beef cattle using single-step genomic evaluation. J. Anim. Sci. 96:27-34. https://doi.org/10.1093/jas/skx006
  • Salem, M., R. Al-Tobasei, A. Ali, D. A. L. Lourenco, G. Gao, Y. Palti, B. Kenney, and T. D. Leeds. 2018. Genome-wide association analysis with a 50K transcribed gene SNP-chip identifies QTL affecting muscle yield in rainbow trout. Front. Genet. 9:387.  https://doi.org/10.3389/fgene.2018.00387
  • Silva, R. M. O., J. P. Evenhuis, R. L. Vallejo, S. Tsuruta, G. D. Wiens, K. E. Martin, J. E. Parsons, Y. Palti, D. A. L. Lourenco, and T. D. Leeds. 2018. 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.  https://doi.org/10.1093/jas/sky478
  • Stafuzza, N. B., R. M. O. Silva, E. Peripolli, L. A. F. Bezerra, R. B. Lôbo, C. U. Magnabosco, F. A. D. Croce, J. B. Osterstock, D. P. Munari, D. A. L. Lourenco, and F. Baldi. 2018. Genome-wide association study provides insights into genes related with horn development in Nelore beef cattle. PLoS ONE. 13: e0202978. https://doi.org/10.1371/journal.pone.0202978 
  • Vallejo R.L., Silva R.M.O., Evenhuis J.P., Gao G., Liu S., Parsons J.E., Martin K.E., Lourenco D.A.L., Leeds T.D. & Y. Palti. 2018. Accurate genomic predictions for BCWD resistance in rainbow trout are achieved using low-density SNP panels: Evidence that long-range LD is a major contributing factor. J. Anim. Breed. Genet. 135:263-274. https://doi.org/10.1111/jbg.12335
  • Zhang, X., S. Tsuruta, S. Andonov, D. A. L. Lourenco, R. L. Sapp, C. Wang, and I. Misztal. 2018. Relationships among mortality, performance, and disorder traits in broiler chickens: a genetic and genomic approach. Poultry Sci. 97:1511-1518. https://doi.org/10.3382/ps/pex431