Daniela Lino Lourenco Assistant Professor Animal & Dairy Science

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Portrait of Daniela Lino Lourenco

Biography 

Dr. Daniela Lourenco is an Assistant Professor in animal breeding and genetics at the University of Georgia. She was born and raised in Brazil, where she earned her MS and PhD degrees in animal breeding and genetics from Maringa State University. Daniela has been working in this field since 2004 and has published over 240 scientific papers and proceedings, including 66 refereed journal publications. Daniela’s research has focused on improving livestock production using genomic information, developing methods for genetic evaluation, and addressing issues related to the implementation of genomic selection in beef and dairy cattle, poultry, swine, and fish. She has been recently involved on the implementation of single-step genomic evaluation for several American and Canadian beef cattle associations. She has been actively working with several US and international breeding companies. Daniela has built a successful and solid international collaboration and has received over 20 visitors from different countries in the past 4 years. Since she started at UGA as an Assistant Professor in 2015, she has been invited to teach courses and give talks in the US, Europe, South America, and Australia.

B.S., Biological Sciences, Maringa State University, Brazil
M.S., Animal Breeding and Genetics, Maringa State University, Brazil
Ph.D., Animal Breeding and Genetics, Maringa State University, Brazil  and University of Georgia

Description of Research Interests

The increasing availability of genomic information for nearly all livestock species have led to increased interest in using this information to help selecting the best animals in genetic improvement programs. The genomic selection has been associated with additional accuracy in estimating breeding values and reduction in generation intervals, which lead to higher and faster genetic gains. However, the genomic response may be different depending on the species and the population structure, and the genomic strategy may be still unclear in some cases. My research has been focused on improving livestock production using genomic information, and addressing issues related to the implementation of genomic selection mostly in beef and dairy cattle and secondly in poultry and swine. My work comprehends finding the most appropriated methodologies, models, and strategies to evaluate livestock populations.


Selected Recent Publications

Lourenco, D.A.L., S. Tsuruta, B.O. Fragomeni, Y. Masuda, I. Aguilar, A. Legarra, J.K. Bertrand, T.S. Amen, L. Wang, D.W. Moser, and I. Misztal. 2015. Genomic evaluation using single-step genomic BLUP in American Angus. J. Anim. Sci. 93:2653–2662.

Lourenco, D.A.L., I. Misztal, B.O. Fragomeni, S. Tsuruta, I. Aguilar, B. Zumbach, and R.R. Hawken. 2015. Accuracy of estimated breeding values with genomic information on males, females, or both: an example in broiler chicken. Genet. Sel. Evol. 47:56.

Fragomeni, B.O., D.A.L. Lourenco, S. Tsuruta, Y. Masuda, I. Aguilar, A. Legarra, T.J. Lawlor, and I. Misztal. 2015. Hot Topic: Use of genomic recursions in single-step genomic best linear unbiased predictor (BLUP) with a large number of genotypes. J. Dairy Sci. 98:4090–4094.

Tsuruta, S., D.A.L. Lourenco, I. Misztal, and T. J. Lawlor. 2015. Genotype by environment interactions on culling rates and 305-d milk yield of Holstein cows in three US regions. J. Dairy Sci. 98:5796–5805. 

Masuda, Y., I. Misztal, S. Tsuruta, A. Legarra, I. Aguilar, D.A.L. Lourenco, B. Fragomeni, and T. Lawlor. 2016. Implementation of genomic recursions in single-step genomic BLUP for US Holsteins with a large number of genotyped animals. J. Dairy Sci. 99:1968–1974.

Lourenco, D.A.L., S. Tsuruta, B.O. Fragomeni, C.Y. Chen, W.O. Herring, and I. Misztal. 2016. Crossbred evaluations in single-step genomic BLUP using adjusted realized relationship matrices. J. Anim. Sci. 94:909–919.

Pocrnic, I., D.A.L. Lourenco, Y. Masuda, A. Legarra, I. Misztal. 2016. The Dimensionality of Genomic Information and Its Effect on Genomic Prediction. Genetics. 203:573–581.

Zhang, X., D.A.L. Lourenco, I. Aguilar, A. Legarra, and I. Misztal. 2016. Weighted single-step genomic BLUP: an iterative approach for accurate calculation of GEBV and GWAS. Front. Genet. 7:151.

Pocrnic, I., D.A.L. Lourenco, Y. Masuda, and I. Misztal. 2016. Dimensionality of genomic information and performance of algorithm for proven and young across livestock species. Genet. Sel. Evol. 48:82.

Fragomeni, B.O., D.A.L. Lourenco, S. Tsuruta, K. Gray, Y. Huang, and I. Misztal. 2016. Using single step genomic BLUP to enhance mitigation of seasonal losses due to heat stress in pigs. J. Anim. Sci. 94:5004–5013.

Andonov, S., D.A.L. Lourenco, B.O. Fragomeni, Y. Masuda, and I. Misztal. 2017. Accuracy of breeding values in small genotyped populations using different sources of external information — A simulation study. J. Dairy Sci. 100:395–401.

Bradford, H.L., I. Pocrnic, B.O. Fragomeni, D.A.L. Lourenco, and I. Misztal. 2017. Selection of core genotypes in the algorithm for proven and young animals in simulations. J. Anim. Bred. Genet. 134:545-552.

Tsuruta, S., D.A.L. Lourenco, I. Misztal, and T.J. Lawlor. 2017. Genomic analysis of cow mortality and milk production using a threshold-linear model. J. Dairy Sci. 100: 7295-7305.

Fragomeni, B.O., D.A.L. Lourenco, Y. Masuda, A. Legarra, I. Misztal. 2017. Incorporation of Causative Quantitative Trait Nucleotides in Single-step GBLUP. Genet. Sel. Evol. 49:59.

Lourenco, D.A.L., B.O. Fragomeni, H. L. Bradford, I.R. Menezes, J.B.S. Ferraz, S. Tsuruta, I. Aguilar, and I. Misztal. 2017. Implications of SNP weighting on single-step genomic predictions for different reference population sizes. J. Anim. Bred. Genet. 134:463-471.

Guarini, A.R., D.A.L. Lourenco, L.F. Brito, M. Sargolzaei, C. Baes, F. Miglior, I. Misztal, and F. Schenkel. 2018. Comparison of genomic predictions for lowly heritable traits using multi-step and single-step genomic BLUP in Holstein cattle. J. Dairy Sci. 101:8076-8086.

Garcia A.L.S., B. Bosworth, G. Waldbieser, I. Misztal, S. Tsuruta, and D.A.L. Lourenco. 2018. Development of genomic predictions for harvest and carcass weight in channel catfish. Gent. Sel. Evol. 50:66.

Cesarani, A., I. Pocrnic, N. Macciotta, I. Misztal, and D.A.L. Lourenco. 2019. Bias in heritability estimates from genomic restricted maximum likelihood (GREML) methods under different genotyping strategies. J. Anim. Breed. Genet. 136:40-50.

Fragomeni, B.O., Y. Masuda, H.L. Bradford, D.A.L. Lourenco, and I. Misztal. 2019. International bull evaluations by GBLUP with a prediction population. J. Dairy Sci. 102:2330-2335.

Guarini, A.R., D.A.L. Lourenco, L.F. Brito, M. Sargolzaei, C. Baes, F. Miglior, S. Tsuruta, I. Misztal, and F. Schenkel. 2019. Genetics and genomics of reproductive disorders in Holstein cattle. J. Dairy Sci. 102:1341-1353.

Web Publications

1) Misztal, I., S. Tsuruta, D.A.L. Lourenco, Y. Masuda, I. Aguilar, A. Legarra, and Z. Vitezica. 2016. Manual for BLUPF90 family of programs. (http://nce.ads.uga.edu/wiki/lib/exe/fetch.php?media=blupf90_all7.pdf)

2) Legarra, A., D.A.L. Lourenco, and Z. Vitezica. 2018. Bases for Genomic Prediction. (http://genoweb.toulouse.inra.fr/~alegarra/GSIP.pdf)