1675 Observatory Dr
436 Animal Sciences Building
Madison, WI 53706
Francisco Peñagaricano is originally from Uruguay, where he earned his BS (2005) in Biology and Biochemistry and his MS (2010) in Animal Science, all from Universidad de la República. He continued his graduate studies at the University of Wisconsin where he earned his MS (2014) in Statistics and Ph.D. (2014) in Animal Science. Before joining UW, Francisco was a faculty member (2015-2020) in the Department of Animal Sciences at the University of Florida.
His research interests are in quantitative genomics and computational biology. His research program focuses on the development and application of methods to dissect the genetic architecture of economically relevant traits in livestock. He typically combines large, nationwide phenotypic datasets or field experiments, with high–throughput genomic technologies, and advanced statistical and computational methods in order to elucidate the connection between genome and phenotype. His research involves gene mapping, gene-set analysis, genomic prediction, methylome and transcriptome analysis, multi-omics data integration, and network modeling.
Selected Peer-Reviewed Articles
JP Nani and F Peñagaricano (2020) Whole-genome homozygosity mapping reveals candidate regions affecting bull fertility in US Holstein cattle. BMC Genomics 21: 338.
A Sigdel, L Liu, R Abdollahi-Arpanahi, I Aguilar, and F Peñagaricano (2020) Genetic dissection of reproductive performance of dairy cows under heat stress. Animal Genetics (in press)
N Gross, F Peñagaricano, and H Khatib (2020) Integration of whole-genome DNA methylation data with RNA sequencing data to identify markers for bull fertility. Animal Genetics (in press)
R Abdollahi-Arpanahi, D Gianola, and F Peñagaricano (2020) Deep learning versus parametric and ensemble methods for genomic prediction of complex phenotypes. Genetics Selection Evolution 52: 12.
H Louvandini, PS Corrêa, R Amorín, L Liu, EH Ieda, CR Jimenez, SM Tsai, CM McManus, and F Peñagaricano (2020) Gestational and lactational exposure to gossypol alters the testis transcriptome. BMC Genomics 21: 59.
FS Lima, FT Silvestre, F Peñagaricano, and WW Thatcher (2020) Early genomic prediction of daughter pregnancy rate is associated with improved reproductive performance in Holstein dairy cows. Journal of Dairy Science 103: 3312-3324.
HA Pacheco, FM Rezende, and F Peñagaricano (2020) Gene mapping and genomic prediction of bull fertility using sex chromosome markers. Journal of Dairy Science 103: 3304-3311.
N Gross, MG Strillacci, F Peñagaricano, and H Khatib (2019) Characterization and functional roles of paternal RNAs in 2–4 cell bovine embryos. Scientific Reports 9: 20347.
A Sigdel, R Abdollahi-Arpanahi, I Aguilar, and F Peñagaricano (2019) Whole genome mapping reveals novel genes and pathways involved in milk production under heat stress in US Holstein cows. Frontiers in Genetics 10: 928.
R Abdollahi-Arpanahi, MR Carvalho, ES Ribeiro, and F Peñagaricano (2019) Association of lipid-related genes implicated in conceptus elongation with female fertility traits in dairy cattle. Journal of Dairy Science 102: 10020–10029.
JP Nani, FM Rezende, and F Peñagaricano (2019) Predicting male fertility in dairy cattle using markers with large effect and functional annotation data. BMC Genomics 20: 258.
FM Rezende, JP Nani, and F Peñagaricano (2019) Genomic prediction of bull fertility in US Jersey dairy cattle. Journal of Dairy Science 102: 3230–3240.
JD Leal Gutierrez, FM Rezende, MA Elzo, DD Johnson, F Peñagaricano, and RG Mateescu (2018) Structural equation modeling and whole-genome scans uncover chromosome regions and enriched pathways for carcass and meat quality in beef. Frontiers in Genetics 9: 532.
AL Skibiel, F Peñagaricano, R Amorín, BM Ahmed, GE Dahl, and J Laporta (2018) In utero heat stress alters the offspring epigenome. Scientific Reports 8: 14609.
HA Pacheco, S da Silva, A Sigdel, CK Mak, KN Galvão, RA Teixeira, LT Dias, and F Peñagaricano (2018) Gene mapping and gene-set analysis for milk fever incidence in Holstein dairy cattle. Frontiers in Genetics 9: 465.
Selected Book Chapters
JE Koltes and F Peñagaricano (2019) Linking genotype to phenotype: functional annotation as a tool to advance dairy cattle breeding. In: Advances in Breeding of Dairy Cattle. Chapter 16. Burleigh Dodds Science.
F Peñagaricano (2019) Genetics and genomics of dairy cattle. In: Animal Agriculture: Challenges, Innovations, and Sustainability. pp 101-119. Elsevier.
F Peñagaricano, A De Vries, and DT Bennink (2017) Genomic selection and reproductive technologies to optimize herd replacements. In: Large Dairy Herd Management, 3rd ed. pp 379-388. ADSA® Foundation.
GJM Rosa, VPS Felipe, and F Peñagaricano (2016) Applications of Graphical Models in Quantitative Genetics and Genomics. In: Systems Biology in Animal Production and Health, Vol. 1. pp 95-116. Springer International Publishing.
Associate Editor BMC Genomics (2018-present)
Member ADSA Program Committee – Breeding and Genetics (2019-present)
Excellence Award for Assistant Professors, University of Florida (2019)