Research

Our group is broadly interested in quantitative genomics and computational biology. Our research focuses on the development and application of statistical and computational methods to dissect the genetic architecture of economically relevant traits in livestock.

DAIRY CATTLE GENOMICS

Genomic analysis of relevant traits that affect animal productivity and welfare in dairy cattle, with special emphasis on fertility and health traits.

Some recent publications:

LC Novo, L Cavani, P Pinedo, P Melendez, and F Peñagaricano (2022)
Genomic analysis of visceral fat accumulation in Holstein cows.
Frontiers in Genetics 12: 803216.

L Cavani, MB Poindexter, CD Nelson, JEP Santos, and F Peñagaricano (2022)
Gene mapping, gene-set analysis, and genomic prediction of postpartum blood calcium in Holstein cows.
Journal of Dairy Science 105: 525-534.

HA Pacheco, M Battagin, A Rossoni, A Cecchinato, and F Peñagaricano (2021)
Evaluation of bull fertility in Italian Brown Swiss dairy cattle using cow field data.
Journal of Dairy Science 104: 10896-10904.

NUTRITIONAL & ENVIRONMENTAL GENOMICS

Evaluation of the effects of prenatal factors on the epigenome and transcriptome of the offspring.

Some recent publications:

L Liu, R Amorín, P Moriel, N DiLorenzo, PA Lancaster, and F Peñagaricano (2021)
Maternal methionine supplementation during gestation alters alternative splicing and DNA methylation in bovine skeletal muscle.
BMC Genomics 22: 780.

EA Palmer, F Peñagaricano, M Vedovatto, RA Oliveira, SL Field, J Laporta, and P Moriel (2021)
Effects of maternal gestational diet on muscle transcriptome of beef calves following a vaccine-induced immunological challenge.
PLoS ONE 16: e0253810.

L Liu, R Amorín, P Moriel, N DiLorenzo, PA Lancaster, and F Peñagaricano (2020)
Differential network analysis of bovine muscle reveals changes in gene coexpression patterns in response to changes in maternal nutrition.
BMC Genomics 21: 684.

NETWORK MODELING

Inference of gene-phenotype networks in multivariate genetic systems.

Some recent publications:

L Liu, R Amorín, P Moriel, N DiLorenzo, PA Lancaster, and F Peñagaricano (2020)
Differential network analysis of bovine muscle reveals changes in gene coexpression patterns in response to changes in maternal nutrition.
BMC Genomics 21: 684.

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.

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.

COMPUTATIONAL BIOLOGY AND BIOINFORMATICS

Analysis of transcriptional and DNA methylation profiling experiments using sequence data

Some recent publications:

E Jara, F Peñagaricano, E Armstrong, C Menezes, L Tardiz, G Rodons, and A Iriarte (2022)
Identification of long noncoding RNAs involved in eyelid pigmentation of Hereford cattle.
Frontiers in Genetics 13: 864567.

CM Sheftel, L Liu, SL Field, SR Weaver, CM Vezina, F Peñagaricano, and LL Hernandez (2022)
Impact of fluoxetine treatment and folic acid supplementation on the mammary gland transcriptome during peak lactation.
Frontiers in Pharmacology 13: 828735.

T Martins, M Sponchiado, FACC Silva, E Estrada-Cortés, PJ Hansen, F Peñagaricano, and M Binelli (2022)
Progesterone-dependent and -independent modulation of luminal epithelial transcription to support pregnancy in cattle.
Physiological Genomics 54: 71–85.