Miguel Pérez-Enciso

Miguel Pérez-Enciso

Universitat Autònoma de Barcelona

Life & Medical Sciences

I am a Biologist and obtained my PhD in 1990 in Genetics (Universidad Complutense, Madrid). After that I moved to the USA and France during three years to carry out post doctoral studies, specializing in Bayesian Statistics applied to Animal Breeding and Quantitative Genetics. I worked at the Institut de Recerca i Tecnologia Agroalimentaria (IRTA) from 1993 - 1999 and at INRA (Toulouse, France) from 1999 til 2003, when I became an ICREA Research Professor. I am also part-time professor in Universitat Autònoma of Barcelona, and I am currently based at Centre for Research in Agricultural Genomics (CRAG) on UAB campus.

Research interests

Most of the genes that are of socioeconomic importance, e.g., genes affecting disease susceptibility or that makes Iberian pig meat taste good, are very difficult to find because they are influenced by many genes of small effect. My main area of research is to develop statistical and computational tools that help us to identify these genes. A topic of particular interest is combining different sources of molecular information, including complete genome sequence, to predict genetic merit. I am also concerned with studying how man has shaped the pattern of genetic variation in livestock species, mainly in the pig, through domestication and artificial selection. I participated in the consortium leading to the publication of the pig genome sequence (Nature, 2012) and I am responsible for the first genome sequence of an ancient pig, a sow that lived in the 16th century in Montsoriu Castle (Girona) and of the first Iberian pig genome.  My current interests include the application of machine learning technologies to genomics in livestock, humans and plants, the use of sequence data for genomic selection and to study adaptation processes, and software development.

Selected publications

– Dufflocq P, Perez-Enciso M, Lhorente JP & Yanez JM 2019, ‘Accuracy of genomic predictions using different imputation error rates in aquaculture breeding programs: A simulation study’, Aquaculture, 503, 225 – 230.

– Zingaretti ML, Monfort A, Perez-Enciso M 2019, ‘pSBVB: A Versatile Simulation Tool To Evaluate Genomic Selection in Polyploid Species’, G3-genes Genomes Genetics, 9, 2, 327 – 334.

Perez-Enciso M & Zingaretti LM 2019, ‘A Guide on Deep Learning for Complex Trait Genomic Prediction’, Genes, 10, 7, 553.

– Ramon E, Belanche-Munoz L & Perez-Enciso M 2019, ‘HIV drug resistance prediction with weighted categorical kernel functions’, Bmc Bioinformatics, 20, 410.

– Cho IC, Park HB, Ahn JI, Han SH, Lee JB, Lim HT, Yoo CK, Jung EJ, Kim DH, Sun WS., Ramayo-Caldas Y, Kim SG, Kang YJ, Kim YK, Shin HS, Seong PN, Hwang IS, Park BY, Hwang S, Lee SS, Ryu YC, Lee JH, Ko MS, Lee K, Andersson G, Pérez-Enciso M & Lee JW 2019, ‘A functional regulatory variant of MYH3 influences muscle fiber-type composition and intramuscular fat content in pigs‘. PLOS Genetics, 15(10), e1008279.