Annual meeting: 2013
Fields-Topics: P6 Applied Maths
Type of talk: Fellows Speed Presentation
I have finished my PhD at the Universitat Autònoma de Barcelona (Spain) in July 2013. My PhD project was mentored by Doctors Josep M. Folch and Miguel Perez-Enciso, and was focused on the use of computational biology and statistical genetics methods for the identification of genes related with meat quality in pigs. Previously, I obtained a degree in Veterinary Sciences at the Universidad de Granma (Cuba) in 2006. The great challenge lies in providing functional links that bridge the gap between the vast amounts of genomic data and complex phenotypes. My research interests are related to develop statistical and computational tools to integrate multiple data source (i.e: phenotype, genomic, transcriptomic and metagenomic) that help us to understand the basis of socioeconomic relevant traits in the fields of agriculture genomics and livestock production. The main goal of my AgreenSkills project was to implement generic data analysis pipelines and to use them to contribute to the production and exploitation of the microbiome catalogues for the pig gut microbiome and for bovine rumen microbiome. I had to stop my mobility projects seven months before the end because I was recruited as young permanent scientist (CR2) to work at Génétique et Génomique bovine team (GABI-Unit) from January 2014. In December 2016, I applied for a mobility position until 2020 at Institut de Recerca i Tecnologia Agroalimentàries (Barcelona, Spain) in the frame of a Marie Sk?odowska-Curie grant (P-Sphere). The main goal of my current project is to implement an analytical framework to integrate multi-level omics data for the molecular-based prediction of traits related to feed efficiency, resilience and robustness in pigs.
Microbiomes and their effects on hosts are emerging as outstanding ecosystems to study in various scientific fields. Due to their unprecedented throughput and precision, next-generation sequencing techniques have revolutionized the study of these complex gastrointestinal microbial communities and their interactions with the host. However, the exponential increase in sequencing power has allowed for the generation of increasingly large metagenomic datasets that are becoming difficult to analyze. This challenging task demands state-of-the-art computational biology tools able to manage the massive amounts of next generation sequencing data being generated and, also, to perform the challenging biostatistical analysis once the metagenomics quantitative data are ready. The global aim of this project is to implement such tools in generic data analysis pipelines and to use them to contribute to the production and exploitation of the microbiota catalogues for the porcine and bovine gastrointestinal datasets. Such approaches will be used within two active international consortia in targeting the characterization of metagenome catalogues for the porcine intestinal tract and the bovine rumen. The results will contribute to generate and analyze the highly expected metagenome reference catalogues for the pig intestinal tract and the bovine rumen as well as state-of-the-art computational tools for metagenomics data analysis. At the mid-long term, these achievements will represent a relevant step towards the characterization of livestock microbiota as a relevant new factor to include in animal science technologies.
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