10/12/2014 - 12:00 - Auditori PRBB

Transcriptome variation across individuals and species

Sessions científiques, CRG Group Leader Seminars

Roderic Guigó

Computational Biology of RNA Processing Group, Bioinformatics and Genomics Programme, CRG

Roderic Guigó obtained his PhD in 1988 for work on Computational Methods on Evolutionary Ecology carried out with Jordi Ocaña at the Department of Statistics from the Universitat de Barcelona. He then moved to the Dana Farber Cancer Institute, and later to Boston University, where he was a postdoctoral fellow with Temple F. Smith. With Smith, he became interested in Computational Genomics, which has been since then the main field of Guigó's research. On 1992 he moved to Los Alamos National Laboratory, where he was a postdoctoral fellow at the Theoretical Biology and Biophysics Group with James W. Fickett. In 1994 he returned to Barcelona where he joined the IMIM. Since 2001 he is the coordinator of the Bioinfomatics and Genomics Program of the Center for Genomic Regulation in Barcelona. He is also a Bionformatics Professor at the Universitat Pompeu Fabra. Guigó's main research topics are the understanding of the sequence signals that guide the molecular pathways leading from DNA to RNA and to protein sequences.


Gene expression is the key determinant of cellular phenotype, and genome-wide RNA expression analysis has long been a mainstay of genomics and biomedical research, providing a basis for disease classification and insights into regulatory changes underlying human disease. Over the last few years, RNA sequencing (RNA-seq) has become the dominant technology for genome-wide expression studies, with its high sensitivity, ability to differentiate among isoforms and call genetic variants. Whereas expression data across tissues and primary cells, individuals and species is accumulating, only limited data has so far been available to investigate how gene expression varies simultaneously both across tissues and individuals within human populations. During the talk I will present preliminary results on the largest effort so far to produce this data.