Bioinformatics and Genomics

Genomics and Disease

Group Structure

Xavier Estivill
Eulàlia Martí
Mariona Bustamante (CREAL), Georgia Escaramis (CIBERESP), Marc Friedländer, Anna Houben, Aparna Prasad, Raquel Rabionet, Mónica Bañez (until December), Hyun Hor (until October), Esther Lizano (until December)
Johanna Aigner (until June), Laia Bassaganyas (until June), Elisa Docampo (until June), Elisabeth Mateu (until June), Daniel Trujillano (until December), Nadia Vilahur (CREAL), Laura Domènech (started September), Joan Pallarés (started September)
Marta Morell, Anna Puig, Yaris Sarria (CREAL), Birgit Kagerbauer (until March), Mª Teresa Zomeño (started May)


Our lab performs experimental and bioinformatics research in medical genomics. The group explores how different types of genetic variants (single nucleotide variants, structural variations, copy number variants, and insertion/deletion variants) contribute to human diseases, mostly neuropsychiatric, neurodegenerative and inflammatory disorders. The interaction of genetic factors with environmental conditions is one of the main areas of research of the group and is addressed by integrating epidemiological and clinical data with genetics information. This interaction can be evaluated throughout a longitudinal approach in the clinical course of each human disorder. We study very well characterized cohorts of patients and use high-throughput genomic platforms and functional studies, including longitudinal investigations of patients at different time-points and cohorts in which exposure to environment has been monitored.

The different research activities of the group can lead to pivotal contributions to the medical genomics field that can, moreover, be strengthened by the development of a coordinated research towards translational medicine. Many of these activities are performed in a framework of collaborations with clinical groups of national and international organizations.

Research Projects

  • Genetic variants and disease
  • Longitudinal and comprehensive -omics analysis of mental diseases
  • Non-coding RNAs and neurodegenerative diseases

Selected Publications

  1. Lappalainen T, Sammeth M, Friedländer MR, ‘t Hoen PA, Monlong J, Rivas MA, Gonzàlez-Porta M, Kurbatova N, Griebel T, Ferreira PG, Barann M, Wieland T, Greger L, van Iterson M, Almlöf J, Ribeca P, Pulyakhina I, Esser D, Giger T, Tikhonov A, Sultan M, Bertier G, MacArthur DG, Lek M, Lizano E, Buermans HP, Padioleau I, Schwarzmayr T, Karlberg O, Ongen H, Kilpinen H, Beltran S, Gut M, Kahlem K, Amstislavskiy V, Stegle O, Pirinen M, Montgomery SB, Donnelly P, McCarthy MI, Flicek P, Strom TM; Geuvadis Consortium, Lehrach H, Schreiber S, Sudbrak R, Carracedo A, Antonarakis SE, Häsler R, Syvänen AC, van Ommen GJ, Brazma A, Meitinger T, Rosenstiel P, Guigó R, Gut IG, Estivill X, Dermitzakis ET; Geuvadis Consortium.
    “Transcriptome and genome sequencing uncovers functional variation in humans.”
    Nature, 501(7468):506-11 (2013).
  2. Bassaganyas L, Beà S, Escaramís G, Tornador C, Salaverria I, Zapata L, Drechsel O, Ferreira PG, Rodriguez-Santiago B, Tubio JM, Navarro A, Martín-García D, López C, Martínez-Trillos A, López-Guillermo A, Gut M, Ossowski S, López-Otín C, Campo E, Estivill X.
    “Sporadic and reversible chromothripsis in chronic lymphocytic leukemia revealed by longitudinal genomic analysis.”
    Leukemia, 27(12):2376-9 (2013).
  3. Trujillano D, Ramos MD, González J, Tornador C, Sotillo F, Escaramis G, Ossowski S, Armengol L, Casals T, Estivill X.
    “Next generation diagnostics of cystic fibrosis and CFTR-related disorders by targeted multiplex high-coverage resequencing of CFTR.”
    J Med Genet, 50(7):455-62 (2013).
  4. Miñones-Moyano E, Friedländer MR, Pallares J, Kagerbauer B, Porta S, Escaramís G, Ferrer I, Estivill X, Martí E.
    “Upregulation of a small vault RNA (svtRNA2-1a) is an early event in Parkinson disease and induces neuronal dysfunction.”
    RNA Biol, 10(7):1093-106 (2013).
  5. Docampo E, Collado A, Escaramís G, Carbonell J, Rivera J, Vidal J, Alegre J, Rabionet R, Estivill X.
    “Cluster analysis of clinical data identifies fibromyalgia subgroups.”
    PLoS One, 8(9):e74873 (2013).