University of Geneva

About: University of Geneva is a education organization based out in Geneva, Switzerland. It is known for research contribution in the topics: Population & Galaxy. The organization has 26887 authors who have published 65265 publications receiving 2931373 citations. The organization is also known as: Geneva University & Universite de Geneve.

The HUPO PSI's molecular interaction format--a community standard for the representation of protein interaction data.

Abstract: A major goal of proteomics is the complete description of the protein interaction network underlying cell physiology. A large number of small scale and, more recently, large-scale experiments have contributed to expanding our understanding of the nature of the interaction network. However, the necessary data integration across experiments is currently hampered by the fragmentation of publicly available protein interaction data, which exists in different formats in databases, on authors' websites or sometimes only in print publications. Here, we propose a community standard data model for the representation and exchange of protein interaction data. This data model has been jointly developed by members of the Proteomics Standards Initiative (PSI), a work group of the Human Proteome Organization (HUPO), and is supported by major protein interaction data providers, in particular the Biomolecular Interaction Network Database (BIND), Cellzome (Heidelberg, Germany), the Database of Interacting Proteins (DIP), Dana Farber Cancer Institute (Boston, MA, USA), the Human Protein Reference Database (HPRD), Hybrigenics (Paris, France), the European Bioinformatics Institute's (EMBL-EBI, Hinxton, UK) IntAct, the Molecular Interactions (MINT, Rome, Italy) database, the Protein-Protein Interaction Database (PPID, Edinburgh, UK) and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING, EMBL, Heidelberg, Germany).

Cornelia de Lange syndrome is caused by mutations in NIPBL , the human homolog of Drosophila melanogaster Nipped-B

Abstract: Cornelia de Lange syndrome (CdLS; OMIM 122470) is a dominantly inherited multisystem developmental disorder characterized by growth and cognitive retardation; abnormalities of the upper limbs; gastroesophageal dysfunction; cardiac, ophthalmologic and genitourinary anomalies; hirsutism; and characteristic facial features. Genital anomalies, pyloric stenosis, congenital diaphragmatic hernias, cardiac septal defects, hearing loss and autistic and self-injurious tendencies also frequently occur. Prevalence is estimated to be as high as 1 in 10,000 (ref. 4). We carried out genome-wide linkage exclusion analysis in 12 families with CdLS and identified four candidate regions, of which chromosome 5p13.1 gave the highest multipoint lod score of 2.7. This information, together with the previous identification of a child with CdLS with a de novo t(5;13)(p13.1;q12.1) translocation, allowed delineation of a 1.1-Mb critical region on chromosome 5 for the gene mutated in CdLS. We identified mutations in one gene in this region, which we named NIPBL, in four sporadic and two familial cases of CdLS. We characterized the genomic structure of NIPBL and found that it is widely expressed in fetal and adult tissues. The fly homolog of NIPBL, Nipped-B, facilitates enhancer-promoter communication and regulates Notch signaling and other developmental pathways in Drosophila melanogaster.

Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics.

Abstract: Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes.