Dataset Information

Systematic documentation and analysis of human genetic variation in hemoglobinopathies using the microattribution approach.

ABSTRACT: We developed a series of interrelated locus-specific databases to store all published and unpublished genetic variation related to hemoglobinopathies and thalassemia and implemented microattribution to encourage submission of unpublished observations of genetic variation to these public repositories. A total of 1,941 unique genetic variants in 37 genes, encoding globins and other erythroid proteins, are currently documented in these databases, with reciprocal attribution of microcitations to data contributors. Our project provides the first example of implementing microattribution to incentivise submission of all known genetic variation in a defined system. It has demonstrably increased the reporting of human variants, leading to a comprehensive online resource for systematically describing human genetic variation in the globin genes and other genes contributing to hemoglobinopathies and thalassemias. The principles established here will serve as a model for other systems and for the analysis of other common and/or complex human genetic diseases.

SUBMITTER: Giardine B

PROVIDER: S-EPMC3878152 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Systematic documentation and analysis of human genetic variation in hemoglobinopathies using the microattribution approach.

Giardine Belinda B Borg Joseph J Higgs Douglas R DR Peterson Kenneth R KR Philipsen Sjaak S Maglott Donna D Singleton Belinda K BK Anstee David J DJ Basak A Nazli AN Clark Barnaby B Costa Flavia C FC Faustino Paula P Fedosyuk Halyna H Felice Alex E AE Francina Alain A Galanello Renzo R Gallivan Monica V E MV Georgitsi Marianthi M Gibbons Richard J RJ Giordano Piero C PC Harteveld Cornelis L CL Hoyer James D JD Jarvis Martin M Joly Philippe P Kanavakis Emmanuel E Kollia Panagoula P Menzel Stephan S Miller Webb W Moradkhani Kamran K Old John J Papachatzopoulou Adamantia A Papadakis Manoussos N MN Papadopoulos Petros P Pavlovic Sonja S Perseu Lucia L Radmilovic Milena M Riemer Cathy C Satta Stefania S Schrijver Iris I Stojiljkovic Maja M Thein Swee Lay SL Traeger-Synodinos Jan J Tully Ray R Wada Takahito T Waye John S JS Wiemann Claudia C Zukic Branka B Chui David H K DH Wajcman Henri H Hardison Ross C RC Patrinos George P GP

Nature genetics 20110320 4

We developed a series of interrelated locus-specific databases to store all published and unpublished genetic variation related to hemoglobinopathies and thalassemia and implemented microattribution to encourage submission of unpublished observations of genetic variation to these public repositories. A total of 1,941 unique genetic variants in 37 genes, encoding globins and other erythroid proteins, are currently documented in these databases, with reciprocal attribution of microcitations to dat ...[more]

PMID: 21423179

Similar Datasets

Project description:Background3'-end processing by cleavage and polyadenylation is an important and finely tuned regulatory process during mRNA maturation. Numerous genetic variants are known to cause or contribute to human disorders by disrupting the cis-regulatory code of polyadenylation signals. Yet, due to the complexity of this code, variant interpretation remains challenging.ResultsWe introduce a residual neural network model, APARENT2, that can infer 3'-cleavage and polyadenylation from DNA sequence more accurately than any previous model. This model generalizes to the case of alternative polyadenylation (APA) for a variable number of polyadenylation signals. We demonstrate APARENT2's performance on several variant datasets, including functional reporter data and human 3' aQTLs from GTEx. We apply neural network interpretation methods to gain insights into disrupted or protective higher-order features of polyadenylation. We fine-tune APARENT2 on human tissue-resolved transcriptomic data to elucidate tissue-specific variant effects. By combining APARENT2 with models of mRNA stability, we extend aQTL effect size predictions to the entire 3' untranslated region. Finally, we perform in silico saturation mutagenesis of all human polyadenylation signals and compare the predicted effects of [Formula: see text] million variants against gnomAD. While loss-of-function variants were generally selected against, we also find specific clinical conditions linked to gain-of-function mutations. For example, we detect an association between gain-of-function mutations in the 3'-end and autism spectrum disorder. To experimentally validate APARENT2's predictions, we assayed clinically relevant variants in multiple cell lines, including microglia-derived cells.ConclusionsA sequence-to-function model based on deep residual learning enables accurate functional interpretation of genetic variants in polyadenylation signals and, when coupled with large human variation databases, elucidates the link between functional 3'-end mutations and human health.

Dataset Information

Systematic documentation and analysis of human genetic variation in hemoglobinopathies using the microattribution approach.

Publications

Systematic documentation and analysis of human genetic variation in hemoglobinopathies using the microattribution approach.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets