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The transcriptional response driven by Hypoxia-inducible factor (HIF) is central to the adaptation to oxygen restriction. Hence, the complete identification of HIF targets is essential for understanding the cellular responses to hypoxia. Herein we describe a computational strategy based on the combination of phylogenetic footprinting and transcription profiling meta-analysis for the identification of HIF-target genes. Comparison of the resulting candidates with published HIF1a genome-wide chromatin immunoprecipitation indicates a high sensitivity (78%) and specificity (97.8%). To validate our strategy, we performed HIF1a chromatin immunoprecipitation on a set of putative targets. Our results confirm the robustness of the computational strategy in predicting HIF-binding sites and reveal several novel HIF targets, including RE1-silencing transcription factor co-repressor (RCOR2). In addition, mapping of described polymorphisms to the predicted HIF-binding sites identified several single-nucleotide polymorphisms (SNPs) that could alter HIF binding. As a proof of principle, we demonstrate that SNP rs17004038, mapping to a functional hypoxia response element in the macrophage migration inhibitory factor (MIF) locus, prevents induction of this gene by hypoxia. Altogether, our results show that the proposed strategy is a powerful tool for the identification of HIF direct targets that expands our knowledge of the cellular adaptation to hypoxia and provides cues on the inter-individual variation in this response. ; Ministerio de Ciencia y Tecnología/Ministerio de Ciencia e Innovación (SAF2005-00180 and SAF2008-03147), Comunidad Autónoma de Madrid (S-SAL-0311_2006); and the METOXIA, project ref. HEALTH-F2-2009-222741, under the 7th Research Framework Programme of the European Union. Funding for open access charge: SAF2008-03147. ; Peer Reviewed

The knowledge of the genetic variability of the local population is of utmost importance in personalized medicine and has been revealed as a critical factor for the discovery of new disease variants. Here, we present the Collaborative Spanish Variability Server (CSVS), which currently contains more than 2000 genomes and exomes of unrelated Spanish individuals. This database has been generated in a collaborative crowdsourcing effort collecting sequencing data produced by local genomic projects and for other purposes. Sequences have been grouped by ICD10 upper categories. A web interface allows querying the database removing one or more ICD10 categories. In this way, aggregated counts of allele frequencies of the pseudo-control Spanish population can be obtained for diseases belonging to the category removed. Interestingly, in addition to pseudo-control studies, some population studies can be made, as, for example, prevalence of pharmacogenomic variants, etc. In addition, this genomic data has been used to define the first Spanish Genome Reference Panel (SGRP1.0) for imputation. This is the first local repository of variability entirely produced by a crowdsourcing effort and constitutes an example for future initiatives to characterize local variability worldwide. CSVS is also part of the GA4GH Beacon network. CSVS can be accessed at: http://csvs.babelomics.org/. ; Spanish Ministry of Economy and Competitiveness [SAF2017-88908-R, PT17/0009/0006 to J.D.; PI19/00321 and CIBERER ACCI-06/07/0036 to C.A., PI14-948, PI171659 and CIBERER ACCI-06/07/0036 to M.A.M.P.]; Regional Government of Madrid, RAREGenomicsCM [B2017/BMD-3721 to C.A. and B2017/BMD3721 to M.A.M.P.]; all co-funded with European Regional Development Funds (ERDF) as well as EU H2020INFRADEV-1-2015-1 ELIXIR-EXCELERATE [676559]; University Chair UAM-IIS-FJD of Genomic Medicine and the Ramon Areces Foundation also supported this work. Funding for open access charge: Spanish Ministry of Economy and Competitiveness [SAF2017-88908-R]. ; Sí

The knowledge of the genetic variability of the local population is of utmost importance in personalized medicine and has been revealed as a critical factor for the discovery of new disease variants. Here, we present the Collaborative Spanish Variability Server (CSVS), which currently contains more than 2000 genomes and exomes of unrelated Spanish individuals. This database has been generated in a collaborative crowdsourcing effort collecting sequencing data produced by local genomic projects and for other purposes. Sequences have been grouped by ICD10 upper categories. A web interface allows querying the database removing one or more ICD10 categories. In this way, aggregated counts of allele frequencies of the pseudo-control Spanish population can be obtained for diseases belonging to the category removed. Interestingly, in addition to pseudo-control studies, some population studies can be made, as, for example, prevalence of pharmacogenomic variants, etc. In addition, this genomic data has been used to define the first Spanish Genome Reference Panel (SGRP1.0) for imputation. This is the first local repository of variability entirely produced by a crowdsourcing effort and constitutes an example for future initiatives to characterize local variability worldwide. CSVS is also part of the GA4GH Beacon network. CSVS can be accessed at: http://csvs.babelomics.org/. ; Spanish Ministry of Economy and Competitiveness [SAF2017-88908-R, PT17/0009/0006 to J.D.; PI19/00321 and CIBERER ACCI-06/07/0036 to C.A., PI14-948, PI17-1659 and CIBERER ACCI-06/07/0036 to M.A.M.P.]; Regional Government of Madrid, RAREGenomics-CM [B2017/BMD-3721 to C.A. and B2017/BMD3721 to M.A.M.P.]; all co-funded with European Regional Development Funds (ERDF) as well as EU H2020-INFRADEV-1-2015-1 ELIXIR-EXCELERATE [676559]; University Chair UAM-IIS-FJD of Genomic Medicine and the Ramon Areces Foundation also supported this work. Funding for open access charge: Spanish Ministry of Economy and Competitiveness [SAF2017-88908-R]. ; Peer reviewed