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1 Uio-UCSD Proposal. Hovig-Dale UiO-UCSD Proposal. Hovig-Dale: Understanding DNA variants A. Project Scope (1) The relevance of the scientific problem within the biological and medical sciences: Most common human disorders are now regarded as complex diseases, with a large number of DNA variants each contributing to the phenotype with a small effect. A large number of Single Nucleotide Polymorphisms (SNPs) have been identified from large genome-wide association studies (GWAS) in various disease contexts. We have developed novel statistical tools to improve discovery of these associations[1]. Despite the success of GWAS, only few of the identified SNPs have direct bearing on the protein coding sequence in the local sequence context, as the majority occurs in noncoding DNA. These variants are mostly indirectly associated with disease, associating a region of DNA with the phenotype. The steps from this rather vague association to functional association of phenotype with genotype is generally very demanding, as there may be many relationships that do not necessarily fall close to the variant identified by the GWAS. A case in point is that of a variant identified for contributing to obesity, originally reported to be associated to the closely located gene FTO. However, it was recently found that the variant rather was influencing a transcription factor, IRX3, located megabases away from the tag SNP variant, through chromatin loop formation. There is a lack of strongly predictive methods to address the relationship between noncoding DNA variants and regulatory mechanisms in noncoding DNA. (2) Computational approaches to be used to address this problem, extending prior work in this field We have unique possibilities to address this field, as we have developed 1) a generic system for statistical genomics, termed the Genomic HyperBrowser [2-6] that is perfectly suited to approach a quantitative understanding of relevant features, relying on existing high-throughput and functional data, and 2) novel Bayesian statistical tools to improve discovery of common variants building on enrichment due to gene annotation [1] and pleiotropy [7,8] for a range of disorders [8-10]. Together, we will build a powerful toolbox, including a set of existing and novel statistical tests, to address questions on biological features along the genome, both in global and regional contexts, as well as three-dimensional settings. Combined with the rich sources of public data on chromatin information from such sources as ENCODE, Roadmap Epigenomics, FANTOM5, The Cancer Genome Atlas, Gene Expression Omnibus and others, and with knowledge sources from the biomedical literature, this opens for a completely novel level of integrated power of analysis. We recently developed functionality for direct import of data from the above mentioned data sources into our HyperBrowser package, and are thus able to take on the challenge. Using this system, we will utilize information on chromatin activation in all relevant tissues for a given phenotype, together with information on transcription status of all relevant promoters, as well as transcription information and where available also 3D information, in order to home in on candidate functional mechanisms. These will be prioritized by applying our novel enrichment toolbox, leveraging information from the huge international GWAS data sets available to the team. The approach will give a completely novel level of integrated power of analysis, permitting multi-scale analysis from the base-pair level, up to chromatin loops and beyond. We will primarily concentrate on the phenotypes of psychiatric disease and heritable cancer, as we have specific domain competence within these areas. B. Inter-Institutional Collaboration (1) This project will be based primarily at UiO It will include one year stay at UCSD, in addition to regular visits between the two sites (2) The contributing faculty at UiO, and their roles Eivind Hovig, Dept of Informatics, primary advisor Geir Kjetil Sandve, Dept of Informatics, secondary advisor, Ole A. Andreassen, Medical Faculty, secondary advisor, (3) The contributing faculty at UCSD, and their roles Anders M. Dale, primary advisor, 1 Dominic Holland, secondary advisor (4) Fostering of collaboration between the UCSD and Oslo groups, and distribution of the major scientific and training objectives of the proposal between Oslo and San Diego The project will provide a major advantage in computational and statistical genetics, bringing together the functional genomics analytical expertise in Oslo, and the statistical genomics expertise in San Diego. It will serve to disseminate knowledge on genomic scale functional analysis to San Diego, and will forge strategic links that have been loosely established between Dept of Informatics and UC San Diego. It will further strengthen cross faculty collaboration in Oslo, linking the project to existing collaborations between Ole A Andreassen and Anders M. Dale. C. International and Local Training (1) Courses to be taken at UiO MNSES9100 - Science, Ethics and Society STK9030 - Modern data analysis STK9021 - Applied Bayesian Analysis and Numerical Methods INF9825 - Algorithms for artificial intelligence and natural language processing (2) Additional professional/research training activities at UiO The candidate will be enrolled in The Genomic HyperBrowser scientific team, consisting of several faculty participants, 3-4 researcher/postdocs, and a similar number of PhD students, and as such be participating in transdisciplinary activities within this platform. (3) Additional professional/research training activities at UCSD Statistical genetics, Bayesian statistics, software tools, survival analysis (4) Advisor monitoring of student’s progress and development This will be achieved in regular supervisory group meetings at each institution on a biweekly basis, with inter-institutional participation by web based teleconferencing bimonthly or more. References: 1. Schork AJ, Thompson WK, Pham P, Torkamani A, Roddey JC, et al. (2013) PLoS Genet 9: e1003449. 2. Sandve GK, Gundersen S, Rydbeck H, Glad IK, Holden L, et al. (2010) Genome Biol 11: R121. 3. Sandve GK, Gundersen S, Rydbeck H, Glad IK, Holden L, et al. (2011) BMC Genomics 12: 353. 4. Sandve GK, Gundersen S, Johansen M, Glad IK, Gunathasan K, et al. (2013) Nucleic Acids Res 41: W133-141. 5. Paulsen J, Sandve GK, Gundersen S, Lien TG, Trengereid K, et al. (2014) Bioinformatics 30: 1620-1622. 6. Paulsen J, Lien TG, Sandve GK, Holden L, Borgan O, et al. (2013) Nucleic Acids Res 41: 5164- 5174. 7. Liu JZ, Hov JR, Folseraas T, Ellinghaus E, Rushbrook SM, et al. (2013) Nat Genet 45: 670-675. 8. Andreassen OA, Djurovic S, Thompson WK, Schork AJ, Kendler KS, et al. (2013) Am J Hum Genet 92: 197-209. 9. Andreassen OA, McEvoy LK, Thompson WK, Wang Y, Reppe S, et al. (2014) Hypertension 63: 819-826. 10. Andreassen OA, Harbo HF, Wang Y, Thompson WK, Schork AJ, et al. (2015) Mol Psychiatry 20: 207-214. 2 Eivind Hovig – Curriculum vitae Gender: Male Year of birth: 1953 Nationality: Norwegian E-mail: [email protected] Oslo University Hospital/ Institute of Cancer Research/Section of Tumour Biology and University of Oslo/Institute of Informatics/ Biomedical informatics group Academic degree: Candidatus realium, 1983, Department of General Genetics, University of Oslo, Doctor philos., 1992, Medical Faculty, University of Oslo. Research experience 1980-91: Student and pre-doctoral work at The Norwegian Radium Hospital, Institute for Cancer Research, Department of Genetics. 1992-96: Post-doctoral research fellow at The Norwegian Radium Hospital, Institute for Cancer Research, Department of Tumor Biology. 1997-: Research fellow, group leader at The Norwegian Radium Hospital, Institute for Cancer Research, the Department of Tumor Biology 2005- : Section head, Medical Informatics, Radium-Rikshospitalet 2005- : Adjunct professor, Institute for Informatics, University of Oslo. Awards 2001: Dr. Ragnar Mørks award for scientifc excellence 2002: Diploma SND Inventor prize Publication statistics ISI: Hirsch-index: 34. Sum of the times cited: 5403, citing articles: 4821, average citations per item: 27.6 Scopus profle: http://tinyurl.com/pdc2qtb, Google Scholar profle (http://tinyurl.com/8up5ck9): All Since 2010 Citations 7324 2127 h-index 40 25 i10-index 92 60 i10-index is the number of articles with at least 10 citations Patents: 6 international patents International funding Partner in two EU projects: (ComplexDis, Framework 6), MultiMod (Framework 7), collaborator in NCI project: Prediagnostic allergy and immune-related biomarkers in glioma risk and survival. J. Schwartzbaum PI). Teaching experience Supervision of twelve doctoral students, two diploma engineers, two medical students, and one agricultural student. Presently supervising fve doctoral students, and co- supervising two other doctoral students. Current group leader for two research groups: Genomics and melanoma: 7 members. The group centers on systems biology approaches for melanoma, combining in silico and wet lab work to develop regulatory models of central oncogenic pathways, the master switch of melanoma (MITF), and oncogene induced senescence. Bioinformatics: 6 members. The group has pioneered the concepts of network models with high throughput genomics and DNA denaturation genomics. Currently, the group continues to develop statistical approaches for genomic information, including support for chromatin 3D datasets, solutions for personalized medicine and novel systems biology approaches. Administrative experience:
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