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SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Natl Genom Infrastruct, Sci Life Lab, Stockholm, Sweden..ORCID iD: 0000-0001-6085-6749
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Natl Genom Infrastruct, Sci Life Lab, Stockholm, Sweden.
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology. Natl Bioinformat Infrastruct, Sci Life Lab, Stockholm, Sweden..
Natl Genom Infrastruct, Sci Life Lab, Stockholm, Sweden.;Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Stockholm, Sweden..
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2017 (English)In: European Journal of Human Genetics, ISSN 1018-4813, E-ISSN 1476-5438, Vol. 25, no 11, p. 1253-1260Article in journal (Refereed) Published
Abstract [en]

Here we describe the SweGen data set, a comprehensive map of genetic variation in the Swedish population. These data represent a basic resource for clinical genetics laboratories as well as for sequencing-based association studies by providing information on genetic variant frequencies in a cohort that is well matched to national patient cohorts. To select samples for this study, we first examined the genetic structure of the Swedish population using high-density SNP-array data from a nation-wide cohort of over 10 000 Swedish-born individuals included in the Swedish Twin Registry. A total of 1000 individuals, reflecting a cross-section of the population and capturing the main genetic structure, were selected for whole-genome sequencing. Analysis pipelines were developed for automated alignment, variant calling and quality control of the sequencing data. This resulted in a genome-wide collection of aggregated variant frequencies in the Swedish population that we have made available to the scientific community through the website https://swefreq.nbis.se. A total of 29.2 million single-nucleotide variants and 3.8 million indels were detected in the 1000 samples, with 9.9 million of these variants not present in current databases. Each sample contributed with an average of 7199 individual-specific variants. In addition, an average of 8645 larger structural variants (SVs) were detected per individual, and we demonstrate that the population frequencies of these SVs can be used for efficient filtering analyses. Finally, our results show that the genetic diversity within Sweden is substantial compared with the diversity among continental European populations, underscoring the relevance of establishing a local reference data set.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP , 2017. Vol. 25, no 11, p. 1253-1260
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:uu:diva-337314DOI: 10.1038/ejhg.2017.130ISI: 000412823800012PubMedID: 28832569OAI: oai:DiVA.org:uu-337314DiVA, id: diva2:1171782
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscienceKnut and Alice Wallenberg Foundation, 2014.0272Swedish Research CouncilSwedish National Infrastructure for Computing (SNIC), sens2016003EU, European Research Council, 282330
Available from: 2018-01-08 Created: 2018-01-08 Last updated: 2018-01-08Bibliographically approved

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Ameur, AdamDahlberg, JohanViklund, JohanKähäri, AndreasLampa, SamuelLiljedahl, UlrikaJonasson, IngerJohansson, ÅsaFeuk, LarsSyvänen, Ann-ChristineNystedt, BjörnGyllensten, Ulf B.
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