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  • Ameur, AdamUppsala universitet,Institutionen för immunologi, genetik och patologi,Science for Life Laboratory, SciLifeLab (author)

De Novo Assembly of Two Swedish Genomes Reveals Missing Segments from the Human GRCh38 Reference and Improves Variant Calling of Population-Scale Sequencing Data

  • Article/chapterEnglish2018

Publisher, publication year, extent ...

  • 2018-10-09
  • MDPI AG,2018
  • printrdacarrier

Numbers

  • LIBRIS-ID:oai:DiVA.org:su-162937
  • https://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-162937URI
  • https://doi.org/10.3390/genes9100486DOI
  • https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-369762URI

Supplementary language notes

  • Language:English
  • Summary in:English

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  • Subject category:ref swepub-contenttype
  • Subject category:art swepub-publicationtype

Notes

  • The current human reference sequence (GRCh38) is a foundation for large-scale sequencing projects. However, recent studies have suggested that GRCh38 may be incomplete and give a suboptimal representation of specific population groups. Here, we performed a de novo assembly of two Swedish genomes that revealed over 10 Mb of sequences absent from the human GRCh38 reference in each individual. Around 6 Mb of these novel sequences (NS) are shared with a Chinese personal genome. The NS are highly repetitive, have an elevated GC-content, and are primarily located in centromeric or telomeric regions. Up to 1 Mb of NS can be assigned to chromosome Y, and large segments are also missing from GRCh38 at chromosomes 14, 17, and 21. Inclusion of NS into the GRCh38 reference radically improves the alignment and variant calling from short-read whole-genome sequencing data at several genomic loci. A re-analysis of a Swedish population-scale sequencing project yields > 75,000 putative novel single nucleotide variants (SNVs) and removes > 10,000 false positive SNV calls per individual, some of which are located in protein coding regions. Our results highlight that the GRCh38 reference is not yet complete and demonstrate that personal genome assemblies from local populations can improve the analysis of short-read whole-genome sequencing data.

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  • Che, HuiwenUppsala universitet,Institutionen för immunologi, genetik och patologi,Science for Life Laboratory, SciLifeLab (author)
  • Martin, MarcelStockholms universitet,Institutionen för biokemi och biofysik,Science for Life Laboratory (SciLifeLab),Stockholm Univ, DBB, Sci Life Lab, S-11419 Stockholm, Sweden(Swepub:su)marcm (author)
  • Bunikis, IgnasUppsala universitet,Science for Life Laboratory, SciLifeLab,Institutionen för immunologi, genetik och patologi,Uppsala Univ, Dept Immunol Genet & Pathol, Sci Life Lab, S-75236 Uppsala, Sweden(Swepub:uu)ignbu776 (author)
  • Dahlberg, JohanUppsala universitet,Molekylär medicin,Science for Life Laboratory, SciLifeLab(Swepub:uu)johda411 (author)
  • Höijer, IdaUppsala universitet,Institutionen för immunologi, genetik och patologi,Science for Life Laboratory, SciLifeLab(Swepub:uu)idaho846 (author)
  • Häggqvist, SusanaUppsala universitet,Institutionen för immunologi, genetik och patologi,Science for Life Laboratory, SciLifeLab(Swepub:uu)susha415 (author)
  • Vezzi, FrancescoStockholms universitet,Institutionen för biokemi och biofysik,Science for Life Laboratory (SciLifeLab),Stockholm Univ, DBB, Sci Life Lab, S-11419 Stockholm, Sweden(Swepub:su)fvezz (author)
  • Nordlund, JessicaUppsala universitet,Molekylär medicin,Science for Life Laboratory, SciLifeLab,Uppsala Univ, Dept Med Sci, Sci Life Lab, Mol Med, S-75236 Uppsala, Sweden(Swepub:uu)jesno775 (author)
  • Olason, PallUppsala universitet,Science for Life Laboratory, SciLifeLab,Institutionen för cell- och molekylärbiologi(Swepub:uu)palol405 (author)
  • Feuk, LarsUppsala universitet,Medicinsk genetik och genomik(Swepub:uu)larsfeuk (author)
  • Gyllensten, Ulf B.Uppsala universitet,Science for Life Laboratory, SciLifeLab,Medicinsk genetik och genomik(Swepub:uu)ulfgyll (author)
  • Uppsala universitetInstitutionen för immunologi, genetik och patologi (creator_code:org_t)

Related titles

  • In:Genes: MDPI AG9:102073-44252073-4425

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