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dc.date.accessioned2018-11-29T15:12:38Z
dc.date.available2018-11-29T15:12:38Z
dc.date.created2018-01-30T10:50:49Z
dc.date.issued2017
dc.identifier.citationMak, Sarah S.T. Gopalakrishnan, Shyam Carøe, Christian Geng, Chunyu Liu, Shanlin Sinding, Mikkel Holger Strander Kuderna, Lukas FK Zhang, Wenwei Fu, Shujin Vieira, Filipe G. Germonpre, Mietje Bocherens, Hervé Fedorov, Sergey Petersen, Bent Sicheritz-Pontén, Thomas Marques-Bonet, Tomas Zhang, Guojie Jiang, Hui Gilbert, Marcus Thomas Pius . Comparative performance of the BGISEQ-500 vs Illumina HiSeq2500 sequencing platforms for palaeogenomic sequencing. GigaScience. 2017, 6(8), 1-13
dc.identifier.urihttp://hdl.handle.net/10852/65844
dc.description.abstractAncient DNA research has been revolutionized following development of next-generation sequencing platforms. Although a number of such platforms have been applied to ancient DNA samples, the Illumina series are the dominant choice today, mainly because of high production capacities and short read production. Recently a potentially attractive alternative platform for palaeogenomic data generation has been developed, the BGISEQ-500, whose sequence output are comparable with the Illumina series. In this study, we modified the standard BGISEQ-500 library preparation specifically for use on degraded DNA, then directly compared the sequencing performance and data quality of the BGISEQ-500 to the Illumina HiSeq2500 platform on DNA extracted from 8 historic and ancient dog and wolf samples. The data generated were largely comparable between sequencing platforms, with no statistically significant difference observed for parameters including level (P = 0.371) and average sequence length (P = 0718) of endogenous nuclear DNA, sequence GC content (P = 0.311), double-stranded DNA damage rate (v. 0.309), and sequence clonality (P = 0.093). Small significant differences were found in single-strand DNA damage rate (δS; slightly lower for the BGISEQ-500, P = 0.011) and the background rate of difference from the reference genome (θ; slightly higher for BGISEQ-500, P = 0.012). This may result from the differences in amplification cycles used to polymerase chain reaction–amplify the libraries. A significant difference was also observed in the mitochondrial DNA percentages recovered (P = 0.018), although we believe this is likely a stochastic effect relating to the extremely low levels of mitochondria that were sequenced from 3 of the samples with overall very low levels of endogenous DNA. Although we acknowledge that our analyses were limited to animal material, our observations suggest that the BGISEQ-500 holds the potential to represent a valid and potentially valuable alternative platform for palaeogenomic data generation that is worthy of future exploration by those interested in the sequencing and analysis of degraded DNA.en_US
dc.languageEN
dc.publisherOxford University Press
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleComparative performance of the BGISEQ-500 vs Illumina HiSeq2500 sequencing platforms for palaeogenomic sequencingen_US
dc.title.alternativeENEngelskEnglishComparative performance of the BGISEQ-500 vs Illumina HiSeq2500 sequencing platforms for palaeogenomic sequencing
dc.typeJournal articleen_US
dc.creator.authorMak, Sarah S.T.
dc.creator.authorGopalakrishnan, Shyam
dc.creator.authorCarøe, Christian
dc.creator.authorGeng, Chunyu
dc.creator.authorLiu, Shanlin
dc.creator.authorSinding, Mikkel Holger Strander
dc.creator.authorKuderna, Lukas FK
dc.creator.authorZhang, Wenwei
dc.creator.authorFu, Shujin
dc.creator.authorVieira, Filipe G.
dc.creator.authorGermonpre, Mietje
dc.creator.authorBocherens, Hervé
dc.creator.authorFedorov, Sergey
dc.creator.authorPetersen, Bent
dc.creator.authorSicheritz-Pontén, Thomas
dc.creator.authorMarques-Bonet, Tomas
dc.creator.authorZhang, Guojie
dc.creator.authorJiang, Hui
dc.creator.authorGilbert, Marcus Thomas Pius
cristin.unitcode185,28,0,0
cristin.unitnameNaturhistorisk museum
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.cristin1555949
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=GigaScience&rft.volume=6&rft.spage=1&rft.date=2017
dc.identifier.jtitleGigaScience
dc.identifier.volume6
dc.identifier.issue8
dc.identifier.startpage1
dc.identifier.endpage13
dc.identifier.doihttp://dx.doi.org/10.1093/gigascience/gix049
dc.identifier.urnURN:NBN:no-68222
dc.type.documentTidsskriftartikkelen_US
dc.type.peerreviewedPeer reviewed
dc.source.issn2047-217X
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/65844/1/gix049.pdf
dc.type.versionPublishedVersion


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