Identification of known and novel recurrent viral sequences in data from multiple patients and multiple cancers

Jens Friis-Nielsen; Kristin Rós Kjartansdóttir; Sarah Mollerup; Maria Asplund; Tobias Mourier; Randi Holm Jensen; Thomas Arn Hansen; Alba Rey de la Iglesia; Stine Raith Richter; Ida Broman Nielsen; David Eugenio Alquezar Planas; Pernille Vibeke Selmer Olsen; Lasse Vinner; Eva Marie Helena Fridholm; Lars Peter Nielsen; Eske Willerslev; Thomas Sicheritz-Pontén; Ole Lund; Anders Johannes Hansen; Jose M. G. Izarzugaza; Søren Brunak

doi:10.3390/v8020053

Identification of known and novel recurrent viral sequences in data from multiple patients and multiple cancers

Jens Friis-Nielsen, Kristin Rós Kjartansdóttir, Sarah Mollerup, Maria Asplund, Tobias Mourier, Randi Holm Jensen, Thomas Arn Hansen, Alba Rey de la Iglesia, Stine Raith Richter, Ida Broman Nielsen, David Eugenio Alquezar Planas, Pernille Vibeke Selmer Olsen, Lasse Vinner, Eva Marie Helena Fridholm, Lars Peter Nielsen, Eske Willerslev, Thomas Sicheritz-Pontén, Ole Lund, Anders Johannes Hansen, Jose M. G. IzarzugazaSøren Brunak

Disease Systems Biology Program

8 Citationer (Scopus)

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Abstract

Virus discovery from high throughput sequencing data often follows a bottom-up approach where taxonomic annotation takes place prior to association to disease. Albeit effective in some cases, the approach fails to detect novel pathogens and remote variants not present in reference databases. We have developed a species independent pipeline that utilises sequence clustering for the identification of nucleotide sequences that co-occur across multiple sequencing data instances. We applied the workflow to 686 sequencing libraries from 252 cancer samples of different cancer and tissue types, 32 non-template controls, and 24 test samples. Recurrent sequences were statistically associated to biological, methodological or technical features with the aim to identify novel pathogens or plausible contaminants that may associate to a particular kit or method. We provide examples of identified inhabitants of the healthy tissue flora as well as experimental contaminants. Unmapped sequences that co-occur with high statistical significance potentially represent the unknown sequence space where novel pathogens can be identified.

Originalsprog	Engelsk
Artikelnummer	53
Tidsskrift	Viruses
Vol/bind	8
Udgave nummer	2
Antal sider	16
ISSN	1999-4915
DOI	https://doi.org/10.3390/v8020053
Status	Udgivet - 1 feb. 2016

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10.3390/v8020053Licens: CC BY

Identification of Known and Novel Recurrent Viral Sequences in Data from Multiple Patients and Multiple CancersForlagets udgivne version, 1,28 MBLicens: CC BY

Citationsformater

Friis-Nielsen, J., Kjartansdóttir, K. R., Mollerup, S., Asplund, M., Mourier, T., Jensen, R. H., Hansen, T. A., Rey de la Iglesia, A., Richter, S. R., Nielsen, I. B., Alquezar Planas, D. E., Olsen, P. V. S., Vinner, L., Fridholm, E. M. H., Nielsen, L. P., Willerslev, E., Sicheritz-Pontén, T., Lund, O., Hansen, A. J., ... Brunak, S. (2016). Identification of known and novel recurrent viral sequences in data from multiple patients and multiple cancers. Viruses, 8(2), Artikel 53. https://doi.org/10.3390/v8020053

Friis-Nielsen, J, Kjartansdóttir, KR, Mollerup, S, Asplund, M, Mourier, T, Jensen, RH, Hansen, TA, Rey de la Iglesia, A, Richter, SR, Nielsen, IB, Alquezar Planas, DE, Olsen, PVS , Vinner, L, Fridholm, EMH, Nielsen, LP, Willerslev, E, Sicheritz-Pontén, T, Lund, O, Hansen, AJ, Izarzugaza, JMG & Brunak, S 2016, 'Identification of known and novel recurrent viral sequences in data from multiple patients and multiple cancers', Viruses, bind 8, nr. 2, 53. https://doi.org/10.3390/v8020053

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title = "Identification of known and novel recurrent viral sequences in data from multiple patients and multiple cancers",

abstract = "Virus discovery from high throughput sequencing data often follows a bottom-up approach where taxonomic annotation takes place prior to association to disease. Albeit effective in some cases, the approach fails to detect novel pathogens and remote variants not present in reference databases. We have developed a species independent pipeline that utilises sequence clustering for the identification of nucleotide sequences that co-occur across multiple sequencing data instances. We applied the workflow to 686 sequencing libraries from 252 cancer samples of different cancer and tissue types, 32 non-template controls, and 24 test samples. Recurrent sequences were statistically associated to biological, methodological or technical features with the aim to identify novel pathogens or plausible contaminants that may associate to a particular kit or method. We provide examples of identified inhabitants of the healthy tissue flora as well as experimental contaminants. Unmapped sequences that co-occur with high statistical significance potentially represent the unknown sequence space where novel pathogens can be identified.",

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author = "Jens Friis-Nielsen and Kjartansd{\'o}ttir, {Kristin R{\'o}s} and Sarah Mollerup and Maria Asplund and Tobias Mourier and Jensen, {Randi Holm} and Hansen, {Thomas Arn} and {Rey de la Iglesia}, Alba and Richter, {Stine Raith} and Nielsen, {Ida Broman} and {Alquezar Planas}, {David Eugenio} and Olsen, {Pernille Vibeke Selmer} and Lasse Vinner and Fridholm, {Eva Marie Helena} and Nielsen, {Lars Peter} and Eske Willerslev and Thomas Sicheritz-Pont{\'e}n and Ole Lund and Hansen, {Anders Johannes} and Izarzugaza, {Jose M. G.} and S{\o}ren Brunak",

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AU - Friis-Nielsen, Jens

AU - Kjartansdóttir, Kristin Rós

AU - Mollerup, Sarah

AU - Asplund, Maria

AU - Mourier, Tobias

AU - Jensen, Randi Holm

AU - Hansen, Thomas Arn

AU - Rey de la Iglesia, Alba

AU - Richter, Stine Raith

AU - Nielsen, Ida Broman

AU - Alquezar Planas, David Eugenio

AU - Olsen, Pernille Vibeke Selmer

AU - Vinner, Lasse

AU - Fridholm, Eva Marie Helena

AU - Nielsen, Lars Peter

AU - Willerslev, Eske

AU - Sicheritz-Pontén, Thomas

AU - Lund, Ole

AU - Hansen, Anders Johannes

AU - Izarzugaza, Jose M. G.

AU - Brunak, Søren

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N2 - Virus discovery from high throughput sequencing data often follows a bottom-up approach where taxonomic annotation takes place prior to association to disease. Albeit effective in some cases, the approach fails to detect novel pathogens and remote variants not present in reference databases. We have developed a species independent pipeline that utilises sequence clustering for the identification of nucleotide sequences that co-occur across multiple sequencing data instances. We applied the workflow to 686 sequencing libraries from 252 cancer samples of different cancer and tissue types, 32 non-template controls, and 24 test samples. Recurrent sequences were statistically associated to biological, methodological or technical features with the aim to identify novel pathogens or plausible contaminants that may associate to a particular kit or method. We provide examples of identified inhabitants of the healthy tissue flora as well as experimental contaminants. Unmapped sequences that co-occur with high statistical significance potentially represent the unknown sequence space where novel pathogens can be identified.

AB - Virus discovery from high throughput sequencing data often follows a bottom-up approach where taxonomic annotation takes place prior to association to disease. Albeit effective in some cases, the approach fails to detect novel pathogens and remote variants not present in reference databases. We have developed a species independent pipeline that utilises sequence clustering for the identification of nucleotide sequences that co-occur across multiple sequencing data instances. We applied the workflow to 686 sequencing libraries from 252 cancer samples of different cancer and tissue types, 32 non-template controls, and 24 test samples. Recurrent sequences were statistically associated to biological, methodological or technical features with the aim to identify novel pathogens or plausible contaminants that may associate to a particular kit or method. We provide examples of identified inhabitants of the healthy tissue flora as well as experimental contaminants. Unmapped sequences that co-occur with high statistical significance potentially represent the unknown sequence space where novel pathogens can be identified.

KW - Journal Article

KW - Research Support, Non-U.S. Gov't

U2 - 10.3390/v8020053

DO - 10.3390/v8020053

M3 - Journal article

C2 - 26907326

SN - 1999-4915

VL - 8

JO - Viruses

JF - Viruses

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ER -

Identification of known and novel recurrent viral sequences in data from multiple patients and multiple cancers

Abstract

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