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Large-scale evolutionary surveillance of the 2009 H1N1 influenza A virus using resequencing arrays
Charlie Wah Heng Lee1,2, Chee Wee Koh1, Yang Sun Chan1, Pauline Poh Kim Aw1, Kuan Hon Loh1, Bing Ling Han1, Pei Ling Thien1, Geraldine Yi Wen Nai1, Martin L. Hibberd1, Christopher W. Wong1,* and Wing-Kin Sung1,2,*
1Genome Institute of Singapore, Genome, 60 Biopolis Street and 2Department of Computer Science, National University of Singapore, 21 Lower Kent Ridge Road, Singapore
*To whom correspondence should be addressed. Email: sungk{at}gis.a-star.edu.sg; ksung{at}comp.nus.edu.sg Correspondence may also be addressed to Christopher W. Wong. Tel: +65 6808-8103; Fax: +65 6808-8305; Email: wongc{at}gis.a-star.edu.sg
Received December 3, 2009. Revised February 2, 2010. Accepted February 2, 2010.
ABSTRACT
In April 2009, a new influenza A (H1N1 2009) virus emerged that rapidly spread around the world. While current variants of this virus have caused widespread disease, particularly in vulnerable groups, there remains the possibility that future variants may cause increased virulence, drug resistance or vaccine escape. Early detection of these virus variants may offer the chance for increased containment and potentially prevention of the virus spread. We have developed and field-tested a resequencing kit that is capable of interrogating all eight segments of the 2009 influenza A(H1N1) virus genome and its variants, with added focus on critical regions such as drug-binding sites, structural components and mutation hotspots. The accompanying base-calling software (EvolSTAR) introduces novel methods that utilize neighbourhood hybridization intensity profiles and substitution bias of probes on the microarray for mutation confirmation and recovery of ambiguous base queries. Our results demonstrate that EvolSTAR is highly accurate and has a much improved call rate. The high throughput and short turn-around time from sample to sequence and analysis results (30 h for 24 samples) makes this kit an efficient large-scale evolutionary biosurveillance tool.
full article
Large-scale evolutionary surveillance of the 2009 H1N1 influenza A virus using resequencing arrays
Charlie Wah Heng Lee1,2, Chee Wee Koh1, Yang Sun Chan1, Pauline Poh Kim Aw1, Kuan Hon Loh1, Bing Ling Han1, Pei Ling Thien1, Geraldine Yi Wen Nai1, Martin L. Hibberd1, Christopher W. Wong1,* and Wing-Kin Sung1,2,*
1Genome Institute of Singapore, Genome, 60 Biopolis Street and 2Department of Computer Science, National University of Singapore, 21 Lower Kent Ridge Road, Singapore
*To whom correspondence should be addressed. Email: sungk{at}gis.a-star.edu.sg; ksung{at}comp.nus.edu.sg Correspondence may also be addressed to Christopher W. Wong. Tel: +65 6808-8103; Fax: +65 6808-8305; Email: wongc{at}gis.a-star.edu.sg
Received December 3, 2009. Revised February 2, 2010. Accepted February 2, 2010.
ABSTRACT
In April 2009, a new influenza A (H1N1 2009) virus emerged that rapidly spread around the world. While current variants of this virus have caused widespread disease, particularly in vulnerable groups, there remains the possibility that future variants may cause increased virulence, drug resistance or vaccine escape. Early detection of these virus variants may offer the chance for increased containment and potentially prevention of the virus spread. We have developed and field-tested a resequencing kit that is capable of interrogating all eight segments of the 2009 influenza A(H1N1) virus genome and its variants, with added focus on critical regions such as drug-binding sites, structural components and mutation hotspots. The accompanying base-calling software (EvolSTAR) introduces novel methods that utilize neighbourhood hybridization intensity profiles and substitution bias of probes on the microarray for mutation confirmation and recovery of ambiguous base queries. Our results demonstrate that EvolSTAR is highly accurate and has a much improved call rate. The high throughput and short turn-around time from sample to sequence and analysis results (30 h for 24 samples) makes this kit an efficient large-scale evolutionary biosurveillance tool.
full article
