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Large-scale evolutionary surveillance of the 2009 H1N1 influenza A virus using resequencing arrays.

Lee CW, Koh CW, Chan YS, Aw PP, Loh KH, Han BL, Thien PL, Nai GY, Hibberd ML, Wong CW, Sung WK - Nucleic Acids Res. (2010)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Genome Institute of Singapore, Genome, 60 Biopolis Street, Singapore.

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.

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Related in: MedlinePlus

Observed neighbourhood hybridization intensity profiles for unknown error/‘N’ calls. A representative set of observed NHIPs for unknown error/‘N’ calls from patient sample 380. This representative set consists of two unknown error/‘N’ calls randomly selected from each segment.
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Figure 5: Observed neighbourhood hybridization intensity profiles for unknown error/‘N’ calls. A representative set of observed NHIPs for unknown error/‘N’ calls from patient sample 380. This representative set consists of two unknown error/‘N’ calls randomly selected from each segment.

Mentions: Unlike the NHIPs of wildtype and true-mutation calls, the NHIPs of most errors and ‘N’ calls appear haphazard (Figure 5). However, when we traced the locations of these errors and ‘N’ calls on the genome, we found that some are isolated among good calls while others are conjugated in a small locality of the genome. We investigated the NHIPs of isolated errors and ‘N’ calls that occurred among good calls and found that in these NHIPs, only the PM probe of the query base that is an error or ‘N’ call has poor hybridization differentiation with its MM probes while other PM probes have hybridization intensities significantly higher than that of their MM probes in general (Figure 6). This suggests that for such calls, only the PM and MM probes of the query base are noisy while neighbouring PM and MM probes are unaffected. In addition, we also found that long chains of consecutive error and ‘N’ calls (especially at the 5′- and 3′-end of the sample sequences) often have NHIPs where the PM probe of the query base together with neighbouring PM probes, have poor hybridization differentiation with their MM probes (Figure 7). These error and ‘N’ calls usually occur at the ends of the genome segments. In summary, NHIP analysis showed that all true mutation calls had a characteristic profile (Figure 2b) that differed from wild-type sequence calls (Figure 2a). Ambiguous calls arising from different causes, such as homopolymers, isolated errors and hybridization artifacts also have profiles that are distinct from true mutation profiles (Figure 2). See ‘Materials and Methods’ section for details.Figure 5.


Large-scale evolutionary surveillance of the 2009 H1N1 influenza A virus using resequencing arrays.

Lee CW, Koh CW, Chan YS, Aw PP, Loh KH, Han BL, Thien PL, Nai GY, Hibberd ML, Wong CW, Sung WK - Nucleic Acids Res. (2010)

Observed neighbourhood hybridization intensity profiles for unknown error/‘N’ calls. A representative set of observed NHIPs for unknown error/‘N’ calls from patient sample 380. This representative set consists of two unknown error/‘N’ calls randomly selected from each segment.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2874996&req=5

Figure 5: Observed neighbourhood hybridization intensity profiles for unknown error/‘N’ calls. A representative set of observed NHIPs for unknown error/‘N’ calls from patient sample 380. This representative set consists of two unknown error/‘N’ calls randomly selected from each segment.
Mentions: Unlike the NHIPs of wildtype and true-mutation calls, the NHIPs of most errors and ‘N’ calls appear haphazard (Figure 5). However, when we traced the locations of these errors and ‘N’ calls on the genome, we found that some are isolated among good calls while others are conjugated in a small locality of the genome. We investigated the NHIPs of isolated errors and ‘N’ calls that occurred among good calls and found that in these NHIPs, only the PM probe of the query base that is an error or ‘N’ call has poor hybridization differentiation with its MM probes while other PM probes have hybridization intensities significantly higher than that of their MM probes in general (Figure 6). This suggests that for such calls, only the PM and MM probes of the query base are noisy while neighbouring PM and MM probes are unaffected. In addition, we also found that long chains of consecutive error and ‘N’ calls (especially at the 5′- and 3′-end of the sample sequences) often have NHIPs where the PM probe of the query base together with neighbouring PM probes, have poor hybridization differentiation with their MM probes (Figure 7). These error and ‘N’ calls usually occur at the ends of the genome segments. In summary, NHIP analysis showed that all true mutation calls had a characteristic profile (Figure 2b) that differed from wild-type sequence calls (Figure 2a). Ambiguous calls arising from different causes, such as homopolymers, isolated errors and hybridization artifacts also have profiles that are distinct from true mutation profiles (Figure 2). See ‘Materials and Methods’ section for details.Figure 5.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Genome Institute of Singapore, Genome, 60 Biopolis Street, Singapore.

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.

Show MeSH
Related in: MedlinePlus