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Hepatitis C virus whole genome position weight matrix and robust primer design

BACKGROUND: The high degree of sequence heterogeneity found in Hepatitis C virus (HCV) isolates, makes robust nucleic acid-based assays difficult to generate. Polymerase chain reaction based techniques, require efficient and specific sequence recognition. Generation of robust primers capable of reco...

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Detalles Bibliográficos
Autores principales: Qiu, Ping, Cai, Xiao-Yan, Wang, Luquan, Greene, Jonathan R, Malcolm, Bruce
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2002
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC130017/
https://www.ncbi.nlm.nih.gov/pubmed/12323075
http://dx.doi.org/10.1186/1471-2180-2-29
Descripción
Sumario:BACKGROUND: The high degree of sequence heterogeneity found in Hepatitis C virus (HCV) isolates, makes robust nucleic acid-based assays difficult to generate. Polymerase chain reaction based techniques, require efficient and specific sequence recognition. Generation of robust primers capable of recognizing a wide range of isolates is a difficult task. RESULTS: A position weight matrix (PWM) and a consensus sequence were built for each region of HCV and subsequently assembled into a whole genome consensus sequence and PWM. For each of the 10 regions, the number of occurrences of each base at a given position was compiled. These counts were converted to frequencies that were used to calculate log odds scores. Using over 100 complete and 14,000 partial HCV genomes from GenBank, a consensus HCV genome sequence was generated along with a PWM reflecting heterogeneity at each position. The PWM was used to identify the most conserved regions for primer design. CONCLUSIONS: This approach allows rapid identification of conserved regions for robust primer design and is broadly applicable to sets of genomes with all levels of genetic heterogeneity.