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The effect of variant interference on de novo assembly for viral deep sequencing.
Castro, Christina J; Marine, Rachel L; Ramos, Edward; Ng, Terry Fei Fan.
Afiliação
  • Castro CJ; Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, 30329, USA.
  • Marine RL; Oak Ridge Institute for Science and Education, Oak Ridge, TN, USA.
  • Ramos E; Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, 30329, USA.
  • Ng TFF; General Dynamics Information Technology, Inc., contracting agency to the Office of Informatics, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Falls Church, VA, USA.
BMC Genomics ; 21(1): 421, 2020 Jun 22.
Article em En | MEDLINE | ID: mdl-32571214
ABSTRACT

BACKGROUND:

Viruses have high mutation rates and generally exist as a mixture of variants in biological samples. Next-generation sequencing (NGS) approaches have surpassed Sanger for generating long viral sequences, yet how variants affect NGS de novo assembly remains largely unexplored.

RESULTS:

Our results from > 15,000 simulated experiments showed that presence of variants can turn an assembly of one genome into tens to thousands of contigs. This "variant interference" (VI) is highly consistent and reproducible by ten commonly-used de novo assemblers, and occurs over a range of genome length, read length, and GC content. The main driver of VI is pairwise identities between viral variants. These findings were further supported by in silico simulations, where selective removal of minor variant reads from clinical datasets allow the "rescue" of full viral genomes from fragmented contigs.

CONCLUSIONS:

These results call for careful interpretation of contigs and contig numbers from de novo assembly in viral deep sequencing.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Vírus / Biologia Computacional / Mutação Tipo de estudo: Prognostic_studies Idioma: En Revista: BMC Genomics Assunto da revista: GENETICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Vírus / Biologia Computacional / Mutação Tipo de estudo: Prognostic_studies Idioma: En Revista: BMC Genomics Assunto da revista: GENETICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos