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Updated: Dec 17, 2025

Unbiased Deep Sequencing of RNA Viruses from Clinical Samples
Published on: July 2, 2016
The effect of variant interference on de novo assembly for viral deep sequencing
Christina J Castro1,2, Rachel L Marine1, Edward Ramos3
1Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, 30329, USA.
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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