Dovrolis N, Kassela K, Konstantinidis K, Kouvela A, Veletza S, Karakasiliotis I. ZWA: Viral genome assembly and characterization hindrances from virus-host chimeric reads; a refining approach.
PLoS Comput Biol 2021;
17:e1009304. [PMID:
34370725 PMCID:
PMC8376068 DOI:
10.1371/journal.pcbi.1009304]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 08/19/2021] [Accepted: 07/24/2021] [Indexed: 11/19/2022] Open
Abstract
Viral metagenomics, also known as virome studies, have yielded an unprecedented number of novel sequences, essential in recognizing and characterizing the etiological agent and the origin of emerging infectious diseases. Several tools and pipelines have been developed, to date, for the identification and assembly of viral genomes. Assembly pipelines often result in viral genomes contaminated with host genetic material, some of which are currently deposited into public databases. In the current report, we present a group of deposited sequences that encompass ribosomal RNA (rRNA) contamination. We highlight the detrimental role of chimeric next generation sequencing reads, between host rRNA sequences and viral sequences, in virus genome assembly and we present the hindrances these reads may pose to current methodologies. We have further developed a refining pipeline, the Zero Waste Algorithm (ZWA) that assists in the assembly of low abundance viral genomes. ZWA performs context-depended trimming of chimeric reads, precisely removing their rRNA moiety. These, otherwise discarded, reads were fed to the assembly pipeline and assisted in the construction of larger and cleaner contigs making a substantial impact on current assembly methodologies. ZWA pipeline may significantly enhance virus genome assembly from low abundance samples and virus metagenomics approaches in which a small number of reads determine genome quality and integrity.
For years now the study of viruses and their genetic composition has been important in their identification and classification. Especially in these times of the pandemic turmoil, accurate knowledge of a virus’ exact genetic composition can help identify its strengths and weaknesses allowing us to track its evolution and assist in the development of vaccines and antiviral agents. The reconstruction of these genomic sequences is called the assembly process, a bioinformatics approach which can be complicated and full of pitfalls. This work identifies one such issue, concerning artifacts introduced in viral genomes from the new technologies of nucleic acid sequencing. The proposed algorithm helps alleviate this problem by tentatively removing these problematic regions while keeping the vast majority of the genetic information required to produce a more complete viral genome. This work is anticipated to assist in the submission of higher integrity and accuracy viral genomes in public databases used for novel virus identification and characterization.
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