A Reference Viral Database (RVDB) To Enhance Bioinformatics Analysis of High-Throughput Sequencing for Novel Virus Detection

Abstract

Detection of distantly related viruses by high-throughput sequencing (HTS) is bioinformatically challenging because of the lack of a public database containing all viral sequences, without abundant nonviral sequences, which can extend runtime and obscure viral hits. Our reference viral database (RVDB) includes all viral, virus-related, and virus-like nucleotide sequences (excluding bacterial viruses), regardless of length, and with overall reduced cellular sequences. Semantic selection criteria (SEM-I) were used to select viral sequences from GenBank, resulting in a first-generation viral database (VDB). This database was manually and computationally reviewed, resulting in refined, semantic selection criteria (SEM-R), which were applied to a new download of updated GenBank sequences to create a second-generation VDB. Viral entries in the latter were clustered at 98% by CD-HIT-EST to reduce redundancy while retaining high viral sequence diversity. The viral identity of the clustered representative sequences (creps) was confirmed by BLAST searches in NCBI databases and HMMER searches in PFAM and DFAM databases. The resulting RVDB contained a broad representation of viral families, sequence diversity, and a reduced cellular content; it includes full-length and partial sequences and endogenous nonretroviral elements, endogenous retroviruses, and retrotransposons. Testing of RVDBv10.2, with an in-house HTS transcriptomic data set indicated a significantly faster run for virus detection than interrogating the entirety of the NCBI nonredundant nucleotide database, which contains all viral sequences but also nonviral sequences. RVDB is publically available for facilitating HTS analysis, particularly for novel virus detection. It is meant to be updated on a regular basis to include new viral sequences added to GenBank. To facilitate bioinformatics analysis of high-throughput sequencing (HTS) data for the detection of both known and novel viruses, we have developed a new reference viral database (RVDB) that provides a broad representation of different virus species from eukaryotes by including all viral, virus-like, and virus-related sequences (excluding bacteriophages), regardless of their size. In particular, RVDB contains endogenous nonretroviral elements, endogenous retroviruses, and retrotransposons. Sequences were clustered to reduce redundancy while retaining high viral sequence diversity. A particularly useful feature of RVDB is the reduction of cellular sequences, which can enhance the run efficiency of large transcriptomic and genomic data analysis and increase the specificity of virus detection.

Comparative genomics suggests limited variability and similar evolutionary patterns between major clades of SARS-CoV-2

“…Genomes were aligned to the reference assembly of SARS-CoV-2 as available from Refseq (O'Leary et al 2016); Refseq accession NC_045512.2) by means of the nucmer (Marçais et al, 2018) program. Viral genomes of the SARS 2003 outbreak were retrieved from the NCBI virus database (Goodacre et al, 2018). Classification/association of strains to the 3 (early/middle/late) phases of the epidemic are according to Song et al 2005. Only isolates from the late phase of the epidemic were considered, based on considerations regarding the availability of a relatively high number of genomes (65) and the high level of similarity with the reference SARS-CoV genome.…”

Clinical metagenomics

“…Additionally, public databases for microbial reference genomes are being continuously updated, and laborato ries need to keep track of the exact versions used in addi tion to dealing with potential misannotations and other database errors. Larger and more complete databases containing publicly deposited sequences such as the National Center for Biotechnology Information (NCBI) Nucleotide database are more comprehensive but also contain more errors than curated, more limited data bases such as FDA ARGOS 91,113 or the FDA Reference Viral Database (RVDB) 114 . A combined approach that incorporates annotated sequences from multiple data bases may enable greater confidence in the sensitivity and specificity of microorganism identification.…”

Current Trends in Diagnostics of Viral Infections of Unknown Etiology

“…The poor quality of the reference sequences is a major obstacle to processing data. Because of this, specialized databases are being compiled manually to ensure a strict quality control, e.g., ViPR [170], RVDB [171] and viruSITE [172]. However, they are reliable for the same reason that they are limited, because only a small fraction of all published sequences ever make it to these databases.…”