Choice of assemblers has a critical impact on de novo assembly of SARS-CoV-2 genome and characterizing variants
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Abstract
Background
Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global pandemic following its initial emergence in China. Using next-generation sequencing technologies, a large number of SARS-CoV-2 genomes are being sequenced at an unprecedented rate and being deposited in public repositories. For the de novo assembly of the SARS-CoV-2 genomes, a myriad of assemblers is being used, although their impact on the assembly quality has not been characterized for this virus. In this study, we aim to understand the variabilities on assembly qualities due to the choice of the assemblers.
Results
We performed 6,648 de novo assemblies of 416 SARS-CoV-2 samples using 8 different assemblers with different k-mers. We used Illumina paired-end sequencing reads and compared the genome assembly quality to that of different assemblers. We showed the choice of assemblers plays a significant role in reconstructing the SARS-CoV-2 genome. Two metagenomic assemblers e.g. MEGAHIT and metaSPAdes performed better compared to others in most of the assembly quality metrics including, recovery of a larger fraction of the genome, constructing larger contigs and higher N50, NA50 values etc. We showed that at least 09% (259/2,873) of the variants present in the assemblies between MEGAHIT and metaSPAdes are unique to the assembly methods.
Conclusion
Our analyses indicate the critical role of assembly methods for assembling SARS-CoV-2 genome using short reads and their impact on variant characterization. This study could help guide future studies to determine which assembler is best suited for the de novo assembly of virus genomes.
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SciScore for 10.1101/2020.12.15.422939: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Data source and annotation: Publicly available raw sequencing data of SARS-CoV-2 genome were acquired from Sequence Read Archive (SRA). Sequence Read Archivesuggested: (DDBJ Sequence Read Archive, RRID:SCR_001370)For annotation of genomics features ‘Sars_cov_2.ASM985889v3.100.gff3’ was downloaded from the Ensembl database. Ensemblsuggested: (Ensembl, RRID:SCR_002344)Read pre-processing: Adapter and low-quality bases were trimmed using Trimmomatic Trimmomaticsuggested: (Trimmomatic, RRID:SCR_011848)Raw reads were quality checked using FastQC and multiQC (Andrews S., 2010; Ewels et al., 2016) … SciScore for 10.1101/2020.12.15.422939: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Data source and annotation: Publicly available raw sequencing data of SARS-CoV-2 genome were acquired from Sequence Read Archive (SRA). Sequence Read Archivesuggested: (DDBJ Sequence Read Archive, RRID:SCR_001370)For annotation of genomics features ‘Sars_cov_2.ASM985889v3.100.gff3’ was downloaded from the Ensembl database. Ensemblsuggested: (Ensembl, RRID:SCR_002344)Read pre-processing: Adapter and low-quality bases were trimmed using Trimmomatic Trimmomaticsuggested: (Trimmomatic, RRID:SCR_011848)Raw reads were quality checked using FastQC and multiQC (Andrews S., 2010; Ewels et al., 2016) (Fig. 1a) FastQCsuggested: (FastQC, RRID:SCR_014583)The parallel version of ABySS is capable of assembling large genomes (Simpson etal. ABySSsuggested: (ABySS, RRID:SCR_010709)SPAdes can assemble sequences from single-cell and multicell data types (Bankevich et al., 2012). SPAdessuggested: (SPAdes, RRID:SCR_000131)Trinity performs de novo transcriptome assembly (Grabherr et al., 2011). Trinitysuggested: (Trinity, RRID:SCR_013048)Fixed k-mer values 21, 63, 99 were used for ABySS, Velvet, MetaVelvet and Ray Meta. MetaVelvetsuggested: (MetaVelvet, RRID:SCR_011915)Alignment: We aligned the assembled contigs to the SARS-CoV-2 ‘MN908947.3’ reference genome using Minimap2 (version 2.17 r941) (Li, 2018). Minimap2suggested: (Minimap2, RRID:SCR_018550)To align Illumina paired-end reads, we used BWA tools (version 0.7.17 r1188) (Li, 2013) with its mem feature enabled and default parameters. BWAsuggested: (BWA, RRID:SCR_010910)Variant calling from assembled contigs: After aligning the assembled contigs to the reference genome using Minimap2, we sorted the contigs by coordinates and indexed using SAMtools (version 1.11)(Li et al., 2009). SAMtoolssuggested: (SAMTOOLS, RRID:SCR_002105)Results from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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