Recently, there have been many noteworthy papers citing CLC Genomics Workbench, a comprehensive, easy-to-use toolbox that ensures continuity in your NGS workflow. Here, we round up just a few of them to offer a sense of the diversity of the research for which CLC Genomics Workbench makes a difference. Below are some examples of how researchers from all over the world use CLC Genomics Workbench as a tool for metagenomic analysis to characterize dengue viruses and pathogens, create de novo assemblies or investigate ocular diseases.
Applied shotgun metagenomics approach for the genetic characterization of dengue viruses
First author: Erley Lizarazo
Dengue virus (DENV) is the fastest pandemic-prone arthropod-borne virus, and is detected through virus serology, isolation of the virus or molecular identification. In this Science Direct paper, an international team of researchers optimized DENV detection using shotgun metagenomics. CLC Genomics Workbench was used to identify, genotype and characterize DENV in tested samples, including SNV calling. Importantly, researchers were able to identify multiple DENV serotypes in the same sample using CLC Genomics Workbench and have defined shotgun metagenomics as a suitable technique for detection and typing of DENV.
FDA-ARGOS is a database with public quality-controlled reference genomes
First author: Heike Sichtig
For correct microbial detection and identification by NGS, quality-controlled and tested databases are fundamental. In a Nature Communications paper, researchers from multiple US government labs and organizations, including NCBI, present the FDA-ARGOS quality-controlled reference genomes as a public database and demonstrate its utility in two example cases. In the first case, CLC Genomics Workbench was used to analyze sequencing reads. For metagenomic analysis, paired-end reads were trimmed and scored on the Phred scale, and trimmed reads were mapped to the Enterococcus avium assembly and Homo sapiens assembly using CLC genomics workbench. The researchers showed an accurate microbial identification of E. avium from metagenomic samples with the FDA-ARGOS reference genomes compared to non-curated GenBank genomes. For Ebola virus molecular inversion probes (MIPS), there was 100% concordance between the gold standard real-time PCR comparator and the in silico target sequence comparison, supporting the feasibility of this strategy for use in NGS-based assay evaluation studies.
A comparison of three different bioinformatics analyses of the 16S–23S rRNA encoding region for bacterial identification
First author: Nilay Peker
To optimize the development of antimicrobial therapy, rapid and reliable identification of pathogens from samples are required. Although Sanger sequencing of the 16S ribosomal RNA (rRNA) gene is used, species identification and discrimination are not always possible due to high sequence homology of the 16S rRNA gene among species. Recently, next–generation sequencing (NGS) of the 16S-23S rRNA encoding region has been proposed as a means for reliable identification of pathogens from samples. However, data analysis is time-consuming, and a database for the complete 16S-23S rRNA encoding regions is not available.
In this study, researchers from the University of Groningen in the Netherlands compared speed and accuracy of different data analysis approaches for 16S-23S rRNA NGS data: de novo assembly followed by BLAST, operational taxonomic unit (OTU) clustering or mapping, using an in-house developed 16S-23S rRNA encoding region database for identification of bacterial species. CLC Genomics Workbench was used for de novo assembly, mapping, and OTU clustering using the CLC Microbial Genomics Module. Furthermore, the researchers’ in-house developed 16S-23S rRNA database was uploaded to CLC Genomics Workbench. The researchers concluded that de novo assembly and BLAST appear to be the optimal approaches for data analysis, with the fastest turnaround time and highest sensitivity for sequencing the 16S-23S rRNA gene.
Role of oxidative stress in Retinitis pigmentosa: new involved pathways by an RNA-Seq analysis
First author: Luigi Donato
Retinitis pigmentosa (RP) is an inherited ocular disease characterized by progressive retinal disruption. One of the leading causes of RP is oxidative stress which arrests the metabolic support of photoreceptors. In this study, a group of researchers from Italy investigated the role of oxidative stress in RP onset and progression by whole transcriptome analysis of human retinal pigment epithelium cells, untreated or treated with 100 µg/ml oxLDL to induce oxidative stress. CLC Genomics Workbench was used for data analysis, including trimming of low-quality reads and quantification of gene expression. As a result, the researchers discovered 29 candidate genes associated with RP.
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