Recently, there have been many noteworthy papers citing QIAGEN 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 QIAGEN CLC Genomics Workbench makes a difference. Below are some examples of how researchers from all over the world use this solution as a tool for metagenomic analysis to characterize dengue viruses and pathogens, create de novo assemblies or investigate ocular diseases.
Identifying SARS-CoV-2 related coronaviruses in Malayan pangolins
First author: Tommy Tsan-Yuk Lam
Coronavirus researchers from Hong Kong University use QIAGEN extraction kits and QIAGEN CLC Genomics Workbench to identify SARS-CoV-2 in Malayan pangolins. Their research helps reveal how pangolins may have facilitated the coronavirus transfer to humans, causing the COVID-19 disease. Read their Nature publication here.
First author: Mathilde Richard
In honor of Global Hand Hygiene Day, remember to wash your hands! Check out this paper by researchers at Erasmus University Medical Center, who use QIAGEN CLC Genomics Workbench to investigate how influenza and other respiratory viruses are transmitted from nasal tracts using ferrets as a model. Read their full paper in Nature Communications.
First author: Yangun Wang
Learn about the critical research by Dr. Y. Wang and team from Guangzhou Medical University who studied a subgenotype of human coronavirus, NL63. They used QIAGEN CLC Genomics Workbench to investigate how this virus undergoes continuous mutation and has the potential to cause severe lower respiratory tract infection in humans. Read their research here.
First author: Bei Li
Dr. B. Li and colleagues from Wuhan Institute of Virology have been observing bats for potential coronavirus outbreaks after the SARS and MERS incidents. With the current pandemic, better surveillance practices are necessary to predict and mitigate the emergence of these viruses in humans. See how the team uses QIAGEN CLC Genomics Workbench and QIAGEN extraction kits in a capture-based NGS approach to overcome cost challenges. Discover their research here.
First author: Kelsi O. West
Great research from Texas A&M HSC where K. West and colleagues look at how pre-mRNA splicing decisions influence or are affected by macrophage activation. See how they use QIAGEN CLC Genomics and QIAGEN IPA to understand this link to the innate immune response in this Cell reports paper.
First author: Shrilakshmi Hedge
April is IBS awareness month. Check out this intriguing research by S. Hegde and colleagues from UTMB who look at how bowel obstruction may cause changes to the gut microbiota composition. See how the team utilizes a complete Sample to Insight approach using QIAGEN’s extraction kits for bacterial DNA and RNA and QIAGEN CLC Microbial Genomics Module to identify bacterial species affected
First author: Thomas Aga Legøy
Exciting research from the University of Bergen, where a team uses every part of the QIAGEN RNA-seq solution from Sample to Insight. See how QIAGEN CLC Genomics Workbench, QIAGEN IPA and other QIAGEN products help the team understand the development process of human-induced pluripotent stem cells into pancreatic islet cells. You can access the full Scientific Reports paper here.
Genetic aberrations in iPSCs are introduced by a transient G1/S cell cycle checkpoint deficiency
First author: Ryoko Araki
Crucial research for cell replacement therapy by Dr. R. Araki and colleagues from the National Institute of Radiological Sciences (NIRS) in Japan where they study how point mutations in reprogrammed pluripotent stem cells prevent their therapeutic application. Learn how the team uses QIAGEN CLC Genomics Workbench to understand how a cell cycle checkpoint deficiency causes a cancer-like state in these cells. Read the full Nature Sciences article here.
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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