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Rapid whole genome sequencing (rWGS) of peripheral blood has been used to detect microbial DNA in acute infections. Cytomegalovirus (CMV) is a herpesvirus capable of causing severe disease in neonates and immunocompromised patients. We identified CMV in patients undergoing diagnostic rWGS by matching reads that did not align to the human reference genome to a database of microbial genomes. rWGS was conducted on peripheral blood obtained from ill pediatric patients (age 1 day to 18 years). Reads not aligning to the human genome were analyzed using an in-house pipeline to identify DNA consistent with CMV infection. Of 669 patients who received rWGS from July 2016 through July 2019, we identified 28 patients (4.2%) with reads that aligned to the CMV reference genome. Six of these patients had clinical findings consistent with symptomatic CMV infection. Positive results were highly correlated (R2 > 0.99, p < 0.001) to a CMV-qPCR assay conducted on DNA isolated from whole blood samples. In acutely ill children receiving rWGS for diagnosis of genetic disease, we propose analysis of patient genetic data to identify CMV, which could impact treatment of up to 4% of children in the intensive care unit.
Pubmed ID: 32620939 RIS Download
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MBGD is a database for comparative analysis of completely sequenced microbial genomes, the number of which is now growing rapidly. The aim of MBGD is to facilitate comparative genomics from various points of view such as ortholog identification, paralog clustering, motif analysis and gene order comparison. The heart of MBGD function is to create orthologous or homologous gene cluster table. For this purpose, similarities between all genes are precomputed and stored into the database, in addition to the annotations of genes such as function categories that were assigned by the original authors and motifs that were found in the translated sequence. Using these homology data, MBGD dynamically creates orthologous gene cluster table. Users can change a set of organisms or cutoff parameters to create their own orthologous grouping. Based on this cluster table, users can further analyze multiple genomes from various points of view with the functions such as global map comparison, local map comparison, multiple sequence alignment and phylogenetic tree construction.
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