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      Dynamic Surveillance of Mosquitoes and Their Viromes in Wuhan During 2020


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          Mosquitoes are medically important arthropod vectors that harbor a variety of viruses. Geography and climate are known to be associated with variations in mosquito density, species and viromes. Our study investigated the dynamic changes in mosquito populations, species compositions and viromes in a regularly disinfected environment in Wuhan, China, during 2020.


          Traps were set in different mosquito habitats, including an urban residential area, two hospitals, a scenic area and a pig farm in a rural region between April and October of 2020. The collected mosquitoes were subjected to morphological identification, RT-qPCR and metagenomic sequencing.


          A total of 2345 adult mosquitoes were collected. Culex mosquitoes were dominant in both urban regions (90.32%, 1538/1703) and the pig farm (54.98%, 353/642). In RT-qPCR screening, the prevalence of Banna virus was 15% and 3% in mosquitoes from the urban area and the pig farm, respectively, whereas no Japanese encephalitis virus was detected. Culex viromes showed dynamic changes during the collection period. Several mosquito-specific viruses, such as Culex flavivirus, Alphamesonivirus 1, Hubei mosquito virus 2 and Hubei mosquito virus 4, showed seasonal changes and unimodal increases or declines. Other mosquito-specific viruses, such as Wuhan mosquito virus 6, Hubei virga-like virus 2 and Zhejiang mosquito virus 3, were stable in all collected Culex and are potential members of the core viromes.


          This study improves understanding of the dynamic composition of mosquito species and the viromes that they carry, and provides useful information for guiding mosquito control and mosquito-borne disease prevention strategies.

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          Most cited references 38

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          CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes.

          Large-scale recovery of genomes from isolates, single cells, and metagenomic data has been made possible by advances in computational methods and substantial reductions in sequencing costs. Although this increasing breadth of draft genomes is providing key information regarding the evolutionary and functional diversity of microbial life, it has become impractical to finish all available reference genomes. Making robust biological inferences from draft genomes requires accurate estimates of their completeness and contamination. Current methods for assessing genome quality are ad hoc and generally make use of a limited number of "marker" genes conserved across all bacterial or archaeal genomes. Here we introduce CheckM, an automated method for assessing the quality of a genome using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes. We demonstrate the effectiveness of CheckM using synthetic data and a wide range of isolate-, single-cell-, and metagenome-derived genomes. CheckM is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches. Using CheckM, we identify a diverse range of errors currently impacting publicly available isolate genomes and demonstrate that genomes obtained from single cells and metagenomic data vary substantially in quality. In order to facilitate the use of draft genomes, we propose an objective measure of genome quality that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities.
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            Complex heatmaps reveal patterns and correlations in multidimensional genomic data.

            Parallel heatmaps with carefully designed annotation graphics are powerful for efficient visualization of patterns and relationships among high dimensional genomic data. Here we present the ComplexHeatmap package that provides rich functionalities for customizing heatmaps, arranging multiple parallel heatmaps and including user-defined annotation graphics. We demonstrate the power of ComplexHeatmap to easily reveal patterns and correlations among multiple sources of information with four real-world datasets.
              • Record: found
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              Is Open Access

              CD-HIT: accelerated for clustering the next-generation sequencing data

              Summary: CD-HIT is a widely used program for clustering biological sequences to reduce sequence redundancy and improve the performance of other sequence analyses. In response to the rapid increase in the amount of sequencing data produced by the next-generation sequencing technologies, we have developed a new CD-HIT program accelerated with a novel parallelization strategy and some other techniques to allow efficient clustering of such datasets. Our tests demonstrated very good speedup derived from the parallelization for up to ∼24 cores and a quasi-linear speedup for up to ∼8 cores. The enhanced CD-HIT is capable of handling very large datasets in much shorter time than previous versions. Availability: http://cd-hit.org. Contact: liwz@sdsc.edu Supplementary information: Supplementary data are available at Bioinformatics online.

                Author and article information

                Compuscript (Shannon, Ireland )
                20 September 2021
                : 1
                : 1
                [1 ]Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, Hubei, China
                [2 ]University of Chinese Academy of Sciences, Beijing, China
                [3 ]Center Lab of Longhua Branch and Department of Infectious Disease, The Second Clinical Medical College, Jinan University (Shenzhen People’s Hospital), Shenzhen, China
                [4 ]Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
                Author notes
                *Corresponding authors: E-mail: yzm@ 123456wh.iov.cn (ZY), hanxia@ 123456wh.iov.cn (HX)

                Edited by: Wanbo Tai, Shenzhen Bay Laboratory

                Reviewed by: Shengyong Feng, Tsinghua University

                Bo Zhang, Wuhan Institute of Virology, Chinese Academy of Science

                The other two reviewers choose to be anonymous

                #These authors contributed equally to this work.

                Copyright © 2021 The Authors.

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY) 4.0, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 3, Tables: 1, References: 40, Pages: 8
                Self URI (journal page): https://zoonoses-journal.org/
                Funded by: Wuhan Science and Technology Plan Project
                Award ID: 2018201261638501
                Funded by: Open Foundation of Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University
                Award ID: 2021TTM010
                This work was supported by the Wuhan Science and Technology Plan Project (2018201261638501) and Open Foundation of Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University (2021TTM010).
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