Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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Author: search.filters.author.de Ligt JSubject: search.filters.subject.genomic surveillance

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    Pangenome graphs in infectious disease: a comprehensive genetic variation analysis of Neisseria meningitidis leveraging Oxford Nanopore long reads.
    (Frontiers Media S.A., 2023-08-10) Yang Z; Guarracino A; Biggs PJ; Black MA; Ismail N; Wold JR; Merriman TR; Prins P; Garrison E; de Ligt J; Hane J
    Whole genome sequencing has revolutionized infectious disease surveillance for tracking and monitoring the spread and evolution of pathogens. However, using a linear reference genome for genomic analyses may introduce biases, especially when studies are conducted on highly variable bacterial genomes of the same species. Pangenome graphs provide an efficient model for representing and analyzing multiple genomes and their variants as a graph structure that includes all types of variations. In this study, we present a practical bioinformatics pipeline that employs the PanGenome Graph Builder and the Variation Graph toolkit to build pangenomes from assembled genomes, align whole genome sequencing data and call variants against a graph reference. The pangenome graph enables the identification of structural variants, rearrangements, and small variants (e.g., single nucleotide polymorphisms and insertions/deletions) simultaneously. We demonstrate that using a pangenome graph, instead of a single linear reference genome, improves mapping rates and variant calling for both simulated and real datasets of the pathogen Neisseria meningitidis. Overall, pangenome graphs offer a promising approach for comparative genomics and comprehensive genetic variation analysis in infectious disease. Moreover, this innovative pipeline, leveraging pangenome graphs, can bridge variant analysis, genome assembly, population genetics, and evolutionary biology, expanding the reach of genomic understanding and applications.
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    Tracking the international spread of SARS-CoV-2 lineages B.1.1.7 and B.1.351/501Y-V2 with grinch
    (F1000 Research Limited, 2021-09-17) O'Toole Á; Hill V; Pybus OG; Watts A; Bogoch II; Khan K; Messina JP; COVID-19 Genomics UK (COG-UK) consortium; Network for Genomic Surveillance in South Africa (NGS-SA); Brazil-UK CADDE Genomic Network; Tegally H; Lessells RR; Giandhari J; Pillay S; Tumedi KA; Nyepetsi G; Kebabonye M; Matsheka M; Mine M; Tokajian S; Hassan H; Salloum T; Merhi G; Koweyes J; Geoghegan JL; de Ligt J; Ren X; Storey M; Freed NE; Pattabiraman C; Prasad P; Desai AS; Vasanthapuram R; Schulz TF; Steinbrück L; Stadler T; Swiss Viollier Sequencing Consortium; Parisi A; Bianco A; García de Viedma D; Buenestado-Serrano S; Borges V; Isidro J; Duarte S; Gomes JP; Zuckerman NS; Mandelboim M; Mor O; Seemann T; Arnott A; Draper J; Gall M; Rawlinson W; Deveson I; Schlebusch S; McMahon J; Leong L; Lim CK; Chironna M; Loconsole D; Bal A; Josset L; Holmes E; St George K; Lasek-Nesselquist E; Sikkema RS; Oude Munnink B; Koopmans M; Brytting M; Sudha Rani V; Pavani S; Smura T; Heim A; Kurkela S; Umair M; Salman M; Bartolini B; Rueca M; Drosten C; Wolff T; Silander O; Eggink D; Reusken C; Vennema H; Park A; Carrington C; Sahadeo N; Carr M; Gonzalez G; SEARCH Alliance San Diego; National Virus Reference Laboratory; SeqCOVID-Spain; Danish Covid-19 Genome Consortium (DCGC); Communicable Diseases Genomic Network (CDGN); Dutch National SARS-CoV-2 surveillance program; Division of Emerging Infectious Diseases (KDCA); de Oliveira T; Faria N; Rambaut A; Kraemer MUG
    Late in 2020, two genetically-distinct clusters of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with mutations of biological concern were reported, one in the United Kingdom and one in South Africa. Using a combination of data from routine surveillance, genomic sequencing and international travel we track the international dispersal of lineages B.1.1.7 and B.1.351 (variant 501Y-V2). We account for potential biases in genomic surveillance efforts by including passenger volumes from location of where the lineage was first reported, London and South Africa respectively. Using the software tool grinch (global report investigating novel coronavirus haplotypes), we track the international spread of lineages of concern with automated daily reports, Further, we have built a custom tracking website (cov-lineages.org/global_report.html) which hosts this daily report and will continue to include novel SARS-CoV-2 lineages of concern as they are detected.