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      Temporal lineage replacements and dominance of imported variants of concern during the COVID-19 pandemic in Kenya

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          Abstract

          Background

          Kenya’s COVID-19 epidemic was seeded early in March 2020 and did not peak until early August 2020 (wave 1), late-November 2020 (wave 2), mid-April 2021 (wave 3), late August 2021 (wave 4), and mid-January 2022 (wave 5).

          Methods

          Here, we present SARS-CoV-2 lineages associated with the five waves through analysis of 1034 genomes, which included 237 non-variants of concern and 797 variants of concern (VOC) that had increased transmissibility, disease severity or vaccine resistance.

          Results

          In total 40 lineages were identified. The early European lineages (B.1 and B.1.1) were the first to be seeded. The B.1 lineage continued to expand and remained dominant, accounting for 60% (72/120) and 57% (45/79) in waves 1 and 2 respectively. Waves three, four and five respectively were dominated by VOCs that were distributed as follows: Alpha 58.5% (166/285), Delta 92.4% (327/354), Omicron 95.4% (188/197) and Beta at 4.2% (12/284) during wave 3 and 0.3% (1/354) during wave 4. Phylogenetic analysis suggests multiple introductions of variants from outside Kenya, more so during the first, third, fourth and fifth waves, as well as subsequent lineage diversification.

          Conclusions

          The data highlights the importance of genome surveillance in determining circulating variants to aid interpretation of phenotypes such as transmissibility, virulence and/or resistance to therapeutics/vaccines.

          Plain language summary

          The SARS-CoV-2 virus that causes COVID-19 has been changing over time. We investigated the changes in the virus present in Kenya from March 2020 to January 2022. During this period there were five successive waves of infection, during which time more people were infected with the virus. The virus arrived in Kenya from other countries many different times. Identifying the changes in the virus helps us to understand how the virus changes over time and the effect this has on its ability to infect people and make them ill.

          Abstract

          Kimita et al. detail the SARS-CoV-2 lineages present in Kenya during 5 waves of the COVID-19 pandemic between March 2020 and January 2022. Analysis of 1034 genomes identified 40 lineages, with phylogenetic analysis suggesting multiple introductions of variants from outside Kenya.

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          Most cited references23

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            Fast and accurate short read alignment with Burrows–Wheeler transform

            Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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              A pneumonia outbreak associated with a new coronavirus of probable bat origin

              Since the outbreak of severe acute respiratory syndrome (SARS) 18 years ago, a large number of SARS-related coronaviruses (SARSr-CoVs) have been discovered in their natural reservoir host, bats 1–4 . Previous studies have shown that some bat SARSr-CoVs have the potential to infect humans 5–7 . Here we report the identification and characterization of a new coronavirus (2019-nCoV), which caused an epidemic of acute respiratory syndrome in humans in Wuhan, China. The epidemic, which started on 12 December 2019, had caused 2,794 laboratory-confirmed infections including 80 deaths by 26 January 2020. Full-length genome sequences were obtained from five patients at an early stage of the outbreak. The sequences are almost identical and share 79.6% sequence identity to SARS-CoV. Furthermore, we show that 2019-nCoV is 96% identical at the whole-genome level to a bat coronavirus. Pairwise protein sequence analysis of seven conserved non-structural proteins domains show that this virus belongs to the species of SARSr-CoV. In addition, 2019-nCoV virus isolated from the bronchoalveolar lavage fluid of a critically ill patient could be neutralized by sera from several patients. Notably, we confirmed that 2019-nCoV uses the same cell entry receptor—angiotensin converting enzyme II (ACE2)—as SARS-CoV.
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                Author and article information

                Contributors
                john.waitumbi@usamru-k.org
                Journal
                Commun Med (Lond)
                Commun Med (Lond)
                Communications Medicine
                Nature Publishing Group UK (London )
                2730-664X
                17 August 2022
                17 August 2022
                2022
                : 2
                : 103
                Affiliations
                [1 ]GRID grid.33058.3d, ISNI 0000 0001 0155 5938, Kenya Medical Research Institute/US Army Medical Research Directorate–Africa/Kenya, Basic Science Laboratory. Off Kisumu - Kakamega Highway, ; Kisumu, Kenya
                [2 ]Ministry of Defence, Nairobi, Kenya
                Author information
                http://orcid.org/0000-0003-4555-4480
                http://orcid.org/0000-0001-7582-3296
                http://orcid.org/0000-0002-8204-7560
                http://orcid.org/0000-0003-3379-7346
                http://orcid.org/0000-0002-7396-3903
                http://orcid.org/0000-0003-2540-4397
                Article
                167
                10.1038/s43856-022-00167-8
                9382597
                35982756
                288978ea-1ce7-4a2e-a399-1e5047fb75ac
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 2 October 2021
                : 29 July 2022
                Funding
                Funded by: Kenya’s Ministry of Health provided extraction and PCR kits. SARS-CoV-2 sequencing and personnel cost were funded by the Armed Forces Health Surveillance Division (AFHSD) and its Global Emerging Infections Surveillance and Research Branch (ProMIS P0095_21_KY, 2021)
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                © The Author(s) 2022

                viral infection,respiratory distress syndrome
                viral infection, respiratory distress syndrome

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