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      A comprehensive review of the analysis and integration of omics data for SARS-CoV-2 and COVID-19

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          Abstract

          Since the first report of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, over 100 million people have been infected by COVID-19, millions of whom have died. In the latest year, a large number of omics data have sprung up and helped researchers broadly study the sequence, chemical structure and function of SARS-CoV-2, as well as molecular abnormal mechanisms of COVID-19 patients. Though some successes have been achieved in these areas, it is necessary to analyze and mine omics data for comprehensively understanding SARS-CoV-2 and COVID-19. Hence, we reviewed the current advantages and limitations of the integration of omics data herein. Firstly, we sorted out the sequence resources and database resources of SARS-CoV-2, including protein chemical structure, potential drug information and research literature resources. Next, we collected omics data of the COVID-19 hosts, including genomics, transcriptomics, microbiology and potential drug information data. And subsequently, based on the integration of omics data, we summarized the existing data analysis methods and the related research results of COVID-19 multi-omics data in recent years. Finally, we put forward SARS-CoV-2 (COVID-19) multi-omics data integration research direction and gave a case study to mine deeper for the disease mechanisms of COVID-19.

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Chaolin Huang, Yeming Wang, Xingwang Li … (2020)
          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
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            A Novel Coronavirus from Patients with Pneumonia in China, 2019

            Na Zhu, Dingyu Zhang, Wenling Wang … (2020)
            Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
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              Is Open Access

              A pneumonia outbreak associated with a new coronavirus of probable bat origin

              Peng Zhou, Xing-Lou Yang, Xian-Guang Wang … (2020)
              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.
              Article 0 comments Cited 10112 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Zijun Zhu
                Sainan Zhang
                Ping Wang
                Xinyu Chen
                Jianxing Bi
                Liang Cheng:
                ORCID: https://orcid.org/0000-0002-6665-6710
                Xue Zhang
                Journal
                Journal ID (nlm-ta): Brief Bioinform
                Journal ID (iso-abbrev): Brief Bioinform
                Journal ID (publisher-id): bib
                Title: Briefings in Bioinformatics
                Publisher: Oxford University Press
                ISSN (Print): 1467-5463
                ISSN (Electronic): 1477-4054
                Publication date (Electronic): 28 October 2021
                Publication date PMC-release: 28 October 2021
                Electronic Location Identifier: bbab446
                Affiliations
                College of Bioinformatics Science and Technology , Harbin Medical University, Harbin, Heilongjiang, China, 150081
                College of Bioinformatics Science and Technology , Harbin Medical University, Harbin, Heilongjiang, China, 150081
                College of Bioinformatics Science and Technology , Harbin Medical University, Harbin, Heilongjiang, China, 150081
                College of Bioinformatics Science and Technology , Harbin Medical University, Harbin, Heilongjiang, China, 150081
                College of Bioinformatics Science and Technology , Harbin Medical University, Harbin, Heilongjiang, China, 150081
                College of Bioinformatics Science and Technology , Harbin Medical University, Harbin, Heilongjiang, China, 150081
                NHC and CAMS Key Laboratory of Molecular Probe and Targeted Theranostics , Harbin Medical University, Harbin, Heilongjiang, China, 150028
                NHC and CAMS Key Laboratory of Molecular Probe and Targeted Theranostics , Harbin Medical University, Harbin, Heilongjiang, China, 150028
                McKusick-Zhang Center for Genetic Medicine, Peking Union Medical College, Beijing, China, 100005
                Author notes
                Corresponding author. Liang Cheng, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150028, China; NHC and CAMS Key Laboratory of Molecular Probe and Targeted Theranostics; E-mail: liangcheng@ 123456hrbmu.edu.cn

                Zijun Zhu, Sainan Zhang contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-6665-6710
                Article
                Publisher ID: bbab446
                DOI: 10.1093/bib/bbab446
                PMC ID: 8574485
                PubMed ID: 34718395
                SO-VID: fb4def93-0902-4e23-a306-9a42de69c29d
                Copyright © © The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
                License:

                This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

                This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections.

                History
                Date received : 28 July 2021
                Date revision received : 6 September 2021
                Date accepted : 28 September 2021
                Page count
                Pages: 14
                Funding
                Funded by: Heilongjiang Postdoctoral Science Foundation, DOI 10.13039/100012548;
                Award ID: LBH-Q20030
                Award ID: 2018-69
                Funded by: National Natural Science Foundation of China, DOI 10.13039/501100001809;
                Award ID: 61871160
                Award ID: 2019-15
                Categories
                Subject: Review
                Subject: AcademicSubjects/SCI01060
                Custom metadata
                article-lifecycle PAP

                ScienceOpen disciplines: Bioinformatics & Computational biology
                Keywords: sars-cov-2,covid-19,pandemic,resources,multi-omics,integration
                Data availability:
                ScienceOpen disciplines: Bioinformatics & Computational biology
                Keywords: sars-cov-2, covid-19, pandemic, resources, multi-omics, integration

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