McAN: an ultrafast haplotype network construction algorithm

SummaryHaplotype network is becoming popular due to its increasing use in analyzing genealogical relationships of closely related genomes. We newly proposed McAN, a minimum-cost arborescence based haplotype network construction algorithm, by considering mutation spectrum history (mutations in ancestry haplotype should be contained in descendant haplotype), node size (corresponding to sample count for a given node) and sampling time. McAN is two orders of magnitude faster than the state-of-the-art algorithms, making it suitable for analyzation of massive sequences. AvailabilitySource code is written in C/C++ and available at https://github.com/Theory-Lun/McAN and https://ngdc.cncb.ac.cn/biocode/tools/BT007301 under the MIT license. The online web service of McAN is available at https://ngdc.cncb.ac.cn/ncov/online/tool/haplotype. SARS-CoV-2 dataset are available at https://ngdc.cncb.ac.cn/ncov/.

Genomic perspectives on the emerging SARS-CoV-2 Omicron variant

A new variant of concern for SARS-CoV-2, Omicron (B.1.1.529), was designated by the World Health Organization on November 26, 2021. This study analyzed the viral genome sequencing data of 108 samples collected from patients infected with Omicron. First, we found that the enrichment efficiency of viral nucleic acids was reduced due to mutations in the region where the primers anneal to. Second, the Omicron variant possesses an excessive number of mutations compared to other variants circulating at the same time (62 vs. 45), especially in the Spike gene. Mutations in the Spike gene confer alterations in 32 amino acid residues, which was more than those observed in other SARS-CoV-2 variants. Moreover, a large number of nonsynonymous mutations occur in the codons for the amino acid residues located on the surface of the Spike protein, which could potentially affect the replication, infectivity, and antigenicity of SARS-CoV-2. Third, there are 53 mutations between the Omicron variant and its closest sequences available in public databases. Many of those mutations were rarely observed in the public database and had a low mutation rate. In addition, the linkage disequilibrium between these mutations were low, with a limited number of mutations (6) concurrently observed in the same genome, suggesting that the Omicron variant would be in a different evolutionary branch from the currently prevalent variants. To improve our ability to detect and track the source of new variants rapidly, it is imperative to further strengthen genomic surveillance and data sharing globally in a timely manner.

Genomic epidemiology of SARS-CoV-2 in Pakistan

Pakistan has been severely affected by the COVID-19 pandemic. To investigate the initial introductions and transmissions of the SARS-CoV-2 in the country, we performed the largest genomic epidemiology study of COVID-19 in Pakistan and generated 150 complete SARS-CoV-2 genome sequences from samples collected before June 1, 2020. We identified a total of 347 variants, 29 of which were over-represented in Pakistan. Meanwhile, we found over one thousand intra-host single-nucleotide variants. Several of them occurred concurrently, indicating possible interactions among them. Some of the hypermutable positions were not observed in the polymorphism data, suggesting strong purifying selections. The genomic epidemiology revealed five distinctive spreading clusters. The largest cluster consisted of 74 viruses which were derived from different geographic locations and formed a deep hierarchical structure, indicating an extensive and persistent nation-wide transmission of the virus that was probably contributed by a signature mutation of this cluster. Twenty-eight putative international introductions were identified, several of which were consistent with the epidemiological investigations. No progenies of any of these 150 viruses have been found outside of Pakistan, most likely due to the nonphmarcological intervention to control the virus. This study has inferred the introductions and transmissions of SARS-CoV-2 in Pakistan, which could provide a guidance for an effective strategy for disease control.

The global landscape of SARS-CoV-2 genomes, variants, and haplotypes in 2019nCoVR

On 22 January 2020, the National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), created the 2019 Novel Coronavirus Resource (2019nCoVR), an open-access SARS-CoV-2 information resource. 2019nCoVR features a comprehensive integration of sequence and clinical information for all publicly available SARS-CoV-2 isolates, which are manually curated with value-added annotations and quality evaluated by our in-house automated pipeline. Of particular note, 2019nCoVR performs systematic analyses to generate a dynamic landscape of SARS-CoV-2 genomic variations at a global scale. It provides all identified variants and detailed statistics for each virus isolate, and congregates the quality score, functional annotation, and population frequency for each variant. It also generates visualization of the spatiotemporal change for each variant and yields historical viral haplotype network maps for the course of the outbreak from all complete and high-quality genomes. Moreover, 2019nCoVR provides a full collection of SARS-CoV-2 relevant literature on COVID-19 (Coronavirus Disease 2019), including published papers from PubMed as well as preprints from services such as bioRxiv and medRxiv through Europe PMC. Furthermore, by linking with relevant databases in CNCB-NGDC, 2019nCoVR offers data submission services for raw sequence reads and assembled genomes, and data sharing with National Center for Biotechnology Information. Collectively, all SARS-CoV-2 genome sequences, variants, haplotypes and literature are updated daily to provide timely information, making 2019nCoVR a valuable resource for the global research community. 2019nCoVR is accessible at https://bigd.big.ac.cn/ncov/.

Worldwide tracing of mutations and the evolutionary dynamics of SARS-CoV-2

Understanding the mutational and evolutionary dynamics of SARS-CoV-2 is essential for treating COVID-19 and the development of a vaccine. Here, we analyzed publicly available 15,818 assembled SARS-CoV-2 genome sequences, along with 2,350 raw sequence datasets sampled worldwide. We investigated the distribution of inter-host single nucleotide polymorphisms (inter-host SNPs) and intra-host single nucleotide variations (iSNVs). Mutations have been observed at 35.6% (10,649/29,903) of the bases in the genome. The substitution rate in some protein coding regions is higher than the average in SARS-CoV-2 viruses, and the high substitution rate in some regions might be driven to escape immune recognition by diversifying selection. Both recurrent mutations and human-to-human transmission are mechanisms that generate fitness advantageous mutations. Furthermore, the frequency of three mutations (S protein, F400L; ORF3a protein, T164I; and ORF1a protein, Q6383H) has gradual increased over time on lineages, which provides new clues for the early detection of fitness advantageous mutations. Our study provides theoretical support for vaccine development and the optimization of treatment for COVID-19. We call researchers to submit raw sequence data to public databases.

Expert consensus on microbiome sequencing and analysis / 生物工程学报

In the past ten years, the research and application of microbiome has continued to increase. The microbiome has gradually become the research focus in the fields of life science, environmental science, and medicine. Meanwhile, many countries and organizations around the world are launching their own microbiome projects and conducting a multi-faceted layout, striving to gain a strategic position in this promising field. In addition, whether it is scientific research or industrial applications, there has been a climax of research and a wave of investment and financing, accordingly, products and services related to the microbiome are constantly emerging. However, due to the rapid development of microbiome sequencing and analysis related technologies and methods, the research and application from various countries have not yet unified on the standards of technology, programs, and data. Domestic industry participants also have insufficient understanding of the microbiome. New methods, technologies, and theories have not yet been fully accepted and used. In addition, some of the existing standards and guidelines are too general with poor practicality. This not only causes obstacles in the integration of scientific research data and waste of resources, but also gives related companies unfair competition opportunity. More importantly, China still lacks national standards related to the microbiome, and the national microbiome project is still in the process of preparation. In this context, the experts and practitioners of the microbiome worked together and developed the consensus of experts. It can not only guide domestic scientific research and industrial institutions to regulate the production, learning and research of the microbiome, the application can also provide reference technical basis for the relevant national functional departments, protect the scale and standardized corporate company's interests, strengthen industry self-discipline, avoid unregulated enterprises from disrupting the market, and ultimately promote the benign development of microbiome-related industries.