SARS-CoV-2 is a new RNA virus affecting humans and spreads extensively throughout the world since its first outbreak in December,2019.Whether the transmissibility and pathogenicity of SARS-CoV-2 in humans after zoonotic transfer are actively evolving,and driven by adaptation to the new host and environments is still under debate.Understanding the evolutionary mechanism underlying epidemiological and pathological characteristics of COVID-19 is essential for predicting the epidemic trend,and providing guidance for disease control and treatments.Interrogating novel strategies for identifying natural selection using within-species polymorphisms and 3,674,076 SARS-CoV-2 genome sequences of 169 countries as of December 30,2021,we demonstrate with popula-tion genetic evidence that during the course of SARS-CoV-2 pandemic in humans,1)SARS-CoV-2 genomes are overall conserved under purifying selection,especially for the 14 genes related to viral RNA replication,transcription,and assembly;2)ongoing positive selection is actively driving the evolution of 6 genes(e.g.,S,ORF3a,and N)that play critical roles in molecular processes involving pathogen-host interactions,including viral invasion into and egress from host cells,and viral inhi-bition and evasion of host immune response,possibly leading to high transmissibility and mild symptom in SARS-CoV-2 evolution.According to an established haplotype phylogenetic relation-ship of 138 viral clusters,a spatial and temporal landscape of 556 critical mutations is constructed based on their divergence among viral haplotype clusters or repeatedly increase in frequency within at least 2 clusters,of which multiple mutations potentially conferring alterations in viral transmis-sibility,pathogenicity,and virulence of SARS-CoV-2 are highlighted,warranting attention.

Objective:To investigate the total radioactivity in drinking well water around the Bayanwula uranium mine.Methods:Totally 174 samples of drinking well water and 5 samples of filtered well water from residential houses were collected during dry and wet seasons in 2020 around the Bayanwula uranium mine. Total α and total β radioactivity in dry season and wet season were analyzed for detrmining whether there were differences between them and the relation between total radioactivity with different locations away from the uranium center. The radioactivity in filtered drinking well water used in residential houses was also investigated. Radioactivity were measured and analyzed using low background alpha and beta radioactivity meters, and the data were analysed using SPSS analytical statistical method.Results:In the drinking well water around Bayanwula uranium mine, the activity concentrations of total α and β measured in dry season were 0.024-2.468 Bq/L with a mean of (0.605±0.507) Bq/L and 0.125-1.395 Bq/L with a mean of (0.420±0.235) Bq/L, respectively. The values measured in wet season were 0.049-2.988 Bq/L with a mean of (0.825±0.605) Bq/L for total α and 0.059-1.623 Bq/L with a mean of (0.506±0.265) Bq/L for total β, respectively. The average value of total radioactivity in water samples was lower within 10, 30 and 20 km of the uranium mine in the descending order.Conclusions:The radioactivity in well water around the Bayanwula uranium mine is high, with the total α and β in samples greater in wet season than in the dry season and without elevated levels as compared to the pre-mining background.

The Genome Sequence Archive (GSA) is a data repository for archiving raw sequence data, which provides data storage and sharing services for worldwide scientific communities. Considering explosive data growth with diverse data types, here we present the GSA family by expanding into a set of resources for raw data archive with different purposes, namely, GSA (https://ngdc.cncb.ac.cn/gsa/), GSA for Human (GSA-Human, https://ngdc.cncb.ac.cn/gsa-human/), and Open Archive for Miscellaneous Data (OMIX, https://ngdc.cncb.ac.cn/omix/). Compared with the 2017 version, GSA has been significantly updated in data model, online functionalities, and web interfaces. GSA-Human, as a new partner of GSA, is a data repository specialized in human genetics-related data with controlled access and security. OMIX, as a critical complement to the two resources mentioned above, is an open archive for miscellaneous data. Together, all these resources form a family of resources dedicated to archiving explosive data with diverse types, accepting data submissions from all over the world, and providing free open access to all publicly available data in support of worldwide research activities.

The Genome Warehouse (GWH) is a public repository housing genome assembly data for a wide range of species and delivering a series of web services for genome data submission, storage, release, and sharing. As one of the core resources in the National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB;https://ngdc.cncb.ac.cn), GWH accepts both full and partial (chloroplast, mitochondrion, and plasmid) genome sequences with different assembly levels, as well as an update of existing genome assemblies. For each assembly, GWH collects detailed genome-related metadata of biological project, biological sample, and genome assembly, in addition to genome sequence and annotation. To archive high-quality genome sequences and annotations, GWH is equipped with a uniform and standardized procedure for quality control. Besides basic browse and search functionalities, all released genome sequences and annotations can be visualized with JBrowse. By May 21, 2021, GWH has received 19,124 direct submissions covering a diversity of 1108 species and has released 8772 of them. Collectively, GWH serves as an important resource for genome-scale data management and provides free and publicly accessible data to support research activities throughout the world. GWH is publicly accessible at https://ngdc.cncb.ac.cn/gwh.

A novel RNA virus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is responsible for the ongoing outbreak of coronavirus disease 2019 (COVID-19). Population genetic analysis could be useful for investigating the origin and evolutionary dynamics of COVID-19. However, due to extensive sampling bias and existence of infection clusters during the epidemic spread, direct applications of existing approaches can lead to biased parameter estima-tions and data misinterpretation. In this study, we first present robust estimator for the time to the most recent common ancestor (TMRCA) and the mutation rate, and then apply the approach to analyze 12,909 genomic sequences of SARS-CoV-2. The mutation rate is inferred to be 8.69 × 10-4 per site per year with a 95％ confidence interval (CI) of [8.61 × 10-4, 8.77 × 10-4], and the TMRCA of the samples inferred to be Nov 28, 2019 with a 95％ CI of [Oct 20, 2019, Dec 9, 2019]. The results indicate that COVID-19 might originate earlier than and outside of Wuhan Seafood Market. We further demonstrate that genetic polymorphism patterns, including the enrichment of specific haplotypes and the temporal allele frequency trajectories generated from infection clusters, are similar to those caused by evolutionary forces such as natural selection. Our results show that population genetic methods need to be developed to efficiently detangle the effects of sampling bias and infection clusters to gain insights into the evolutionary mechanism ofSARS-CoV-2. Software for implementing VirusMuT can be downloaded at https://bigd.big.ac.cn/biocode/tools/BT007081.

On January 22, 2020, China National Center for Bioinformation (CNCB) released the 2019 Novel Coronavirus Resource (2019nCoVR), an open-access information resource for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). 2019nCoVR features a comprehensive integra-tion 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 an automated in-house pipeline. Of particular note, 2019nCoVR offers systematic analyses to generate a dynamic landscape of SARS-CoV-2 genomic variations at a global scale. It provides all identified variants and their detailed statistics for each virus isolate, and congregates the quality score, functional annotation,and population frequency for each variant. Spatiotemporal change for each variant can be visualized and historical viral haplotype network maps for the course of the outbreak are also generated based on all complete and high-quality genomes available. Moreover, 2019nCoVR provides a full collection of SARS-CoV-2 relevant literature on the coronavirus disease 2019 (COVID-19), 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, 2019nCoVR offers data submission services for raw sequence reads and assembled genomes, and data sharing with NCBI. Collectively, SARS-CoV-2 is updated daily to collect the latest information on genome sequences, variants, hap-lotypes, and literature for a timely reflection, making 2019nCoVR a valuable resource for the global research community. 2019nCoVR is accessible at https://bigd.big.ac.cn/ncov/.

Objective: To investigate the molecular markers of copy number aberrations (CNAs) of genes related to extrohepatic metastasis-free survival after the operation for hepatocellular carcinoma (HCC). Methods: The CNA status of 20 candidate genes in 66 HCC samples was detected by microarray comparative genomic hybridization. The associations between gene CNAs and extrohepatic metastasis-free survival were evaluated using the Cox regression model, Log-rank test, and Kaplan-Meier survival analysis. Results: Multivariate Cox analysis revealed that the independent risk factors for metastasis-free survival were MDM4 gain (hazard ratio [HR] = 2.74, 95% confidence interval [CI] = 1.18-6.37, P < 0.05), APC loss (HR = 8.43, 95% CI = 2.48-28.66, P < 0.01), and BCL2L1 gain (HR = 3.45, 95% CI = 1.13-10.52, P < 0.05) and the independent protective factor was FBXW7 loss (HR = 0.32, 95% CI = 0.12-0.89, P < 0.05). By stepwise Cox regression analysis, three CNAs related to metastasis-free survival were screened out: MDM4 gain (HR = 2.71, 95% CI = 1.11-6.64, P < 0.05), APC loss (HR = 7.19, 95% CI = 1.88-27.60, P < 0.005), and FBXW7 loss (HR = 0.16, 95% CI = 0.05-0.46, P < 0.01). There were significant differences in metastasis-free survival rate between the HCC patients with FBXW7 loss and without MDM4 gain or APC loss, those with MDM4 gain and/or APC loss and without FBXW7 loss, and those with other CNA combinations (log-rank test, P < 0.01). Conclusion MDM4 gain, APC loss, and FBXW7 loss are the independent prognostic factors for extrohepatic metastasis-free survival after the operation for HCC and can be used to predict the risk of extrohepatic metastasis after the operation for HCC.

Objective To explore the effect of prophylactic hepatic artery infusion chemotherapy (HAIC) on survival after curative resection in patients with primary pancreatic cancer. Methods A total of 106 patients with pancreatic cancer after pancreatectomy received 2 cycles of HAIC plus 4 cycles of systemic chemotherapy (HAIC) or 6 cycles of sys-temic chemotherapy alone (Control). Both the HAIC and systemic chemotherapy regimen consisted of 5-fluorouracil 1000 mg/m2 on day 1 and Gemcitabine 800 mg/m2 on day 1 and 8. The treatment was started on an average of 3 weeks after surgery and repeated every 4 weeks. The disease-free survival , overall survival and liver metastases-free survival were compared. Results Significant differences were found in 3-year overall survival (HAIC, 23.08 %; Control, 14.81%;P=0.0473) and liver metastases-free survival (HAIC, 80.77%;Control, 55.56%;P=0.0014). There was no significant difference in adverse effects between two groups. Conclusion HAIC effectively and safely prevented liver metastases and improved the prognosis of patients with pancreatic cancer after pancreatectomy.

Objective To evaluate the effects of preoperative regional intra-arterial infusion chemotherapy for patients with advanced gastric cancer (AGC). Methods A total of 82 patients with clinical stage Ⅲ,Ⅳ gastric cancer received two cycles of neoadjuvant regional intra-arterial infusion chemotherapy (arterial infusion group, n=42) or neoadjuvant systemic chemotherapy (systemic chemotherapy group, n=40). The operation was administrated in 10 to 15 days before chemotherapy. All patients received 6 course of systemic chemotherapy after surgery. Chemotherapy toxicity and sur-vival rate were retrospectively analyzed. Results No significant difference was found in chemotherapy toxicity between two groups. The median survival period was 25.3 months in arterial infusion group and 19.1 months in systemic chemotherapy group. 3-year survival rate was 36.4% in arterial infusion group and 21.0% in systemic chemotherapy group respectively, there were significant differences (P<0.05). Conclusion Preoperative regional intra-arterial infusion chemotherapy is well tolerated in advanced gastric cancer patients and could improve short-term survival.