特色分析 – 主要针对医院及高校的科研团队，从实验设计、样本收集、测序标准分析、个性化分析到结果解读等科研过程提供全方位或是某一过程的服务。
基因组分析 – 根据测序结果，比对参考基因组，检测样本基因组的单核苷酸多样性变异，插入缺失变异，拷贝数变异及结构变异，并对无参考基因组的物种构建对应参
转录组分析 – 根据测序结果比对参考基因组，整理转录本及基因水平表达量，并预测新转录及基因融合结果。
对特定组织或细胞在特定状态下转录出的所有转录本的总和，包括mRNA和所有的non-coding RNA，通过构建small RNA文库和去rRNA的链特异性文库，分析mRNA和non-coding RNA 的表达和调控关系。
Molecular Phylogenesis and Spatiotemporal Spread of SARS-CoV-2 in Southeast Asia
Background: The ongoing coronavirus disease 2019 (COVID-19) pandemic has posed an unprecedented challenge to public health in Southeast Asia, a tropical region with limited resources. This study aimed to investigate the evolutionary dynamics and spatiotemporal patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the region.
Materials and Methods: A total of 1491 complete SARS-CoV-2 genome sequences from 10 Southeast Asian countries were downloaded from the Global Initiative on Sharing Avian Influenza Data (GISAID) database on November 17, 2020. The evolutionary relationships were assessed using maximum likelihood (ML) and time-scaled Bayesian phylogenetic analyses, and the phylogenetic clustering was tested using principal component analysis (PCA). The spatial patterns of SARS-CoV-2 spread within Southeast Asia were inferred using the Bayesian stochastic search variable selection (BSSVS) model. The effective population size (Ne) trajectory was inferred using the Bayesian Skygrid model.
Results: Four major clades (including one potentially endemic) were identified based on the maximum clade credibility (MCC) tree. Similar clustering was yielded by PCA; the first three PCs explained 46.9% of the total genomic variations among the samples. The time to the most recent common ancestor (tMRCA) and the evolutionary rate of SARS-CoV-2 circulating in Southeast Asia were estimated to be November 28, 2019 (September 7, 2019 to January 4, 2020) and 1.446 × 10−3 (1.292 × 10−3 to 1.613 × 10−3) substitutions per site per year, respectively. Singapore and Thailand were the two most probable root positions, with posterior probabilities of 0.549 and 0.413, respectively. There were high-support transmission links (Bayes factors exceeding 1,000) in Singapore, Malaysia, and Indonesia; Malaysia involved the highest number (7) of inferred transmission links within the region. A twice-accelerated viral population expansion, followed by a temporary setback, was inferred during the early stages of the pandemic in Southeast Asia.
Conclusions: With available genomic data, we illustrate the phylogeography and phylodynamics of SARS-CoV-2 circulating in Southeast Asia. Continuous genomic surveillance and enhanced strategic collaboration should be listed as priorities to curb the pandemic, especially for regional communities dominated by developing countries.
H NMR and UHPLC/Q-Orbitrap-MS-Based Metabolomics Combined with 16S rRNA Gut Microbiota Analysis Revealed the Potential Regulation Mechanism of Nuciferine in Hyperuricemia Rats
Hyperuricemia seriously jeopardizes human health by increasing the risk of several diseases, such as gout and stroke. Nuciferine is able to alleviate hyperuricemia significantly. However, the underlying metabolic regulation mechanism remains unknown. To understand the metabolic effects of nuciferine on hyperuricemia by establishing a rat model of rapid hyperuricemia, 1H NMR and liquid chromatography-mass spectrometry were used to conduct nontargeted metabolomics studies. A total of 21 metabolites were authenticated in plasma and urine to be closely related with hyperuricemia, which were mainly correlated to the six metabolic pathways. Moreover, 16S rRNA analysis indicated that diversified intestinal microorganisms are closely related to changes in differential metabolites, especially bacteria from Firmicutes and Bacteroidetes. We propose that indoxyl sulfate and N-acetylglutamate in urine may be the potential biomarkers besides uric acid for early diagnosis and prevention of hyperuricemia. Gut microbiological analysis found that changes in the gut microbiota are closely related to these metabolites.
A database for risk assessment and comparative genomic analysis of foodborne Vibrio parahaemolyticus in China
Vibrio parahaemolyticus is a major foodborne pathogen worldwide. The increasing number of cases of V. parahaemolyticus infections in China indicates an urgent need to evaluate the prevalence and genetic diversity of this pathogenic bacterium. In this paper, we introduce the Foodborne Vibrio parahaemolyticus genome database (FVPGD), the first scientific database of foodborne V. parahaemolyticus distribution and genomic data in China, based on our previous investigations of V. parahaemolyticus contamination in different kinds of food samples across China from 2011 to 2016. The dataset includes records of 2,499 food samples and 643 V. parahaemolyticus strains from supermarkets and marketplaces distributed over 39 cities in China; 268 whole-genome sequences have been deposited in this database. A spatial view on the risk situations of V. parahaemolyticus contamination in different food types is provided. Additionally, the database provides a functional interface of sequence BLAST, core genome multilocus sequence typing, and phylogenetic analysis. The database will become a powerful tool for risk assessment and outbreak investigations of foodborne pathogens in China.
Different Exosomal microRNA Profile in Aquaporin-4 Antibody Positive Neuromyelitis Optica Spectrum Disorders
Neuromyelitis optica spectrum disorders (NMOSD) and multiple sclerosis (MS) are inflammatory demyelinating diseases of the central nervous system. Exosomal microRNAs (miRNAs) are emerging biomarkers for demyelinating diseases. In this study, 52 aquaporin-4 antibody serum-positive NMOSD patients, 18 relapsing-remitting multiple sclerosis (RRMS) patients and 17 healthy controls (HCs) were included for the next-generation sequencing (NGS). To validate the NGS results, the valuable miRNAs were selected for validation by real-time quantitative polymerase chain reaction in another cohort of patients, comprising 31 NMOSD patients and 14 HCs. In addition, these miRNAs were also validated in a longitudinal study. NGS data revealed the exosomal miRNAs profile in NMOSD patients was different from HCs. Among those potential exosomal miRNAs which can distinguish NMOSD status, hsa-miR-122-3p and hsa-miR-200a-5p were the most abundant miRNAs. In addition, hsa-miR-122-3p and hsa-miR-200a-5p were significantly upregulated in the serum exosome of relapsing NMOSD compared with that in remitting NMOSD. Hsa-miR-122-3p and hsa-miR-200a-5p had positive correlations with disease severity in NMOSD patients. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the MAPK, Wnt and Ras signaling pathways were enriched. Further biological function analysis demonstrated that these two miRNAs might be involved in the immunoregulation of NMOSD pathogenesis. Our results indicated that miRNAs delivered by exosomes could be applied as potential biomarkers for NMOSD.
Myelin oligodendrocyte glycoprotein-associated disorders are associated with HLA subtypes in a Chinese paediatric-onset cohort
Objective: Myelin oligodendrocyte glycoprotein-associated disorders (MOGADs) are a rare new neurological autoimmune disease with unclear pathogenesis. Since a linkage of the disease to the human leucocyte antigen (HLA) has not been shown, we here investigated whether MOGAD is associated with the HLA locus.
Methods: HLA genotypes of 95 patients with MOGADs, assessed between 2016 and 2018 from three academic centres, were compared with 481 healthy Chinese Han individuals. Patients with MOGADs included 51 paediatric-onset and 44 adult-onset cases. All patients were seropositive for IgG targeting the myelin oligodendrocyte glycoprotein (MOG).
Results: Paediatric-onset MOGAD was associated with the DQB1*05:02–DRB1*16:02 alleles (OR=2.43; OR=3.28) or haplotype (OR=2.84) of HLA class II genes. The prevalence of these genotypes in patients with paediatric-onset MOGAD was significantly higher than healthy controls (padj=0.0154; padj=0.0221; padj=0.0331). By contrast, adult-onset MOGAD was not associated with any HLA genotype. Clinically, patients with the DQB1*05:02–DRB1*16:02 haplotype exhibited significantly higher expanded disability status scale scores at onset (p=0.004) and were more likely to undergo a disease relapse (p=0.030). HLA–peptide binding prediction algorithms and computational docking analysis provided supporting evidence for the close relationship between the MOG peptide subunit and DQB1*05:02 allele. In vitro results indicated that site-specific mutations of the predicted target sequence reduced the antigen–antibody binding, especially in the paediatric-onset group with DQB1*05:02 allele.
Conclusions: This study demonstrates a possible association between specific HLA class II alleles and paediatric-onset MOGAD, providing evidence for the conjecture that different aetiology and pathogenesis likely underlie paediatric-onset and adult-onset cases of MOGAD.
Whole-exome sequencing reveals the major genetic factors contributing to neuromyelitis optica spectrum disorder in Chinese patients with aquaporin 4-IgG seropositivity
Background and objective: Neuromyelitis optica spectrum disorder (NMOSD) is an autoimmune disease. Although genetic factors are involved in its pathogenesis, limited evidence is available in this area. The aim of the present study was to identify the major genetic factors contributing to NMOSD in Chinese patients with aquaporin 4 (AQP4)-IgG seropositivity.
Methods: Whole-exome sequencing (WES) was performed on 228 Chinese NMOSD patients seropositive for AQP4-IgG and 1400 healthy controls in Guangzhou, South China. Human leukocyte antigen (HLA) sequencing was also utilized. Genotype model and haplotype, gene burden, and enrichment analyses were conducted.
Results: A significant region of the HLA composition is on chromosome 6, and great variation was observed in DQB1, DQA2 and DQA1. HLA sequencing confirmed that the most significant allele was HLA-DQB1* 05:02 ( p < 0.01, odds ratio [OR] 3.73). The genotype model analysis revealed that HLA-DQB1* 05:02 was significantly associated with NMOSD in the additive effect model and dominant effect model (p < 0.05). The proportion of haplotype “HLA-DQB1* 05:02-DRB1* 15:01” was significantly greater in the NMOSD patients than the controls, at 8.42% and 1.23%, respectively (p < 0.001, OR 7.39). The gene burden analysis demonstrated that loss-of-function mutations in NOP16 were more common in the NMOSD patients (11.84%) than the controls (5.71%; p < 0.001, OR 2.22). The IgG1-G390R variant was significantly more common in NMOSD, and the rate of the T allele was 0.605 in patients and 0.345 in the controls (p < 0.01, OR 2.92). The enrichment analysis indicated that most of the genetic factors were mainly correlated with nervous and immune processes.
Conclusions: Human leukocyte antigen is highly correlated with NMOSD. NOP16 and IgG1-G390R play important roles in disease susceptibility.