1.Seroepidemiology of dengue virus infection among adults in Singapore.
Yik Weng YEW ; Tun YE ; Li Wei ANG ; Lee Ching NG ; Grace YAP ; Lyn JAMES ; Suok Kai CHEW ; Kee Tai GOH
Annals of the Academy of Medicine, Singapore 2009;38(8):667-675
INTRODUCTIONTo determine the seroepidemiology of dengue virus infection in a representative sample of the adult resident population aged 18 years old to 74 years old in Singapore and to estimate the proportion of asymptomatic dengue infection during the 2004 epidemic.
MATERIALS AND METHODSThe study was based on 4152 stored blood samples collected between September and December 2004 from participants aged 18 years old to 74 years old during the 2004 National Health Survey. Sera were tested for IgG and IgM antibodies using a commercial test kit (PanBio Capture/Indirect ELISA).
RESULTSOf the study population, 59.0% and 2.6% tested positive for dengue IgG (past infection) and IgM/high-titre IgG (recent infection), respectively. Only 17.2% of young adults aged 18 years old to 24 years old were dengue IgG positive. Multivariate analyses showed that older age, Indian ethnicity and male gender were significantly associated with past infection, whereas only age was significantly associated with recent dengue infection. Based on the dengue cases notified during the period of survey, it was estimated that for every 23 individuals recently infected with dengue, only 1 was reported to the health authority as a clinical case.
CONCLUSIONThe Singapore population is highly susceptible to dengue epidemics despite its aggressive Aedes prevention and control programme. The finding of a high proportion of unreported cases due to asymptomatic and subclinical infection poses a challenge for dengue control.
Adolescent ; Adult ; Aedes ; Aged ; Animals ; Confidence Intervals ; Cross-Sectional Studies ; Dengue ; epidemiology ; transmission ; Dengue Virus ; Disease Outbreaks ; Female ; Health Surveys ; Humans ; Immunoglobulin G ; Immunoglobulin M ; Logistic Models ; Male ; Middle Aged ; Mosquito Control ; Multivariate Analysis ; Odds Ratio ; Population Surveillance ; Risk Factors ; Seroepidemiologic Studies ; Singapore ; epidemiology ; Young Adult
2.High-quality Arabidopsis thaliana Genome Assembly with Nanopore and HiFi Long Reads
Wang BO ; Yang XIAOFEI ; Jia YANYAN ; Xu YU ; Jia PENG ; Dang NINGXIN ; Wang SONGBO ; Xu TUN ; Zhao XIXI ; Gao SHENGHAN ; Dong QUANBIN ; Ye KAI
Genomics, Proteomics & Bioinformatics 2022;20(1):4-13
Arabidopsis thaliana is an important and long-established model species for plant molec-ular biology,genetics,epigenetics,and genomics.However,the latest version of reference genome still contains a significant number of missing segments.Here,we reported a high-quality and almost complete Col-0 genome assembly with two gaps(named Col-XJTU)by combining the Oxford Nanopore Technologies ultra-long reads,Pacific Biosciences high-fidelity long reads,and Hi-C data.The total genome assembly size is 133,725,193 bp,introducing 14.6 Mb of novel sequences compared to the TAIR1 0.1 reference genome.All five chromosomes of the Col-XJTU assembly are highly accurate with consensus quality(QV)scores>60(ranging from 62 to 68),which are higher than those of the TAIR10.1 reference(ranging from 45 to 52).We completely resolved chro-mosome(Chr)3 and Chr5 in a telomere-to-telomere manner.Chr4 was completely resolved except the nucleolar organizing regions,which comprise long repetitive DNA fragments.The Chr1 cen-tromere(CEN1),reportedly around 9 Mb in length,is particularly challenging to assemble due to the presence of tens of thousands of CEN180 satellite repeats.Using the cutting-edge sequencing data and novel computational approaches,we assembled a 3.8-Mb-long CEN1 and a 3.5-Mb-long CEN2.We also investigated the structure and epigenetics of centromeres.Four clusters of CEN180 monomers were detected,and the centromere-specific histone H3-like protein(CENH3)exhibited a strong preference for CEN 180 Cluster 3.Moreover,we observed hypomethylation patterns in CENH3-enriched regions.We believe that this high-quality genome assembly,Col-XJTU,would serve as a valuable reference to better understand the global pattern of centromeric polymorphisms,as well as the genetic and epigenetic features in plants.
3.Mako:A Graph-based Pattern Growth Approach to Detect Complex Structural Variants
Lin JIADONG ; Yang XIAOFEI ; Kosters WALTER ; Xu TUN ; Jia YANYAN ; Wang SONGBO ; Zhu QIHUI ; Ryan MALLORY ; Guo LI ; Zhang CHENGSHENG ; The Human Genome Structural Variation Consortium ; Lee CHARLES ; E.Devine SCOTT ; E.Eichler EVAN ; Ye KAI
Genomics, Proteomics & Bioinformatics 2022;20(1):205-218
Complex structural variants(CSVs)are genomic alterations that have more than two breakpoints and are considered as the simultaneous occurrence of simple structural variants.How-ever,detecting the compounded mutational signals of CSVs is challenging through a commonly used model-match strategy.As a result,there has been limited progress for CSV discovery com-pared with simple structural variants.Here,we systematically analyzed the multi-breakpoint con-nection feature of CSVs,and proposed Mako,utilizing a bottom-up guided model-free strategy,to detect CSVs from paired-end short-read sequencing.Specifically,we implemented a graph-based pattern growth approach,where the graph depicts potential breakpoint connections,and pattern growth enables CSV detection without pre-defined models.Comprehensive evaluations on both simulated and real datasets revealed that Mako outperformed other algorithms.Notably,validation rates of CSVs on real data based on experimental and computational validations as well as manual inspections are around 70%,where the medians of experimental and computational breakpoint shift are 13 bp and 26 bp,respectively.Moreover,the Mako CSV subgraph effectively characterized the breakpoint connections of a CSV event and uncovered a total of 15 CSV types,including two novel types of adjacent segment swap and tandem dispersed duplication.Further analysis of these CSVs also revealed the impact of sequence homology on the formation of CSVs.Mako is publicly available at https://github.com/xjtu-omics/Mako.