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Yang Yang

Publications and source records attributed to Yang Yang.

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Recurrently deregulated lncRNAs associated with HCC tumorigenesis and metastasis revealed by genomic, epigenomic and transcriptomic profiling in paired primary tumor and PVTT samples

Hepatocellular carcinoma (HCC) are highly potent to invade the portal venous system and subsequently develop into the portal vein tumor thrombosis (PVTT). PVTT could induce intrahepatic metastasis, which is closely associated with poor prognosis. A comprehensive systematic characterization of long noncoding RNAs (lncRNAs) associated with HCC metastasis has not been reported. Here, we first assayed 60 clinical samples (matched primary tumor, adjacent normal tissue, and PVTT) from 20 HCC patients using total RNA sequencing. We identified and characterized 8,603 novel lncRNAs from 9.6 billion sequenced reads, indicating specific expression of these lncRNAs in our samples. On the other hand, the expression patterns of 3,212 known and novel recurrently deregulated lncRNAs (in >=20% of our patients) were well correlated with clinical data in a TCGA cohort and published liver cancer data. Some lncRNAs (e.g., RP11-166D19.1/MIR100HG) were shown to be useful as putative biomarkers for prognosis and metastasis. Moreover, matched array data from 60 samples showed that copy number variations (CNVs) and alterations in DNA methylation contributed to the observed recurrent deregulation of 716 lncRNAs. Subsequently, using a coding-noncoding co-expression network, we found that many recurrently deregulated lncRNAs were enriched in clusters of genes related to cell adhesion, immune response, and metabolic processes. Candidate lncRNAs related to metastasis, such as HAND2-AS1, were further validated using RNAi-based loss-of-function assays. The results of our integrative analysis provide a valuable resource regarding functional lncRNAs and novel biomarkers associated with HCC tumorigenesis and metastasis.

Genomics

The Epidemiology and Transmissibility of Zika Virus in Girardot and San Andres Island, Colombia

BackgroundZika virus (ZIKV) is an arbovirus in the same genus as dengue virus and yellow fever virus. ZIKV transmission was first detected in Colombia in September 2015. The virus has spread rapidly across the country in areas infested with the vector Aedes aegypti. As of March 2016, Colombia has reported over 50,000 cases of Zika virus disease (ZVD).\n\nMethodsWe analyzed surveillance data of ZVD cases reported to the local health authorities of San Andres, Colombia, and Girardot, Colombia, between September 2015 and January 2016. Standardized case definitions used in both areas were determined by the Ministry of Health and Colombian National Institute of Health at the beginning of the ZIKV epidemic. ZVD was laboratory-confirmed by a finding of Zika virus RNA in the serum of acute cases. We report epidemiological summaries of the two outbreaks. We also use daily incidence data to estimate the basic reproductive number R0 in each population.\n\nFindingsWe identified 928 and 1,936 laboratory or clinically confirmed cases in San Andres and Girardot, respectively. The overall attack rate for reported ZVD detected by healthcare local surveillance was 12{middle dot}13 cases per 1,000 residents of San Andres and 18{middle dot}43 cases per 1,000 residents of Girardot. Attack rates were significantly higher in females in both municipalities. Cases occurred in all age groups but the most affected group was 20 to 49 year olds. The estimated R0 for the Zika outbreak in San Andres was 1{middle dot}41 (95% CI 1{middle dot}15 to 1{middle dot}74), and in Girardot was 4{middle dot}61 (95% CI 4{middle dot}11 to 5{middle dot}16).\n\nInterpretationTransmission of ZIKV is ongoing and spreading throughout the Americas rapidly. The observed rapid spread is supported by the relatively high basic reproductive numbers calculated from these two outbreaks in Colombia.\n\nFundingThis work was supported by National Institutes of Health (NIH) U54 GM111274, NIH R37 AI032042 and the Colombian Department of Science and Technology (Fulbright-Colciencias scholarship to D.P.R). The funding source had no role in the preparation of this manuscript or in the decision to publish this study.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSThe ongoing outbreak of Zika virus disease in the Americas is the largest ever recorded. Since its first detection in April 2015 in Brazil, around 500,000 cases have been estimated, and the virus is spreading rapidly in the Americas region. There are many unanswered questions about the transmissibility and pathogenicity of the virus. Limited data are available from recent outbreaks occurring in islands in the Pacific, and little epidemiological data is available on the current outbreak.\n\nWe searched PubMed on March 12, 2016, for epidemiological reports on Zika virus outbreaks using the search terms \"Zika\" AND \"Basic reproductive number\". We applied no date or language restrictions. Our search identified one previous paper assessing the basic reproductive number, R0 of Zika virus in Yap Island, Federal State of Micronesia and in French Polynesia, but no papers estimating R0 using data from the Latin American Zika outbreak. Because of the sparsity of the data, we could not do a detailed systematic review at this point in time.\n\nAdded value of this studyWe report detailed epidemiological data on outbreaks in San Andres and Girardot, Colombia. Because such reports are currently unavailable, we provide early information on age and gender effects and the functioning of local and national surveillance in the second-most affected country in this epidemic. We provide early estimates of R0. Our results can be used by mathematical modelers to understand the future impact of the disease and potential spread.\n\nImplications of all the available evidenceWe report attack rates similar to those reported in the Yap Island outbreak. We find that Zika impacts individuals of all ages, though the most affected age group is 20 to 49 years of age. The surveillance system detected more cases among women in both areas, though this finding may be attributable to reporting bias. Our estimates of R0 imply that Zika has the capacity for widespread transmission in areas with the vector.

Epidemiology

Comprehensive mapping of mammalian transcriptomes identifies conserved genes associated with different cell differentiation states

Cell identity (or cell state) is established via gene expression programs, represented by \"associated genes\" with dynamic expression across cell identities. Here we integrate RNA-seq data from 40 tissues and cell types from human, chimpanzee, bonobo, and mouse to investigate the conservation and differentiation of cell states. We employ a statistical tool, \"Transcriptome Overlap Measure\" (TROM) to first identify cell-state-associated genes, both protein-coding and non-coding. Next, we use TROM to comprehensively map the cell states within each species and also between species based on the cell-state-associated genes. The within-species mapping measures which cell states are similar to each other, allowing us to construct a human cell differentiation tree that recovers both known and novel lineage relationships between cell states. Moreover, the between-species mapping summarizes the conservation of cell states across the four species. Based on these results, we identify conserved associated genes for different cell states and annotate their biological functions. Interestingly, we find that neural and testis tissues exhibit distinct evolutionary signatures in which neural tissues are much less enriched in conserved associated genes than testis. In addition, our mapping demonstrate that besides protein-coding genes, long non-coding RNAs serve well as associated genes to indicate cell states. We further infer the biological functions of those non-coding associated genes based on their co-expressed protein-coding associated genes. Overall, we provide a catalog of conserved and species-specific associated genes that identifies candidates for downstream experimental studies of the roles of these candidates in controlling cell identity.\n\nHighlightsO_LIComprehensive transcriptome mapping of cell states across four mammalian species\nC_LIO_LIBoth protein-coding genes and long non-coding RNAs serve as good markers of cell identity\nC_LIO_LIDistinct evolutionary signatures of neural and testis tissues\nC_LIO_LIA catalog of conserved associated protein-coding genes and lncRNAs in different mammalian tissues and cell types\nC_LI

Systems Biology