We extended our previous GWAS for psoriasis with a a multistage replication study including 8,312 cases and 12,919 controls from China as well as 3,293 cases, 4,188 controls from Germany and the USA, and 254 nuclear families from the USA. We identified 6 new susceptibility loci associated to psoriasis in Chinese, containing candidate genes ERAP1, PTTG1, CSMD1, GJB2, SERPINB8, ZNF816A (PCombined<5×10−8) and replicated one locus 5q33.1 (TNIP1/ANXA6) previously reported (PCombined=3.8×10−21) in European studies. Two of these loci showed evidence for association evidence in the German study, at ZNF816A and GJB2 with P=3.6×10−3 and P=7.9×10−3, respectively. ERAP1 and ZNF816A were preferentially associated with Type I (early onset) psoriasis in Chinese Han population (test for heterogeneity P=6.5×10−3 and P=1.5×10−3, respectively). Comparisons with previous GWAS of psoriasis highlight the heterogeneity of disease susceptibility between Chinese and European populations. Our study identifies new genetic susceptibility factors and suggests new biological pathways in psoriasis.

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We conducted a genome-wide association study of generalized vitiligo in the Chinese Han population by genotyping 1,117 cases and 1,429 controls. The 34 most promising SNPs were carried forward for replication in samples from individuals of the Chinese Han (5,910 cases and 9,916 controls) and Chinese Uygur (713 cases and 824 controls) populations. We identified two independent association signals within the major histocompatibility complex (MHC) region (rs11966200, Pcombined=1.48x10(-48), OR=1.90; rs9468925, Pcombined=2.21x10(-33), OR=0.74). Further analyses suggested that the strong association at rs11966200 might reflect the reported association of the HLA-A*3001, HLA-B*1302, HLA-C*0602 and HLA-DRB1*0701 alleles and that the association at rs9468925 might represent a previously unknown HLA susceptibility allele. We also identified one previously undescribed risk locus at 6q27 (rs2236313, Pcombined=9.72x10(-17), OR=1.20), which contains three genes: RNASET2, FGFR1OP and CCR6. Our study provides new insights into the genetic basis of vitiligo.

During investigations into an outbreak of egg production decline, retarded growth, and even death among ducks in Southeast China, a novel Tembusu virus strain named Tembusu virus Fengxian 2010 (FX2010) was isolated. This virus replicated in embryonated chicken eggs and caused embryo death. In cross-neutralization tests, antiserum to the partial E protein of Tembusu virus Mm1775 strain neutralized FX2010, whereas antiserum to Japanese encephalitis virus did not. FX2010 is an enveloped RNA virus of approximately 45-50 nm in diameter. Sequence analysis of its E and NS5 genes showed that both genes share up to 99.6% nucleotide sequence identity with Baiyangdian virus, and up to 88% nucleotide sequence identity with their counterparts in Tembusu virus. FX2010 was transmitted without mosquito, and caused systemic infection and lesions in experimentally infected ducks. These results indicate that FX2010 and BYD virus are newly emerged Tembusu virus strains that cause an infectious disease in ducks.

The human disease methylation database (DiseaseMeth, http://bioinfo.hrbmu.edu.cn/diseasemeth/) is an interactive database that aims to present the most complete collection and annotation of aberrant DNA methylation in human diseases, especially various cancers. Recently, the high-throughput microarray and sequencing technologies have promoted the production of methylome data that contain comprehensive knowledge of human diseases. In this DiseaseMeth update, we have increased the number of samples from 3610 to 32 701, the number of diseases from 72 to 88 and the disease–gene associations from 216 201 to 679 602. DiseaseMeth version 2.0 provides an expanded comprehensive list of disease–gene associations based on manual curation from experimental studies and computational identification from high-throughput methylome data. Besides the data expansion, we also updated the search engine and visualization tools. In particular, we enhanced the differential analysis tools, which now enable online automated identification of DNA methylation abnormalities in human disease in a case-control or disease–disease manner. To facilitate further mining of the disease methylome, three new web tools were developed for cluster analysis, functional annotation and survival analysis. DiseaseMeth version 2.0 should be a useful resource platform for further understanding the molecular mechanisms of human diseases.

Super-enhancers are large clusters of transcriptional enhancers regarded as having essential roles in driving the expression of genes that control cell identity during development and tumorigenesis. The construction of a genome-wide super-enhancer database is urgently needed to better understand super-enhancer-directed gene expression regulation for a given biology process. Here, we present a specifically designed web-accessible database, Super-Enhancer Archive (SEA, http://sea.edbc.org). SEA focuses on integrating super-enhancers in multiple species and annotating their potential roles in the regulation of cell identity gene expression. The current release of SEA incorporates 83 996 super-enhancers computationally or experimentally identified in 134 cell types/tissues/diseases, including human (75 439, three of which were experimentally identified), mouse (5879, five of which were experimentally identified), Drosophila melanogaster (1774) and Caenorhabditis elegans (904). To facilitate data extraction, SEA supports multiple search options, including species, genome location, gene name, cell type/tissue and super-enhancer name. The response provides detailed (epi)genetic information, incorporating cell type specificity, nearby genes, transcriptional factor binding sites, CRISPR/Cas9 target sites, evolutionary conservation, SNPs, H3K27ac, DNA methylation, gene expression and TF ChIP-seq data. Moreover, analytical tools and a genome browser were developed for users to explore super-enhancers and their roles in defining cell identity and disease processes in depth.

-1 , respectively. The biodeposition rates of 2-yr-old scallops were almost double these values. Sedimentation rates at scallop culture sites averaged 2.46 times that at the reference site. Theoretically, the total water column of the bay could be filtered by the cultured scallops in 12 d, with daily seston removal amounting to 64%. This study indicated that filteringbiodeposition by suspension-cultured scallops could exert long-lasting top-down control on phytoplankton biomass and other suspended material in the Sishili Bay ecosystem. In coastal waters subject to anthropogenic N and P inputs, suspended bivalve aquaculture could be advantageous, not only economically, but also ecologically, by functioning as a biofilter and potentially mitigating eutrophication pressures. Compared with distribution-restricted wild bivalves, suspension-cultured bivalves in deeper coastal bays may be more efficient in processing seston on a basin scale.

Tumour heterogeneity is an obstacle to effective breast cancer diagnosis and therapy. DNA methylation is an important regulator of gene expression, thus characterizing tumour heterogeneity by epigenetic features can be clinically informative. In this study, we explored specific prognosis‐subtypes based on DNA methylation status using 669 breast cancers from the TCGA database. Nine subgroups were distinguished by consensus clustering using 3869 CpGs that significantly influenced survival. The specific DNA methylation patterns were reflected by different races, ages, tumour stages, receptor status, histological types, metastasis status and prognosis. Compared with the PAM50 subtypes, which use gene expression clustering, DNA methylation subtypes were more elaborate and classified the Basal‐like subtype into two different prognosis‐subgroups. Additionally, 1252 CpGs (corresponding to 888 genes) were identified as specific hyper/hypomethylation sites for each specific subgroup. Finally, a prognosis model based on Bayesian network classification was constructed and used to classify the test set into DNA methylation subgroups, which corresponded to the classification results of the train set. These specific classifications by DNA methylation can explain the heterogeneity of previous molecular subgroups in breast cancer and will help in the development of personalized treatments for the new specific subtypes.