ORCID Profile
0000-0003-2509-9599
Current Organisation
Barts Cancer Institute
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Publisher: MDPI AG
Date: 19-01-2021
Abstract: Next-generation sequencing of primary tumors is now standard for transcriptomic studies, but microarray-based data still constitute the majority of available information on other clinically valuable s les, including archive material. Using prostate cancer (PC) as a model, we developed a robust analytical framework to integrate data across different technical platforms and disease subtypes to connect distinct disease stages and reveal potentially relevant genes not identifiable from single studies alone. We reconstructed the molecular profile of PC to yield the first comprehensive insight into its development, by tracking changes in mRNA levels from normal prostate to high-grade prostatic intraepithelial neoplasia, and metastatic disease. A total of nine previously unreported stage-specific candidate genes with prognostic significance were also found. Here, we integrate gene expression data from disparate s le types, disease stages and technical platforms into one coherent whole, to give a global view of the expression changes associated with the development and progression of PC from normal tissue through to metastatic disease. Summary and in idual data are available online at the Prostate Integrative Expression Database (PIXdb), a user-friendly interface designed for clinicians and laboratory researchers to facilitate translational research.
Publisher: Springer Science and Business Media LLC
Date: 19-04-2018
Publisher: Springer Science and Business Media LLC
Date: 29-06-2012
DOI: 10.1007/S00122-012-1920-9
Abstract: This paper develops a simple diagnostic for the investigation of uncertainty within genetic linkage maps using a Bayesian procedure. The method requires only the genotyping data and the proposed genetic map, and calculates the posterior probability for the possible orders of any set of three markers, accounting for the presence of genotyping error (mistyping) and for missing genotype data. The method uses a Bayesian approach to give insight into conflicts between the order in the proposed map and the genotype scores. The method can also be used to assess the accuracy of a genetic map at different genomic scales and to assess alternative potential marker orders. Simulation and two case studies were used to illustrate the method. In the first case study, the diagnostic revealed conflicts in map ordering for short inter-marker distances that were resolved at a distance of 8-12 cM, except for a set of markers at the end of the linkage group. In the second case study, the ordering did not resolve as distances increase, which could be attributed to regions of the map where many in iduals were untyped.
Publisher: Springer Science and Business Media LLC
Date: 28-08-2011
DOI: 10.1038/NG.919
Abstract: We report the annotation and analysis of the draft genome sequence of Brassica rapa accession Chiifu-401-42, a Chinese cabbage. We modeled 41,174 protein coding genes in the B. rapa genome, which has undergone genome triplication. We used Arabidopsis thaliana as an outgroup for investigating the consequences of genome triplication, such as structural and functional evolution. The extent of gene loss (fractionation) among triplicated genome segments varies, with one of the three copies consistently retaining a disproportionately large fraction of the genes expected to have been present in its ancestor. Variation in the number of members of gene families present in the genome may contribute to the remarkable morphological plasticity of Brassica species. The B. rapa genome sequence provides an important resource for studying the evolution of polyploid genomes and underpins the genetic improvement of Brassica oil and vegetable crops.
Publisher: Springer Science and Business Media LLC
Date: 09-02-2011
Abstract: The large number of genetic linkage maps representing Brassica chromosomes constitute a potential platform for studying crop traits and genome evolution within Brassicaceae . However, the alignment of existing maps remains a major challenge. The integration of these genetic maps will enhance genetic resolution, and provide a means to navigate between sequence-tagged loci, and with contiguous genome sequences as these become available. We report the first genome-wide integration of Brassica maps based on an automated pipeline which involved collation of genome-wide genotype data for sequence-tagged markers scored on three extensively used hidiploid Brassica napus (2n = 38) populations. Representative markers were selected from consolidated maps for each population, and skeleton bin maps were generated. The skeleton maps for the three populations were then combined to generate an integrated map for each LG, comparing two different approaches, one encapsulated in JoinMap and the other in MergeMap. The BnaWAIT_01_2010a integrated genetic map was generated using JoinMap, and includes 5,162 genetic markers mapped onto 2,196 loci, with a total genetic length of 1,792 cM. The map density of one locus every 0.82 cM, corresponding to 515 Kbp, increases by at least three-fold the locus and marker density within the original maps. Within the B. napus integrated map we identified 103 conserved collinearity blocks relative to Arabidopsis , including five previously unreported blocks. The BnaWAIT_01_2010a map was used to investigate the integrity and conservation of order proposed for genome sequence scaffolds generated from the constituent A genome of Brassica rapa . Our results provide a comprehensive genetic integration of the B. napus genome from a range of sources, which we anticipate will provide valuable information for rapeseed and Canola research.
Publisher: Oxford University Press (OUP)
Date: 28-04-2011
Abstract: Gene expression is a quantitative trait that can be mapped genetically in structured populations to identify expression quantitative trait loci (eQTL). Genes and regulatory networks underlying complex traits can subsequently be inferred. Using a recently released genome sequence, we have defined cis- and trans-eQTL and their environmental response to low phosphorus (P) availability within a complex plant genome and found hotspots of trans-eQTL within the genome. Interval mapping, using P supply as a covariate, revealed 18,876 eQTL. trans-eQTL hotspots occurred on chromosomes A06 and A01 within Brassica rapa these were enriched with P metabolism-related Gene Ontology terms (A06) as well as chloroplast- and photosynthesis-related terms (A01). We have also attributed heritability components to measures of gene expression across environments, allowing the identification of novel gene expression markers and gene expression changes associated with low P availability. Informative gene expression markers were used to map eQTL and P use efficiency-related QTL. Genes responsive to P supply had large environmental and heritable variance components. Regulatory loci and genes associated with P use efficiency identified through eQTL analysis are potential targets for further characterization and may have potential for crop improvement.
Publisher: Springer Science and Business Media LLC
Date: 14-08-2017
DOI: 10.1038/LEU.2017.255
Publisher: Wiley
Date: 05-2012
DOI: 10.1111/J.1744-7909.2012.01120.X
Abstract: Associating phenotypic traits and quantitative trait loci (QTL) to causative regions of the underlying genome is a key goal in agricultural research. InterStoreDB is a suite of integrated databases designed to assist in this process. The in idual databases are species independent and generic in design, providing access to curated datasets relating to plant populations, phenotypic traits, genetic maps, marker loci and QTL, with links to functional gene annotation and genomic sequence data. Each component database provides access to associated metadata, including data provenance and parameters used in analyses, thus providing users with information to evaluate the relative worth of any associations identified. The databases include CropStoreDB, for management of population, genetic map, QTL and trait measurement data, SeqStoreDB for sequence-related data and AlignStoreDB, which stores sequence alignment information, and allows navigation between genetic and genomic datasets. Genetic maps are visualized and compared using the CMAP tool, and functional annotation from sequenced genomes is provided via an EnsEMBL-based genome browser. This framework facilitates navigation of the multiple biological domains involved in genetics and genomics research in a transparent manner within a single portal. We demonstrate the value of InterStoreDB as a tool for Brassica research. InterStoreDB is available from: www.interstoredb.org.
Publisher: Springer Science and Business Media LLC
Date: 20-05-2016
DOI: 10.1038/LEU.2016.134
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Jun Wang.