Biology subjects
Publications and source records attributed to Wang, K. Y..
We present Cepo, a method to generate cell-type-specific gene statistics of differentially stable genes from single-cell RNA-sequencing (scRNA-seq) data to define cell identity. Cepo outperforms current methods in assigning cell identity and enhances several cell identification applications such as cell-type characterisation, spatial mapping of single cells, and lineage inference of single cells.
There is no consensus methodology that can account for the variation in omics signatures when they are acquired across different platforms and times. This poses a significant barrier to the implementation of valuable biomarkers into clinical practice. We present a novel procedure (Cross-Platform Omics Prediction) that accounts for these variations and demonstrate its utility in three risk models for different diseases that is suitable for prospective and multi-centre clinical implementation.
Mechanisms to coordinately regulate energy expenditure and glucose uptake into muscle and fat cells are not well described. Insulin stimulates glucose uptake in part by causing site-specific endoproteolytic cleavage of TUG, which mobilizes GLUT4 glucose transporters to the cell surface. Here, we show that the TUG C-terminal cleavage product enters the nucleus, binds the transcriptional regulators PGC-1 and PPAR{gamma}, and increases oxidative metabolism and thermogenic protein expression. Muscle-specific genetic manipulation of this pathway impacts whole-body energy expenditure, independent of glucose uptake. The PPAR{gamma}2 Pro12Ala polymorphism, which reduces diabetes risk, enhances TUG binding. The TUG cleavage product stabilizes PGC-1 and is itself susceptible to an Ate1 arginyltransferase -dependent degradation mechanism; binding of the TUG product confers Ate1-dependent stability upon PGC-1. We conclude that TUG cleavage coordinates energy expenditure with glucose uptake, that this pathway may contribute to the thermic effect of food, and that its attenuation may be important in obesity.
Motivation: Gene annotation and pathway databases such as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes are important tools in Gene Set Test (GST) that describe gene biological functions and associated pathways. GST aims to establish an association relationship between a gene set of interest and an annotation. Importantly, GST tests for over-representation of genes in an annotation term. One implicit assumption of GST is that the gene expression platform captures the complete or a very large proportion of the genome. However, this assumption is neither satisfied for the increasingly popular boutique array nor the custom designed gene expression profiling platform. Specifically, conventional GST is no longer appropriate due to the gene set selection bias induced during the construction of these platforms.\n\nResults: We propose bcGST, a bias-corrected Gene Set Test by introducing bias correction terms in the contingency table needed for calculating the Fishers Exact Test (FET). The adjustment method works by estimating the proportion of genes captured on the array with respect to the genome in order to assist filtration of annotation terms that would otherwise be falsely included or excluded. We illustrate the practicality of bcGST and its stability through multiple differential gene expression analyses in melanoma and TCGA cancer studies.\n\nAvailability: The bcGST method is made available as a Shiny web application at http://shiny.maths.usyd.edu.au/bcGST/\n\nContact: kevin.wang@sydney.edu.au