Joshua W. K. Ho

Comparative analysis of metazoan chromatin organization

Genome function is dynamically regulated in part by chromatin, which consists of the histones, non-histone proteins and RNA molecules that package DNA. Studies in Caenorhabditis elegans and Drosophila melanogaster have contributed substantially to our understanding of molecular mechanisms of genome function in humans, and have revealed conservation of chromatin components and mechanisms. Nevertheless, the three organisms have markedly different genome sizes, chromosome architecture and gene organization. On human and fly chromosomes, for example, pericentric heterochromatin flanks single centromeres, whereas worm chromosomes have dispersed heterochromatin-like regions enriched in the distal chromosomal ‘arms’, and centromeres distributed along their lengths. To systematically investigate chromatin organization and associated gene regulation across species, we generated and analysed a large collection of genome-wide chromatin data sets from cell lines and developmental stages in worm, fly and human. Here we present over 800 new data sets from our ENCODE and modENCODE consortia, bringing the total to over 1,400. Comparison of combinatorial patterns of histone modifications, nuclear lamina-associated domains, organization of large-scale topological domains, chromatin environment at promoters and enhancers, nucleosome positioning, and DNA replication patterns reveals many conserved features of chromatin organization among the three organisms. We also find notable differences in the composition and locations of repressive chromatin. These data sets and analyses provide a rich resource for comparative and species-specific investigations of chromatin composition, organization and function.

ChIP-chip versus ChIP-seq: Lessons for experimental design and data analysis

BackgroundChromatin immunoprecipitation (ChIP) followed by microarray hybridization (ChIP-chip) or high-throughput sequencing (ChIP-seq) allows genome-wide discovery of protein-DNA interactions such as transcription factor bindings and histone modifications. Previous reports only compared a small number of profiles, and little has been done to compare histone modification profiles generated by the two technologies or to assess the impact of input DNA libraries in ChIP-seq analysis. Here, we performed a systematic analysis of a modENCODE dataset consisting of 31 pairs of ChIP-chip/ChIP-seq profiles of the coactivator CBP, RNA polymerase II (RNA PolII), and six histone modifications across four developmental stages of Drosophila melanogaster.ResultsBoth technologies produce highly reproducible profiles within each platform, ChIP-seq generally produces profiles with a better signal-to-noise ratio, and allows detection of more peaks and narrower peaks. The set of peaks identified by the two technologies can be significantly different, but the extent to which they differ varies depending on the factor and the analysis algorithm. Importantly, we found that there is a significant variation among multiple sequencing profiles of input DNA libraries and that this variation most likely arises from both differences in experimental condition and sequencing depth. We further show that using an inappropriate input DNA profile can impact the average signal profiles around genomic features and peak calling results, highlighting the importance of having high quality input DNA data for normalization in ChIP-seq analysis.ConclusionsOur findings highlight the biases present in each of the platforms, show the variability that can arise from both technology and analysis methods, and emphasize the importance of obtaining high quality and deeply sequenced input DNA libraries for ChIP-seq analysis.

Differential variability analysis of gene expression and its application to human diseases

Motivation: Current microarray analyses focus on identifying sets of genes that are differentially expressed (DE) or differentially coexpressed (DC) in different biological states (e.g. diseased versus non-diseased). We observed that in many human diseases, some genes have a significantincrease or decrease in expression variability (variance). Asthese observed changes in expression variability may be caused by alteration of the underlying expression dynamics, such differential variability (DV) patterns are also biologically interesting. Results: Here we propose a novel analysis for changes in gene expression variability between groups of amples, which we call differential variability analysis. We introduce the concept of differential variability (DV), and present a simple procedure for identifying DV genes from microarray data. Our procedure is evaluated with simulated and real microarray datasets. The effect of data preprocessing methods on identification of DV gene is investigated. The biological significance of DV analysis is demonstrated with four human disease datasets. The relationships among DV, DE and DC genes are investigated. The results suggest that changes in expression variability are associated with changes in coexpression pattern, which imply that DV is not merely stochastic noise, but informative signal. Availability: The R source code for differential variability analysis is available from the contact authors upon request. Contact: joshua@it.usyd.edu.au; mcharleston@it.usyd.edu.au

Lung Stem Cell Self-Renewal Relies on BMI1-Dependent Control of Expression at Imprinted Loci

BMI1 is required for the self-renewal of stem cells in many tissues including the lung epithelial stem cells, Bronchioalveolar Stem Cells (BASCs). Imprinted genes, which exhibit expression from only the maternally or paternally inherited allele, are known to regulate developmental processes, but what their role is in adult cells remains a fundamental question. Many imprinted genes were derepressed in Bmi1 knockout mice, and knockdown of Cdkn1c (p57) and other imprinted genes partially rescued the self-renewal defect of Bmi1 mutant lung cells. Expression of p57 and other imprinted genes was required for lung cell self-renewal in culture and correlated with repair of lung epithelial cell injury in vivo. Our data suggest that BMI1-dependent regulation of expressed alleles at imprinted loci, distinct from imprinting per se, is required for control of lung stem cells. We anticipate that the regulation and function of imprinted genes is crucial for self-renewal in diverse adult tissue-specific stem cells.

An innovative approach for testing bioinformatics programs using metamorphic testing

BackgroundRecent advances in experimental and computational technologies have fueled the development of many sophisticated bioinformatics programs. The correctness of such programs is crucial as incorrectly computed results may lead to wrong biological conclusion or misguide downstream experimentation. Common software testing procedures involve executing the target program with a set of test inputs and then verifying the correctness of the test outputs. However, due to the complexity of many bioinformatics programs, it is often difficult to verify the correctness of the test outputs. Therefore our ability to perform systematic software testing is greatly hindered.ResultsWe propose to use a novel software testing technique, metamorphic testing (MT), to test a range of bioinformatics programs. Instead of requiring a mechanism to verify whether an individual test output is correct, the MT technique verifies whether a pair of test outputs conform to a set of domain specific properties, called metamorphic relations (MRs), thus greatly increases the number and variety of test cases that can be applied. To demonstrate how MT is used in practice, we applied MT to test two open-source bioinformatics programs, namely GNLab and SeqMap. In particular we show that MT is simple to implement, and is effective in detecting faults in a real-life program and some artificially fault-seeded programs. Further, we discuss how MT can be applied to test programs from various domains of bioinformatics.ConclusionThis paper describes the application of a simple, effective and automated technique to systematically test a range of bioinformatics programs. We show how MT can be implemented in practice through two real-life case studies. Since many bioinformatics programs, particularly those for large scale simulation and data analysis, are hard to test systematically, their developers may benefit from using MT as part of the testing strategy. Therefore our work represents a significant step towards software reliability in bioinformatics.

Heart failure-associated changes in RNA splicing of sarcomere genes.

Background—Alternative mRNA splicing is an important mechanism for regulation of gene expression. Altered mRNA splicing occurs in association with several types of cancer, and a small number of disease-associated changes in splicing have been reported in heart disease. However, genome-wide approaches have not been used to study splicing changes in heart disease. We hypothesized that mRNA splicing is different in diseased hearts compared with control hearts. Methods and Results—We used the Affymetrix Exon array to globally evaluate mRNA splicing in left ventricular myocardial RNA from controls (n=15) and patients with ischemic cardiomyopathy (n=15). We observed a broad and significant decrease in mRNA splicing efficiency in heart failure, which affected some introns to a greater extent than others. The profile of mRNA splicing separately clustered ischemic cardiomyopathy and control samples, suggesting distinct changes in mRNA splicing between groups. Reverse transcription–polymerase chain reaction validated 9 previously unreported alternative splicing events. Furthermore, we demonstrated that splicing of 4 key sarcomere genes, cardiac troponin T (TNNT2), cardiac troponin I (TNNI3), myosin heavy chain 7 (MYH7), and filamin C,gamma (FLNC), was significantly altered in ischemic cardiomyopathy and in dilated cardiomyopathy and aortic stenosis. In aortic stenosis samples, these differences preceded the onset of heart failure. Remarkably, the ratio of minor to major splice variants of TNNT2, MYH7, and FLNC classified independent test samples as control or disease with >98% accuracy. Conclusions—Our data indicate that mRNA splicing is broadly altered in human heart disease and that patterns of aberrant RNA splicing accurately assign samples to control or disease classes.

A Wnt-Bmp Feedback Circuit Controls Intertissue Signaling Dynamics in Tooth Organogenesis

Computational and genetic analyses reveal a key circuit involving Wnt and Bmp in developing teeth in mice. A Toothsome Circuit Interactions between two different types of tissue, epithelium and mesenchyme, play important roles in development and cancer. Tooth development is a system for studying epithelial-mesenchymal interactions that is amenable to experimental manipulation. O’Connell et al. performed gene expression profiling of developing molar dental tissues in mice and computational analyses to construct a gene regulatory network that identified a key feedback circuit mediated by diffusible signaling molecules of the Wnt and Bmp families. This circuit controls the production of signaling molecules in other pathways and is self-sustaining. The authors validated their circuit in mice with mutations expected to disrupt the Wnt-Bmp signaling pathways. Similar feedback circuits may also operate in epithelial-mesenchymal interactions in other developing organs or in tumors. Many vertebrate organs form through the sequential and reciprocal exchange of signaling molecules between juxtaposed epithelial and mesenchymal tissues. We undertook a systems biology approach that combined the generation and analysis of large-scale spatiotemporal gene expression data with mouse genetic experiments to gain insight into the mechanisms that control epithelial-mesenchymal signaling interactions in the developing mouse molar tooth. We showed that the shift in instructive signaling potential from dental epithelium to dental mesenchyme was accompanied by temporally coordinated genome-wide changes in gene expression in both compartments. To identify the mechanism responsible, we developed a probabilistic technique that integrates regulatory evidence from gene expression data and from the literature to reconstruct a gene regulatory network for the epithelial and mesenchymal compartments in early tooth development. By integrating these epithelial and mesenchymal gene regulatory networks through the action of diffusible extracellular signaling molecules, we identified a key epithelial-mesenchymal intertissue Wnt-Bmp (bone morphogenetic protein) feedback circuit. We then validated this circuit in vivo with compound genetic mutations in mice that disrupted this circuit. Moreover, mathematical modeling demonstrated that the structure of the circuit accounted for the observed reciprocal signaling dynamics. Thus, we have identified a critical signaling circuit that controls the coordinated genome-wide expression changes and reciprocal signaling molecule dynamics that occur in interacting epithelial and mesenchymal compartments during organogenesis.

iSyTE: Integrated Systems Tool for Eye Gene Discovery

PURPOSE To facilitate the identification of genes associated with cataract and other ocular defects, the authors developed and validated a computational tool termed iSyTE (integrated Systems Tool for Eye gene discovery; http://bioinformatics.udel.edu/Research/iSyTE). iSyTE uses a mouse embryonic lens gene expression data set as a bioinformatics filter to select candidate genes from human or mouse genomic regions implicated in disease and to prioritize them for further mutational and functional analyses. METHODS Microarray gene expression profiles were obtained for microdissected embryonic mouse lens at three key developmental time points in the transition from the embryonic day (E)10.5 stage of lens placode invagination to E12.5 lens primary fiber cell differentiation. Differentially regulated genes were identified by in silico comparison of lens gene expression profiles with those of whole embryo body (WB) lacking ocular tissue. RESULTS Gene set analysis demonstrated that this strategy effectively removes highly expressed but nonspecific housekeeping genes from lens tissue expression profiles, allowing identification of less highly expressed lens disease-associated genes. Among 24 previously mapped human genomic intervals containing genes associated with isolated congenital cataract, the mutant gene is ranked within the top two iSyTE-selected candidates in approximately 88% of cases. Finally, in situ hybridization confirmed lens expression of several novel iSyTE-identified genes. CONCLUSIONS iSyTE is a publicly available Web resource that can be used to prioritize candidate genes within mapped genomic intervals associated with congenital cataract for further investigation. Extension of this approach to other ocular tissue components will facilitate eye disease gene discovery.

GEOMI: GEOmetry for maximum insight

This paper describes the GEOMI system, a visual analysis tool for the visualisation and analysis of large and complex networks. GEOMI provides a collection of network analysis methods, graph layout algorithms and several graph navigation and interaction methods. GEOMI is part of a new generation of visual analysis tools combining graph visualisation techniques with network analysis methods. GEOMI is available from http://www.cs.usyd.edu.au/~visual/valacon/geomi/.

CIDR: Ultrafast and accurate clustering through imputation for single-cell RNA-seq data

Most existing dimensionality reduction and clustering packages for single-cell RNA-seq (scRNA-seq) data deal with dropouts by heavy modeling and computational machinery. Here, we introduce CIDR (Clustering through Imputation and Dimensionality Reduction), an ultrafast algorithm that uses a novel yet very simple implicit imputation approach to alleviate the impact of dropouts in scRNA-seq data in a principled manner. Using a range of simulated and real data, we show that CIDR improves the standard principal component analysis and outperforms the state-of-the-art methods, namely t-SNE, ZIFA, and RaceID, in terms of clustering accuracy. CIDR typically completes within seconds when processing a data set of hundreds of cells and minutes for a data set of thousands of cells. CIDR can be downloaded at https://github.com/VCCRI/CIDR.