ORCID Profile
0000-0002-1711-7454
Current Organisation
Walter and Eliza Hall Institute of Medical Research
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Publisher: American Society of Hematology
Date: 10-10-2013
DOI: 10.1182/BLOOD-2013-02-484055
Abstract: PRC1 and PRC2 have opposing activity in Eμ-myc lymphoma. Inhibition of PRC2 leads to increased self-renewal in B-cell progenitors.
Publisher: F1000 Research Ltd
Date: 08-06-2016
DOI: 10.12688/F1000RESEARCH.8839.1
Abstract: Methylation in the human genome is known to be associated with development and disease. The Illumina Infinium methylation arrays are by far the most common way to interrogate methylation across the human genome. This paper provides a Bioconductor workflow using multiple packages for the analysis of methylation array data. Specifically, we demonstrate the steps involved in a typical differential methylation analysis pipeline including: quality control, filtering, normalization, data exploration and statistical testing for probe-wise differential methylation. We further outline other analyses such as differential methylation of regions, differential variability analysis, estimating cell type composition and gene ontology testing. Finally, we provide some ex les of how to visualise methylation array data.
Publisher: F1000 Research Ltd
Date: 26-07-2016
DOI: 10.12688/F1000RESEARCH.8839.2
Abstract: Methylation in the human genome is known to be associated with development and disease. The Illumina Infinium methylation arrays are by far the most common way to interrogate methylation across the human genome. This paper provides a Bioconductor workflow using multiple packages for the analysis of methylation array data. Specifically, we demonstrate the steps involved in a typical differential methylation analysis pipeline including: quality control, filtering, normalization, data exploration and statistical testing for probe-wise differential methylation. We further outline other analyses such as differential methylation of regions, differential variability analysis, estimating cell type composition and gene ontology testing. Finally, we provide some ex les of how to visualise methylation array data.
Publisher: F1000 Research Ltd
Date: 05-04-2017
DOI: 10.12688/F1000RESEARCH.8839.3
Abstract: Methylation in the human genome is known to be associated with development and disease. The Illumina Infinium methylation arrays are by far the most common way to interrogate methylation across the human genome. This paper provides a Bioconductor workflow using multiple packages for the analysis of methylation array data. Specifically, we demonstrate the steps involved in a typical differential methylation analysis pipeline including: quality control, filtering, normalization, data exploration and statistical testing for probe-wise differential methylation. We further outline other analyses such as differential methylation of regions, differential variability analysis, estimating cell type composition and gene ontology testing. Finally, we provide some ex les of how to visualise methylation array data.
Publisher: Proceedings of the National Academy of Sciences
Date: 14-04-2015
Abstract: The body is patterned in the anterior–posterior axis by the correct spatial and temporal expression of Hox genes during embryonic development. One mechanism critical for the precise spatiotemporal expression of Hox genes is the chromatin state. While changes in chromatin conformation during the activation of Hox genes have been well described, the importance of the factors that in turn regulate chromatin remains enigmatic and controversial. In the current study, we investigate the role of two critical chromatin regulators, MOZ and BMI1, during Hox gene activation and in specifying body segment identity. We establish the importance of MOZ and BMI1 during the initial activation of Hox genes in ES cells and in correctly specifying body segment identity during embryonic development.
Publisher: The American Association of Immunologists
Date: 15-07-2011
Abstract: Three surface molecules of mouse CD8+ dendritic cells (DCs), also found on the equivalent human DC subpopulation, were compared as targets for Ab-mediated delivery of Ags, a developing strategy for vaccination. For the production of cytotoxic T cells, DEC-205 and Clec9A, but not Clec12A, were effective targets, although only in the presence of adjuvants. For Ab production, however, Clec9A excelled as a target, even in the absence of adjuvant. Potent humoral immunity was a result of the highly specific expression of Clec9A on DCs, which allowed longer residence of targeting Abs in the bloodstream, prolonged DC Ag presentation, and extended CD4 T cell proliferation, all of which drove highly efficient development of follicular helper T cells. Because Clec9A shows a similar expression pattern on human DCs, it has particular promise as a target for vaccines of human application.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 04-10-2022
Publisher: Springer Science and Business Media LLC
Date: 21-08-2018
Publisher: Cold Spring Harbor Laboratory
Date: 02-05-2017
DOI: 10.1101/133173
Abstract: As single-cell RNA sequencing technologies have rapidly developed, so have analysis methods. Many methods have been tested, developed and validated using simulated datasets. Unfortunately, current simulations are often poorly documented, their similarity to real data is not demonstrated, or reproducible code is not available. Here we present the Splatter Bioconductor package for simple, reproducible and well-documented simulation of single-cell RNA-seq data. Splatter provides an interface to multiple simulation methods including Splat, our own simulation, based on a gamma-Poisson distribution. Splat can simulate single populations of cells, populations with multiple cell types or differentiation paths.
Publisher: Cold Spring Harbor Laboratory
Date: 14-08-2023
DOI: 10.1101/2023.08.14.553168
Abstract: The rapid advancements in cytometry technologies have enabled the quantification of up to 50 proteins across millions of cells at the single-cell resolution. The analysis of cytometry data necessitates the use of computational tools for tasks such as data integration, clustering, and dimensionality reduction. While numerous computational methods exist in the cytometry and single-cell RNA sequencing (scRNAseq) fields, many are hindered by extensive run times when processing large cytometry data containing millions of cells. Existing solutions, such as random subs ling, often prove inadequate as they risk excluding small, rare cell subsets. To address this, we propose a practical strategy that builds on the SuperCell framework from the scRNAseq field. The supercell concept involves grouping single cells with highly similar transcriptomic profiles, and has been shown to be an effective unit of analysis for scRNAseq data. We show that for cytometry datasets, there is no loss of information by grouping cells into supercells. Further, we demonstrate the effectiveness of our approach by conducting a series of downstream analyses on six publicly available cytometry datasets at the supercell level, and successfully replicating previous findings performed at the single cell level. We present a computationally efficient solution for transferring cell type labels from single-cell multiomics data which combines RNA with protein measurements, to a cytometry dataset, allowing for more precise cell type annotations. Our SuperCellCyto R package and the associated analysis workflows are available on our GitHub repositories ( hipsonlab/SuperCellCyto and phipsonlab.github.io/SuperCellCyto-analysis/ ).
Publisher: American Society of Hematology
Date: 09-2011
DOI: 10.1182/BLOOD-2010-06-286393
Abstract: To investigate the role of Aire in thymic selection, we examined the cellular requirements for generation of ovalbumin (OVA)–specific CD4 and CD8 T cells in mice expressing OVA under the control of the rat insulin promoter. Aire deficiency reduced the number of mature single-positive OVA-specific CD4+ or CD8+ T cells in the thymus, independent of OVA expression. Importantly, it also contributed in 2 ways to OVA-dependent negative selection depending on the T-cell type. Aire-dependent negative selection of OVA-specific CD8 T cells correlated with Aire-regulated expression of OVA. By contrast, for OVA-specific CD4 T cells, Aire affected tolerance induction by a mechanism that operated independent of the level of OVA expression, controlling access of antigen presenting cells to medullary thymic epithelial cell (mTEC)–expressed OVA. This study supports the view that one mechanism by which Aire controls thymic negative selection is by regulating the indirect presentation of mTEC-derived antigens by thymic dendritic cells. It also indicates that mTECs can mediate tolerance by direct presentation of Aire-regulated antigens to both CD4 and CD8 T cells.
Publisher: F1000 Research Ltd
Date: 28-04-2017
DOI: 10.12688/F1000RESEARCH.11290.1
Abstract: Background : Single cell RNA sequencing (scRNA-seq) has rapidly gained popularity for profiling transcriptomes of hundreds to thousands of single cells. This technology has led to the discovery of novel cell types and revealed insights into the development of complex tissues. However, many technical challenges need to be overcome during data generation. Due to minute amounts of starting material, s les undergo extensive lification, increasing technical variability. A solution for mitigating lification biases is to include unique molecular identifiers (UMIs), which tag in idual molecules. Transcript abundances are then estimated from the number of unique UMIs aligning to a specific gene, with PCR duplicates resulting in copies of the UMI not included in expression estimates. Methods : Here we investigate the effect of gene length bias in scRNA-Seq across a variety of datasets that differ in terms of capture technology, library preparation, cell types and species. Results : We find that scRNA-seq datasets that have been sequenced using a full-length transcript protocol exhibit gene length bias akin to bulk RNA-seq data. Specifically, shorter genes tend to have lower counts and a higher rate of dropout. In contrast, protocols that include UMIs do not exhibit gene length bias, with a mostly uniform rate of dropout across genes of varying length. Across four different scRNA-Seq datasets profiling mouse embryonic stem cells (mESCs), we found the subset of genes that are only detected in the UMI datasets tended to be shorter, while the subset of genes detected only in the full-length datasets tended to be longer. Conclusions : We find that the choice of scRNA-seq protocol influences the detection rate of genes, and that full-length datasets exhibit gene-length bias. In addition, despite clear differences between UMI and full-length transcript data, we illustrate that full-length and UMI data can be combined to reveal the underlying biology influencing expression of mESCs.
Publisher: Public Library of Science (PLoS)
Date: 19-09-2018
Publisher: Institute of Mathematical Statistics
Date: 06-2016
DOI: 10.1214/16-AOAS920
Publisher: Springer Science and Business Media LLC
Date: 04-12-2018
DOI: 10.1038/S41467-018-07594-Z
Abstract: The podocytes within the glomeruli of the kidney maintain the filtration barrier by forming interdigitating foot processes with intervening slit diaphragms, disruption in which results in proteinuria. Studies into human podocytopathies to date have employed primary or immortalised podocyte cell lines cultured in 2D. Here we compare 3D human glomeruli sieved from induced pluripotent stem cell-derived kidney organoids with conditionally immortalised human podocyte cell lines, revealing improved podocyte-specific gene expression, maintenance in vitro of polarised protein localisation and an improved glomerular basement membrane matrisome compared to 2D cultures. Organoid-derived glomeruli retain marker expression in culture for 96 h, proving amenable to toxicity screening. In addition, 3D organoid glomeruli from a congenital nephrotic syndrome patient with compound heterozygous NPHS1 mutations reveal reduced protein levels of both NEPHRIN and PODOCIN. Hence, human iPSC-derived organoid glomeruli represent an accessible approach to the in vitro modelling of human podocytopathies and screening for podocyte toxicity.
Publisher: Public Library of Science (PLoS)
Date: 14-05-2015
Publisher: Springer Science and Business Media LLC
Date: 10-05-2012
Publisher: Cold Spring Harbor Laboratory
Date: 28-11-2021
DOI: 10.1101/2021.11.28.470236
Abstract: Single cell RNA Sequencing (scRNA-seq) has rapidly gained popularity over the last few years for profiling the transcriptomes of thousands to millions of single cells. This technology is now being used to analyse experiments with complex designs including biological replication. One question that can be asked from single cell experiments, which has been difficult to directly address with bulk RNA-seq data, is whether the cell type proportions are different between two or more experimental conditions. As well as gene expression changes, the relative depletion or enrichment of a particular cell type can be the functional consequence of disease or treatment. However, cell type proportions estimates from scRNA-seq data are variable and statistical methods that can correctly account for different sources of variability are needed to confidently identify statistically significant shifts in cell type composition between experimental conditions. We have developed propeller , a robust and flexible method that leverages biological replication to find statistically significant differences in cell type proportions between groups. Using simulated cell type proportions data we show that propeller performs well under a variety of scenarios. We applied propeller to test for significant changes in proportions of cell types related to human heart development, ageing and COVID-19 disease severity. The propeller method is publicly available in the open source speckle R package ( hipsonlab/speckle ). All the analysis code for the paper is available at hipsonlab ropeller-paper-analysis/ , and the associated analysis website is available at phipsonlab.github.io ropeller-paper-analysis/ . Alicia Oshlack: Alicia.Oshlack@petermac.org Belinda Phipson: phipson.b@wehi.edu.au Yes.
Publisher: American Society of Hematology
Date: 09-12-2010
DOI: 10.1182/BLOOD-2010-04-280818
Abstract: DNA-damaging chemotherapy is the backbone of cancer treatment, although it is not clear how such treatments kill tumor cells. In nontransformed lymphoid cells, the combined loss of 2 proapoptotic p53 target genes, Puma and Noxa, induces as much resistance to DNA damage as loss of p53 itself. In Eμ-Myc lymphomas, however, lack of both Puma and Noxa resulted in no greater drug resistance than lack of Puma alone. A third B-cell lymphoma-2 homology domain (BH)3-only gene, Bim, although not a direct p53 target, was up-regulated in Eμ-Myc lymphomas incurring DNA damage, and knockdown of Bim levels markedly increased the drug resistance of Eμ-Myc/Puma−/−Noxa−/− lymphomas both in vitro and in vivo. Remarkably, c-MYC–driven lymphoma cell lines from Noxa−/−Puma−/−Bim−/− mice were as resistant as those lacking p53. Thus, the combinatorial action of Puma, Noxa, and Bim is critical for optimal apoptotic responses of lymphoma cells to 2 commonly used DNA-damaging chemotherapeutic agents, identifying Bim as an additional biomarker for treatment outcome in the clinic.
Publisher: Cold Spring Harbor Laboratory
Date: 15-03-2023
DOI: 10.1101/2023.03.15.532733
Abstract: Spatial molecular technologies have revolutionised the study of disease microenvironments by providing spatial context to tissue heterogeneity. Recent spatial technologies are increasing the throughput and spatial resolution of measurements, resulting in larger datasets. The added spatial dimension and volume of measurements poses an analytics challenge that has, in the short-term, been addressed by adopting methods designed for the analysis of single-cell RNA-seq data. Though these methods work well in some cases, not all necessarily translate appropriately to spatial technologies. A common assumption is that total sequencing depth, also known as library size, represents technical variation in single-cell RNA-seq technologies, and this is often normalised out during analysis. Through analysis of several different spatial datasets, we noted that this assumption does not necessarily hold in spatial molecular data. To formally assess this, we explore the relationship between library size and independently annotated spatial regions, across 23 s les from 4 different spatial technologies with varying throughput and spatial resolution. We found that library size confounded biology across all technologies, regardless of the tissue being investigated. Statistical modelling of binned total transcripts shows that tissue region is strongly associated with library size across all technologies, even after accounting for cell density of the bins. Through a benchmarking experiment, we show that normalising out library size leads to sub-optimal spatial domain identification using common graph-based clustering algorithms. On average, better clustering was achieved when library size effects were not normalised out explicitly, especially with data from the newer sub-cellular localised technologies. Taking these results into consideration, we recommend that spatial data should not be specifically corrected for library size prior to analysis unless strongly motivated. We also emphasise that spatial data are different to single-cell RNA-seq and care should be taken when adopting algorithms designed for single cell data.
Publisher: Cold Spring Harbor Laboratory
Date: 25-08-2020
DOI: 10.1101/2020.08.24.265702
Abstract: DNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normalisation and identification of differentially methylated CpGs and regions. GOmeth and GOregion are new methods for performing unbiased gene set testing following differential methylation analysis. Benchmarking analyses demonstrate GOmeth outperforms other approaches and GOregion is the first method for gene set testing of differentially methylated regions. Both methods are publicly available in the missMethyl Bioconductor R package.
Publisher: American Society of Hematology
Date: 05-08-2010
DOI: 10.1182/BLOOD-2009-12-260760
Abstract: Polycomb group (PcG) proteins are transcriptional repressors with a central role in the establishment and maintenance of gene expression patterns during development. We have investigated the role of polycomb repressive complexes (PRCs) in hematopoietic stem cells (HSCs) and progenitor populations. We show that mice with loss of function mutations in PRC2 components display enhanced HSC rogenitor population activity, whereas mutations that disrupt PRC1 or pleiohomeotic repressive complex are associated with HSC rogenitor cell defects. Because the hierarchical model of PRC action would predict synergistic effects of PRC1 and PRC2 mutation, these opposing effects suggest this model does not hold true in HSC rogenitor cells. To investigate the molecular targets of each complex in HSC rogenitor cells, we measured genome-wide expression changes associated with PRC deficiency, and identified transcriptional networks that are differentially regulated by PRC1 and PRC2. These studies provide new insights into the mechanistic interplay between distinct PRCs and have important implications for approaching PcG proteins as therapeutic targets.
Publisher: Springer Science and Business Media LLC
Date: 08-06-2021
DOI: 10.1186/S13059-021-02388-X
Abstract: DNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normalization, and identification of differentially methylated CpGs and regions. GOmeth and GOregion are new methods for performing unbiased gene set testing following differential methylation analysis. Benchmarking analyses demonstrate GOmeth outperforms other approaches, and GOregion is the first method for gene set testing of differentially methylated regions. Both methods are publicly available in the missMethyl Bioconductor R package.
Publisher: American Society of Hematology
Date: 14-06-2012
DOI: 10.1182/BLOOD-2011-12-400929
Abstract: The BH3-mimetic ABT-737 and an orally bioavailable compound of the same class, navitoclax (ABT-263), have shown promising antitumor efficacy in preclinical and early clinical studies. Although both drugs avidly bind Bcl-2, Bcl-xL, and Bcl-w in vitro, we find that Bcl-2 is the critical target in vivo, suggesting that patients with tumors overexpressing Bcl-2 will probably benefit. In human non-Hodgkin lymphomas, high expression of Bcl-2 but not Bcl-xL predicted sensitivity to ABT-263. Moreover, we show that increasing Bcl-2 sensitized normal and transformed lymphoid cells to ABT-737 by elevating proapoptotic Bim. In striking contrast, increasing Bcl-xL or Bcl-w conferred robust resistance to ABT-737, despite also increasing Bim. Cell-based protein redistribution assays unexpectedly revealed that ABT-737 disrupts Bcl-2/Bim complexes more readily than Bcl-xL/Bim or Bcl-w/Bim complexes. These results have profound implications for how BH3-mimetics induce apoptosis and how the use of these compounds can be optimized for treating lymphoid malignancies.
Publisher: Springer Science and Business Media LLC
Date: 20-12-2018
Publisher: Oxford University Press (OUP)
Date: 25-08-2022
DOI: 10.1093/BIOINFORMATICS/BTAC582
Abstract: Single cell RNA-Sequencing (scRNA-seq) has rapidly gained popularity over the last few years for profiling the transcriptomes of thousands to millions of single cells. This technology is now being used to analyse experiments with complex designs including biological replication. One question that can be asked from single cell experiments, which has been difficult to directly address with bulk RNA-seq data, is whether the cell type proportions are different between two or more experimental conditions. As well as gene expression changes, the relative depletion or enrichment of a particular cell type can be the functional consequence of disease or treatment. However, cell type proportion estimates from scRNA-seq data are variable and statistical methods that can correctly account for different sources of variability are needed to confidently identify statistically significant shifts in cell type composition between experimental conditions. We have developed propeller, a robust and flexible method that leverages biological replication to find statistically significant differences in cell type proportions between groups. Using simulated cell type proportions data, we show that propeller performs well under a variety of scenarios. We applied propeller to test for significant changes in cell type proportions related to human heart development, ageing and COVID-19 disease severity. The propeller method is publicly available in the open source speckle R package (hipsonlab/speckle). All the analysis code for the article is available at the associated analysis website: phipsonlab.github.io ropeller-paper-analysis/. The speckle package, analysis scripts and datasets have been deposited at 0.5281/zenodo.7009042. Supplementary data are available at Bioinformatics online.
Publisher: Springer Science and Business Media LLC
Date: 09-2014
Publisher: Oxford University Press (OUP)
Date: 30-09-2016
DOI: 10.1093/BIOINFORMATICS/BTV560
Abstract: Summary: DNA methylation is one of the most commonly studied epigenetic modifications due to its role in both disease and development. The Illumina HumanMethylation450 BeadChip is a cost-effective way to profile & 000 CpGs across the human genome, making it a popular platform for profiling DNA methylation. Here we introduce missMethyl, an R package with a suite of tools for performing normalization, removal of unwanted variation in differential methylation analysis, differential variability testing and gene set analysis for the 450K array. Availability and implementation: missMethyl is an R package available from the Bioconductor project at www.bioconductor.org. Contact: alicia.oshlack@mcri.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.
Publisher: Springer Science and Business Media LLC
Date: 16-03-2015
DOI: 10.1038/ONC.2015.33
Abstract: Cellular senescence is an important mechanism that restricts tumour growth. The Ink4a-Arf locus (also known as Cdkn2a), which encodes p16(INK4A) and p19(ARF), has a central role in inducing and maintaining senescence. Given the importance of cellular senescence in restraining tumour growth, great emphasis is being placed on the identification of novel factors that can modulate senescence. The MYST-family histone acetyltransferase MOZ (MYST3, KAT6A), first identified in recurrent translocations in acute myeloid leukaemia, has been implicated in both the promotion and inhibition of senescence. In this study, we investigate the role of MOZ in cellular senescence and show that MOZ is a potent inhibitor of senescence via the INK4A-ARF pathway. Primary mouse embryonic fibroblasts (MEFs) isolated from Moz-deficient embryos exhibit premature senescence, which was rescued on the Ink4a-Arf(-/-) background. Importantly, senescence resulting from the absence of MOZ was not accompanied by DNA damage, suggesting that MOZ acts independently of the DNA damage response. Consistent with the importance of senescence in cancer, expression profiling revealed that genes overexpressed in aggressive and highly proliferative cancers are expressed at low levels in Moz-deficient MEFs. We show that MOZ is required to maintain normal levels of histone 3 lysine 9 (H3K9) and H3K27 acetylation at the transcriptional start sites of at least four genes, Cdc6, Ezh2, E2f2 and Melk, and normal mRNA levels of these genes. CDC6, EZH2 and E2F2 are known inhibitors of the INK4A-ARF pathway. Using chromatin immunoprecipitation, we show that MOZ occupies the Cdc6, Ezh2 and Melk loci, thereby providing a direct link between MOZ, H3K9 and H3K27 acetylation, and normal transcriptional levels at these loci. This work establishes that MOZ is an upstream inhibitor of the INK4A-ARF pathway, and suggests that inhibiting MOZ may be one way to induce senescence in proliferative tumour cells.
Publisher: Oxford University Press (OUP)
Date: 25-08-2009
DOI: 10.1093/JXB/ERP254
Publisher: Cold Spring Harbor Laboratory
Date: 04-11-2010
Abstract: More than 25 loci have been linked to type 1 diabetes (T1D) in the nonobese diabetic (NOD) mouse, but identification of the underlying genes remains challenging. We describe here the positional cloning of a T1D susceptibility locus, Idd11 , located on mouse chromosome 4. Sequence analysis of a series of congenic NOD mouse strains over a critical 6.9-kb interval in these mice and in 25 inbred strains identified several haplotypes, including a unique NOD haplotype, associated with varying levels of T1D susceptibility. Haplotype ersity within this interval between congenic NOD mouse strains was due to a recombination hotspot that generated four crossover breakpoints, including one with a complex conversion tract. The Idd11 haplotype and recombination hotspot are located within a predicted gene of unknown function, which exhibits decreased expression in relevant tissues of NOD mice. Notably, it was the recombination hotspot that aided our mapping of Idd11 and confirms that recombination hotspots can create genetic variation affecting a common polygenic disease. This finding has implications for human genetic association studies, which may be affected by the approximately 33,000 estimated hotspots in the genome.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 20-04-2021
DOI: 10.1161/CIRCULATIONAHA.120.051921
Abstract: Despite in-depth knowledge of the molecular mechanisms controlling embryonic heart development, little is known about the signals governing postnatal maturation of the human heart. Single-nucleus RNA sequencing of 54 140 nuclei from 9 human donors was used to profile transcriptional changes in erse cardiac cell types during maturation from fetal stages to adulthood. Bulk RNA sequencing and the Assay for Transposase-Accessible Chromatin using sequencing were used to further validate transcriptional changes and to profile alterations in the chromatin accessibility landscape in purified cardiomyocyte nuclei from 21 human donors. Functional validation studies of sex steroids implicated in cardiac maturation were performed in human pluripotent stem cell–derived cardiac organoids and mice. Our data identify the progesterone receptor as a key mediator of sex-dependent transcriptional programs during cardiomyocyte maturation. Functional validation studies in human cardiac organoids and mice demonstrate that the progesterone receptor drives sex-specific metabolic programs and maturation of cardiac contractile properties. These data provide a blueprint for understanding human heart maturation in both sexes and reveal an important role for the progesterone receptor in human heart development.
Publisher: Elsevier BV
Date: 2023
Publisher: Public Library of Science (PLoS)
Date: 25-06-2018
Publisher: Cold Spring Harbor Laboratory
Date: 20-10-2017
DOI: 10.1101/206573
Abstract: As single-cell RNA-sequencing (scRNA-seq) datasets have become more widespread the number of tools designed to analyse these data has dramatically increased. Navigating the vast sea of tools now available is becoming increasingly challenging for researchers. In order to better facilitate selection of appropriate analysis tools we have created the scRNA-tools database ( www.scRNA-tools.org ) to catalogue and curate analysis tools as they become available. Our database collects a range of information on each scRNA-seq analysis tool and categorises them according to the analysis tasks they perform. Exploration of this database gives insights into the areas of rapid development of analysis methods for scRNA-seq data. We see that many tools perform tasks specific to scRNA-seq analysis, particularly clustering and ordering of cells. We also find that the scRNA-seq community embraces an open-source approach, with most tools available under open-source licenses and preprints being extensively used as a means to describe methods. The scRNA-tools database provides a valuable resource for researchers embarking on scRNA-seq analysis and records of the growth of the field over time. In recent years single-cell RNA-sequeing technologies have emerged that allow scientists to measure the activity of genes in thousands of in idual cells simultaneously. This means we can start to look at what each cell in a s le is doing instead of considering an average across all cells in a s le, as was the case with older technologies. However, while access to this kind of data presents a wealth of opportunities it comes with a new set of challenges. Researchers across the world have developed new methods and software tools to make the most of these datasets but the field is moving at such a rapid pace it is difficult to keep up with what is currently available. To make this easier we have developed the scRNA-tools database and website ( www.scRNA-tools.org ). Our database catalogues analysis tools, recording the tasks they can be used for, where they can be downloaded from and the publications that describe how they work. By looking at this database we can see that developers have focued on methods specific to single-cell data and that they embrace an open-source approach with permissive licensing, sharing of code and preprint publications.
Publisher: Springer Science and Business Media LLC
Date: 12-09-2017
Publisher: Walter de Gruyter GmbH
Date: 31-01-2010
Abstract: Permutation tests are amongst the most commonly used statistical tools in modern genomic research, a process by which p-values are attached to a test statistic by randomly permuting the s le or gene labels. Yet permutation p-values published in the genomic literature are often computed incorrectly, understated by about 1/m, where m is the number of permutations. The same is often true in the more general situation when Monte Carlo simulation is used to assign p-values. Although the p-value understatement is usually small in absolute terms, the implications can be serious in a multiple testing context. The understatement arises from the intuitive but mistaken idea of using permutation to estimate the tail probability of the test statistic. We argue instead that permutation should be viewed as generating an exact discrete null distribution. The relevant literature, some of which is likely to have been relatively inaccessible to the genomic community, is reviewed and summarized. A computation strategy is developed for exact p-values when permutations are randomly drawn. The strategy is valid for any number of permutations and s les. Some simple recommendations are made for the implementation of permutation tests in practice.
Publisher: Elsevier BV
Date: 06-2012
Publisher: Cold Spring Harbor Laboratory
Date: 25-11-2022
DOI: 10.1101/2022.11.23.516993
Abstract: Between tetrapods the limbs have undergone considerable remodelling to achieve unique adaptive behaviours. The forelimb is an ideal model for exploring the molecular basis of adaptive limb development, as it shows remarkable structural variation and is accessible for experimental manipulation. Of the most striking alterations to limb shape is the evolution of powered flight in birds. However, subsequently the flightless ratites (Paleognathae) have further evolved multiple instances of wing reductions, each utilizing distinct molecular mechanisms and displaying heterochrony with flighted birds (Neoaves). The emu has evolved a greatly reduced wing, consisted of a single digit. Thus, the emu is an excellent model to comparatively determine the cellular and molecular basis of wing heterochrony. We utilize comparative single cell transcriptomics of the developing forelimb field in the emu and chicken, to identify the source of the emus reduced wing. This was observed to occur via reduced specification and commitment of lateral plate mesoderm limb progenitor cells, which was accompanied by differential gene expression, persisting during limb initiation and outgrowth. These data suggest a progenitor allocation model, whereby altered limb morphologies may be achieved through altered commitment of precursor cells which act as an underlying template for pre- and post-patterning mechanisms.
Publisher: The Company of Biologists
Date: 12-06-2019
DOI: 10.1242/DEV.178673
Abstract: Recent advances in the generation of kidney organoids and the culture of primary nephron progenitors from mouse and human have been based on knowledge of the molecular basis of kidney development in mice. Although gene expression during kidney development has been intensely investigated, single cell profiling provides new opportunities to further subsect component cell types and the signalling networks at play. Here, we describe the generation and analysis of 6732 single cell transcriptomes from the fetal mouse kidney [embryonic day (E)18.5] and 7853 sorted nephron progenitor cells (E14.5). These datasets provide improved resolution of cell types and specific markers, including sub ision of the renal stroma and heterogeneity within the nephron progenitor population. Ligand-receptor interaction and pathway analysis reveals novel crosstalk between cellular compartments and associates new pathways with differentiation of nephron and ureteric epithelium cell types. We identify transcriptional congruence between the distal nephron and ureteric epithelium, showing that most markers previously used to identify ureteric epithelium are not specific. Together, this work improves our understanding of metanephric kidney development and provides a template to guide the regeneration of renal tissue.
Publisher: Elsevier BV
Date: 03-2018
Publisher: Elsevier BV
Date: 05-2018
Publisher: Cold Spring Harbor Laboratory
Date: 04-07-2017
DOI: 10.1101/159228
Abstract: Short tandem repeat (STR) expansions have been identified as the causal DNA mutation in dozens of Mendelian diseases. Historically, pathogenic STR expansions could only be detected by single locus techniques, such as PCR and electrophoresis. The ability to use short read sequencing data to screen for STR expansions has the potential to reduce both the time and cost to reaching diagnosis and enable the discovery of new causal STR loci. Most existing tools detect STR variation within the read length, and so are unable to detect the majority of pathogenic expansions. Those tools that can detect large expansions are limited to a set of known disease loci and as yet no new disease causing STR expansions have been identified with high-throughput sequencing technologies. Here we address this by presenting STRetch, a new genome-wide method to detect STR expansions at all loci across the human genome. We demonstrate the use of STRetch for detecting pathogenic STR expansions in short-read whole genome sequencing data with a very low false discovery rate. We further demonstrate the application of STRetch to solve cases of patients with undiagnosed disease and apply STRetch to the analysis of 97 whole genomes to reveal variation at STR loci. STRetch assesses expansions at all STR loci in the genome and allows screening for novel disease-causing STRs. STRetch is open source software, available from github.com/Oshlack/STRetch .
Publisher: Springer Science and Business Media LLC
Date: 17-10-2016
DOI: 10.1038/NBT.3702
Abstract: The ability to generate hematopoietic stem cells from human pluripotent cells would enable many biomedical applications. We find that hematopoietic CD34
Publisher: Cold Spring Harbor Laboratory
Date: 22-03-2017
DOI: 10.1101/119222
Abstract: Single cell RNA sequencing (scRNA-seq) has rapidly gained popularity for profiling transcriptomes of hundreds to thousands of single cells. This technology has led to the discovery of novel cell types and revealed insights into the development of complex tissues. However, many technical challenges need to be overcome during data generation. Due to minute amounts of starting material, s les undergo extensive lification, increasing technical variability. A solution for mitigating lification biases is to include Unique Molecular Identifiers (UMIs), which tag in idual molecules. Transcript abundances are then estimated from the number of unique UMIs aligning to a specific gene and PCR duplicates resulting in copies of the UMI are not included in expression estimates. Here we investigate the effect of gene length bias in scRNA-Seq across a variety of datasets differing in terms of capture technology, library preparation, cell types and species. We find that scRNA-seq datasets that have been sequenced using a full-length transcript protocol exhibit gene length bias akin to bulk RNA-seq data. Specifically, shorter genes tend to have lower counts and a higher rate of dropout. In contrast, protocols that include UMIs do not exhibit gene length bias, and have a mostly uniform rate of dropout across genes of varying length. Across four different scRNA-Seq datasets profiling mouse embryonic stem cells (mESCs), we found the subset of genes that are only detected in the UMI datasets tended to be shorter, while the subset of genes detected only in the full-length datasets tended to be longer. We briefly discuss the role of these genes in the context of differential expression testing and GO analysis. In addition, despite clear differences between UMI and full-length transcript data, we illustrate that full-length and UMI data can be combined to reveal underlying biology influencing expression of mESCs.
Publisher: Springer Science and Business Media LLC
Date: 14-10-2017
DOI: 10.1038/LEU.2016.279
Abstract: Enforced expression of microRNA-155 (miR-155) in myeloid cells has been shown to have both oncogenic or tumour-suppressor functions in acute myeloid leukaemia (AML). We sought to resolve these contrasting effects of miR-155 overexpression using murine models of AML and human paediatric AML data sets. We show that the highest miR-155 expression levels inhibited proliferation in murine AML models. Over time, enforced miR-155 expression in AML in vitro and in vivo, however, favours selection of intermediate miR-155 expression levels that results in increased tumour burden in mice, without accelerating the onset of disease. Strikingly, we show that intermediate and high miR-155 expression also regulate very different subsets of miR-155 targets and have contrasting downstream effects on the transcriptional environments of AML cells, including genes involved in haematopoiesis and leukaemia. Furthermore, we show that elevated miR-155 expression detected in paediatric AML correlates with intermediate and not high miR-155 expression identified in our experimental models. These findings collectively describe a novel dose-dependent role for miR-155 in the regulation of AML, which may have important therapeutic implications.
Publisher: Proceedings of the National Academy of Sciences
Date: 10-11-2009
Abstract: Two distinct bone marrow-derived blast colony-forming cells can generate colonies of lineage-restricted progenitor cells in agar cultures of murine bone marrow. Both cell types selectively had a Kit + ScaI + phenotype distinguishing them from most lineage-restricted progenitor cells. Multicentric blast colony-forming cells stimulated by stem cell factor plus interleukin-6 (IL-6) (BL-CFC-S) were separable from most dispersed blast colony-forming cells stimulated by Flt3 ligand and IL-6 (BL-CFC-F) using CD34 and Flt3R probes. Multicentric BL-CFC-S cofractionated with colony-forming units, spleen (CFU-S) supporting the possibility that the 2 cells may be identical. The colony populations generated by BL-CFC-S were similar in their phenotype and proliferative capacity to progenitor cells in whole bone marrow but the progeny of BL-CFC-F were skewed with an abnormally high proportion of Kit − Flt3R + cells whose clonogenic cells tended to generate only macrophage progeny. Both blast colony populations had a high percentage of GR1 + and Mac1 + cells but BL-CFC-F colonies also contained a significant population of B220 + and IL-7R + cells relevant to the superior ability of BL-CFC-F colony cells to generate B lymphocytes and the known dependency of this process on Flt3 ligand and IL-7. The commitment events and phenotypic changes during the generation of differing progenitor cells in blast colonies can now be clonally analyzed in a convenient in vitro culture system.
Publisher: American Diabetes Association
Date: 31-03-2010
DOI: 10.2337/DB09-0287
Abstract: Insulin resistance and other features of the metabolic syndrome have been causally linked to adipose tissue macrophages (ATMs) in mice with diet-induced obesity. We aimed to characterize macrophage phenotype and function in human subcutaneous and omental adipose tissue in relation to insulin resistance in obesity. Adipose tissue was obtained from lean and obese women undergoing bariatric surgery. Metabolic markers were measured in fasting serum and ATMs characterized by immunohistology, flow cytometry, and tissue culture studies. ATMs comprised CD11c+CD206+ cells in “crown” aggregates and solitary CD11c−CD206+ cells at adipocyte junctions. In obese women, CD11c+ ATM density was greater in subcutaneous than omental adipose tissue and correlated with markers of insulin resistance. CD11c+ ATMs were distinguished by high expression of integrins and antigen presentation molecules interleukin (IL)-1β, -6, -8, and -10 tumor necrosis factor-α and CC chemokine ligand-3, indicative of an activated, proinflammatory state. In addition, CD11c+ ATMs were enriched for mitochondria and for RNA transcripts encoding mitochondrial, proteasomal, and lysosomal proteins, fatty acid metabolism enzymes, and T-cell chemoattractants, whereas CD11c− ATMs were enriched for transcripts involved in tissue maintenance and repair. Tissue culture medium conditioned by CD11c+ ATMs, but not CD11c− ATMs or other stromovascular cells, impaired insulin-stimulated glucose uptake by human adipocytes. These findings identify proinflammatory CD11c+ ATMs as markers of insulin resistance in human obesity. In addition, the machinery of CD11c+ ATMs indicates they metabolize lipid and may initiate adaptive immune responses.
Location: Australia
No related grants have been discovered for Belinda Phipson.