School of Mathematics and Statistics - Research Publications

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    HBO1 (KAT7) Does Not Have an Essential Role in Cell Proliferation, DNA Replication, or Histone 4 Acetylation in Human Cells
    Kueh, AJ ; Eccles, S ; Tang, L ; Garnham, AL ; May, RE ; Herold, MJ ; Smyth, GK ; Voss, AK ; Thomas, T (American Society for Microbiology, 2020-02-01)
    HBO1 (MYST2/KAT7) is essential for histone 3 lysine 14 acetylation (H3K14ac) but is dispensable for H4 acetylation and DNA replication in mouse tissues. In contrast, previous studies using small interfering RNA (siRNA) knockdown in human cell lines have suggested that HBO1 is essential for DNA replication. To determine if HBO1 has distinctly different roles in immortalized human cell lines and normal mouse cells, we performed siRNA knockdown of HBO1. In addition, we used CRISPR/Cas9 to generate 293T, MCF7, and HeLa cell lines lacking HBO1. Using both techniques, we show that HBO1 is essential for all H3K14ac in human cells and is unlikely to have a direct effect on H4 acetylation and only has minor effects on cell proliferation. Surprisingly, the loss of HBO1 and H3K14ac in HeLa cells led to the secondary loss of almost all H4 acetylation after 4 weeks. Thus, HBO1 is dispensable for DNA replication and cell proliferation in immortalized human cells. However, while cell proliferation proceeded without HBO1 and H3K14ac, HBO1 gene deletion led to profound changes in cell adhesion, particularly in 293T cells. Consistent with this phenotype, the loss of HBO1 in both 293T and HeLa principally affected genes mediating cell adhesion, with comparatively minor effects on other cellular processes.
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    Gata-3 Negatively Regulates the Tumor-Initiating Capacity of Mammary Luminal Progenitor Cells and Targets the Putative Tumor Suppressor Caspase-14
    Asselin-Labat, M-L ; Sutherland, KD ; Vaillant, F ; Gyorki, DE ; Wu, D ; Holroyd, S ; Breslin, K ; Ward, T ; Shi, W ; Bath, ML ; Deb, S ; Fox, SB ; Smyth, GK ; Lindeman, GJ ; Visvader, JE (AMER SOC MICROBIOLOGY, 2011-11)
    The transcription factor Gata-3 is a definitive marker of luminal breast cancers and a key regulator of mammary morphogenesis. Here we have explored a role for Gata-3 in tumor initiation and the underlying cellular mechanisms using a mouse model of "luminal-like" cancer. Loss of a single Gata-3 allele markedly accelerated tumor progression in mice carrying the mouse mammary tumor virus promoter-driven polyomavirus middle T antigen (MMTV-PyMT mice), while overexpression of Gata-3 curtailed tumorigenesis. Through the identification of two distinct luminal progenitor cells in the mammary gland, we demonstrate that Gata-3 haplo-insufficiency increases the tumor-initiating capacity of these progenitors but not the stem cell-enriched population. Overexpression of a conditional Gata-3 transgene in the PyMT model promoted cellular differentiation and led to reduced tumor-initiating capacity as well as diminished angiogenesis. Transcript profiling studies identified caspase-14 as a novel downstream target of Gata-3, in keeping with its roles in differentiation and tumorigenesis. A strong association was evident between GATA-3 and caspase-14 expression in preinvasive ductal carcinoma in situ samples, where GATA-3 also displayed prognostic significance. Overall, these studies identify GATA-3 as an important regulator of tumor initiation through its ability to promote the differentiation of committed luminal progenitor cells.
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    A non-canonical function of Ezh2 preserves immune homeostasis
    Vasanthakumar, A ; Xu, D ; Lun, ATL ; Kueh, AJ ; van Gisbergen, KPJM ; Iannarella, N ; Li, X ; Yu, L ; Wang, D ; Williams, BRG ; Lee, SCW ; Majewski, IJ ; Godfrey, DI ; Smyth, GK ; Alexander, WS ; Herold, MJ ; Kallies, A ; Nutt, SL ; Allan, RS (WILEY, 2017-04)
    Enhancer of zeste 2 (Ezh2) mainly methylates lysine 27 of histone-H3 (H3K27me3) as part of the polycomb repressive complex 2 (PRC2) together with Suz12 and Eed. However, Ezh2 can also modify non-histone substrates, although it is unclear whether this mechanism has a role during development. Here, we present evidence for a chromatin-independent role of Ezh2 during T-cell development and immune homeostasis. T-cell-specific depletion of Ezh2 induces a pronounced expansion of natural killer T (NKT) cells, although Ezh2-deficient T cells maintain normal levels of H3K27me3. In contrast, removal of Suz12 or Eed destabilizes canonical PRC2 function and ablates NKT cell development completely. We further show that Ezh2 directly methylates the NKT cell lineage defining transcription factor PLZF, leading to its ubiquitination and subsequent degradation. Sustained PLZF expression in Ezh2-deficient mice is associated with the expansion of a subset of NKT cells that cause immune perturbation. Taken together, we have identified a chromatin-independent function of Ezh2 that impacts on the development of the immune system.
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    A guide to creating design matrices for gene expression experiments.
    Law, CW ; Zeglinski, K ; Dong, X ; Alhamdoosh, M ; Smyth, GK ; Ritchie, ME (F1000 Research Ltd, 2020)
    Differential expression analysis of genomic data types, such as RNA-sequencing experiments, use linear models to determine the size and direction of the changes in gene expression. For RNA-sequencing, there are several established software packages for this purpose accompanied with analysis pipelines that are well described. However, there are two crucial steps in the analysis process that can be a stumbling block for many -- the set up an appropriate model via design matrices and the set up of comparisons of interest via contrast matrices. These steps are particularly troublesome because an extensive catalogue for design and contrast matrices does not currently exist. One would usually search for example case studies across different platforms and mix and match the advice from those sources to suit the dataset they have at hand. This article guides the reader through the basics of how to set up design and contrast matrices. We take a practical approach by providing code and graphical representation of each case study, starting with simpler examples (e.g. models with a single explanatory variable) and move onto more complex ones (e.g. interaction models, mixed effects models, higher order time series and cyclical models). Although our work has been written specifically with a limma-style pipeline in mind, most of it is also applicable to other software packages for differential expression analysis, and the ideas covered can be adapted to data analysis of other high-throughput technologies. Where appropriate, we explain the interpretation and differences between models to aid readers in their own model choices. Unnecessary jargon and theory is omitted where possible so that our work is accessible to a wide audience of readers, from beginners to those with experience in genomics data analysis.
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    Canonical PRC2 function is essential for mammary gland development and affects chromatin compaction in mammary organoids
    Michalak, EM ; Milevskiy, MJG ; Joyce, RM ; Dekkers, JF ; Jamieson, PR ; Pal, B ; Dawson, CA ; Hu, Y ; Orkin, SH ; Alexander, WS ; Lindeman, GJ ; Smyth, GK ; Visvader, JE ; Rawlins, E (PUBLIC LIBRARY SCIENCE, 2018-08)
    Distinct transcriptional states are maintained through organization of chromatin, resulting from the sum of numerous repressive and active histone modifications, into tightly packaged heterochromatin versus more accessible euchromatin. Polycomb repressive complex 2 (PRC2) is the main mammalian complex responsible for histone 3 lysine 27 trimethylation (H3K27me3) and is integral to chromatin organization. Using in vitro and in vivo studies, we show that deletion of Suz12, a core component of all PRC2 complexes, results in loss of H3K27me3 and H3K27 dimethylation (H3K27me2), completely blocks normal mammary gland development, and profoundly curtails progenitor activity in 3D organoid cultures. Through the application of mammary organoids to bypass the severe phenotype associated with Suz12 loss in vivo, we have explored gene expression and chromatin structure in wild-type and Suz12-deleted basal-derived organoids. Analysis of organoids led to the identification of lineage-specific changes in gene expression and chromatin structure, inferring cell type-specific PRC2-mediated gene silencing of the chromatin state. These expression changes were accompanied by cell cycle arrest but not lineage infidelity. Together, these data indicate that canonical PRC2 function is essential for development of the mammary gland through the repression of alternate transcription programs and maintenance of chromatin states.
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    Construction of developmental lineage relationships in the mouse mammary gland by single-cell RNA profiling
    Pal, B ; Chen, Y ; Vaillant, F ; Jamieson, P ; Gordon, L ; Rios, AC ; Wilcox, S ; Fu, N ; Liu, KH ; Jackling, FC ; Davis, MJ ; Lindeman, GJ ; Smyth, GK ; Visvader, JE (NATURE PORTFOLIO, 2017-11-20)
    The mammary epithelium comprises two primary cellular lineages, but the degree of heterogeneity within these compartments and their lineage relationships during development remain an open question. Here we report single-cell RNA profiling of mouse mammary epithelial cells spanning four developmental stages in the post-natal gland. Notably, the epithelium undergoes a large-scale shift in gene expression from a relatively homogeneous basal-like program in pre-puberty to distinct lineage-restricted programs in puberty. Interrogation of single-cell transcriptomes reveals different levels of diversity within the luminal and basal compartments, and identifies an early progenitor subset marked by CD55. Moreover, we uncover a luminal transit population and a rare mixed-lineage cluster amongst basal cells in the adult mammary gland. Together these findings point to a developmental hierarchy in which a basal-like gene expression program prevails in the early post-natal gland prior to the specification of distinct lineage signatures, and the presence of cellular intermediates that may serve as transit or lineage-primed cells.
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    Impaired thermogenesis and adipose tissue development in mice with fat-specific disruption of insulin and IGF-1 signalling
    Boucher, J ; Mori, MA ; Lee, KY ; Smyth, G ; Liew, CW ; Macotela, Y ; Rourk, M ; Bluher, M ; Russell, SJ ; Kahn, CR (NATURE PUBLISHING GROUP, 2012-06)
    Insulin and insulin-like growth factor 1 (IGF-1) have important roles in adipocyte differentiation, glucose tolerance and insulin sensitivity. Here to assess how these pathways can compensate for each other, we created mice with a double tissue-specific knockout of insulin and IGF-1 receptors to eliminate all insulin/IGF-1 signalling in fat. These FIGIRKO mice had markedly decreased white and brown fat mass and were completely resistant to high fat diet-induced obesity and age- and high fat diet-induced glucose intolerance. Energy expenditure was increased in FIGIRKO mice despite a >85% reduction in brown fat mass. However, FIGIRKO mice were unable to maintain body temperature when placed at 4 °C. Brown fat activity was markedly decreased in FIGIRKO mice but was responsive to β3-receptor stimulation. Thus, insulin/IGF-1 signalling has a crucial role in the control of brown and white fat development, and, when disrupted, leads to defective thermogenesis and a paradoxical increase in basal metabolic rate.
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    Complementarity and redundancy of IL-22-producing innate lymphoid cells
    Rankin, LC ; Girard-Madoux, MJH ; Seillet, C ; Mielke, LA ; Kerdiles, Y ; Fenis, A ; Wieduwild, E ; Putoczki, T ; Mondot, S ; Lantz, O ; Demon, D ; Papenfuss, AT ; Smyth, GK ; Lamkanfi, M ; Carotta, S ; Renauld, J-C ; Shi, W ; Carpentier, S ; Soos, T ; Arendt, C ; Ugolini, S ; Huntington, ND ; Bez, GT ; Vivier, E (NATURE PUBLISHING GROUP, 2016-02)
    Intestinal T cells and group 3 innate lymphoid cells (ILC3 cells) control the composition of the microbiota and gut immune responses. Within the gut, ILC3 subsets coexist that either express or lack the natural cytoxicity receptor (NCR) NKp46. We identified here the transcriptional signature associated with the transcription factor T-bet-dependent differentiation of NCR(-) ILC3 cells into NCR(+) ILC3 cells. Contrary to the prevailing view, we found by conditional deletion of the key ILC3 genes Stat3, Il22, Tbx21 and Mcl1 that NCR(+) ILC3 cells were redundant for the control of mouse colonic infection with Citrobacter rodentium in the presence of T cells. However, NCR(+) ILC3 cells were essential for cecal homeostasis. Our data show that interplay between intestinal ILC3 cells and adaptive lymphocytes results in robust complementary failsafe mechanisms that ensure gut homeostasis.
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    Blimp-1 controls plasma cell function through the regulation of immunoglobulin secretion and the unfolded protein response
    Tellier, J ; Shi, W ; Minnich, M ; Liao, Y ; Crawford, S ; Smyth, GK ; Kallies, A ; Busslinger, M ; Nutt, SL (NATURE PUBLISHING GROUP, 2016-03)
    Plasma cell differentiation requires silencing of B cell transcription, while it establishes antibody-secretory function and long-term survival. The transcription factors Blimp-1 and IRF4 are essential for the generation of plasma cells; however, their function in mature plasma cells has remained elusive. We found that while IRF4 was essential for the survival of plasma cells, Blimp-1 was dispensable for this. Blimp-1-deficient plasma cells retained their transcriptional identity but lost the ability to secrete antibody. Blimp-1 regulated many components of the unfolded protein response (UPR), including XBP-1 and ATF6. The overlap in the functions of Blimp-1 and XBP-1 was restricted to that response, with Blimp-1 uniquely regulating activity of the kinase mTOR and the size of plasma cells. Thus, Blimp-1 was required for the unique physiological ability of plasma cells that enables the secretion of protective antibody.
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    A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium
    Su, Z ; Labaj, PP ; Li, S ; Thierry-Mieg, J ; Thierry-Mieg, D ; Shi, W ; Wang, C ; Schroth, GP ; Setterquist, RA ; Thompson, JF ; Jones, WD ; Xiao, W ; Xu, W ; Jensen, RV ; Kelly, R ; Xu, J ; Conesa, A ; Furlanello, C ; Gao, H ; Hong, H ; Jafari, N ; Letovsky, S ; Liao, Y ; Lu, F ; Oakeley, EJ ; Peng, Z ; Praul, CA ; Santoyo-Lopez, J ; Scherer, A ; Shi, T ; Smyth, GK ; Staedtler, F ; Sykacek, P ; Tan, X-X ; Thompson, EA ; Vandesompele, J ; Wang, MD ; Wang, J ; Wolfinger, RD ; Zavadil, J ; Auerbach, SS ; Bao, W ; Binder, H ; Blomquist, T ; Brilliant, MH ; Bushel, PR ; Cain, W ; Catalano, JG ; Chang, C-W ; Chen, T ; Chen, G ; Chen, R ; Chierici, M ; Chu, T-M ; Clevert, D-A ; Deng, Y ; Derti, A ; Devanarayan, V ; Dong, Z ; Dopazo, J ; Du, T ; Fang, H ; Fang, Y ; Fasold, M ; Fernandez, A ; Fischer, M ; Furio-Tari, P ; Fuscoe, JC ; Caiment, F ; Gaj, S ; Gandara, J ; Gao, H ; Ge, W ; Gondo, Y ; Gong, B ; Gong, M ; Gong, Z ; Green, B ; Guo, C ; Guo, L ; Guo, L-W ; Hadfield, J ; Hellemans, J ; Hochreiter, S ; Jia, M ; Jian, M ; Johnson, CD ; Kay, S ; Kleinjans, J ; Lababidi, S ; Levy, S ; Li, Q-Z ; Li, L ; Li, L ; Li, P ; Li, Y ; Li, H ; Li, J ; Li, S ; Lin, SM ; Lopez, FJ ; Lu, X ; Luo, H ; Ma, X ; Meehan, J ; Megherbi, DB ; Mei, N ; Mu, B ; Ning, B ; Pandey, A ; Perez-Florido, J ; Perkins, RG ; Peters, R ; Phan, JH ; Pirooznia, M ; Qian, F ; Qing, T ; Rainbow, L ; Rocca-Serra, P ; Sambourg, L ; Sansone, S-A ; Schwartz, S ; Shah, R ; Shen, J ; Smith, TM ; Stegle, O ; Stralis-Pavese, N ; Stupka, E ; Suzuki, Y ; Szkotnicki, LT ; Tinning, M ; Tu, B ; van Deft, J ; Vela-Boza, A ; Venturini, E ; Walker, SJ ; Wan, L ; Wang, W ; Wang, J ; Wang, J ; Wieben, ED ; Willey, JC ; Wu, P-Y ; Xuan, J ; Yang, Y ; Ye, Z ; Yin, Y ; Yu, Y ; Yuan, Y-C ; Zhang, J ; Zhang, KK ; Zhang, W ; Zhang, W ; Zhang, Y ; Zhao, C ; Zheng, Y ; Zhou, Y ; Zumbo, P ; Tong, W ; Kreil, DP ; Mason, CE ; Shi, L (NATURE PORTFOLIO, 2014-09)
    We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the US Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed for all examined platforms, including qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.