School of Mathematics and Statistics - Research Publications

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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, 2016-02-01)
    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, 2016-03-01)
    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 PUBLISHING GROUP, 2014-09-01)
    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.
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    HDAC inhibitors induce tumor-cell-selective pro-apoptotic transcriptional responses
    Bolden, JE ; Shi, W ; Jankowski, K ; Kan, C-Y ; Cluse, L ; Martin, BP ; MacKenzie, KL ; Smyth, GK ; Johnstone, RW (NATURE PUBLISHING GROUP, 2013-02-01)
    The identification of recurrent somatic mutations in genes encoding epigenetic enzymes has provided a strong rationale for the development of compounds that target the epigenome for the treatment of cancer. This notion is supported by biochemical studies demonstrating aberrant recruitment of epigenetic enzymes such as histone deacetylases (HDACs) and histone methyltransferases to promoter regions through association with oncogenic fusion proteins such as PML-RARα and AML1-ETO. HDAC inhibitors (HDACi) are potent inducers of tumor cell apoptosis; however, it remains unclear why tumor cells are more sensitive to HDACi-induced cell death than normal cells. Herein, we assessed the biological and molecular responses of isogenic normal and transformed cells to the FDA-approved HDACi vorinostat and romidepsin. Both HDACi selectively killed cells of diverse tissue origin that had been transformed through the serial introduction of different oncogenes. Time-course microarray expression profiling revealed that normal and transformed cells transcriptionally responded to vorinostat treatment. Over 4200 genes responded differently to vorinostat in normal and transformed cells and gene ontology and pathway analyses identified a tumor-cell-selective pro-apoptotic gene-expression signature that consisted of BCL2 family genes. In particular, HDACi induced tumor-cell-selective upregulation of the pro-apoptotic gene BMF and downregulation of the pro-survival gene BCL2A1 encoding BFL-1. Maintenance of BFL-1 levels in transformed cells through forced expression conferred vorinostat resistance, indicating that specific and selective engagement of the intrinsic apoptotic pathway underlies the tumor-cell-selective apoptotic activities of these agents. The ability of HDACi to affect the growth and survival of tumor cells whilst leaving normal cells relatively unharmed is fundamental to their successful clinical application. This study provides new insight into the transcriptional effects of HDACi in human donor-matched normal and transformed cells, and implicates specific molecules and pathways in the tumor-selective cytotoxic activity of these compounds.
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    The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote
    Liao, Y ; Smyth, GK ; Shi, W (OXFORD UNIV PRESS, 2013-05-01)
    Read alignment is an ongoing challenge for the analysis of data from sequencing technologies. This article proposes an elegantly simple multi-seed strategy, called seed-and-vote, for mapping reads to a reference genome. The new strategy chooses the mapped genomic location for the read directly from the seeds. It uses a relatively large number of short seeds (called subreads) extracted from each read and allows all the seeds to vote on the optimal location. When the read length is <160 bp, overlapping subreads are used. More conventional alignment algorithms are then used to fill in detailed mismatch and indel information between the subreads that make up the winning voting block. The strategy is fast because the overall genomic location has already been chosen before the detailed alignment is done. It is sensitive because no individual subread is required to map exactly, nor are individual subreads constrained to map close by other subreads. It is accurate because the final location must be supported by several different subreads. The strategy extends easily to find exon junctions, by locating reads that contain sets of subreads mapping to different exons of the same gene. It scales up efficiently for longer reads.
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    Illumina WG-6 BeadChip strips should be normalized separately
    Shi, W ; Banerjee, A ; Ritchie, ME ; Gerondakis, S ; Smyth, GK (BMC, 2009-11-11)
    BACKGROUND: Illumina Sentrix-6 Whole-Genome Expression BeadChips are relatively new microarray platforms which have been used in many microarray studies in the past few years. These Chips have a unique design in which each Chip contains six microarrays and each microarray consists of two separate physical strips, posing special challenges for precise between-array normalization of expression values. RESULTS: None of the normalization strategies proposed so far for this microarray platform allow for the possibility of systematic variation between the two strips comprising each array. That this variation can be substantial is illustrated by a data example. We demonstrate that normalizing at the strip-level rather than at the array-level can effectively remove this between-strip variation, improve the precision of gene expression measurements and discover more differentially expressed genes. The gain is substantial, yielding a 20% increase in statistical information and doubling the number of genes detected at a 5% false discovery rate. Functional analysis reveals that the extra genes found tend to have interesting biological meanings, dramatically strengthening the biological conclusions from the experiment. Strip-level normalization still outperforms array-level normalization when non-expressed probes are filtered out. CONCLUSION: Plots are proposed which demonstrate how the need for strip-level normalization relates to inconsistent intensity range variation between the strips. Strip-level normalization is recommended for the preprocessing of Illumina Sentrix-6 BeadChips whenever the intensity range is seen to be inconsistent between the strips. R code is provided to implement the recommended plots and normalization algorithms.
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    limma powers differential expression analyses for RNA-sequencing and microarray studies
    Ritchie, ME ; Phipson, B ; Wu, D ; Hu, Y ; Law, CW ; Shi, W ; Smyth, GK (OXFORD UNIV PRESS, 2015-04-20)
    limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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    The BTB-ZF transcription factor Zbtb20 is driven by Irf4 to promote plasma cell differentiation and longevity
    Chevrier, S ; Emslie, D ; Shi, W ; Kratina, T ; Wellard, C ; Karnowski, A ; Erikci, E ; Smyth, GK ; Chowdhury, K ; Tarlinton, D ; Corcoran, LM (ROCKEFELLER UNIV PRESS, 2014-05-05)
    The transcriptional network regulating antibody-secreting cell (ASC) differentiation has been extensively studied, but our current understanding is limited. The mechanisms of action of known "master" regulators are still unclear, while the participation of new factors is being revealed. Here, we identify Zbtb20, a Bcl6 homologue, as a novel regulator of late B cell development. Within the B cell lineage, Zbtb20 is specifically expressed in B1 and germinal center B cells and peaks in long-lived bone marrow (BM) ASCs. Unlike Bcl6, an inhibitor of ASC differentiation, ectopic Zbtb20 expression in primary B cells facilitates terminal B cell differentiation to ASCs. In plasma cell lines, Zbtb20 induces cell survival and blocks cell cycle progression. Immunized Zbtb20-deficient mice exhibit curtailed humoral responses and accelerated loss of antigen-specific plasma cells, specifically from the BM pool. Strikingly, Zbtb20 induction does not require Blimp1 but depends directly on Irf4, acting at a newly identified Zbtb20 promoter in ASCs. These results identify Zbtb20 as an important player in late B cell differentiation and provide new insights into this complex process.
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    Integration of microRNA signatures of distinct mammary epithelial cell types with their gene expression and epigenetic portraits
    Pal, B ; Chen, Y ; Bert, A ; Hu, Y ; Sheridan, JM ; Beck, T ; Shi, W ; Satterley, K ; Jamieson, P ; Goodall, GJ ; Lindeman, GJ ; Smyth, GK ; Visvader, JE (BMC, 2015-06-18)
    INTRODUCTION: MicroRNAs (miRNAs) have been implicated in governing lineage specification and differentiation in multiple organs; however, little is known about their specific roles in mammopoiesis. We have determined the global miRNA expression profiles of functionally distinct epithelial subpopulations in mouse and human mammary tissue, and compared these to their cognate transcriptomes and epigenomes. Finally, the human miRNA signatures were used to interrogate the different subtypes of breast cancer, with a view to determining miRNA networks deregulated during oncogenesis. METHODS: RNA from sorted mouse and human mammary cell subpopulations was subjected to miRNA expression analysis using the TaqMan MicroRNA Array. Differentially expressed (DE) miRNAs were correlated with gene expression and histone methylation profiles. Analysis of miRNA signatures of the intrinsic subtypes of breast cancer in The Cancer Genome Atlas (TCGA) database versus those of normal human epithelial subpopulations was performed. RESULTS: Unique miRNA signatures characterized each subset (mammary stem cell (MaSC)/basal, luminal progenitor, mature luminal, stromal), with a high degree of conservation across species. Comparison of miRNA and transcriptome profiles for the epithelial subtypes revealed an inverse relationship and pinpointed key developmental genes. Interestingly, expression of the primate-specific miRNA cluster (19q13.4) was found to be restricted to the MaSC/basal subset. Comparative analysis of miRNA signatures with H3 lysine modification maps of the different epithelial subsets revealed a tight correlation between active or repressive marks for the top DE miRNAs, including derepression of miRNAs in Ezh2-deficient cellular subsets. Interrogation of TCGA-identified miRNA profiles with the miRNA signatures of different human subsets revealed specific relationships. CONCLUSIONS: The derivation of global miRNA expression profiles for the different mammary subpopulations provides a comprehensive resource for understanding the interplay between miRNA networks and target gene expression. These data have highlighted lineage-specific miRNAs and potential miRNA-mRNA networks, some of which are disrupted in neoplasia. Furthermore, our findings suggest that key developmental miRNAs are regulated by global changes in histone modification, thus linking the mammary epigenome with genome-wide changes in the expression of genes and miRNAs. Comparative miRNA signature analyses between normal breast epithelial cells and breast tumors confirmed an important linkage between luminal progenitor cells and basal-like tumors.
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    Whole transcriptome analysis for T cell receptor-affinity and IRF4-regulated clonal expansion of T cells.
    Shi, W ; Man, K ; Smyth, GK ; Nutt, SL ; Kallies, A (Elsevier BV, 2014-12)
    Clonal population expansion of T cells during an immune response is dependent on the affinity of the T cell receptor (TCR) for its antigen [1]. However, there is little understanding of how this process is controlled transcriptionally. We found that the transcription factor IRF4 was induced in a manner dependent on TCR-affinity and was critical for the clonal expansion and maintenance of effector function of antigen-specific CD8(+) T cells. We performed a genome-wide expression profiling experiment using RNA sequencing technology (RNA-seq) to interrogate global expression changes when IRF4 was deleted in CD8(+) T cells activated with either a low or high affinity peptide ligand. This allowed us not only to determine IRF4-dependent transcriptional changes but also to identify transcripts dependent on TCR-affinity [2]. Here we describe in detail the analyses of the RNA-seq data, including quality control, read mapping, quantification, normalization and assessment of differential gene expression. The RNA-seq data can be accessed from Gene Expression Omnibus database (accession number GSE49929).