School of Mathematics and Statistics - Research Publications

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    Removing unwanted variation from large-scale RNA sequencing data with PRPS
    Molania, R ; Foroutan, M ; Gagnon-Bartsch, JA ; Gandolfo, LC ; Jain, A ; Sinha, A ; Olshansky, G ; Dobrovic, A ; Papenfuss, AT ; Speed, TP (NATURE PORTFOLIO, 2023-01)
    Accurate identification and effective removal of unwanted variation is essential to derive meaningful biological results from RNA sequencing (RNA-seq) data, especially when the data come from large and complex studies. Using RNA-seq data from The Cancer Genome Atlas (TCGA), we examined several sources of unwanted variation and demonstrate here how these can significantly compromise various downstream analyses, including cancer subtype identification, association between gene expression and survival outcomes and gene co-expression analysis. We propose a strategy, called pseudo-replicates of pseudo-samples (PRPS), for deploying our recently developed normalization method, called removing unwanted variation III (RUV-III), to remove the variation caused by library size, tumor purity and batch effects in TCGA RNA-seq data. We illustrate the value of our approach by comparing it to the standard TCGA normalizations on several TCGA RNA-seq datasets. RUV-III with PRPS can be used to integrate and normalize other large transcriptomic datasets coming from multiple laboratories or platforms.
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    Targeting histone acetylation dynamics and oncogenic transcription by catalytic P300/CBP inhibition
    Hogg, SJ ; Motorna, O ; Cluse, LA ; Johanson, TM ; Coughlan, HD ; Raviram, R ; Myers, RM ; Costacurta, M ; Todorovski, I ; Pijpers, L ; Bjelosevic, S ; Williams, T ; Huskins, SN ; Kearney, CJ ; Devlin, JR ; Fan, Z ; Jabbari, JS ; Martin, BP ; Fareh, M ; Kelly, MJ ; Dupere-Richer, D ; Sandow, JJ ; Feran, B ; Knight, D ; Khong, T ; Spencer, A ; Harrison, SJ ; Gregory, G ; Wickramasinghe, VO ; Webb, A ; Taberlay, PC ; Bromberg, KD ; Lai, A ; Papenfuss, AT ; Smyth, GK ; Allan, RS ; Licht, JD ; Landau, DA ; Abdel-Wahab, O ; Shortt, J ; Vervoort, SJ ; Johnstone, RW (CELL PRESS, 2021-05-20)
    To separate causal effects of histone acetylation on chromatin accessibility and transcriptional output, we used integrated epigenomic and transcriptomic analyses following acute inhibition of major cellular lysine acetyltransferases P300 and CBP in hematological malignancies. We found that catalytic P300/CBP inhibition dynamically perturbs steady-state acetylation kinetics and suppresses oncogenic transcriptional networks in the absence of changes to chromatin accessibility. CRISPR-Cas9 screening identified NCOR1 and HDAC3 transcriptional co-repressors as the principal antagonists of P300/CBP by counteracting acetylation turnover kinetics. Finally, deacetylation of H3K27 provides nucleation sites for reciprocal methylation switching, a feature that can be exploited therapeutically by concomitant KDM6A and P300/CBP inhibition. Overall, this study indicates that the steady-state histone acetylation-methylation equilibrium functions as a molecular rheostat governing cellular transcription that is amenable to therapeutic exploitation as an anti-cancer regimen.
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    Evolutionary analyses of the major variant surface antigen-encoding genes reveal population structure of Plasmodium falciparum within and between continents
    Tonkin-Hill, G ; Ruybal-Pesantez, S ; Tiedje, KE ; Rougeron, V ; Duffy, MF ; Zakeri, S ; Pumpaibool, T ; Harnyuttanakorn, P ; Branch, OH ; Ruiz-Mesia, L ; Rask, TS ; Prugnolle, F ; Papenfuss, AT ; Chan, Y-B ; Day, KP ; Buchrieser, C (PUBLIC LIBRARY SCIENCE, 2021-02)
    Malaria remains a major public health problem in many countries. Unlike influenza and HIV, where diversity in immunodominant surface antigens is understood geographically to inform disease surveillance, relatively little is known about the global population structure of PfEMP1, the major variant surface antigen of the malaria parasite Plasmodium falciparum. The complexity of the var multigene family that encodes PfEMP1 and that diversifies by recombination, has so far precluded its use in malaria surveillance. Recent studies have demonstrated that cost-effective deep sequencing of the region of var genes encoding the PfEMP1 DBLα domain and subsequent classification of within host sequences at 96% identity to define unique DBLα types, can reveal structure and strain dynamics within countries. However, to date there has not been a comprehensive comparison of these DBLα types between countries. By leveraging a bioinformatic approach (jumping hidden Markov model) designed specifically for the analysis of recombination within var genes and applying it to a dataset of DBLα types from 10 countries, we are able to describe population structure of DBLα types at the global scale. The sensitivity of the approach allows for the comparison of the global dataset to ape samples of Plasmodium Laverania species. Our analyses show that the evolution of the parasite population emerging out of Africa underlies current patterns of DBLα type diversity. Most importantly, we can distinguish geographic population structure within Africa between Gabon and Ghana in West Africa and Uganda in East Africa. Our evolutionary findings have translational implications in the context of globalization. Firstly, DBLα type diversity can provide a simple diagnostic framework for geographic surveillance of the rapidly evolving transmission dynamics of P. falciparum. It can also inform efforts to understand the presence or absence of global, regional and local population immunity to major surface antigen variants. Additionally, we identify a number of highly conserved DBLα types that are present globally that may be of biological significance and warrant further characterization.