Anna Mantsoki
University of Edinburgh
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Featured researches published by Anna Mantsoki.
Scientific Reports | 2015
Anna Mantsoki; Guillaume Devailly; Anagha Joshi
In embryonic stem (ES) cells, developmental regulators have a characteristic bivalent chromatin signature marked by simultaneous presence of both activation (H3K4me3) and repression (H3K27me3) signals and are thought to be in a ‘poised’ state for subsequent activation or silencing during differentiation. We collected eleven pairs (H3K4me3 and H3K27me3) of ChIP sequencing datasets in human ES cells and eight pairs in murine ES cells, and predicted high-confidence (HC) bivalent promoters. Over 85% of H3K27me3 marked promoters were bivalent in human and mouse ES cells. We found that (i) HC bivalent promoters were enriched for developmental factors and were highly likely to be differentially expressed upon transcription factor perturbation; (ii) murine HC bivalent promoters were occupied by both polycomb repressive component classes (PRC1 and PRC2) and grouped into four distinct clusters with different biological functions; (iii) HC bivalent and active promoters were CpG rich while H3K27me3-only promoters lacked CpG islands. Binding enrichment of distinct sets of regulators distinguished bivalent from active promoters. Moreover, a ‘TCCCC’ sequence motif was specifically enriched in bivalent promoters. Finally, this analysis will serve as a resource for future studies to further understand transcriptional regulation during embryonic development.
Computational Biology and Chemistry | 2016
Anna Mantsoki; Guillaume Devailly; Anagha Joshi
Background Gene expression heterogeneity contributes to development as well as disease progression. Due to technological limitations, most studies to date have focused on differences in mean expression across experimental conditions, rather than differences in gene expression variance. The advent of single cell RNA sequencing has now made it feasible to study gene expression heterogeneity and to characterise genes based on their coefficient of variation. Methods We collected single cell gene expression profiles for 32 human and 39 mouse embryonic stem cells and studied correlation between diverse characteristics such as network connectivity and coefficient of variation (CV) across single cells. We further systematically characterised properties unique to High CV genes. Results Highly expressed genes tended to have a low CV and were enriched for cell cycle genes. In contrast, High CV genes were co-expressed with other High CV genes, were enriched for bivalent (H3K4me3 and H3K27me3) marked promoters and showed enrichment for response to DNA damage and DNA repair. Conclusions Taken together, this analysis demonstrates the divergent characteristics of genes based on their CV. High CV genes tend to form co-expression clusters and they explain bivalency at least in part.
FEBS Letters | 2015
Guillaume Devailly; Anna Mantsoki; Tom Michoel; Anagha Joshi
Genome‐wide data is accumulating in an unprecedented way in the public domain. Re‐mining this data shows great potential to generate novel hypotheses. However this approach is dependent on the quality (technical and biological) of the underlying data. Here we performed a systematic analysis of chromatin immunoprecipitation (ChIP) sequencing data of transcription and epigenetic factors from the encyclopaedia of DNA elements (ENCODE) resource to demonstrate that about one third of conditions with replicates show low concordance between replicate peak lists. This serves as a case study to demonstrate a caveat concerning genome‐wide analyses and highlights a need to validate the quality of each sample before performing further associative analyses.
Bioinformatics | 2016
Guillaume Devailly; Anna Mantsoki; Anagha Joshi
Summary: Better protocols and decreasing costs have made high-throughput sequencing experiments now accessible even to small experimental laboratories. However, comparing one or few experiments generated by an individual lab to the vast amount of relevant data freely available in the public domain might be limited due to lack of bioinformatics expertise. Though several tools, including genome browsers, allow such comparison at a single gene level, they do not provide a genome-wide view. We developed Heat*seq, a web-tool that allows genome scale comparison of high throughput experiments chromatin immuno-precipitation followed by sequencing, RNA-sequencing and Cap Analysis of Gene Expression) provided by a user, to the data in the public domain. Heat*seq currently contains over 12 000 experiments across diverse tissues and cell types in human, mouse and drosophila. Heat*seq displays interactive correlation heatmaps, with an ability to dynamically subset datasets to contextualize user experiments. High quality figures and tables are produced and can be downloaded in multiple formats. Availability and Implementation: Web application: http://www.heatstarseq.roslin.ed.ac.uk/. Source code: https://github.com/gdevailly. Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.
The International Journal of Biochemistry & Cell Biology | 2017
Ángeles Arzalluz-Luque; Guillaume Devailly; Anna Mantsoki; Anagha Joshi
Single cell transcriptomics is becoming a common technique to unravel new biological phenomena whose functional significance can only be understood in the light of differences in gene expression between single cells. The technology is still in its early days and therefore suffers from many technical challenges. This review discusses the continuous effort to identify and systematically characterise various sources of technical variability in single cell expression data and the need to further develop experimental and computational tools and resources to help deal with it.
BMC Developmental Biology | 2018
Anna Mantsoki; Guillaume Devailly; Anagha Joshi
BackgroundMammalian embryonic stem cells display a unique epigenetic and transcriptional state to facilitate pluripotency by maintaining lineage-specification genes in a poised state. Two epigenetic and transcription processes involved in maintaining poised state are bivalent chromatin, characterized by the simultaneous presence of activating and repressive histone methylation marks, and RNA polymerase II (RNAPII) promoter proximal pausing. However, the dynamics of histone modifications and RNAPII at promoters in diverse cellular contexts remains underexplored.ResultsWe collected genome wide data for bivalent chromatin marks H3K4me3 and H3K27me3, and RNAPII (8WG16) occupancy together with expression profiling in eight different cell types, including ESCs, in mouse. The epigenetic and transcription profiles at promoters grouped in over thirty clusters with distinct functional identities and transcription control.ConclusionThe clustering analysis identified distinct bivalent clusters where genes in one cluster retained bivalency across cell types while in the other were mostly cell type specific, but neither showed a high RNAPII pausing. We noted that RNAPII pausing is more associated with active genes than bivalent genes in a cell type, and was globally reduced in differentiated cell types compared to multipotent.
international conference on bioinformatics and biomedical engineering | 2015
Anna Mantsoki; Anagha Joshi
Bivalent promoters are defined by the presence of both activating (H3K4me3) and repressive (H3K27me3) chromatin marks. In this paper, we first identified high confidence bivalent promoters in murine ES cells integrating data across eight studies using two methods; peak-based and cutoff-based. We showed that peak-based method is more reliable as promoters are more enriched for developmental regulators than the cutoff-based method. We further identified bivalent promoters in human and pig using the peak-based method to show that the bivalent promoters conserved across species were highly enriched for embryonic developmental processes.
F1000Research | 2017
Guillaume Devailly; Anna Mantsoki; Anagha Joshi
F1000Research | 2016
Guillaume Devailly; Anna Mantsoki; Anagha Joshi
F1000Research | 2016
Guillaume Devailly; Anna Mantsoki; Anagha Joshi