gganatogram: An R package for modular visualisation of anatograms and tissues based on ggplot2 [version 2; referees: 2 approved]

Displaying data onto anatomical structures is a convenient technique to quickly observe tissue related information. However, drawing tissues is a complex task that requires both expertise in anatomy and the arts. While web based applications exist for displaying gene expression on anatograms, other non-genetic disciplines lack similar tools. Moreover, web based tools often lack the modularity associated with packages in programming languages, such as R. Here I present gganatogram, an R package used to plot modular species anatograms based on a combination of the graphical grammar of ggplot2 and the publicly available anatograms from the Expression Atlas. This combination allows for quick and easy, modular, and reproducible generation of anatograms. Using only one command and a data frame with tissue name, group, colour, and  value, this tool enables the user to visualise specific human and mouse tissues with desired colours, grouped by a variable, or displaying a desired value, such as gene-expression, pharmacokinetics, or bacterial load across selected tissues. gganatogram consists of 5 highly annotated organisms, male/female human/mouse, and a cell anatogram. It further consists of 24 other less annotated organisms from the animal and plant kingdom. I hope that this tool will be useful by the wider community in biological sciences. Community members are welcome to submit additional anatograms, which can be incorporated into the package. A stable version gganatogram has been deposited to neuroconductor, and a development version can be found on github/jespermaag/gganatogram. An interactive shiny app of gganatogram can be found on https://jespermaag.shinyapps.io/gganatogram/, which allows for non-R users to create anatograms

gganatogram: An R package for modular visualisation of anatograms and tissues based on ggplot2 [version 1; referees: 2 approved]

Displaying data onto anatomical structures is a convenient technique to quickly observe tissue related information. However, drawing tissues is a complex task that requires both expertise in anatomy and the arts. While web based applications exist for displaying gene expression on anatograms, other non-genetic disciplines lack similar tools. Moreover, web based tools often lack the modularity associated with packages in programming languages, such as R. Here I present gganatogram, an R package used to plot modular species anatograms based on a combination of the graphical grammar of ggplot2 and the publicly available anatograms from the Expression Atlas. This combination allows for quick and easy, modular, and reproducible generation of anatograms. Using only one command and a data frame with tissue name, group, colour, and value, this tool enables the user to visualise specific human and mouse tissues with desired colours, grouped by a variable, or displaying a desired value, such as gene-expression, pharmacokinetics, or bacterial load across selected tissues. I hope that this tool will be useful by the wider community in biological sciences. Community members are welcome to submit additional anatograms, which can be incorporated into the package. A stable version gganatogram has been deposited to neuroconductor, and a development version can be found on github/jespermaag/gganatogram

Widespread promoter methylation of synaptic plasticity genes in long-term potentiation in the adult brain in vivo.

Background: DNA methylation is a key modulator of gene expression in mammalian development and cellular differentiation, including neurons. To date, the role of DNA modifications in long-term potentiation (LTP) has not been explored. Results: To investigate the occurrence of DNA methylation changes in LTP, we undertook the first detailed study to describe the methylation status of all known LTP-associated genes during LTP induction in the dentate gyrus of live rats. Using a methylated DNA immunoprecipitation (MeDIP)-array, together with previously published matched RNA-seq and public histone modification data, we discover widespread changes in methylation status of LTP-genes. We further show that the expression of many LTP-genes is correlated with their methylation status. We show that these correlated genes are enriched for RNA-processing, active histone marks, and specific transcription factors. These data reveal that the synaptic activity-evoked methylation changes correlates with pre-existing activation of the chromatin landscape. Finally, we show that methylation of Brain-derived neurotrophic factor (Bdnf) CpG-islands correlates with isoform switching from transcripts containing exon IV to exon I. Conclusions: Together, these data provide the first evidence of widespread regulation of methylation status in LTP-associated genes

FOXA1 Mutations Reveal Distinct Chromatin Profiles and Influence Therapeutic Response in Breast Cancer

Mutations in the pioneer transcription factor FOXA1 are a hallmark of estrogen receptor-positive (ER+) breast cancers. Examining FOXA1 in ∼5,000 breast cancer patients identifies several hotspot mutations in the Wing2 region and a breast cancer-specific mutation SY242CS, located in the third β strand. Using a clinico-genomically curated cohort, together with breast cancer models, we find that FOXA1 mutations associate with a lower response to aromatase inhibitors. Mechanistically, Wing2 mutations display increased chromatin binding at ER loci upon estrogen stimulation, and an enhanced ER-mediated transcription without changes in chromatin accessibility. In contrast, SY242CS shows neomorphic properties that include the ability to open distinct chromatin regions and activate an alternative cistrome and transcriptome. Structural modeling predicts that SY242CS confers a conformational change that mediates stable binding to a non-canonical DNA motif. Taken together, our results provide insights into how FOXA1 mutations perturb its function to dictate cancer progression and therapeutic response. [Display omitted] •FOXA1 mutations are enriched in metastatic tumors•FOXA1 mutations are associated with worse outcome to aromatase inhibitors•Wing2 mutations promote an enhanced estrogen response upon estrogen•SY242CS induces alternative chromatin states by binding to a non-canonical motif Arruabarrena-Aristorena et al. determine that mutations in the pioneer transcription factor FOXA1 lower the therapeutic response to aromatase inhibitors in ER+ breast cancer. Mechanistically, two phenotypic groups are established: hypermorphic Wing2 mutants that augment estrogen response, and a neomorphic SY242CS mutant that promotes an alternative pioneering, and cistromic and transcriptomic function