Training data for ChIP-seq data analysis (Galaxy Training Material): Identification of the binding sites of the Estrogen receptor

<p>The data provided here are part of a Galaxy Training Network tutorial that analyzes ChIP-seq data from a study published by Ross-Inness et al., 2012 (DOI:10.1038/nature10730) to identify the binding sites of the Estrogen receptor, a transcription factor known to be associated with different types of breast cancer.</p

deeptools/HiCExplorer: Fall 2023 maintenance update

&lt;ul&gt; &lt;li&gt;Maintenance update for HiCExplorer to keep up to date with APIs of dependencies&lt;/li&gt; &lt;li&gt;Add the polarization ratio to the output of hicCompartmentalization. Thanks @contessoto.&lt;/li&gt; &lt;/ul&gt

An autoimmune stem-like CD8 T cell population drives type 1 diabetes

CD8 T cell-mediated autoimmune diseases result from the breakdown of self-tolerance mechanisms in autoreactive CD8 T cells1. How autoimmune T cell populations arise and are sustained and the molecular programs defining the autoimmune T cell state are unknown. In Type 1 diabetes (T1D), beta cell-specific CD8 T cells destroy insulin-producing beta cells. We followed the fate of beta cell-specific CD8 T cells in non-obese diabetic mice throughout the course of T1D. We identified a stem-like autoimmune progenitor (AP) population in the pancreatic draining lymph node (pLN), which self-renews and gives rise to pLN autoimmune mediators (AM). pLN AM migrate to the pancreas, where they differentiate further and destroy beta cells. While transplantation of as few as 20 AP induced T1D, as many as 100,000 pancreatic AM failed to do so. Pancreatic AM are short-lived and stem-like AP must continuously seed the pancreas to sustain beta cell destruction. Single cell RNA-sequencing and clonal analysis revealed that autoimmune CD8 T cells represent unique T cell differentiation states and identified features driving the transition from AP to AM. Strategies aimed at targeting the stem-like AP pool could emerge as novel and powerful immunotherapeutic interventions for T1D

A reversible epigenetic memory of inflammatory injury controls lineage plasticity and tumor initiation in the mouse pancreas

Inflammation is essential to the disruption of tissue homeostasis and can destabilize the identity of lineage-committed epithelial cells. Here, we employ lineage-traced mouse models, single-cell transcriptomic and chromatin analyses, and CUT&TAG to identify an epigenetic memory of inflammatory injury in the pancreatic acinar cell compartment. Despite resolution of pancreatitis, our data show that acinar cells fail to return to their molecular baseline, with retention of elevated chromatin accessibility and H3K4me1 at metaplasia genes, such that memory represents an incomplete cell fate decision. In vivo, we find this epigenetic memory controls lineage plasticity, with diminished metaplasia in response to a second insult but increased tumorigenesis with an oncogenic Kras mutation. The lowered threshold for oncogenic transformation, in turn, can be restored by blockade of MAPK signaling. Together, we define the chromatin dynamics, molecular encoding, and recall of a prolonged epigenetic memory of inflammatory injury that impacts future responses but remains reversible

deeptools/deepTools: 3.5.4

error handling + cases for bwAverage with > 2 samples (@lldelisle ) Tick.label deprecated for matplotlib 3.8 (@lldelisle ) matplotlib minimal version is now 3.5 cicd update for pypi pus

deeptools/deepTools: 3.5.4

error handling + cases for bwAverage with > 2 samples (@lldelisle) tick.label deprecation for compatibility with matplotlib 3.8 (@lldelisle) matplotlib minimal version from 3.3 to 3.5 pypi upload cicd stricter check for tag creatio

A beta cell subset with enhanced insulin secretion and glucose metabolism is reduced in type 2 diabetes.

The pancreatic islets are composed of discrete hormone-producing cells that orchestrate systemic glucose homeostasis. Here we identify subsets of beta cells using a single-cell transcriptomic approach. One subset of beta cells marked by high CD63 expression is enriched for the expression of mitochondrial metabolism genes and exhibits higher mitochondrial respiration compared with CD63lo beta cells. Human and murine pseudo-islets derived from CD63hi beta cells demonstrate enhanced glucose-stimulated insulin secretion compared with pseudo-islets from CD63lo beta cells. We show that CD63hi beta cells are diminished in mouse models of and in humans with type 2 diabetes. Finally, transplantation of pseudo-islets generated from CD63hi but not CD63lo beta cells into diabetic mice restores glucose homeostasis. These findings suggest that loss of a specific subset of beta cells may lead to diabetes. Strategies to reconstitute or maintain CD63hi beta cells may represent a potential anti-diabetic therapy

deeptools/deepTools: 3.5.4

error handling fix and cases for bigwigAverage for > 2 samples (@lldelisle) Tick.label deprecation to support matplotlib 3.8 matplotlib minimal supported version from 3.3 to 3.5 tag check changes in pypi upload actio