Biology subjects

Glass, C.

Publications and source records attributed to Glass, C..

7 recordsLinked to original sources

bioRxiv2025

PEAS: Detection of Clustered Differences in Genomic Data

MotivationStudies of genetically-distinct individuals have shown that differences in marks of transcriptional regulation such as chromatin accesibility, transcription factor binding and histone modifications are often proximally clustered along the genome. These proximal clusters, which have been labeled as cis-regulatory domains (CRDs), are thought to reflect topological features of the genome and may demarcate functional units linking genetic variation to transcriptional regulation. The problem of distinguishing CRDs from background variation is computationally difficult and current methods rely on greedy approaches with ad-hoc parameters and do not provide an assessment of statistical significance, an important consideration for investigating CRDs in small sample cohorts. ResultsWe developed a software package, PEAS (Proximal Enrichment by Approximated Sampling), to identify CRDs from a small number of samples (as few as two distinct genetic backgrounds) using a robust statistical approach. PEAS uses methods for efficient and accurate estimation of empirical distributions to quantify the significance of enriched regions, followed by a dynamic programming algorithm to identify the minimum likelihood set of non-overlapping enriched regions. We used it to identify clusters of proximally-enriched differences in the histone mark H3K27ac between two mouse strains as well as proximally-enriched regions of correlation in this mark across five mouse strains. We find that differences in histone acetylation between two mouse strains form signficant clusters that overlap closely with differences in the first principal component of their Hi-C correlation matrices. AvailabilityPEAS is written in Python and is available at https://pypi.org/project/PEAS/. Methods for approximating empirical distributions are implemented in C and Python and are available at https://pypi.org/project/empdist/.

bioinformatics↗

bioRxiv2024

Genetic variation in the activity of a TREM2-p53 signaling axis determines oxygen-inducedlung injury

Bronchopulmonary dysplasia (BPD), a chronic lung disease, is the most common major complication of preterm birth. Supplemental oxygen administration, while lifesaving in the neonatal period, remains a key determinant of BPD pathophysiology. Exposure of the immature lung to increased levels of oxygen elicits an inflammatory response resulting in abnormal lung development. However, not every premature infant is equally sensitive to develop BPD. Using genetically diverse mouse strains, we show that the innate immune response activated in the lungs of mice sensitive to hyperoxia that develop BPD-like lung injury differs from mice resilient to disease. Specifically, we identified a selective upregulation of triggering receptor expressed on myeloid cells 2 (TREM2) on lung macrophages and monocytes in the hyperoxia-sensitive C57BL/6J mouse strain. We show that loss of function of TREM2 signaling in myeloid cells resulted in a dramatically improved phenotype after neonatal hyperoxia exposure characterized by a dampened immune response, preserved alveolar structure, and preserved cell proliferative potential supporting normal lung development. At the molecular level, inhibition of TREM2 signaling dampened the magnitude of p53 activation and resulted in cell cycle arrest instead of apoptosis. These findings show that TREM2 is a critical regulator of the pathogenic innate immune response to hyperoxia and highlight its importance as a potential therapeutic target for mitigating injury in the hyperoxia-exposed developing lung.

immunology↗

bioRxiv2024

Direct and indirect regulation of β- glucocerebrosidase by the transcription factors USF2 and ONECUT2

Mutations in the GBA gene, which encodes the lysosomal enzyme {beta}-glucocerebrosidase (GCase), are the most prevalent genetic susceptibility factor for Parkinsons disease (PD). However, only approximately 20% of carriers develop the disease, suggesting the presence of genetic modifiers influencing the risk of developing PD in the presence of GBA mutations. Here we screened 1,634 human transcription factors (TFs) for their effect on GCase activity in cell lysates of the human glioblastoma line LN-229, into which we introduced the pathogenic GBA L444P variant via adenine base editing. Using a novel arrayed CRISPR activation library, we uncovered 11 TFs as regulators of GCase activity. Among these, activation of MITF and TFEC increased lysosomal GCase activity in live cells, while activation of ONECUT2 and USF2 decreased it. Conversely, ablating USF2 increased GBA mRNA and led to enhanced levels of GCase protein and activity. While MITF, TFEC, and USF2 affected GBA transcription, ONECUT2 was found to control GCase trafficking by modulating the guanine exchange factors PLEKHG4 and PLEKHG4B. Hence, our study provides a systematic approach to identifying modulators of GCase activity, expands the transcriptional landscape of GBA regulation, and deepens our understanding of the mechanisms involved in influencing GCase activity.

molecular biology↗

bioRxiv2023

APOE4/4 is linked to damaging lipid droplets in Alzheimer's microglia

Several genetic risk factors for Alzheimers Disease (AD) implicate genes involved in lipid metabolism and many of these lipid genes are highly expressed in glial cells. However, the relationship between lipid metabolism in glia and AD pathology remains poorly understood. Through single-nucleus RNA-sequencing of AD brain tissue, we have identified a microglial state defined by the expression of the lipid droplet (LD) associated enzyme ACSL1 with ACSL1-positive microglia most abundant in AD patients with the APOE4/4 genotype. In human iPSC-derived microglia (iMG) fibrillar A{beta} (fA{beta}) induces ACSL1 expression, triglyceride synthesis, and LD accumulation in an APOE-dependent manner. Additionally, conditioned media from LD-containing microglia leads to Tau phosphorylation and neurotoxicity in an APOE-dependent manner. Our findings suggest a link between genetic risk factors for AD with microglial LD accumulation and neurotoxic microglial-derived factors, potentially providing novel therapeutic strategies for AD.

neuroscience↗

bioRxiv2022

A resource for generating and manipulating human microglial states in vitro

Microglia have emerged as key players in the pathogenesis of neurodegenerative conditions such as Alzheimers disease (AD). In response to CNS stimuli, these cells adopt distinct transcriptional and functional subtypes known as states. However, an understanding of the function of these states has been elusive, especially in human microglia, due to lack of tools to model and manipulate this cell-type. Here, we provide a platform for modeling human microglia transcriptional states in vitro. Using single-cell RNA sequencing, we found that exposure of human stem-cell differentiated microglia (iMGLs) to brain-related challenges generated extensive transcriptional diversity which mapped to gene signatures identified in human brain microglia. We identified two in vitro transcriptional clusters that were analogous to human and mouse disease-associated microglia (DAMs), a state enriched in neurodegenerative disease contexts. To facilitate scalable functional analyses, we established a lentiviral approach enabling broad and highly efficient genetic transduction of microglia in vitro. Using this new technology, we demonstrated that MITF (Melanocyte Inducing Transcription Factor), an AD-enriched transcription factor in microglia, drives both a disease-associated transcriptional signature and a highly phagocytic state. Finally, we confirmed these results across iMGLs differentiated from multiple iPSC lines demonstrating the broad utility of this platform. Together, these tools provide a comprehensive resource that enables the manipulation and functional interrogation of human microglial states in both homeostatic and disease-relevant contexts.

neuroscience↗

bioRxiv2021

Gene regulatory networks underlying human microglia maturation

The fetal period is a critical time for brain development, characterized by neurogenesis, neural migration, and synaptogenesis1-3. Microglia, the tissue resident macrophages of the brain, are observed as early as the fourth week of gestation4 and are thought to engage in a variety of processes essential for brain development and homeostasis5-11. Conversely, microglia phenotypes are highly regulated by the brain environment12-14. Mechanisms by which human brain development influences the maturation of microglia and microglia potential contribution to neurodevelopmental disorders remain poorly understood. Here, we performed transcriptomic analysis of human fetal and postnatal microglia and corresponding cortical tissue to define age-specific brain environmental factors that may drive microglia phenotypes. Comparative analysis of open chromatin profiles using bulk and single-cell methods in conjunction with a new computational approach that integrates epigenomic and single-cell RNA-seq data allowed decoding of cellular heterogeneity with inference of subtype- and development stage-specific transcriptional regulators. Interrogation of in vivo and in vitro iPSC-derived microglia models provides evidence for roles of putative instructive signals and downstream gene regulatory networks which establish human-specific fetal and postnatal microglia gene expression programs and potentially contribute to neurodevelopmental disorders.

genomics↗

bioRxiv2020

MAGGIE: leveraging genetic variation to identify DNA sequence motifs mediating transcription factor binding and function

Genetic variation in regulatory elements can alter transcription factor (TF) binding by mutating a TF binding motif, which in turn may affect the activity of the regulatory elements. However, it is unclear which TFs are prone to be affected by a given variant. Current motif analysis tools either prioritize TFs based on motif enrichment without linking to a function or are limited in their applications due to the assumption of linearity between motifs and their functional effects. Here, we present MAGGIE, a novel method for identifying motifs mediating TF binding and function. By leveraging measurements from diverse genotypes, MAGGIE uses a statistical approach to link mutation of a motif to changes of an epigenomic feature without assuming a linear relationship. We benchmark MAGGIE across various applications using both simulated and biological datasets and demonstrate its improvement in sensitivity and specificity compared to the state-of-the-art motif analysis approaches. We use MAGGIE to reveal insights into the divergent functions of distinct NF-{kappa}B factors in the pro-inflammatory macrophages, showing its promise in discovering novel functions of TFs. The Python package for MAGGIE is freely available at https://github.com/zeyang-shen/maggie.

bioinformatics↗