Biology subjects

Cooper, S. J.

Publications and source records attributed to Cooper, S. J..

10 recordsLinked to original sources

bioRxiv2023

MAPT expression is regulated by long-range interactions with cis-regulatory elements

BackgroundTauopathies are a group of neurodegenerative diseases driven by abnormal aggregates of tau, a microtubule associated protein encoded by the MAPT gene. MAPT expression is absent in neural progenitor cells (NPCs) and increases during differentiation. This temporally dynamic expression pattern suggests that MAPT expression is controlled by transcription factors and cis-regulatory elements specific to differentiated cell types. Given the relevance of MAPT expression to neurodegeneration pathogenesis, identification of such elements is relevant to understanding genetic risk factors. MethodsWe performed HiC, chromatin conformation capture (Capture-C), single-nucleus multiomics (RNA-seq+ATAC-seq), bulk ATAC-seq, and ChIP-seq for H3K27Ac and CTCF in NPCs and neurons differentiated from human iPSC cultures. We nominated candidate cis-regulatory elements (cCREs) for MAPT in human NPCs, differentiated neurons, and pure cultures of inhibitory and excitatory neurons. We then assayed these cCREs using luciferase assays and CRISPR interference (CRISPRi) experiments to measure their effects on MAPT expression. Finally, we integrated cCRE annotations into an analysis of genetic variation in AD cases and controls. ResultsUsing orthogonal genomics approaches, we nominated 94 cCREs for MAPT, including the identification of cCREs specifically active in differentiated neurons. Eleven regions enhanced reporter gene transcription in luciferase assays. Using CRISPRi, 5 of the 94 regions tested were identified as necessary for MAPT expression as measured by RT-qPCR and RNA-seq. Rare and predicted damaging genetic variation in both nominated and confirmed CREs was depleted in AD cases relative to controls (OR = 0.40, p = 0.004), consistent with the hypothesis that variants that disrupt MAPT enhancer activity, and thereby reduce MAPT expression, may be protective against neurodegenerative disease. ConclusionsWe identified both proximal and distal regulatory elements for MAPT and confirmed the regulatory function for several regions, including three regions centromeric to MAPT beyond the well-described H1/H2 haplotype inversion breakpoint. This study provides compelling evidence for pursuing detailed knowledge of CREs for genes of interest to permit better understanding of disease risk.

genomics↗

bioRxiv2022

Transcriptomic and functional analysis of ANGPTL4 overexpression in pancreatic cancer nominates novel drug targets that reverse chemoresistance

BackgroundPancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers based on five-year survival rates. Genes contributing to chemoresistance represent novel therapeutic targets that can improve treatment response. Increased expression of ANGPTL4 in tumors correlates with poor outcomes in pancreatic cancer. MethodsWe used statistical analysis of publicly available gene expression data (TCGA-PAAD) to test whether expression of ANGPTL4 and its downstream targets, ITGB4 and APOL1, were correlated with patient survival. We measured the impact of ANGPTL4 overexpression in a common pancreatic cancer cell line, MIA PaCa-2 cells, using CRISPRa for overexpression and DsiRNA for knockdown. We characterized global gene expression changes associated with high levels of ANGPTL4 and response to gemcitabine treatment using RNA-sequencing. Gemcitabine dose response curves were calculated on modified cell lines by measuring cell viability with CellTiter-Glo (Promega). Impacts on cell migration were measured using a time course scratch assay. ResultsWe show that ANGPTL4 overexpression leads to in vitro resistance to gemcitabine and reduced survival times in patients. Overexpression of ANGPTL4 induces transcriptional signatures of tumor invasion and metastasis, proliferation and differentiation, and inhibition of apoptosis. Analyses revealed an overlapping signature of genes associated with both ANGPTL4 activation and gemcitabine response. Increased expression of the genes in this signature in patient PDAC tissues was significantly associated with shorter patient survival. We identified 42 genes that were both co-regulated with ANGPTL4 and were responsive to gemcitabine treatment. ITGB4 and APOL1 were among these genes. Knockdown of either of these genes in cell lines overexpressing ANGPTL4 reversed the observed gemcitabine resistance and inhibited cellular migration associated with epithelial to mesenchymal transition (EMT) and ANGPTL4 overexpression. ConclusionsThese data suggest that ANGPTL4 promotes EMT and regulates the genes APOL1 and ITGB4. Importantly, we show that inhibition of both targets reverses chemoresistance and decreases migratory potential. Our findings have revealed a novel pathway regulating tumor response to treatment and suggest relevant therapeutic targets in pancreatic cancer.

cancer biology↗

bioRxiv2022

Highly dynamic evolution of the chemosensory gene repertoire driven by gene gain and expansion across subterranean beetles

Chemical cues in subterranean habitats differ highly from those on the surface due to the contrasting environmental conditions, such as absolute darkness, high humidity or food scarcity. Subterranean animals underwent changes to their sensory systems to facilitate the perception of essential stimuli for underground lifestyles. Despite representing unique systems to understand biological adaptation, the genomic basis of chemosensation across cave-dwelling species remains unexplored from a macroevolutionary perspective. Here, we explore the evolution of chemoreception in three beetle tribes that underwent at least six independent transitions to the underground, through a phylogenomics spyglass. Our findings suggest that the chemosensory gene repertoire varies dramatically between species. Overall, no parallel changes in the net rate of evolution of chemosensory gene families were detected prior, during, or after the habitat shift among subterranean lineages. Contrarily, we found evidence of lineage-specific changes within surface and subterranean lineages. However, our results reveal key duplications and losses shared between some of the lineages transitioning to the underground, including the loss of sugar receptors and gene duplications of the highly conserved ionotropic receptors IR25a and IR8a, involved in thermal and humidity sensing among other olfactory roles in insects. These duplications were detected both in independent subterranean lineages and their surface relatives, suggesting parallel evolution of these genes across lineages giving rise to cave-dwelling species. Overall, our results shed light on the genomic basis of chemoreception in subterranean beetles and contribute to our understanding of the genomic underpinnings of adaptation to the subterranean lifestyle at a macroevolutionary scale.

evolutionary biology↗

bioRxiv2022

HDAC1 overexpression alters GTPase activity impacting chemoresistance in pancreatic cancer

Novel strategies are needed to combat multidrug resistance in pancreatic ductal adenocarcinoma (PDAC). We applied genomic approaches to understand mechanisms of resistance in order to better inform treatment and precision medicine. Altered function of chromatin remodeling complexes contribute to chemoresistance. Our study generates and analyzes genomic and biochemical data from PDAC cells overexpressing HDAC1, a histone deacetylase involved in several chromatin remodeling complexes. We characterized the impact of overexpression on drug response, gene expression, HDAC1 binding, and chromatin structure using RNA-sequencing and ChIP-sequencing for HDAC1 and H3K27 acetylation. Integrative genomic analysis shows that HDAC1 overexpression promotes activation of key resistance pathways including epithelial to mesenchymal transition, cell cycle, and apoptosis through global chromatin remodeling. Target genes are similarly altered in patient tissues and show correlation with patient survival. We also demonstrate that direct targets of HDAC1 that also show altered chromatin are enriched near genes associated with altered GTPase activity. HDAC1 target genes identified using in vitro methods and observed in patient tissues were used to develop a clinically relevant nine-transcript signature associated with patient prognosis. Integration of multiple genomic and biochemical data types enables understanding of multidrug resistance and tumorigenesis in PDAC, a disease in desperate need of novel treatment strategies.

cancer biology↗

bioRxiv2019

Dissecting the regulatory activity and key sequence elements of loci with exceptional numbers of transcription factor associations

DNA associated proteins (DAPs) classically regulate gene expression by binding to regulatory loci such as enhancers or promoters. As expanding catalogs of genome-wide DAP binding maps reveal thousands of loci that, unlike the majority of conventional enhancers and promoters, associate with dozens of different DAPs with apparently little regard for motif preference, an understanding of DAP association and coordination at such regulatory loci is essential to deciphering how these regions contribute to normal development and disease. In this study, we aggregated publicly available ChIP-seq data from 469 human DAPs assayed in three cell lines and integrated these data with an orthogonal dataset of 352 non-redundant, in vitro-derived motifs mapped to the genome within DNase hypersensitivity footprints in an effort to characterize regions of the genome that have exceptionally high numbers of DAP associations. We subsequently performed a massively parallel mutagenesis assay to search for sequence elements driving transcriptional activity at such loci and explored plausible biological mechanisms underlying their formation. We establish a generalizable definition for High Occupancy Target (HOT) loci and identify putative driver DAP motifs in HEPG2 cells, including HNF4A, SP1, SP5, and ETV4, that are highly prevalent and exhibit sequence conservation at HOT loci. The number of different DAPs associated with an element is positively associated with evidence of regulatory activity and, by systematically mutating 245 HOT loci, we localized regulatory activity to a central core region that depends on the motif sequences of our previously nominated driver DAPs. In sum, this work leverages the increasingly large number of DAP motif and ChIP-seq data publicly available to explore how DAP associations contribute to genome-wide transcriptional regulation.

genomics↗

bioRxiv2019

Hotspot coevolution at protein-protein interfaces is a key identifier of native protein complexes

Protein-protein interactions play a key role in mediating numerous biological functions, with more than half the proteins in living organisms existing as either homo- or hetero-oligomeric assemblies. Protein subunits that form oligomers minimize the free energy of the complex, but exhaustive computational search-based docking methods have not comprehensively addressed the protein docking challenge of distinguishing a natively bound complex from non-native forms. In this study, we propose a scoring function, KFC-E, that accounts for both conservation and coevolution of putative binding hotspot residues at protein-protein interfaces. For a benchmark set of 53 bound complexes, KFC-E identifies a near-native binding mode as the top-scoring pose in 38% and in the top 5 in 55% of the complexes. For a set of 17 unbound complexes, KFC-E identifies a near-native pose in the top 10 ranked poses in more than 50% of the cases. By contrast, a scoring function that incorporates information on coevolution at predicted non-hotspots performs poorly by comparison. Our study highlights the importance of coevolution at hotspot residues in forming natively bound complexes and suggests a novel approach for coevolutionary scoring in protein docking.\n\nAuthor SummaryA fundamental problem in biology is to distinguish between the native and non-native bound forms of protein-protein complexes. Experimental methods are often used to detect the native bound forms of proteins but, are demanding in terms of time and resources. Computational approaches have proven to be a useful alternative; they sample the different binding configurations for a pair of interacting proteins and then use an heuristic or physical model to score them. In this study we propose a new scoring approach, KFC-E, which focuses on the evolutionary contributions from a subset of key interface residues (hotspots) to identify native bound complexes. KFC-E capitalizes on the wealth of information in protein sequence databases by incorporating residue-level conservation and coevolution of putative binding hotspots. As hotspot residues mediate the binding energetics of protein-protein interactions, we hypothesize that the knowledge of putative hotspots coupled with their evolutionary information should be helpful in the identification of native bound protein-protein complexes.

bioinformatics↗

bioRxiv2019

High-throughput identification of genes involved in single and multi-drug resistance in pancreatic cancer with pooled CRISPR screening

Pancreatic ductal adenocarcinoma (PDAC) patients suffer poor outcomes in part due to therapeutic resistance. We conducted four genome-wide CRISPR activation (CRISPRact) and CRISPR knock out (CRISPRko) screens to identify novel resistance mechanisms to four cytotoxic chemotherapies (gemcitabine, 5-fluorouracil, irinotecan, and oxaliplatin). ABCG2, a well-described efflux pump was the strongest mediator of resistance. We showed that overexpressing HDAC1 altered promoter occupancy and expression of genes involved in the epithelial-to-mesenchymal transition. Using the results of our CRISPR screens, we predicted drug sensitivity for patients and cell lines based on gene expression profiles. These predictions could be clinically useful for treatment selection.

genomics↗

bioRxiv2018

powerTCR: a model-based approach to comparative analysis of the clone size distribution of the T cell receptor repertoire

Sequencing of the T cell receptor repertoire is a powerful tool for deeper study of immune response, but the unique structure of this type of data makes its meaningful quantification challenging. We introduce a new method, the Gamma-GPD spliced threshold model, to address this difficulty. This biologically interpretable model captures the distribution of the TCR repertoire, demonstrates stability across varying sequencing depths, and permits comparative analysis across any number of sampled individuals. We apply our method to several datasets and obtain insights regarding the differentiating features in the T cell receptor repertoire among sampled individuals across conditions. We have implemented our method in the open-source R package powerTCR.\n\nAuthor summaryA more detailed understanding of the immune response can unlock critical information concerning diagnosis and treatment of disease. Here, in particular, we study T cells through T cell receptor sequencing, as T cells play a vital role in immune response. One important feature of T cell receptor sequencing data is the frequencies of each receptor in a given sample. These frequencies harbor global information about the landscape of the immune response. We introduce a flexible method that extracts this information by modeling the distribution of these frequencies, and show that it can be used to quantify differences in samples from individuals of different biological conditions.

immunology↗

bioRxiv2017

R2DGC: Threshold-free peak alignment and identification for 2D gas chromatography mass in R

Summary: Comprehensive two dimensional gas chromatography-mass spectrometry is a powerful method for analyzing complex mixtures of volatile compounds. This method produces a large amount of raw data that requires downstream processing to align signals of interest (peaks) across multiple samples and match peak characteristics to reference standard libraries prior to downstream statistical analysis. To address the paucity of applications addressing this need, we have developed an R package that implements retention time and mass spectra similarity threshold-free alignments, seamlessly integrates retention time standards for universally reproducible alignments, performs common ion filtering, and provides compatibility with multiple peak quantification methods. We demonstrate the packages utility on a controlled mix of metabolite standards separated under variable chromatography conditions and data generated from cell lines.\n\nAvailability and documentation: R2DGC can be downloaded at https://github.com/rramaker/R2DGC or installed via the Comprehensive R Archive Network (CRAN).\n\nContact: sjcooper@hudsonalpha.org\n\nSupplementary information: Supplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2017

A genome-wide interactome of DNA-associated proteins in the human liver

Large-scale efforts like the Encyclopedia of DNA Elements (ENCODE) Project have made tremendous progress in cataloging the genomic binding patterns of DNA-associated proteins (DAPs), such as transcription factors (TFs). However most chromatin immunoprecipitation-sequencing (ChIP-seq) analyses have focused on a few immortalized cell lines whose activities and physiology deviate in important ways from endogenous cells and tissues. Consequently, binding data from primary human tissue are essential to improving our understanding of in vivo gene regulation. Here we analyze ChIP-seq data for 20 DAPs assayed in two healthy human liver tissue samples, identifying more than 450,000 binding sites. We integrated binding data with transcriptome and phased whole genome data to investigate allelic DAP interactions and the impact of heterozygous sequence variation on the expression of neighboring genes. We find our tissue-based dataset demonstrates binding patterns more consistent with liver biology than cell lines, and describe uses of these data to better prioritize impactful non-coding variation. Collectively, our rich dataset offers novel insights into genome function in healthy liver tissue and provides a valuable research resource for assessing disease-related disruptions.

genomics↗