Biology subjects

Powell, J.

Publications and source records attributed to Powell, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

A DNA-based molecular clamp for probing protein interactions and structure under force.

Cellular mechanotransduction, a process central to cell biology, embryogenesis, adult physiology and multiple diseases, is thought to be mediated by force-driven changes in protein conformation that control protein function. However, methods to study proteins under defined mechanical loads on a biochemical scale are lacking. We report the development of a DNA based device in which the transition between single-stranded and double-stranded DNA applies tension to an attached protein. Using a fragment of the talin rod domain as a test case, negative-stain electron microscopy reveals programmable extension while pull down assays show tension-induced binding to two ligands, ARPC5L and vinculin, known to bind to cryptic sites inside the talin structure. These results demonstrate the utility of the DNA clamp for biochemical studies and potential structural analysis.

bioengineering↗

bioRxiv2024

Protein Translation Dysregulation and Immune Cell Evasion Define Metastatic Clones in HPV-related Cancer of the Oropharynx

Head and neck cancers, representing the seventh most common malignancy globally, have seen a shift in causative factors from traditional smoking and alcohol use to human papillomavirus (HPV) infection, now accounting for up to 80% of oropharyngeal cancers. We identify the cellular and clonal mechanisms underlying immune avoidance and metastasis by analysing single-cell and spatial genomic data from primary and metastatic cancers. We first map the clonal evolution of malignant cells based on the accumulation of mutations. We identify metastasising clones based on mutational similarity scores between cells in the primary and lymph node metastasis. Genomic analysis of metastasising and non-metastasising clones identified virally mediated protein translation relief (P=4.24x10-24) pathway underlying metastatic expansion. We show that in metastatic clones, this process is driven through upregulation of transition-initiating factors, EIF4E (P=1.5x10-13) and EIFG1 (P<2.22x10-16), and suppression of regulatory kinases EIF4EBP1 (P=2.1x10), EIF2AK2 (P<2.22x10-16), and EIF2S1 (P<2.22x10-16). We subsequently identify that metastatic clones have a corresponding downregulation of the JAK/STAT pathway and immunoproteasome genes PSMB8 (P<2.22x10- 16) and PSMB9 (P<2.22x10-16), suggesting these clones escape immune surveillance through decreased INF inflammatory response and antigen presentation. We validate these results using spatial RNA-seq data, where metastatic cancer clones show decreased cell-to-cell interactions with CD4 T-effector memory cells (CD4TEM) (P=0.0077), CD8 T-exhausted cells (CD8Ex) (P=0.0191), and innate lymphoid cells (ILC) (P=0.04). Finally, we demonstrate that the upregulation of cap-independent translational drives cell proliferation in metastatic clones through the expression of translation initiation factors (EIF4G1: P<2.22x10-16). Our results provide evidence of the mechanisms by which virally induced cancer clones lead to advanced disease and poor prognosis in patients.

cancer biology↗

bioRxiv2024

Deep sequencing of proteotoxicity modifier genes uncovers a Presenilin-2/beta-amyloid-actin genetic risk module shared among alpha-synucleinopathies

Whether neurodegenerative diseases linked to misfolding of the same protein share genetic risk drivers or whether different protein-aggregation pathologies in neurodegeneration are mechanistically related remains uncertain. Conventional genetic analyses are underpowered to address these questions. Through careful selection of patients based on protein aggregation phenotype (rather than clinical diagnosis) we can increase statistical power to detect associated variants in a targeted set of genes that modify proteotoxicities. Genetic modifiers of alpha-synuclein ([a]S) and beta-amyloid (A{beta}) cytotoxicity in yeast are enriched in risk factors for Parkinsons disease (PD) and Alzheimers disease (AD), respectively. Here, along with known AD/PD risk genes, we deeply sequenced exomes of 430 [a]S/A{beta} modifier genes in patients across alpha-synucleinopathies (PD, Lewy body dementia and multiple system atrophy). Beyond known PD genes GBA1 and LRRK2, rare variants AD genes (CD33, CR1 and PSEN2) and A{beta} toxicity modifiers involved in RhoA/actin cytoskeleton regulation (ARGHEF1, ARHGEF28, MICAL3, PASK, PKN2, PSEN2) were shared risk factors across synucleinopathies. Actin pathology occurred in iPSC synucleinopathy models and RhoA downregulation exacerbated [a]S pathology. Even in sporadic PD, the expression of these genes was altered across CNS cell types. Genome-wide CRISPR screens revealed the essentiality of PSEN2 in both human cortical and dopaminergic neurons, and PSEN2 mutation carriers exhibited diffuse brainstem and cortical synucleinopathy independent of AD pathology. PSEN2 contributes to a common-risk signal in PD GWAS and regulates [a]S expression in neurons. Our results identify convergent mechanisms across synucleinopathies, some shared with AD.

genomics↗

bioRxiv2024

Discovery and characterization of chromosomal inversions in the arboviral vector mosquito Aedes aegypti

Chromosomal inversions play a fundamental role in evolution and have been shown to regulate epidemiologically important traits in malaria mosquitoes. However, they have never been characterized in Aedes aegypti, the major vector of arboviruses, because of the poor structure of its polytene chromosomes. In this study, we applied a Hi-C proximity ligation approach to identify chromosomal inversions in 25 strains of Ae. aegypti, acquired from its worldwide distribution, as well as in one strain of Ae. mascarensis. The study identified 21 multi-megabase inversions with uneven distributions along the three chromosomes. All chromosomal inversions, including one specific for Ae. mascarensis, were polymorphic. Nevertheless, geographic origin separated the strains into two clusters carrying African and non-African inversions suggesting their potential association with Ae. aegypti subspecies. Some of the inversions colocalized with chemoreceptor genes and quantitative trait loci associated with pathogen infection, implicating the potential role of inversions in host choice and disease transmission.

evolutionary biology↗

bioRxiv2023

Salmonella impairs macrophage immunity through effector-independent rapid translational induction in response to membrane puncture by the SPI-1 injectisome

During bacterial infection both the host cell and its invader must divert intracellular resources to synthesise specific proteins in a timely manner. For the host, these factors may be needed for innate immune responses, including programmed cell death, and in the bacteria newly synthesized proteins may be survival factors needed to counteract host responses. Salmonella is an important food-borne bacterial pathogen that invades and multiplies within host cells. It is well established that invasion of epithelial cells is dependent upon the SPI-1 Type III injectisome, a biological needle that penetrates and secretes effectors into host cells to promote internalization. However, the importance of the SPI-1 injectisome in infection of professional phagocytes such as macrophages, which are the predominant host cell type during systemic infection, is less clear. Through time resolved parallel transcriptomic and translatomic studies of macrophage infection, we revealed that SPI-1 injectisome-dependent infection of macrophages triggers rapid translation of transcription factor mRNAs, including Early Growth Response 1 (Egr1). Despite the short half-life of EGR1 protein, its swift synthesis within the initial hour of infection is sufficient to inhibit transcription of pro-inflammatory genes and thereby restrain inflammatory responses and programmed cell death within the first hour of during early infection. This transient period of inflammatory suppression in macrophages is exploited by Salmonella to establish infection and sheds new insight on the importance of translational activation in host-pathogen dynamics during Salmonella infection.

molecular biology↗

bioRxiv2023

High throughput functional profiling of genes at intraocular pressure loci reveals distinct networks for glaucoma

INTRODUCTIONPrimary open angle glaucoma (POAG) is a leading cause of blindness globally. Characterised by progressive retinal ganglion cell degeneration, the precise pathogenesis remains unknown. Genome-wide association studies (GWAS) have uncovered many genetic variants associated with elevated intraocular pressure (IOP), one of the key risk factors for POAG. This study sought to investigate the morphological and transcriptional consequences of perturbation of key genes at IOP loci in trabecular meshwork cell (TMC); the cellular regulators of IOP. We aimed to identify genetic and morphological variation that can be attributed to TMC dysfunction and raised IOP in POAG. METHODS62 genes across 55 loci were knocked-out in a primary human TMC line. Each knockout group, including five non-targeting control groups, underwent single-cell RNA-sequencing (scRNA-seq) for differentially-expressed gene (DEG) analysis. Multiplexed fluorescent staining of key organelles, was coupled with high-throughput microscopy for single-cell morphological analysis using CellProfiler image analysis. RESULTSAcross many of the individual gene knockouts scRNA-seq highlighted genes relating to matrix metalloproteinases and interferon-induced proteins. Our work has prioritised genes at four loci of interest to identify gene knockouts that may contribute to the pathogenesis of POAG, including ANGPTL2, LMX1B, CAV1, and KREMEN1. Three genetic networks of gene knockouts with similar transcriptomic profiles were identified (ABO / CAV1 / MYOC, ANGPT2 / PKHD1 / TNS1 / TXNRD2, and CAPZA1 / KALRN / LMO7 / PLEKHA7 / GNB1L / TEX41), suggesting a synergistic function in trabecular meshwork cell physiology. TEK knockout caused significant upregulation of nuclear granularity on morphological analysis, whilst knockout of TRIOBP, TMCO1 and PLEKHA7 increased granularity and intensity of actin and the cell-membrane. CONCLUSIONHigh throughput analysis of cellular structure and function through multiplex fluorescent single-cell analysis and scRNA-seq assays enabled the direct study of genetic perturbations at the single-cell resolution. This work provides a framework for investigating the role of genes in the pathogenesis of glaucoma and heterogenous diseases with a strong genetic basis.

genetics↗

bioRxiv2023

The distinct translational landscapes of Gram-positive and Gram-negative bacteria

Translational control in pathogenic bacteria is fundamental to gene expression and affects virulence and other infection phenotypes. We used an enhanced ribosome profiling protocol coupled with parallel transcriptomics to capture accurately the global translatome of two evolutionarily distant pathogenic bacteria - the Gram-negative bacterium Salmonella and the Gram positive bacterium Listeria We find that the two bacteria use different mechanisms to translationally regulate protein synthesis. In Salmonella, in addition to the expected correlation between translational efficiency and cis-regulatory features such as Shine-Dalgarno (SD) strength and RNA secondary structure around the initiation codon, our data reveal an effect of the 2nd and 3rd codons, where the presence of tandem lysine codons (AAA-AAA) enhances translation in both Salmonella and E. coli. Strikingly, none of these features are seen in efficiently translated Listeria transcripts. Instead, approximately 15% of efficiently translated Listeria genes exhibit 70S footprints seven nt upstream of the authentic start codon, suggesting that these genes may be subject to a novel translational initiation mechanism. Our results show that SD strength is not a direct hallmark of translational efficiency in all bacteria. Instead, Listeria has evolved additional mechanisms to control gene expression level that are distinct from those utilised by Salmonella and E. coli. For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising

microbiology↗

bioRxiv2023

An experimental comparison of the Digital Spatial Profiling and Visium spatial transcriptomics technologies for cancer research

BackgroundSpatial transcriptomic technologies are powerful tools for resolving the spatial heterogeneity of gene expression in tissue samples. However, little evidence exists on relative strengths and weaknesses of the various available technologies for profiling human tumour tissue. In this study, we aimed to provide an objective assessment of two common spatial transcriptomics platforms, 10X Genomics Visium and Nanostrings GeoMx DSP. MethodThe abilities of the DSP and Visium platforms to profile transcriptomic features were compared using matching cell line and primary breast cancer tissue samples. A head-to-head comparison was conducted using data generated from matching samples and synthetic tissue references. Platform specific features were also assessed according to manufacturers recommendations to evaluate the optimal usage of the two technologies. ResultsWe identified substantial variations in assay design between the DSP and Visium assays such as transcriptomic coverage and composition of the transcripts detected. When the data was standardised according to manufacturers recommendations, the DSP platform was more sensitive in gene expression detection. However, its specificity was diminished by the presence of non-specific detection. Our results also confirmed the strength and weakness of each platform in characterising spatial transcriptomic features of tissue samples, in particular their application to hypothesis generation versus hypothesis testing. ConclusionIn this study, we share our experience on both DSP and Visium technologies as end users. We hope this can guide future users to choose the most suitable platform for their research. In addition, this dataset can be used as an important resource for the development of new analysis tools.

cancer biology↗

bioRxiv2023

Distinct Myeloid Derived Suppressor Cell Populations Promote Tumor Aggression in Glioblastoma

The diversity of genetic programs and cellular plasticity of glioma-associated myeloid cells, and thus their contribution to tumor growth and immune evasion, is poorly understood. We performed single cell RNA-sequencing of immune and tumor cells from 33 glioma patients of varying tumor grades. We identified two populations characteristic of myeloid derived suppressor cells (MDSC), unique to glioblastoma (GBM) and absent in grades II and III tumors: i) an early progenitor population (E-MDSC) characterized by strong upregulation of multiple catabolic, anabolic, oxidative stress, and hypoxia pathways typically observed within tumor cells themselves, and ii) a monocytic MDSC (M-MDSC) population. The E-MDSCs geographically co-localize with a subset of highly metabolic glioma stem-like tumor cells with a mesenchymal program in the pseudopalisading region, a pathognomonic feature of GBMs associated with poor prognosis. Ligand-receptor interaction analysis revealed symbiotic cross-talk between the stemlike tumor cells and E-MDSCs in GBM, whereby glioma stem cells produce chemokines attracting E-MDSCs, which in turn produce growth and survival factors for the tumor cells. Our large-scale single-cell analysis elucidated unique MDSC populations as key facilitators of GBM progression and mediators of tumor immunosuppression, suggesting that targeting these specific myeloid compartments, including their metabolic programs, may be a promising therapeutic intervention in this deadly cancer. One-Sentence SummaryAggressive glioblastoma harbors two unique myeloid populations capable of promoting stem-like properties of tumor cells and suppressing T cell function in the tumor microenvironment.

immunology↗

bioRxiv2023

Deep Learning-based Identification of Intraocular Pressure-Associated Genes Influencing Trabecular Meshwork Cell and Organelle Morphology

PURPOSEThe exact pathogenesis of primary open-angle glaucoma (POAG) is poorly understood. Genome-wide association studies (GWAS) have recently uncovered many loci associated with variation in intraocular pressure (IOP); a crucial risk factor for POAG. Artificial intelligence (AI) can be used to interrogate the effect of specific genetic knockouts on the morphology of trabecular meshwork cells (TMCs), the regulatory cells of IOP. METHODSSixty-two genes at fifty-five loci associated with IOP variation were knocked out in primary TMC lines. All cells underwent high-throughput microscopy imaging after being stained with a five-channel fluorescent cell staining protocol. A convolutional neural network (CNN) was trained to distinguish between gene knockout and normal control cell images. The area under the receiver operator curve (AUC) metric was used to quantify morphological variation in gene knockouts to identify potential pathological perturbations. RESULTSCells where RALGPS1 had been perturbed demonstrated the greatest morphological variation from normal TMCs (AUC 0.851, SD 0.030), followed by LTBP2 (AUC 0.846, SD 0.029) and BCAS3 (AUC 0.845, SD 0.020). Of seven multi-gene loci, five had statistically significant differences in AUC (p<0.05) between genes, allowing for pathological gene prioritisation. The mitochondrial channel most frequently showed the greatest degree of morphological variation (33.9% of cell lines). CONCLUSIONSWe demonstrate a robust method for functionally interrogating genome-wide association signals using high-throughput microscopy and AI. Genetic variations inducing marked morphological variation can be readily identified, allowing for the gene-based dissection of loci associated with complex traits.

genetics↗

bioRxiv2023

Nutrient niche partitioning between tropical legumes and grasses strengthens under elevated CO2

O_LIPlant community biodiversity can be maintained, at least partially, by shifts in species interactions between facilitation and competition for resources as environmental conditions change. These interactions also drive ecosystem functioning, including productivity, and can promote over-yielding-an ecosystem service prioritized in agro-ecosystems, such as pastures, that occurs when multiple species together are more productive than the component species alone. Importantly, species interactions that can result in over-yielding may shift in response to rising CO2 concentrations and changes in resource availability, and the consequences these shifts have on production is uncertain especially in the context of tropical mixed-species grasslands. C_LIO_LIWe examined the relative performance of two species pairs of tropical pasture grasses and legumes growing in monoculture and mixtures in a glasshouse experiment manipulating CO2. We investigated how over-yielding can arise from nitrogen (N) niche partitioning and biotic facilitation using stable isotopes to differentiate soil N from biological N fixation (BNF) within N acquisition into aboveground biomass for these two-species mixtures. C_LIO_LIWe found that N niche partitioning in species-level use of soil N vs. BNF drove species interactions in mixtures. Importantly partitioning and overyielding were generally reduced under elevated CO2. However, this finding was mixture-dependent based on biomass of dominant species in mixtures and the strength of selection effects for the dominant species. C_LIO_LIThis study demonstrates that rising atmospheric CO2 may alter niche partitioning between co-occurring species, with negative implications for the over-yielding benefits predicted for legume-grass mixtures in working landscapes with tropical species. Furthermore, these changes in inter-species interactions may have consequences for grassland composition that are not yet considered in larger-scale projections for impacts of climate change and species distributions. C_LI Graphical abstract(Image by H. Zhang): Among our tropical pasture species we found that grasses (dotted lines) grown in monoculture rely fully on soil nitrogen (N), while legumes (solid lines) grown in monoculture relied approximately equally on soil N and biological nitrogen fixation (BNF) to meet N requirements. When grown with tropical grasses, however, legumes shifted to rely more strongly on BNF, indicative of niche partitioning and decreased competition for soil nutrients with grasses. This separation of niche space was weakened under elevated CO2 conditions, ultimately reducing legume production. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/524162v3_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@70de5corg.highwire.dtl.DTLVardef@1685f0org.highwire.dtl.DTLVardef@b3662corg.highwire.dtl.DTLVardef@1f911a3_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2022

Pitfalls and opportunities for applying PEER factors in single-cell eQTL analyses

Using latent variables in gene expression data can help correct spurious correlations due to unobserved confounders and increase statistical power for expression Quantitative Trait Loci (eQTL) detection. Probabilistic Estimation of Expression Residuals (PEER) is a widely used statistical method that has been developed to remove unwanted variation and improve eQTL discovery power in bulk RNA-seq analysis. However, its performance has not been largely evaluated in single-cell eQTL data analysis, where it is becoming a commonly used technique. Potential challenges arise due to the structure of single-cell data, including sparsity, skewness, and mean-variance relationship. Here, we show by a series of analyses that this method requires additional quality control and data transformation steps on the pseudo-bulk matrix to obtain valid PEER factors. By using a population-scale single-cell cohort (OneK1K, N = 982), we found that generating PEER factors without further QC or transformation on the pseudo-bulk matrix could result in inferred factors that are highly correlated (Pearsons correlation r = 0.626[~]0.997). Similar spurious correlations were also found in PEER factors inferred from an independent dataset (induced pluripotent stem cells, N = 31). Optimization of the strategy for generating PEER factors and incorporating the improved PEER factors in the eQTL association model can identify 9.0[~]23.1% more eQTLs or 1.7%[~]13.3% more eGenes. Sensitivity analysis showed that the pattern of change between the number of eGenes detected and PEER factors fitted varied significantly for different cell types. In addition, using highly variable genes (e.g., top 2000) to generate PEER factors could achieve similar eGenes discovery power as using all genes but save considerable computational resources ([~]6.2-fold faster). We provide diagnostic guidelines to improve the robustness and avoid potential pitfalls when generating PEER factors for single-cell eQTL association analyses.

bioinformatics↗

bioRxiv2022

Optical mapping compendium of structural variants across global cattle breeds

Structural variants (SV) have been linked to important bovine disease phenotypes, but due to the difficulty of their accurate detection with standard sequencing approaches, their role in shaping important traits across cattle breeds is largely unexplored. Optical mapping is an alternative approach for mapping SVs that has been shown to have higher sensitivity than DNA sequencing approaches. The aim of this project was to use optical mapping to develop a high-quality database of structural variation across cattle breeds from different geographical regions, to enable further study of SVs in cattle. To do this we generated 100X Bionano optical mapping data for 18 cattle of nine different ancestries, three continents and both cattle sub-species. In total we identified 13,457 SVs, of which 1,200 putatively overlap coding regions. This resource provides a high-quality set of optical mapping-based SV calls that can be used across studies, from validating DNA sequencing-based SV calls to prioritising candidate functional variants in genetic association studies and expanding our understanding of the role of SVs in cattle evolution.

genomics↗

bioRxiv2022

Demuxafy: Improvement in droplet assignment by integrating multiple single-cell demultiplexing and doublet detection methods

Recent innovations in droplet-based single-cell RNA-sequencing (scRNA-seq) have provided the technology necessary to investigate biological questions at cellular resolution. With the ability to assay thousands of cells in a single capture, pooling cells from multiple individuals has become a common strategy. Droplets can subsequently be assigned to a specific individual by leveraging their inherent genetic differences, and numerous computational methods have been developed to address this problem. However, another challenge implicit with droplet-based scRNA-seq is the occurrence of doublets - droplets containing two or more cells. The inaccurate assignment of cells to individuals or failure to remove doublets contribute unwanted noise to the data and result in erroneous scientific conclusions. Therefore, it is essential to assign cells to individuals and remove doublets accurately. We present a new framework to improve individual singlet classification and doublet removal through a multi-method intersectional approach. We developed a framework to evaluate the enhancement in donor assignment and doublet removal through the consensus intersection of multiple demultiplexing and doublet detecting methods. The accuracy was assessed using scRNA-seq data of [~]1.4 million peripheral blood mononucleated cells from 1,034 unrelated individuals and [~]90,000 fibroblast cells from 81 unrelated individuals. We show that our approach significantly improves droplet assignment by separating singlets from doublets and classifying the correct individual compared to any single method. We show that the best combination of techniques varies under different biological and experimental conditions, and we present a framework to optimise cell assignment for a given experiment. We offer Demuxafy (https://demultiplexing-doublet-detecting-docs.readthedocs.io/en/latest/index.html) - a framework built-in Singularity to provide clear, consistent documentation of each method and additional tools to simplify and improve demultiplexing and doublet removal. Our results indicate that leveraging multiple demultiplexing and doublet detecting methods improves accuracy and, consequently, downstream analyses in multiplexed scRNA-seq experiments.

genomics↗

bioRxiv2022

Prox1 dynamically regulates downstream targets and chromatin accessibility during venous to lymphatic endothelial cell transdifferentiation in the embryo

During development, the lymphatic vasculature forms as a second, new vascular network derived from blood vessels. The transdifferentiation of embryonic venous endothelial cells (VECs) into lymphatic endothelial cells (LECs) is the first step in this process. Specification, differentiation and maintenance of LEC fate are all driven by the transcription factor Prox1, yet downstream mechanisms remain to be elucidated. We present a single cell transcriptomic atlas of lymphangiogenesis in zebrafish revealing new markers and hallmarks of LEC differentiation over four developmental stages. We further profile single cell transcriptomic and chromatin accessibility changes in zygotic prox1a mutants that are undergoing a VEC-LEC fate reversion during differentiation. Using maternal and zygotic prox1a/prox1b mutants, we determine the earliest transcriptomic changes directed by Prox1 during LEC specification. This work altogether reveals new transcriptional targets and regulatory regions of the genome downstream of Prox1 in LEC maintenance, as well as showing that Prox1 specifies LEC fate primarily by limiting blood vascular and hematopoietic fate. This extensive single cell resource provides new mechanistic insights into the enigmatic role of Prox1 and the control of LEC differentiation in development.

developmental biology↗

bioRxiv2021

propeller: testing for differences in cell type proportions in single cell data

MotivationSingle cell RNA Sequencing (scRNA-seq) has rapidly gained popularity over the last few years for profiling the transcriptomes of thousands to millions of single cells. This technology is now being used to analyse experiments with complex designs including biological replication. One question that can be asked from single cell experiments, which has been difficult to directly address with bulk RNA-seq data, is whether the cell type proportions are different between two or more experimental conditions. As well as gene expression changes, the relative depletion or enrichment of a particular cell type can be the functional consequence of disease or treatment. However, cell type proportions estimates from scRNA-seq data are variable and statistical methods that can correctly account for different sources of variability are needed to confidently identify statistically significant shifts in cell type composition between experimental conditions. ResultsWe have developed propeller, a robust and flexible method that leverages biological replication to find statistically significant differences in cell type proportions between groups. Using simulated cell type proportions data we show that propeller performs well under a variety of scenarios. We applied propeller to test for significant changes in proportions of cell types related to human heart development, ageing and COVID-19 disease severity. Availability and implementationThe propeller method is publicly available in the open source speckle R package (https://github.com/phipsonlab/speckle). All the analysis code for the paper is available at https://github.com/phipsonlab/propeller-paper-analysis/, and the associated analysis website is available at https://phipsonlab.github.io/propeller-paper-analysis/. ContactAlicia Oshlack: Alicia.Oshlack@petermac.org Belinda Phipson: phipson.b@wehi.edu.au Supplementary informationYes.

bioinformatics↗

bioRxiv2021

Transcriptomic and proteomic retinal pigment epithelium signatures of age-related macular degeneration.

Induced pluripotent stem cells generated from patients with geographic atrophy as well as healthy individuals were differentiated to retinal pigment epithelium (RPE) cells. By integrating transcriptional profiles of 127,659 RPE cells generated from 43 individuals with geographic atrophy and 36 controls with genotype data, we identified 439 expression Quantitative Trait (eQTL) loci in cis that were associated with disease status and specific to subpopulations of RPE cells. We identified loci linked to two genes with known associations with geographic atrophy - PILRB and PRPH2, in addition to 43 genes with significant genotype x disease interactions that are candidates for novel genetic associations for geographic atrophy. On a transcriptome-only level, we identified molecular pathways significantly upregulated in geographic atrophy-RPE including in extracellular cellular matrix reorganisation, neurodegeneration, and mitochondrial functions. We subsequently implemented a large-scale proteomics analysis, confirming modification in proteins associated with these pathways. We also identified six significant protein (p) QTL that regulate protein expression in the RPE cells and in geographic atrophy - two of which share variants with cis-eQTL. Transcriptome-wide association analysis identified genes at loci previously associated with age-related macular degeneration. Further analysis conditional on disease status, implicated statistically significant RPE-specific eQTL. This study uncovers important differences in RPE homeostasis associated with geographic atrophy.

neuroscience↗

bioRxiv2021

Village in a dish: a model system for population-scale hiPSC studies

The mechanisms by which DNA alleles contribute to disease risk, drug response, and other human phenotypes are highly context-specific, varying across cell types and under different conditions. Human induced pluripotent stem cells (hiPSCs) are uniquely suited to study these context-dependent effects, but to do so requires cell lines from hundreds or potentially thousands of individuals. Village cultures, where multiple hiPSC lines are cultured and differentiated together in a single dish, provide an elegant solution for scaling hiPSC experiments to the necessary sample sizes required for population-scale studies. Here, we show the utility of village models, demonstrating how cells can be assigned back to a donor line using single cell sequencing, and addressing whether line-specific signaling alters the transcriptional profiles of companion lines in a village culture. We generated single cell RNA sequence data from hiPSC lines cultured independently (uni-culture) and in villages at three independent sites. We show that the transcriptional profiles of hiPSC lines are highly consistent between uni- and village cultures for both fresh (0.46 < R < 0.88) and cryopreserved samples (0.46 < R < 0.62). Using a mixed linear model framework, we estimate that the proportion of transcriptional variation across cells is predominantly due to donor effects, with minimal evidence of variation due to culturing in a village system. We demonstrate that the genetic, epigenetic or hiPSC line-specific effects on gene expression are consistent whether the lines are uni- or village-cultured (0.82 < R < 0.94). Finally, we identify the consistency in the landscape of cell states between uni- and village-culture systems. Collectively, we demonstrate that village methods can be effectively used to detect hiPSC line-specific effects including sensitive dynamics of cell states.

genomics↗