Biology subjects

Park, Y.

Publications and source records attributed to Park, Y..

At least 163 records · Page 9Linked to original sources

bioRxiv2020

Label-free bone marrow white blood cell classification using refractive index tomograms and deep learning

In this study, we report a label-free bone marrow white blood cell classification framework that captures the three-dimensional (3D) refractive index (RI) distributions of individual cells and analyzes with deep learning. Without using labeling or staining processes, 3D RI distributions of individual white blood cells were exploited for accurate profiling of their subtypes. Powered by deep learning, our method used the high-dimensional information of the WBC RI tomogram voxels and achieved high accuracy. The results show >99 % accuracy for the binary classification of myeloids and lymphoids and >96 % accuracy for the four-type classification of B, T lymphocytes, monocytes, and myelocytes. Furthermore, the feature learning of our approach was visualized via an unsupervised dimension reduction technique. We envision that this framework can be integrated into existing workflows for blood cell investigation, thereby providing cost-effective and rapid diagnosis of hematologic malignancy.

bioengineering↗

bioRxiv2020

The SARS-CoV-2 RNA interactome

SARS-CoV-2 is an RNA virus whose success as a pathogen relies on its ability to repurpose host RNA-binding proteins (RBPs) to form its own RNA interactome. Here, we developed and applied a robust ribonucleoprotein capture protocol to uncover the SARS-CoV-2 RNA interactome. We report 109 host factors that directly bind to SARS-CoV-2 RNAs including general antiviral factors such as ZC3HAV1, TRIM25, and PARP12. Applying RNP capture on another coronavirus HCoV-OC43 revealed evolutionarily conserved interactions between viral RNAs and host proteins. Network and transcriptome analyses delineated antiviral RBPs stimulated by JAK-STAT signaling and proviral RBPs responsible for hijacking multiple steps of the mRNA life cycle. By knockdown experiments, we further found that these viral-RNA-interacting RBPs act against or in favor of SARS-CoV-2. Overall, this study provides a comprehensive list of RBPs regulating coronaviral replication and opens new avenues for therapeutic interventions.

microbiology↗

bioRxiv2020

Functional interpretation of ATAD3A variants in neuro-mitochondrial phenotypes

BackgroundThe ATPase family AAA-domain containing protein 3A (ATAD3A) is a nuclear-encoded mitochondrial membrane anchored protein involved in diverse processes including mitochondrial dynamics, mitochondrial DNA organization, and cholesterol metabolism. Biallelic deletions (null), recessive missense variants (hypomorph), and heterozygous missense variants or duplications (antimorph) in ATAD3A lead to neurological syndromes in humans. ObjectiveTo expand the mutational spectrum of ATAD3A variants and to provide functional interpretation of missense alleles in trans to deletion alleles. MethodsExome sequencing was used to identify single nucleotide variants (SNVs) and copy number variants (CNVs) in ATAD3A in individuals with neurological and mitochondrial phenotypes. A Drosophila Atad3A Gal4 trap null allele was generated using CRISPR-Cas9 genome editing technology to aid interpretation of variants. ResultsWe report 13 individuals from 8 unrelated families with biallelic ATAD3A variants. Four of the identified missense variants, p.(Leu77Val), p.(Phe50Leu), p.(Arg170Trp), p.(Gly236Val), were inherited in trans to loss-of-function alleles. A fifth missense variant, p.(Arg327Pro), was homozygous. Affected individuals exhibited findings previously associated with ATAD3A pathogenic variation, including developmental delay, hypotonia, congenital cataracts, hypertrophic cardiomyopathy, and cerebellar atrophy. Drosophila studies indicated that Phe50Leu, Gly236Val, and Arg327Pro are severe loss-of-function alleles leading to early developmental lethality and neurogenesis defects, whereas Leu77Val and Arg170Trp are partial loss of function alleles that cause progressive locomotion defects. Moreover, Leu77Val and Arg170Trp expression leads to an increase in autophagy and mitophagy in adult muscles. ConclusionOur findings expand the allelic spectrum of ATAD3A variants, and exemplify the use of a functional assay in Drosophila to aid variant interpretation.

genetics↗

bioRxiv2020

Data-driven multiplexed microtomography of endogenous subcellular dynamics

Simultaneous imaging of various facets of intact biological systems across multiple spatiotemporal scales would be an invaluable tool in biomedicine. However, conventional imaging modalities have stark tradeoffs precluding the fulfilment of all functional requirements. Here we propose the refractive index (RI), an intrinsic quantity governing light-matter interaction, as a means for such measurement. We show that major endogenous subcellular structures, which are conventionally accessed via exogenous fluorescence labeling, are encoded in 3D RI tomograms. We decode this information in a data-driven manner, thereby achieving multiplexed microtomography. This approach inherits the advantages of both high-specificity fluorescence imaging and label-free RI imaging. The performance, reliability, and scalability of this technology have been extensively characterized, and its application within single-cell profiling at unprecedented scales has been demonstrated.

bioengineering↗

bioRxiv2020

Oncogenic KRAS engages an RSK1/NF1 complex in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with limited treatment options. Although activating mutations of the KRAS GTPase are the predominant dependency present in >90% of PDAC patients, targeting KRAS mutants directly has been challenging in PDAC. Similarly, strategies targeting known KRAS downstream effectors have had limited clinical success due to feedback mechanisms, alternate pathways and toxicity due to the targeting of normal tissues. Therefore, identifying additional functionally relevant KRAS interactions in PDAC may allow for a better understanding of feedback mechanisms and unveil new potential therapeutic targets. Here, we used proximity labelling to identify protein interactors of active KRAS in PDAC cells. Fusions of wildtype (BirA-KRAS4B), mutant (BirA-KRAS4BG12D) and non-transforming and cytosolic double mutant (BirA-KRAS4BG12D/C185S) KRAS with the BirA biotin ligase were expressed in murine PDAC cells. Mass spectrometry analysis revealed that RSK1 was enriched among proteins that selectively interacted with membrane-bound KRASG12D. RSK1 required the NF1 and SPRED proteins to interact with KRAS-GTP at the membrane. In both murine and human PDAC lines, membrane-targeted RSK1 was tolerated but inhibited cell proliferation following oncogenic KRAS abrogation to reveal a negative feedback role for membrane-localized RSK1 on wild-type KRAS. Inhibition of the wild-type KRAS, which has been previously proposed to suppress KRAS oncogenesis, may partially explain how RSK1 has been identified as a dependency in some KRAS mutant cells and may provide an additional function for NF1 in tumorigenesis. Significance StatementFor decades, KRAS interactors have been sought after as potential therapeutic targets in KRAS mutant cancers, especially pancreatic adenocarcinoma (PDAC). Our proximity labeling screen with KRAS in PDAC cells highlight RSK1 as a notable mutant-specific interactor. Functionally, we show that RSK1 mediates negative feedback on wild-type KRAS in PDAC cells.

cancer biology↗

bioRxiv2020

Three-Dimensional Label-Free Imaging and Quantification of Migrating Cells during Wound Healing

The wound healing assay provides essential information about collective cell migration and cell-to-cell interactions. It is a simple, effective, and widely used tool for observing the effect of numerous chemical treatments on wound healing speed. To perform and analyze a wound healing assay, various imaging techniques have been utilized. However, image acquisition and analysis are often limited in two-dimensional space or require the use of exogenous labeling agents. Here, we present a method for imaging large-scale wound healing assays in a label-free and volumetric manner using optical diffraction tomography (ODT). We performed quantitative high-resolution three-dimensional (3D) analysis of cell migration over a long period without difficulties such as photobleaching or phototoxicity. ODT enables the reconstruction of the refractive index (RI) tomogram of unlabeled cells, which provides both structural and biochemical information about the individual cell at subcellular resolution. Stitching multiple RI tomograms enables long-term (24 h) and large field-of-view imaging (> 800 x 400 m2) with a lateral resolution of 110 nm. We demonstrated the thickness changes of leading cells and studied the effects of cytochalasin D. The 3D RI tomogram also revealed increased RI values in leading cells compared to lagging cells, suggesting the formation of a highly concentrated subcellular structure. STATEMENT OF SIGNIFICANCEThe wound healing assay is a simple but effective tool for studying collective cell migration (CCM) that is widely used in biophysical studies and high-throughput screening. However, conventional imaging and analysis methods only address two-dimensional properties in a wound healing assay, such as gap closure rate. This is unfortunate because biological cells are complex 3D structures, and their dynamics provide significant information about cell physiology. Here, we presented three-dimensional (3D) label-free imaging for wound healing assays and investigated the 3D dynamics of CCM. High-resolution subcellular structures as well as their collective dynamics were imaged and analyzed quantitatively. Our label-free quantitative 3D analysis method provides a unique opportunity to study the behavior of migrating cells during the wound healing process.

biophysics↗

bioRxiv2020

Multiscale label-free volumetric holographic histopathology of thick-tissue slides with subcellular resolution

Histopathology relies upon the staining and sectioning of biological tissues, which can be laborious and may cause artefacts and distort tissues. Here, we demonstrate label-free volumetric imaging of thick-tissue slides, exploiting refractive index distributions as intrinsic imaging contrast. The present method systematically exploits label-free quantitative phase imaging techniques, volumetric reconstruction of intrinsic refractive index distributions in tissues, and numerical algorithms for the seamless stitching of multiple 3D tomograms and for reducing scattering-induced image distortion. We demonstrate demonstrated label-free volumetric imaging of thick tissues with the field of view of 2 mm x 1.75 mm x 0.2 mm with a spatial resolution of 170 nm x 170 nm x 1200 nm. The number of optical modes, calculated as the reconstructed volume divided by the size of the point spread function, was approximately 20 Giga voxels. We have also demonstrated that different tumour types, and a variety of precursor lesions and pathologies can be visualized with the present method. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/205633v1_ufig1.gif" ALT="Figure 1"> View larger version (98K): org.highwire.dtl.DTLVardef@dcf15corg.highwire.dtl.DTLVardef@16a05d3org.highwire.dtl.DTLVardef@1a48860org.highwire.dtl.DTLVardef@f57430_HPS_FORMAT_FIGEXP M_FIG C_FIG

pathology↗

bioRxiv2020

Curvature effect of PE-included membrane on the behavior of cinnamycin on the membrane

The behavior of the cinnamycin on the biomimetic membrane was studied with respect to the curvature of the phosphatidylethanolamine(PE)-included membrane with the adhesion measured by the atomic force microscope(AFM). The membrane was formed through vesicle fusion on the hydrophobic surface of the sphere spheres, which was used to define the curvature of the membrane. The hydrophobicity was generated by the reaction of alkyl-silane and analyzed with the X-ray photoelectron spectrometer. The cinnamycin, immobilized covalently to the AFM tip coated with 1-mercapto-1-undecanol that was observed inert to any adhesion to the membrane, showed that the adhesion became stronger with the increase in the curvature. The correlation between the adhesion and the curvature was linearly proportional. Previously, it was found that the cinnamycin was bound to PE headgroup and the binding was enhanced by the interaction of the hydrophobic area located at one side of the cinnamycin. Therefore, the linear proportionality seems to suggest that the interaction is related to the one dimensional orientation of the binding. Statement of SignificanceThe behavior of the cinnamycin was studied on the phosphatidylethanolamine(PE)-included membrane with respect to the curvature of the membrane. The cinnamycin, immobilized covalently to the atomic force microscope, showed that the adhesion became stronger linearly with the increase in the curvature. Previously, it was found that the specific binding between the cinnamycin and PE headgroup was enhanced by the interaction of the hydrophobic area located at one side of the cinnamycin. Therefore, the linear proportionality seems to suggest that the interaction is related to the one dimensional orientation of the binding.

biophysics↗

bioRxiv2020

Laser-activated drug implant for controlled release to the posterior segment of the eye

The current standard of care for posterior segment eye diseases, such as age-related macular degeneration and diabetic macular edema, is frequent intravitreal injections or sustained-release drug implants. Drug implants have side effects due to the burst release of the drugs, and their release cannot be easily controlled after implantation. Present study attempts to develop a dosage-controllable drug delivery implant which consists of a nanoporous biodegradable PLGA capsule and light-activated liposomes. Controllable drug release from the implant was achieved by using pulsed near-infrared (NIR) laser both in vitro and in vivo. The in vitro drug release kinetics from two different initial dose implants, 1000 g and 500 g, was analyzed by fitting zero order and first order kinetics, as well as the Korsmeyer-Peppas and Higuchi models. The 1000 g and 500 g implants fit the first-order and zero-order kinetics model, respectively, the best. The multiple drug releases in the vitreous was determined by in vivo fluorimeter, which was consistent with the in vitro data. The dose released was also clinically relevant. Histology and optical and ultrasound imaging data showed no abnormality in the eyes received implant treatment suggesting that the drug delivery system was safe to the retina. This on-demand dose-controllable drug delivery system could be potentially used for long-term posterior eye disease treatment.

bioengineering↗

bioRxiv2020

Correcting for experiment-specific variability in expression compendia can remove underlying signals

MotivationIn the last two decades, scientists working in different labs have assayed gene expression from millions of samples. These experiments can be combined into compendia and analyzed collectively to extract novel biological patterns. Technical variability, sometimes referred to as batch effects, may result from combining samples collected and processed at different times and in different settings. Such variability may distort our ability to interpret and extract true underlying biological patterns. As more multi-experiment, integrative analysis methods are developed and available data collections increase in size, it is crucial to determine how technical variability affect our ability to detect desired patterns when many experiments are combined ObjectiveWe sought to determine the extent to which an underlying signal was masked by technical variability by simulating compendia comprised of data aggregated across multiple experiments. MethodWe developed a generative multi-layer neural network to simulate compendia of gene expression experiments from large-scale microbial and human datasets. We compared simulated compendia before and after introducing varying numbers of sources of undesired variability. ResultsWe found that the signal from a baseline compendium was obscured when the number of added sources of variability was small. Perhaps as expected, applying statistical correction methods rescued the underlying signal in these cases. As the number of sources of variability increased, surprisingly, we observed that detecting the original signal became increasingly easier even without correction. In fact, applying statistical correction methods reduced our power to detect the underlying signal. ConclusionWhen combining a modest number of experiments, it is best to correct for experiment-specific noise. However, when many experiments are combined, statistical correction reduces ones ability to extract underlying patterns.

bioinformatics↗

bioRxiv2020

Sparse long-range connections in visual cortex for cost-efficient small-world networks

The brain performs visual object recognition using much shallower hierarchical stages than artificial deep neural networks employ. However, the mechanism underlying this cost-efficient function is elusive. Here, we show that cortical long-range connectivity(LRC) may enable this parsimonious organization of circuits for balancing cost and performance. Using model network simulations based on data in tree shrews, we found that sparse LRCs, when added to local connections, organize a small-world network that dramatically enhances object recognition of shallow feedforward networks. We found that optimization of the ratio between LRCs and local connections maximizes the small-worldness and task performance of the network, by minimizing the total length of wiring needed for integration of the global information. We also found that the effect of LRCs varies by network size, which explains the existence of species-specific LRCs in mammalian visual cortex of various sizes. Our results demonstrate a biological strategy to achieve cost-efficient brain circuits. HighlightsO_LILong-range connections (LRCs) enhance the object recognition of shallow networks C_LIO_LISparse LRCs added to dense local connections organize a small-world type network C_LIO_LISmall-worldness of networks modulates the balance between performance and wiring cost C_LIO_LIDistinct LRCs in various species are due to the size-dependent effect of LRCs C_LI Significance statementThe hierarchical depth of the visual pathway in the brain is constrained by biological factors, whereas artificial deep neural networks consist of super-deep structures (i.e., as deep as computational power allows). Here, we show that long-range horizontal connections (LRCs) observed in mammalian visual cortex may enable shallow biological networks to perform cognitive tasks that require deeper artificial structures, by implementing cost-efficient organization of circuitry. Using model simulations based on anatomical data, we found that sparse LRCs, when added to dense local circuits, organize "small-world" type networks and that this dramatically enhances image classification performance by integrating both local and global components of visual stimulus. Our findings show a biological strategy of brain circuitry to balance sensory performance and wiring cost in the networks. One sentence summaryCortical long-range connections organize a small-world type network to achieve cost-efficient functional circuits under biological constraints

neuroscience↗

bioRxiv2020

Correlating predicted epigenetic marks with expression data to find interactions between SNPs and genes

Despite all the work done, mapping GWAS SNPs in non-coding regions to their target genes remains a challenge. The SNP can be associated with target genes by eQTL analysis. Here we introduce a method to make these eQTLs more robust. Instead of correlating the gene expression with the SNP value like in eQTLs, we correlate it with epigenomic data. This epigenomic data is very expensive and noisy. We therefore predict the epigenomic data from the DNA sequence using the deep learning framework DeepSEA (Zhou and Troyanskaya, 2015).

bioinformatics↗

bioRxiv2020

Exome-wide age-of-onset analysis reveals exonic variants in ERN1, TACR3 and SPPL2C associated with Alzheimer's disease

Despite recent discovery in GWAS of genomic variants associated with Alzheimers disease (AD), its underlying biological mechanisms are still elusive. Discovery of novel AD-associated genetic variants, particularly in coding regions and from APOE {varepsilon}4 non-carriers, is critical for understanding the pathology of AD. In this study, we carried out an exome-wide association analysis of age-of-onset of AD with ~20,000 subjects and placed more emphasis on APOE {varepsilon}4 non-carriers. Using Cox mixed-effects models, we find that age-of-onset shows a stronger genetic signal than AD case-control status, capturing many known variants with stronger significance, and also revealing new variants. We identified two novel rare variants, rs56201815, a synonymous variant in ERN1, from the analysis of APOE {varepsilon}4 non-carriers, and a missense variant rs144292455 in TACR3. In addition, we detected rs12373123, a common missense variant in SPPL2C in the MAPT region in APOE {varepsilon}4 non-carriers. In an attempt to unravel their regulatory and biological functions, we found that the minor allele of rs56201815 was associated with lower average FDG uptake across five brain regions in ADNI. Our eQTL analyses based on 6198 gene expression samples from ROSMAP and GTEx revealed that the minor allele of rs56201815 was associated with elevated expression of ERN1, a key gene triggering unfolded protein response (UPR), in multiple brain regions, including posterior cingulate cortex and nucleus accumbens. Our cell-type-specific eQTL analysis of based on ~80,000 single nuclei in the prefrontal cortex revealed that the protective minor allele of rs12373123 significantly increased expression of GRN in microglia, and was associated with MAPT expression in astrocytes. These findings provide novel evidence supporting the hypothesis of the potential involvement of the UPR to ER stress in the pathological pathway of AD, and also give more insights into underlying regulatory mechanisms behind the pleiotropic effects of rs12373123 in multiple degenerative diseases including AD and Parkinsons disease.

neuroscience↗

bioRxiv2020

Label-free three-dimensional observations and quantitative characterisation of on-chip vasculogenesis using optical diffraction tomography

Label-free, three-dimensional (3D) quantitative observations of on-chip vasculogenesis were achieved using optical diffraction tomography. Exploiting 3D refractive index maps as an intrinsic imaging contrast, the vascular structures, multicellular activities, and subcellular organelles of endothelial cells were imaged and analysed throughout vasculogenesis to characterise mature vascular networks without exogenous labelling. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=176 SRC="FIGDIR/small/892620v1_ufig1.gif" ALT="Figure 1"> View larger version (98K): org.highwire.dtl.DTLVardef@12a786eorg.highwire.dtl.DTLVardef@14892dforg.highwire.dtl.DTLVardef@1a28091org.highwire.dtl.DTLVardef@1a6e9df_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2019

Measurements of 3-D morphology of individual red blood cells upon localized photothermal effects using gold nanorods

We investigated the in-situ photothermal response of human red blood cells (RBCs) by combining photothermal heat generation and 3D quantitative phase imaging techniques. Gold-nanorod-coated substrates were excited using near-infrared light to generate local heat to RBCs, and response was measured by imaging 3-D refractive index tomograms of cells under various near infrared (NIR) excitation conditions. On photothermal treatment, cell morphology changed from discoid to crescent shapes, cell volume and dry mass decreased, and hemoglobin concentration increased. We also investigated the irreversible deformation of RBCs when multiple intense excitation shocks are applied. These results provide a new understanding of thermodynamic aspects of cell biology and hematology. O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

biophysics↗

bioRxiv2019

Rapid antimicrobial susceptibility test using spatiotemporal analysis of laser speckle dynamics of bacterial colonies

Antimicrobial susceptibility testing (AST) is crucial for providing appropriate choices and doses of antibiotics to patients. However, standard ASTs require a time-consuming incubation of about 16-20 h for visual accumulation of bacteria, limiting the use of AST for an early prescription. In this study, we propose a rapid AST based on laser speckle formation (LSF) that enables rapid detection of bacterial growth, with the same sample preparation protocol as in solid-based ASTs. The proposed method exploits the phenomenon that well-grown bacterial colonies serve as optical diffusers, which convert a plane-wave laser beam into speckles. The generation of speckle patterns indicates bacterial growth at given antibiotic concentrations. Speckle formation is evaluated by calculating the spatial autocorrelation of speckle images, and bacterial growth is determined by tracking the autocorrelation value over time. We demonstrated the performance of the proposed method for several combinations of bacterial species and antibiotics to achieve the AST in 2-4.5 hours. Furthermore, we also demonstrated the sensitivity of the technique for low bacterial density. The proposed method can be a powerful tool for rapid, simple, and low-cost AST. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=160 SRC="FIGDIR/small/853168v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@8ee314org.highwire.dtl.DTLVardef@de47c5org.highwire.dtl.DTLVardef@13a0103org.highwire.dtl.DTLVardef@118ad36_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2019

Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx

BackgroundPopulation structure among study subjects may confound genetic association studies, and lack of proper correction can lead to spurious findings. The Genotype-Tissue Expression (GTEx) project largely contains individuals of European ancestry, but the final release (v8) also includes up to 15% of individuals of non-European ancestry. Assessing ancestry-based adjustments in GTEx provides an opportunity to improve portability of this research across populations and to further measure the impact of population structure on GWAS colocalization.\n\nResultsHere, we identify a subset of 117 individuals in GTEx (v8) with a high degree of population admixture and estimate genome-wide local ancestry. We perform genome-wide cis-eQTL mapping using admixed samples in six tissues, adjusted by either global or local ancestry. Consistent with previous work, we observe improved power with local ancestry adjustment. At loci where the two adjustments produce different lead variants, we observe only 0.8% of tests with GWAS colocalization posterior probabilities that change by 10% or more. Notably, both adjustments produce similar numbers of significant colocalizations. Finally, we identify a small subset of GTEx v8 eQTL-associated variants highly correlated with local ancestry (R2 > 0.7), providing a resource to enhance functional follow-up.\n\nConclusionsWe provide a local ancestry map for admixed individuals in the final GTEx release and describe the impact of ancestry and admixture on gene expression, eQTLs, and GWAS colocalization. While the majority of results are concordant between local and global ancestry-based adjustments, we identify distinct advantages and disadvantages to each approach.

genetics↗

bioRxiv2019

PhenomeXcan: Mapping the genome to the phenome through the transcriptome

Large-scale genomic and transcriptomic initiatives offer unprecedented ability to study the biology of complex traits and identify target genes for precision prevention or therapy. Translation to clinical contexts, however, has been slow and challenging due to lack of biological context for identified variant-level associations. Moreover, many translational researchers lack the computational or analytic infrastructures required to fully use these resources. We integrate genome-wide association study (GWAS) summary statistics from multiple publicly available sources and data from Genotype-Tissue Expression (GTEx) v8 using PrediXcan and provide a user-friendly platform for translational researchers based on state-of-the-art algorithms. We develop a novel Bayesian colocalization method, fastENLOC, to prioritize the most likely causal gene-trait associations. Our resource, PhenomeXcan, synthesizes 8.87 million variants from GWAS on 4,091 traits with transcriptome regulation data from 49 tissues in GTEx v8 into an innovative, gene-based resource including 22,255 genes. Across the entire genome/phenome space, we find 65,603 significant associations (Bonferroni-corrected p-value of 5.5 x 10-10), where 19,579 (29.8 percent) were colocalized (locus regional colocalization probability > 0.1). We successfully replicate associations from PheWAS Catalog (AUC=0.61) and OMIM (AUC=0.64). We provide examples of (a) finding novel and underreported genome-to-phenome associations, (b) exploring complex gene-trait clusters within PhenomeXcan, (c) studying phenome-to-phenome relationships between common and rare diseases via further integration of PhenomeXcan with ClinVar, and (d) evaluating potential therapeutic targets. PhenomeXcan (phenomexcan.org) broadens access to complex genomic and transcriptomic data and empowers translational researchers. One-Sentence SummaryPhenomeXcan is a gene-based resource of gene-trait associations with biological context that supports translational research.

genetics↗