Biology subjects

Qiu, Y.

Publications and source records attributed to Qiu, Y..

At least 181 records · Page 10Linked to original sources

bioRxiv2021

Direct photoresponsive inhibition of a p53-like transcription activation domain in PIF3 by Arabidopsis phytochrome B

Phytochrome B (PHYB) triggers diverse light responses in Arabidopsis by binding to a group of antagonistically acting PHYTOCHROME-INTERACTING transcription FACTORs (PIFs) to promote PIF degradation, consequently downregulating PIF target genes. However, whether PHYB directly controls the transactivation activity of PIFs remains ambiguous. Here we show that the prototypic PIF, PIF3, possesses a p53-like transcription activation domain (TAD) consisting of a sequence-specific, hydrophobic activator motif surrounded by acidic residues. A PIF3mTAD mutant in which the activator motif is replaced with alanines fails to activate PIF3 target genes in Arabidopsis in dark, light, and shade conditions, validating the in vivo functions of the PIF3 TAD. Intriguingly, binding of PHYBs N-terminal photosensory module to the PHYB-binding site adjacent to the TAD inhibits its transactivation activity. These results unveil a photoresponsive transcriptional switching mechanism in which photoactivated PHYB directly masks the transactivation activity of PIF3. Our study also suggests the unexpected conservation of sequence-specific TADs between the animal and plant kingdoms.

plant biology↗

bioRxiv2021

H2A ubiquitination is essential for Polycomb Repressive Complex 1-mediated gene regulation in Marchantia polymorpha

Polycomb repressive complex 1 (PRC1) and PRC2 are chromatin regulators maintaining transcriptional repression. The deposition of H3 lysine 27 tri-methylation (H3K27me3) by PRC2 is known to be required for transcriptional repression, whereas the contribution of H2A ubiquitination (H2Aub) in the Polycomb repressive system remains unclear in plants. We directly tested the requirement of H2Aub for gene regulation in Marchantia polymorpha by generating point mutations in H2A that prevent ubiquitination by PRC1. These mutants show reduced H3K27me3 levels on the same target sites as mutants defective in PRC1 subunits MpBMI1 and the homolog MpBMI1L, revealing that PRC1-catalyzed H2Aub is essential for Polycomb system function. Furthermore, by comparing transcriptome data between mutants in MpH2A and MpBMI1/1L, we demonstrate that H2Aub contributes to the PRC1-mediated transcriptional level of genes and transposable elements. Together, our data demonstrate that H2Aub plays a direct role in H3K27me3 deposition and is required for PRC1-mediated transcriptional changes in both genic and intergenic regions in Marchantia.

plant biology↗

bioRxiv2021

Multiple morphogens and rapid elongation promote segmental patterning during development

The vertebrate hindbrain is segmented into rhombomeres (r) initially defined by distinct domains of gene expression. Previous studies have shown that noise-induced gene regulation and cell sorting are critical for the sharpening of rhombomere boundaries, which start out rough in the forming neural plate (NP) and sharpen over time. However, the mechanisms controlling simultaneous formation of multiple rhombomeres and accuracy in their sizes are unclear. We have developed a stochastic multiscale cell-based model that explicitly incorporates dynamic morphogenetic changes (i.e. convergent-extension of the NP), multiple morphogens, and gene regulatory networks to investigate the formation of rhombomeres and their corresponding boundaries in the zebrafish hindbrain. During pattern initiation, the short-range signal, fibroblast growth factor (FGF), works together with the longer-range morphogen, retinoic acid (RA), to specify all of these boundaries and maintain accurately-sized segments with sharp boundaries. At later stages of patterning, we show a nonlinear change in the shape of rhombomeres with rapid left-right narrowing of the NP followed by slower dynamics. Rapid initial convergence improves boundary sharpness and segment size by regulating cell sorting and cell fate both independently and coordinately. Overall, multiple morphogens and tissue dynamics synergize to regulate the sizes and boundaries of multiple segments during development. Author SummaryIn segmental pattern formation, chemical gradients control gene expression in a concentration-dependent manner to specify distinct gene expression domains. Despite the stochasticity inherent to such biological processes, precise and accurate borders form between segmental gene expression domains. Previous work has revealed synergy between gene regulation and cell sorting in sharpening borders that are initially rough. However, it is still poorly understood how size and boundary sharpness of multiple segments are regulated in a tissue that changes dramatically in its morphology as the embryo develops. Here we develop a stochastic multiscale cell-base model to investigate these questions. Two novel strategies synergize to promote accurate segment formation, a combination of long- and short-range morphogens plus rapid tissue convergence, with one responsible for pattern initiation and the other enabling pattern refinement.

developmental biology↗

bioRxiv2021

Host EPAC1 modulates rickettsial adhesion to vascular endothelial cells via regulation of ANXA2 Y23 phosphorylation

Recently we have identified that endothelial surface annexin A2 (ANAX2) functions as a receptor for spotted fever group rickettsial adhesin outer membrane protein B (OmpB), which binds to the endothelial cell (EC) surface. Moreover, we reported that intracellular cAMP receptor EPAC1 modulates ANXA2 tyrosine (Y) 23 phosphorylation, and inactivation of EPAC1 suppresses ANXA2 expression on the EC luminal surface by downregulating Y23 phosphorylation. Since we reported that EPAC1 plays a critical role in the initial step to successfully establish rickettsial infection of ECs, this work aims to answer the following: (a) What is the mechanism underlying the regulatory role of EPAC1 in ECs during the initial step of bacterial infection? (b) Is the EPAC1-ANXA2 signaling pathway involved in the regulation of rickettsial adhesion to ECs? In the present study, an established system that is anatomically-based and quantifies bacterial adhesion to ECs in vivo was combined with novel fluidic force microscopy (FluidFM) to dissect the functional role of the EPAC1-ANXA2 signaling pathway in rickettsiae-EC adhesion. We reveal that the deletion of the EPAC1 gene impedes rickettsial binding to endothelium in vivo. In addition, single living brain microvascular EC study that employs FluidFM and site-directed mutagenesis provides evidence that supports our finding that EPAC1 governs rickettsial adhesion to EC surfaces via regulation of ANXA2 Y23 phosphorylation.

pathology↗

bioRxiv2021

Radiation Exposure of the Base of the Heart Accelerates Coronary Atherosclerosis

Clinical studies have identified cardiac exposure as an independent predictor for cardiovascular mortality in patients treated with radiation therapy (RT) for thoracic malignancies. Although the mechanisms are not completely understood, the available evidence indicate that direct injury to the coronary arteries endothelium is implicated. In these studies we tested the hypothesis that different areas of the heart are more sensitive to the effects of RT on the formation of atherosclerotic plaque in apolipoprotein E deficient (ApoE-/-) mice, a well validated model of atherosclerosis. MethodsApoE-/- mice on a high fat diet (HFD) received 16Gy cardiac irradiation targeted to the whole or partial (apical or basal) region of the heart at 9 weeks or 16 weeks of age. Atherosclerotic lesions and inflammatory changes in the hearts as compared to control unirradiated mice were assessed eight weeks following radiation. ResultsAfter either basal or whole heart RT at 9 weeks of age the number of subendocardial atherosclerotic lesions at the heart base was higher as compared to unirradiated mice. Irradiation of the apex did not increase the number of subendocardial atherosclerotic lesions in any region. After basal RT at 16 weeks of age the number of coronary and subendocardial atherosclerotic lesions was higher as compared to controls. Neither apical or whole heart RT had an impact on the development or acceleration of lesions in the basal region of the hearts of 16 week old mice, thus demonstrating the adverse impact of basal irradiation. Infiltration of inflammatory cells (CD45+ and CD3+) and enhanced expression of endothelial adhesion molecules (CD31), were differentially and locally regulated based upon the site of irradiation. In support of a role of eicosanoid mediators for base or whole heart atherogenic irradiation effects, apex irradiation eicosanoid mediators are not clearly atherogenic, in contrast to eicosanoid mediators detected in serum after base heart irradiation. These results indicate that the base of the heart is significantly more prone to the development of atherosclerotic lesions in the coronary arteries post-RT. ConclusionOur results indicate that the base of the heart is more susuceptible to development of RT-induced atherosclerotic lesions and therefore avoidance from RT direct exposure to this area may reduce the risk for atherosclerotic disease in patients undergoing RT.

cancer biology↗

bioRxiv2021

Multi-scale predictive modeling discovers Ibudilast as a polypharmacological agent to improve hippocampal dependent spatial learning and memory and mitigate plaque and tangle pathology in a transgenic rat model of Alzheimer's disease

Alzheimers disease (AD) is a multifactorial disease that exhibits cognitive deficits, neuronal loss, amyloid plaques, neurofibrillary tangles and neuroinflammation in the brain. We developed a multi-scale predictive modeling strategy that integrates machine learning with biophysics and systems pharmacology to model drug actions from molecular interactions to phenotypic responses. We predicted that ibudilast (IBU), a phosphodiesterase inhibitor and toll-like receptor 4 (TLR4) antagonist, inhibited multiple kinases (e.g., IRAK1 and GSG2) as off-targets, modulated multiple AD-associated pathways, and reversed AD molecular phenotypes. We address for the first time the efficacy of ibudilast (IBU) in a transgenic rat model of AD. IBU-treated transgenic rats showed improved cognition and reduced hallmarks of AD pathology. RNA sequencing analyses in the hippocampus showed that IBU affected the expression of pro-inflammatory genes in the TLR signaling pathway. Our results identify IBU as a potential therapeutic to be repurposed for reducing neuroinflammation in AD by targeting TLR signaling.

pharmacology and toxicology↗

bioRxiv2021

Development of an integrated structural biology platform specialized for sub-100 kDa protein complexes to support biologics discovery and rational engineering

Developing a biologic medicine requires successful decision making at each step of selection, optimization, and/or combination of the right candidates at early research stages. Knowing the structural information and binding pattern between drug target and discovery candidates greatly increases the possibility of success. With the cryo-EM resolution revolution and rapid development of computational software, we have evaluated and integrated different tools in structural biology and the computation field and established a highly cost-effective platform, which allows us to obtain fast and accurate structural information for biologics projects with a close to 100% success rate and as fast as weeks turn-around time. Here we report four case studies selected from over 40 different protein structures and share how we integrate cryo-EM structure determination, computational structure modeling, and molecular dynamics simulation. With proper decision making and strategic planning, the platform allows us to obtain quality results within days to weeks, including sub-100 kDa complexes which are usually considered as a challenge due to their small size. Our utilization of this differential approach and use of multiple software packages, allows to manage priorities and resources to achieve goals quickly and efficiently. We demonstrate how to effectively overcome particle orientation bias by altering complex composition. In several of our examples, we use glycan density to facilitate interpretation of low-resolution 3D reconstruction and epitope mapping. Protein information plays an important role in our cryo-EM projects, especially in cases where we see significant challenges in obtaining high-resolution 3D maps.

molecular biology↗

bioRxiv2021

Application of an integrated computational antibody engineering platform to design SARS-CoV-2 neutralizers

As the COVID-19 pandemic continues to spread, hundreds of new initiatives including studies on existing medicines are running to fight the disease. To deliver a potentially immediate and lasting treatment to current and emerging SARS-CoV-2 variants, new collaborations and ways of sharing are required to create as many paths forward as possible. Here we leverage our expertise in computational antibody engineering to rationally design/optimize three previously reported SARS-CoV neutralizing antibodies and share our proposal towards anti-SARS-CoV-2 biologics therapeutics. SARS-CoV neutralizing antibodies, m396, 80R, and CR-3022 were chosen as templates due to their diversified epitopes and confirmed neutralization potency against SARS. Structures of variable fragment (Fv) in complex with receptor binding domain (RBD) from SARS-CoV or SARS-CoV2 were subjected to our established in silico antibody engineering platform to improve their binding affinity to SARS-CoV2 and developability profiles. The selected top mutations were ensembled into a focused library for each antibody for further screening. In addition, we convert the selected binders with different epitopes into the trispecific format, aiming to increase potency and to prevent mutational escape. Lastly, to avoid antibody induced virus activation or enhancement, we applied NNAS and DQ mutations to the Fc region to eliminate effector functions and extend half-life.

bioengineering↗

bioRxiv2021

Enhancing Drug-Drug Interaction Prediction Using Deep Attention Neural Networks

Drug-drug interactions are one of the main concerns in drug discovery. Accurate prediction of drug-drug interactions plays a key role in increasing the efficiency of drug research and safety when multiple drugs are c o-prescribed. With various data sources that describe the relationships and properties between drugs, the comprehensive approach that integrates multiple data sources would be considerably effective in making high-accuracy prediction. In this paper, we propose a Deep Attention Neural Network based Drug-Drug Interaction prediction framework, abbreviated as DANN-DDI, to predict unobserved drug-drug interactions. First, we construct multiple drug feature networks and learn drug representations from these networks using the graph embedding method; then, we concatenate the learned drug embeddings and design an attention neural network to learn representations of drug-drug pairs; finally, we adopt a deep neural network to accurately predict drug-drug interactions. The experimental results demonstrate that our model DANN-DDI has improved prediction performance compared with state-of-the-art methods. Moreover, the proposed model can predict novel drug-drug interactions and drug-drug interaction-associated events.

bioinformatics↗

bioRxiv2021

Metabolic characteristics of taste differences under the soil and hydroponic cultures of sweet potato leaves by using non-targeted metabolomics

Sweet potato leaves are consumed as green leafy vegetables in most of the world due to their nutritional and functional values, and the taste characteristics determine their commodity value and consumer acceptance. However, the metabolic composition and formation mechanism of taste quality in its leaves are not clear. In this study, we found that sweet potato leaves under different growing patterns, soil culture and hydroponic culture, which result in different taste quality. In particular, the taste quality in leafy sweet potato was effectively improved under hydroponic culture. Meanwhile, we further profiled metabolites in leaves of sweet potatoes under different growing patterns by using GC-QToF-MS. A total of 200 metabolites were identified, covering most of the metabolic pathways in plants. A comparison of the good taste and poor taste of sweet potato leaves resulted in 71 metabolites related to taste quality formation. In addition, the leaves with poor taste had lower levels of metabolites regarding amino acids metabolism, whereas was accompanied by high levels of metabolites in carbohydrates and secondary metabolism. This study provides new insights into the improvement of taste quality in leafy sweet potato.

plant biology↗

bioRxiv2021

A cell atlas of chromatin accessibility across 25 adult human tissues

Current catalogs of regulatory sequences in the human genome are still incomplete and lack cell type resolution. To profile the activity of human gene regulatory elements in diverse cell types and tissues in the human body, we applied single cell chromatin accessibility assays to 25 distinct human tissue types from multiple donors. The resulting chromatin maps comprising [~]500,000 nuclei revealed the status of open chromatin for over 750,000 candidate cis-regulatory elements (cCREs) in 54 distinct cell types. We further delineated cell type-specific and tissue-context dependent gene regulatory programs, and developmental stage specificity by comparing with a recent human fetal chromatin accessibility atlas. We finally used these chromatin maps to interpret the noncoding variants associated with complex human traits and diseases. This rich resource provides a foundation for the analysis of gene regulatory programs in human cell types across tissues and organ systems.

genomics↗

bioRxiv2021

Constructing smaller genome graphs via string compression

The size of a genome graph -- the space required to store the nodes, their labels and edges -- affects the efficiency of operations performed on it. For example, the time complexity to align a sequence to a graph without a graph index depends on the total number of characters in the node labels and the number of edges in the graph. The size of the graph also affects the size of the graph index that is used to speed up the alignment. This raises the need for approaches to construct space-efficient genome graphs. We point out similarities in the string encoding approaches of genome graphs and the external pointer macro (EPM) compression model. Supported by these similarities, we present a pair of linear-time algorithms that transform between genome graphs and EPM-compressed forms. We show that the algorithms result in an upper bound on the size of the genome graph constructed based on an optimal EPM compression. In addition to the transformation, we show that equivalent choices made by EPM compression algorithms may result in different sizes of genome graphs. To further optimize the size of the genome graph, we purpose the source assignment problem that optimizes over the equivalent choices during compression and introduce an ILP formulation that solves that problem optimally. As a proof-of-concept, we introduce RLZ-Graph, a genome graph constructed based on the relative Lempel-Ziv EPM compression algorithm. We show that using RLZ-Graph, across all human chromosomes, we are able to reduce the disk space to store a genome graph on average by 40.7% compared to colored de Bruijn graphs constructed by Bifrost under the default settings. The RLZ-Graph software is available at https://github.com/Kingsford-Group/rlzgraph

bioinformatics↗

bioRxiv2021

De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes

We report de novo genome assemblies, transcriptomes, annotations, and methylomes for the 26 inbreds that serve as the founders for the maize nested association mapping population. The data indicate that the number of pan-genes exceeds 103,000 and that the ancient tetraploid character of maize continues to degrade by fractionation to the present day. Excellent contiguity over repeat arrays and complete annotation of centromeres further reveal the locations and internal structures of major cytological landmarks. We show that combining structural variation with SNPs can improve the power of quantitative mapping studies. Finally, we document variation at the level of DNA methylation, and demonstrate that unmethylated regions are enriched for cis-regulatory elements that overlap QTL and contribute to changes in gene expression. One sentence summaryA multi-genome analysis of maize reveals previously unknown variation in gene content, genome structure, and methylation.

genomics↗

bioRxiv2020

Mouse retinal specializations reflect knowledge of natural environment statistics

Pressures for survival drive sensory circuit adaption to a species habitat, making it essential to statistically characterise natural scenes. Mice, a prominent visual system model, are dichromatic with enhanced sensitivity to green and UV. Their visual environment, however, is rarely considered. Here, we built a UV-green camera to record footage from mouse habitats. We found chromatic contrast to greatly diverge in the upper but not the lower visual field, an environmental difference that may underlie the species superior colour discrimination in the upper visual field. Moreover, training an autoencoder on upper but not lower visual field scenes was sufficient for the emergence of colour-opponent filters. Furthermore, the upper visual field was biased towards dark UV contrasts, paralleled by more light-offset-sensitive cells in the ventral retina. Finally, footage recorded at twilight suggests that UV promotes aerial predator detection. Our findings support that natural scene statistics shaped early visual processing in evolution. Lead contactFurther information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Thomas Euler (thomas.euler@cin.uni-tuebingen.de)

neuroscience↗

bioRxiv2020

Prokaryotic virus Host Predictor: a Gaussian model for host prediction of prokaryotic viruses in metagenomics

BackgroundViruses are ubiquitous biological entities, estimated to be the largest reservoirs of unexplored genetic diversity on Earth. Full functional characterization and annotation of newly-discovered viruses requires tools to enable taxonomic assignment, the range of hosts, and biological properties of the virus. Here we focus on prokaryotic viruses, which include phages and archaeal viruses, and for which identifying the viral host is an essential step in characterizing the virus, as the virus relies on the host for survival. Currently, the method for determining the viral host is either to culture the virus, which is low-throughput, time-consuming, and expensive, or to computationally predict the viral hosts, which needs improvements at both accuracy and usability. Here we develop a Gaussian model to predict hosts for prokaryotic viruses with better performances than previous computational methods. ResultsWe present here Prokaryotic virus Host Predictor (PHP), a software tool using a Gaussian model, to predict hosts for prokaryotic viruses using the differences of Ae-mer frequencies between viral and host genomic sequences as features. PHP gave a host prediction accuracy of 34% (genus level) on the VirHostMatcher benchmark dataset and a host prediction accuracy of 35% (genus level) on a new dataset containing 671 viruses and 60,105 prokaryotic genomes. The prediction accuracy exceeded that of two alignment-free methods (VirHostMatcher and WIsH, 28%-34%, genus level). PHP also outperformed these two alignment-free methods much (24%-38%vs 18%-20%, genus level) when predicting hosts for prokaryotic viruses which cannot be predicted by the BLAST-based or the CRISPR-spacer-based methods alone. Requiring a minimal score for making predictions (thresholding) and taking the consensus of the top 30 predictions further improved the host prediction accuracy of PHP. ConclusionsThe Prokaryotic virus Host Predictor software tool provides an intuitive and user-friendly API for the Gaussian model described herein. This work will facilitate the rapid identification of hosts for newly-identified prokaryotic viruses in metagenomic studies. Author SummaryProkaryotic viruses which include phages and archaeal viruses play an important role in balancing the global ecosystem by regulating the composition of bacteria and archaea in water and soil. Identifying the viral host is essential for characterizing the virus, as the virus relies on the host for survival. Currently, the method for determining the viral host is either to culture the virus which is low-throughput, time-consuming, and expensive, or to computationally predict the viral hosts which needs improvements at both accuracy and usability. This study developed a Gaussian model to predict hosts for prokaryotic viruses with better performances than previous computational methods. It will contribute to the rapid identification of hosts for prokaryotic viruses in metagenomic studies, and will extend our knowledge of virus-host interactions.

bioinformatics↗

bioRxiv2020

Evaluating the Effects of Propiconazole on Hard Fescue (Festuca brevipila) via RNA sequencing and Liquid Chromatography Mass Spectrometry

Propiconazole is often used to remove fungal endophytes from turfgrass to study the effects of Epichloe endophytes. However, besides a fungicidal effect, propiconazole can bind to the genes in the cytochrome P450 family and affect the biosynthesis of brassinosteroids. For this reason, outside of fungicidal application, propiconazole has also been used as plant growth regulator. In this study, we used a combination of RNA sequencing and liquid chromatography-mass spectrometry (LC-MS) to study how hard fescue (Festuca brevipila) responded to the high dose of propiconazole treatment. To test the long-term effect of the heavy use of propiconazole on plants, we inoculated with Microdochium nivale (causal agent of pink snow mold) half year post the last fungicide application. Propiconazole-treated plants showed enhanced pink snow mold resistance. This study suggested that the high dose use of propiconazole fungicide resulted in phenotypic and physiological changes in the plant such as slow growth and change in disease resistance. Genes and pathways affected by propiconazole identified in this study provide turfgrass breeders new information for genetic improvement of hard fescue and also provide turfgrass management new ways to control turfgrass diseases.

plant biology↗

bioRxiv2020

Endothelial exosome plays functional role during rickettsial infection

Spotted fever group rickettsioses (SFRs) are devastating human infections. Vascular endothelial cells (ECs) are the primary targets of infection. Edema resulting from EC barrier dysfunction occurs in the brain and lungs in most cases of lethal SFR, but the underlying mechanisms remain unclear. The aim of the study is to explore the potential role of Rickettsia (R)-infected, EC-derived exosomes (Exos) during infection. Using size-exclusion chromatography (SEC), we purified Exos from conditioned, filtered, bacteria-free media collected from R-infected human umbilical vein ECs (HUVECs) (R-ECExos) and plasma of R-infected mice (R-plsExos). We observed that rickettsial infection increases the release of heterogeneous plsExos, but endothelial exosomal size, morphology, and production were not significantly altered following infection. Compared to normal plsExos and ECExos, both R-plsExos and R-ECExos induced dysfunction of recipient normal brain microvascular Ecs (BMECs). The effect of R-plsExos on mouse recipient BMEC barrier function is dose-dependent. The effect of R-ECExos on human recipient BMEC barrier function is dependent on exosomal RNA cargo. Next-generation sequencing analysis and stem-loop quantitative reverse transcription PCR (RT-qPCR) validation revealed that R infection triggered the selective enrichment of endothelial exosomal mir-23a and mir-30b, which target the endothelial barrier. To our knowledge, this is the first report on the functional role of extracellular vesicles following infection by obligately intracellular bacteria. ImportanceSpotted fever group rickettsioses are devastating human infections. Vascular endothelial cells are the primary targets of infection. Edema resulting from endothelial barrier dysfunction occurs in the brain and lungs in most cases of lethal rickettsioses, but the underlying mechanisms remain unclear. The aim of the study is to explore the potential role of Rickettsia-infected, endothelial cell-derived exosomes during infection. We observed that rickettsial infection increases the release of heterogeneous plasma Exos, but endothelial exosomal size, morphology, and production were not significantly altered following infection. Rickettsia-infected, endothelial cell-derived exosomes induced dysfunction of recipient normal brain microvascular endothelial cells. The effect is dependent on exosomal RNA cargo. Next-generation sequencing analysis revealed that rickettsial infection triggered the selective enrichment of endothelial exosomal mir-23a and mir-30b, which target the endothelial barrier. To our knowledge, this is the first report on the functional role of extracellular vesicles following infection by obligately intracellular bacteria.

microbiology↗

bioRxiv2020

Identification of cell-type-specific marker genes from co-expression patterns in tissue samples

MotivationMarker genes, defined as genes that are expressed primarily in a single cell type, can be identified from the single cell transcriptome; however, such data are not always available for the many uses of marker genes, such as deconvolution of bulk tissue. Marker genes for a cell type, however, are highly correlated in bulk data, because their expression levels depend primarily on the proportion of that cell type in the samples. Therefore, when many tissue samples are analyzed, it is possible to identify these marker genes from the correlation pattern. ResultsTo capitalize on this pattern, we develop a new algorithm to detect marker genes by combining published information about likely marker genes with bulk transcriptome data in the form of a semi-supervised algorithm. The algorithm then exploits the correlation structure of the bulk data to refine the published marker genes by adding or removing genes from the list. Availability and implementationWe implement this method as an R package markerpen, hosted on https://github.com/yixuan/markerpen. Contactroeder@andrew.cmu.edu

bioinformatics↗