Biology subjects

Guan, Y.

Publications and source records attributed to Guan, Y..

At least 127 records · Page 7Linked to original sources

bioRxiv2020

Hypercholesterolemia risk associated GPR146 is an orphan G-protein coupled receptor that regulates blood cholesterol level in human and mouse

Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with dyslipidemia. However, about 95% of of these variants are located in genome noncoding regions and cluster in different loci. The disease-causing variant for each locus and underline mechanism remain largely unknown. We systematically analyzed these noncoding variants and found that rs1997243 is the disease-causing variant in locus 7p22, which is strongly associated with hypercholesterolemia. The rs1997243 risk allele is associated with increased expression of GPR146 in human and targeted activation of the rs1997243 site specifically up regulates GPR146 expression in cultured cells. GPR146 is an orphan G-protein coupled receptor that is located on plasma membrane and responses to stimulation of heat-inactivated serum. Disrupting gpr146 specifically in the liver decreases the blood cholesterol level and prevents high-fat or high-fat high-cholesterol diets induced hypercholesterolemia in mice. Thus we uncovered a novel G-protein coupled receptor that regulates blood cholesterol level in both human and mouse. Our results also suggest that antagonizing GPR146 function will be an effective strategy to treat hypercholesterolemia.

genetics↗

bioRxiv2019

DeepSleep: Fast and Accurate Delineation of Sleep Arousals at Millisecond Resolution by Deep Learning

Sleep arousals are transient periods of wakefulness punctuated into sleep. Excessive sleep arousals are associated with many negative effects including daytime sleepiness and sleep disorders. High-quality annotation of polysomnographic recordings is crucial for the diagnosis of sleep arousal disorders. Currently, sleep arousals are mainly annotated by human experts through looking at millions of data points manually, which requires considerable time and effort. Here we present a deep learning approach, DeepSleep, which ranked first in the 2018 PhysioNet Challenge for automatically segmenting sleep arousal regions based on polysomnographic recordings. DeepSleep features accurate (area under receiver operating characteristic curve of 0.93), high-resolution (5-millisecond resolution), and fast (10 seconds per sleep record) delineation of sleep arousals.

bioinformatics↗

bioRxiv2019

Leopard: fast decoding cell type-specific transcription factor binding landscape at single-nucleotide resolution

Decoding the cell type-specific transcription factor (TF) binding landscape at single-nucleotide resolution is crucial for understanding the regulatory mechanisms underlying many fundamental biological processes and human diseases. However, limits on time and resources restrict the high-resolution experimental measurements of TF binding profiles of all possible TF-cell type combinations. Previous computational approaches either can not distinguish the cell-context-dependent TF binding profiles across diverse cell types, or only provide a relatively low-resolution prediction. Here we present a novel deep learning approach, Leopard, for predicting TF-binding sites at single-nucleotide resolution, achieving the median area under receiver operating characteristic curve (AUROC) of 0.994. Our method substantially outperformed state-of-the-art methods Anchor and FactorNet, improving the performance by 19% and 27% respectively despite evaluated at a lower resolution. Meanwhile, by leveraging a many-to-many neural network architecture, Leopard features hundred-fold to thousand-fold speedup compared to current many-to-one machine learning methods.

bioinformatics↗

bioRxiv2019

Deep residual neural networks resolve quartet molecular phylogenies

Phylogenetic inference is of fundamental importance to evolutionary as well as other fields of biology, and molecular sequences have emerged as the primary data for this task. Although many phylogenetic methods have been developed to explicitly take into account substitution models of sequence evolution, such methods could fail due to model misspecification and insufficiency, especially in the face of heterogeneities in substitution processes across sites and among lineages. In this study, we propose to infer topologies of four-taxon trees using deep residual neural networks, a machine learning approach needing no explicit modeling of the subject system and having a record of success in solving complex non-linear inference problems. We train residual networks on simulated protein sequence data with extensive amino acid substitution heterogeneities. We show that the well-trained residual network predictors can outperform existing state-of-the-art inference methods such as the maximum likelihood method on diverse simulated test data, especially under extensive substitution heterogeneities. Reassuringly, residual network predictors generally agree with existing methods in the trees inferred from real phylogenetic data with known or widely believed topologies. We conclude that deep learning represents a powerful new approach to phylogenetic reconstruction, especially when sequences evolve via heterogeneous substitution processes. We present our best trained predictor in a freely available program named Phylogenetics by Deep Learning (PhyDL, https://gitlab.com/ztzou/phydl).

evolutionary biology↗

bioRxiv2019

The Manganese Salt (MnJ) Functions as A Potent Universal Adjuvant

Aluminum adjuvants have been used for a century in various vaccines due to its ability to potentiate humoral immunity and safety records since 1920s. Manganese is an essential micronutrient required for diverse biological activities in cells. We previously found that Mn2+ is a strong type I-interferon stimulator activating the cGAS-STING pathway. Herein we report that a colloidal manganese salt (MnJ) is a potent adjuvant to induce both humoral and cellular immune responses, particularly CTL activation. When administrated intranasally, MnJ was also a strong mucosal adjuvant, inducing high levels of IgA antibodies. MnJ strongly promoted dendritic cell maturation and antigen-specific T cell activation. Interestingly, IL-1/-18 induction and release by Mn2+-activated ASC-mediated inflammasomes were not observed. MnJ showed great adjuvant effects to all tested antigens including inactivated viruses, recombinant proteins and peptides by either intramuscular or intranasal immunization. These findings may have implications in developing potent but safe Mn2+-containing vaccines.

immunology↗

bioRxiv2019

Human microbiome sequences in the light of the Nubeam

We present Nubeam (nucleotide be a matrix) as a novel reference-free approach to analyze short sequencing reads. Nubeam represents nucleotides by matrices, transforms a read into a product of matrices, and based on which assigns numbers to reads. Nubeam capitalizes on the non-commutative property of matrix multiplication, such that different reads are assigned different numbers, and similar reads similar numbers. A sample, which is a collection of reads, becomes a collection of numbers that form an empirical distribution. We demonstrate that the genetic difference between samples can be quantified by the distance between empirical distributions. Nubeam can account for GC bias and nucleotide quality, and is computationally efficient; the K-mer method is a special case of Nubeam, but without those benefits. As a reference-free approach, Nubeam avoids reference bias and mapping bias and can work with organisms without reference genomes. Thus, Nubeam is ideal to analyze datasets from metagenomic whole-genome sequencing, where the amount of unmapped reads is substantial. When applied to human microbiome sequencing, Nubeam recapitulated findings made by mapping-based methods, and shed lights on contributions of unmapped reads. In particular, body habitats dominate clustering of unmapped pseudo-samples; there are more outliers in skin whole samples than the skin mapped pseudo-samples; and analysis of unmapped reads suggested that the sequencing depth is far from sufficient for urogenital samples.

genetics↗

bioRxiv2019

Single cell ATAC-seq in human pancreatic islets and deep learning upscaling of rare cells reveals cell-specific type 2 diabetes regulatory signatures

ObjectiveType 2 diabetes (T2D) is a complex disease characterized by pancreatic islet dysfunction, insulin resistance, and disruption of blood glucose levels. Genome wide association studies (GWAS) have identified >400 independent signals that encode genetic predisposition. More than 90% of the associated single nucleotide polymorphisms (SNPs) localize to non-coding regions and are enriched in chromatin-defined islet enhancer elements, indicating a strong transcriptional regulatory component to disease susceptibility. Pancreatic islets are a mixture of cell types that express distinct hormonal programs, and so each cell type may contribute differentially to the underlying regulatory processes that modulate T2D-associated transcriptional circuits. Existing chromatin profiling methods such as ATAC-seq and DNase-seq, applied to islets in bulk, produce aggregate profiles that mask important cellular and regulatory heterogeneity.\n\nMethodsWe present genome-wide single cell chromatin accessibility profiles in >1,600 cells derived from a human pancreatic islet sample using single-cell-combinatorial-indexing ATAC-seq (sci-ATAC-seq). We also developed a deep learning model based on the U-Net architecture to accurately predict open chromatin peak calls in rare cell populations.\n\nResultsWe show that sci-ATAC-seq profiles allow us to deconvolve alpha, beta, and delta cell populations and identify cell-type-specific regulatory signatures underlying T2D. Particularly, we find that T2D GWAS SNPs are significantly enriched in beta cell-specific and cross cell-type shared islet open chromatin, but not in alpha or delta cell-specific open chromatin. We also demonstrate, using less abundant delta cells, that deep-learning models can improve signal recovery and feature reconstruction of rarer cell populations. Finally, we use co-accessibility measures to nominate the cell-specific target genes at 104 non-coding T2D GWAS signals.\n\nConclusionsCollectively, we identify the islet cell type of action across genetic signals of T2D predisposition and provide higher-resolution mechanistic insights into genetically encoded risk pathways.

genomics↗

bioRxiv2019

Multiple Myeloma DREAM Challenge Reveals Epigenetic Regulator PHF19 As Marker of Aggressive Disease

While the past decade has seen meaningful improvements in clinical outcomes for multiple myeloma patients, a subset of patients do not benefit from current therapeutics for unclear reasons. Many gene expression-based models of risk have been developed, but each model uses a different combination of genes and often involve assaying many genes making them difficult to implement. We organized the Multiple Myeloma DREAM Challenge, a crowdsourced effort to develop models of rapid progression in newly diagnosed myeloma patients and to benchmark these against previously published models. This effort lead to more robust predictors and found that incorporating specific demographic and clinical features improved gene expression-based models of high risk. Furthermore, post challenge analysis identified a novel expression-based risk marker and histone modifier, PHF19, which featured prominently in several independent models. Lastly, we show that a simple four feature predictor composed of age, International Staging System stage (ISS), and expression of PHF19 and MMSET performs similarly to more complex models with many more gene expression features included.\n\nKey pointsO_LIMost comprehensive and unbiased assessment of prognostic biomarkers in MM resulting in a robust and parsimonious model.\nC_LIO_LIIdentification of PHF19 as the expression based biomarker most strongly associated with rapid progression in MM patients.\nC_LI

cancer biology↗

bioRxiv2019

Chromosome 17: neXt-MP50 C-HPP Challenge Completed

The C-HPP Team for Chromosome 17 has documented meeting the neXt-MP50 Missing Protein Challenge. Protein-level PE1 evidence including MS and protein-protein interaction data from the global proteomics community has reduced the number of PE2,3,4 proteins coded on Chromosome 17 by 50 since the 2016 baseline in neXtProt. As a follow-up to our analysis and prioritization of Chr 17 missing proteins last year, we describe what predictions and guidance were successful in this update and we explain the dynamics of a net reduction of PE2,3,4 Missing Proteins. This analysis can serve as a guide for other C-HPP chromosome teams seeking high-quality evidence for the 2129 remaining missing proteins.

systems biology↗

bioRxiv2019

Quantitative three-dimensional nondestructive imaging of whole anaerobic ammonium-oxidizing bacteria

Anaerobic ammonium-oxidizing (anammox) bacteria play a key role in the global nitrogen cycle and the treatment of nitrogenous wastewater. These functions are closely related to the unique biophysical structure of anammox bacteria. However, the research on the biophysical ultrastructure of intact anammox bacteria is lacking. In this study, in-situ three-dimensional nondestructive ultrastructure imaging of whole anammox cell was performed using synchrotron soft X-ray nano-computed tomography and the total variation-based simultaneous algebraic reconstruction technique (TV-SART). Statistical and quantitative analyses of the ultrastructures of intact anammox bacteria were performed. The linear absorption coefficient values of the ultrastructures of anammox bacteria were calculated and the asymmetric structure of the anammox bacteria was quantified. On this basis, the shape adaptation of the anammox bacteria responses to Fe2+ were explored, and the underlying regulation mechanism of Fe2+ on anammox bacteria was explored. Furthermore, a promising method to study the biophysical properties of cells in different environments and engineering processes was proposed.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC=\"FIGDIR/small/709188v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (23K):\norg.highwire.dtl.DTLVardef@1994e5eorg.highwire.dtl.DTLVardef@1e80137org.highwire.dtl.DTLVardef@a7f418org.highwire.dtl.DTLVardef@8a77e5_HPS_FORMAT_FIGEXP M_FIG C_FIG Statement of SignificanceAnaerobic ammonium-oxidizing (anammox) bacteria play key role in global nitrogen cycle, and this physiological function depends on the unique morphology of anammox bacteria. In this study, synchrotron soft-X ray imaging technique coupled with simultaneous algebraic reconstruction technique with total variation (SART-TV) algorithm were performed to quantify the three-dimensional ultrastructure of the whole anammox bacteria for the first time. On this basis, the shape adaptation and mechanism of the anammox bacteria responses to Fe2+ were explored and a promising method for detecting the physiological properties of anammox bacteria was proposed.

cell biology↗

bioRxiv2019

Monocarboxylate transporter 1 in Schwann cells is critical for maintenance of sensory nerve myelination during aging

Schwann cell (SC)-specific monocarboxylate transporter 1 (MCT1) knockout mice were generated by mating MCT1f/f mice with myelin protein zero (P0)-Cre mice. P0-Cre+/-, MCT1f/f mice have no detectable early developmental defects, but develop hypomyelination and reduced conduction velocity in sensory, but not motor, peripheral nerves during maturation and aging. Furthermore, enlarged node length and reduced mechanical sensitivity were evident in aged P0-Cre+/-, MCT1f/f mice. MCT1 deletion in SCs impairs both their glycolytic and mitochondrial functions, leading to altered lipid metabolism of triacylglycerides, diacylglycerides, and sphingomyelin, decreased expression of myelin-associated glycoprotein (MAG), and increased expression of c-Jun and p75-neurotrophin receptor, suggesting a regression of SCs to a less mature developmental state. Taken together, our results define the essential role of SC MCT1 in both SC metabolism and peripheral nerve maturation and aging.\n\nMain PointsO_LISC MCT1 deficiency causes hypomyelination of sensory, but not motor, axons during aging\nC_LIO_LIEnlarged node length of sensory axons is evident in mutant mouse with SC-specific MCT1 deletion\nC_LIO_LISelective ablation of MCT1 within SCs impairs glycolytic and mitochondrial functions\nC_LIO_LISC-specific MCT1 deficiency impairs proteins that regulate myelin and lipid metabolism in peripheral nerves\nC_LI

neuroscience↗

bioRxiv2019

Quantifying within-host evolution of H5N1 influenza in humans and poultry in Cambodia

Avian influenza viruses (AIVs) periodically cross species barriers and infect humans. The likelihood that an AIV will evolve mammalian transmissibility depends on acquiring and selecting mutations during spillover, but data from natural infection is limited. We analyze deep sequencing data from infected humans and domestic ducks in Cambodia to examine how H5N1 viruses evolve during spillover. Overall, viral populations in both species are predominated by low-frequency (<10%) variation shaped by purifying selection and genetic drift, and half of the variants detected within-host are never detected on the H5N1 virus phylogeny. However, we do detect a subset of mutations linked to human receptor binding and replication (PB2 E627K, HA A150V, and HA Q238L) that arose in multiple, independent humans. PB2 E627K and HA A150V were also enriched along phylogenetic branches leading to human infections, suggesting that they are likely human-adaptive. Our data show that H5N1 viruses generate putative human-adapting mutations during natural spillover infection, many of which are detected at >5% frequency within-host. However, short infection times, genetic drift, and purifying selection likely restrict their ability to evolve extensively during a single infection. Applying evolutionary methods to sequence data, we reveal a detailed view of H5N1 virus adaptive potential, and develop a foundation for studying host-adaptation in other zoonotic viruses. Author summaryH5N1 avian influenza viruses can cross species barriers and cause severe disease in humans. H5N1 viruses currently cannot replicate and transmit efficiently among humans, but animal infection studies and modeling experiments have suggested that human adaptation may require only a few mutations. However, data from natural spillover infection has been limited, posing a challenge for risk assessment. Here, we analyze a unique dataset of deep sequence data from H5N1 virus-infected humans and domestic ducks in Cambodia. We find that well-known markers of human receptor binding and replication arise in multiple, independent humans. We also find that 3 mutations detected within-host are enriched along phylogenetic branches leading to human infections, suggesting that they are likely human-adapting. However, we also show that within-host evolution in both humans and ducks are shaped heavily by purifying selection and genetic drift, and that a large fraction of within-host variation is never detected on the H5N1 phylogeny. Taken together, our data show that H5N1 viruses do generate human-adapting mutations during natural infection. However, short infection times, purifying selection, and genetic drift may severely limit how much H5N1 viruses can evolve during the course of a single infection.

microbiology↗

bioRxiv2019

T Lymphopoiesis from Pluripotent Stem Cells by Defined Transcription Factors at Single Cell Resolution

Achievement of immunocompetent and therapeutic T lymphopoiesis from pluripotent stem cells is a central aim in T cell regenerative medicine. To date, preferentially regenerating T lymphopoiesis in vivo from pluripotent stem cells (PSC) remains a practical challenge. Here we documented that synergistic and transient expression of Runx1 and Hoxa9 restricted in the time window of endothelial to hematopoietic transition and hematopoietic maturation stages induced in vitro from PSC (iR9-PSC) preferentially generated engraftable hematopoietic progenitors capable of homing to thymus and developing into mature T (iT) cells in primary and secondary immunodeficient recipients. Single-cell transcriptome and functional analyses illustrated the cellular trajectory of T lineage induction from PSC, unveiling the T-lineage specification determined at as early as hemogenic endothelial cell stage and identifying the bona fide pre-thymic progenitors. The iT cells distributed normally in central and peripheral lymphoid organs and exhibited abundant TCR{beta} repertoire. The regenerative T lymphopoiesis rescued the immune-surveillance ability in immunodeficient mice. Furthermore, gene-edited iR9-PSC produced tumor-specific-T cells in vivo that effectively eradicated tumor cells. This study provides insight into universal generation of functional and therapeutic T lymphopoiesis from the unlimited and editable PSC source.

immunology↗

bioRxiv2019

Mesenchymal stem cells restore local microenvironment and systemically suppress leukemia via reprogramming macrophages

Bone marrow (BM) mesenchymal stem cells (MSCs) are critical components of the BM microenvironment and play an essential role in supporting hematopoiesis. Dysfunction of MSCs is associated with the impaired BM microenvironment that promotes leukemia development. However, whether and how restoration of the impaired BM microenvironment can inhibit leukemia development remain unknown. Using an established leukemia model and the RNA-seq analysis, we discovered functional degeneration of MSCs during leukemia progression. Importantly, intra-BM instead of systemic transfusion of donor healthy MSCs restored the BM microenvironment, thus systemically altering cytokine expression patterns, improving normal hematopoiesis, reducing tumor burden, and ultimately prolonging survival of the leukemia-bearing mice. Donor MSC treatment restored the function of host MSCs and reprogrammed host macrophages to fulfill tissue-repair function. Transfusion of MSC-reprogrammed macrophages largely recapitulated the therapeutic effects of MSCs. Further, we found that donor MSCs reprogrammed macrophages to reduce leukemia burden through autocrine of IL-6. Taken together, our study reveals that donor MSCs reprogram host macrophages to restore the BM microenvironment and inhibit leukemia development, thus offering rationales for local MSC administration as a potentially effective therapy for leukemia.\n\nKey PointsKey Point 1: Intra-BM transfusion of MSCs restores the BM microenvironment, improves thrombopoiesis, and suppresses MDS/MPN initiated by Nras mutation.\n\nKey Point 2: Donor MSCs reprogram macrophages to restore the BM microenvironment, improve thrombopoiesis, and suppress leukemia.

cancer biology↗

bioRxiv2018

A robust image registration interface for large volume brain atlas

Mapping the brain structures in three-dimensional accurately is critical for an in-depth understanding of the brain functions. By using the brain atlas as a hub, mapping detected datasets into a standard brain space enables efficiently use of various datasets. However, because of the heterogeneous and non-uniform characteristics of the brain structures at cellular level brought with the recently developed high-resolution whole-brain microscopes, traditional registration methods are difficult to apply to the robust mapping of various large volume datasets. Here, we proposed a robust Brain Spatial Mapping Interface (BrainsMapi) to address the registration of large volume datasets at cellular level by introducing the extract regional features of the anatomically invariant method and a strategy of parameter acquisition and large volume transformation. By performing validation on model data and biological images, BrainsMapi can not only achieve robust registration on sample tearing and streak image datasets, different individual and modality datasets accurately, but also are able to complete the registration of large volume dataset at cellular level which dataset size reaches 20 TB. Besides, it can also complete the registration of historical vectorized dataset. BrainsMapi would facilitate the comparison, reuse and integration of a variety of brain datasets.

neuroscience↗

bioRxiv2018

The Association between Alcohol Consumption and Telomere Length: A Meta-Analysis Focusing on Observational Studies

BackgroundBoth telomere length and alcohol consumption play important roles in carcinogenesis and biological age. Many efforts have been made to investigate the association between alcohol consumption and telomere length. However, no consensus has been reached yet.\n\nMethodsIn this article, we performed a meta-analysis to integrate the investigation results in the literature about the association between alcohol consumption and telomere length. After searching articles published between 2000 and 2016, 21 articles (including 27 analyses, total sample size 35,891) met our eligibility criteria.\n\nResultsWe found a significant association between alcohol consumption and telomere length (Fishers combined p-value = 3.52E-8 and Liptaks weighted p-value = 8.24E-3). We also found that the significance of the association between alcohol consumption and telomere length varies with study type (cohort, case-control, or cross-sectional) and study population (Europe, Asia, American, or Australia).\n\nConclusionsCombined evidence showed that alcohol consumption is associated with telomere length. The consistent quantifications of alcohol consumption and telomere length would benefit the future aggregation of the evidence from different studies.

cancer biology↗

bioRxiv2018

RNA-Seq analysis of compatible and incompatible styles of Pyrus species at the beginning of pollination

In Rosaceae, incompatible pollen can penetrate into the style during the gametophytic self-incompatibility response. It is therefore considered a stylar event rather than a stigmatic event. In this study, we explored the differences in gene expression between compatibility and incompatibility in the early stage of pollination. The self-compatible pear variety \"Jinzhuili\" is a naturally occurring bud mutant from \"Yali\", a leading Chinese native cultivar exhibiting typical gametophytic self-incompatibility. We collected the styles of Yali and Jinzhuili at 0.5 and 2 h after self-pollination and then performed high-throughput sequencing. According to the pathway enrichment analysis of the differentially expressed genes, \"plant-pathogen interaction\" was the most represented pathway. Quantitative PCR was used to validate these differential genes. The expression levels of genes related to pollen growth and disease inhibition, such as LRR (LEUCINE-RICH REPEAT EXTENSIN), resistance, and defensin, differed significantly between compatible and incompatible pollination. Interestingly, at 0.5 h, most of these genes were upregulated in the compatible pollination system compared with the incompatible pollination system. Calcium ion transport, which requires ATPase, also demonstrated upregulated expression. In summary, the self-incompatibility reaction was initiated when the pollen came into contact with the stigma.

plant biology↗

bioRxiv2018

Tissue-specific Gene Expression Prediction Associates Vitiligo with SUOX through an Active Enhancer

Vitiligo is an autoimmune disease featuring destruction of melanocytes, which results in patchy depigemtation of skin and hair; two vitiligo GWAS studies identified multiple significant associations, including SNPs in 12q13.2 region. But one study ascribed the association to IKZF4 because it encodes a regulator of T cell activation and is associated with two autoimmune diseases; while the other study ascribed the association to PMEL because it encodes melanocyte protein and has the strongest differential expression between vitiligo lesions and perilesional normal skins. Here we show that vitiligo associated gene in 12q13.2 region is SUOX. Reanalyzing one GWAS dataset, we predicted tissue-specific gene-expression by leveraging Genotype-Tissue Expression (GTEx) datasets, and performed association mapping between the predicted gene-expressions and vitiligo status. SUOX expression is significantly associated with vitiligo in both Nerve (tibia) and Skin (sun exposed) tissues. Epigenetic marks encompass the most significant eQTL of SUOX in both nerve and skin tissues suggest a putative enhancer 3Kb downstream of SUOX. We silenced the putative enhancer using the CRISPR interference system and observed 50% decrease in SUOX expression in K562 cells, a cell line that has similar DNase hypersensitive sites and gene expression pattern to the skin tissue at SUOX locus. Our work provided an example to make sense GWAS hits through examining factors that affect gene expression both computationally and experimentally.

genetics↗