Biology subjects

Yang, P.

Publications and source records attributed to Yang, P..

At least 181 records · Page 10Linked to original sources

bioRxiv2020

Mistranslating tRNA identifies a deleterious S213P mutation in the Saccharomyces cerevisiae eco1-1 allele

Mistranslation occurs when an amino acid not specified by the standard genetic code is incorporated during translation. Since the ribosome does not read the amino acid, tRNA variants aminoacylated with a non-cognate amino acid or containing a non-cognate anticodon dramatically increase the frequency of mistranslation. In a systematic genetic analysis, we identified a suppression interaction between tRNASerUGG, G26A, which mistranslates proline codons by inserting serine, and eco1-1, a temperature sensitive allele of the gene encoding an acetyltransferase required for sister chromatid cohesion. The suppression was partial with a tRNA that inserts alanine at proline codons and not apparent for a tRNA that inserts serine at arginine codons. Sequencing of the eco1-1 allele revealed a mutation that would convert the highly conserved serine 213 within {beta}7 of the GCN5-related N-acetyltransferase core to proline. Mutation of P213 in eco1-1 back to the wild-type serine restored function of the enzyme at elevated temperature. Our results indicate the utility of mistranslating tRNA variants to identify functionally relevant mutations and identify eco1 as a reporter for mistranslation. We propose that mistranslation could be used as a tool to treat genetic disease.

genetics↗

bioRxiv2020

Tead1 reciprocally regulates adult β-cell proliferation and function

Proliferative quiescence in {beta}-cells is required to maintain functional competence. While this presents a significant hurdle in regenerative therapy for diabetes, the molecular underpinnings of this reciprocal relationship remain unclear. Here, we demonstrate that TEAD1, the transcription effector of the mammalian-Hippo pathway, drives developmental stage-specific {beta}-cell proliferative capacity in conjunction with its functional maturation. TEAD1 promotes adult {beta}-cell mature identity by direct transcriptional control of a network of critical {beta}-cell transcription factors, including, Pdx1, Nkx6.1, and MafA, while its regulation of Cdkn2a maintains proliferative quiescence. Consequently, mice with either constitutive or inducible genetic deletion of TEAD1 in {beta}-cells developed overt diabetes due to a severe loss of secretory function despite induction of proliferation. Furthermore, we show that TEAD1 has a similar regulatory role in human {beta}-cells. Consistent with this function in {beta}-cells, variants in TEAD1 have been associated with c-HOMA-B in American Indians. We propose that TEAD1 is an essential intrinsic molecular switch coordinating adult {beta}-cell proliferative quiescence with mature identity and its differential modulation may be necessary to overcome the challenge of inducing proliferation with functional competence in human beta cells.

molecular biology↗

bioRxiv2020

OGP: A Repository of Experimentally Characterized O-Glycoproteins to Facilitate Studies on O-Glycosylation

Numerous studies on cancer, biopharmaceuticals, and clinical trials have necessitated comprehensive and precise analysis of protein O-glycosylation. However, the lack of updated and convenient databases deters the storage and utilization of emerging O-glycoprotein data. To resolve this issue, an O-glycoprotein repository named OGP was established in this work. It was constructed with a collection of O-glycoprotein data from different sources. OGP contains 9354 O-glycosylation sites and 11,633 site-specific O-glycans mapping to 2133 O-glycoproteins, and it is the largest O-glycoprotein repository thus far. Based on the recorded O-glycosites, an O-glycosylation site prediction tool was developed. Moreover, an OGP-backed website is already available (http://www.oglyp.org/). The website comprises four specially designed and user-friendly modules: Statistic Analysis, Database Search, Site Prediction, and Data Submit. The first version of OGP repository and the website allow users to obtain vast O-glycoprotein related information, such as protein accession numbers, glycopeptides, site-specific glycan structures, experimental methods, and potential glycosylation sites. O-glycosylation data mining can be performed efficiently on this website, which can greatly facilitates O-glycosylation studies.

bioinformatics↗

bioRxiv2020

Enhanced stress tolerance through reduction of G3BP and suppression of stress granules

Stress granules (SG) are membrane-less ribonucleoprotein condensates that form in response to various stress stimuli via phase separation. SG act as a protective mechanism to cope with acute stress, but persistent SG have cytotoxic effects that are associated with several age-related diseases. Here, we demonstrate that the testis-specific protein, MAGE-B2, increases cellular stress tolerance by suppressing SG formation through translational inhibition of the key SG nucleator G3BP. MAGE-B2 reduces G3BP protein levels below the critical concentration for phase separation and suppresses SG initiation. Importantly, knockout of the MAGE-B2 mouse ortholog confers hypersensitivity of the male germline to heat stress in vivo. Thus, MAGE-B2 provides cytoprotection to maintain mammalian spermatogenesis, a highly thermo-sensitive process that must be preserved throughout reproductive life. These results demonstrate a mechanism that allows for tissue-specific resistance against stress through fine-tuning phase separation and could aid in the development of male fertility therapies.

cell biology↗

bioRxiv2019

CiteFuse enables multi-modal analysis of CITE-seq data

Multi-modal profiling of single cells represents one of the latest technological advancements in molecular biology. Among various single-cell multi-modal strategies, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) allows simultaneous quantification of two distinct species: RNA and surface marker proteins (ADT). Here, we introduce CiteFuse, a streamlined package consisting of a suite of tools for pre-processing, modality integration, clustering, differential RNA and ADT expression analysis, ADT evaluation, ligand-receptor interaction analysis, and interactive web-based visualization of CITE-seq data. We show the capacity of CiteFuse to integrate the two data modalities and its relative advantage against data generated from single modality profiling. Furthermore, we illustrate the pre-processing steps in CiteFuse and in particular a novel doublet detection method based on a combined index of cell hashing and transcriptome data. Collectively, we demonstrate the utility and effectiveness of CiteFuse for the integrative analysis of transcriptome and epitope profiles from CITE-seq data.

bioinformatics↗

bioRxiv2019

scClassify: hierarchical classification of cells

Cell type identification is a key computational challenge in single-cell RNA-sequencing (scRNA-seq) data. To capitalize on the large collections of well-annotated scRNA-seq datasets, we present scClassify, a hierarchical classification framework based on ensemble learning. scClassify can identify cells from published scRNA-seq datasets more accurately and more finely than in the original publications. We also estimate the cell number needed for accurate classification anywhere in a cell type hierarchy.

bioinformatics↗

bioRxiv2019

Autoencoder-based cluster ensembles for single-cell RNA-seq data analysis

BackgroundSingle-cell RNA-sequencing (scRNA-seq) is a transformative technology, allowing global transcriptomes of individual cells to be profiled with high accuracy. An essential task in scRNA-seq data analysis is the identification of cell types from complex samples or tissues profiled in an experiment. To this end, clustering has become a key computational technique for grouping cells based on their transcriptome profiles, enabling subsequent cell type identification from each cluster of cells. Due to the high feature-dimensionality of the transcriptome (i.e. the large number of measured genes in each cell) and because only a small fraction of genes are cell type-specific and therefore informative for generating cell type-specific clusters, clustering directly on the original feature/gene dimension may lead to uninformative clusters and hinder correct cell type identification.\n\nResultsHere, we propose an autoencoder-based cluster ensemble framework in which we first take random subspace projections from the data, then compress each random projection to a low-dimensional space using an autoencoder artificial neural network, and finally apply ensemble clustering across all encoded datasets for generating clusters of cells. We employ four evaluation metrics to benchmark clustering performance and our experiments demonstrate that the proposed autoencoder-based cluster ensemble can lead to substantially improved cell type-specific clusters when applied with both the standard k-means clustering algorithm and a state-of-the-art kernel-based clustering algorithm (SIMLR) designed specifically for scRNA-seq data. Compared to directly using these clustering algorithms on the original datasets, the performance improvement in some cases is up to 100%, depending on the evaluation metrics used.\n\nConclusionsOur results suggest that the proposed framework can facilitate more accurate cell type identification as well as other downstream analyses. The code for creating the proposed autoencoder-based cluster ensemble framework is freely available from https://github.com/gedcom/autoencoder_cluster_ensemble

bioinformatics↗

bioRxiv2019

Suppression of membranous LRP5 recycling, WNT/β-catenin signaling, and colorectal tumorigenesis by 15-LOX-1 peroxidation of PI3P_linoleic acid

Aberrant Wnt/{beta}-catenin activation is a major driver of colorectal cancer (CRC), which is typically initiated by APC mutations. Additional modifiable factors beyond APC mutations have been recognized to be important for further potentiation of aberrant {beta}-catenin activation to promote colorectal tumorigenesis. These factors have yet to be clearly identified. Western-type diets are increasingly enriched in linoleic acid (LA). LA-enriched diet however promotes chemically-induced colorectal tumorigenesis in rodent models. Furthermore, the main metabolizing enzyme of LA, 15-lipoxygenase-1 (15-LOX-1), is transcriptionally silenced in CRC. Whether LA and 15-LOX-1 affect Wnt/{beta}-catenin signaling to modulate colorectal tumorigenesis is poorly understood. Herein, we report that high dietary LA promoted colorectal tumorigenesis in mice with intestinally targeted APC mutation (Apc{Delta}580) by upregulating a Wnt receptor, LRP5 expression, and {beta}-catenin activation. 15-LOX-1 transgenic expression in intestinal epithelial cells suppressed LRP5 expression, {beta}-catenin activation and subsequently CRC in these mice. In particular, 15-LOX-1 peroxidation of LA in phosphatidylinositol-3-phosphates (PI3P_LA) into PI3P_13-HODE decreased PI3P binding to SNX17and LRP5, which inhibited LRP5 recycling from endosomes to the plasma membrane, thereby leading to an increase of LRP5 lysosomal degradation. Our findings demonstrate for the first time that 15-LOX-1 metabolism of LA in PI3P to regulate LRP5 membrane abundance is a modifiable factor of Wnt/{beta}-catenin aberrant signaling that could be potentially therapeutically targeted to suppress colorectal tumorigenesis and progression.

cancer biology↗

bioRxiv2019

Long noncoding RNA AVAN promotes antiviral innate immunity by interacting with TRIM25 and enhancing the transcription of FOXO3a

Accumulating evidence has shown that long noncoding RNAs (lncRNAs) are involved in several biological processes, including immune responses. However, the role of lncRNAs in antiviral innate immune responses remains largely unexplored. Here, we identify an uncharacterized human lncRNA from influenza A virus (IAV) patients, antivirus and activate neutrophil (AVAN), that is significantly up-regulated upon virus infection. Mechanistically, nuclear lncRNA-AVAN positively regulates the transcription of forkhead box O3A (FOXO3a) by associating with its promoter and inducing chromatin remodeling to promote neutrophil chemotaxis. Furthermore, we also found that cytoplasmic lncRNA-AVAN directly binds tripartite motif containing 25 (TRIM25) and enhances the association of TRIM25 and Retinoic acid inducible gene-1 proteins (RIG-I) and the ubiquitylation of RIG-I, thereby promoting TRIM25- and RIG-I-mediated antiviral innate immune signaling. More importantly, we enforced the expression of AVAN in transgenic mice and found that it significantly alleviated IAV virulence and virus production. Collectively, these findings highlight the potential clinical implications of lncRNA-AVAN as a key positive regulator of the antiviral innate immune response and a promising target for developing broad antiviral therapeutics.

immunology↗

bioRxiv2019

Multilayered N-glycoproteomics reveals impaired N-glycosylation promoting Alzheimer’s disease

Alzheimers disease (AD) is one of the most common neurodegenerative diseases that currently lacks clear pathogenesis and effective treatment. Protein glycosylation is ubiquitous in brain tissue and site-specific analysis of N-glycoproteome, which is technically challenging, can advance our understanding of the glycoproteins role in AD. In this study, we profiled the multilayered variations in proteins, N-glycosites, N-glycans, and in particular site-specific N-glycopeptides in the APP/PS1 and wild type mouse brain through combining pGlyco 2.0 strategy with other quantitative N-glycoproteomic strategies. The comprehensive brain N-glycoproteome landscape was constructed, and rich details of the heterogeneous site-specific protein N-glycosylations were exhibited. Quantitative analyses explored generally downregulated N-glycosylation involving proteins such as glutamate receptors, as well as fucosylated and oligo-mannose type glycans in APP/PS1 mice versus wild type mice. Moreover, our preliminary functional study revealed that N-glycosylation was crucial for the membrane localization of NCAM1 and for maintaining the excitability and viability of neuron cells. Our work offered a panoramic view of the N-glycoproteomes in Alzheimers disease and revealed that generally impaired N-glycosylation promotes Alzheimers disease progression.

systems biology↗

bioRxiv2019

PGCN: Disease gene prioritization by disease and gene embedding through graph convolutional neural networks

MotivationProper prioritization of candidate genes is essential to the genome-based diagnostics of a range of genetic diseases. However, it is a highly challenging task involving limited and noisy knowledge of genes, diseases and their associations. While a number of computational methods have been developed for the disease gene prioritization task, their performance is largely limited by manually crafted features, network topology, or pre-defined rules of data fusion. ResultsHere, we propose a novel graph convolutional network-based disease gene prioritization method, PGCN, through the systematic embedding of the heterogeneous network made by genes and diseases, as well as their individual features. The embedding learning model and the association prediction model are trained together in an end-to-end manner. We compared PGCN with five state-of-the-art methods on the Online Mendelian Inheritance in Man (OMIM) dataset for tasks to recover missing associations and discover associations between novel genes and diseases. Results show significant improvements of PGCN over the existing methods. We further demonstrate that our embedding has biological meaning and can capture functional groups of genes. AvailabilityThe main program and the data are available at https://github.com/lykaust15/Disease_gene_prioritization_GCN.

bioinformatics↗

bioRxiv2018

Identification of TTN as a novel candidate gene for atrioventricular block in a Chinese pedigree by whole-exome sequencing

PurposeCardiovascular diseases are the most common cause of death globally. In which atrioventricular block (AVB) is a common disorder with genetic causes, but the responsible genes have not been fully identified yet. To determine the underlying causative genes involved in cardiac AVB, here we report a three-generation Chinese family with severe autosomal dominant cardiac AVB that has been ruled out as being caused by known genes mutations.\n\nMethodsWhole-exome sequencing was performed in five affected family members across three generations, and co-segregation analysis was validated on other members of this family.\n\nResultsWhole-exome sequencing and subsequent co-segregation validation identified a novel germline heterozygous point missense mutation, c.49287C>A (p.N16429K), in the titin (TTN, NM_001267550.2) gene in all 5 affected family members, but not in the unaffected family members. The point mutation is predicted to be functionally deleterious by in-silico software tools. Our finding was further supported by the conservative analysis across species.\n\nConclusionBased on this study, TTN was identified as a potential novel candidate gene for autosomal dominant AVB; this study expands the mutational spectrum of TTN gene and is the first to implicate TTN mutations as AVB disease causing in a Chinese pedigree.

genetics↗

bioRxiv2018

Multi-Omic Profiling Reveals Dynamics of the Phased Progression of Pluripotency

Pluripotency is highly dynamic and progresses through a continuum of pluripotent stem-cell states. The two states that bookend the pluripotency continuum, naive and primed, are well characterized, but our understanding of the intermediate states and transitions between them remain incomplete. Here, we dissect the dynamics of pluripotent state transitions underlying pre-to post-implantation epiblast differentiation. Through comprehensive mapping of the proteome, phosphoproteome, transcriptome, and epigenome of mouse embryonic stem cells transitioning from naive to primed pluripotency, we find that rapid, acute, and widespread changes to the phosphoproteome precede ordered changes to the epigenome, transcriptome, and proteome. Reconstruction of kinase-substrate networks reveals signaling cascades, dynamics, and crosstalk. Distinct waves of global proteomic changes demarcate discrete phases of pluripotency, characterized by cell-state-specific surface marker expression. Our data provide new insights into the multi-layered control of the phased progression of pluripotency and a foundation for modeling mechanisms underlying pre-to post-implantation epiblast differentiation.\n\nHIGHLIGHTSO_LIMulti-ome maps of cells transitioning from naive to primed pluripotency\nC_LIO_LIPhosphoproteome dynamics precede changes to epigenome, transcriptome, and proteome\nC_LIO_LIKinase-substrate network reconstruction uncovers signaling dynamics and crosstalk\nC_LIO_LIProteins and cell surface markers that track pluripotent state transitions\nC_LIO_LIComparative analysis of mouse and human pluripotent states\nC_LI

genomics↗

bioRxiv2018

scMerge: Integration of multiple single-cell transcriptomics datasets leveraging stable expression and pseudo-replication

Concerted examination of multiple collections of single cell RNA-Seq (scRNA-Seq) data promises further biological insights that cannot be uncovered with individual datasets. However, such integrative analyses are challenging and require sophisticated methodologies. To enable effective interrogation of multiple scRNA-Seq datasets, we have developed a novel algorithm, named scMerge, that removes unwanted variation by combining stably expressed genes and utilizing pseudo-replicates across datasets. Analysis of large collections of publicly available datasets demonstrates that scMerge performs well in multiple scenarios and enhances biological discovery, including inferring cell developmental trajectories.

bioinformatics↗

bioRxiv2018

NF-Y Controls Fidelity of Transcription Initiation at Gene Promoters Through Maintenance of the Nucleosome-Depleted Region

Faithful transcription initiation is critical for accurate gene expression, yet the mechanisms underlying specific transcription start site (TSS) selection in mammals remain unclear. Here, we show that the histone-fold domain protein NF-Y, a ubiquitously expressed transcription factor, controls the fidelity of transcription initiation at gene promoters. We report that NF-Y maintains the region upstream of TSSs in a nucleosome-depleted state while simultaneously protecting this accessible region against aberrant and/or ectopic transcription initiation. We find that loss of NF-Y binding in mammalian cells disrupts the promoter chromatin landscape, leading to nucleosomal encroachment over the canonical TSS. Importantly, this chromatin rearrangement is accompanied by upstream relocation of the transcription preinitiation complex and ectopic transcription initiation. Further, this phenomenon generates aberrant extended transcripts that undergo translation, disrupting gene expression profiles. These results establish NF-Y as a central player in TSS selection in metazoans and highlight the deleterious consequences of inaccurate transcription initiation.

genomics↗

bioRxiv2018

OptoGranules reveal the evolution of stress granules to ALS-FTD pathology

Stress granules are non-membranous assemblies of mRNA and protein that form in response to a variety of stressors. Genetic, pathologic, biophysical and cell biological studies have implicated disturbances in the dynamics of membrane-less organelles, such as stress granules, as a pathobiological component of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD)1-12. This confluence of evidence has inspired the hypothesis that these diseases reflect an underlying disturbance in the dynamics and material properties of stress granules; however, this concept has remained largely untestable in available models of stress granule assembly, which require the confounding variable of exogenous stressors. Here we demonstrate the development and use of a light-inducible stress granule system, termed OptoGranules, which permits discrete, experimental control of the dynamics and material properties of stress granules in living cells in the absence of exogenous stressors. The nucleator in this system is Opto-G3BP1, a light-sensitive chimeric protein assembled from the intrinsically disordered region (IDR) and RNA-binding domain of G3BP1 combined with the light-sensitive oligomerization domain of Arabidopsis thaliana cryptochrome 2 (CRY2) photolyase homology region (PHR). Upon stimulation with blue light, Opto-G3BP1 initiates the rapid assembly of dynamic, cytoplasmic, liquid granules that are composed of canonical stress granule components, including G3BP1, PABP, TIA1, TIAR, eIF4G, eIF3{eta}, ataxin 2, GLE1, TDP-43 and polyadenylated RNA. With this system, we demonstrate that persistent or repetitive assembly of stress granules is cytotoxic and is accompanied by the evolution of stress granules to neuronal cytoplasmic inclusions that recapitulate the pathology of ALS-FTD.

neuroscience↗

bioRxiv2018

Data-mining of Antibiotic Resistance Genes Provides Insight into the Community Structure of Ocean Microbiome

BackgroundAntibiotics have been spread widely in environments, asserting profound effects on environmental microbes as well as antibiotic resistance genes (ARGs) within these microbes. Therefore, investigating the associations between ARGs and bacterial communities become an important issue for environment protection. Ocean microbiomes are potentially large ARG reservoirs, but the marine ARG distribution and its associations with bacterial communities remain unclear.\n\nMethodswe have utilized the big-data mining techniques on ocean microbiome data to analysis the marine ARGs and bacterial distribution on a global scale, and applied comprehensive statistical analysis to unveil the associations between ARG contents, ocean microbial community structures, and environmental factors by reanalyzing 132 metagenomic samples from the Tara Oceans project.\n\nResultsWe identified in total 1,926 unique ARGs and found that: firstly, ARGs are more abundant and diverse in the mesopelagic zone than other water layers. Additionally, ARG-enriched genera are closely connected in co-occurrence network. We also found that ARG-enriched genera are often more abundant than their ARG-less neighbors. Furthermore, we found that samples from the Mediterranean that is surrounded by human activities often contain more ARGs.\n\nConclusionOur research for investigating the marine ARG distribution and revealing the association between ARG and bacterial communities provide a deeper insight into the marine bacterial communities. We found that ARG-enriched genera were often more abundant than their ARG-less neighbors in the same environment, indicating that genera enriched with ARGs might possess an advantage over others in the competition for survival in the oceanic microbial communities.

microbiology↗

bioRxiv2017

Housekeeping genes, revisited at the single-cell level

BackgroundSingle-cell RNA-seq (scRNA-seq) profiling has revealed remarkable variation in transcription, suggesting that expression of many genes at the single-cell level are intrinsically stochastic and noisy. Yet, on cell population level, a subset of genes traditionally referred to as housekeeping genes (HKGs) are found to be stably expressed in different cell and tissue types. It is therefore critical to question whether stably expressed genes (SEGs) can be identified on the single-cell level, and if so, how their expression stability can be assessed? We have developed a computational framework for ranking expression stability of genes in single cells. Here we evaluate the proposed framework and characterize SEGs derived from two scRNA-seq datasets that profile early human and mouse development.\n\nResultsHere, we show that gene expression stability indices derived from the early human and mouse development scRNA-seq datasets are highly reproducible and conserved across species. We demonstrate that SEGs identified from single cells based on their stability indices are considerably more stable than HKGs defined previously from cell populations across 10 diverse biological systems. Our analyses indicate that SEGs are inherently more stable at the single-cell level and their characteristics reminiscent of HKGs, suggesting their potential role in sustaining essential functions in individual cells.\n\nConclusionsSEGs identified in this study have immediate utility both for understanding variation/stability of single-cell transcriptomes and for practical applications including scRNA-seq data normalization, the proposed framework can be applied to identify genes with stable expression in other scRNA-seq datasets.

bioinformatics↗