Biology subjects

Dai, X.

Publications and source records attributed to Dai, X..

120 records · Page 7Linked to original sources

bioRxiv2019

An MCMC-based method for Bayesian inference of natural selection from time series DNA data across linked loci

Recent advances in DNA sequencing techniques have made it possible to monitor genomes in great detail over time. This improvement provides an opportunity for us to study natural selection based on time serial samples of genomes while accounting for genetic recombination effect and local linkage information. Such genomic time series data allow for more accurate estimation of population genetic parameters and hypothesis testing on the recent action of natural selection. In this work, we develop a novel Bayesian statistical framework for inferring natural selection at a pair of linked loci by capitalising on the temporal aspect of DNA data with the additional flexibility of modelling the sampled chromosomes that contain unknown alleles. Our approach is based on a hidden Markov model where the underlying process is a two-locus Wright-Fisher diffusion with selection, which enables us to explicitly model genetic recombination and local linkage. The posterior probability distribution for the selection coefficients is obtained by using the particle marginal Metropolis-Hastings algorithm, which allows us to efficiently calculate the likelihood. We evaluate the performance of our Bayesian inference procedure through extensive simulations, showing that our method can deliver accurate estimates of selection coefficients, and the addition of genetic recombination and local linkage brings about significant improvement in the inference of natural selection. We illustrate the utility of our approach on real data with an application to ancient DNA data associated with white spotting patterns in horses.

genetics↗

bioRxiv2019

Pancreas patch-seq links physiologic dysfunction in diabetes to single-cell transcriptomic phenotypes

Pancreatic islet cells regulate glucose homeostasis through insulin and glucagon secretion; dysfunction of these cells leads to severe diseases like diabetes. Prior single-cell transcriptome studies have shown heterogeneous gene expression in major islet cell-types; however it remains challenging to reconcile this transcriptomic heterogeneity with observed islet cell functional variation. Here we achieved electrophysiological profiling and single-cell RNA sequencing in the same islet cell (pancreas patch-seq) thereby linking transcriptomic phenotypes to physiologic properties. We collected 1,369 cells from the pancreas of donors with or without diabetes and assessed function-gene expression networks. We identified a set of genes and pathways that drive functional heterogeneity in {beta}-cells and used these to predict {beta}-cell electrophysiology. We also report specific transcriptional programs that correlate with dysfunction in type 2 diabetes (T2D) and extend this approach to cryopreserved cells from donors with type 1 diabetes (T1D), generating a valuable resource for understanding islet cell heterogeneity in health and disease. Key findingsO_LIPancreas patch-seq provides a single-cell survey of function-transcriptome pairing in 1,369 islet cells from donors with and without diabetes C_LIO_LIExpression of a specific subset of genes predicts {beta}-cell electrophysiology in transcriptome-function networks. C_LIO_LICompromised {beta}-cell function in T2D correlates with altered ETV1 expression and inflammatory pathways C_LIO_LIFunctional heterogeneity in -cells maps to ER stress and islet lineage markers C_LIO_LIApplication of patch-seq to cells from rare cryopreserved islets from donors with T1D C_LI

genomics↗

bioRxiv2019

Analysis of genetically driven alternative splicing identifies FBXO38 as a novel COPD susceptibility gene

While many disease-associated single nucleotide polymorphisms (SNPs) are associated with gene expression (expression quantitative trait loci, eQTLs), a large proportion of complex disease genome-wide association study (GWAS) variants are of unknown function. Some of these SNPs may contribute to disease by regulating gene splicing. Here, we investigate whether SNPs that are associated with alternative splicing (splice QTL or sQTL) can identify novel functions for existing GWAS variants or suggest new associated variants in chronic obstructive pulmonary disease (COPD). RNA sequencing was performed on whole blood from 376 subjects from the COPDGene Study. Using linear models, we identified 561,060 unique sQTL SNPs associated with 30,333 splice sites corresponding to 6,419 unique genes. Similarly, 708,928 unique eQTL SNPs involving 15,913 genes were detected at 10% FDR. While there is overlap between sQTLs and eQTLs, 60% of sQTLs are not eQTLs. Co-localization analysis revealed that 7 out of 21 loci associated with COPD (p<1x10-6) in a published GWAS have at least one shared causal variant between the GWAS and sQTL studies. Among the genes identified to have splice sites associated with top GWAS SNPs was FBXO38, in which a novel exon was discovered to be protective against COPD. Importantly, the sQTL in this locus was validated by qPCR in both blood and lung tissue, demonstrating that splice variants relevant to lung tissue can be identified in blood. Other identified genes included CDK11A and SULT1A2. Overall, these data indicate that analysis of alternative splicing can provide novel insights into disease mechanisms. In particular, we demonstrated that SNPs in a known COPD GWAS locus on chromosome 5q32 influence alternative splicing in the gene FBXO38. Author SummaryWhile it is known that chronic obstructive pulmonary disease (COPD) is caused in part by genetic factors, few studies have identified specific causative genes. Genetic variants that alter the expression levels of genes have explained part of the genetic component of COPD, however, there are additional genetic variants with unknown function. In some genes the protein coding sequence can be altered by a mechanism known as RNA splicing. We hypothesized that some genetic variants that are associated with risk of COPD contribute to the disease by altering RNA splicing. In this study, we identified genetic variants that are associated both with COPD risk and RNA splicing. In particular, we found that a COPD associated variant of previously unknown function may contribute to the inclusion of a new exon in the FBXO38 gene. These finding are significant because they indicate that analysis of RNA splicing can help identify genes that contribute to disease.

genetics↗

bioRxiv2019

A glucose-dependent spatial patterning of exocytosis inhuman β-cells is disrupted in type 2 diabetes

Impaired insulin secretion in type 2 diabetes (T2D) is linked to reduced insulin granule docking, disorganization of the exocytotic site, and an impaired glucose-dependent facilitation of insulin exocytosis. We show in {beta}-cells from 80 human donors that the glucose-dependent amplification of exocytosis is disrupted in T2D. Spatial analyses of granule fusion events, visualized by total internal reflection fluorescence (TIRF) microscopy, demonstrate that these are non-random across the surface of {beta}-cells from donors with no diabetes (ND). The compartmentalization of events occurs within regions defined by concurrent or recent membrane-resident secretory granules. This organization, and the number of membrane-associated granules, is glucose-dependent and notably impaired in T2D {beta}-cells. Mechanistically, multi-channel Kv2.1 clusters contribute to maintaining the density of membrane-resident granules and the number of fusion hot spots, while SUMOylation sites at the channel N-(K145) and C-terminus (K470) determine the relative proportion of fusion events occurring within these regions. Thus, a glucose-dependent compartmentalization of fusion, regulated in part by a structural role for Kv2.1, is disrupted in {beta}-cells from donors with type 2 diabetes. HIGHLIGHTSO_LIExocytosis of secretory granules is non-random across the surface of human {beta}-cells, and this organization is disrupted in type 2 diabetes. C_LIO_LIIncreasing glucose facilitates the spatial compartmentalization of fusion, independent of an overall increase in event frequency. C_LIO_LICompartmentalized hot spots occur at sites marked by membrane-associated granules, the density of which is regulated in part by a clustered K+ channel (Kv2.1). C_LIO_LISUMOylation status of the channel controls the proportion of events that occur within these local regions. C_LI

cell biology↗

bioRxiv2019

EK-DRD: a comprehensive database for drug repositioning inspired by experimental knowledge

SummaryDrug repositioning, or the identification of new indications for approved therapeutic drugs, has gained substantial traction with both academics and pharmaceutical companies because it reduces the cost and duration of the drug development pipeline and it reduces the likelihood of unforeseen adverse events. So far, there has not been a systematic effort to identify such opportunities, in part because of the lack of a comprehensive resource for an enormous amount of unsystematic drug repositioning information to support scientists who could benefit from this endeavor. To address this challenge, we developed a new database, Experimental Knowledge-Based Drug Repositioning Database (EK-DRD) by using text and data mining, as well as manual curation. EK-DRD contains experimentally validated drug repositioning annotation for 1861 FDA-approved and 102 withdrawn small molecule drugs. Annotation was done at four levels, using 70,212 target assay records, 3999 cell assay records, 585 organism assay records, and 8910 clinical trial records. Additionally, approximately 1799 repositioning protein or target sequences coupled with 856 related diseases and 1332 pathways are linked to the drug entries. Our web-based software displays a network for integrative relationships between drugs, their repositioning targets, and related diseases. The database is fully searchable and supports extensive text, sequence, chemical structure, and relational query searches.\n\nAvailabilityEK-DRD is freely available at http://www.idruglab.com/drd/index.php.\n\nContactlingwang@scut.edu.cn.

bioinformatics↗

bioRxiv2018

Sparse functional data analysis accounts for missing information in single-cell epigenomics

Single-cell epigenome assays produce sparsely sampled data, leading to coverage pooling across cells to increase resolution. Imputation of missing data using deep learning is available but requires intensive computation, and it has been applied only to DNA methylation obtained by single cell bisulfite sequencing. Here, sparsity in chromatin accessibility obtained by scNMT-seq is addressed using functional data analysis to fit sparsely sampled GpC coverage profiles of individual cells taking into account all the cells of the same cell-type or condition. For that, sparse functional principal component analysis (S-FPCA) is applied, and the principal components are used to estimate chromatin accessibility coverage in individual cells. This methodology can potentially be used with other single-cell assays with missing data such as scBS-seq, scNOME-seq, or scATAC-seq. The R package fdapace is available in CRAN, and R code used in this manuscript can be found at: http://github.com/pmb59/sparseSingleCell.

bioinformatics↗

bioRxiv2018

Nanoporous Boron Nitride for High Efficient Water Desalination

Membrane filtration processes for water desalination have been greatly improved thanks to rapid development of nanoporous 2-dimentional (2D) materials. Nanoporous graphene and molybdenum disulfide have proved to show promising properties for desalination. In this study, we detailly investigated the desalination performance of a different nanoporous 2D material, nanoporous boron nitride (BN), by Molecular Dynamics simulation. Our calculations demonstrated that nanoporous BN allows for rapid water permeability with effective salt rejection. The permeability is not only two orders of magnitude higher than existing commercial techniques but also much higher than nanoporous graphene and molybdenum disulfide membranes. We further showed that the pores with B-h edges or with N-h edges present different desalination efficiency. Compared to N-h pores, B-h pores have better desalination performance in term of higher water flux. To the best of our knowledge, nanoporous BN is the 2D material having the highest water permeability thus far while maintaining high salt rejection. Overall, our results shed light on the potential

biophysics↗

bioRxiv2018

Different capsid-binding patterns of the β-herpesvirus-specific tegument protein pp150 (pM32/pUL32) in murine and human cytomegaloviruses

The phosphoprotein pp150 is a structurally, immunogenically, and regulatorily important capsid-associated tegument protein abundant in {beta}-herpesviruses including cytomegaloviruses (CMV), but absent in -herpesviruses and {Gamma}-herpesviruses. In human CMV (HCMV), bridging across each triplex and three adjacent major capsid proteins (MCPs) is a group of three pp150 subunits in a \"{bigtriangleup}\"-shaped fortifying configuration, 320 of which encase and stabilize the genome-containing capsid. Because murine CMV (MCMV) has been used as a model for HCMV pathogenesis and therapeutic studies, one might expect that pp150 and the capsid in MCMV and HCMV have similar structures. Here, by cryoEM and sub-particle reconstructions, we have obtained structures of MCMV capsid and pp150 at near atomic resolutions and built their atomic models. Surprisingly, the capsid-binding patterns of pp150 differ between HCMV and MCMV despite their highly similar capsid structures. In MCMV, pp150 is absent on triplex Tc and exists as a \"{Lambda}\"-shaped dimer on other triplexes, leading to only 260 groups of two pp150 subunits per capsid in contrast to 320 groups of three pp150 subunits encasing each HCMV capsid. Many more amino acids contribute to pp150-pp150 interactions in MCMV than in HCMV, making MCMV pp150 dimer inflexible thus incompatible to instigate triplex Tc-binding as observed in HCMV. While pp150 is essential in HCMV, pp150-deleted MCMV mutants remained viable though with attenuated infectivity and exhibiting defects in retaining viral genome. These results support targeting capsid proteins, but invalidate targeting pp150, when using MCMV as a model for HCMV pathogenesis and therapeutic studies.\n\nImportanceCMV infection is a leading viral cause of congenital birth defects and often responsible for life-threating complications in immunocompromised individuals like AIDS and post-organ transplantation patients. Absence of effective vaccines and potent drugs against CMV infections has motivated animal-based studies, mostly based on the mouse model with MCMV, both for understanding pathogenesis of CMV infections and for developing therapeutic strategies. Here, we present the first atomic structures of MCMV and show that the organization patterns of capsid-associated tegument protein pp150 between human and mouse CMV are different despite their highly similar capsid structures. Our functional studies demonstrate that deleting pp150 does not eliminate MCMV infection in contrast to pp150s essential role in HCMV infections. These results thus establish the validity to target capsid proteins, but raise concerns to target pp150, when using MCMV as HCMV model for pathogenesis and therapeutic studies.

microbiology↗

bioRxiv2018

Strategies to improve photosynthetic nitrogen-use efficiency with no yield penalty: lessons from late-sown winter wheat

HighlightOptimal N allocation at several integration levels accounts for improved canopy PNUE while maintaining high grain yield in winter wheat\n\nAbstractImproving canopy photosynthetic nitrogen-use efficiency (PNUE) may maintain or even increase yield with reduced N input. In this study, later-sown winter wheat was studied to reveal the mechanism underlying improved canopy PNUE while maintaining high yield. N allocation at several levels was optimised in late-sown wheat plants. N content per plant increased. Increased N was allocated to the flag leaf and second leaf, and to ribulose-1, 5-bisphosphate carboxylase/oxygenase (Rubisco) in upper leaves. Constant or reduced N was allocated to leaf 3, leaf 4, and Rubisco in lower leaves. The specific green leaf area nitrogen (SLN) of upper leaves increased, while that of lower leaves remained unchanged or decreased. N allocation to the cell wall decreased in all leaves. As a result, the maximum carboxylation rate of upper leaves increased, and that of lower leaves remained constant or decreased. CO2 diffusion capacity was enhanced in all leaves. Outperformance by light-saturated net photosynthetic rate (Pmax) over SLN led to improved PNUE in upper leaves. Enhanced Pmax coupled with unchanged or decreased SLN resulted in improved PNUE in lower leaves. High yield was maintained because enhanced photosynthetic capacity at the leaf and whole plant levels compensated for reduced canopy leaf area.

cell biology↗

bioRxiv2017

Boosting Gene Expression Clustering with System-Wide Biological Information: A Robust Autoencoder Approach

Gene expression analysis provides genome-wide insights into the transcriptional activity of a cell. One of the first computational steps in exploration and analysis of the gene expression data is clustering. With a number of standard clustering methods routinely used, most of the methods do not take prior biological information into account. In this paper, we propose a new approach for gene expression clustering analysis. The approach benefits from a new deep learning architecture, Robust Autoencoder, which provides a more accurate high-level representation of the feature sets, and from incorporating prior biological information into the clustering process. We tested our approach on two distinct gene expression datasets and compared the performance with two widely used clustering methods, hierarchical clustering and k-means, as well as with a recent deep learning clustering approach. As a result, our approach outperformed all other clustering methods on the labeled yeast gene expression dataset. Furthermore we showed that it is better in identifying the functionally common clusters than k-means on the unlabeled human gene expression dataset. The results demonstrate that our new deep learning architecture could generalize well the specific properties of gene expression profiles. Furthermore, the results confirm our hypothesis that the prior biological network knowledge could be helpful in the gene expression clustering task.

bioinformatics↗

bioRxiv2017

Pooled AAV-CRISPR Screen with Targeted Amplicon Sequencing

High-resolution, high-throughput direct in vivo screening of functional genetic factors in native tissues has long been challenging. Adeno-associated viruses (AAV) are powerful carriers of transgenes and have been shown to mediate efficient genome editing in various organs in mice. Here, we developed a new technological approach, Pooled AAV-CRISPR Screen with Targeted Amplicon Sequencing (PASTAS), and demonstrated its application for directly mapping functional cancer driver variants in the mouse liver in an autochthonous manner. Intravenous delivery of an AAV-CRISPR library targeting a set of the most frequently mutated tumor suppressor genes into fully immunocompetent conditional Cas9 knock-in mice consistently generated highly complex autochthonous liver tumors. The molecular landscapes of these genetically diverse tumors were mapped out by deep direct readout of Cas9-generated variants at predicted sgRNA cut sites using molecular inversion probe sequencing. Co-occurrence and correlation analyses as well as validation with lower complexity minipools further confirmed the potency of various co-mutated drivers. The PASTAS method can be applied to virtually any gene sets, any cancer types, or any type of in vivo genetic studies other than cancer.

systems biology↗

bioRxiv2017

Isolation And Characterization Of Key Genes That Promote Flavonoid Accumulation In Purple-Leaf Tea (Camellia sinensis L.)

There were several high concentrations of flavonoid components in tea leaves that present health benefits. A novel purple-leaf tea variety, Mooma1, was obtained from the natural hybrid population of Longjing 43 variety. The buds and young leaves of Mooma1 were displayed in bright red. HPLC and LC-MS analysis showed that anthocyanins and O-Glycosylated flavonols were remarkably accumulated in the leaves of Mooma1, while the total amount of catechins in purple-leaf leaves was slightly decreased compared with the control. A R2R3-MYB transcription factor (CsMYB6A) and a novel UGT gene (CsUGT72AM1), that were highly expressed in purple leaf were isolated and identified by transcriptome sequencing. The over-expression of transgenic tobacco confirmed that CsMYB6A can activate the expression of flavonoid-related structural genes, especially CHS and 3GT, controlling the accumulation of anthocyanins in the leaf of transgenic tobacco. Enzymatic assays in vitro confirmed that CsUGT72AM1 has catalytic activity as a flavonol 3-O-glucosyltransferase, and displayed broad substrate specificity. The results were useful for further elucidating the molecular mechanisms of the flavonoid metabolic fluxes in the tea plant.

plant biology↗