Biology subjects

Yang, J.

Publications and source records attributed to Yang, J..

At least 55 records · Page 3Linked to original sources

bioRxiv2018

Mycobacterium tuberculosis-specific CD4+ and CD8+ T cells differ in their capacity to recognize infected macrophages

Containment of Mycobacterium tuberculosis (Mtb) infection requires T cell recognition of infected macrophages. Mtb has evolved to tolerate, evade, and subvert host immunity. Despite a vigorous and sustained CD8+ T cell response during Mtb infection, CD8+ T cells make limited contribution to protection. Here, we ask whether the ability of Mtb-specific T cells to restrict Mtb growth is related to their capacity to recognize Mtb-infected macrophages.\n\nWe derived CD8+ T cell lines that recognized the Mtb immunodominant epitope TB10.44-11 and compared them to CD4+ T cell lines that recognized Ag85b240-254 or ESAT63-17. While the CD4+ T cells recognized Mtb-infected macrophages and inhibited Mtb growth in vitro, the TB10.4-specific CD8+ T cells neither recognized Mtb-infected macrophages nor restricted Mtb growth. TB10.4-specific CD8+ T cells recognized macrophages infected with Listeria monocytogenes expressing TB10.4. However, over-expression of TB10.4 in Mtb did not confer recognition by TB10.4-specific CD8+ T cells. Importantly, CD8+ T cells recognized macrophages pulsed with irradiated Mtb, indicating that macrophages can efficiently cross-present the TB10.4 protein and raising the possibility that viable bacilli might suppress cross-presentation. Importantly, polyclonal CD8+ T cells specific for Mtb antigens other than TB10.4 recognized Mtb-infected macrophages in a MHC-restricted manner.\n\nAs TB10.4 elicits a dominant CD8+ T cell response that poorly recognizes Mtb-infected macrophages, we propose that TB10.4 acts as a decoy antigen. Moreover, it appears that this response overshadows subdominant CD8+ T cell response that can recognize Mtb-infected macrophages. The ability of Mtb to subvert the CD8+ T cell response may explain why CD8+ T cells make a disproportionately small contribution to host defense compared to CD4+ T cells. The selection of Mtb antigens for vaccines has focused on antigens that generate immunodominant responses. We propose that establishing whether vaccine-elicited, Mtb-specific T cells recognize Mtb-infected macrophages could be a useful criterion for preclinical vaccine development.

immunology↗

bioRxiv2018

Xist Intron 1 Repression by TALE Transcriptional Factor Improves Somatic Cell Reprogamming in Mice

Xist is the master regulator of X chromosome inactivation (XCI). In order to further understand the Xist locus in reprogramming of somatic cells to induced pluripotent stem cells (iPSCs) and in somatic cell nuclear transfer (SCNT), we tested transcription-factor-like effectors (TALE)-based designer transcriptional factors (dTFs), which were specific to numerous regions at the Xist locus. We report that the selected dTF repressor 6 (R6) binding the intron 1 of Xist, which did not affect Xist expression in mouse embryonic fibroblasts (MEFs), substantially improved the iPSC generation and the SCNT preimplantation embryo development. Conversely, the dTF activator targeting the same genomic region of R6 decreased iPSC formation, and blocked SCNT-embryo development. These results thus uncover the critical requirement for the Xist locus in epigenetic resetting, which is not directly related to Xist transcription. This may provide a unique route to improving the reprogramming.

developmental biology↗

bioRxiv2018

Exploring morphological motifs for a single neuron based on multiple 3D reconstructions

The morphology of individual neurons is useful to study structures and functions of nervous system. Researchers have invented many semi or fully automatic tracing methods to efficiently generate a reconstruction from a single neuron. Different tracing methods have different design principles, and could produce different reconstructions. However, the \"common substructures\" of various reconstructions, called morphological motifs, should be highly reliable. In this work, we propose a Vaa3D based framework to explore morphological motifs of 3D reconstructions from a single neuron. The framework contains four steps: (1) resampling and sorting each reconstruction according to a standard reconstruction, such as a gold standard reconstruction, consensus reconstruction or a certain reliable reconstruction; (2) applying local alignment algorithm for each pair of the standard reconstruction and a reconstruction, or each pair of two reconstructions; (3) constructing overlaps based on selected points in local alignment pairs; (4) obtaining morphological motifs by post-processing these overlaps. Under the proposed framework, three methods were implemented and tested on a dataset of 73 fruitfly neurons released by the BigNeuron project (http://bigneuron.org), which contains a gold standard reconstruction, a consensus reconstruction and about 40 automatic reconstructions for each neuron. We quantitatively evaluated these three methods to choose reliable morphological motifs.

bioinformatics↗

bioRxiv2018

Generation of a novel growth-enhanced and reduced environmental impact transgenic pig strain

In pig production, insufficient feed digestion causes excessive nutrients such as phosphorus and nitrogen, which are then released to the environment. To address the issue of environmental emissions, we have established transgenic pigs harboring a single-copy quad-cistronic transgene and simultaneously expressing three microbial enzymes, {beta}-glucanase, xylanase, and phytase in the salivary glands. All the transgenic enzymes were successfully expressed, and the digestion of non-starch polysaccharides (NSPs) and phytate in the feedstuff was enhanced. Fecal nitrogen and phosphate outputs were reduced by 23%-46%, and growth rate improved by 23.4% (gilts) and 24.4% (boars) when the pigs were fed on a corn and soybean-based diet and high-NSP diet. The transgenic pigs showed a 11.5%- 14.5% improvement in feed conversion rate compared to the age-matched wild-type littermates. These findings indicate that transgenic pigs are promising resources for improving feed efficiency and reducing nutrient emissions to the environment.

biochemistry↗

bioRxiv2018

Inference of CRISPR Edits from Sanger Trace Data

Efficient precision genome editing requires a quick, quantitative, and inexpensive assay of editing outcomes. Here we present ICE (Inference of CRISPR Edits), which enables robust analysis of CRISPR edits using Sanger data. ICE proposes potential outcomes for editing with guide RNAs (gRNAs) and then determines which are supported by the data via regression. Additionally, we develop a score called ICE-D (Discordance) that can provide information on large or unexpected edits. We empirically confirm through over 1,800 edits that the ICE algorithm is robust, reproducible, and can analyze CRISPR experiments within days after transfection. We also confirm that ICE strongly correlates with next-generation sequencing of amplicons (Amp-Seq). The ICE tool is free to use and offers several improvements over current analysis tools. For instance, ICE can analyze individual experiments as well as multiple experiments simultaneously (batch analysis). ICE can also detect a wider variety of outcomes, including multi-guide edits (multiple gRNAs per target) and edits resulting from homology-directed repair (HDR), such as knock-ins and base edits. ICE is a reliable analysis tool that can significantly expedite CRISPR editing workflows. It is available online at ice.synthego.com, and the source code is at github.com/synthego-open/ice

bioinformatics↗

bioRxiv2018

GWAS on family history of Alzheimer’s disease

Alzheimers disease (AD) is a public health priority for the 21st century. Risk reduction currently revolves around lifestyle changes with much research trying to elucidate the biological underpinnings. Using self-report of parental history of Alzheimers dementia for case ascertainment in a genome-wide association study of over 300,000 participants from UK Biobank (32,222 maternal cases, 16,613 paternal cases) and meta-analysing with published consortium data (n=74,046 with 25,580 cases across the discovery and replication analyses), six new AD-associated loci (P<5x10-8) are identified. Three contain genes relevant for AD and neurodegeneration: ADAM10, ADAMTS4, and ACE. Suggestive loci include drug targets such as VKORC1 (warfarin dose) and BZRAP1 (benzodiazepine receptor). We report evidence that association of SNPs and AD at the PVR gene is potentially mediated by both gene expression and DNA methylation in the prefrontal cortex. Our discovered loci may help to elucidate the biological mechanisms underlying AD and, given that many are existing drug targets for other diseases and disorders, warrant further exploration for potential precision medicine applications.

genetics↗

bioRxiv2017

bcGST - an interactive bias-correction method to identify over-represented gene-sets in boutique arrays

Motivation: Gene annotation and pathway databases such as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes are important tools in Gene Set Test (GST) that describe gene biological functions and associated pathways. GST aims to establish an association relationship between a gene set of interest and an annotation. Importantly, GST tests for over-representation of genes in an annotation term. One implicit assumption of GST is that the gene expression platform captures the complete or a very large proportion of the genome. However, this assumption is neither satisfied for the increasingly popular boutique array nor the custom designed gene expression profiling platform. Specifically, conventional GST is no longer appropriate due to the gene set selection bias induced during the construction of these platforms.\n\nResults: We propose bcGST, a bias-corrected Gene Set Test by introducing bias correction terms in the contingency table needed for calculating the Fishers Exact Test (FET). The adjustment method works by estimating the proportion of genes captured on the array with respect to the genome in order to assist filtration of annotation terms that would otherwise be falsely included or excluded. We illustrate the practicality of bcGST and its stability through multiple differential gene expression analyses in melanoma and TCGA cancer studies.\n\nAvailability: The bcGST method is made available as a Shiny web application at http://shiny.maths.usyd.edu.au/bcGST/\n\nContact: kevin.wang@sydney.edu.au

bioinformatics↗

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↗

bioRxiv2017

C-type lectin-like receptor 2 (CLEC-2)-dependent DC migration is controlled by tetraspanin CD37

Cell migration is central to evoke a potent immune response. Dendritic cell (DC) migration to lymph nodes is dependent on the interaction of C-type lectin-like receptor 2 (CLEC-2) expressed by DCs, with podoplanin expressed by lymph node stromal cells (LNSCs). However, the underlying molecular mechanisms by which CLEC-2 influences DC migration remain elusive. Here, we show that CLEC-2-dependent DC migration is tightly controlled by tetraspanin CD37, a membrane-organizing protein. Our findings demonstrate a specific molecular interaction between CLEC-2 and CD37. Myeloid cells lacking CD37 (Cd37-/-) expressed less CLEC-2 on their surface compared to wild-type cells, indicating that CD37 is required to stabilize membrane expression of CLEC-2. In addition, CLEC-2-expressing DCs lacking CD37 showed impaired adhesion, migration velocity and displacement on LNSCs. Moreover, Cd37-/- DCs failed to form actin protrusions in a 3D collagen matrix upon podoplanin-induced CLEC-2 stimulation, phenocopying CLEC-2-deficient DCs (CD11c{Delta}CLEC-2). Microcontact printing experiments revealed that CD37 is required for CLEC-2 recruitment in the membrane to its ligand podoplanin. This study demonstrates that tetraspanin CD37 controls CLEC-2 membrane organization and provides new molecular insights underlying CLEC-2-dependent DC migration.

cell biology↗

bioRxiv2017

Improving the calling of non-invasive prenatal testing on 13-/18-/21-trisomy by support vector machine discrimination

With the advance of next-generation sequencing technologies, non-invasive prenatal testing (NIPT) has been developed and employed in fetal aneuploidy screening on 13-/18-/21-trisomies through detecting cell-free fetal DNA (cffDNA) in maternal blood. Although Z test is widely used in NIPT nowadays, there is still necessity to improve its accuracy for removing a) false negatives and false positives, and b) the ratio of unclassified data, so as to reduce the potential harm to patients caused by these inaccuracies as well as the induced cost of retests.\n\nEmploying multiple Z tests with machine-learning algorithm could provide a better prediction on NIPT data. Combining the multiple Z values with indexes of clinical signs and quality control, features were collected from the known samples and scaled for model training in support vector machine (SVM) discrimination. The trained model was applied to predict the unknown samples, which showed significant improvement. In 4752 qualified NIPT data, our method reached 100% accuracies on all three chromosomes, including 151 data that were grouped as unclassified by one-Z-value based method. Moreover, four false positives and four false negatives were corrected by using this machine-learning model.\n\nTo our knowledge, this is the first study to employ support vector machine in NIPT data analysis. It is expected to replace the current one-Z-value based NIPT analysis in clinical use.

bioinformatics↗

bioRxiv2017

Targeting stromal remodeling and cancer stem cell plasticity to overcome chemoresistance in triple negative breast cancer

The cellular and molecular basis of stromal cell recruitment, activation and crosstalk in carcinomas is poorly understood, limiting the development of targeted anti-stromal therapies. In mouse models of triple negative breast cancer (TNBC), Hh ligand produced by neoplastic cells reprogrammed cancer-associated fibroblast (CAF) gene expression, driving tumor growth and metastasis. Hh-activated CAFs upregulated expression of FGF5 and production of fibrillar collagen, leading to FGFR and FAK activation in adjacent neoplastic cells, which then acquired a stem-like, drug-resistant phenotype. Treatment with smoothened inhibitors (SMOi) reversed these phenotypes. Stromal treatment of TNBC patient-derived xenograft (PDX) models with SMOi downregulated the expression of cancer stem cell markers and sensitized tumors to docetaxel, leading to markedly improved survival and reduced metastatic burden. In the phase I clinical trial EDALINE, 3 of 12 patients with metastatic TNBC derived clinical benefit from combination therapy with the SMOi Sonidegib and docetaxel chemotherapy, with one patient experiencing a complete response. Markers of pathway activity correlated with response. These studies identify Hh signaling to CAFs as a novel mediator of cancer stem cell plasticity and an exciting new therapeutic target in TNBC.\n\nSIGNIFICANCECompared to other breast cancer subtypes, TNBCs are associated with significantly worse patient outcomes. Standard of care systemic treatment for patients with non-BRCA1/2 positive TNBC is cytotoxic chemotherapy. However, the failure of 70% of treated TNBCs to attain complete pathological response reflects the relative chemoresistance of these tumors. New therapeutic strategies are needed to improve patient survival and quality of life. Here, we provide new insights into the dynamic interactions between heterotypic cells within a tumor. Specifically, we establish the mechanisms by which CAFs define cancer cell phenotype and demonstrate that the bidirectional CAF-cancer cell crosstalk can be successfully targeted in mice and humans using anti-stromal therapy.

cancer biology↗

bioRxiv2017

Forward-reverse mutation cycles between stages of cancer development

Earlier, prominent occurrences of interstitial loss-of-heterozygosities (LOHs) were found in different cancers as a type of single-nucleotide-variations (SNVs), at rates far exceeding those of the commonly investigated gain-of-heterozygosities (GOHs) type of SNVs. Herein, such co-occurrences of LOHs and GOHs were confirmed in 102 cases of four cancer types analyzed with three different next-generation sequencing platforms, comparing non-tumor, paratumor, and tumor tissues with white-blood-cell controls; and in 246 pan-cancer cases of whole-genome tumor-control pairs. Unexpectedly, large numbers of SNVs enriched with CG>TG GOHs and copy-number-variations (CNVs) proximal to these GOHs were detected in the non-tumor tissues, which were extensively reversed in paratumors showing prominent TG>CG LOHs with proximal CNVs, and less so in tumors to form forward-reverse mutation cycles. Lineage effects in the reversions, likely resulting from directional selection, supported a sequential rather than parallel mode of evolution as described in a Stage Specific Populations model of cancer development.

cancer biology↗

bioRxiv2017

SWEET11 and 15 as key players in seed filling in rice

SummaryO_LIDespite the relevance of seed filling mechanisms for crop yield, we still have only a rudimentary understanding of the pathways and transport processes for supplying the caryopsis with sugars. We hypothesized that the recently identified SWEET sucrose transporters may play important roles in nutrient import pathways in the rice caryopsis.\nC_LIO_LIWe used a combination of mRNA quantification, histochemical analyses, translational promoter-reporter fusions and analysis of knock out mutants created by genomic editing to evaluate the contribution of SWEET transporters to seed filling.\nC_LIO_LIIn rice caryopses, SWEET11 and 15 had the highest mRNA levels and proteins localized to four key sites: the nucellus proper at early stages, the nucellar projection close to the dorsal vein, the nucellar epidermis that surrounds the endosperm, and the aleurone. ossweet11;15 double knock-out lines accumulated starch in the pericarp while caryopses did not contain a functional endosperm.\nC_LIO_LIJointly, SWEET11 and 15 show all hallmarks of being responsible for seed filling with sucrose efflux function at the nucellar projection and transfer across the nucellar epidermis/aleurone interface, delineating two major steps for apoplasmic seed filling, observations that are discussed in relation to observations made in rice and barely on the relative prevalence of these two potential import routes.\nC_LI

plant biology↗

bioRxiv2017

Impaired phloem loading in genome-edited triple knock-out mutants of SWEET13 sucrose transporters

Crop yield depends on efficient allocation of sucrose from leaves to seeds. In Arabidopsis, phloem loading is mediated by a combination of SWEET sucrose effluxers and subsequent uptake by SUT1/SUC2 sucrose/H+ symporters. ZmSUT1 is essential for carbon allocation in maize, but the relative contribution to apoplasmic phloem loading and retrieval of sucrose leaking from the translocation path is not known. We therefor tested whether SWEETs are important for phloem loading in maize.\n\nHere we identified three leaf-expressed SWEET sucrose transporters as key components of apoplasmic phloem loading in Zea mays L. Notably, ZmSWEET13 paralogs (a, b, c) are among the highest expressed genes in the leaf vasculature. Genome-edited triple knock-out mutants are severely stunted. Photosynthesis of mutants was impaired and leaves accumulated starch and soluble sugars. RNA-seq revealed profound transcriptional deregulation of genes associated with the photosynthetic apparatus and carbohydrate metabolism. GWAS analyses may indicate that variability in ZmSWEET13s is correlated with agronomical traits, specifically flowering time and leaf angle.\n\nThis work provides support for cooperation of three ZmSWEET13s with ZmSUT1 in phloem loading in Zea mays L. Our study highlights these three ZmSWEET13 sucrose transporters as possible candidates for the engineering of crop yield.\n\nOne Sentence Summary: Three SWEET sucrose transporter paralogs are necessary for phloem loading in maize.

plant biology↗

bioRxiv2017

Short-term stabilities of 21 amino acids in dried blood spots

BACKGROUNDDried blood spots (DBSs) have potential use in remote health applications for individual and population diagnosis, and can enable epidemiological surveillance for known and unknown diseases. The preparation and transportation of DBSs from remote settings often exposes these cards to extreme environmental stress that may impact the quality of the diagnostic data. Given these risks, it is essential to investigate the individual stabilities of biomarkers in DBSs. This paper details the stability of routinely-analyzed amino acids (AAs) on DBSs under environmental conditions that simulate a global health workflow.\n\nMETHODSThe extractions of 21 AAs from three sets of DBSs prepared on cellulose and cotton filter paper were optimized for quantitation by dansylation-UPLC/MRM-MS. The effects of sunlight exposure, temperature, humidity, and storage time were studied.\n\nRESULTSThe AAs were stable in DBSs after 4-hour sunlight exposure, and after storage at -20 and 4 {degrees}C for 30 days. At 25 and 40 {degrees}C, only 7 AAs showed significant concentration decreases over time, while 2 showed concentration increases. The changes were accelerated by high humidity. Histidine was the least stable AA under the conditions tested.\n\nCONCLUSIONSThis study provides quantitative data on the short-term stabilities of 21 AAs in DBSs on cellulose and cotton-based filter paper, under environmental conditions that simulate a global-health workflow. These results highlight the importance of assessing the stability of clinically-relevant biomarkers in DBSs. Based on the measured stabilities, we recommend that higher-temperature and high-humidity storage of DBS samples be avoided for AA analysis in remote health applications.

biochemistry↗

bioRxiv2017

Improved Score Statistics for Meta-analysis in Single-variant and Gene-level Association Studies

Meta-analysis is now an essential tool for genetic association studies, allowing these to combine large studies and greatly accelerating the pace of genetic discovery. Although the standard meta-analysis methods perform equivalently as the more cumbersome joint analysis under ideal settings, they result in substantial power loss under unbalanced settings with various case-control ratios. Here, we investigate why the standard meta-analysis methods lose power under unbalanced settings, and further propose a novel meta-analysis method that performs as efficiently as joint analysis under general settings. Our proposed method can accurately approximate the score statistics obtainable by joint analysis, for both linear and logistic regression models, with and without covariates. In addition, we propose a novel approach to adjust for population stratification by correcting for known population structures through minor allele frequencies (MAFs). In the simulated gene-level association studies under unbalanced settings, our method recovered up to 85% power loss caused by the standard method. We further showed the power gain of our method in gene-level association studies with 26 unbalanced real studies of Age-related Macular Degeneration (AMD). In addition, we took the meta-analysis of three studies of type 2 diabetes (T2D) as an example to discuss the challenges of meta-analyzing multi-ethnic samples. In summary, we propose improved single-variant score statistics in meta-analysis, requiring \"accurate\" population-specific MAFs for multi-ethnic studies. These improved score statistics can be used to construct both single-variant and gene-level association studies, providing a useful framework for ensuring well-powered, convenient, cross-study analyses.

genetics↗

bioRxiv2017

Resolution of Reprogramming Transition States by Single Cell RNA-Sequencing

The Yamanaka factors convert mouse embryonic fibroblasts (MEFs) into induced pluripotent stem cells (iPSCs) through a highly heterogeneous process. Here we profile single cells undergoing an optimized 7-day reprogramming process and show that cells start reprogramming relatively in sync, but diverge into two branches around day 2. The first branch of cells expressing Cd34/Fxyd5/Psca become nonpluripotent. The second one contains cells that are first Oct4+, then Dppa5a+ and pluripotent. We show that IFN-{gamma} blocks this late transition. Our results reveal the heterogeneous nature of somatic cell reprogramming, identify Dppa5a as a marker for pluripotent and innate immunity as a potential barrier for reprogramming.\n\nOne Sentence SummarySingle cell RNA sequencing reveals a continuum of cell fates from somatic to pluripotent and Dppa5a as a marker for chimera-competent iPSCs.

cell biology↗

bioRxiv2017

Genetic Architecture of Subcortical Brain Structures in Over 40,000 Individuals Worldwide

Subcortical brain structures are integral to motion, consciousness, emotions, and learning. We identified common genetic variation related to the volumes of nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen, and thalamus, using genome-wide association analyses in over 40,000 individuals from CHARGE, ENIGMA and the UK-Biobank. We show that variability in subcortical volumes is heritable, and identify 25 significantly associated loci (20 novel). Annotation of these loci utilizing gene expression, methylation, and neuropathological data identified 62 candidate genes implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.

genetics↗