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Wu, Z.

Publications and source records attributed to Wu, Z..

31 records · Page 2Linked to original sources

NormExpression: an R package to normalize gene expression data using evaluated methods

Data normalization is a crucial step in the gene expression analysis as it ensures the validity of its downstream analyses. Although many metrics have been designed to evaluate the current normalization methods, the different metrics yield inconsistent results. In this study, we designed a new metric named Area Under normalized CV threshold Curve (AUCVC) and applied it with another metric mSCC to evaluate 14 commonly used normalization methods, achieving consistency in our evaluation results using both bulk RNA-seq and scRNA-seq data from the same library construction protocol. This consistency has validated the underlying theory that a sucessiful normalization method simultaneously maximizes the number of uniform genes and minimizes the correlation between the expression profiles of gene pairs. This consistency can also be used to analyze the quality of gene expression data. The gene expression data, normalization methods and evaluation metrics used in this study have been included in an R package named NormExpression. NormExpression provides a framework and a fast and simple way for researchers to evaluate methods (particularly some data-driven methods or their own methods) and then select a best one for data normalization in the gene expression analysis.

bioinformatics

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

An improved mitochondrial reference genome for Arabidopsis thaliana Col-0

Arabidopsis thaliana remains the foremost model system for plant genetics and genomics, and researchers rely on the accuracy of its genomic resources. The first completely sequenced angiosperm mitochondrial genome was obtained from A. thaliana C24 (Unseld et al., 1997), and more recent efforts have produced additional A. thaliana reference genomes, including one for Col-0, the most widely used ecotype (Davila et al., 2011). These studies were based on older DNA sequencing methods, making them subject to errors associated with lower levels of sequencing coverage or the extremely short read lengths produced by early-generation Illumina technologies. Indeed, although the more recently published A. thaliana mitochondrial reference genome sequences made substantial progress in improving upon earlier versions, they still have high error rates. By comparing publicly available Illumina sequence data to the A. thaliana Col-0 reference genome, we found that it contains a sequence error every 2.4 kb on average, including 57 SNPs, 96 indels (up to 901 bp in size), and a large repeat-mediated rearrangement. Most of these errors appear to have been carried over from the original A. thaliana mitochondrial genome sequence by reference-based assembly approaches, which has misled subsequent studies of plant mitochondrial mutation and molecular evolution by giving the false impression that the errors are naturally occurring variants present in multiple ecotypes. Building on the progress made by previous researchers, we provide a corrected reference sequence that we hope will serve as a useful community resource for future investigations in the field of plant mitochondrial genetics.

genomics

Differentiation of primate primordial germ cell-like cells following transplantation into the adult gonadal niche

A major challenge in stem cell differentiation validation is the availability of bioassays to prove cell types generated in vitro are equivalent to cells in vivo. In the mouse model, differentiation of primordial germ cell-like cells (PGCLCs) from pluripotent cells was validated by transplantation, leading to the generation of spermatogenesis and to the birth of offspring. Here we report the use of xenotransplantation (monkey to mouse) and homologous transplantation (monkey to monkey) to validate our in vitro protocol for differentiating male rhesus macaque PGCLCs (rPGCLCs) from rhesus macaque induced pluripotent stem cells (riPSCs). Specifically, transplantation of aggregates containing rPGCLCs into mouse and nonhuman primate testicles overcomes a major bottleneck in rPGCLC differentiation with the expression of VASA and MAGEA4, but not ENO2. These findings suggest that immature rPGCLCs once transplanted into an adult gonadal niche commit to differentiate towards late PGCs and spermatogonia-like cells but do not complete the conversion into ENO2-positive spermatogonia.

developmental biology

GABAergic deficits and schizophrenia-like behaviors in a mouse model carrying patient-derived neuroligin-2 R215H mutation

Schizophrenia (SCZ) is a severe mental disorder characterized by delusion, hallucination, and cognitive deficits. We have previously identified from schizophrenia patients a loss-of-function mutation Arg215 [->] His215 (R215H) of neuroligin 2 (NLGN2) gene, which encodes a cell adhesion molecule critical for GABAergic synapse formation and function. Here, we generated a novel transgenic mouse line with neuroligin-2 (NL2) R215H mutation, which showed a significant loss of NL2 protein, reduced GABAergic transmission, and impaired hippocampal activation. Importantly, R215H KI mice displayed anxiety-like behaviors, impaired pre-pulse inhibition (PPI), cognition deficits and abnormal stress responses, recapitulating several key aspects of schizophrenia-like behavior. Our results demonstrate a significant impact of a single point mutation NL2 R215H on brain functions, providing a novel animal model for the study of schizophrenia and neuropsychiatric disorders.

neuroscience

Association of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study: Results from The Michigan Genomics Initiative

Health systems are stewards of patient electronic health record (EHR) data with extraordinarily rich depth and breadth, reflecting thousands of diagnoses and exposures. Measures of genomic variation integrated with EHRs offer a potential strategy to accurately stratify patients for risk profiling and discover new relationships between diagnoses and genomes. The objective of this study was to evaluate whether Polygenic Risk Scores (PRS) for common cancers are associated with multiple phenotypes in a Phenome-wide Association Study (PheWAS) conducted in 28,260 unrelated, genotyped patients of recent European ancestry who consented to participate in the Michigan Genomics Initiative, a longitudinal biorepository effort within Michigan Medicine. PRS for 12 cancer traits were calculated using summary statistics from the NHGRI-EBI catalog. A total of 1,711 synthetic case-control studies was used for PheWAS analyses. There were 13,490 (47.7%) patients with at least one cancer diagnosis in this study sample. PRSs exhibited strong association for several cancer traits they were designed for including female breast cancer, prostate cancer, melanoma, basal cell carcinoma, squamous cell carcinoma and thyroid cancer. Phenome-wide significant associations were observed between PRS and many non-cancer diagnoses. To differentiate PRS associations driven by the primary trait from associations arising through shared genetic risk profiles, the idea of \"exclusion PRS PheWAS\" was introduced. This approach led to phenome-wide significant associations between a lower risk for hypothyroidism in patients with high thyroid cancer PRS and a higher risk for actinic keratosis in patients with high squamous cell carcinoma PRS after removing all cases of the primary cancer trait. Further analysis of temporal order of the diagnoses improved our understanding of these secondary associations. This is the first comprehensive PheWAS study using PRS instead of a single variant.

genetics

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

Complemented palindrome small RNAs first discovered from SARS coronavirus

In this study, we reported for the first time the existence of complemented palindrome small RNAs (cpsRNAs) and proposed cpsRNAs and palindrome small RNAs (psRNAs) as a novel class of small RNAs. The first discovered cpsRNA UCUUUAACAAGCUUGUUAAAGA from SARS coronavirus named SARS-CoV-cpsR-22 contained 22 nucleotides perfectly matching its reverse complementary sequence. Further sequence analysis supported that SARS-CoV-cpsR-22 originated from bat betacoronavirus. The results of RNAi experiments showed that one 19-nt segment of SARS-CoV-cpsR-22 significantly induced cell apoptosis. These results suggested that SARS-CoV-cpsR-22 could play a role in SARS-CoV infection or pathogenicity. The discovery of psRNAs and cpsRNAs paved the way to find new markers for pathogen detection and reveal the mechanisms in the infection or pathogenicity from a different point of view. The discovery of psRNAs and cpsRNAs also broaden the understanding of palindrome motifs in animal of plant genomes.

genomics

Imaging specific cellular glycan structures using glycosyltransferases via click chemistry

Heparan sulfate (HS) is a polysaccharide fundamentally important for biologically activities. T/Tn antigens are universal carbohydrate cancer markers. Here, we report the specific imaging of these carbohydrates using a mesenchymal stem cell line and human umbilical vein endothelial cells (HUVEC). The staining specificities were demonstrated by comparing imaging of different glycans and validated by either removal of target glycans, which results in loss of signal, or installation of target glycans, which results in gain of signal. As controls, representative key glycans including O-GlcNAc, lactosaminyl glycans and hyaluronan were also imaged. HS staining revealed novel architectural features of the extracellular matrix (ECM) of HUVEC cells. Results from T/Tn antigen staining suggest that O-GalNAcylation is a rate-limiting step for O-glycan synthesis. Overall, these highly specific approaches for HS and T/Tn antigen imaging should greatly facilitate the detection and functional characterization of these biologically important glycans.

molecular biology

Single-molecule force spectroscopy of protein-membrane interactions

Many biological processes rely on protein-membrane interactions in the presence of mechanical forces, yet high resolution methods to quantify such interactions are lacking. Here, we describe a single-molecule force spectroscopy approach to quantify membrane binding of C2 domains in Synaptotagmin-1 (Syt1) and Extended Synaptotagmin-2 (E-Syt2). Syts and E-Syts bind the plasma membrane via multiple C2 domains, bridging the plasma membrane with synaptic vesicles or endoplasmic reticulum to regulate membrane fusion or lipid exchange, respectively. In our approach single proteins attached to membranes supported on silica beads are pulled by optical tweezers, allowing membrane binding and unbinding transitions to be measured with unprecedented spatiotemporal resolution. C2 domains from either protein resisted unbinding forces of 2-7 pN and had binding energies of 4-14 kBT per C2 domain. Regulation by bilayer composition or Ca2+ recapitulated known properties of both proteins. The method can be widely applied to study protein-membrane interactions.

biophysics

Collective membrane dynamics emerging from curvature-dependent spatial coupling

Membrane curvature has been recognized as an active participant of fundamental biological processes including vesicular transport and organelle biogenesis, but its effects on membrane remodeling are typically local. Here we show membrane curvature plays a critical role in propagating cortical waves and modulating mesoscale dynamics in living cells. We employ a membrane shape-dependent mechanochemical feedback model to account for the observed oscillatory travelling waves of Cdc42, F-BAR proteins and actin. We demonstrate that oscillatory membrane shape changes accompany and are required for such spatiotemporal patterns. In addition, modulating the curvature preference of the F-BAR proteins or membrane tension perturbs wave propagation. Our findings identify a distinct role of membrane curvature in mediating collective dynamics of cortical proteins and provide a molecular framework for integrating membrane mechanics and biochemical signaling in the context of subcellular pattern formation.

biophysics

Estimating Autoantibody Signatures To Detect Autoimmune Disease Patient Subsets

Autoimmune diseases are characterized by highly specific immune responses against molecules in self-tissues. Different autoimmune diseases are characterized by distinct immune responses, making autoantibodies useful for diagnosis and prediction. In many diseases, the targets of autoantibodies are incompletely defined. Although the technologies for autoantibody discovery have advanced dramatically over the past decade, each of these techniques generates hundreds of possibilities, which are onerous and expensive to validate. We set out to establish a method to greatly simplify autoantibody discovery, using a pre-filtering step to define subgroups with similar specificities based on migration of radiolabeled, immunoprecipitated proteins on sodium dodecyl sulfate (SDS) gels and autoradiography [Gel Electrophoresis and band detection on Autoradiograms (GEA)]. Human recognition of patterns is not optimal when the patterns are complex or scattered across many samples. Multiple sources of errors - including irrelevant intensity differences and warping of gels - have challenged automation of pattern discovery from autoradiograms.\n\nIn this paper, we address these limitations using a Bayesian hierarchical model with shrinkage priors for pattern alignment and spatial dewarping. The Bayesian model combines information from multiple gel sets and corrects spatial warping for coherent estimation of autoantibody signatures defined by presence or absence of a grid of landmark proteins. We show the pre-processing creates more clearly separated clusters and improves the accuracy of autoantibody subset detection via hierarchical clustering. Finally, we demonstrate the utility of the proposed methods with GEA data from scleroderma patients.

cancer biology

Gene expression profiling reveals U1 snRNA regulates cancer gene expression

U1 small nuclear RNA (U1 snRNA), as one of the most abundant noncoding RNA in eukaryotic cells plays an important role in splicing of pre-mRNAs. Compared to other studies which have focused on the primary function of U1 snRNA and the neurodegenerative diseases caused by the abnormalities of U1 snRNA, this study is to investigate how the U1 snRNA over-expression affects the expression of genes on a genome-wide scale. In this study, we built a model of U1 snRNA over-expression in a rat cell line. By comparing the gene expression profiles of U1 snRNA over-expressed cells with those of their controls using the microarray experiments, 916 genes or loci were identified significantly differentially expressed. These 595 up-regulated genes and 321 down-regulated genes were further analyzed using the annotations from the GO terms and the KEGG database. As a result, three of 12 enriched pathways are well-known cancer pathways, while nine of them were associated to cancers in previous studies. The further analysis of 73 genes involved in 12 pathways suggests that U1 snRNA regulates cancer gene expression. The microarray data with ID GSE84304 is available in the NCBI GEO database.

cancer biology