Biology subjects

Yu, G.

Publications and source records attributed to Yu, G..

At least 163 records · Page 9Linked to original sources

bioRxiv2019

Alignment of LC-MS Profiles by Neighbor-wise Compound-specific Graphical Time Warping with Misalignment Detection

MotivationLiquid chromatography - mass spectrometry (LC-MS) is a standard method for proteomics and metabolomics analysis of biological samples. Unfortunately, it suffers from various changes in the retention times (RT) of the same compound in different samples, and these must be subsequently corrected (aligned) during data processing. Classic alignment methods such as in the popular XCMS package often assume a single time-warping function for each sample. Thus, the potentially varying RT drift for compounds with different masses in a sample is neglected in these methods. Moreover, the systematic change in RT drift across run order is often not considered by alignment algorithms. Therefore, these methods cannot completely correct misalignments. For a large-scale experiment involving many samples, the existence of misalignment becomes inevitable and concerning.\n\nResultsHere we describe an integrated reference-free profile alignment method, neighbor-wise compound-specific Graphical Time Warping (ncGTW), that can detect misaligned features and align profiles by leveraging expected RT drift structures and compound-specific warping functions. Specifically, ncGTW uses individualized warping functions for different compounds and assigns constraint edges on warping functions of neighboring samples. Validated with both realistic synthetic data and internal quality control samples, ncGTW applied to two large-scale metabolomics LC-MS datasets identifies many misaligned features and successfully realigns them. These features would otherwise be discarded or uncorrected using existing methods. The ncGTW software tool is developed currently as a plug-in to the XCMS package.\n\nAvailability and ImplementationAn R package of ncGTW is freely available at https://github.com/ChiungTingWu/ncGTW. A detailed users manual and a vignette are provided within the package.\n\nContactyuewang@vt.edu, yug@vt.edu\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2019

MMCA: a Web-based Server for the Microbiome and Metabolome Correlation Analysis

BackgroundIn the last decade, integrative studies of microbiome and metabolome have experienced exponential growth in understanding their impact on human health and diseases. However, analyzing the resulting multi-omics data and their correlations remains a significant challenge in current studies due to the lack of a comprehensive computational tool to facilitate data integration and interpretation. In this study, we have developed a microbiome and metabolome integrative analysis pipeline (M2IA) to meet the urgent needs for tools that effectively integrate microbiome and metabolome data to derive biological insights.\n\nResultsM2IA streamlines the integrative data analysis between metabolome and microbiome, including both univariate analysis and multivariate modeling methods. KEGG-based functional analysis of microbiome and metabolome are provided to explore their biological interactions within specific metabolic pathways. The functionality of M2IA was demonstrated using TwinsUK cohort data with 1116 fecal metabolites and 16s rRNA microbiome from 786 individuals. As a result, we identified two important pathways, i.e., the benzoate degradation and phosphotransferase system, were closely associated with obesity from both metabolome and microbiome.\n\nConclusionsM2IA is a public available web server (http://m2ia.met-bioinformatics.cn) with the capability to investigate the complex interplay between microbiome and metabolome, and help users to develop mechanistic hypothesis for nutritional and personalized therapies of diseases.

bioinformatics↗

bioRxiv2019

Tissue-specific 3 prime end-adenylation of miR-125b mediates cell survival

Next-generation sequencing has uncovered microRNAs (miRNAs) that undergo sequence modifications, known as isomiRs. Their physiological significance, however, remains uncertain, partly because they generally comprise a small fraction of total miRNAs. Here we report that more than 60% of miR-125b, one of the most abundant miRNAs in vascular smooth muscle cells (vSMC), exists as an edited isoform containing a non-templated adenosine residue at the 3 prime-end (miR-125b+A). The properties of miR-125b+A, such as stability and subcellular localization, are similar to those of canonical miR-125b, but miR-125b+A more potently inhibits the expression of a subgroup of targets, including the apoptosis effector Caspase-6 (CASP6). In the CASP6 transcript, adenylated miR125b preferentially targets a conserved, atypical site, with an unusual 36 nucleotides loop between seed sequence and 3 prime-end supplementary site. PAP associated domain containing 2 (PAPD2) is responsible for monoadenylation of miR-125b. Downregulation of PAPD2 results in the conversion of miR-125b+A to miR-125b, derepression of CASP6, and sensitization of vSMC to apoptotic stimuli. Thus, atypical site recognition by a tissue-specific isomiR fulfills a pro-survival role.

molecular biology↗

bioRxiv2019

Integrated Identification of Disease Specific Pathways Using Multi-omics data

MotivationIdentification of biological pathways plays a central role in understanding both human health and diseases. Although much work has previously been done to explore the biological pathways by using single omics data, little effort has been reported using multi-omics data integration, mainly due to methodological and technological limitations. Compared to single omics data, multi-omics data will help identifying disease specific functional pathways with both higher sensitivity and specificity, thus gaining more comprehensive insights into the molecular architecture of disease processes.\n\nResultsIn this paper, we propose two computational approaches that integrate multi-omics data and identify disease-specific biological pathways with high sensitivity and specificity. Applying our methods to an experimental multi-omics data dataset on muscular dystrophy subtypes, we identified disease-specific pathways of high biological plausibility. The developed methodology will likely have a broad impact on improving the molecular characterization of many common diseases.\n\nContactyuewang@vt.edu\n\nSupplementary informationSupplementary information attached.

bioinformatics↗

bioRxiv2019

A bacterial effector protein prevents MAPK-mediated phosphorylation of SGT1 to suppress plant immunity

Nucleotide-binding domain and leucine-rich repeat-containing (NLR) proteins function as sensors that perceive pathogen molecules and activate immunity. In plants, the accumulation and activation of NLRs is regulated by SUPPRESSOR OF G2 ALLELE OF skp1 (SGT1). In this work, we found that an effector protein named RipAC, secreted by the plant pathogen Ralstonia solanacearum, associates with SGT1 to suppress NLR-mediated SGT1-dependent immune responses, including those triggered by another R. solanacearum effector, RipE1. RipAC does not affect the accumulation of SGT1 or NLRs, or their interaction. However, RipAC inhibits the interaction between SGT1 and MAP kinases, and the phosphorylation of a MAPK target motif in the C-terminal domain of SGT1. Such phosphorylation is enhanced upon activation of immune signaling, leads to the release of the interaction between SGT1 and NLRs, and contributes to the activation of NLR-mediated responses. Additionally, SGT1 phosphorylation contributes to resistance against R. solanacearum, and this is particularly evident in the absence of RipAC. Our results shed light onto the mechanism of activation of NLR-mediated immunity, and suggest a positive feedback loop between MAPK activation and SGT1-dependent NLR activation.

plant biology↗

bioRxiv2019

3D association of ER, PR and Her2 at protein levels to aid sub-grouping of breast cancer patients in routine clinical practice

Treatments of patients with solid tumors frequently rely on the relative and semi-quantitative assessment of tissue protein biomarkers by immunohistochemistry (IHC). The perspective of transition to absolute and quantitative assessment of tissue biomarkers is hindered by lack of a suitable method, especially for Formalin Fixed Paraffin Embedded (FFPE) tissues. In this study, we explored the feasibility of Quantitative Dot Blot (QDB) method as a universal platform to quantitate tissue biomarkers as absolute and continuous variables in FFPE samples by measuring unprecedentedly the protein levels of Estrogen Receptor (ER), Progesterone Receptor (PR), Her2 and Ki67 simultaneously in 1048 FFPE samples. When using measured Her2, ER and PR levels as coordinates to develop 3D scatterplot, we observed a distinct distribution pattern of the samples with natural segregation of three groups as the likely phenotypical projection of known intrinsic subtypes. Thus, we have achieved a major milestone in this transition by identifying the first practice method for daily clinical practice, and one clinical usage in 3D subtyping of samples for prediction and prognosis. This study may serve as basis for a new field of Quantitative Diagnosis where diagnosis, prognosis and prediction are derived from database analysis of protein biomarkers as absolute and continuous variables.

pathology↗

bioRxiv2019

Developing a routine lab test for absolute quantification of Her2 in Formalin Fixed Paraffin Embedded (FFPE) breast cancer tissues using Quantitative Dot Blot (QDB) method

While the transition from current prevailing method of relative and semi-quantitative assessment of solid tumor biomarkers to their absolute quantitation promises improved objectivity, consistency and accuracy in daily clinical practice, this transition is hindered by lacking of suitable technique, especially for Formalin Fixed Paraffin Embedded (FFPE) tissue samples. In this retrospective study, Quantitative Dot Blot (QDB) method was adopted to measure Her2 levels absolutely and quantitatively at protein level using 2X15 m FFPE breast cancer tissue slices collected sequentially and non-selectively from local hospital. Her2 levels measured from 332 samples using two diagnostic antibodies respectively were strongly correlated (r=0.963, p=0.0000). When the result was evaluated with results from IHC or FISH analysis using Receiving Operating Characteristics (ROC) analysis, we were able to achieve 100% sensitivity (95% CI: 95.6% to 100%) and 99.3% specificity (95% CI: 96.14% to 99.98%) with results from IHC analysis using 0.267 nmole/g as cutoff, and 93.02% sensitivity (95%CI: 80.94% to 98.54%) and 93.68% specificity (95% CI: 86.76% to 97.65%) with results from FISH analysis using 0.261 nmole/g as cutoff. Thus, QDB method is demonstrated to provide objective and consistent assessment of Her2 levels in FFPE samples with comparable results from both IHC and FISH analyses. It is also the first method to achieve absolute quantitation of tissue biomarkers in FFPE samples to meet daily clinical need.

pathology↗

bioRxiv2019

SynQuant: An Automatic Tool to Quantify Synapses from Microscopy Images

MotivationSynapses are essential to neural signal transmission. Therefore, quantification of synapses and related neurites from images is vital to gain insights into the underlying pathways of brain functionality and diseases. Despite the wide availability of synapse imaging data, several issues prevent satisfactory quantification of these structures by current tools. First, the antibodies used for labeling synapses are not perfectly specific to synapses. These antibodies may exist in neurites or other cell compartments. Second, the brightness for different neurites and synapses is heterogeneous due to the variation of antibody concentration and synapse-intrinsic differences. Third, images often have low signal to noise ratio (SNR) due to constraints of experiments and availability of sensitive antibodies. The combination of these issues makes the detection of synapses challenging and necessitates developing a new tool to accurately and reliably quantify synapses. ResultsWe present an automatic probability-principled synapse detection algorithm and integrate it into our synapse quantification tool SynQuant. Derived from the theory of order statistics, our method controls the false discovery rate and improves the power of detecting synapses. Through extensive experiments on both synthetic and real images in the presence of severe antibody diffusion, high heterogeneity, and large noise, our method was demonstrated to outperform peer specialized synapse detection tools as well as generic spot detection methods by a large margin. Finally, we show SynQuant reliably uncovers statistically significant differences between disease and control conditions in a neuron-astrocyte co-culture based model of Down Syndrome. AvailabilityThe Java source code, Fiji plug-in, and test data are available at https://github.com/yu-lab-vt/SynQuant. Contactyug@vt.edu

neuroscience↗

bioRxiv2019

Data-driven robust detection of tissue/cell-specific markers

Tissue or cell subtype-specific and differentially-expressed genes (SDEGs) are defined as being differentially expressed in a particular tissue or cell subtype among multiple subtypes. Detecting SDEGs plays a critical rolse in molecularly characterizing and identifying tissue or cell subtypes, and facilitating supervised deconvolution of complex tissues. Unfortunately, classic differential analysis assumes a convenient null hypothesis and associated test statistic that is subtype-non-specific and thus, resulting in a high false positive rate and/or lower detection power with respect to particular subtypes. Here we introduce One-Versus-Everyone Fold Change (OVE-FC) test for detecting SDEGs. To assess the statistical significance of such test, we also propose the scaled test statistic OVE-sFC together with a mixture null distribution model and a tailored permutation scheme. Validated with realistic synthetic data sets on both type 1 error and detection power, OVE-FC/sFC test applied to two benchmark gene expression data sets detects many known and de novo SDEGs. Subsequent supervised deconvolution results, obtained using the SDEGs detected by OVE-FC/sFC test, showed superior performance in deconvolution accuracy when compared with popular peer methods.

bioinformatics↗

bioRxiv2018

An event-based paradigm for analyzing fluorescent astrocyte activity uncovers novel single-cell and population-level physiology

Recent work examining astrocytic physiology centers on fluorescence imaging approaches, due to development of sensitive fluorescent indicators and observation of spatiotemporally complex calcium and glutamate activity. However, the field remains hindered in fully characterizing these dynamics, both within single cells and at the population-level, because of the insufficiency of current region-of-interest-based approaches to describe activity that is often spatially unfixed, size-varying, and propagative. Here, we present a paradigm-shifting analytical framework that releases astrocyte biologists from ROI-based tools. Astrocyte Quantitative Analysis (AQuA) software enables users to take an event-based approach to accurately capture and quantify the irregular activity observed in astrocyte imaging datasets. We apply AQuA to a range of ex vivo and in vivo imaging data, and uncover previously undescribed physiological phenomena in each. Since AQuA is data-driven and based on machine learning principles, it can be applied across model organisms, fluorescent indicators, experimental modes, and imaging resolutions and speeds, enabling researchers to elucidate fundamental astrocyte physiology.

neuroscience↗

bioRxiv2018

Astroglial dysfunctions drive aberrant synaptogenesis in developing brain with lengthy general anesthesia

Lengthy use of general anesthetics (GAs) causes cognitive deficits in developing brain, which has raised significant clinical concerns such that FDA is warning on the use of GAs in children younger than 3 years. However, the molecular and cellular mechanisms for GAs-induced neurotoxicity remain largely unknown. Here we report that sevoflurane, a commonly used GA in pediatrics, causes compromised astrocyte morphogenesis, spatiotemporally correlated to the synaptic overgrowth with reduced synaptic function in developing cortex in a regional-, exposure-length- and age-specific manner. Sevoflurane disrupts astrocyte Ca2+ homeostasis both acutely and chronically, which leads to the down regulation of Ezrin, an actin-binding membrane protein, which we found is critically involved in astrocyte morphogenesis in vivo. Importantly, in normal developing brain, the genetic intervention of astrocyte morphogenesis is sufficient to produce the aberrant synaptic structure and function virtually identical to the ones induced by lengthy sevoflurane exposure. Our data uncover that astrocytes are unexpectedly central targets for GAs to exert toxic effects, and that astrocyte morphological integrity is crucial for synaptogenesis in the developing brain.

neuroscience↗

bioRxiv2018

Specificity of RNA folding and its association with evolutionarily adaptive mRNA secondary structure

Secondary structure is a fundamental feature for both noncoding and messenger RNA. However, our understandings about the secondary structure of mRNA, especially for the coding regions, remain elusive, likely due to translation and the lack of RNA binding proteins that sustain the consensus structure, such as those bind to noncoding RNA. Indeed, mRNA has recently been found to bear pervasive alternative structures, whose overall evolutionary and functional significance remained untested. We hereby approached this problem by estimating folding specificity, the probability that a fragment of RNA folds back to the same partner once re-folded. We showed that folding specificity for mRNA is lower than noncoding RNA, and displays moderate evolutionary conservation between orthologs and between paralogs. More importantly, we found that specific rather than alternative folding is more likely evolutionarily adaptive, since it is more frequently associated with functionally important genes or sites within a gene. Additional analysis in combination with ribosome density suggests the capability of modulating ribosome movement as one potential functional advantage provided by specific folding. Our findings revealed a novel facet of RNA structome with important functional and evolutionary implications, and points to a potential way of disentangling mRNA secondary structures maintained by natural selection from molecular noise.

evolutionary biology↗

bioRxiv2018

FT/FD-GRF5 repression loop directs growth to increase soybean yield

Major advances in crop yield are eternally needed to cope with population growth. To balance vegetative and reproductive growth plays an important role in agricultural yield. To extend vegetative phase can increase crop yield, however, this strategy risks loss of yield in the field as crops may not mature in time before winter come. Here, we identified a repression feedback loop between GmFTL/GmFDL and GmGRF5-1 (Glycine-max-Flowering-Locus-T/Glycine-max-FDL and Glycine-max-GROWTH-REGULATING-FACTOR5-1), which functions as a pivotal regulator in balancing vegetative and reproductive phases in soybean. GmFTL/GmFDL and GmGRF5-1 directly repress gene expression each other. Additionally, GmGRF5-1 enhances vegetative growth by directly enhancing expression of photosynthesis- and auxin synthesis-related genes. To modulate the loop, such as fine-tuning GmFTL expression to trade-off vegetative and reproductive growth, increases substantially soybean yield in the field. Our findings not only uncover the mechanism balancing vegetative and reproductive growth, but open a new window to improve crop yield.

plant biology↗

bioRxiv2018

Localization of balanced chromosome translocation breakpoints by long-read sequencing on the Oxford Nanopore platform

Structural variants (SVs) in genomes, including translocations, inversions, insertions, deletions and duplications, remain difficult to be detected reliably by traditional genomic technologies. In particular, balanced translocations and inversions cannot be detected by microarrays since they do not alter chromosome copy numbers; they cannot be reliably detected by short-read sequencing either, since many breakpoints are located within repetitive regions of the genome that are unmappable by short reads. However, the detection and the precise localization of breakpoints at the nucleotide level are important to study the genetic causes in patients carrying balanced translocations or inversions. Long-read sequencing techniques, such as the Oxford Nanopore Technology (ONT), may detect these SVs in a more direct, efficient and accurate manner. In this study, we applied whole-genome long-read sequencing on the Oxford Nanopore GridION sequencer to detect the breakpoints from 6 carriers of balanced translocations and one carrier of inversion, where SVs had initially been detected by karyotyping at the chromosome level. The results showed that all the balanced translocations were detected with [~]10X coverage and were consistent with the karyotyping results. PCR and Sanger sequencing confirmed 8 of the 14 breakpoints to single base resolution, yet other breakpoints cannot be refined to single-base due to their localization at highly repetitive regions or pericentromeric regions, or due to the possible presence of local deletions/duplications. Our results indicate that low-coverage whole-genome sequencing is an ideal tool for the precise localization of most translocation breakpoints and may provide haplotype information on the breakpoint-linked SNPs, which may be widely applied in SV detection, therapeutic monitoring, assisted reproduction technology (ART) and preimplantation genetic diagnosis (PGD).

genetics↗

bioRxiv2018

Developmental heterogeneity of microglia and brain myeloid cells revealed by deep single-cell RNA sequencing

Microglia are increasingly recognized for their major contributions during brain development and neurodegenerative disease. It is currently unknown if these functions are carried out by subsets of microglia during different stages of development and adulthood or within specific brain regions. Here, we performed deep single-cell RNA sequencing (scRNA-seq) of microglia and related myeloid cells sorted from various regions of embryonic, postnatal, and adult mouse brains. We found that the majority of adult microglia with homeostatic signatures are remarkably similar in transcriptomes, regardless of brain region. By contrast, postnatal microglia represent a more heterogeneous population. We discovered that postnatal white matter-associated microglia (WAM) are strikingly different from microglia in other regions and express genes enriched in degenerative disease-associated microglia. These postnatal WAM have distinct amoeboid morphology, are metabolically active, and phagocytose newly formed oligodendrocytes. This scRNA-seq atlas will be a valuable resource for dissecting innate immune functions in health and disease.\n\nHighlightsO_LIMyeloid scRNA-seq atlas across brain regions and developmental stages\nC_LIO_LILimited transcriptomic heterogeneity of homeostatic microglia in the adult brain\nC_LIO_LIPhase-specific gene sets of proliferating microglia along cell cycle pseudotime\nC_LIO_LIPhagocytic postnatal white matter-associated microglia sharing DAM gene signatures\nC_LI

neuroscience↗

bioRxiv2018

The wheat Sr22, Sr33, Sr35 and Sr45 genes confer resistance against stem rust in barley

In the last 20 years, stem rust caused by the fungus Puccinia graminis f. sp. tritici (Pgt), has re-emerged as a major threat to wheat and barley cultivation in Africa and Europe. In contrast to wheat with 82 designated stem rust (Sr) resistance genes, barleys genetic variation for stem rust resistance is very narrow with only seven resistance genes genetically identified. Of these, only one locus consisting of two genes is effective against Ug99, a strain of Pgt which emerged in Uganda in 1999 and has since spread to much of East Africa and parts of the Middle East. The objective of this study was to assess the functionality, in barley, of cloned wheat Sr genes effective against Ug99. Sr22, Sr33, Sr35 and Sr45 were transformed into barley cv. Golden Promise using Agrobacterium-mediated transformation. All four genes were found to confer effective stem rust resistance. The barley transgenics remained susceptible to the barley leaf rust pathogen Puccinia hordei, indicating that the resistance conferred by these wheat Sr genes was specific for Pgt. Cloned Sr genes from wheat are therefore a potential source of resistance against wheat stem rust in barley.

plant biology↗

bioRxiv2018

Physical and transcriptional organisation of the bread wheat intracellular immune receptor repertoire

Disease resistance genes encoding intracellular immune receptors of the nucleotide-binding and leucine-rich repeat (NLR) class of proteins detect pathogens by the presence of pathogen effectors. Plant genomes typically contain hundreds of NLR encoding genes. The availability of the hexaploid wheat cultivar Chinese Spring reference genome now allows a detailed study of its NLR complement. However, low NLR expression as well as high intra-family sequence homology hinders their accurate gene annotation. Here we developed NLR-Annotator for in silico NLR identification independent of transcript support. Although developed for wheat, we demonstrate the universal applicability of NLR-Annotator across diverse plant taxa. Applying our tool to wheat and combining it with a transcript-validated subset of genes from the reference gene annotation, we characterized the structure, phylogeny and expression profile of the NLR gene family. We detected 3,400 full-length NLR loci of which 1,540 were confirmed as complete genes. NLRs with integrated domains mostly group in specific sub-clades. Members of another subclade predominantly locate in close physical proximity to NLRs carrying integrated domains suggesting a paired helper-function. Most NLRs (88%) display low basal expression (in the lower 10 percentile of transcripts), which may be tissue-specific and/or induced by biotic stress. As a case study for applying our tool to the positional cloning of resistance genes, we estimated the number of NLR genes within the intervals of mapped rust resistance genes. Our study will support the identification of functional resistance genes in wheat to accelerate the breeding and engineering of disease resistant varieties.

plant biology↗

bioRxiv2018

clusterProfiler: universal enrichment tool for functional and comparative study

I present the open-source software package clusterProfiler (https://github.com/GuangchuangYu/clusterProfiler) for functional enrichment analysis. clusterProfiler provides a universal interface for functional enrichment analysis for internal supported ontologies/pathways as well as annotation data provided by users or obtained from online databases. It enables comparative analysis and offers comprehensive visualization tools for result interpretation.

bioinformatics↗