Biology subjects

Gu, X.

Publications and source records attributed to Gu, X..

10 recordsLinked to original sources

bioRxiv2018

Noninvasive prenatal test of methylmalonic academia cblC type through targeted sequencing of cell-free DNA in maternal plasma

Methylmalonic acidemia (MMA) cblC type is the most frequent inborn error of intracellular cobalamin metabolism which is caused by mutations of MMACHC gene. Non-invasive test of MMA for pregnant women facilitates safe and timely prenatal diagnosis of the disease. In our study, we aimed to design and validate a haplotype-based noninvasive prenatal test (NIPT) method for cblC type of MMA. Targeted capture sequencing using customized hybridization was performed utilizing gDNA (genomic DNA) of trios including parents and an affected proband to determine parental haplotypes associated with the mutant and wild allele. The fetal haplotype was inferred later based on the high depth sequencing data of maternal plasma as well as haplotype linkage analysis. The fetal genotypes deduced by NIPT were further validated by amniocentesis. Haplotype-based NIPT was successfully performed in 21 families. The results of NIPT of 21 families were all consistent with invasive prenatal diagnosis, which was interpreted in a blinded fashion. Three fetuses were identified as compound heterozygosity of MMACHC, 9 fetuses were carriers of MMACHC variant, and 9 fetuses were normal. These results indicated that the haplotype-based NIPT for MMA through small target capture region sequencing is technically accurate and feasible.

genetics↗

bioRxiv2018

Transient Overexpression of VEGF-A in Adipose Tissue Promotes Energy Expenditure via Activation of the Sympathetic Nervous System

Adipose-derived VEGF-A stimulates functional blood vessel formation in obese fat pads which in turn facilitates healthy expansion of the adipose tissue. However, the detailed mechanism(s) governing the process remains largely unknown. Here, we investigated the role of sympathetic nervous system activation in the process. To this end, we induced overexpression of VEGF-A in an adipose-specific doxycycline (Dox)-inducible transgenic mouse model for a short period of time during high fat-diet (HFD) feeding. We found that local overexpression of VEGF-A in adipose tissue stimulated lipolysis and browning rapidly after Dox induction. Immunofluorescent staining against tyrosine hydroxylase (TH) indicated higher levels of sympathetic innervation in adipose tissue of transgenic mice. In response to the increased norepinephrine (NE) level, expression of {beta}3-andrenoceptor was significantly upregulated and the downstream protein kinase A (PKA) pathway was activated, as indicated by the enhanced phosphorylation of the whole PKA substrates, in particular the hormone sensitive lipase (HSL) in adipocytes. As the result, the adipose tissue exhibited increased lipolysis, browning, and energy expenditure. Importantly, all these effects were abolished upon the treatment with {beta}3-adrenoceptor antagonist SR59230A. Collectively, these results demonstrate that transient overexpressed VEGF-A activates sympathetic nervous system which hence promotes lipolysis and browning in adipose tissue.

physiology↗

bioRxiv2018

Using the residual bootstrap to quantify uncertainty in mean apparent propagator MRI

Estimation of noise-induced variability in MAP-MRI is needed to properly characterize the amount of uncertainty in quantities derived from the estimated MAP-MRI coefficients. Bootstrap metrics, such as the standard deviation, provides additional valuable diffusion information in addition to common MAP-MRI parameters, and can be incorporated in MAP-MRI studies to provide more extensive insight. To the best of our knowledge, this is the first paper to study the uncertainty of MAP-MRI derived metrics. The noise variability of quantities of MAP-MRI have been quantified using the residual bootstrap, in which the residuals are resampled using two sampling schemes. The residual bootstrap method can provide empirical distributions for MAP-MRI derived quantities, even when the exact distributions are not easily derived. The residual bootstrap methods are applied to SPARC data and HCP-MGH data, and empirical distributions are obtained for the zero-displacement probabilities. Here, we compare and contrast the residual bootstrap schemes using all shells and within the same shell. We show that residual resampling within each shell generates larger uncertainty than using all shells for the HCP-MGH data. Standard deviation and quartile coefficient maps of the estimated variability are provided.

neuroscience↗

bioRxiv2018

smCounter2: an accurate low-frequency variant caller for targeted sequencing data with unique molecular identifiers

MotivationLow-frequency DNA mutations are often confounded with technical artifacts from sample preparation and sequencing. With unique molecular identifiers (UMIs), most of the sequencing errors can be corrected. However, errors before UMI tagging, such as DNA polymerase errors during end-repair and the first PCR cycle, cannot be corrected with single-strand UMIs and impose fundamental limits to UMI-based variant calling.\n\nResultsWe developed smCounter2, a UMI-based variant caller for targeted sequencing data and an upgrade from the current version of smCounter. Compared to smCounter, smCounter2 features lower detection limit at 0.5%, better overall accuracy (particularly in non-coding regions), a consistent threshold that can be applied to both deep and shallow sequencing runs, and easier use via a Docker image and code for read pre-processing. We benchmarked smCounter2 against several state-of-the-art UMI-based variant calling methods using multiple datasets and demonstrated smCounter2s superior performance in detecting somatic variants. At the core of smCounter2 is a statistical test to determine whether the allele frequency of the putative variant is significantly above the background error rate, which was carefully modeled using an independent dataset. The improved accuracy in non-coding regions was mainly achieved using novel repetitive region filters that were specifically designed for UMI data.\n\nAvailabilityThe entire pipeline is available at https://github.com/qiaseq/qiaseq-dna under MIT license.

bioinformatics↗

bioRxiv2018

A role for phylloquinone biosynthesis in the plasma membrane as revealed in a non-photosynthetic parasitic plant

Phylloquinone is a lipophilic naphthoquinone found predominantly in chloroplasts and best known for its function in photosystem I electron transport and disulfide bridge formation of photosystem II subunits. Phylloquinone has also been detected in plasma membrane preparations of heterotrophic tissues with potential transmembrane redox function, but the molecular basis for this noncanonical pathway is unknown. Here we provide evidence of plasma membrane phylloquinone biosynthesis in a nonphotosynthetic holoparasite Phelipanche aegyptiaca. A nonphotosynthetic and nonplastidial role for phylloquinone is supported by transcription of phylloquinone biosynthetic genes during seed germination and haustorium development, by plasma membrane-localization of alternative terminal enzymes, and by detection of phylloquinone in germinated seeds. Comparative gene network analysis with photosynthetically competent parasites revealed a bias of Phelipanche phylloquinone genes toward coexpression with oxidoreductases involved in plasma membrane electron transport. Genes encoding the plasma membrane phylloquinone pathway are also present in several photoautotrophic taxa of Asterids, suggesting an ancient origin of multifunctionality. Our findings suggest that nonphotosynthetic holoparasites exploit alternative targeting of phylloquinone for transmembrane redox signaling associated with parasitism.

plant biology↗

bioRxiv2017

Value Encoding in the Globus Pallidus: fMRI reveals an interaction effect between reward and dopamine drive

The external part of the globus pallidus (GPe) is a core nucleus of the basal ganglia (BG) whose activity is disrupted under conditions of low dopamine release, as in Parkinsons disease. Current models assume decreased dopamine release in the dorsal striatum results in deactivation of dorsal GPe, which in turn affects motor expression via a regulatory effect on other nuclei of the BG. However, recent studies in healthy and pathological animal models have reported neural dynamics that do not match with this view of the GPe as a relay in the BG circuit. Thus, the computational role of the GPe in the BG is still to be determined. We previously proposed a neural model that revisits the functions of the nuclei of the BG, and this model predicts that GPe encodes values which are amplified under a condition of low striatal dopaminergic drive. To test this prediction, we used an fMRI paradigm involving a within-subject placebo-controlled design, using the dopamine antagonist risperidone, wherein healthy volunteers performed a motor selection and maintenance task under low and high reward conditions. ROI-based fMRI analysis revealed an interaction between reward and dopamine drive manipulations, with increased BOLD activity in GPe in a high compared to low reward condition, and under risperidone compared to placebo. These results confirm the core prediction of our computational model, and provide a new perspective on neural dynamics in the BG and their effects on motor selection and motor disorders.

neuroscience↗

bioRxiv2017

A Multilevel Computational Characterization of Endophenotypes in Addiction

Substance use disorders are characterized by a profound intersubject (phenotypic) variability in the expression of addictive symptomatology and propensity to relapse following treatment. However, laboratory investigations have primarily focused on common neural substrates in addiction, and have not yet been able to identify mechanisms that can account for the multifaceted phenotypic behaviors reported in literature. To investigate this knowledge gap theoretically, here we simulated phenotypic variations in addiction symptomology and responses to putative treatments, using both a neural model based on cortico-striatal circuit dynamics, and an algorithmic model of reinforcement learning. These simulations rely on the widely accepted assumption that both the ventral, model-based, goal-directed system and the dorsal, model-free, habitual system are vulnerable to extra-physiologic dopamine reinforcements triggered by drug consumption. We found that endophenotypic differences in the balance between the two circuit or control systems resulted in an inverted U-shape in optimal choice behavior. Specifically, greater unbalance led to a higher likelihood of developing addiction and more severe drug-taking behaviors. Furthermore, endophenotypes with opposite asymmetrical biases among cortico-striatal circuits expressed similar addiction behaviors, but responded differently to simulated treatments, suggesting personalized treatment development could rely on endophenotypic rather than phenotypic differentiations. We propose our simulated results, confirmed across neural and algorithmic levels of analysis, inform on a fundamental and, to date, neglected quantitative method to characterize clinical heterogeneity in addiction.

neuroscience↗

bioRxiv2017

Endodermal differentiation is reconstructed by coordination of two parallel signaling systems derived from the stele in roots

The plant roots represent the exquisitely controlled cell fate map in which different cell types undergo a complete status transition from stem cell division and initial fate specification, to the terminal differentiation. The endodermis is initially specified in meristem but further differentiates to form Casparian strips (CSs), the apoplastic barrier in the mature zone for the selective transport between stele and outer tissues, and thus is regarded as plant inner skin. In the Arabidopsis thaliana root the transcription factors SHORTROOT (SHR) regulate asymmetric cell division in cortical initials to separate endodermal and cortex cell layer. In this paper, we utilized synthetic approach to examine the reconstruction of fully functional Casparian strips in plant roots. Our results revealed that SHR serves as a master regulator of a hierarchical signaling cascade that, combined with stele-derived small peptides, is sufficient to rebuild the functional CS in non-endodermal cells. This is a demonstration of the deployment of two parallel signaling systems, in which both apoplastic and symplastic communication were employed, for coordinately specifying the endodermal cell fate.

plant biology↗

bioRxiv2017

Sodium valproate rescues expression of TRANK1 in iPSC-derived neural cells that carry a genetic variant associated with serious mental illness

Biological characterization of genetic variants identified in genome-wide association studies (GWAS) remains a substantial challenge. Here we used human induced pluripotent stem cells (hiPSC) and their neural derivatives to characterize common variants on chromosome 3p22 that have been associated by GWAS with major mental illnesses. HiPSC-derived neural progenitor cells carrying the risk allele of the single nucleotide polymorphism (SNP), rs9834970, displayed lower baseline TRANK1 expression that was rescued by chronic treatment with therapeutic dosages of valproic acid (VPA). Although rs9834970 has no known function, we demonstrated that a nearby SNP, rs90832, strongly affects binding by the transcription factor, CTCF, and that the high-affinity allele usually occurs on haplotypes carrying the rs9834970 risk allele. Decreased expression of TRANK1 perturbed expression of many genes involved in neural development and differentiation. These findings have important implications for the pathophysiology of major mental illnesses and the development of novel therapeutics.\n\nHighlightsO_LIhiPSC-derived neural cells carrying a mental illness risk allele showed lower expression of TRANK1\nC_LIO_LIValproic acid rescued TRANK1expression in cells carrying the risk allele\nC_LIO_LIRisk haplotypes usually carry an allele that increased CTCF binding\nC_LIO_LIReduced expression of TRANK1 perturbed genes involved in neural development and differentiation\nC_LI\n\nIn BriefUsing neural derivatives of human induced pluripotent stem cells, Jiang et al. demonstrate that genetic variants associated with mental illness alter transcription factor binding and decrease expression of a nearby gene, an effect which is rescued by valproic acid.

genetics↗

bioRxiv2017

Addiction in a Bounded Rational Model: Role of Environment and its Exploration

Several decision-making vulnerabilities have been identified as underlying causes for addictive behaviours, or the repeated execution of stereotyped actions despite their adverse consequences. These vulnerabilities are mostly associated with brain alterations caused by the consumption of substances of abuse. However, addiction can also happen in the absence of a pharmacological component, such as seen in pathological gambling and videogaming. We use a new reinforcement learning model to highlight a previously neglected vulnerability that we suggest interacts with those already identified, whilst playing a prominent role in non-pharmacological forms of addiction. Specifically, we show that a duallearning system (i.e. combining model-based and model-free) can be vulnerable to highly rewarding, but suboptimal actions, that are followed by a complex ramification of stochastic adverse effects. This phenomenon is caused by the overload of the capabilities of an agent, as time and cognitive resources required for exploration, deliberation, situation recognition, and habit formation, all increase as a function of the depth and richness of detail of an environment. Furthermore, the cognitive overload can be aggravated due to alterations (e.g. caused by stress) in the bounded rationality, i.e. the limited amount of resources available for the model-based component, in turn increasing the agents chances to develop or maintain addictive behaviours. Our study demonstrates that, independent of drug consumption, addictive behaviours can arise in the interaction between the environmental complexity and the biologically finite resources available to explore and represent it.

neuroscience↗