Biology subjects

An, J.

Publications and source records attributed to An, J..

64 records · Page 4Linked to original sources

bioRxiv2019

Blood-spinal cord barrier leakage is not caused by neurodegeneration in amyotrophic lateral sclerosis

BackgroundAmyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease involving progressive degeneration of upper and lower motor neurons. Both lower motor neuron loss and the deposition of phosphorylated TDP-43 inclusions display regional patterning along the spinal cord. The blood-spinal cord barrier (BSCB) ordinarily restricts entry into the spinal cord parenchyma of blood components that are neurotoxic, but in ALS there is evidence for barrier breakdown. Here we sought to examine whether BSCB breakdown, motor neuron loss, and TDP-43 proteinopathy display the same regional patterning across and along the spinal cord.\n\nMethodsWe measured cerebrospinal fluid (CSF) hemoglobin in living ALS patients (n=87 controls, n=236 ALS) as a potential biomarker of BSCB and blood-brain barrier leakage. We then immunostained cervical, thoracic, and lumbar post mortem spinal cord tissue (n=5 controls, n=13 ALS) and employed semi-automated imaging and analysis to quantify and map lower motor neuron loss and phosphorylated TDP-43 inclusion load against hemoglobin leakage.\n\nResultsMotor neuron loss and TDP-43 proteinopathy were seen at all three levels of the ALS spinal cord, with most abundant TDP-43 deposition in the ventral grey (lamina IX) of the cervical and lumbar cord. In contrast, hemoglobin leakage was observed along the ALS spinal cord axis but was most severe in the dorsal grey and white matter in the thoracic spinal cord.\n\nConclusionsOur data show that leakage of the blood-spinal cord barrier occurs during life but at end-stage its distribution is independent from the major motor neuron pathology and is unlikely to be a major contributor to pathogenesis in ALS.

neuroscience↗

bioRxiv2019

Mutation profiling of both cfDNAs and CTCs in gynecological cancer patients

In the recent years, microRNAs (miRNAs) have been discovered to play a very important role in biological processes such as development, differentiation, and apoptosis. The miRNA expression levels in cells are associated with diverse diseases including cancers. MiRNA inhibitors have been widely employed for studying the functions and targets of miRNAs by transfecting the inhibitors into cells. The concentrations of miRNA inhibitors used for such studies can vary depending on the types of miRNAs being tested, the cell lines under study, and the analysis methods. Therefore, in order to obtain accurate results, appropriate amounts of miRNA inhibitors have to be used in the experiments. Apart from amounts, the evaluation of inhibitors may also have to be conducted for functional studies.\n\nHere we developed capillary electrophoresis with laser-induced fluorescence (CE-LIF) method for evaluating miRNA inhibitor and for optimizing miRNA inhibitor concentrations, in the A549 lung cancer cell line. The target miRNAs, miRNA-23a and miRNA-24 are biomarker candidates in lung cancer cell lines. Our results showed that miRNA-23a and miRNA-24 were effectively inhibited upon transfection with 20 nM miRNA inhibitors using CE-LIF method. Furthermore, these results demonstrated the potential of CE for fast, specific, sensitive and specific analyses for the evaluation and determination of the optimal concentration of miRNA inhibitors for functional studies.\n\nAbstract Graphics\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC=\"FIGDIR/small/566786v4_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (31K):\norg.highwire.dtl.DTLVardef@2bbfeeorg.highwire.dtl.DTLVardef@45b7e3org.highwire.dtl.DTLVardef@12ba79borg.highwire.dtl.DTLVardef@108ec2f_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2019

Investigating Genetic Heterogeneity in Major Depression Through Item-level Genetic Analyses of the PHQ-9

BackgroundMajor Depressive Disorder (MDD) is a clinically heterogeneous disorder. Previous large-scale genetic studies of MDD have explored genetic risk factors of MDD case-control status or aggregated sums of depressive symptoms, ignoring possible clinical or genetic heterogeneity. AimIn this study, we present the results of symptom-level genetic analyses and compare SNP-based heritability (h2 O_SCPCAPSNPC_SCPCAP) and genetic correlations across major depression symptoms. We further investigate genetic correlations with a range of psychiatric disorders and other associated traits. Methods: We have analysed data from the UK biobank and included 148,752 subjects of white British ancestry with genotype data who completed nine items of a self-rated measure of depression: the Patient Health Questionnaire (PHQ-9). Genome-Wide Association analyses were conducted for nine symptoms and two composite measures. LD score regression analysis was used to calculate SNP-based heritability (h2 O_SCPCAPSNPC_SCPCAP) and genetic correlations (rg) across symptoms and to investigate genetic correlations with 25 external phenotypes. Confirmatory factor analyses were applied to test whether one, two, or three-factor models best fit the pattern of genetic correlations across the nine symptoms. ResultsWe identified 9 novel genome-wide significant genomic loci, with no overlap in loci across depression symptoms. h2 O_SCPCAPSNPC_SCPCAP ranged from 3% (suicidal ideation) to 11% (fatigue). Genetic correlations range from 0.54 to 0.96 (all p < 1.39x10-3) with 30 of 36 correlations being significantly smaller than 1. A 3-factor model provided the best fit to the genetic correlation matrix, with factors representing "psychological", "neurovegetative", and "psychomotor / concentration" symptoms. The genetic correlations with external phenotypes showed large variation across the nine symptoms. DiscussionPatterns of h2 O_SCPCAPSNPC_SCPCAP and genetic correlations differed across the nine symptoms of depression. Our findings suggest that the large phenotypic heterogeneity observed for MDD is recapitulated at a genetic level. Future studies should investigate how genetic heterogeneity in MDD influences the efficacy of clinical interventions.

genetics↗

bioRxiv2019

Genetic diversity analysis of an isolate of microsporidia infesting Athetis lepigone

In this study, PCR amplification, cloning and sequencing analysis were adopted to explore genetic diversity of microsporidia (LEP9557) infecting Athetis lepigone. The small subunit ribosomal DNA (SSU rDNA), internal transcribed spacer (ITS) and intergenic spacers (IGS) of ribosomal RNA (rRNA) were cloned from the strain and sequenced. By means of multiple sequence alignment, we found that the three gene regions had different levels of polymorphism. There was greater polymorphism in ITS (74 variable sites) and IGS (55.59%) regions than in the SSU rDNA (17 variable sites). Phylogenetic analysis was performed using Kimura 2-parameter with neighbor joining and the results showed that LEP9557 had a close relationship with Nosema bombycis. Sequences of each clone were submitted to Genbank (Accession number: MF150254-MF150258). All of the results indicated the presence of genetic diversity in LEP9557, which established the foundation for identifying the phylogeny and relationships with other microsporidian strains, and had significant biological meaning for maintaining the survival and population continuity of the strain.

microbiology↗

bioRxiv2018

Genomic perspectives on adaptation and conservation in the endangered long-tailed goral (Naemorhedus caudatus).

Native to the mountains of East Asia, the long-tailed goral (Naemorhedus caudatus) is a vulnerable wild ungulate in the tribe Caprini. To understand key conservation issues related to fragmentation and subsequent endangerment of this montane species, we sequenced and analyzed the genome of a long-tailed goral to explore historical demography, contemporary levels of genetic diversity, and potential immune response. When compared to ten additional mammalian reference genomes, we identified 357 positively selected genes (PSGs) in the long-tailed goral and 364 PSGs in the Caprini lineage. Gene Ontology analyses showed statistical enrichment in biological processes related to immune function and in genes and pathways related to blood coagulation. We also identified low levels of heterozygosity (0.00114) in the long-tailed goral along with decreases in population size relative to other species of Caprini. Finally, we provide evidence for positive selection on the muscle development gene myostatin (MSTN) in the Caprini lineage, which may have increased the muscle development and climbing ability in the caprine common ancestor. Low effective population size and decreased heterozygosity of the long-tailed goral raise conservation concern about the effects of habitat fragmentation, over harvest, and inbreeding on this vulnerable species.

bioinformatics↗

bioRxiv2018

Reward Modulates Local Field Potentials, Spiking Activity and Spike-Field Coherence in the Primary Motor Cortex

Reward modulation of the primary motor cortex (M1) could be exploited in developing an autonomously updating brain-machine interface (BMI) based on a reinforcement learning architecture. In order to understand the multifaceted effects of reward on M1 activity, we investigated how neural spiking, oscillatory activities and their functional interactions are modulated by conditioned stimuli related reward expectation. To do so, local field potentials (LFPs) and singleunit/multi-unit activities were recorded simultaneously and bilaterally from M1 cortices while five non-human primates performed cued center-out reaching or grip force tasks either manually using their right arm/hand or observed passively. We found that reward expectation influenced the strength of alpha (8-14 Hz) power, alpha-gamma comodulation, alpha spike-field coherence, and firing rates in general in M1. Furthermore, we found that an increase in alpha-band power was correlated with a decrease in neural spiking activity, that firing rates were highest at the trough of the alpha-band cycle and lowest at the peak of its cycle. These findings imply that alpha oscillations modulated by reward expectation have an influence on spike firing rate and spike timing during both reaching and grasping tasks in M1. These LFP, spike, and spike-field interactions could be used to follow the M1 neural state in order to enhance BMI decoding (An et al., 2018; Zhao et al., 2018).\n\nSignificance StatementKnowing the subjective value of performed or observed actions is valuable feedback that can be used to improve the performance of an autonomously updating brain-machine interface (BMI). Reward-related information in the primary motor cortex (M1) may be crucial for more stable and robust BMI decoding (Zhao et al., 2018). Here, we present how expectation of reward during motor tasks, or simple observation, is represented by increased spike firing rates in conjunction with decreased alpha (8-14 Hz) oscillatory power, alpha-gamma comodulation, and alpha spike-field coherence, as compared to non-rewarding trials. Moreover, a phasic relation between alpha oscillations and firing rates was observed where firing rates were found to be lowest and highest at the peak and trough of alpha oscillations, respectively.

neuroscience↗

bioRxiv2018

BALLI: Bartlett-Adjusted Likelihood-based LInear Model Approach for Identifying Differentially Expressed Gene with RNA-seq Data

MotivationTranscriptomic profiles can improve our understanding of the phenotypic molecular basis of biological research, and many statistical methods have been proposed to identify differentially expressed genes under two or more conditions with RNA-seq data. However, statistical analyses with RNA-seq data often suffer from small sample sizes, and global variance estimates of RNA expression levels have been utilized as prior distributions for gene-specific variance estimates, making it difficult to generalize the methods to more complicated settings. We herein proposed a Bartlett-Adjusted Likelihood based LInear mixed model approach (BALLI) to analyze more complicated RNA-seq data. The proposed method estimates the technical and biological variances with a linear mixed effect model, with and without adjusting small sample bias using Bartletts corrections.\n\nResultsWe conducted extensive simulations to compare the performance of BALLI with those of existing approaches (edgeR, DESeq2, and voom). Results from the simulation studies showed that BALLI correctly controlled the type-1 error rates at the various nominal significance levels, and produced better statistical power and precision estimates than those of other competing methods in various scenarios. Furthermore, BALLI was robust to variation of library size. It was also successfully applied to Holstein milk yield data, illustrating its practical value.\n\nAvailability and ImplementationBALLI is implemented as R package and freely available at http://healthstat.snu.ac.kr/software/balli/.\n\nContactwon1@snu.ac.kr\n\nSupplementary InformationSupplementary data are available at Bioinformatics online

bioinformatics↗

bioRxiv2018

Near Perfect Neural Critic from Motor Cortical Activity Toward an Autonomously Updating Brain Machine Interface

We are developing an autonomously updating brain machine interface (BMI) utilizing reinforcement learning principles. One aspect of this system is a neural critic that determines reward expectations from neural activity. This critic is then used to update a BMI decoder towards an improved performance from the users perspective. Here we demonstrate the ability of a neural critic to classify trial reward value given activity from the primary motor cortex (M1), using neural features from single/multi units (SU/MU), and local field potentials (LFPs) with prediction accuracies up to 97% correct. A nonhuman primate subject conducted a cued center out reaching task, either manually, or observationally. The cue indicated the reward value of a trial. Features such as power spectral density (PSD) of the LFPs and spike-field coherence (SFC) between SU/MU and corresponding LFPs were calculated and used as inputs to several classifiers. We conclude that hybrid features of PSD and SFC show higher classification performance than PSD or SFC alone (accuracy was 92% for manual tasks, and 97% for observational). In the future, we will employ these hybrid features towards our autonomously updating BMI.

neuroscience↗

bioRxiv2017

Loss of CHIP Expression Perturbs Glucose Homeostasis and Leads to Type II Diabetes through Defects in Microtubule Polymerization and Glucose Transporter Localization

Recent evidence has implicated CHIP (carboxyl terminus of Hsc/Hsp70-interacting protein), a co-chaperone and ubiquitin ligase, in the functional support of several metabolism-related proteins, including AMPK and SirT6. In addition to previously reported aging and stress intolerance phenotypes, we find that CHIP -/- mice also demonstrate a Type II diabetes-like phenotype, including poor glucose tolerance, decreased sensitivity to insulin, and decreased insulin-stimulated glucose uptake in isolated skeletal muscle, characteristic of insulin resistance. In CHIP-deficient cells, glucose stimulation fails to induce translocation of Glut4 to the plasma membrane. This impairment in Glut4 translocation in CHIP-deficient cells is accompanied by decreased tubulin polymerization associated with decreased phosphorylation of stathmin, a microtubule-associated protein required for polymerization-dependent protein trafficking within the cell. Together, these data describe a novel role for CHIP in regulating microtubule polymerization that assists in glucose transporter translocation, promoting whole-body glucose homeostasis and sensitivity to insulin.

physiology↗

bioRxiv2017

Myotis rufoniger Genome Sequence and Analyses: M. rufoniger’s Genomic Feature and the Decreasing Effective Population Size of Myotis Bats

Myotis rufoniger is a vesper bat in the genus Myotis. Here we report the whole genome sequence and analyses of the M. rufoniger. We generated 124 Gb of short-read DNA sequences with an estimated genome size of 1.88 Gb at a sequencing depth of 66x fold. The sequences were aligned to M. brandtii bat reference genome at a mapping rate of 96.50% covering 95.71% coding sequence region at 10x coverage. The divergence time of Myotis bat family is estimated to be 11.5 million years, and the divergence time between M. rufoniger and its closest species M. davidii is estimated to be 10.4 million years. We found 1,239 function-altering M. rufoniger specific amino acid sequences from 929 genes compared to other Myotis bat and mammalian genomes. The functional enrichment test of the 929 genes detected amino acid changes in melanin associated DCT, SLC45A2, TYRP1, and OCA2 genes possibly responsible for the M. rufonigers red fur color and a general coloration in Myotis. N6AMT1 gene, associated with arsenic resistance, showed a high degree of function alteration in M. rufoniger. We further confirmed that M. rufoniger also has bat-specific sequences within FSHB, GHR, IGF1R, TP53, MDM2, SLC45A2, RGS7BP, RHO, OPN1SW, and CNGB3 genes that have already been published to be related to bats reproduction, lifespan, flight, low vision, and echolocation. Additionally, our demographic history analysis found that the effective population size of Myotis clade has been consistently decreasing since [~]30k years ago. M. rufonigers effective population size was the lowest in Myotis bats, confirming its relatively low genetic diversity.

genomics↗