Biology subjects

An, J.

Publications and source records attributed to An, J..

4 recordsLinked to original sources

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↗