Biology subjects

Lin, C.

Publications and source records attributed to Lin, C..

13 recordsLinked to original sources

bioRxiv2018

Cell lineage inference from SNP and scRNA-Seq data

Several recent studies focus on the inference of developmental and response trajectories from single cell NA-Seq (scRNA-Seq) data. A number of computational methods, often referred to as pseudo-time ordering, have been developed for this task. Recently, CRISPR has also been used to reconstruct lineage trees by inserting random mutations. However, both approaches suffer from drawbacks that limit their use. Here we develop a method to detect significant, cell type specific, sequence mutations from scRNA-Seq data. We show that only a few mutations are enough for reconstructing good branching models. Integrating these mutations with expression data further improves the accuracy of the reconstructed models. As we show, the majority of mutations we identify are likely RNA editing events indicating that such information can be used to distinguish cell types.

genomics↗

bioRxiv2018

Genetics of mouse Tas1r3-independent sucrose intake

We have previously shown that variation in sucrose intake among inbred mouse strains is due in part to polymorphisms in the Tas1r3 gene, which encodes a sweet taste receptor subunit and accounts for the Sac locus on distal Chr4. To discover other quantitative trait loci (QTLs) influencing sucrose intake, voluntary daily sucrose intake was measured in an F2 intercross with the Sac locus fixed; in backcross, reciprocal consomic strains; and in single- and double-congenic strains. Chromosome mapping identified Scon3, located on Chr9, and epistasis of Scon3 with Scon4 on Chr1. Mice with different combinations of Scon3 and Scon4 genotypes differed more than threefold in sucrose intake. To understand how these two QTLs influenced sucrose intake, we measured resting metabolism, glucose and insulin tolerance, and peripheral taste responsiveness in congenic mice. We found that the combinations of Scon3 and Scon4 genotypes influenced thermogenesis and the oxidation of fat and carbohydrate. Results of glucose and insulin tolerance tests, peripheral taste tests, and gustatory nerve recordings ruled out plasma glucose homoeostasis and peripheral taste sensitivity as major contributors to the differences in voluntary sucrose consumption. Our results provide evidence that these two novel QTLs influence mouse-to-mouse variation in sucrose intake and that both likely act through a common postoral mechanism.

animal behavior and cognition↗

bioRxiv2018

Continuous State HMMs for Modeling Time Series Single Cell RNA-Seq Data

MotivationMethods for reconstructing developmental trajectories from time series single cell RNA-Seq (scRNA-Seq) data can be largely divided into two categories. The first, often referred to as pseudotime ordering methods, are deterministic and rely on dimensionality reduction followed by an ordering step. The second learns a probabilistic branching model to represent the developmental process. While both types have been successful, each suffers from shortcomings that can impact their accuracy.\n\nResultsWe developed a new method based on continuous state HMMs (CSHMMs) for representing and modeling time series scRNA-Seq data. We define the CSHMM model and provide efficient learning and inference algorithms which allow the method to determine both the structure of the branching process and the assignment of cells to these branches. Analyzing several developmental single cell datasets we show that the CSHMM method accurately infers branching topology and correctly and continuously assign cells to paths, improving upon prior methods proposed for this task. Analysis of genes based on the continuous cell assignment identifies known and novel markers for different cell types.\n\nAvailabilitySoftware and Supporting website: www.andrew.cmu.edu/user/chiehll/CSHMM/\n\nContactzivbj@cs.cmu.edu\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

systems biology↗

bioRxiv2018

Personalized expression of bitter ‘taste’ receptors in human skin

The integumentary (i.e., skin) and gustatory systems both function to protect the human body and are a first point of contact with poisons and pathogens. These systems may share a similar protective mechanism because both human taste and skin cells express mRNA for bitter taste receptors (TAS2Rs). Here, we used gene-specific methods to measure mRNA from all known bitter receptor genes in adult human skin from freshly biopsied samples and from samples collected at autopsy from the Genotype-Tissue Expression project. Human skin expressed some but not all TAS2Rs, and for those that were expressed, the relative amounts differed markedly among individuals. For some TAS2Rs, mRNA abundance was related to sun exposure (TAS2R14, TAS2R30, TAS2R42, and TAS2R60), sex (TAS2R3, TAS2R4, TAS2R8, TAS2R9, TAS2R14, and TAS2R60), and age (TAS2R5), although these effects were not large. These findings contribute to our understanding of extraoral expression of chemosensory receptors.

molecular biology↗

bioRxiv2018

Autophagy determines osimertinib resistance through regulation of stem cell-like properties in EGFR-mutant lung cancer

Drug resistance to Osimertinib, a 3rd-generation EGFR-TKI is inevitable. Autophagy plays a contradictory role in resistance of 1st and 2nd generation EGFR-TKI, and its significance in osimertinib resistance is much less clear. We therefore investigated whether autophagy determines osimertinib resistance. First, osimertinib induced autophagy to a much greater extent than that of gefitinib, and autophagy inhibition further increased osimertinib efficacy. Next, enhanced autophagy was found in osimertinib resistant cells and autophagy inhibition partially reversed osimertinib resistance. Enhanced stem-cell like properties were found in resistant cells, and siRNA-knock down of SOX2 or ALDH1A1reversed osimertinib resistance. Of note, autophagy inhibition or siRNA-knock down of Beclin-1 decreased expression of SOX2 and ALDH1A1 and stem-cell like properties. Next, autophagy inhibition and osimertinib in combination effectively blocked tumor growth in xenografts, which was associated with decreased autophagy and stem cell-like properties in vivo. Finally, enhanced autophagy was found in lung cancer patients with resistance to osimertinib. In conclusion, the current study delineates a previously unknown function of autophagy in determining osimertinib resistance through promoting stem-cell like properties.

cancer biology↗

bioRxiv2018

Deciphering the metabolic perturbation in hepatic alveolar echinococcosis: a 1H NMR-based metabolomics study

Hepatic alveolar echinococcosis (HAE) is a chronic and potentially lethal parasitic disease. It is caused by growth of Echinococcus multilocularis larvae in liver. To date, early-stage diagnosis for the disease is not mature due to its long asymptomatic incubation period. In this study, a proton nuclear magnetic resonance (1H NMR) -based metabolomics approach was applied in conjunction with multivariate statistical analysis to investigate the altered metabolic profiles in blood serum and urine samples from HAE patients and to identify characteristic metabolic markers associated with HAE. The current results identified 21 distinctive metabolic difference between the HAE patients and healthy individuals, which can be associated with perturbations in energy metabolism, amino acid metabolism, oxidative stress, and neurotransmitter imbalance. In addition, the Fischer ratio, which is the molar ratio of branched-chain amino acids to aromatic amino acids was found significantly lower (p<0.001) in blood serum from HAE patients. The ratio, together with changes in other metabolic pathways may provide new insight into mechanistic understanding of HAE pathogenesis, and may be useful for early-stage HAE diagnosis.\n\nAuthor SummaryHepatic alveolar echinococcosis (HAE) is a life-threatening disease caused by Echinococcus multilocularis infection. The disease has a long asymptomatic early stage (5~15 years), which complicates effective diagnosis of early-stage HAE even with advanced imaging techniques. Metabolomics is an emerging analytical platform that comprises of analysis of all small molecule metabolites that are present within an organism. The applications of metabolomics method on HAE may help to reveal the molecular biology mechanisms of HAE. In the current study, we had used 1H NMR-based metabolomics technique to investigate blood serum and urine samples from HAE patients. Altered metabolic responses and characteristic differential metabolites for HAE were identified. The metabolic profiling of human biofluids provided valuable information for early-stage HAE diagnosis and for therapeutic interventions, without having to extract HAE vesicles from patients. By featuring global and comprehensive metabolic status, the metabolomics approach holds considerable promise as a noninvasive, dynamic, and effective tool for probing the underlying mechanism of HAE.

systems biology↗

bioRxiv2018

Intrinsic Excitability Increase in Cerebellar Purkinje Cells Following Delay Eyeblink Conditioning in Mice

Cerebellar learning is canonically thought to rely on synaptic plasticity, particularly at synaptic inputs to Purkinje cells. Recently, however, other complementary mechanisms have been identified. Intrinsic plasticity is one such mechanism, and depends in part on the down-regulation of calcium-dependent SK-type K channels, which is associated with an increase in neuronal excitability. In the hippocampus, SK-mediated intrinsic plasticity has been shown to play a role in trace eyeblink conditioning; however, it is not yet known how intrinsic plasticity contributes to a cerebellar learning task such as delay eyeblink conditioning. Whole cell recordings were obtained from acute cerebellar slices from mice ~48 hours after learning a delay eyeblink conditioning task. Over a period of repeated training sessions mice received either distinctly paired trials of a tone co-terminating with a periorbital shock (conditioned mice) or trials in which these stimuli were presented in an unpaired manner (pseudoconditioned mice). Conditioned mice show a significantly reduced afterhyperpolarization (AHP) following trains of parallel fiber stimuli. Moreover, we find that SK-dependent intrinsic plasticity is occluded in conditioned, but not pseudoconditioned mice. These findings show that excitability is enhanced in Purkinje cells after delay eyeblink conditioning and point toward a downregulation of SK channels as a potential underlying mechanism.

neuroscience↗

bioRxiv2018

Tissue dependent expression of bitter receptor TAS2R38 mRNA

TAS2R38 is a human bitter receptor gene with a common but inactive allele and people homozygous for the inactive form cannot perceive certain bitter compounds. The frequency of the inactive and active form of this receptor is nearly equal in many human populations and heterozygotes (with one copy of the active form and another copy of the inactive form) have the most common diplotype. However, heterozygotes differ markedly in their perception of bitterness, in part perhaps because of differences in TAS2R38 mRNA expression. Other tissues including the nasal sinuses express this receptor, where it contributes to pathogen defense. We asked whether heterozygotes with high TAS2R38 mRNA expression in taste tissue were also likely to express more TAS2R38 mRNA in sinonasal tissue. To that end, we measured TAS2R38 bitter taste receptor mRNA by qPCR in biopsied tissue, and learned that expression amount of one is not related to the other. We confirmed the general independence of expression in other tissue expressing TAS2R38 mRNA using autopsy data from the GTEx project. Taste tissue TAS2R38 mRNA expression among heterozygotes is unlikely to predict expression in other tissues, perhaps reflecting tissue-dependent function and hence regulation of this protein.

molecular biology↗

bioRxiv2018

Fast and Flexible GPU Accelerated Binding Free Energy Calculations within the AMBER Molecular Dynamics Package

Alchemical free energy calculations (AFE) based on molecular dynamics (MD) simulations are key tools in both improving our understanding of a wide variety of biological processes and accelerating the design and optimization of therapeutics for numerous diseases. Computing power and theory have, however, long been insufficient to enable AFE calculations to be routinely applied in early stage drug discovery. One of the major difficulties in performing AFE calculations is the length of time required for calculations to converge to an ensemble average. CPU implementations of MD based free energy algorithms can effectively only reach tens of nanoseconds per day for systems on the order of 50,000 atoms, even running on massively parallel supercomputers. Therefore, converged free energy calculations on large numbers of potential lead compounds are often untenable, preventing researchers from gaining crucial insight into molecular recognition, potential druggability, and other crucial areas of interest. Graphics Processing Units (GPUs) can help address this. We present here a seamless GPU implementation, within the PMEMD module of the AMBER molecular dynamics package, of thermodynamic integration (TI) capable of reaching speeds of >140 ns/day for a 44,907-atom system, with accuracy equivalent to the existing CPU implementation in AMBER. The implementation described here is currently part of the AMBER 18 beta code and will be an integral part of the upcoming version 18 release of AMBER.

biophysics↗

bioRxiv2017

Burly1 is a mouse QTL for lean body mass that maps to a 0.8-Mb region on chromosome 2

Our goal was to fine map a mouse QTL for lean body mass (Burly1) using information from several populations including newly created congenic mice derived from the B6 (host) and 129 (donor) strains. The results from each mapping population were concordant and showed that Burly1 is likely a single QTL in a 0.8-Mb region at 151.9-152.7 Mb (rs33197365 to rs3700604) on mouse chromosome 2. Results from mice of all the mapping populations we studied including intercrossed, backcrossed, consomic, and congenic strains indicate that lean body mass was increased by the B6-derived allele relative to the 129-derived allele. We determined that the congenic region harboring Burly1 contains 26 protein-coding genes, 11 noncoding RNA elements (e.g., lncRNA), and 4 pseudogenes, with 1949 predicted functional variants. The effect of the Burly1 locus on lean body weight was apparent at all ages measured and did not affect food intake or locomotor activity. However, congenic mice with the B6-allele produced more heat per kilogram of lean body weight than did controls, pointing to a genotype effect on lean mass metabolism. These results show the value of integrating information from several mapping populations to refine the map location of body composition QTLs.

genetics↗

bioRxiv2017

Adiposity QTL Adip20 decomposes into at least four loci when dissected using congenic strains

An average mouse in midlife weighs between 25 and 30 g, with about a gram of tissue in the largest adipose depot (gonadal), and the weight of this depot differs between inbred strains. Specifically, C57BL/6ByJ mice have heavier gonadal depots on average than do 129P3/J mice. To understand the genetic contributions to this trait, we mapped several quantitative trait loci (QTLs) for gonadal depot weight in an F2 intercross population. Our goal here was to fine-map one of these QTLs, Adip20 (formerly Adip5), on mouse chromosome 9. To that end, we analyzed the weight of the gonadal adipose depot from newly created congenic strains. Results from the sequential comparison method indicated at least four rather than one QTL; two of the QTLs were less than 0.5 Mb apart, with opposing directions of allelic effect. Different types of evidence (missense and regulatory genetic variation, human adiposity/body mass index orthologues, and differential gene expression) implicated numerous candidate genes from the four QTL regions. These results highlight the value of mouse congenic strains and the value of this sequential method to dissect challenging genetic architecture.

genetics↗

bioRxiv2017

OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps

Human genomes contain structural variations (SVs) that are associated with various phenotypic variations and diseases. SV detection by sequencing is incomplete due to limited read length. Nanochannel-based optical mapping (OM) allows direct observation of SVs up to hundreds of kilo-bases in size on individual DNA molecules, making it a promising alternative technology for identifying large SVs. SV detection from optical maps is non-trivial due to complex types of error present in OM data, and no existing methods can simultaneously handle all these complex errors and the wide spectrum of SV types. Here we present a novel method, OMSV, for accurate and comprehensive identification of SVs from optical maps. OMSV detects both homozygous and heterozygous SVs, SVs of various types and sizes, and SVs with and without creating/destroying restriction sites. In an extensive series of tests based on real and simulated data, OMSV achieved both high sensitivity and specificity, with clear performance gains over the latest existing method. Applying OMSV to a human cell line, we identified hundreds of SVs >2kbp, with 65% of them missed by sequencing-based callers. Independent experimental validations confirmed the high accuracy of these SVs. We also demonstrate how OMSV can incorporate sequencing data to determine precise SV break points and novel sequences in the SVs not contained in the reference. We provide OMSV as open-source software to facilitate systematic studies of large SVs.

bioinformatics↗

bioRxiv2017

Using Neural Networks To Improve Single-Cell RNA-Seq Data Analysis

While only recently developed, the ability to profile expression data in single cells (scRNA-Seq) has already led to several important studies and findings. However, this technology has also raised several new computational challenges including questions related to handling the noisy and sometimes incomplete data, how to identify unique group of cells in such experiments and how to determine the state or function of specific cells based on their expression profile. To address these issues we develop and test a method based on neural networks (NN) for the analysis and retrieval of single cell RNA-Seq data. We tested various NN architectures, some biologically motivated, and used these to obtain a reduced dimension representation of the single cell expression data. We show that the NN method improves upon prior methods in both, the ability to correctly group cells in experiments not used in the training and the ability to correctly infer cell type or state by querying a database of tens of thousands of single cell profiles. Such database queries (which can be performed using our web server) will enable researchers to better characterize cells when analyzing heterogeneous scRNA-Seq samples.\n\nSupporting website: http://sb.cs.cmu.edu/scnn/\n\nPassword for accessing the retrieval task webserver: scRNA-Seq

bioinformatics↗