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Liu, J. S.

Publications and source records attributed to Liu, J. S..

8 recordsLinked to original sources

The Drosophila wing is a high-throughput and versatile screening tool for Tau-mediated disease mechanisms and drug discovery.

Tau protein contributes to microtubule stability, which is disrupted in Alzheimers disease and other Tauopathies. In these diseases, Tau molecules become hyperphosphorylated, misfolded and aggregated, propagating pathology across the brain. Studies dissecting disease mechanisms or screening disease-modifying therapies rely on animal models that unveil pathogenic events in vivo but also take several weeks or months to complete. Here we describe a versatile experimental paradigm that yields results in days and yet offers all the advantages of a genetically tractable in vivo system: the Drosophila wing disc. Mimicking neurotoxicity, human Tau expression causes cell death in the wing disc leading to quantifiable phenotypes in the adult wing. The neuroprotective peptide NAP ameliorates Tau toxicity in this system, validating it as a cost-effective drug screening tool. Phenocopying adult neurons, Tau toxicity in the wing disc is exacerbated by simulating hyper-phosphorylation and prevented by suppressing aggregation. Additionally, we show that the wing disc can dissect disease mechanisms that underpin clinically relevant Tau variants. Thus, the wing disc offers an in vivo experimental paradigm for fast and efficient exploration of disease mechanism and screening.

neuroscience↗

A phylogenetic method linking nucleotide substitution rates to rates of continuous trait evolution

Genomes contain conserved non-coding sequences that perform important biological functions, such as gene regulation. We present a phylogenetic method, PhyloAcc-C, that associates nucleotide substitution rates with changes in a continuous trait of interest. The method takes as input a multiple sequence alignment of conserved elements, continuous trait data observed in extant species, and a background phylogeny and substitution process. Gibbs sampling is used to assign rate categories (background, conserved, accelerated) to lineages and explore whether the assigned rate categories are associated with increases or decreases in the rate of trait evolution. We test our method using simulations and then illustrate its application using mammalian body size and lifespan data previously analyzed with respect to protein coding genes. Like other studies, we find processes such as tumor suppression, telomere maintenance, and p53 regulation to be related to changes in longevity and body size. In addition, we also find that skeletal genes, and developmental processes, such as sprouting angiogenesis, are relevant. The R/C++ software package implementing our method is available under an open source license from https://github.com/phyloacc/PhyloAcc-C.

bioinformatics↗

PhyloAcc-GT: A Bayesian method for inferringpatterns of substitution rate shifts and associations with binary traits under gene tree discordance

An important goal of evolutionary genomics is to identify genomic regions whose substitution rates differ among lineages. For example, genomic regions experiencing accelerated molecular evolution in some lineages may provide insight into links between genotype to phenotype. Several comparative genomics methods have been developed to identify genomic accelerations between species, including a Bayesian method called PhyloAcc, which models shifts in substitution rate in multiple target lineages on a phylogeny. However, few methods consider the possibility of discordance between the trees of individual loci and the species tree due to incomplete lineage sorting, which might cause false positives. Here we present PhyloAcc-GT, which extends PhyloAcc by modeling gene tree heterogeneity to detect rate shifts across genomic regions. Given a species tree, we adopt the multispecies coalescent model as the prior distribution of gene trees, use Markov chain Monte Carlo (MCMC) for inference, and design novel MCMC moves to sample gene trees efficiently. Through extensive simulations, we show that PhyloAcc-GT outperforms PhyloAcc and other methods in identifying target-lineage-specific accelerations and detecting complex patterns of rate shifts, and is robust to specification of population size parameters. We apply PhyloAcc-GT to two examples of convergent evolution: flightlessness in ratites and marine mammal adaptations. PhyloAcc-GT is usually more conservative than PhyloAcc in calling convergent rate shifts because it identifies more accelerations on ancestral than on terminal branches. In summary, PhyloAcc-GT is a useful tool to identify shifts in substitution rate associated with specific target lineages while accounting for incomplete lineage sorting.

evolutionary biology↗

ASH1L REGULATES THE STRUCTURAL DEVELOPMENT OF NEURONAL CIRCUITRY BY MODULATING BDNF/TrkB SIGNALING IN HUMAN NEURONS

Autism spectrum disorders (ASD) are associated with defects in neuronal connectivity and are highly heritable. Genetic findings suggest that there is an overrepresentation of chromatin regulatory genes among the genes associated with ASD. ASH1 like histone lysine methyltransferase (ASH1L) was identified as a major risk factor for autism. ASH1L methylates Histone H3 on Lysine 36, which is proposed to result primarily in transcriptional activation. However, how mutations in ASH1L lead to deficits in neuronal connectivity associated with autism pathogenesis is not known. We report that ASH1L regulates neuronal morphogenesis by counteracting the catalytic activity of Polycomb Repressive complex 2 group (PRC2) in stem cell-derived human neurons. Depletion of ASH1L decreases neurite outgrowth and decreases expression of the gene encoding the neurotrophin receptor TrkB whose signaling pathway is linked to neuronal morphogenesis. This is overcome by inhibition of PRC2 activity, indicating a balance between the Trithorax group protein ASH1L and PRC2 activity determines neuronal morphology and connectivity. Thus, ASH1L epigenetically regulates neuronal connectivity by modulating the BDNF-TrkB signaling pathway, which likely contributes to the neurodevelopmental pathogenesis associated with ASD in patients with ASH1L mutations. eTOC BLURBCheon et al. report a novel epigenetic mechanism that implicates the counteracting activities of the evolutionarily conserved Trithorax (ASH1L) and Polycomb (PRC2) chromatin regulators, in the modulation of human neuronal connectivity by regulating the developmentally important TrkB-BDNF signaling pathway. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/954586v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@738ee5org.highwire.dtl.DTLVardef@aa8085org.highwire.dtl.DTLVardef@1dbc315org.highwire.dtl.DTLVardef@e4bfa2_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LIASH1L regulates neuronal morphogenesis by modulating neurotrophin signaling C_LIO_LICounteracting activities of Trithorax (ASH1L) and Polycomb (PRC2) affect neuronal arborization C_LIO_LILoss of ASH1L modulates growth cone size in human neurons C_LI

neuroscience↗

SIMPLEs: a single-cell RNA sequencing imputation strategy preserving gene modules and cell clusters variation

A main challenge in analyzing single-cell RNA sequencing (scRNASeq) data is to reduce technical variations yet retain cell heterogeneity. Due to low mRNAs content per cell and molecule losses during the experiment (called "dropout"), the gene expression matrix has substantial zero read counts. Existing imputation methods either treat each cell or each gene identically and independently, which oversimplifies the gene correlation and cell type structure. We propose a statistical model-based approach, called SIMPLEs, which iteratively identifies correlated gene modules and cell clusters and imputes dropouts customized for individual gene module and cell type. Simultaneously, it quantifies the uncertainty of imputation and cell clustering. Optionally, SIMPLEs can integrate bulk RNASeq data for estimating dropout rates. In simulations, SIMPLEs performed significantly better than prevailing scRNASeq imputation methods by various metrics. By applying SIMPLEs to several real data sets, we discovered gene modules that can further classify subtypes of cells. Our imputations successfully recovered the expression trends of marker genes in stem cell differentiation and can discover putative pathways regulating biological processes.

bioinformatics↗

Determinants of transcription factor regulatory range

To characterize the genomic distances over which transcription factors (TFs) influence gene expression, we examined thousands of TF and histone modification ChIP-seq datasets and thousands of gene expression profiles. A model integrating these data revealed two classes of TF: one with short-range regulatory influence, the other with long-range regulatory influence. The two TF classes also had distinct chromatin-binding preferences and auto-regulatory properties. The regulatory range of a single TF bound within different topologically associating domains (TADs) depended on intrinsic TAD properties such as local gene density and G/C content, but also on the TAD chromatin state in specific cell types. Our results provide evidence that most TFs belong to one of these two functional classes, and that the regulatory range of long-range TFs is chromatin-state dependent. Thus, consideration of TF type, distance-to-target, and chromatin context is likely important in identifying TF regulatory targets and interpreting GWAS and eQTL SNPs.

genomics↗

A hierarchical Bayesian model for detecting convergent rate changes of conserved elements on phylogenetic trees

Conservation of DNA sequence over evolutionary time is a strong indicator of function, and gain or loss of sequence conservation can be used to infer changes in function across a phylogeny. Changes in evolutionary rates on particular lineages in a phylogeny can indicate shared functional shifts, and thus can be used to detect genomic correlates of phenotypic convergence. However, existing methods do not allow easy detection of patterns of rate variation, which causes challenges for detecting convergent rate shifts or other complex evolutionary scenarios. Here we introduce PhyloAcc, a new Bayesian method to model substitution rate changes in conserved elements across a phylogeny. The method assumes several categories of substitution rate for each branch on the phylogenetic tree, estimates substitution rates per category, and detects changes of substitution rate as the posterior probability of a category switch. Simulations show that PhyloAcc can detect genomic regions with rate shifts in multiple target species better than previous methods and has a higher accuracy of reconstructing complex patterns of substitution rate changes than prevalent Bayesian relaxed clock models. We demonstrate the utility of PhyloAcc in two classic examples of convergent phenotypes: loss of flight in birds and the transition to marine life in mammals. In each case, our approach reveals numerous examples of conserved non-exonic elements with accelerations specific to the phenotypically convergent lineages. Our method is widely applicable to any set of conserved elements where multiple rate changes are expected on a phylogeny.

evolutionary biology↗

Convergent regulatory evolution and the origin of flightlessness in palaeognathous birds

The relative roles of regulatory and protein evolution in the origin and loss of convergent phenotypic traits is a core question in evolutionary biology. Here we combine phylogenomic, epigenomic and developmental data to show that convergent evolution of regulatory regions, but not protein-coding genes, is associated with flightlessness in palaeognathous birds, a classic example of a convergent phenotype. Eleven new genomes, including a draft genome from an extinct moa, resolve palaeognath phylogeny and show that the incidence of independent, convergent accelerations among 284,000 conserved non-exonic elements is significantly more frequent in ratites than other bird lineages. Ratite-specific acceleration of conserved regions and measures of open chromatin across eight tissues in the developing chick identify candidate regulatory regions that may have modified or lost function in ratites. Enhancer activity assays conducted in the early developing chicken forelimb confirm that volant versions of a conserved element in the first intron of the TEAD1 gene display conserved enhancer activity, whereas an accelerated flightless version fails to drive reporter gene expression. Our results show that convergent molecular changes associated with loss of flight are largely regulatory in nature.

evolutionary biology↗