Biology subjects

Gu, S.

Publications and source records attributed to Gu, S..

108 records · Page 6Linked to original sources

bioRxiv2019

Genome-wide CRISPR screens identify essential cell growth mediators in BRAF-inhibitor resistant melanoma

BRAF is a serine-threonine kinase that harbors activating mutations in [~]7% of human malignancies and [~]60% of melanomas. Despite initial clinical responses to BRAF inhibitors (BRAFi), patients frequently develop drug resistance. To identify candidate therapeutic targets for BRAFi-resistant melanoma, we conducted CRISPR screens in melanoma cells harboring an activating BRAF mutation that had also acquired resistance to BRAFi. The screens identified pathways and genes critical for BRAFi resistance in melanoma cells. To investigate the mechanisms and pathways enabling resistance to BRAFi in melanomas, we integrated expression data, ATAC-seq, and CRISPR screen results. We identified the JUN family of transcription factors and the ETS family transcription factor ETV5 as key regulators of CDK6 that enabled resistance to BRAFi in melanoma cells. Our findings reveal genes whose loss of function conferred resistance to a selective BRAF inhibitor, providing new insight into signaling pathways that contribute to acquired resistance in melanoma.

cancer biology↗

bioRxiv2019

Integrated Sequencing & Array Comparative Genomic Hybridization in Familial Parkinson’s Disease

BackgroundParkinsons disease (PD) is a genetically heterogeneous condition; both single nucleotide variants (SNVs) and copy number variants (CNVs) are important genetic risk factors. We examined the utility of combining exome sequencing and genome-wide array-based comparative genomic hybridization (aCGH) for identification of PD genetic risk factors. MethodsWe performed exome sequencing on 110 subjects with PD and a positive family history; 99 subjects were also evaluated using genome-wide aCGH. We interrogated exome sequencing and array comparative genomic hybridization data for pathogenic SNVs and CNVs at Mendelian PD gene loci. SNVs were confirmed via Sanger sequencing. CNVs were confirmed with custom-designed high-density aCGH, droplet digital PCR, and breakpoint sequencing. ResultsUsing exome sequencing, we discovered individuals with known pathogenic single nucleotide variants in GBA (p.E365K, p.T408M, p.N409S, p.L483P) and LRRK2 (p.R1441G and p.G2019S). Two subjects were each double heterozygotes for variants in GBA and LRRK2. Based on aCGH, we additionally discovered cases with an SNCA duplication and heterozygous intragenic GBA deletion. Five additional subjects harbored both SNVs (p.N52fs, p.T240M, p.P437L, p.W453*) and likely disrupting CNVs at the PARK2 locus, consistent with compound heterozygosity. In nearly all cases, breakpoint sequencing revealed microhomology, a mutational signature consistent with CNV formation due to DNA replication errors. ConclusionsIntegrated exome sequencing and aCGH yielded a genetic diagnosis in 19.3% of our familial PD cohort. Our analyses highlight potential mechanisms for SNCA and PARK2 CNV formation, uncover multilocus pathogenic variation, and identify novel SNVs and CNVs for further investigation as potential PD risk alleles.

genetics↗

bioRxiv2019

TGS-GapCloser: fast and accurately passing through the Bermuda in large genome using error-prone third-generation long reads

The completeness and accuracy of genome assemblies determine the quality of subsequent bioinformatics analysis. Despite benefiting from the medium/long-range information of third-generation sequencing techniques, current gap-closing tools to enhance assemblies suffer multi-alignments and high error rates, resulting in huge time and money costs.\n\nWe developed a software tool, TGS-GapCloser that uses the low depth (>=10X) single molecule sequencing long reads without any error correction to close gaps. The algorithm distinguishes gap regions from the alignments of long reads against original scaffolds, corrects only the candidate regions, and assigns the best sequences to each gap. We demonstrate that TGS-GapCloser improves the contig N50 value of draft assembly by 25-fold on average, updating above 90% gaps with 93.96% positive predictive value. Despite of high error rate of raw long reads, improved assemblies archive Q50 (99.999%) single-base accuracy with only 11.8% decrement to inputs. Besides it could complete more gaps, and is also [~]29-fold faster than mainstream gap-closing tools. BUSCO analysis revealed that 3.4%-13.1% more expected genes were complete. TGS-GapCloser also shows its power to fill gaps for ultra large genome assembly of ginkgo ([~]12Gb) with 71.6% of gaps closed. The validation of inserted or merged gap sequences was conducted with NGS reads and reference genomes, respectively. The updated genome assemblies may promote the gene annotation, structure variant calling and thus improving the downstream analysis of ontogeny, phylogeny, and evolution.

bioinformatics↗

bioRxiv2019

One-step generation of zebrafish carrying a conditional knockout-knockin visible switch via CRISPR/Cas9-mediated intron targeting

The zebrafish has been becoming a popular vertebrate animal model in biomedical research. However, it is still challenging for making conditional gene knockout (CKO) zebrafish due to the low efficiency of homologous recombination (HR). Here we report an efficient non-HR-based method for generating zebrafish carrying a CKO and knockin (KI) switch (zCKOIS) coupled with dual-color fluorescent reporters. Using this strategy, we generated hey2zCKOIS which served as a hey2 KI reporter with EGFP expression. Upon Cre induction in targeted cells, the hey2zCKOIS was switched to a non-functional CKO allele hey2zCKOIS-inv associated with TagRFP expression, enabling to visualize CKO alleles. Thus, the simplification of the design, and the visibility and combination of both CKO and KI alleles engineering make our zCKOIS strategy an applicable CKO approach for zebrafish.

genetics↗

bioRxiv2019

SLR-superscaffolder: a de novo scaffolding tool for synthetic long reads using a top-to-bottom scheme

Synthetic long reads (SLR) with long-range co-barcoding information have been recently developed and widely applied in genomics researches. We proposed a scaffolding model of the co-barcoding information and developed a scaffolding tool with adopting a top-to-bottom scheme to make full use of the complementary information in SLR datasets and a screening algorithm to reduce negative effects from misassembled contigs in an input assembly. In comparison with other available SLR scaffolding tools, our tool obtained the best quality improvement for different input assemblies, especially for those assembled by the next-generation sequencing reads, where the improvement of contiguity is about several hundred-folds.

bioinformatics↗

bioRxiv2019

Single cell and single nucleus RNA-Seq reveal cellular heterogeneity and homeostatic regulatory networks in adult mouse stria vascularis

The stria vascularis (SV) generates the endocochlear potential (EP) in the inner ear and is necessary for proper hair cell mechanotransduction and hearing. While channels belonging to SV cell types are known to play crucial roles in EP generation, relatively little is known about gene regulatory networks that underlie the ability of the SV to generate and maintain the EP. Using single cell and single nucleus RNA-sequencing, we identify and validate known and rare cell populations in the SV. Furthermore, we establish a basis for understanding molecular mechanisms underlying SV function by identifying potential gene regulatory networks as well as druggable gene targets. Finally, we associate known deafness genes with adult SV cell types. This work establishes a basis for dissecting the genetic mechanisms underlying the role of the SV in hearing and will serve as a basis for designing therapeutic approaches to hearing loss related to SV dysfunction.

genomics↗

bioRxiv2019

Interpretable Multimodality Embedding of Cerebral Cortex Using Attention Graph Network for Identifying Bipolar Disorder

Bipolar Disorder (BP) is a mental disorder that affects 1 [~] 2% of the population. Early diagnosis and targeted treatment can benefit from associated biological markers. The existing methods typically utilize biomarkers from anatomical MRI or functional BOLD imaging, but lack the ability of revealing the relationship between integrated modalities and disease. In this paper, we developed an Edge-weighted Graph Attention Network (EGAT) with Dense Hierarchical Pooling (DHP), to better understand the underlying roots of the disorder from the view of structure-function integration. For the input, the underlying graphs are constructed from functional connectivity matrices and the nodal features consist of both the anatomical features and the statistics of the connectivity. We investigated the potential benefits of using EGAT to classify BP vs. Healthy Control (HC). Compared with traditional machine learning classifiers, our proposed EGAT embedding increased improved 10 [~] 20% in the accuracy and F1-score, compared with alternative classifiers. More specifically, by examining the attention map and gradient sensitivity of nodal features, we indicated that associated with the abnormality of anatomical geometric properties, multiple interactive patterns among Default Mode, Fronto-parietal and Cingulo-opercular networks contribute to identifying BP.

neuroscience↗

bioRxiv2019

Phosgene Inhalation Causes Hemolysis and Acute Lung Injury

Phosgene (Carbonyl Chloride, COCl2) remains an important chemical intermediate in many industrial processes such as combustion of chlorinated hydrocarbons and synthesis of solvents (degreasers, cleaners). It is a sweet smelling gas, and therefore does not prompt escape by the victim upon exposure. Supplemental oxygen and ventilation are the only available management strategies. This study was aimed to delineate the pathogenesis and identify novel biomarkers of acute lung injury post exposure to COCl2 gas. Adult male and female C57BL/6 mice (20-25 g), exposed to COCl2 gas (10 or 20ppm) for 10 minutes in environmental chambers, had a dose dependent reduction in PaO2 and an increase in PaCO2, 1 day post exposure. However, mortality increased only in mice exposed to 20ppm of COCl2 for 10 minutes. Correspondingly, these mice (20ppm) also had severe acute lung injury as indicated by an increase in lung wet to dry weight ratio, extravasation of plasma proteins and neutrophils into the bronchoalveolar lavage fluid, and an increase in total lung resistance. The increase in acute lung injury parameters in COCl2 (20ppm, 10min) exposed mice correlated with simultaneous increase in oxidation of red blood cells (RBC) membrane, RBC fragility, and plasma levels of cell-free heme. In addition, these mice had decreased plasmalogen (plasmenylethanolamine) and elevated levels of their breakdown product, polyunsaturated lysophosphatidylethanolamine, in the circulation suggesting damage to cellular plasma membranes. This study highlights the importance of free heme in the pathogenesis of COCl2 lung injury and identifies plasma membrane breakdown product as potential biomarkers of COCl2 toxicity.

physiology↗

bioRxiv2018

A pairwise maximum entropy model uncovers the white matter scaffold underlying emergent dynamics in intracranial EEG

A major challenge in systems neuroscience is to understand how the brains structural architecture gives rise to its complex functional dynamics. Here, we address this challenge by examining the inter-ictal activity of five patients with medically refractory epilepsy during [~] 15 hours of multi-channel intracranial recording. By constructing a pairwise maximum entropy model (MEM) of the observed neural dynamics, we seek to uncover the fundamental relationship between functional activity and its underlying structural substrate. Despite only incorporating the pairwise correlations in the observed neural activity, we find that the pairwise MEM robustly fits large-scale patterns of inter-ictal power dynamics across a wide range of frequency bands, notably displaying time-invariance and cross-frequency similarity. Furthermore, across all frequency bands, we demonstrate that the pairwise MEM accurately identifies the structural white matter connections between brain regions, outperforming other common model-free measures of functional connectivity. Together, our findings show that a simple pairwise MEM, which is explicitly ignorant of higher-order correlations between three or more brain regions, not only captures complex spatiotemporal patterns of neural activity across the frequency spectrum, but also suggests that the network of structural connections in the human brain is a plausible scaffold capable of supporting observed wide-band neural dynamics.

neuroscience↗

bioRxiv2018

A giant ankyrin-B mechanism for neuro-diversity/divergence through stochastic ectopic axon projections

ANK2 is a high-confidence autism spectrum disorder (ASD) gene where affected individuals exhibit diverse symptoms with a wide range of IQ. We report a cellular mechanism resulting in stochastic brain connectivity that provides a rationale for both gain and loss of function due to ANK2 mutation. Deficiency of giant ankyrin-B (ankB), the neurospecific ANK2 mutation target, results in ectopic CNS axon tracts associated with increased axonal branching. We elucidate a mechanism limiting axon branching, whereby giant ankB is recruited by L1CAM to periodic axonal plasma membrane domains where it coordinates cortical microtubules and prevents microtubule stabilization of nascent axon branches. Heterozygous giant ankB mutant mice exhibit innate social deficits combined with normal/enhanced cognitive function. Thus, giant ankB-deficiency results in gain of aberrant structural connectivity with penetrant behavioral consequences that may contribute to both high and low-function ASD and other forms of neurodiversity/divergence.

neuroscience↗

bioRxiv2018

Optimization of Energy State Transition Trajectory Supports the Development of Executive Function During Youth

Executive function develops rapidly during adolescence, and failures of executive function are associated with both risk-taking behaviors and psychopathology. However, it remains relatively unknown how structural brain networks mature during this critical period to facilitate energetically demanding transitions to activate the frontoparietal system, which is critical for executive function. In a sample of 946 human youths (ages 8-23 yr) who completed diffusion imaging as part of the Philadelphia Neurodevelopment Cohort, we capitalized upon recent advances in network control theory in order to calculate the control energy necessary to activate the frontoparietal system given the existing structural network topology. We found that the control energy required to activate the frontoparietal system declined with development. Moreover, we found that this control energy pattern contains sufficient information to make accurate predictions about individuals brain maturity. Finally, the control energy costs of the cingulate cortex were negatively correlated with executive performance, and partially mediated the development of executive performance with age. These results could not be explained by changes in general network control properties or in network modularity. Taken together, our results reveal a mechanism by which structural networks develop during adolescence to facilitate the instantiation of activation states necessary for executive function.\n\nSIGNIFICANCE STATEMENTExecutive function undergoes protracted development during youth, but it is unknown how structural brain networks mature to facilitate the activation of the frontoparietal cortex that is critical for executive processes. Here, we leverage recent advances in network control theory to establish that structural brain networks evolve in adolescence to lower the energetic cost of activating the frontoparietal system. Our results suggest a new mechanistic framework for understanding how brain network maturation supports cognition, with clear implications for disorders marked by executive dysfunction, such as ADHD and psychosis.

neuroscience↗

bioRxiv2018

Structural differences between pri-miRNA paralogs promotes alternative Drosha cleavage and expands target repertoires

MicroRNA (miRNA) processing begins with Drosha cleavage, the fidelity of which is critical for downstream processing and mature miRNA target specificity. To understand how pri-miRNA sequence and structure influence Drosha cleavage, we studied the maturation of three pri-miR-9 paralogs, which encode the same mature miRNA but differ in the surrounding scaffold. We show that pri-miR-9-1 has a unique Drosha cleavage profile due to its distorted and flexible stem structure. Cleavage of pri-miR-9-1, but not pri-miR-9-2 or pri-miR-9-3, generates an alternative-miR-9 with a shifted seed sequence that expands the scope of its target RNAs. Analyses of low grade glioma patient samples indicate that the alternative-miR-9 plays a distinct role in preventing tumor progression. To generalize our model, we provide evidence that distortion of pri-miRNA stems correlates with Drosha cleavage at non-canonical sites. Our studies reveal that pri-miRNA paralogs can have distinct functions via differential Drosha processing.

molecular biology↗

bioRxiv2018

Unsupervised discovery of temporal sequences in high-dimensional datasets, with applications to neuroscience

Identifying low-dimensional features that describe large-scale neural recordings is a major challenge in neuroscience. Repeated temporal patterns (sequences) are thought to be a salient feature of neural dynamics, but are not succinctly captured by traditional dimensionality reduction techniques. Here we describe a software toolbox--called seqNMF--with new methods for extracting informative, non-redundant, sequences from high-dimensional neural data, testing the significance of these extracted patterns, and assessing the prevalence of sequential structure in data. We test these methods on simulated data under multiple noise conditions, and on several real neural and behavioral data sets. In hippocampal data, seqNMF identifies neural sequences that match those calculated manually by reference to behavioral events. In songbird data, seqNMF discovers neural sequences in untutored birds that lack stereotyped songs. Thus, by identifying temporal structure directly from neural data, seqNMF enables dissection of complex neural circuits without relying on temporal references from stimuli or behavioral outputs.

neuroscience↗

bioRxiv2018

Caenorhabditis elegans heterochromatin factor SET-32 plays an essential role in transgenerational establishment of nuclear RNAi-mediated epigenetic silencing

Epigenetic inheritance contributes fundamentally to transgenerational physiology and fitness. Mechanistic understanding of RNA-mediated chromatin modification and transgenerational epigenetic inheritance, which in C. elegans can be triggered by exogenous double-stranded RNA (exo-dsRNA) or facilitated by endogenous small interfering RNAs (endo-siRNAs), has mainly been limited to the post-initiation phases of silencing. Indeed, the dynamic process by which nuclear RNAi engages a transcriptionally active target, before the repressive state is stably established, remains largely a mystery. Here we found that the onset of exo-dsRNA-induced nuclear RNAi is a transgenerational process, and that establishment requires SET-32, one of the three putative histone methyltransferases (HMTs) that are required for H3K9me3 deposition at the nuclear RNAi targets. We also performed multigenerational whole-genome analyses to examine the establishment of silencing at endogenous targets of germline nuclear RNAi. The nuclear Argonaute protein HRDE-1 is essential for the maintenance of nuclear RNAi. Repairing a loss-of-function mutation in hrde-1 by CRISPR restored the silencing of endogenous targets in animals carrying wild type set-32. However, for numerous endogenous targets, repairing the hrde-1 mutation in a set-32;hrde-1 double mutant failed to restore their silencing states in up to 20 generations after the hrde-1 repair, using a similar genome editing approach. We found that despite a prominent role in the establishment of silencing, however, set-32 is completely dispensable for the maintenance of silencing once HRDE-1-dependent gene repression is established. Our study indicates that: 1) establishment and maintenance of siRNA-guided transcriptional repression are two distinct processes with different genetic requirements; and 2) the rate-limiting step of the establishment phase is a transgenerational, chromatin-based process. In addition, our study reveals a novel paradigm in which a heterochromatin factor primarily functions to promote the establishment of transgenerational silencing, expanding mechanistic understanding of the well-recognized role of heterochromatin in epigenetic maintenance.

molecular biology↗

bioRxiv2017

Tellurium Notebooks - An Environment for Dynamical Model Development, Reproducibility, and Reuse

The considerable difficulty encountered in reproducing the results of published dynamical models limits validation, exploration and reuse of this increasingly large biomedical research resource. To address this problem, we have developed Tellurium Notebook, a software system that facilitates building reproducible dynamical models and reusing models by 1) supporting the COMBINE archive format during model development for capturing model information in an exchangeable format and 2) enabling users to easily simulate and edit public COMBINE-compliant models from public repositories to facilitate studying model dynamics, variants and test cases. Tellurium Notebook, a Python-based Jupyter-like environment, is designed to seamlessly inter-operate with these community standards by automating conversion between COMBINE standards formulations and corresponding in-line, human-readable representations. Thus, Tellurium brings to systems biology the strategy used by other literate notebook systems such as Mathematica. These capabilities allow users to edit every aspect of the standards-compliant models and simulations, run the simulations in-line, and re-export to standard formats. We provide several use cases illustrating the advantages of our approach and how it allows development and reuse of models without requiring technical knowledge of standards. Adoption of Tellurium should accelerate model development, reproducibility and reuse.\n\nAuthor summaryThere is considerable value to systems and synthetic biology in creating reproducible models. An essential element of reproducibility is the use of community standards, an often challenging undertaking for modelers. This article describes Tellurium Notebook, a tool for developing dynamical models that provides an intuitive approach to building and reusing models built with community standards. Tellurium automates embedding human-readable representations of COMBINE archives in literate coding notebooks, bringing to systems biology this strategy central to other literate notebook systems such as Mathematica. We show that the ability to easily edit this human-readable representation enables users to test models under a variety of conditions, thereby providing a way to create, reuse, and modify standard-encoded models and simulations, regardless of the users level of technical knowledge of said standards.

systems biology↗

bioRxiv2017

Linked dimensions of psychopathology and connectivity in functional brain networks

Neurobiological abnormalities associated with psychiatric disorders do not map well to existing diagnostic categories. High co-morbidity and overlapping symptom domains suggest dimensional circuit-level abnormalities that cut across clinical diagnoses. Here we sought to identify brain-based dimensions of psychopathology using multivariate sparse canonical correlation analysis (sCCA) in a sample of 663 youths imaged as part of the Philadelphia Neurodevelopmental Cohort. This analysis revealed highly correlated patterns of functional connectivity and psychiatric symptoms. We found that four dimensions of psychopathology -- mood, psychosis, fear, and externalizing behavior -- were highly associated (r=0.68-0.71) with distinct patterns of functional dysconnectivity. Loss of network segregation between the default mode network and executive networks (e.g. fronto-parietal and salience) emerged as a common feature across all dimensions. Connectivity patterns linked to mood and psychosis became more prominent with development, and significant sex differences were present for connectivity patterns related to mood and fear. Critically, findings replicated in an independent dataset (n=336). These results delineate connectivity-guided dimensions of psychopathology that cut across traditional diagnostic categories, which could serve as a foundation for developing network-based biomarkers in psychiatry.

neuroscience↗

bioRxiv2017

SHP2 Is Required for BCR-ABL1-Induced Hematologic Neoplasms

BCR-ABL1-targeting tyrosine kinase inhibitors (TKIs) have revolutionized treatment of Philadelphia chromosome-positive (Ph+) hematologic neoplasms. Nevertheless, acquired TKI resistance remains a major problem in chronic myeloid leukemia (CML), and TKIs are less effective against Ph+ B-cell acute lymphoblastic leukemia (B-ALL). GAB2, a scaffolding adaptor that binds and activates SHP2, is essential for leukemogenesis by BCR-ABL1, and a GAB2 mutant lacking SHP2 binding cannot mediate leukemogenesis. Using a genetic loss-of-function approach and bone marrow transplantation (BMT) models for CML and BCR-ABL1+ B-ALL, we show that SHP2 is required for BCR-ABL1-evoked myeloid and lymphoid neoplasia. Ptpn11 deletion impairs initiation and maintenance of CML-like myeloproliferative neoplasm, and compromises induction of BCR-ABL1+ B-ALL. SHP2, and specifically, its SH2 domains, PTP activity and C-terminal tyrosines, is essential for BCR-ABL1+, but not WT, pre-B cell proliferation. The MEK/ERK pathway is regulated by SHP2 in WT and BCR-ABL1+ pre-B cells, but is only required for the proliferation of BCR-ABL1+ cells. SHP2 is required for SRC family kinase (SFK) activation only in BCR-ABL1+ pre-B cells. RNAseq reveals distinct SHP2-dependent transcriptional programs in BCR-ABL1+ and WT pre-B cells. Our results suggest that SHP2, via SFKs and ERK, represses MXD3/4 to facilitate a MYC-dependent proliferation program in BCR-ABL1-transformed pre-B cells.

cancer biology↗

bioRxiv2016

Detecting hierarchical 3-D genome domain reconfiguration with network modularity

Mammalian genomes are folded in a hierarchy of topologically associating domains (TADs), subTADs and looping interactions. The nested nature of chromatin domains has rendered it challenging to identify a sensitive and specific metric for detecting subTADs and quantifying their dynamic reconfiguration across cellular states. Here, we apply graph theoretic principles to quantify hierarchical folding patterns in high-resolution chromatin topology maps. We discover that TADs can be accurately detected using a Louvain-like locally greedy algorithm to maximize network modularity. By varying a resolution parameter in the modularity quality function, we accurately partition the mouse genome across length scales into a hierarchical nested structure of network communities exhibiting a wide range of sizes. To distinguish high probability subTADs from the full detected set, we developed and applied a new hierarchical spatial variance minimization method. Moreover, we identified a large number of dynamically altered communities between pluripotent embryonic stem cells and multipotent neural progenitor cells. Cell type specific boundaries correlate with trends in dynamic occupancy of the architectural protein CTCF, thereby validating their biological relevance. Together, these data demonstrate the utility of metrics from network science in quantifying a nested hierarchy of dynamic 3D chromatin communities across length scales. Our findings are significant toward unraveling the link between higher-order genome folding and gene expression during healthy development and the deregulation of molecular pathways linked to disease.

genomics↗