Biology subjects

Gu, S.

Publications and source records attributed to Gu, S..

8 recordsLinked to original sources

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↗