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Ramanathan, Sharad

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Ramanathan

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Sharad

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Ramanathan, Sharad
Author's Publications: search.filters.isAuthorOfPublication.48e6edb9-c395-4121-bdc4-088c9a96d03a

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Now showing 1 - 6 of 6
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    Controlling Interneuron Activity in Caenorhabditis Elegans to Evoke Chemotactic Behaviour
    (Nature Publishing Group, 2012) Kocabas, Askin; Shen, Ching-Han; Guo, Zengcai V.; Ramanathan, Sharad
    Animals locate and track chemoattractive gradients in the environment to find food. With its small nervous system, Caenorhabditis elegans is a good model system in which to understand how the dynamics of neural activity control this search behaviour. Extensive work on the nematode has identified the neurons that are necessary for the different locomotory behaviours underlying chemotaxis through the use of laser ablation, activity recording in immobilized animals and the study of mutants. However, we do not know the neural activity patterns in C. elegans that are sufficient to control its complex chemotactic behaviour. To understand how the activity in its interneurons coordinate different motor programs to lead the animal to food, here we used optogenetics and new optical tools to manipulate neural activity directly in freely moving animals to evoke chemotactic behaviour. By deducing the classes of activity patterns triggered during chemotaxis and exciting individual neurons with these patterns, we identified interneurons that control the essential locomotory programs for this behaviour. Notably, we discovered that controlling the dynamics of activity in just one interneuron pair (AIY) was sufficient to force the animal to locate, turn towards and track virtual light gradients. Two distinct activity patterns triggered in AIY as the animal moved through the gradient controlled reversals and gradual turns to drive chemotactic behaviour. Because AIY neurons are post-synaptic to most chemosensory and thermosensory neurons, it is probable that these activity patterns in AIY have an important role in controlling and coordinating different taxis behaviours of the animal.
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    Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states
    (eLife Sciences Publications, Ltd, 2017) Jang, Sumin; Choubey, Sandeep; Furchtgott, Leon; Zou, Ling-Nan; Doyle, Adele; Menon, Vilas; Loew, Ethan B; Krostag, Anne-Rachel; Martinez, Refugio A; Madisen, Linda; Levi, Boaz P; Ramanathan, Sharad
    The complexity of gene regulatory networks that lead multipotent cells to acquire different cell fates makes a quantitative understanding of differentiation challenging. Using a statistical framework to analyze single-cell transcriptomics data, we infer the gene expression dynamics of early mouse embryonic stem (mES) cell differentiation, uncovering discrete transitions across nine cell states. We validate the predicted transitions across discrete states using flow cytometry. Moreover, using live-cell microscopy, we show that individual cells undergo abrupt transitions from a naïve to primed pluripotent state. Using the inferred discrete cell states to build a probabilistic model for the underlying gene regulatory network, we further predict and experimentally verify that these states have unique response to perturbations, thus defining them functionally. Our study provides a framework to infer the dynamics of differentiation from single cell transcriptomics data and to build predictive models of the gene regulatory networks that drive the sequence of cell fate decisions during development. DOI: http://dx.doi.org/10.7554/eLife.20487.001
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    Discovering sparse transcription factor codes for cell states and state transitions during development
    (eLife Sciences Publications, Ltd, 2017) Furchtgott, Leon; Melton, Samuel; Menon, Vilas; Ramanathan, Sharad
    Computational analysis of gene expression to determine both the sequence of lineage choices made by multipotent cells and to identify the genes influencing these decisions is challenging. Here we discover a pattern in the expression levels of a sparse subset of genes among cell types in B- and T-cell developmental lineages that correlates with developmental topologies. We develop a statistical framework using this pattern to simultaneously infer lineage transitions and the genes that determine these relationships. We use this technique to reconstruct the early hematopoietic and intestinal developmental trees. We extend this framework to analyze single-cell RNA-seq data from early human cortical development, inferring a neocortical-hindbrain split in early progenitor cells and the key genes that could control this lineage decision. Our work allows us to simultaneously infer both the identity and lineage of cell types as well as a small set of key genes whose expression patterns reflect these relationships. DOI: http://dx.doi.org/10.7554/eLife.20488.001
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    Fixed single-cell transcriptomic characterization of human radial glial diversity
    (2016) Thomsen, Elliot R.; Mich, John K.; Yao, Zizhen; Hodge, Rebecca D.; Doyle, Adele M.; Jang, Sumin; Shehata, Soraya I.; Nelson, Angelique M.; Shapovalova, Nadiya V.; Levi, Boaz P.; Ramanathan, Sharad
    The human neocortex is created from diverse intermixed progenitors in the prenatal germinal zones. These progenitors have been difficult to characterize since progenitors—particularly radial glia (RG)—are rare, and are defined by a combination of intracellular markers, position and morphology. To circumvent these problems we developed a method called FRISCR for transcriptome profiling of individual fixed, stained and sorted cells. After validation of FRISCR using human embryonic stem cells, we profiled primary human RG that constitute only 1% of the mid-gestation cortex. These RG could be classified into ventricular zone-enriched RG (vRG) that express ANXA1 and CRYAB, and outer subventricular zone-localized RG (oRG) that express HOPX. Our study identifies the first markers and molecular profiles of vRG and oRG cells, and provides an essential step for understanding molecular networks driving the lineage of human neocortical progenitors. Furthermore, FRISCR allows targeted single-cell transcriptomic profiling of tissues that lack live-cell markers.
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    A Single-Cell Roadmap of Lineage Bifurcation in Human ESC Models of Embryonic Brain Development
    (Elsevier BV, 2017-01) Yao, Zizhen; Mich, John; Ku, Sherman; Menon, Vilas; Krostag, Anne-Rachel; Martinez, Refugio A.; Furchtgott, Leon; Mulholland, Heather; Bort, Susan; Fuqua, Margaret; Gregor, Ben; Hodge, Rebecca; Jayabalu, Anu; May, Ryan; Melton, Samuel; Nelson, Angelique; Ngo, N. Kiet; Shapovalova, Nadiya; Shehata, Soraya; Smith, Michael; Tait, Leah; Thompson, Carol; Thomsen, Elliot; Ye, Chaoyang; Glass, Ian; Kaykas, Ajamete; Yao, Shuyuan; Phillips, John; Grimley, Joshua; Levi, Boaz; Wang, Yanling; Ramanathan, Sharad
    During human brain development, multiple signaling pathways generate diverse cell types with varied regional identities. Here, we integrate single-cell RNA sequencing and clonal analyses to reveal lineage trees and molecular signals underlying early forebrain and mid/hindbrain cell differentiation from human embryonic stem cells (hESCs). Clustering single-cell transcriptomic data identified 41 distinct populations of progenitor, neuronal, and non-neural cells across our differentiation time course. Comparisons with primary mouse and human gene expression data demonstrated rostral and caudal progenitor and neuronal identities from early brain development. Bayesian analyses inferred a unified cell-type lineage tree that bifurcates between cortical and mid/hindbrain cell types. Two methods of clonal analyses confirmed these findings and further revealed the importance of Wnt/β-catenin signaling in controlling this lineage decision. Together, these findings provide a rich transcriptome-based lineage map for studying human brain development and modeling developmental disorders.
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    A Compressed Sensing Framework for Efficient Dissection of Neural Circuits
    (Springer Nature, 2018-12-20) Lee, Jeffrey B.; Yonar, Abdullah; Hallacy, Timothy; Shen, Ching-Han; Milloz, Josselin; Srinivasan, Jagan; Kocabas, Askin; Ramanathan, Sharad
    A fundamental question in neuroscience is how neural networks generate behavior. The lack of genetic tools and unique promoters to functionally manipulate specific neuronal subtypes makes it challenging to determine the roles of individual subtypes in behavior. We describe a compressed sensing-based framework in combination with non-specific genetic tools to infer candidate neurons controlling behaviors with fewer measurements than previously thought possible. We tested this framework by inferring interneuron subtypes regulating the speed of locomotion of the nematode Caenorhabditis elegans. We developed a real-time stabilization microscope for accurate long-term, high-magnification imaging and targeted perturbation of neural activity in freely moving animals to validate our inferences. We show that a circuit of three interconnected interneuron subtypes, RMG, AVB and SIA control different aspects of locomotion speed as the animal navigates its environment. Our work suggests that compressed sensing approaches can be used to identify key nodes in complex biological networks.