<mods:mods xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-7.xsd"><mods:titleInfo><mods:title>Reverse-Engineering the Sea Urchin: Uncovering Network Mechanisms of Differentiation Through Single-Cell Transcriptomics</mods:title></mods:titleInfo><mods:abstract>Reverse engineering is described as extracting complexities without a-priori knowledge. Biological organisms are complex and contain many regulatory elements that control defined processes such as the cell cycle, morphogenesis, and cellular differentiation. Temporal and spatial regulation of gene expression is important to describe potential models for the differentiated cell lineages. Through a reverse engineering approach, this project aims to construct gene regulatory networks depicting important cellular differentiation events in sea urchin embryogenesis through scRNA-seq data. &#13;
&#13;
Available scRNA-seq data of the sea urchin embryo from Foster et al., 2020 was used to develop gene regulatory networks driving differentiation of important cell lineages such as pigment vs blastocoel cells, primary mesenchyme vs secondary mesenchyme cells, etc. The scRNA-seq data covered eight time points in sea urchin embryogenesis, 8-cell to late gastrula stage. scRNA-seq data was clustered into cell lineages through semi-supervised algorithms using marker gene expression and neighboring non-marker gene expression levels. Trajectory inference was performed on sets of cell lineages to depict the start, decision, and endpoints of a particular topology (linear, bifurcation, tree, etc.). Differentially expressed genes along multiple lineages were characterized by their pattern of expression and potential to be a driver of differentiation. Network analysis was performed on the differentially expressed set of genes to detail networks specific to each cell lineage and find possible subnetworks that describe decision points in differentiation. &#13;
&#13;
Through this process, gene regulatory networks were constructed describing both the differentiation of cell lineages and cell lineage-specific regulation. These constructed networks can be used to assess perturbations that can lead to failure to differentiate, developmental delays, gastrulation failure, etc. Through these computational results, experimental tests involving the knockdown of genes and validation of localization of genes through whole-mount in-situ hybridization can be performed.</mods:abstract><mods:name type="personal"><mods:namePart>Isaac, Shakson</mods:namePart><mods:role><mods:roleTerm type="text">creator</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart>Subramanian, Mahadevan</mods:namePart><mods:role><mods:roleTerm type="text">creator</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart>Yajima, Mamiko</mods:namePart><mods:role><mods:roleTerm type="text">advisor</mods:roleTerm></mods:role><mods:affiliation>Brown University. Molecular Biology, Cell Biology, &amp; Biochemistry</mods:affiliation></mods:name><mods:name type="corporate"><mods:namePart>Brown University. Karen T. Romer Undergraduate Teaching and Research Awards</mods:namePart><mods:role><mods:roleTerm type="text">research program</mods:roleTerm></mods:role></mods:name><mods:subject authority="fast" authorityURI="http://id.worldcat.org/fast" valueURI="http://id.worldcat.org/fast/00832383"><mods:topic>Biology</mods:topic></mods:subject><mods:subject authority="fast" authorityURI="http://id.worldcat.org/fast" valueURI="http://id.worldcat.org/fast/00871990"><mods:topic>Computational biology</mods:topic></mods:subject><mods:subject authority="fast" authorityURI="http://id.worldcat.org/fast" valueURI="http://id.worldcat.org/fast/00939613"><mods:topic>Gene expression</mods:topic></mods:subject><mods:subject authority="fast" authorityURI="http://id.worldcat.org/fast" valueURI="http://id.worldcat.org/fast/01893891"><mods:topic>Gene regulatory networks</mods:topic></mods:subject><mods:subject authority="fast" authorityURI="http://id.worldcat.org/fast" valueURI="http://id.worldcat.org/fast/00850182"><mods:topic>Cell differentiation</mods:topic></mods:subject><mods:language><mods:languageTerm type="text" authority="iso639-2b">English</mods:languageTerm></mods:language><mods:typeOfResource authority="primo">text_resources</mods:typeOfResource><mods:genre authority="aat">posters</mods:genre><mods:originInfo><mods:place><mods:placeTerm type="code" authority="marccountry">riu</mods:placeTerm></mods:place><mods:place><mods:placeTerm type="text">Providence, RI</mods:placeTerm></mods:place><mods:publisher>Brown University</mods:publisher><mods:dateCreated keyDate="yes" encoding="w3cdtf">2021</mods:dateCreated></mods:originInfo><mods:physicalDescription><mods:extent>1 poster</mods:extent><mods:digitalOrigin>born digital</mods:digitalOrigin></mods:physicalDescription><mods:accessCondition type="use and reproduction">All rights reserved</mods:accessCondition><mods:accessCondition type="rights statement" xlink:href="http://rightsstatements.org/vocab/InC/1.0/">In Copyright</mods:accessCondition><mods:accessCondition type="restriction on access">All Rights Reserved</mods:accessCondition><mods:identifier type="doi">10.26300/v3n8-z948</mods:identifier></mods:mods>