scholarly journals Automated high-throughput registration for localizing 3D mouse brain gene expression using ITK

2005 ◽  
Author(s):  
Lydia Ng ◽  
Michael Hawrylycz ◽  
David Haynor
Keyword(s):  
Gene Expression ◽  
Mouse Brain ◽  
High Throughput ◽  
Image Data ◽  
Brain Structures ◽  
Brain Atlas ◽  
The Public ◽  
Brain Gene Expression ◽  
Genome Wide ◽  
Registration Scheme

The Allen Brain Atlas (ABA) project aims to create a cellular-resolution, genome-wide map of gene expression in the adult mouse brain. The resulting in situ hybridization (ISH) image data will be available free-of-charge to the public. Additionally, we are developing an informatics pipeline to support searching of the data by anatomic region and expression level and/or pattern. This paper describes a robust, high-throughput registration scheme to automatically annotate hierarchical brain structures in the ISH imagery.

scholarly journals Supervised Learning With Perceptual Similarity for Multimodal Gene Expression Registration of a Mouse Brain Atlas

2021 ◽  
Vol 15 ◽  
Author(s):  
Jan Krepl ◽  
Francesco Casalegno ◽  
Emilie Delattre ◽  
Csaba Erö ◽  
Huanxiang Lu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Supervised Learning ◽  
Mouse Brain ◽  
Brain Structures ◽  
Brain Atlas ◽  
Perceptual Similarity ◽  
Gene Expressions ◽  
Individual Gene ◽  
Staining Techniques ◽  
Quality Maps

The acquisition of high quality maps of gene expression in the rodent brain is of fundamental importance to the neuroscience community. The generation of such datasets relies on registering individual gene expression images to a reference volume, a task encumbered by the diversity of staining techniques employed, and by deformations and artifacts in the soft tissue. Recently, deep learning models have garnered particular interest as a viable alternative to traditional intensity-based algorithms for image registration. In this work, we propose a supervised learning model for general multimodal 2D registration tasks, trained with a perceptual similarity loss on a dataset labeled by a human expert and augmented by synthetic local deformations. We demonstrate the results of our approach on the Allen Mouse Brain Atlas (AMBA), comprising whole brain Nissl and gene expression stains. We show that our framework and design of the loss function result in accurate and smooth predictions. Our model is able to generalize to unseen gene expressions and coronal sections, outperforming traditional intensity-based approaches in aligning complex brain structures.

scholarly journals Cross-species alcohol dependence-associated gene networks: Co-analysis of mouse brain gene expression and human genome-wide association data

PLoS ONE ◽  
2019 ◽  
Vol 14 (4) ◽  
pp. e0202063 ◽  
Author(s):  
Kristin M. Mignogna ◽  
Silviu A. Bacanu ◽  
Brien P. Riley ◽  
Aaron R. Wolen ◽  
Michael F. Miles
Keyword(s):  
Gene Expression ◽  
Alcohol Dependence ◽  
Human Genome ◽  
Mouse Brain ◽  
Gene Networks ◽  
Genome Wide Association ◽  
Brain Gene Expression ◽  
Genome Wide ◽  
Association Data

scholarly journals Homologous laminar organization of the mouse and human subiculum

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Michael S. Bienkowski ◽  
Farshid Sepehrband ◽  
Nyoman D. Kurniawan ◽  
Jim Stanis ◽  
Laura Korobkova ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hippocampal Formation ◽  
Expression Patterns ◽  
Pyramidal Cells ◽  
Brain Structures ◽  
Longitudinal Axis ◽  
Brain Atlas ◽  
Fiber Density ◽  
Laminar Organization ◽  
Hybridization Data

AbstractThe subiculum is the major output component of the hippocampal formation and one of the major brain structures most affected by Alzheimer’s disease. Our previous work revealed a hidden laminar architecture within the mouse subiculum. However, the rotation of the hippocampal longitudinal axis across species makes it unclear how the laminar organization is represented in human subiculum. Using in situ hybridization data from the Allen Human Brain Atlas, we demonstrate that the human subiculum also contains complementary laminar gene expression patterns similar to the mouse. In addition, we provide evidence that the molecular domain boundaries in human subiculum correspond to microstructural differences observed in high resolution MRI and fiber density imaging. Finally, we show both similarities and differences in the gene expression profile of subiculum pyramidal cells within homologous lamina. Overall, we present a new 3D model of the anatomical organization of human subiculum and its evolution from the mouse.

scholarly journals Flexible annotation atlas of the mouse brain: combining and dividing brain structures of the Allen Brain Atlas while maintaining anatomical hierarchy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Norio Takata ◽  
Nobuhiko Sato ◽  
Yuji Komaki ◽  
Hideyuki Okano ◽  
Kenji F. Tanaka
Keyword(s):  
Mouse Brain ◽  
Brain Structures ◽  
Brain Atlas ◽  
Resting State Functional Connectivity ◽  
Brain Science ◽  
Step Procedure ◽  
Public Resources ◽  
Large Brain ◽  
Magnetic Resonance Imaging Mri ◽  
And Function

AbstractA brain atlas is necessary for analyzing structure and function in neuroimaging research. Although various annotation volumes (AVs) for the mouse brain have been proposed, it is common in magnetic resonance imaging (MRI) of the mouse brain that regions-of-interest (ROIs) for brain structures (nodes) are created arbitrarily according to each researcher’s necessity, leading to inconsistent ROIs among studies. One reason for such a situation is the fact that earlier AVs were fixed, i.e. combination and division of nodes were not implemented. This report presents a pipeline for constructing a flexible annotation atlas (FAA) of the mouse brain by leveraging public resources of the Allen Institute for Brain Science on brain structure, gene expression, and axonal projection. A mere two-step procedure with user-specified, text-based information and Python codes constructs FAA with nodes which can be combined or divided objectively while maintaining anatomical hierarchy of brain structures. Four FAAs with total node count of 4, 101, 866, and 1381 were demonstrated. Unique characteristics of FAA realized analysis of resting-state functional connectivity (FC) across the anatomical hierarchy and among cortical layers, which were thin but large brain structures. FAA can improve the consistency of whole brain ROI definition among laboratories by fulfilling various requests from researchers with its flexibility and reproducibility.

scholarly journals Behavior-dependent cis regulation reveals genes and pathways associated with bower building in cichlid fishes

2018 ◽  
Vol 115 (47) ◽  
pp. E11081-E11090 ◽  
Author(s):  
Ryan A. York ◽  
Chinar Patil ◽  
Kawther Abdilleh ◽  
Zachary V. Johnson ◽  
Matthew A. Conte ◽  
...  
Keyword(s):  
Gene Expression ◽  
Neural Plasticity ◽  
Genetic Basis ◽  
Specific Expression ◽  
Preferential Expression ◽  
Cichlid Fishes ◽  
Brain Gene Expression ◽  
Genome Wide ◽  
Allele Specific ◽  
Genomic Regions

Many behaviors are associated with heritable genetic variation [Kendler and Greenspan (2006) Am J Psychiatry 163:1683–1694]. Genetic mapping has revealed genomic regions or, in a few cases, specific genes explaining part of this variation [Bendesky and Bargmann (2011) Nat Rev Gen 12:809–820]. However, the genetic basis of behavioral evolution remains unclear. Here we investigate the evolution of an innate extended phenotype, bower building, among cichlid fishes of Lake Malawi. Males build bowers of two types, pits or castles, to attract females for mating. We performed comparative genome-wide analyses of 20 bower-building species and found that these phenotypes have evolved multiple times with thousands of genetic variants strongly associated with this behavior, suggesting a polygenic architecture. Remarkably, F1 hybrids of a pit-digging and a castle-building species perform sequential construction of first a pit and then a castle bower. Analysis of brain gene expression in these hybrids showed that genes near behavior-associated variants display behavior-dependent allele-specific expression with preferential expression of the pit-digging species allele during pit digging and of the castle-building species allele during castle building. These genes are highly enriched for functions related to neurodevelopment and neural plasticity. Our results suggest that natural behaviors are associated with complex genetic architectures that alter behavior via cis-regulatory differences whose effects on gene expression are specific to the behavior itself.

Investigation of Different Transcript Quantitation Tools for High-Throughput Mapping of Brain Gene Expression Using Voxelation

2003 ◽  
Vol 35 (4) ◽  
pp. 397-402 ◽  
Author(s):  
Ram P. Singh ◽  
Dahai Liu ◽  
Abhijit Chaudhari ◽  
Simon R. Cherry ◽  
Richard M. Leahy ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Throughput ◽  
Brain Gene Expression

P1-229: Genome-Wide Association Study of Brain Gene Expression Levels (eGWAS)

2011 ◽  
Vol 7 ◽  
pp. S184-S184
Author(s):  
Nilufer Ertekin-Taner ◽  
Fanggeng Zou ◽  
High Chai ◽  
Curtis Younkin ◽  
Julia Crook ◽  
...  
Keyword(s):  
Gene Expression ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Expression Levels ◽  
Brain Gene Expression ◽  
Genome Wide ◽  
Gene Expression Levels

scholarly journals Cross-species alcohol dependence-associated gene networks: Co-analysis of mouse brain gene expression and human genome-wide association data

2018 ◽  
Author(s):  
Kristin M. Mignogna ◽  
Silviu A. Bacanu ◽  
Brien P. Riley ◽  
Aaron R. Wolen ◽  
Michael F. Miles
Keyword(s):  
Gene Expression ◽  
Alcohol Dependence ◽  
Mouse Brain ◽  
Gene Networks ◽  
Association Studies ◽  
Complex Trait ◽  
Genome Wide Association ◽  
Model Organisms ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractGenome-wide association studies on alcohol dependence, by themselves, have yet to account for the estimated heritability of the disorder and provide incomplete mechanistic understanding of this complex trait. Integrating brain ethanol-responsive gene expression networks from model organisms with human genetic data on alcohol dependence could aid in identifying dependence-associated genes and functional networks in which they are involved. This study used a modification of the Edge-Weighted Dense Module Searching for genome-wide association studies (EW-dmGWAS) approach to co-analyze whole-genome gene expression data from ethanol-exposed mouse brain tissue, human protein-protein interaction databases and alcohol dependence-related genome-wide association studies. Results revealed novel ethanol-regulated and alcohol dependence-associated gene networks in prefrontal cortex, nucleus accumbens, and ventral tegmental area. Three of these networks were overrepresented with genome-wide association signals from an independent dataset. These networks were significantly overrepresented for gene ontology categories involving several mechanisms, including actin filament-based activity, transcript regulation, Wnt and Syndecan-mediated signaling, and ubiquitination. Together, these studies provide novel insight for brain mechanisms contributing to alcohol dependence.

scholarly journals A Gene Expression High-Throughput Screen (GE-HTS) for Coordinated Detection of Functionally Similar Effectors in Cancer

Cancers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3143
Author(s):  
Chaitra Rao ◽  
Dianna H. Huisman ◽  
Heidi M. Vieira ◽  
Danielle E. Frodyma ◽  
Beth K. Neilsen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Natural Products ◽  
High Throughput ◽  
High Throughput Screening ◽  
Loss Of Function ◽  
Synthetic Lethal ◽  
Genome Wide ◽  
Pathway Activation ◽  
Kinase Suppressor Of Ras ◽  
Kinase Cascade

Genome-wide, loss-of-function screening can be used to identify novel vulnerabilities upon which specific tumor cells depend for survival. Functional Signature Ontology (FUSION) is a gene expression-based high-throughput screening (GE-HTS) method that allows researchers to identify functionally similar proteins, small molecules, and microRNA mimics, revealing novel therapeutic targets. FUSION uses cell-based high-throughput screening and computational analysis to match gene expression signatures produced by natural products to those produced by small interfering RNA (siRNA) and synthetic microRNA libraries to identify putative protein targets and mechanisms of action (MoA) for several previously undescribed natural products. We have used FUSION to screen for functional analogues to Kinase suppressor of Ras 1 (KSR1), a scaffold protein downstream of Ras in the Raf-MEK-ERK kinase cascade, and biologically validated several proteins with functional similarity to KSR1. FUSION incorporates bioinformatics analysis that may offer higher resolution of the endpoint readout than other screens which utilize Boolean outputs regarding a single pathway activation (i.e., synthetic lethal and cell proliferation). Challenges associated with FUSION and other high-content genome-wide screens include variation, batch effects, and controlling for potential off-target effects. In this review, we discuss the efficacy of FUSION to identify novel inhibitors and oncogene-induced changes that may be cancer cell-specific as well as several potential pitfalls within FUSION and best practices to avoid them.

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