12 research outputs found
DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders
This paper presents a novel deep learning-based method for learning a
functional representation of mammalian neural images. The method uses a deep
convolutional denoising autoencoder (CDAE) for generating an invariant, compact
representation of in situ hybridization (ISH) images. While most existing
methods for bio-imaging analysis were not developed to handle images with
highly complex anatomical structures, the results presented in this paper show
that functional representation extracted by CDAE can help learn features of
functional gene ontology categories for their classification in a highly
accurate manner. Using this CDAE representation, our method outperforms the
previous state-of-the-art classification rate, by improving the average AUC
from 0.92 to 0.98, i.e., achieving 75% reduction in error. The method operates
on input images that were downsampled significantly with respect to the
original ones to make it computationally feasible
Discovering Neuronal Cell Types and Their Gene Expression Profiles Using a Spatial Point Process Mixture Model
Cataloging the neuronal cell types that comprise circuitry of individual
brain regions is a major goal of modern neuroscience and the BRAIN initiative.
Single-cell RNA sequencing can now be used to measure the gene expression
profiles of individual neurons and to categorize neurons based on their gene
expression profiles. While the single-cell techniques are extremely powerful
and hold great promise, they are currently still labor intensive, have a high
cost per cell, and, most importantly, do not provide information on spatial
distribution of cell types in specific regions of the brain. We propose a
complementary approach that uses computational methods to infer the cell types
and their gene expression profiles through analysis of brain-wide single-cell
resolution in situ hybridization (ISH) imagery contained in the Allen Brain
Atlas (ABA). We measure the spatial distribution of neurons labeled in the ISH
image for each gene and model it as a spatial point process mixture, whose
mixture weights are given by the cell types which express that gene. By fitting
a point process mixture model jointly to the ISH images, we infer both the
spatial point process distribution for each cell type and their gene expression
profile. We validate our predictions of cell type-specific gene expression
profiles using single cell RNA sequencing data, recently published for the
mouse somatosensory cortex. Jointly with the gene expression profiles, cell
features such as cell size, orientation, intensity and local density level are
inferred per cell type
Computational neuroanatomy and co-expression of genes in the adult mouse brain, analysis tools for the Allen Brain Atlas
We review quantitative methods and software developed to analyze
genome-scale, brain-wide spatially-mapped gene-expression data. We expose new
methods based on the underlying high-dimensional geometry of voxel space and
gene space, and on simulations of the distribution of co-expression networks of
a given size. We apply them to the Allen Atlas of the adult mouse brain, and to
the co-expression network of a set of genes related to nicotine addiction
retrieved from the NicSNP database. The computational methods are implemented
in {\ttfamily{BrainGeneExpressionAnalysis}}, a Matlab toolbox available for
download.Comment: 25 pages, 8 figures, accepted in Quantitative Biology (2012) 000
Evidence for the role of EPHX2 gene variants in anorexia nervosa.
Anorexia nervosa (AN) and related eating disorders are complex, multifactorial neuropsychiatric conditions with likely rare and common genetic and environmental determinants. To identify genetic variants associated with AN, we pursued a series of sequencing and genotyping studies focusing on the coding regions and upstream sequence of 152 candidate genes in a total of 1205 AN cases and 1948 controls. We identified individual variant associations in the Estrogen Receptor-ß (ESR2) gene, as well as a set of rare and common variants in the Epoxide Hydrolase 2 (EPHX2) gene, in an initial sequencing study of 261 early-onset severe AN cases and 73 controls (P=0.0004). The association of EPHX2 variants was further delineated in: (1) a pooling-based replication study involving an additional 500 AN patients and 500 controls (replication set P=0.00000016); (2) single-locus studies in a cohort of 386 previously genotyped broadly defined AN cases and 295 female population controls from the Bogalusa Heart Study (BHS) and a cohort of 58 individuals with self-reported eating disturbances and 851 controls (combined smallest single locus P<0.01). As EPHX2 is known to influence cholesterol metabolism, and AN is often associated with elevated cholesterol levels, we also investigated the association of EPHX2 variants and longitudinal body mass index (BMI) and cholesterol in BHS female and male subjects (N=229) and found evidence for a modifying effect of a subset of variants on the relationship between cholesterol and BMI (P<0.01). These findings suggest a novel association of gene variants within EPHX2 to susceptibility to AN and provide a foundation for future study of this important yet poorly understood condition
Progress towards mammalian whole-brain cellular connectomics
Neurons are the fundamental structural units of the nervous system i.e., the Neuron Doctrine as the pioneering work of Santiago Ramon y Cajal in the 1880's clearly demonstrated through careful observation of Golgi-stained neuronal morphologies. However, at that time sample preparation, imaging methods and computational tools were either nonexistent or insufficiently developed to permit the precise mapping of an entire brain with all of its neurons and their connections. Some measure of the "mesoscopic" connectional organization of the mammalian brain has been obtained over the past decade by alignment of sparse subsets of labeled neurons onto a reference atlas or via MRI-based diffusion tensor imaging. Neither method, however, provides data on the complete connectivity of all neurons comprising an individual brain. Fortunately, whole-brain cellular connectomics now appears within reach due to recent advances in whole-brain sample preparation and high-throughput electron microscopy (EM), though substantial obstacles remain with respect to large volume electron microscopic acquisitions and automated neurite reconstructions. This perspective examines the current status and problems associated with generating a mammalian whole-brain cellular connectome and argues that the time is right to launch a concerted connectomic attack on a small mammalian whole-brain
Adar3 is involved in learning and memory in mice
© 2018 Mladenova, Barry, Konen, Pineda, Guennewig, Avesson, Zinn, Schonrock, Bitar, Jonkhout, Crumlish, Kaczorowski, Gong, Pinese, Franco, Walkley, Vissel and Mattick. The amount of regulatory RNA encoded in the genome and the extent of RNA editing by the post-transcriptional deamination of adenosine to inosine (A-I) have increased with developmental complexity and may be an important factor in the cognitive evolution of animals. The newest member of the A-I editing family of ADAR proteins, the vertebrate-specific ADAR3, is highly expressed in the brain, but its functional significance is unknown. In vitro studies have suggested that ADAR3 acts as a negative regulator of A-I RNA editing but the scope and underlying mechanisms are also unknown. Meta-analysis of published data indicates that mouse Adar3 expression is highest in the hippocampus, thalamus, amygdala, and olfactory region. Consistent with this, we show that mice lacking exon 3 of Adar3 (which encodes two double stranded RNA binding domains) have increased levels of anxiety and deficits in hippocampus-dependent short- and long-term memory formation. RNA sequencing revealed a dysregulation of genes involved in synaptic function in the hippocampi of Adar3-deficient mice. We also show that ADAR3 transiently translocates from the cytoplasm to the nucleus upon KCl-mediated activation in SH-SY5Y cells. These results indicate that ADAR3 contributes to cognitive processes in mammals