epDevAtlas: Mapping GABAergic cells and microglia in postnatal mouse brains
Josephine K. Liwang,
Fae A. Kronman,
Jennifer A. Minteer
et al.
Abstract:During development, brain regions follow encoded growth trajectories. Compared to classical brain growth charts, high-definition growth charts could quantify regional volumetric growth and constituent cell types, improving our understanding of typical and pathological brain development. Here, we create high-resolution 3D atlases of the early postnatal mouse brain, using Allen CCFv3 anatomical labels, at postnatal days (P) 4, 6, 8, 10, 12, and 14, and determine the volumetric growth of different brain regions. … Show more
“…We resampled them to isotropic 20 × 20 × 20 µm voxel size using AMIRA (version 6.3.0; https://www.thermofisher.com/no/en/home/electron-microscopy/products/software-em-3dvis/amira-software.html). We also used the P4 volume shared by Liwang and colleagues 5 , which was provided as a .tif file with isotropic 20 × 20 × 20 µm voxel size. All volumes were converted to .nii.gz files for further processing.…”
Section: Allen Common Coordinatementioning
confidence: 99%
“…Efforts to construct such frameworks have almost exclusively focused on the adult brain, and atlases representing developing brain anatomy have consequently lagged behind. While some studies have addressed this by providing atlases for a subset of discrete, critical developmental stages [3][4][5] , this approach has notable limitations. First, when the temporal dimension is reduced to a subset of stages, data falling between established stages are not represented.…”
mentioning
confidence: 99%
“…template (CCFv3 1 ; RRID:SCR_020999; postnatal day 56) to developing mouse brain templates (postnatal day 4, 7, 14, 21 and 28) sourced from multiple publicly shared datasets 5,8 . The transformations were based on a three-step (translation, affine, b-spline) registration using elastix 9 , optimised by manually defined regions and landmarks.…”
Studies of the adult mouse brain have benefited from three-dimensional atlases providing a standard frame of reference for data analysis and integration. Extending these resources to the developing mouse brain has been challenging due to the need to integrate time as a dimension of the atlas. To address this, we present the Developmental Mouse Brain Atlas, a four-dimensional atlas encompassing each postnatal day from 4 to 56.
“…We resampled them to isotropic 20 × 20 × 20 µm voxel size using AMIRA (version 6.3.0; https://www.thermofisher.com/no/en/home/electron-microscopy/products/software-em-3dvis/amira-software.html). We also used the P4 volume shared by Liwang and colleagues 5 , which was provided as a .tif file with isotropic 20 × 20 × 20 µm voxel size. All volumes were converted to .nii.gz files for further processing.…”
Section: Allen Common Coordinatementioning
confidence: 99%
“…Efforts to construct such frameworks have almost exclusively focused on the adult brain, and atlases representing developing brain anatomy have consequently lagged behind. While some studies have addressed this by providing atlases for a subset of discrete, critical developmental stages [3][4][5] , this approach has notable limitations. First, when the temporal dimension is reduced to a subset of stages, data falling between established stages are not represented.…”
mentioning
confidence: 99%
“…template (CCFv3 1 ; RRID:SCR_020999; postnatal day 56) to developing mouse brain templates (postnatal day 4, 7, 14, 21 and 28) sourced from multiple publicly shared datasets 5,8 . The transformations were based on a three-step (translation, affine, b-spline) registration using elastix 9 , optimised by manually defined regions and landmarks.…”
Studies of the adult mouse brain have benefited from three-dimensional atlases providing a standard frame of reference for data analysis and integration. Extending these resources to the developing mouse brain has been challenging due to the need to integrate time as a dimension of the atlas. To address this, we present the Developmental Mouse Brain Atlas, a four-dimensional atlas encompassing each postnatal day from 4 to 56.
This paper explicates a solution to building correspondences between molecular-scale transcriptomics and tissue-scale atlases. This problem arises in atlas construction and cross-specimen/technology alignment where specimens per emerging technology remain sparse and conventional image representations cannot efficiently model the high dimensions from subcellular detection of thousands of genes. We address these challenges by representing spatial transcriptomics data as generalized functions encoding position and high-dimensional feature (gene, cell type) identity. We map onto low-dimensional atlas ontologies by modeling regions as homogeneous random fields with unknown transcriptomic feature distribution. We solve simultaneously for the minimizing geodesic diffeomorphism of coordinates through LDDMM and for these latent feature densities. We map tissue-scale mouse brain atlases to gene-based and cell-based transcriptomics data from MERFISH and BARseq technologies and to histopathology and cross-species atlases to illustrate integration of diverse molecular and cellular datasets into a single coordinate system as a means of comparison and further atlas construction.
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