Search bioRxiv⌕ Search

Biology subjects

Jacobs, M. W.

Publications and source records attributed to Jacobs, M. W..

2 recordsLinked to original sources

Brain-wide Correspondence Between Neuronal Epigenomics and Long-Distance Projections

Single-cell genetic and epigenetic analyses parse the brains billions of neurons into thousands of "cell-type" clusters, each residing in different brain structures. Many of these cell types mediate their unique functions by virtue of targeted long-distance axonal projections to allow interactions between specific cell types. Here we have used Epi-Retro-Seq to link single cell epigenomes and associated cell types to their long-distance projections for 33,034 neurons dissected from 32 different source regions projecting to 24 different targets (225 source [->]target combinations) across the whole mouse brain. We highlight uses of this large data set for interrogating both overarching principles relating projection cell types to their transcriptomic and epigenomic properties and for addressing and developing specific hypotheses about cell types and connections as they relate to genetics. We provide an overall synthesis of the data set with 926 statistical comparisons of the discriminability of neurons projecting to each target for every dissected source region. We integrate this dataset into the larger, annotated BICCN cell type atlas composed of millions of neurons to link projection cell types to consensus clusters. Integration with spatial transcriptomic data further assigns projection-enriched clusters to much smaller source regions than afforded by the original dissections. We exemplify these capabilities by presenting in-depth analyses of neurons with identified projections from the hypothalamus, thalamus, hindbrain, amygdala, and midbrain to provide new insights into the properties of those cell types, including differentially expressed genes, their associated cis-regulatory elements and transcription factor binding motifs, and neurotransmitter usage.

neuroscience↗

Bell Jar: A Semi-Automated Registration and Cell Counting Tool for Mouse Neurohistology Analysis

To investigate the anatomical organization of neural circuits across the whole brain, it is essential to register the experimental brain tissues to a reference atlas accurately. This procedure is also a prerequisite to quantify the locations and numbers of cells of interest in specific regions. However, it remains challenging to do registration on experimental tissue due to the intrinsic variation among the specimens, tissue deformation introduced by histological processing, and the potential inconsistency in the judgment of the experimenter during manual annotation. Here, we introduce Bell Jar, a multi-platform analysis tool with semi-automated affine warping of atlas maps onto microscopic images of brain slices and machine learning-based cell detection. Bell Jars intuitive GUI and internal dependency management enable users of all skill levels to obtain accurate results without programming expertise. To compare the performance of Bell Jar with previously published methods1-4, we labeled neurons in the mouse visual cortex with either an engineered rabies virus or an adeno-associated virus (AAV) for neural circuit tracing5, and quantified Bell Jars performance at each step of the pipeline for image alignment, segmentation, and cell counting. We demonstrated that Bell Jars output is as reliable as manual counting by an expert; it is more accurate than currently available techniques even with noisy data and takes less time with fewer user interventions. Bell Jar is an easy-to-navigate application that provides a reproducible, automated analysis workflow to facilitate the precise mapping of histological images of the mouse brain to the reference atlas and the quantification of cellular signals it is trained to recognize.

neuroscience↗