Data from: Whole-brain spatial organization of hippocampal single-neuron projectomes

# Whole-brain spatial organization of hippocampal single-neuron projectomes Code and data for mouse hippocampal single-neuron projectome and spatial transcriptome analysis and visualization. ## Description of the data and file structure The neuronal data is represented as tree-structured swc files following specifications as: . All the swcs are registered to the Allen Template Brain CCF 2017 (Wang, Quanxin, et al. "The Allen mouse brain common coordinate framework: a 3D reference atlas." Cell 181.4 (2020): 936-953) with brain regions following Allen naming conventions, e.g. HPF: Hippocampal formation; HIP: Hippocampal region; CA1: Field CA1; CA3: Field CA3; DG: Dentate gyrus; SUB: Subiculum. We organize the repository following research article figure groups; at the same time, we provide description for our data and scripts below for easy and independent access to our resources. The projectome data are mainly presented in: 1. readable tabular and JSON files, with description listed below; 2. pickle objects that can be read using Python `pickle.load(open($file_path, 'rb'))` function, stored within each figure with variable description in *[note for pkl files.ipynb]* under its designated directory. The spatial transcriptome data are stored as Seurat object that can be read using R `readRDS($file_path)` function. The main structure for the repository: * archive `###pre-requisites to run python files.` ├─ requirements.txt `###data and scripts (*.ipynb, *.py, *.R) for analysis grouped by figures.` ├─ figures `###Projectome subtype classifications of hippocampal neurons.` │ ├─ fig1 │ │ ├─ fig1_D │ │ ├─ fig1_E │ │ ├─ fig1_panelD.ipynb `###Code for heatmap showing the whole-brain projection strength of caudal part and rostral part for each single neuron` │ │ └─ fig1_panelE.ipynb `###Code for hierarchical clustering based on the whole-brain projection patterns.` │ │ └─ note for pkl files.ipynb `###projection target-dependent soma locations of hippocampal neurons.` │ ├─ fig2 │ │ ├─ fig2_A │ │ ├─ fig2_A.ipynb `###Code for the top 50 most frequent single-cell target patterns` │ │ ├─ fig2_C │ │ ├─ fig2_C.ipynb `###Code for the distribution of LEC-MEC selectivity for each ENT projecting neurons and their distribution in CA1, SUB, ProS and SUBr neurons` │ │ ├─ fig2_G │ │ ├─ fig2_G.ipynb `###Code for showing the neuron number and soma locations in given joint projection patterns and subtypes` │ │ ├─ fig2_H │ │ ├─ fig2_H.ipynb `###Code for showing the soma locations for specified projection patterns among given target areas.` │ │ └─ note for pkl files.ipynb `###Spatial correlation between transcriptome and projectome subtypes;` │ ├─ fig3 │ │ └─ figure_3.xlsx `###list of data and functions linked to spatialTranscriptome/R_data and spatialTranscriptome/python_data;` `###Bi-hemispheric projecting neurons in hippocampus.` │ ├─ fig4 │ │ ├─ fig4_A │ │ ├─ fig4_A.ipynb `###Code for showing the distribution of bilaterally projecting neurons in different subtype` │ │ ├─ fig4_E │ │ ├─ fig4_E.ipynb `###Code for showing the distribution of CA3 neurons and CA1 neurons that bilaterally projecting to HIP` │ │ ├─ fig4_H │ │ ├─ fig4_H.ipynb `###Code for showing the projection strength in different layers of bilateral LEC and MEC for ProS,PAR,PRE,POST neurons that could bilaterally projecting to RHP` │ │ ├─ fig4_I │ │ ├─ fig4_I.ipynb `###Code for showing intersection of neurons that bilaterally projecting to different areas.` │ │ ├─ fig4_J │ │ ├─ fig4_J.ipynb `###Code for showing the neuron number, soma distribution in sub-hip regions and ipsilateral or contralateral projection strength in different target areas ` │ │ ├─ fig4_L │ │ ├─ fig4_L.ipynb `###Code for showing the ipsi-preference index of neurons having bilateral projections` │ │ ├─ fig4_M │ │ ├─ fig4_M.ipynb `###Code for showing the ratio of ipsi-only,contra-only and bilateral projection neurons` │ │ └─ note for pkls.ipynb `###Projection patterns of CA1, SUB and SUBr neurons` │ ├─ fig5 │ │ ├─ fig5_A │ │ ├─ fig5_A.ipynb `###Code for showing enriched target patterns in CA1, SUB, ProS and SUBr neurons.` │ │ ├─ fig5_B │ │ ├─ fig5_B.ipynb `###Code for showing the neuron number percentage which have different target number` │ │ ├─ fig5_C │ │ ├─ fig5_C.ipynb `###Code for showing the collateral index of CA1,SUB,ProS and SUBr neurons projecting to different downstream areas.` │ │ ├─ fig5_EFG │ │ ├─ fig5_EFG.ipynb `###Code for showing the correlation motif of downstream areas for CA1,SUB,ProS and SUBr neurons` │ │ ├─ fig5_H │ │ ├─ fig5_H.ipynb `###Code for showing the intra-HPF projection patterns and extra-HPF projection patterns of neurons preferring different intra-HPF targets. ` │ │ ├─ fig5_I │ │ ├─ fig5_I.ipynb `###Code for showing the collateral index of neurons preferring different intra-HPF target` │ │ ├─ fig5_K │ │ ├─ fig5_K.ipynb `###Code for showing the correlation of projection strength in intra-HPF tragets and extra-HPF targets` │ │ └─ note for pkl files.ipynb `###Longitudinal spread of Schaffer collaterals and mossy fiber axons` │ ├─ fig6 │ │ ├─ fig6_C │ │ ├─ fig6_D │ │ ├─ fig6_F │ │ ├─ fig6_H │ │ ├─ fig6_I │ │ ├─ fig6_J │ │ ├─ fig6_K │ │ ├─ fig_6C.ipynb `###Code for showing the T-L index of axon projections in ipsilateral and contralateral CA3 from every single CA3 neuron ` │ │ ├─ fig_6D.ipynb `###Code for showing the T-L index of axon projections in ipsilateral and contralateral CA1 from every signle CA3 neuron ` │ │ ├─ fig_6F.ipynb `###Code for showing the T-L index of axon projections in DG and CA3 from every signle DG neuron ` │ │ ├─ fig_6H.ipynb `###Code for showing the statistic of overall T-L index for all CA3 neurons` │ │ ├─ fig_6J.ipynb `###Code for showing the statistic of overall T-L index for all DG neurons` │ │ ├─ fig_6i.ipynb `###Code for showing the statistic of overall span for all CA3 neurons` │ │ └─ fig_6k.ipynb `###Code for showing the statistic of overall span for all DG neurons` │ │ └─ note for pkl files.ipynb `#Dependence of axon arbor distribution on the transverse location of soma.` │ ├─ fig7 │ │ ├─ HIP_CA1_CA3_proximodistal_analysis.py `###code for HPF transverse plane analysis` │ │ ├─ allen_annotation │ │ │ └─ allen_struct_info.json `###json file that store the Allen CCFv3 structure information` │ │ ├─ resource │ │ │ ├─ CA1_ipsi_targets_proximodistal_info.csv `###table of CA1 neuron's location on CA1 proximodistal and longitudinal position, mean terminal location in specific target regions.` │ │ │ ├─ CA1_soma_info.csv `###table of CA1 neuron's soma information, for example, neuron id, neuron's soma location, neuron's laterality, neuron's depth in CA1.` │ │ │ ├─ CA1_terminal_info.csv `### table of CA1 neuron's terminal information, for example, terminal location, laterality, CCFv3 structure id that the terminal located in.` │ │ │ ├─ CA3_soma_info.csv `###table of CA3 neuron's soma information, for example, neuron id, neuron's longitudinal location in HIP, neuron's laterality, neuron's proximodistal location in CA3.` │ │ │ └─ CA3_terminal_info.csv `### table of CA3 neuron's terminal information, for example, laterality, CCFv3 structure id that the terminal located in, terminal's longitudinal position and depth in CA1.` │ │ └─ utils │ │ ├─ **init**.py │ │ └─ allen_struct_info.py `### map function between Allen CCFv3 structure informations, for example, map CCFv3 structure id to CCFv3 structure acronym.` `###Dependence of axonal arbor distribution on the longitudinal location of soma` │ ├─ fig8 │ │ ├─ fig8_C │ │ ├─ fig8_D │ │ ├─ fig8_EF │ │ ├─ fig8_G │ │ ├─ fig_8C.ipynb `###Code for showing the topographic projection correlation between the somalocations and the axon terminal locations for all ENT projecting neurons` │ │ ├─ fig_8D.ipynb `###Code for showing the whole-brain topographic projection correlation between the somalocations and the axon terminan locations ` │ │ ├─ fig_8EF.ipynb `###Code for showing the correlation between somalocations and the target number,the correlation between the longitudinal span and the target number` │ │ └─ fig_8G.ipynb `###Code for showing the whole brain topographic projection patterns for all the neurons` │ │ └─ note for pklfiles.ipynb `###dendrite analysis` │ ├─ fig_s10 │ │ ├─ CA1_to_MSC_dendritic_analysis.py `### Code for dendritic morphological feature analysis of MSC projecting CA1 neurons.` │ │ └─ resource │ │ ├─ CA1_dendritic_cluster.csv `### Dendritic cluster of all CA1 neurons.` │ │ ├─ CA1_projection_strength.csv `### MSC projecting CA1 neurons' projection strength in different target regions.` │ │ ├─ CA1_to_MSC_dendritic_cluster.csv `###Dendritic clusters of MSC projecting CA1 neurons` │ │ ├─ CA1_to_MSC_dendritic_features.csv `###Dendritic mophological features of MSC projecting CA1 neurons` │ │ ├─ CA1_to_MSC_feature_importance.csv `###Dendritic feature importance for dendritic classicication.` │ │ ├─ CA1_to_MSC_soma_info.csv `###Location information of MSC projecting CA1 neurons` │ │ └─ MSC_projecting_axon_length.csv `### CA1 neurons' axon length in MSC` `###Intra-HPF target-specific preference in hippocampal axon projections.` │ ├─ fig_s11 │ │ ├─ figS11_A.ipynb `###Code for clustermap of intra-HPF projection patterns.` │ │ ├─ figS11_B.ipynb `###Code for intra-HPF projection subtype distribution in CA1, SUB, ProS, and SUBr neuron groups.` │ │ ├─ figS11_DEFG.ipynb `###Code for intersection among neurons having different target numbers, neurons projecting different targets and intra-HPF projection subtype ` │ │ ├─ figS11_H.ipynb `###Code for co-projecting neuron numbers of intra-HPF areas and extra-HPF areas` │ │ ├─ figS11_I.ipynb `###Code for the fraction of SUBr neurons in each intra-HPF prjectiono subtype ` │ │ ├─ fig_s11A │ │ ├─ fig_s11B │ │ ├─ fig_s11DEFG │ │ ├─ fig_s11H │ │ ├─ fig_s11I │ │ └─ note for pklfiles.ipynb `###superficial/deep CA1 neuron analysis` │ ├─ fig_s12 │ │ ├─ S12.py `### Code for demostrate the projection pattern difference of superficial CA1 neurons and deep CA1 neurons.` │ │ └─ resource │ │ ├─ S12_deep_superficial_projection_features.csv `### Projection strength in different target regions of deep superficial CA1 neurons.` │ │ └─ S12_dorsal_CA1_soma_depth_and_projection_features.csv `### Table of neurons' location and projection strength in target regions.` `###Morphological features of neurons in hippocampal subregions.` │ ├─ fig_s2 │ │ ├─ fig_s2_morphology_parameters.ipynb `###Code for box plot for morphology features quantification.` │ │ └─ morphology_parameters.xlsx `###Morphology features quantification.` `###Neuron clustering.` │ ├─ fig_s4 │ │ ├─ fig_s4D │ │ ├─ fig_s4E │ │ ├─ figs4_D.ipynb `###Code for dot plot of downstream target patterns along axon trajectories of axon arbor templates.` │ │ ├─ figs4_E_caudal.ipynb `###Code for hierarchical clustering of caudal projection patterns ` │ │ ├─ figs4_E_combine.ipynb `###Code for generate whole-brain projection patterns by combining caudal projection patterns and rostral projection patterns ` │ │ └─ figs4_E_rostral.ipynb `###Code for hierarchical clustering of rostral projection patterns ` │ │ └─ note for pklfiles.ipynb `###Discrete longitudinal distribution of projectome subtypes.` │ ├─ fig_s7 │ │ ├─ fig_s7_plot_distribution.ipynb `###Code for distribution plot for projectome subtypes.` │ │ ├─ neuronInfo.csv `###Neuron sample information.` │ │ ├─ scatter.csv `###Downstream projection patterns for subtype5 and subtype21 neurons.` │ │ ├─ slopes.csv `###Distribution quantification for each projectome subtypes.` │ │ └─ slopes_region.csv `###Distribution quantification for each projectome subtypes per region.` `###The long-range projection from neurons in DG, CA2 and CA3.` │ ├─ fig_s8 │ │ ├─ figS8_B.ipynb `###Code for pie plot and distribution plot for DG long-range projection neurons of subtype 5, 34, 35, 39.` │ │ ├─ figS8_C.ipynb `###Code for violin plot of axon lengths in target areas (HPF, LSX and MSC) for DG long-range projection neurons of subtype 5, 34, 35, 39.` │ │ ├─ figS8_E.ipynb `###Code for stacked bar plot of DG-mo, DG-po, and DG-sg neuron numbers in local and long-range projection DG neurons.` │ │ ├─ figS8_I.ipynb `###Code for pie plot and distribution plot for CA3 neurons of subtype 5, 34, 35, 39, and 43.` │ │ ├─ figS8_J.ipynb `###Code for violin plot of axon lengths in target areas (HPF, LSX and MSC) for CA3 neurons of subtype 5, 34, 35, 39, and 43.` │ │ ├─ figS8_LMN.ipynb `###Code for neuron distribution and downstream projection patterns for CA2 neurons of subtype 34, 39, and 43.` │ │ ├─ fig_s8B │ │ ├─ fig_s8C │ │ ├─ fig_s8E │ │ ├─ fig_s8I │ │ ├─ fig_s8J │ │ ├─ fig_s8LMN │ │ └─ note for pklfiles.ipynb `###Spatial transcriptome analysis for CA1 sections.` │ └─ fig_s9 │ └─ figure_s9.xlsx `###list of data and functions linked to spatialTranscriptome/R_data and spatialTranscriptome/python_data.` `###data and scripts (*.R, *.ipynb) to analyze spatial transcriptome and its correlation to projectome, including Seurat objects for mouse CA1 spatial transcriptome analysis and documents on how to use them, mainly used for fig3 and fig_s9.` └─ spatialTranscriptome ├─ How to process transcriptomic data.pptx ├─ R_data │ ├─ bregma.txt `###chip bregma coordinates.` │ ├─ cluster │ │ └─ cluster.rds `###Seurat object of CA1 spatial bin-resolution cells` │ ├─ cluster_pipeline.R `###code for CA1 cells processing and clustering` │ ├─ mask_data `###Allen brain region mask.` │ ├─ subcluster │ │ ├─ CA_subcluster_transcriptomic_proportion.csv `###transcriptomic proportion in CA1 subcluster C1.` │ │ ├─ CA_subtype_projectomic_proportion.csv `###projectome proportion in bregma.` │ │ └─ subcluster.rds `###Seurat object of CA1 subcluster C1 spatial bin-resolution cells` │ └─ subcluster_pipeline.R `###code for CA1 subcluster C1 cells processing and clustering` └─ python_data ├─ fig3_GI_figS9_J.ipynb `###code to plot cell distribution in coronal slice` ├─ for_qc_heatmap_and_cor.csv `###sample information` └─ mask.csv `###Allen brain region mask.` ## Sharing/Access information This data is also available at: * \[] (Brain Science Data Center, Chinese Academy of Sciences) ## Code/Software All data can be used independently. All scripts can be run seperately using desired functions and data with pre-requisite libraries installed properly. The pre-requisites to run the Python code are listed in requirements.txt, the Python version used is Python 3.8.18. The pre-requisites to run the R code are listed below with R 4.3.1: * Seurat 4.4.0 * tidyverse 2.0.0 * pheatmap 1.0.12 * reshape2 1.4.4 * harmony 1.0.3