The ion channel mechanisms of the subthreshold inward depolarizing currents in the mice VTA dopaminergic neurons and their roles in the depression-like behavior
Data files
Oct 16, 2024 version files 25.97 MB
-
gene_expression.zip
19.65 MB
-
README.md
8.17 KB
-
reads_quality_statistics.zip
6.29 MB
-
samples_information.xlsx
16.65 KB
Abstract
The dopaminergic (DA) neurons in the ventral tegmental area (VTA) of the middle brain play an important role in emotion-related behaviour, and the alteration of excitability of VTA DA neurons are believed to be the key determinants in behaviours of depression and drug addictions. The excitability of VTA DA neurons controls the release of DA in the projection fiber terminals thus controls the function of VTA DA neurons. After many years of hard work, we begin to understand how the excitability of VTA DA neurons is regulated, but these achievements are far from satisfactory. Furthermore, with recent progress and realization that property of VTA DA neurons, against the classical view that VTA DA neurons are homogeneous population, are distinctly different, thus the accumulated limited knowledge on the mechanism of excitability modulation of VTA DA neurons is especially short of expectation. The most outstanding indications of the heterogeneity of VTA DA neurons are represented by the distinctly different electrophysiological properties among VTA DA neurons projecting to different brain regions. However, the underlying mechanism is not clear. In this application, we plan to investigate the underlying mechanism determining the distinct excitability of VTA DA neurons projecting to the cortical and the limbic regions of the brain by single cell RNA sequencing (scRNA-seq). The main focus of the study will be on the intrinsic ion channels and the related modulation mechanism of VTA DA neuron excitability. Based on this, we will further study the mechanism which underlies the alteration of excitability of VTA DA neurons in the condition of a depression state, and still further the related depression behaviour.
https://doi.org/10.5061/dryad.41ns1rnq5
Description of the data and file structure
Red retrobeads (100 nl for single injection) were injected into the following sites: bilaterally into NAc core (NAc c), NAc lateral shell (NAc ls), NAc medial shell (NAc ms), and basolateral amygdala (BLA), 4 separate sites (2 per hemisphere) into medial prefrontal cortex (mPFC). After retrobeads injection, following brain slice preparation and recording, the recorded and retrobeads-labelled neurons were aspirated into the patch pipette and were then broken into the PCR tube containing 1 μl lysis buffer. For mRNA in individual cells, mRNA was amplified by SMARTer Ultra Low Input RNA for Illumina Kit, which was qualified and reversely transcribed to cDNA by Qubit and Agilent Bioanalyzer 2100 electrophoresis. After fragmentation of cDNA (300 bp) by ultrasound, sequencing libraries (end repair, addition of poly(A), and ligation of sequencing connectors) were built using the Ovation Ultralow Library System V2. After that, the constructed libraries were sequenced using Illumina HiseqXten.
Files and variables
File: reads_quality_statistics.zip
Description: Quality control metrics for each individual using FastQC software.
File: gene_expression.zip
Description: Gene expression;In single-cell mRNA sequencing, the level of gene expression is estimated by the number of reads mapped to the gene region, but the number of reads is not only proportional to the level of gene expression, but also related to the length of the gene itself, and the amount of data sequenced. In order to make the gene expression levels comparable between different genes and samples, the reads were converted into FPKM (Fragments Per Kilobase of exon model per Million mapped reads) for the normalisation of gene expression. the number of Fragments for each gene is counted by Stringtie (version:1.3.0) after Hisat2 comparison, then normalised by TMM (trimmed mean of M values) method, and finally the FPKM value for each gene is calculated using perl script.
File: samples_information.xlsx
Description: Detailed information on individual sequencing samples.
| Variable | Definition |
|---|---|
| library name | A unique and arbitrary identifier for each sample. This information will not appear in the final records and is only used as an internal reference. |
| title | Unique title that describes the Sample. We suggest the convention: [biomaterial] [condition(s)] [replicate number] |
| organism | the organism(s) from which the sequences were derived. |
| tissue | Tissue |
| cell type | Cell type |
| molecule | Type of molecule that was extracted from the biological material. |
| single or paired-end | "single" (usual case) or "paired-end". |
| *instrument model | Instrument model |
| description | Additional information not provided in the other fields, |
| processed data file | Exact name of the file containing the processed data. |
Details on samples
| *library name | *title | details |
|---|---|---|
| X3-23-0 | c1 | NAc core-projecting VTA neurons |
| X3-23-1 | c2 | NAc core-projecting VTA neurons |
| X3-24-0 | c3 | NAc core-projecting VTA neurons |
| X3-24-1 | c4 | NAc core-projecting VTA neurons |
| X3-24-2 | c5 | NAc core-projecting VTA neurons |
| X181004C0 | c6 | NAc core-projecting VTA neurons |
| X181004C1 | c7 | NAc core-projecting VTA neurons |
| X3-19-0 | m1 | NAc medial shell-projecting VTA neurons |
| X3-19-1 | m2 | NAc medial shell-projecting VTA neurons |
| X3-19-2 | m3 | NAc medial shell-projecting VTA neurons |
| X3-19-3 | m4 | NAc medial shell-projecting VTA neurons |
| X20180923m4 | m5 | NAc medial shell-projecting VTA neurons |
| X20180924m0 | m6 | NAc medial shell-projecting VTA neurons |
| X20180924m1 | m7 | NAc medial shell-projecting VTA neurons |
| X20180924m3 | m8 | NAc medial shell-projecting VTA neurons |
| X3-13-1 | l1 | NAc lateral shell-projecting VTA neurons |
| X3-13-2 | l2 | NAc lateral shell-projecting VTA neurons |
| X3-14-0 | l3 | NAc lateral shell-projecting VTA neurons |
| X3-25-1 | l4 | NAc lateral shell-projecting VTA neurons |
| X3-25-2 | l5 | NAc lateral shell-projecting VTA neurons |
| X3-25-3 | l6 | NAc lateral shell-projecting VTA neurons |
| X181005L0 | l7 | NAc lateral shell-projecting VTA neurons |
| X181005L3 | l8 | NAc lateral shell-projecting VTA neurons |
| X181005L4 | l9 | NAc lateral shell-projecting VTA neurons |
| X20180922L0 | l10 | NAc lateral shell-projecting VTA neurons |
| X20180922L1 | l11 | NAc lateral shell-projecting VTA neurons |
| X20180922L2 | l12 | NAc lateral shell-projecting VTA neurons |
| X20180922L3 | l13 | NAc lateral shell-projecting VTA neurons |
| X181006B1 | b1 | BLA-projecting VTA neurons |
| X181006B3 | b2 | BLA-projecting VTA neurons |
| X181010B0 | b3 | BLA-projecting VTA neurons |
| X181010B1 | b4 | BLA-projecting VTA neurons |
| X181013B1 | b5 | BLA-projecting VTA neurons |
| X181013B3 | b6 | BLA-projecting VTA neurons |
| X181014B1 | b7 | BLA-projecting VTA neurons |
| X181014B2 | b8 | BLA-projecting VTA neurons |
| X181014B4 | b9 | BLA-projecting VTA neurons |
| X181014B5 | b10 | BLA-projecting VTA neurons |
| S0511-P10 | p1 | mPFC-projecting VTA neurons |
| S0511-P11 | p2 | mPFC-projecting VTA neurons |
| S0511-P7 | p3 | mPFC-projecting VTA neurons |
| S0512-P1 | p4 | mPFC-projecting VTA neurons |
| S0512-P2 | p5 | mPFC-projecting VTA neurons |
| S0512-P3 | p6 | mPFC-projecting VTA neurons |
| S0512-P8 | p7 | mPFC-projecting VTA neurons |
Raw genomic data were uploaded to the NCBI Gene Expression Omnibus, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE276319.
Code/software
Just EXCEL is needed to view the uploaded data.
After retrobeads injection, following brain slice preparation and recording, the recorded and retrobeads-labelled neurons were aspirated into the patch pipette and were then broken into the PCR tube containing 1 μl lysis buffer. For mRNA in individual cells, mRNA was amplified by SMARTer Ultra Low Input RNA for Illumina Kit, which was qualified and reversely transcribed to cDNA by Qubit and Agilent Bioanalyzer 2100 electrophoresis. After fragmentation of cDNA (300 bp) by ultrasound, sequencing libraries (end repair, addition of poly(A), and ligation of sequencing connectors) were built using the Ovation Ultralow Library System V2. After that, the constructed libraries were sequenced using Illumina HiseqXten.
