Combinatorial expression of gamma-protocadherins regulates synaptic connectivity in the mouse neocortex

In the process of synaptic formation, neurons must not only adhere to specific principles when selecting synaptic partners but also possess mechanisms to avoid undesirable connections. Yet, the strategies employed to prevent unwarranted associations have remained largely unknown. In our study, we have identified the pivotal role of combinatorial clustered protocadherin gamma (γ-PCDH) expression in orchestrating synaptic connectivity in the mouse neocortex. Through 5-prime end single-cell sequencing, we unveiled the intricate combinatorial expression patterns of γ-PCDH variable isoforms within neocortical neurons. Furthermore, our whole-cell patch-clamp recordings demonstrated that as the similarity in this combinatorial pattern among neurons increased, their synaptic connectivity decreased. Our findings elucidate a sophisticated molecular mechanism governing the construction of neural networks in the mouse neocortex., 1, Single-cell dissociation. 2, FACS with DAPI.
3, Using Chromium Single Cell V(D)J Enrichment Kit, Mouse T Cell, PN-1000071 Kit (switching the primer with pcdhg specific primers) to get 5' end RNA seq.
4, Get clean reads from Novagene  Cellranger v3.0 for gene expression
5, Using  custom pipeline (written in the Matlab code)and Bowtie for pcdhg 5'end;, , # Combinatorial expression of gamma-protocadherins regulates synaptic connectivity in the mouse neocortex

Single cell profilling of pcdhg in neocortical neurons

## Description of the data and file structure

We isolated the neocortex of one P11 mouse, then applied single cell dissociation, collect around 20000 cells through FACs.
Library construction protocol: Chromium Single Cell V(D)J Enrichment Kit (Mouse T Cell, PN-1000071).
Library strategy: 5'end RNA seq.
Novaseq 6000 (Illumina, Novogene) was used for sequencing. Cellranger v3.0 was used for gene expression analysis. The data we uploaded contained the 3 Cellranger output files(barcodes.tsv.gz, features.tsv.gz, matrix.mtx.gz).

The data files consist of key components: 'barcodes.tsv.gz,' which comprises the cell barcode list and serves as the row identifier for 'matrix.mtx.gz'; 'features.tsv.gz,' containing the gene names for expression and acting as the column identifier for 'matrix.mtx.gz'; and 'matrix.mtx.gz,' housing the expr...