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Bioinformatics, Computational and Systems Biology

Bioinformatics, Computational and Systems Biology - Poster Session D

Poster A3 - Mapping the Spatial Transcriptome of Clustered Protocadherins in Early Mouse Brain Development

Friday, October 25, 2024
3:30 PM - 4:30 PM EST
Location: Exhibit Hall E, F & G

Introduction:  Clustered protocadherins (cPcdh) are a family of calcium-dependent cell adhesion proteins that are critical for the development of the mammalian nervous system. These proteins are encoded by three linked gene families—Pcdha, Pcdhb, and Pcdh—resulting in over 50 distinct cPcdh protein isoforms. Each neuron expresses a unique combination of cPcdh genes, and this diversity provides each neuron with the single-cell identity required for dendritic self-avoidance in the brain (Chen et al., 2017).

Past research efforts have characterized these gene families at both genomic and transcriptomic levels. For example, studies of mice bearing deletions of the entire Pcdhγ gene cluster have deficits in circuit formation and behavior (Chen et al., 2017). Another study used single-cell reverse transcription-polymerase chain reaction (RT-PCR) in Purkinje neurons to show that the alternate Pcdh isoforms are randomly expressed, while the C-type isoforms are consistently expressed(Shigeyuki Esumi et al., 2005). However, these studies have not fully delineated the regulatory mechanisms driving cPcdh expression or their varying expression across different neuronal types.

To address these gaps, here we use spatial transcriptomics in the mouse brain, to understand the stochastic expression patterns and functional roles of cPcdhs genes by exploring their spatial correlations both within the gene families and with all other genes in our dataset. We intend to elucidate the regulatory networks that control cPcdh expression and understand the molecular mechanisms underlying dendritic self-avoidance. This exploration is expected to offer insights into the dynamics of neuronal network development and provide implications for addressing neurodevelopmental disorders more effectively.

Materials and

Methods:  To extend our knowledge on clustered protocadherins (cPcdh) gene expression into the spatial context, we adapted the Curio Seeker Slide-seqV2 technology, which utilizes arrays of 10 µm DNA-barcoded beads to create transcriptome-wide spatial maps of RNA molecules within tissue samples. In brief, a 10 μm sagittal slice from a flash-frozen, 10 day old wild-type mouse brain was placed onto the 10 mm × 10 mm spatially-indexed Slide-seqV2 bead surface. The Curio Seeker protocol was followed for RNA hybridization,reverse transcription, second strand synthesis, and cDNA amplification. Then, to further amplify the cPcdh reads and to differentiate cPcdh isoforms, we used IDT xGen custom hybridization probe panels to selectively bind to the cPcdh genes and their isoforms in the cDNA library. The enriched cDNA samples were then sequenced using long-read nanopore sequencing technology.

The resulting Slide-seq count matrix and the spatial position information for every bead barcode were loaded into an AnnData object and quality control filtering was done using Scanpy. The spatial beads were then grouped with UMAP and Leiden clustering, and the clusters were annotated with marker genes. A nearest neighbors smoothing algorithm was applied on the AnnData object matrix to reduce variability in expression levels that might be due to technical artifacts or experimental noise, improving the reliability of the subsequent spatial correlation analyses. Pearson R correlation coefficients were calculated both among isoforms of the cPcdh families and with other genes.

Results, Conclusions, and Discussions: By employing targeted probes to pulldown cPcdh transcripts, we achieved a capture rate of 68.7% of cPcdh gene transcripts relative to total reads, indicating effective enrichment. Our analytical approach enabled a profiling of 270,000 spatial locations, classifying them into 31 refined cell types, and identification of 13 distinct brain regions. Among the 18,940 genes identified, all 58 cPcdh isoforms were detected, underscoring the efficacy of long-read sequencing in capturing intricate details of the cPcdh gene family.

Notably, all Pcdhα genes exhibited consistent tissue-wide spatial expression patterns, with higher expression observed in the cortex, hippocampus, cerebellum, and thalamus. Specifically, the Pcdhac2 isoform was generally more highly expressed, aligning with previous studies that identified Pcdhac2 as the sole Pcdha isoform in serotonergic neurons via single-cell sequencing (Chen et al., 2017). Conversely, the Pcdhb family showed no distinct spatial expression patterns and was characterized by sparse distribution across tissues, attributed to generally low expression levels. In contrast, most Pcdhγ genes mirrored the expression patterns of Pcdha genes, with the exception of Pcdhγ2 and Pcdhγb4.

To quantify relationships further, we used Pearson R correlation with a 0.7 cutoff, focusing on genes with over 100 transcripts. This approach identified 500 genes with similar expression patterns to the Pcdha family, including eight transcription factors potentially upregulating Pcdha expression. Additionally, ten transcription factors negatively correlated with all Pcdha genes, suggesting a regulatory role in their expression. For the Pcdhγ family, 25 transcription factors showed similar patterns, with four also closely correlating with Pcdha genes, reinforcing the intricate regulatory networks within these gene families.

Our study effectively utilized targeted probes and long-read sequencing to spatially map the complex expression patterns of the cPcdh gene family across multiple brain regions. By achieving a high capture rate, we identified novel expression patterns within the cPcdh families, revealing significant variability in expression levels and spatial distributions. Additionally, we identified potential transcription factors that may be responsible for these patterns. Future motif analysis could be compared against the transcription factors we found to be spatially coexpressed with cPcdh isoforms to further explore the regulatory mechanisms governing cPcdh proteins.

Acknowledgements (Optional):