Biology subjects

Bamford, R. A.

Publications and source records attributed to Bamford, R. A..

3 recordsLinked to original sources

bioRxiv2023

Long-read transcript sequencing identifies differential isoform expression in the entorhinal cortex in a transgenic model of tau pathology

Increasing evidence suggests that alternative splicing plays an important role in Alzheimers disease (AD), a devastating neurodegenerative disorder involving the intracellular aggregation of hyperphosphorylated tau. We used long-read cDNA sequencing to profile transcript diversity in the entorhinal cortex of wild-type (WT) and transgenic (TG) mice harboring a mutant form of human tau. Whole transcriptome profiling showed that previously reported gene-level expression differences between WT and TG mice reflect changes in the abundance of specific transcripts. Ultradeep targeted long-read cDNA sequencing of genes implicated in AD revealed hundreds of novel isoforms and identified specific transcripts associated with the development of tau pathology. Our results highlight the importance of differential transcript usage, even in the absence of gene-level expression alterations, as a mechanism underpinning gene regulation in the development of neuropathology. Our transcript annotations and a novel informatics pipeline for the analysis of long-read transcript sequencing data are provided as a resource to the community.

neuroscience↗

bioRxiv2023

CNTN4 modulates neural elongation through interplay with APP

The neuronal cell adhesion molecule contactin-4 (CNTN4) has been genetically linked to autism spectrum disorders (ASD) and other psychiatric disorders. The Cntn4-deficient mouse model has previously shown that CNTN4 has important roles in axon guidance and synaptic plasticity in the hippocampus. However, the pathogenesis and functional role of CNTN4 in the cortex have not yet been investigated. Using Nissl staining, immunohistochemistry and Golgi staining the motor cortex of Cntn4-/- mice was analysed for abnormalities. Interacting partners of CNTN4 were identified by immunoprecipitation and mass spectrometry. Further analysis of the interaction between CNTN4 and APP utilised knockout human cells generated via CRISPR-Cas9 gene editing. Our study newly identified reduced cortical thickness in the motor cortex of Cntn4-/- mice, but cortical cell migration and differentiation were unaffected. Significant morphological changes were observed in neurons in the M1 region of the motor cortex, indicating that CNTN4 is also involved in the morphology and spine density of neurons in the motor cortex. Furthermore, mass spectrometry analysis identified an interaction partner for CNTN4, and we confirmed an interaction between CNTN4 and APP. Knockout human cells of CNTN4 and/or APP revealed a relationship between CNTN4 and APP. This study demonstrates that CNTN4 contributes to cortical development, and that its binding and interplay with APP controls neural elongation. This is an important finding for understanding the function of APP, a target protein for Alzheimers disease. The binding between Cntn4 and APP, which is involved in neurodevelopment, is essential for healthy nerve outgrowth.

neuroscience↗

bioRxiv2023

Quantifying the proportion of different cell types in the human cortex using DNA methylation profiles

BackgroundDue to inter-individual variation in the cellular composition of the human cortex, it is essential that covariates that capture these differences are included in epigenome-wide association studies using bulk tissue. As experimentally derived cell counts are often unavailable, computational solutions have been adopted to estimate the proportion of different cell-types using DNA methylation data. Here, we validate and profile the use of an expanded reference DNA methylation dataset incorporating two neuronal- and three glial-cell subtypes for quantifying the cellular composition of the human cortex. ResultsWe tested eight reference panels containing different combinations of neuronal- and glial-cell types and characterized their performance in deconvoluting cell proportions from computationally reconstructed or empirically-derived human cortex DNA methylation data. Our analyses demonstrate that these novel brain deconvolution models produce accurate estimates of cellular proportions from profiles generated on postnatal human cortex samples, they are not appropriate for the use in prenatal cortex or cerebellum tissue samples. Applying our models to an extensive collection of empirical datasets, we show that glial cells are twice as abundant as neuronal cells in the human cortex and identify significant associations between increased Alzheimers disease neuropathology and the proportion of specific cell types including a decrease in NeuNNeg/SOX10Neg nuclei and an increase of NeuNNeg/SOX10Pos nuclei. ConclusionsOur novel deconvolution models produce accurate estimates for cell proportions in the human cortex. These models are available as a resource to the community enabling the control of cellular heterogeneity in epigenetic studies of brain disorders performed on bulk cortex tissue.

genomics↗