ePoster

Spatially resolved transcriptomics of newborn human prefrontal cortex

Kseniia Kubenko, Olga Efimova, Ilia Kurochkin, Aljes Binkevich, Zhenzhen Song, Anna Tkachev, Philipp Khaitovich
FENS Forum 2024(2024)
Messe Wien Exhibition & Congress Center, Vienna, Austria

Conference

FENS Forum 2024

Messe Wien Exhibition & Congress Center, Vienna, Austria

Resources

Authors & Affiliations

Kseniia Kubenko, Olga Efimova, Ilia Kurochkin, Aljes Binkevich, Zhenzhen Song, Anna Tkachev, Philipp Khaitovich

Abstract

The human prefrontal neocortex has undergone dramatic expansion during evolution and is involved in decision-making, stress resistance, and behavioral flexibility. Its capacity for high-level cognition emerges from a regularly organized, six-layered structure; however, the newborn transcriptome architecture underlying layer-specific traits remains unknown. To address this complexity, we characterized the transcriptome of the six cortical layers and adjacent white matter in the dorsolateral prefrontal cortex of 5 newborns, using Visium Spatial Gene Expression kits, followed by high-resolution imaging and RNA sequencing. Reads were mapped to histological images, cortical layers were identified by neuronal morphology and cell density and obtained results were compared to published data in the adult human prefrontal cortex (Maynard et al, 2021) to find common and group-specific gene expression by layers. Unsupervised clustering revealed 8 clusters in spatial transcriptomics data, with 5 clusters demonstrating neuronal cell type-specific expression. Newborn-specific gene expression in one cluster showed an excess of mature neuronal markers compared with that of the adult; two other neuronal clusters changed reciprocally to reflect corticocortical projection development, with learning and memory-related gene expression increase in layers V-VI. Superficial white matter, a thin layer of white matter underneath layer VI, appeared to have increased expression of RNA splicing genes in newborns. Spatial resolution transcriptomic analysis of normal cortical development may help in understanding some neurodevelopmental disorders such as childhood-onset schizophrenia or autism. This research was partially supported by the Russian Science Foundation (project #22-15-00474).

Unique ID: fens-24/spatially-resolved-transcriptomics-b2f4de93