Predicted cell types across functional regions based on human brain spatio-temporal transcriptome
Poster No:
705
Submission Type:
Abstract Submission
Authors:
Man Liang1,2, Na Luo2, Tianzi Jiang1,2,3
Institutions:
1School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China, 2Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China, 3Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital, Yongzhou, China
First Author:
Man Liang
School of Artificial Intelligence, University of Chinese Academy of Sciences|Brainnetome Center, Institute of Automation, Chinese Academy of Sciences
Beijing, China|Beijing, China
School of Artificial Intelligence, University of Chinese Academy of Sciences|Brainnetome Center, Institute of Automation, Chinese Academy of Sciences
Beijing, China|Beijing, China
Co-Author(s):
Tianzi Jiang
School of Artificial Intelligence, University of Chinese Academy of Sciences|Brainnetome Center, Institute of Automation, Chinese Academy of Sciences|Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital
Beijing, China|Beijing, China|Yongzhou, China
School of Artificial Intelligence, University of Chinese Academy of Sciences|Brainnetome Center, Institute of Automation, Chinese Academy of Sciences|Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital
Beijing, China|Beijing, China|Yongzhou, China
Introduction:
Genes, as carriers of genetic information, regulate the formation of cells with distinct functions, which coordinate to form complex tissues and larger brain regions, ultimately supporting brain functions and behaviors. Previously, invasive techniques were used to explain the formation and developmental mechanisms of brain regional layouts at the genetic level(Amunts, 2015). With advancements in transcriptomics and MRI, researchers have begun to explore the genetic mechanisms underlying brain regional formation (Hawrylycz, 2012). However, multi-scale studies linking molecular structures to macroscopic brain regions through cells remain limited. Computational methods for inferring regional cell abundance from bulk transcriptomes (Newman, 2019) provide new insights into the cellular basis of gene-driven functional regions. Recent work reveals spatial coupling between gene-based cell type distributions and cortical organization (Zhang, 2024). Building on previous research, we utilized developmental transcriptomic data from various brain regions and single-nucleus RNA sequencing data to explore the spatial topography of cell types in functional brain regions during development, spanning from the early fetal(period 3) to middle adulthood(period 14).
Methods:
We analyzed developmental transcriptomic microarray data from the BrainSpan dataset (Kang, 2011), which includes data from 33 donors covering 16 brain regions from the early fetal period to middle adulthood. These 16 regions comprise the cerebellar cortex(CBC), mediodorsal nucleus of the thalamus(MD), striatum(STR), amygdala(AMY), hippocampus(HIP), and 11 areas of the neocortex(NCX).After preprocessing the transcriptomic data from 456 samples, differential expression analysis yielded the expression profiles of 4,085 genes across 16 regions over 12 developmental stages. Cell type deconvolution was performed using Siletti's snRNA-Seq data (Siletti, 2023), which includes eight GABAergic inhibitory interneurons, eight glutamatergic excitatory neurons, and six non-neuronal cell types. Using 500 permutations, we ultimately obtained predictions of cell abundance across 16 brain regions during various developmental stages.
Results:
Across developmental stages, transcriptomic differences between brain regions are significantly more pronounced than those across developmental stages. Each functional brain region contains many region-specific genes, which are strongly associated with the formation of brain regions with distinct functions. In comparison to genes, cells exhibit less specificity across functional brain regions and display more similar distribution patterns. However, they still demonstrate unique topographical features, such as Astro being more enriched in HIP, CBC, and MD; L4 IT being more enriched in V1C, S1C, and A1C; and VIP being more enriched in MFC, DFC, and MD. Meanwhile, cell types also exhibit temporal specificity partly. For instance, Astro exhibits increased enrichment beyond the age of 40, whereas VIP gradually declines throughout developmental stages (see Fig. 1).
Conclusions:
By predicting cell type regional abundances based on genes over the developmental timeline, we found that these abundances exhibit specificity across functional brain regions and developmental stages, and they align closely with the spatial topography of cell types derived from invasive techniques. This provides insights into how genes govern cell formation, which subsequently aggregates to form functional brain regions, suggesting that both genes and cell types follow functionally constrained spatial topography.
Genetics:
Genetic Association Studies 2
Transcriptomics 1
Genetics Other
Lifespan Development:
Early life, Adolescence, Aging
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Normal Development
Keywords:
Development
Neurological
Other - Single-nucleus RNA sequencing;Developmental transcriptomic;Cell-type abundance
1|2Indicates the priority used for review
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