RT Journal
A1 Pei, Guangsheng
A1 Wang, Yin-Ying
A1 Simon, Lukas M.
A1 Dai, Yulin
A1 Zhao, Zhongming
A1 Jia, Peilin
T1 Gene expression imputation and cell-type deconvolution in human brain with spatiotemporal precision and its implications for brain-related disorders
JF Genome Research 
JO Genome Research 
YR 2021 
FD January 01 
VO 31 
IS 1 
SP 146 
OP 158 
DO 10.1101/gr.265769.120 
UL http://genome.cshlp.org/content/31/1/146.abstract 
AB As the most complex organ of the human body, the brain is composed of diverse regions, each consisting of distinct cell types and their respective cellular interactions. Human brain development involves a finely tuned cascade of interactive events. These include spatiotemporal gene expression changes and dynamic alterations in cell-type composition. However, our understanding of this process is still largely incomplete owing to the difficulty of brain spatiotemporal transcriptome collection. In this study, we developed a tensor-based approach to impute gene expression on a transcriptome-wide level. After rigorous computational benchmarking, we applied our approach to infer missing data points in the widely used BrainSpan resource and completed the entire grid of spatiotemporal transcriptomics. Next, we conducted deconvolutional analyses to comprehensively characterize major cell-type dynamics across the entire BrainSpan resource to estimate the cellular temporal changes and distinct neocortical areas across development. Moreover, integration of these results with GWAS summary statistics for 13 brain-associated traits revealed multiple novel trait–cell-type associations and trait-spatiotemporal relationships. In summary, our imputed BrainSpan transcriptomic data provide a valuable resource for the research community and our findings help further studies of the transcriptional and cellular dynamics of the human brain and related diseases.