Human-specific features of spatial gene expression and regulation in eight brain regions

Abstract

Molecular maps of the human brain alone do not inform us of the features unique to humans. Yet, the identification of these features is important for understanding both the evolution and nature of human cognition. Here, we approached this question by analyzing gene expression and H3K27ac chromatin modification data collected in eight brain regions of humans, chimpanzees, gorillas, a gibbon, and macaques. An analysis of spatial transcriptome trajectories across eight brain regions in four primate species revealed 1851 genes showing human-specific transcriptome differences in one or multiple brain regions, in contrast to 240 chimpanzee-specific differences. More than half of these human-specific differences represented elevated expression of genes enriched in neuronal and astrocytic markers in the human hippocampus, whereas the rest were enriched in microglial markers and displayed human-specific expression in several frontal cortical regions and the cerebellum. An analysis of the predicted regulatory interactions driving these differences revealed the role of transcription factors in species-specific transcriptome changes, and epigenetic modifications were linked to spatial expression differences conserved across species.

Single-cell-resolution transcriptome map of human, chimpanzee, bonobo, and macaque brains

“…1H). Overall, in agreement with previous works [Sousa et al, 2017a;Xu et al, 2018], more differences mapped to the human lineage (the average n=712) than to the chimpanzee (n=641) or bonobo (n=640) lineages.…”

“…While the expression differences shared among brain regions often represent molecular and functional changes not specific to the brain [Khaitovich et al, 2004a;Khaitovich et al, 2005], differences particular to individual brain regions tend to be associated with specific brain functions [Khaitovich et al, 2004a]. Recent studies examining eight and 16 brain regions in humans and closely related NHPs expanded these results further by revealing the rapid expression evolution of several subcortical regions in addition to the neocortical areas [Sousa et al, 2017;Xu et al, 2018].…”

Systems Biology Perspectives for Studying Neurodevelopmental Events

“…Even if few percentages of genes have different trajectories in non-human primate and human in contrast to rodent, this model can help to understand brain development, but it cannot model all features found in human [79,81]. In fact, comparison between non-human primate and human brains transcriptome analysis showed human specificity in gene expression profiling [82][83][84] with demonstration that genes differentially expressed are principally upregulated in human brains in contrast to other organs [85,86]. In addition, the transcriptome remodeling during postnatal periods appears delayed in human brain comparing to non-human primate [87].…”

Evolutionary Transcriptome Analysis Based on Differentially Expressed (DE) Genes

“…With enormous amounts of transcriptome (RNA-seq) data from multiple tissues with diverse species available, it is the exciting time for evolutionary biologists to address how gene regulation plays a key role in phenotypic innovations (King and Wilson 1975;Lehner 2013) (e.g., Wang, et al 2009;Brawand, et al 2011;McCarthy, et al 2012;Necsulea and Kaessmann 2014;Xu, et al 2018;Cardoso-Moreira, et al 2019). To help achieve this goal, development of statistically-sound methods that enable researchers to study the pattern of transcriptome evolution is desirable (Gu and Su 2007;Pereira, et al 2009;Gu, et al 2013;Gu 2016;Ruan, et al 2016;Gu, et al 2017;Sudmant, et al 2015;Yang et al 2018;Gu et al 2019).…”

“…Each statistical hypothesis testing (usually for each gene) results in a p-value summarizing the level of statistical significance of the observed differential gene expression. Xu et al (2018) conducted an analysis to predict differentially expressed (DE) genes between the human and chimpanzee in several brain regions. Their study indicated that detection of DE genes between species is a valuable approach to understanding the pattern of transcriptome evolution.…”