Modern human changes in regulatory regions implicated in cortical development

Abstract

Background: Recent paleogenomic studies have highlighted a very small set of proteins carrying modern humanspecific missense changes in comparison to our closest extinct relatives. Despite being frequently alluded to as highly relevant, species-specific differences in regulatory regions remain understudied. Here, we integrate data from paleogenomics, chromatin modification and physical interaction, and single-cell gene expression of neural progenitor cells to identify derived regulatory changes in the modern human lineage in comparison to Neanderthals/Denisovans. We report a set of genes whose enhancers and/or promoters harbor modern human single nucleotide changes and are active at early stages of cortical development. Results: We identified 212 genes controlled by regulatory regions harboring modern human changes where Neanderthals/Denisovans carry the ancestral allele. These regulatory regions significantly overlap with putative modern human positively-selected regions and schizophrenia-related genetic loci. Among the 212 genes, we identified a substantial proportion of genes related to transcriptional regulation and, specifically, an enrichment for the SETD1A histone methyltransferase complex, known to regulate WNT signaling for the generation and proliferation of intermediate progenitor cells. Conclusions: This study complements previous research focused on protein-coding changes distinguishing our species from Neanderthals/Denisovans and highlights chromatin regulation as a functional category so far overlooked in modern human evolution studies. We present a set of candidates that will help to illuminate the investigation of modern human-specific ontogenetic trajectories.

Fine-grained temporal mapping of derived high-frequency variants supports the mosaic nature of the evolution ofHomo sapiens

“…Our analysis highlights the importance of a temporal window between 300-500k that may well correspond to a significant behavioral shift in our lineage, corresponding to the Jebel Irhoud fossil, but also in other parts of the African continent, to increased ecological resource variability [53], and evidence of long-distance stone transport and pigment use [54]. Other aspects of our cognitive and anatomical modernity emerged much more recently, in the last 150000 years, and for these our analysis points to the relevance of gene expression regulation differences in recent human evolution, in line with [55,56,57].…”

“…analysis points to the relevance of gene expression regulation differences in recent human evolution, in line with [55,56,57].…”

FOS Rescues Neuronal Differentiation of Sox2-Deleted Neural Stem Cells by Genome-Wide Regulation of Common SOX2 and AP1(FOS-JUN) Target Genes

“…Finally, the human Sox2 gene homolog SOX2 , together with FOXP2 (whose mutation causes language impairment), GLI3 (part of the network in Figure 6 ), RCAN1 (involved in the pathogenesis of Down’s syndrome) and other genes, belong to a set of genes whose enhancers or promoters harbor modern human single-nucleotide changes that appeared after the split from the Neanderthal/Denisovan lineage, and have been proposed to contribute to modern human-specific characteristics [ 64 ]. In mice, SOX2 directly binds to FOXP2, GLI3, and RCAN1 regulatory elements [ 8 ], raising the intriguing possibility that changes in SOX2/AP1 co-binding may contribute to the evolution of human-specific gene regulation.…”

The cis-regulatory effects of modern human-specific variants

“…We have previously used patterns of cytosine degradation in ancient samples to reconstruct whole-genome archaic DNA methylation maps ( Gokhman et al, 2020 ; Gokhman et al, 2014 ; Gokhman et al, 2016 ). However, despite various approaches to extract regulatory information from ancient genomes ( Yan and McCoy, 2020 ; Colbran, 2019 ; Gokhman et al, 2016 ; Barker et al, 2020 ; Batyrev et al, 2019 ; Pedersen et al, 2014 ; Silvert et al, 2019 ; Moriano and Boeckx, 2020 ), our understanding of gene regulation in archaic humans remains minimal, with most archaic regulatory information being currently inaccessible ( Yan and McCoy, 2020 ). Additionally, whereas expression quantitative trait locus (eQTL) mapping can be used to identify variants that drive differential expression between individuals, it can only be applied to loci that are variable within the present-day human population.…”