Abstract

Recent advances in paleo-genetics allowed the identification of protein-coding changes apparently fixed on the lineage leading to Homo sapiens, by comparing genomes of present-day humans and archaic hominins. Although such genomic differences are thought to make key contributions to distinctly modern human traits, experimental validation of their potential impact was so far restricted to functional assays and model organisms. With the availability of large-scale genetically informative population databases, it now becomes possible to identify present-day carriers of rare archaic alleles of interest and to directly assess putative phenotypic consequences in living humans. We queried exome sequencing data of around half a million people in the UK Biobank in search of carriers of archaic alleles at 37 genomic positions with supposedly fixed human-specific changes. This search yielded 103 carriers of the archaic allele for 17 positions, with diverging allele counts across ancestries. We contrasted carriers of an exemplary archaic allele in SSH2 with a curated set of non-carriers, observing no deviation from the norm in a range of health, psychological, and cognitive traits. We also identified 62 carriers of the archaic allele of a missense change in the TKTL1 gene, previously reported to have large effects on cortical neurogenesis based on functional analyses in brain organoids and animal models. However, human carriers of the archaic TKTL1 allele did not show differences in anatomical brain measures and qualification level, compared to non-carriers. These results highlight the importance of investigating diverse ancestral populations for a more accurate representation of shared human variation and challenge the notion of permanently fixed genetic changes that set Homo sapiens apart from Neandertals and Denisovans. Lastly, we propose that future investigations should assess effects of multiple archaic alleles in aggregate, since any single genetic change is unlikely to itself explain the emergence of complex human traits.Competing Interest StatementThe authors have declared no competing interest.

Abstract

Compared with our fossil ancestors and Neandertal kin, modern humans have evolved a distinctive skull shape, with a rounder braincase and more delicate face. Competing explanations for this rounder skull have either linked it to changes in brain organisation, or seen it as a by-product of gracilization (evolution of thinner and lighter skeletal anatomy). Here, we combined palaeoanthropological data from hominin fossils and imaging genomics data from living humans to gain insight into evolutionary and developmental mechanisms shaping this uniquely modern human phenotype. We analysed endocranial globularity from magnetic resonance imaging (MRI) brain scans and genetic data of more than 33,000 adults. We discovered 28 genomic loci significantly associated with endocranial globularity. There was genetic overlap with the brain’s ventricular system, white matter microstructure, and sulcal morphology, and with multivariate genetic analyses of reading/language skills, but not with general cognition. The associated genes exhibited enriched expression in the brain during prenatal development and early childhood. The connection to the ventricular system hints at a role for cerebrospinal fluid pressure in shaping the endocranium during development. Genes linked to endocranial globularity also showed enhanced expression in the cardiovascular and female reproductive systems. This finding suggests co-evolutionary pathways whereby changes impacting factors such as energy needs, pregnancy, or fertility concurrently shape the brain and its structure.Competing Interest StatementThe authors have declared no competing interest.

Abstract

Language is supported by a distributed network of brain regions with a particular contribution from the left hemisphere. A multi-level understanding of this network requires studying the genetic architecture of its functional connectivity and hemispheric asymmetry. We used resting state functional imaging data from 29,681 participants from the UK Biobank to measure functional connectivity between 18 left-hemisphere regions implicated in multimodal sentence-level processing, as well as their homotopic regions in the right-hemisphere, and interhemispheric connections. Multivariate genome-wide association analysis of this total network, based on common genetic variants (with population frequencies above 1%), identified 14 loci associated with network functional connectivity. Three of these loci were also associated with hemispheric differences of intrahemispheric connectivity. Polygenic dispositions to lower language-related abilities, dyslexia and left-handedness were associated with generally reduced leftward asymmetry of functional connectivity, but with some trait- and connection-specific exceptions. Exome-wide association analysis based on rare, protein-altering variants (frequencies < 1%) suggested 7 additional genes. These findings shed new light on the genetic contributions to language network connectivity and its asymmetry based on both common and rare genetic variants, and reveal genetic links to language-related traits and hemispheric dominance for hand preference.