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Human brain evolution: from gene discovery to phenotype discovery.

ABSTRACT: The rise of comparative genomics and related technologies has added important new dimensions to the study of human evolution. Our knowledge of the genes that underwent expression changes or were targets of positive selection in human evolution is rapidly increasing, as is our knowledge of gene duplications, translocations, and deletions. It is now clear that the genetic differences between humans and chimpanzees are far more extensive than previously thought; their genomes are not 98% or 99% identical. Despite the rapid growth in our understanding of the evolution of the human genome, our understanding of the relationship between genetic changes and phenotypic changes is tenuous. This is true even for the most intensively studied gene, FOXP2, which underwent positive selection in the human terminal lineage and is thought to have played an important role in the evolution of human speech and language. In part, the difficulty of connecting genes to phenotypes reflects our generally poor knowledge of human phenotypic specializations, as well as the difficulty of interpreting the consequences of genetic changes in species that are not amenable to invasive research. On the positive side, investigations of FOXP2, along with genomewide surveys of gene-expression changes and selection-driven sequence changes, offer the opportunity for "phenotype discovery," providing clues to human phenotypic specializations that were previously unsuspected. What is more, at least some of the specializations that have been proposed are amenable to testing with noninvasive experimental techniques appropriate for the study of humans and apes.

SUBMITTER: Preuss TM

PROVIDER: S-EPMC3386880 | biostudies-other | 2012 Jun

REPOSITORIES: biostudies-other

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Project description:Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's "functional connectome." Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/.

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Human brain evolution: from gene discovery to phenotype discovery.

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