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W. Haubensak,  F. Ganglberger,  J. Kaczanowska,  J. M. Penninger,  A. Hess,  K. Bühler (2017)

Predicting brain functional maps from genetic information

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Society for Neuroscience (SFN) 2017 (Poster)

Abstract

Linking genetic information to brain anatomy allows for the computational exploration of molecular-to-systems level organization of brain function. Here, we fused publicly available brain gene expression maps and connectivity data with functionally related gene sets. We find that the functional genetic load accumulates in specific nodes in the brain and associates neuronal networks with specific multigenic functions. These maps recapture known functional anatomical annotations from literature and functional MRI data. When applied to meta data from mouse QTLs and human neuropsychiatric databases, our method predicts functional maps underlying behavioral or psychiatric traits. We show that it is possible to predict functional neuroanatomy from mouse and human genetic meta data and provide a discovery tool for high throughput functional exploration of brain anatomy in silico.

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