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Machine learning dissection of human accelerated regions in primate neurodevelopment
Sean Whalen1, Fumitaka Inoue2, Hane Ryu3
1Gladstone Institutes, San Francisco, CA 94158, USA.
Neuron
|January 14, 2023
Summary
Machine learning revealed that human accelerated regions (HARs) variants impact chromatin and neurodevelopment. HARs likely evolved by altering factor binding, not compensatory evolution, driving rapid human brain development.
Area of Science:
- Evolutionary biology
- Genomics
- Neuroscience
Background:
- Human accelerated regions (HARs) are key genomic elements showing rapid evolution.
- Understanding HARs' functional impact on human neurodevelopment is crucial.
Purpose of the Study:
- To investigate the functional impact of human-chimpanzee variants in HARs using machine learning.
- To elucidate the evolutionary mechanisms driving HAR rapid evolution.
Main Methods:
- Machine learning (ML) analysis of variants in 2,645 HARs.
- Massively parallel reporter assays (MPRAs) in human and chimpanzee neural progenitor cells.
- Analysis of transcription factor footprints.
Main Results:
- 43% of HARs showed variants with opposing effects on chromatin state; 14% on neurodevelopmental enhancer activity.
- Species-specific HAR enhancer activity was predicted by transcription factor footprints.
- HAR activity was similar in human and chimpanzee cells, despite cis effects.
Conclusions:
- HARs likely evolved by altering their ability to bind conserved transcription factors.
- This mechanism, rather than compensatory evolution, may explain rapid HAR evolution and human neurodevelopment.
- ML effectively identified functional variants impacting human neurodevelopment within HARs.
