Scientists Leverage Machine Learning to Decode Gene Regulation in Human Brain Cells
In groundbreaking research, scientists from Gladstone Institutes and University of California, San Francisco (UCSF) have utilized high-throughput experiments and machine learning to analyze over 100,000 sequences in human brain cells. Their efforts have led to the identification of more than 150 variants that are likely linked to various diseases affecting brain development and psychiatric disorders.
The study, published in the journal Science, marks a significant advancement in our understanding of genetic changes that influence brain development and contribute to conditions like schizophrenia and autism spectrum disorder. Senior Investigator Katie Pollard, PhD, stated that the team collected a vast amount of data from noncoding regions of DNA known to play crucial roles in brain development and disease. By conducting functional tests on these sequences, they were able to pinpoint specific alterations that could impact gene activity and potentially lead to disease.
Collaborating with Nadav Ahituv, PhD, and Tomasz Nowakowski, PhD, the scientists identified 164 variants associated with psychiatric disorders and discovered 46,802 sequences with enhancer activity in developing neurons, indicating their role in controlling gene function. Ahituv highlighted the potential of leveraging these enhancers to treat diseases caused by malfunctioning genes, emphasizing the opportunity to enhance gene function through these regulatory elements.
The study also showcased two other significant findings. Firstly, the researchers validated the effectiveness of a brain organoid developed from human stem cells as a reliable model for studying gene regulatory activity, with results closely resembling those observed in real human brain tissue. Secondly, by employing machine learning to analyze DNA sequence data and gene regulatory activity, the team successfully trained a computer model to predict the impact of specific sequences on gene expression activity. This innovative approach enables researchers to anticipate experimental outcomes, accelerating the pace of discoveries and optimizing resource utilization.
The study, carried out as part of the PsychENCODE Consortium, aligns with the consortium’s mission to advance understanding of psychiatric disorders and facilitate the development of novel treatment strategies through comprehensive analyses of human brain data. As the research unfolds, it sheds light on previously unexplored aspects of brain development and gene regulation, offering new avenues for exploring therapeutic interventions for complex neurological conditions.
The groundbreaking study, Massively Parallel Characterization of Regulatory Elements in the Developing Human Cortex, published in Science, signifies a significant step forward in deciphering the intricate mechanisms underlying brain development and psychiatric disorders. With a focus on leveraging cutting-edge technologies and interdisciplinary collaborations, the research holds immense promise for driving transformative advancements in the field of neuroscience and potentially revolutionizing our approach to treating neurological disorders.
