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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

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BRAIN-MAGNET: A functional genomics atlas for interpretation of non-coding variants.

Ruizhi Deng¹, Elena Perenthaler¹, Anita Nikoncuk¹

¹Department of Clinical Genetics, Erasmus MC University Medical Center, Rotterdam, 3000 CA, the Netherlands.

|November 20, 2025

Summary

Researchers created a functional genomics atlas of brain development and BRAIN-MAGNET, an AI tool. This resource aids in interpreting non-coding genetic variants for neurological disorders and common traits.

Keywords:

Genomics England 100,000 Genomes project RAB7A artificial intelligence diagnostics enhancer gene regulation massively parallel reporter assay neurodevelopmental disorders neurogenetics non-coding genome whole-genome sequencing

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In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

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Published on: August 20, 2019

Area of Science:

Genomics
Neuroscience
Computational Biology

Background:

Interpreting non-coding genetic variants for diseases is challenging.
Non-coding regulatory elements (NCREs) play crucial roles in gene regulation.
Understanding NCREs is vital for deciphering genetic contributions to neurological disorders.

Purpose of the Study:

To functionally annotate NCREs in human brain development using ChIP-STARR-seq.
To develop BRAIN-MAGNET, an AI tool for predicting NCRE activity and identifying critical nucleotides.
To leverage the NCRE atlas and BRAIN-MAGNET for fine-mapping GWAS loci and prioritizing rare variants in neurogenetic disorders.

Main Methods:

Chromatin immunoprecipitation coupled to self-transcribing active regulatory region sequencing (ChIP-STARR-seq) for NCRE functional annotation.
Development and validation of BRAIN-MAGNET, a convolutional neural network for NCRE activity prediction.
Application of the functional genomics atlas and BRAIN-MAGNET to analyze common neurological traits and rare neurogenetic disorders.

Main Results:

Generated a functional genomics atlas of NCREs in human brain development, revealing insights into neural stem cells and early NCRE priming.
BRAIN-MAGNET accurately predicts NCRE activity and identifies essential nucleotides from DNA sequence.
Demonstrated the utility of BRAIN-MAGNET in fine-mapping GWAS loci and prioritizing candidate disease-causing variants.

Conclusions:

The NCRE atlas and BRAIN-MAGNET provide a powerful resource for interpreting non-coding genetic variation.
This approach can aid in identifying enhanceropathies and understanding the genetic basis of neurological disorders.
Integrating functional genomics and AI facilitates the interpretation of complex genetic data in human diseases.