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Epigenetic Regulation

Epigenetic Regulation

Epigenetic changes alter the physical structure of the DNA without changing the genetic sequence and often regulate whether genes are turned on or off. This regulation ensures that each cell produces only proteins necessary for its function. For example, proteins that promote bone growth are not produced in muscle cells. Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
X-chromosome...

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Related Experiment Video

Updated: Sep 20, 2025

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons

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Predicting expression-altering promoter mutations with deep learning.

Kishore Jaganathan¹, Nicole Ersaro¹, Gherman Novakovsky¹

¹Illumina Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA, USA.

Science (New York, N.Y.)

|May 29, 2025

Summary

This summary is machine-generated.

A new deep neural network, PromoterAI, identifies noncoding promoter variants that cause rare genetic diseases. These variants impact gene expression and are under negative selection, explaining 6% of the genetic burden in rare diseases.

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Area of Science:

Genetics
Bioinformatics
Genomics

Background:

Exome sequencing diagnoses only a minority of rare genetic diseases.
Unrecognized pathogenic variants may exist in noncoding DNA sequences.

Purpose of the Study:

To develop a deep neural network, PromoterAI, for identifying noncoding promoter variants that dysregulate gene expression.
To assess the impact of these variants on gene expression and their role in rare diseases.

Main Methods:

Developed PromoterAI, a deep neural network for predicting expression-altering promoter variants.
Analyzed RNA and protein expression data from thousands of individuals.
Investigated negative selection acting on these variants.
Validated functional impact using reporter assays.

Main Results:

PromoterAI accurately identifies noncoding promoter variants.
Variants with predicted expression-altering consequences show outlier expression levels.
These variants are under strong negative selection in human populations.
Clinically relevant genes in rare disease patients are enriched for these variants.

Conclusions:

Noncoding promoter variants significantly contribute to rare genetic diseases.
PromoterAI is a valuable tool for diagnosing rare genetic disorders.
Promoter variation accounts for an estimated 6% of the genetic burden in rare diseases.