Multiomics and deep learning dissect regulatory syntax in human development

Area of Science:

• Genomics
• Developmental Biology
• Computational Biology

Background:

• Transcription factors regulate cell identity by binding DNA, influencing chromatin accessibility and gene expression.
• Existing human developmental datasets lack single-cell resolution across multiple organs and modalities.
• Understanding cis-regulatory elements is crucial for deciphering gene control.

Purpose of the Study:

• To create a comprehensive single-cell atlas of chromatin accessibility and gene expression in human fetal development.
• To identify sequence motifs governing chromatin accessibility and transcription factor cooperativity.
• To explore the role of motif syntax in cell-type-specific gene regulation and interpret genetic variants.

Main Methods:

• Generated a single-cell atlas from 817,740 fetal cells across 12 organs, profiling chromatin accessibility and gene expression.
• Utilized deep learning models to predict chromatin accessibility from DNA sequence and identify regulatory motifs.
• Analyzed motif syntax, including composite motifs, and their impact on transcription factor cooperativity.
• Interpreted genetic variants using model-based approaches to assess their effects on gene expression.

Main Results:

• The Human Development Multiomic Atlas comprises 203 cell types and over 1 million candidate cis-regulatory elements with organ-specific enhancer activity.
• Identified a lexicon of DNA sequence motifs and their 'hard' and 'soft' syntactic rules governing chromatin accessibility.
• Demonstrated that motif disruption correlates with gene expression changes, revealing regulatory logic.
• Uncovered ubiquitous motifs that inhibit chromatin accessibility.

Conclusions:

• Motif syntax dictates cell-type-specific chromatin accessibility and gene regulation during human development.
• The atlas provides a foundational resource for decoding cis-regulatory logic and interpreting genetic variation.
• This work deepens our understanding of how transcription factors establish cell identity through precise DNA interactions.