Massively parallel characterization of transcriptional regulatory elements

Area of Science:

• Genomics
• Epigenetics
• Molecular Biology

Background:

• Millions of candidate cis-regulatory elements (cCREs) in the human genome exhibit cell-type-specific activities crucial for health and disease.
• A functional understanding of sequence features governing cCRE activity and cell-type specificity is lacking.

Purpose of the Study:

• To functionally characterize a large set of annotated cCREs across multiple cell types.
• To identify sequence features that determine cCRE activity and cell-type specificity.
• To develop predictive models for cCRE function and variant effects.

Main Methods:

• Lentivirus-based massively parallel reporter assays (lentiMPRAs) were employed to test the regulatory activity of over 680,000 sequences.
• Experiments were conducted in three cell types (HepG2, K562, WTC11) with sequences tested in both orientations.
• Sequence-based models were developed using lentiMPRA data to predict cCRE function and regulatory motif effects.

Main Results:

• 41.7% of tested cCRE sequences demonstrated activity.
• Promoters showed strand-orientation biases and acted as non-cell-type-specific 'on switches', while enhancers exhibited weaker orientation biases but stronger tissue-specific characteristics.
• Sequence-based models achieved high accuracy in predicting cCRE function and variant effects, identifying regulatory motifs and their combinatorial actions.

Conclusions:

• This study provides an extensive catalog of functional CREs in three cell lines.
• Large-scale functional measurements effectively dissect regulatory grammar, revealing sequence features that control cCRE activity and cell-type specificity.
• The findings contribute to a deeper understanding of gene regulation in health and disease.