Forebrain Enhancers Track Hub Description

From cellular differentiation to organismal development, the spatiotemporal expression of tissue-specific genes is driven by regulatory DNA elements. Among these, enhancers—also referred to as distal-acting cis-regulatory modules (CRMs)—are essential for increasing gene expression. Enhancers are cis-acting DNA sequences that are functional irrespective of their orientation and exhibit variable distances from their target genes.

Challenges in Annotating Tissue-Specific Enhancers

Given the critical role of tissue-specific enhancers in development and disease, annotating the human genome with tissue- or cell-type-specific enhancers has garnered significant attention. However, this task presents several challenges:

• Vast Search Space: Enhancers are dispersed throughout the 98.5% of the human genome that is non-protein-coding, creating a vast search space.
• Variable Positioning: Enhancers can regulate target genes from upstream, downstream, or intronic locations, and may skip proximal genes to influence more distant ones.
• Complex Gene Regulation: Some enhancers simultaneously regulate multiple genes, adding to the complexity of their annotation.
• Lack of a Universal Sequence Code: Unlike protein-coding genes, enhancers lack a defined sequence code, making prediction highly nontrivial.

Traditional Approaches and Limitations

Traditional enhancer prediction approaches, such as those based on evolutionary conservation or biochemical markers, face inherent limitations. Evolutionary methods often miss lineage-specific enhancers, while biochemical marks are not always definitive indicators of enhancer activity and can appear stochastically.

Our Approach

To address these challenges, we recently developed and published (FEBS Letters, https://doi.org/10.1002/1873-3468.15030) a DNA-sequence-based enhancer prediction pipeline tailored to tissue-specific transcription factor (TF) occupancy patterns. This sequence-based model improves enhancer prediction accuracy by incorporating the following:

• A curated set of tissue- or cell-type-relevant transcription factors.
• Well-characterized binding motifs for the selected TFs.
• A benchmark dataset of enhancers validated in vivo or in vitro for the relevant tissue or cell type.

Results: Predicting Forebrain Enhancers

Using the mammalian forebrain as a model, we applied this approach to predict 25,000 distinct forebrain enhancers within the non-coding and non-repetitive regions of the human genome (hg19).

Functional Evaluation of Predicted Forebrain Enhancers

Our predicted enhancer datasets were evaluated by intersecting predictions with the following:

• Active brain enhancer-associated chromatin marks.
• DNase hypersensitivity (HS) site data from brain cell lines.
• GWAS-based brain-specific SNP data.

Additionally, subsets of the predictions were experimentally validated through in vivo zebrafish transgenic models. Evolutionary analysis revealed that >85% of these enhancers are conserved only in mammals or primates, underscoring their lineage-specific functionality.

Utility of This Track Hub

This track hub presents the genomic coordinates of these 25,000 predicted forebrain enhancers (CRMs) in the hg19 genome assembly. Researchers can visualize and analyze these enhancers in the UCSC Genome Browser alongside abundant genomic and epigenomic datasets. This hub enables the following:

• Investigating Pathological and Developmental Mechanisms: Explore the genomic basis of brain-related diseases and developmental processes.
• Examining Evolutionary Significance: Study the gene-regulatory foundations of mammalian and primate brain evolution.

Access the Track Hub

Access the track hub and begin exploring these predicted forebrain enhancers in the context of gene bodies and genomic regions of interest:

Citation

While utilizing these data for your publications, please remember to cite our relevant paper:

Shireen, H., Batool, F., Khatoon, H., Parveen, N., Sehar, N.U., Noor, U.S., Hussain, I., Ali, S., Abbasi, A. A. (2024). Predicting genome-wide tissue-specific enhancers via combinatorial transcription factor genomic occupancy analysis. FEBS Letters. https://doi.org/10.1002/1873-3468.15030

Contact Information

Name: Amir Ali Abbasi

Website: https://ncb.qau.edu.pk/index.php/dr-amir-ali-abbasi.html

Email: abbasiam@qau.edu.pk