Predicting genome-wide tissue-specific enhancers via combinatorial transcription factor genomic occupancy analysis

Huma Shireen, Fatima Batool, Hizran Khatoon, Nazia Parveen, Noor Us Sehar, Irfan Hussain, Shahid Ali, Amir Ali Abbasi

Research output: Contribution to journalArticlepeer-review

Abstract

Enhancers are non-coding cis-regulatory elements crucial for transcriptional regulation. Mutations in enhancers can disrupt gene regulation, leading to disease phenotypes. Identifying enhancers and their tissue-specific activity is challenging due to their lack of stereotyped sequences. This study presents a sequence-based computational model that uses combinatorial transcription factor (TF) genomic occupancy to predict tissue-specific enhancers. Trained on diverse datasets, including ENCODE and Vista enhancer browser data, the model predicted 25 000 forebrain-specific cis-regulatory modules (CRMs) in the human genome. Validation using biochemical features, disease-associated SNPs, and in vivo zebrafish analysis confirmed its effectiveness. This model aids in predicting enhancers lacking well-characterized chromatin features, complementing experimental approaches in tissue-specific enhancer discovery.

Original languageEnglish
JournalFEBS Letters
DOIs
Publication statusAccepted/In press - 2024

Keywords

  • cis-regulatory modules
  • DNase I hypersensitive sites
  • forebrain
  • histone modification
  • transcription factors
  • zebrafish

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