Comparative Genomics and Epigenomics of Transcriptional Regulation

Huaijun Zhou, Emily Clark, Dailu Guan, Sandrine Lagarrigue, Lingzhao Fang, Hao Cheng, Christopher K Tuggle, Muskan Kapoor, Ying Wang, Elisabetta Giuffra, Giorgia Egidy

Research output: Contribution to journalReview articlepeer-review

Abstract / Description of output

Transcriptional regulation in response to diverse physiological cues involves complicated biological processes. Recent initiatives that leverage whole genome sequencing and annotation of regulatory elements significantly contribute to our understanding of transcriptional gene regulation. Advances in the data sets available for comparative genomics and epigenomics can identify evolutionarily constrained regulatory variants and shed light on noncoding elements that influence transcription in different tissues and developmental stages across species. Most epigenomic data, however, are generated from healthy subjects at specific developmental stages. To bridge the genotype-phenotype gap, future research should focus on generating multidimensional epigenomic data under diverse physiological conditions. Farm animal species offer advantages in terms of feasibility, cost, and experimental design for such integrative analyses in comparison to humans. Deep learning modeling and cutting-edge technologies in sequencing and functional screening and validation also provide great promise for better understanding transcriptional regulation in this dynamic field.

Original languageEnglish
JournalAnnual Review of Animal Biosciences
Early online date20 Nov 2024
DOIs
Publication statusE-pub ahead of print - 20 Nov 2024

Keywords / Materials (for Non-textual outputs)

  • Transcriptional regulation
  • non-coding variants
  • regulatory elements
  • molecule QTL
  • comparative genomics and epigenomics
  • deep learning modeling

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