Precision biology has emerged from precision medicine, aiming to gain a more complete and accurate understanding of biological systems through the utilization of advanced technologies and methods. The concept of precision medicine was introduced by the National Institutes of Health (NIH) in 2015, with the goal of providing personalized information to individuals and their families to improve health outcomes [27]. Precision medicine represents a novel approach to disease prevention and management [1,28] that considers individual genetic, environmental, and lifestyle differences. Its primary focus is on treating cancer, while the long-term objective is to establish a new model of medicine that emphasizes individualized engagement, data sharing, and privacy protection [29,30]. The integration of artificial intelligence (AI) and machine learning (ML) makes it possible to employ computational approaches in precision medicine [31,32]. These approaches enable the identification of drugs that can be repurposed for other diseases, utilizing diverse sources of data ranging from molecular signatures to the effects of drugs at the molecular and system levels. In precision biology, advanced technologies and methods are employed, including high-throughput experimental techniques, such as genome sequencing, proteomics, metabolomics, and single-cell analysis. These techniques generate large amounts of data, which can then be analyzed using computational methods [27,33].

In the previous section, we mentioned that subtle changes in gene expression patterns resulting from interactions between genes and transcriptional elements (especially enhancers) play a direct role in precision biology research. To investigate these “minor changes”, a number of 3D genomics techniques have been developed. These include chromosome conformation capture (3C)-based technologies, such as chromosome conformation capture-on-chip (4C) [34], chromosome conformation capture carbon copy (5C) [35], high-throughput/resolution chromosome conformation capture (Hi-C) [36], Single-cell Hi-C [37], eHi-C [38], in 3D genomics, chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) [39], and related methods, which have enabled the discovery of transcriptional regulatory elements, especially enhancers, and their effects on gene expression (Figure 1). In addition, various methods, such as self-transcribing active regulatory region sequencing (STARR-seq), chromatin immunoprecipitation sequencing (ChIP-seq) [40,41], DNase-seq, site-specific integration FACS-sequencing (SIF-seq), assay for transposase accessible chromatin with high-throughput sequencing (ATAC-seq), robust statistical estimation (ROSE) algorithm, in situ Hi-C followed by chromatin immunoprecipitation (HiChIP), have been widely used for the identification and annotation of enhancers and super enhancers (annotations of enhancer and super enhancer are described in detail in Section 4). These techniques significantly contribute to the development of 3D genomics.

For instance, researchers have utilized Hi-C and ChIP-seq to investigate the impact of MED23 mutations on enhancer activation and chromatin conformation. These studies have provided insights into the pathogenic mutations of MED23 and the role of mediator in transcriptional control based on enhancer topology [42]. Single-cell Hi-C has been used to systematically map the three-dimensional genomic and dynamic epigenetic profiles of macrophages during differentiation and immune response [43]. This approach has revealed the potential mechanisms underlying the reprogramming of gene expression profiles in immune cells (Figure 1). The SIF-seq has been developed to evaluate enhancer activity in various disease-associated cell types. It has successfully identified cardiac enhancers in in vitro differentiated cardiomyocytes and neuronal enhancers in neural progenitor cells [44], contributing to our understanding of disease-related mechanisms. STARR-seq has been instrumental in identifying regulatory variants associated with cancer susceptibility [45]. It has contributed to the interpretation of genome-wide association studies (GWAS) results and provided valuable information for cancer risk assessment. Moreover, these cutting-edge technologies have also been used to uncover potential target enhancers for agronomic traits in plants, such as salt stress tolerance [46], facilitating the achievement of precision crop breeding. These advanced techniques have significantly expanded scientists’ knowledge of the relationship between genome-wide spatial conformation and gene transcriptional regulation, thereby driving the progress of precision biology.

On the other hand, recent changes in sequencing technology have led to the rapid development of single-cell sequencing [37], enabling researchers to gain insights into cellular information at the individual cell level and creating new opportunities for studying enhancer-mediated transcriptional regulation. Single-cell omics and imaging techniques have become essential tools for the realization of precision biology [47,48,49]. These techniques, including single-cell RNA sequencing (scRNA-Seq), single-cell DNA sequencing (scDNA-Seq), and single-cell assay for transposase accessible chromatin with high-throughput sequencing (scATAC-Seq), as well as various in situ analysis methods, allow for the measurement of gene expression, mutations, epigenetics, and open chromatin regions. Such information is crucial for resolving tumor heterogeneity, characterizing the tumor microenvironment, and identifying rare cell subpopulations [50,51]. Furthermore, advancements in imaging techniques have facilitated the study of single-cell imaging, overcoming the limitations of single-cell histology techniques in capturing and visualizing the spatial relationships of cells within their native tissue environment [52]. Spatially single-cell epigenomics approaches have enabled the labeling of histone modifications of active promoters, putative enhancers, and silent promoters, enabling spatial analysis of epigenetic modifications and DNA-binding proteins [53]. These techniques have advanced our understanding of how gene expression is regulated spatially and temporally by the epigenome. By simultaneously capturing genomic output at different levels, single-cell techniques allow scientists to document cellular properties and functions [54,55]. Epigenomic technologies play a crucial role in understanding cellular diversity and uncovering mechanisms of gene regulation. This, in turn, contributes to the discovery of enhancer-mediated transcriptional regulation. It has been observed that there is a synergistic effect of tumorigenesis among super enhancers [56]. Therefore, understanding the mechanism of enhancer-mediated transcriptional regulation from a single-cell perspective can provide a new level of understanding of cell fate determination, identity, and function in normal development, physiology, and disease. Careful and comprehensive analysis of individual cells within a population will likely completely change the way we describe and treat disease and may even explain some of the different responses that occur in patients with similar conditions and treatment processes.

Developments in bioinformatics and computational biology have further improved data availability and accuracy, contributing to accurate screening enhancers and enhancer-promoter interactions from large sequencing datasets [57,58]. Furthermore, the Human Genome Project (HGP) [59], the Human Genome Encyclopedia (ENCODE) Project [13], and the ongoing 4D Nucleosome Project [60] are progressing well thanks to the infrastructure of systems biology (Figure 1). These initiatives provide valuable resources for precisely targeting, screening, and comprehensively characterizing the enhancer-mediated transcriptional regulation network.

The advancements in precision biology have yielded remarkable progress in medical research, leading to improved healthcare standards and overall public health. In the pursuit of precision biology, to explore the individual differences and mutations that exist in individual genomes and how these differences and mutations affect the physiological and pathological characteristics of cells, tissues, and individuals, transcriptional regulation, especially enhancer-mediated transcriptional regulation, serves as a crucial tool and platform for precision biology.

Transcriptional regulation is commonly believed that occurs at two interrelated levels: The first involves transcription factors and the transcriptional apparatus, while the second involves chromatin and its regulators, including enhancers. Researchers are currently striving to elucidate how mammalian gene expression is temporally and spatially constrained by integrating these two aspects [16,61].

4. The Role of Different Enhancers in Transcriptional Regulation

4.1. Typical Enhancers

4.2. Annotation of Typical Enhancers

4.3. Super Enhancer