A Comparative Analysis of Super-Enhancers and Broad H3K4me3 Domains in Pig, Human, and Mouse Tissues

Peng, Yanling; Kang, Huifang; Jia, Luo; Zhang, Yubo

doi:10.3389/fgene.2021.701049

Cited by 6 publications

(6 citation statements)

References 35 publications

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“…Furthermore, we must acknowledge that although the PorcineAI-enhancer framework performs well in practical applications, this study still has its limitations. Firstly, due to the diversity of pig breeds [ 56 ], tissue specificity [ 57 , 88 ], and developmental stages in reality, further validation and verification of the enhancer prediction capability need to be conducted under controlled conditions to ensure the reliability of the predictions. This represents the next step for model improvement, namely fine-tuning by incorporating Chip-seq-detected enhancer sequences from different breeds, tissues, and cells, expanding its applicability to more refined application scenarios.…”

Section: Discussionmentioning

confidence: 99%

“…Although several scientists have conducted ChIP-seq experiments to explore enhancer elements in pigs [ 47 , 56 , 57 , 58 ], most of these experiments lack collaborative support from other high-throughput data and functional validation in the laboratory. This phenomenon has resulted in a limited number of reliable enhancers in pigs, with varying quality.…”

Section: Methodsmentioning

confidence: 99%

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PorcineAI-Enhancer: Prediction of Pig Enhancer Sequences Using Convolutional Neural Networks

Wang,

Zhang,

Chen

et al. 2023

Animals

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Understanding the mechanisms of gene expression regulation is crucial in animal breeding. Cis-regulatory DNA sequences, such as enhancers, play a key role in regulating gene expression. Identifying enhancers is challenging, despite the use of experimental techniques and computational methods. Enhancer prediction in the pig genome is particularly significant due to the costliness of high-throughput experimental techniques. The study constructed a high-quality database of pig enhancers by integrating information from multiple sources. A deep learning prediction framework called PorcineAI-enhancer was developed for the prediction of pig enhancers. This framework employs convolutional neural networks for feature extraction and classification. PorcineAI-enhancer showed excellent performance in predicting pig enhancers, validated on an independent test dataset. The model demonstrated reliable prediction capability for unknown enhancer sequences and performed remarkably well on tissue-specific enhancer sequences.The study developed a deep learning prediction framework, PorcineAI-enhancer, for predicting pig enhancers. The model demonstrated significant predictive performance and potential for tissue-specific enhancers. This research provides valuable resources for future studies on gene expression regulation in pigs.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

PorcineAI-Enhancer: Prediction of Pig Enhancer Sequences Using Convolutional Neural Networks

Wang,

Zhang,

Chen

et al. 2023

Animals

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“…In a study comparing H3K4me3‐BDs and non‐broad H3K4me3 regions in pig, mouse and human they found that H3K4me3‐BDs marked cell‐type‐specific genes in the brain and adipose tissue for all three species. [ 84 ] Further investigation into pig H3K4me3‐BDs identified between 99 and 309 H3K4me3‐BDs that shared orthologous regions in human and mouse, indicating that they might be functionally conserved. Using ChIP‐seq data from hESC H1 and mESC, Kurum et al.…”

Section: Extension Of Promoter Signatures Demarcates Broad H3k4 Domainsmentioning

confidence: 99%

Broad H3K4me3 domains: Maintaining cellular identity and their implication in super‐enhancer hijacking

et al. 2023

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The human and mouse genomes are complex from a genomic standpoint. Each cell has the same genomic sequence, yet a wide array of cell types exists due to the presence of a plethora of regulatory elements in the non‐coding genome. Recent advances in epigenomic profiling have uncovered non‐coding gene proximal promoters and distal enhancers of transcription genome‐wide. Extension of promoter‐associated H3K4me3 histone mark across the gene body, known as a broad H3K4me3 domain (H3K4me3‐BD), is a signature of constitutive expression of cell‐type‐specific regulation and of tumour suppressor genes in healthy cells. Recently, it has been discovered that the presence of H3K4me3‐BDs over oncogenes is a cancer‐specific feature associated with their dysregulated gene expression and tumourigenesis. Moreover, it has been shown that the hijacking of clusters of enhancers, known as super‐enhancers (SE), by proto‐oncogenes results in the presence of H3K4me3‐BDs over the gene body. Therefore, H3K4me3‐BDs and SE crosstalk in healthy and cancer cells therefore represents an important mechanism to identify future treatments for patients with SE driven cancers.

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“…In addition, 30 shared transcription factors and BRD4 were found to be conserved activators of mammalian pluripotency-associated SEs in parallel with three pluripotency-associated SEs (SE-SOX2, SE-PIM1, and SE-FGFR1) that are highly conserved in mammals [ 95 ]. In SE conservation studies, it is probably more accurate to speak of functional conservation and/or structural conservation in regard to the pool of regulated genes both in studying the evolution of enhancers in mammals [ 96 , 97 ] and in vertebrates in general when, for example, comparing the results to zebrafish [ 98 ]. Nevertheless, the genomic distribution of zebrafish TEs and SEs differs from that of mammalian regions.…”

Section: Constitutive Super-enhancers In Different Cell Typesmentioning

confidence: 99%

Experimental Validation and Prediction of Super-Enhancers: Advances and Challenges

Kravchuk

Ashniev

Гладкова

et al. 2023

Cells

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Super-enhancers (SEs) are cis-regulatory elements of the human genome that have been widely discussed since the discovery and origin of the term. Super-enhancers have been shown to be strongly associated with the expression of genes crucial for cell differentiation, cell stability maintenance, and tumorigenesis. Our goal was to systematize research studies dedicated to the investigation of structure and functions of super-enhancers as well as to define further perspectives of the field in various applications, such as drug development and clinical use. We overviewed the fundamental studies which provided experimental data on various pathologies and their associations with particular super-enhancers. The analysis of mainstream approaches for SE search and prediction allowed us to accumulate existing data and propose directions for further algorithmic improvements of SEs’ reliability levels and efficiency. Thus, here we provide the description of the most robust algorithms such as ROSE, imPROSE, and DEEPSEN and suggest their further use for various research and development tasks. The most promising research direction, which is based on topic and number of published studies, are cancer-associated super-enhancers and prospective SE-targeted therapy strategies, most of which are discussed in this review.

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A Comparative Analysis of Super-Enhancers and Broad H3K4me3 Domains in Pig, Human, and Mouse Tissues

Cited by 6 publications

References 35 publications

PorcineAI-Enhancer: Prediction of Pig Enhancer Sequences Using Convolutional Neural Networks

PorcineAI-Enhancer: Prediction of Pig Enhancer Sequences Using Convolutional Neural Networks

Broad H3K4me3 domains: Maintaining cellular identity and their implication in super‐enhancer hijacking

Experimental Validation and Prediction of Super-Enhancers: Advances and Challenges

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