Self-transcribing active regulatory region sequencing (STARR-seq) is a high-throughput sequencing method capable of simultaneously discovering and validating all enhancers within the genome. In this method, candidate sequences are inserted into plasmid vectors and electroporated into cells. Acting as both enhancers and target genes, the self-transcription of these sequences will also be enhanced by themselves. By sequencing the transcriptome and comparing the results with the non-inserted control, the locations and activity of enhancers can be determined. In traditional enhancer discovery strategies, the chromatin open regions and transcription active regions were sequenced and predicted as enhancers. However, the activity of these putative enhancers could only be validated one by one without a high-throughput method. STARR-seq solved this limitation, allowing simultaneous enhancers discovery and activity validation in a high-throughput manner. Since the introduction of STARR-seq, it has been widely used to discover enhancers and validate enhancer activity in a number of organisms and cells. In this review, we present the traditional enhancer prediction methods and the basic principles, development history, specific applications of STARR-seq, and its future prospects, aiming to provide a reference for researchers in related fields conducting enhancer studies.
自转录活性调节区测序(self-transcribing active regulatory region sequencing，STARR-seq)是一种可发现并同时验证全基因组增强子活性的高通量测序方法。其原理为：将待验证序列插入质粒载体并电转入细胞中，该序列在作为增强子提高靶基因转录的同时，其本身也作为靶基因被增强转录。通过对转录组进行测序，并对比未插入片段的测序结果，可获得增强子在基因组位置及活性的信息。在传统增强子研究方法中，通过对染色质开放区域和转录活性区域进行测序以预测增强子，但只能逐一验证预测结果，无法高通量验证增强子活性。STARR-seq技术解决了上述缺陷，可在对全基因组增强子高通量挖掘的同时，对其活性进行可靠的验证。自STARR-seq技术发明以来，已被广泛运用于不同物种与细胞中的增强子发现及活性验证研究。本文对传统增强子预测方法以及STARR-seq技术的基本原理、发展历史和具体运用进行了介绍，并对其发展前景进行展望，以期为后续增强子相关领域研究人员提供参考。.

The myeloma overexpressed gene (MYEOV) has been proposed to be a proto-oncogene due to high RNA transcript levels found in multiple cancers, including myeloma, breast, lung, pancreas and esophageal cancer. The presence of an open reading frame (ORF) in humans and other primates suggests protein-coding potential. Yet, we still lack evidence of a functional MYEOV protein. It remains undetermined how MYEOV overexpression affects cancerous tissues. In this work, we show that MYEOV has likely originated and may still function as an enhancer, regulating CCND1 and LTO1. Firstly, MYEOV 3\' enhancer activity was confirmed in humans using publicly available ATAC-STARR-seq data, performed on B-cell-derived GM12878 cells. We detected enhancer histone marks H3K4me1 and H3K27ac overlapping MYEOV in multiple healthy human tissues, which include B cells, liver and lung tissue. The analysis of 3D genome datasets revealed chromatin interactions between a MYEOV-3\'-putative enhancer and the proto-oncogene CCND1. BLAST searches and multi-sequence alignment results showed that DNA sequence from this human enhancer element is conserved from the amphibians/amniotes divergence, with a 273 bp conserved region also found in all mammals, and even in chickens, where it is consistently located near the corresponding CCND1 orthologues. Furthermore, we observed conservation of an active enhancer state in the MYEOV orthologues of four non-human primates, dogs, rats, and mice. When studying this homologous region in mice, where the ORF of MYEOV is absent, we not only observed an enhancer chromatin state but also found interactions between the mouse enhancer homolog and Ccnd1 using 3D-genome interaction data. This is similar to the interaction observed in humans and, interestingly, coincides with CTCF binding sites in both species. Taken together, this suggests that MYEOV is a primate-specific gene with a de novo ORF that originated at an evolutionarily older enhancer region. This deeply conserved putative enhancer element could regulate CCND1 in both humans and mice, opening the possibility of studying MYEOV regulatory functions in cancer using non-primate animal models.

Experimental access to cell types within the mammalian spinal cord is severely limited by the availability of genetic tools. To enable access to lower motor neurons (LMNs) and LMN subtypes, which function to integrate information from the brain and control movement through direct innervation of effector muscles, we generated single cell multiome datasets from mouse and macaque spinal cords and discovered putative enhancers for each neuronal population. We cloned these enhancers into adeno-associated viral vectors (AAVs) driving a reporter fluorophore and functionally screened them in mouse. The most promising candidate enhancers were then extensively characterized using imaging and molecular techniques and further tested in rat and macaque to show conservation of LMN labeling. Additionally, we combined enhancer elements into a single vector to achieve simultaneous labeling of upper motor neurons (UMNs) and LMNs. This unprecedented LMN toolkit will enable future investigations of cell type function across species and potential therapeutic interventions for human neurodegenerative diseases.

Coronaviruses constitute a global threat to human and animal health. It is essential to investigate the long-distance RNA-RNA interactions that approximate remote regulatory elements in strategies, including genome circularization, discontinuous transcription, and transcriptional enhancers, aimed at the rapid replication of their large genomes, pathogenicity, and immune evasion. Based on the primary sequences and modeled RNA-RNA interactions of two experimentally defined coronaviral enhancers, we detected via an in silico primary and secondary structural analysis potential enhancers in various coronaviruses, from the phylogenetically ancient avian infectious bronchitis virus (IBV) to the recently emerged SARS-CoV-2. These potential enhancers possess a core duplex-forming region that could transition between closed and open states, as molecular switches directed by viral or host factors. The duplex open state would pair with remote sequences in the viral genome and modulate the expression of downstream crucial genes involved in viral replication and host immune evasion. Consistently, variations in the predicted IBV enhancer region or its distant targets coincide with cases of viral attenuation, possibly driven by decreased open reading frame (ORF)3a immune evasion protein expression. If validated experimentally, the annotated enhancer sequences could inform structural prediction tools and antiviral interventions.

Mouse FOXA1 and GATA4 are prototypes of pioneer factors, initiating liver cell development by binding to the N1 nucleosome in the enhancer of the ALB1 gene. Using cryoelectron microscopy (cryo-EM), we determined the structures of the free N1 nucleosome and its complexes with FOXA1 and GATA4, both individually and in combination. We found that the DNA-binding domains of FOXA1 and GATA4 mainly recognize the linker DNA and an internal site in the nucleosome, respectively, whereas their intrinsically disordered regions interact with the acidic patch on histone H2A-H2B. FOXA1 efficiently enhances GATA4 binding by repositioning the N1 nucleosome. In vivo DNA editing and bioinformatics analyses suggest that the co-binding mode of FOXA1 and GATA4 plays important roles in regulating genes involved in liver cell functions. Our results reveal the mechanism whereby FOXA1 and GATA4 cooperatively bind to the nucleosome through nucleosome repositioning, opening chromatin by bending linker DNA and obstructing nucleosome packing.

UNASSIGNED: Children with severe asthma suffer from recurrent symptoms and impaired quality of life despite advanced treatment. Underlying causes of severe asthma are not completely understood, although genetic mechanisms are known to be important.
UNASSIGNED: The aim of this study was to identify gene regulatory enhancers in leukocytes, to describe the role of these enhancers in regulating genes related to severe and mild asthma in children, and to identify known asthma-related SNPs situated in proximity to enhancers.
UNASSIGNED: Gene enhancers were identified and expression of enhancers and genes were measured by Cap Analysis Gene Expression (CAGE) data from peripheral blood leukocytes from children with severe asthma (n = 13), mild asthma (n = 15), and age-matched controls (n = 9).
UNASSIGNED: From a comprehensive set of 8,289 identified enhancers, we further defined a robust sub-set of the high-confidence and most highly expressed 4,738 enhancers. Known single nucleotide polymorphisms, SNPs, related to asthma coincided with enhancers in general as well as with specific enhancer-gene interactions. Blocks of enhancer clusters were associated with genes including TGF-beta, PPAR and IL-11 signaling as well as genes related to vitamin A and D metabolism. A signature of 91 enhancers distinguished between children with severe and mild asthma as well as controls.
UNASSIGNED: Gene regulatory enhancers were identified in leukocytes with potential roles related to severe and mild asthma in children. Enhancers hosting known SNPs give the opportunity to formulate mechanistic hypotheses about the functions of these SNPs.

Enhancers are crucial in gene expression regulation, dictating the specificity and timing of transcriptional activity, which highlights the importance of their identification for unravelling the intricacies of genetic regulation. Therefore, it is critical to identify enhancers and their strengths. Repeated sequences in the genome are repeats of the same or symmetrical fragments. There has been a great deal of evidence that repetitive sequences contain enormous amounts of genetic information. Thus, We introduce the W2V-Repeated Index, designed to identify enhancer sequence fragments and evaluates their strength through the analysis of repeated K-mer sequences in enhancer regions. Utilizing the word2vector algorithm for numerical conversion and Manta Ray Foraging Optimization for feature selection, this method effectively captures the frequency and distribution of K-mer sequences. By concentrating on repeated K-mer sequences, it minimizes computational complexity and facilitates the analysis of larger K values. Experiments indicate that our method performs better than all other advanced methods on almost all indicators.

Pancreatic cancer is a malignancy arising from the endocrine or exocrine compartment of this organ. Tumors from exocrine origin comprise over 90% of all pancreatic cancers diagnosed. Of these, pancreatic ductal adenocarcinoma (PDAC) is the most common histological subtype. The five-year survival rate for PDAC ranged between 5 and 9% for over four decades, and only recently saw a modest increase to ∼12-13%, making this a severe and lethal disease. Like other cancers, PDAC initiation stems from genetic changes. However, therapeutic targeting of PDAC genetic drivers has remained relatively unsuccessful, thus the focus in recent years has expanded to the non-genetic factors underlying the disease pathogenesis. Specifically, it has been proposed that dynamic changes in the epigenetic landscape promote tumor growth and metastasis. Emphasis has been given to the re-organization of enhancers, essential regulatory elements controlling oncogenic gene expression, commonly marked my histone 3 lysine 4 monomethylation (H3K4me1). H3K4me1 is typically deposited by histone lysine methyltransferases (KMTs). While well characterized as oncogenes in other cancer types, recent work has expanded the role of KMTs as tumor suppressor in pancreatic cancer. Here, we review the role and translational significance for PDAC development and therapeutics of KMTs.

Histone modifications, known as histone marks, are pivotal in regulating gene expression within cells. The vast array of potential combinations of histone marks presents a considerable challenge in decoding the regulatory mechanisms solely through biological experimental approaches. To overcome this challenge, we have developed a method called CatLearning. It utilizes a modified convolutional neural network architecture with a specialized adaptation Residual Network to quantitatively interpret histone marks and predict gene expression. This architecture integrates long-range histone information up to 500Kb and learns chromatin interaction features without 3D information. By using only one histone mark, CatLearning achieves a high level of accuracy. Furthermore, CatLearning predicts gene expression by simulating changes in histone modifications at enhancers and throughout the genome. These findings help comprehend the architecture of histone marks and develop diagnostic and therapeutic targets for diseases with epigenetic changes.

Long or Post COVID-19 is a condition of collected symptoms persisted after recovery from COVID-19. Host genetic factors play a crucial role in developing Long COVID-19, and GWAS studies identified several SNPs/genes in various ethnic populations. In African-American population two SNPS, rs10999901 (C>T, p = 3.6E-08, OR = 1.39, MAF-0,27, GRCH38, chr10:71584799 bp) and rs1868001 (G>A, p = 6.7E-09, OR = 1.40, MAF-0.46, GRCH38, chr10:71587815 bp) and in Hispanic population, rs3759084 (A>C, p = 9.7E-09, OR = 1.56, MAF-0.17, chr12: 81,110,156 bp) are strongly associated with Long COVID-19. All these three SNPs reside in noncoding regions implying their regulatory function in the genome. In silico dissection suggests that rs10999901 and rs1868001 physically interact with the CDH23 and C10orf105 genes. Both SNPs act as distant enhancers and bind with several transcription factors (TFs). Further, rs10999901 SNP is a CpG that is methylated in CD4++ T cells and monocytes and loses its methylation due to transition from C>T. rs3759084 is located in the promoter (- 687 bp) of MYF5, acts as a distant enhancer, and physically interacts with PTPRQ. These results offer plausible explanations for their association and provide the basis for experiments to dissect the development of symptoms of Long COVID-19.