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.

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.

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.

Gene targeting (GT) allows precise manipulation of genome sequences, such as knock-ins and sequence substitutions, but GT in seed plants remains a challenging task. Engineered sequence-specific nucleases (SSNs) are known to facilitate GT via homology-directed repair (HDR) in organisms. Here, we demonstrate that Cas12a and a temperature-tolerant Cas12a variant (ttCas12a) can efficiently establish precise and heritable GT at two loci in Arabidopsis thaliana (Arabidopsis) through a sequential transformation strategy. As a result, ttCas12a showed higher GT efficiency than unmodified Cas12a. In addition, the efficiency of transcriptional and translational enhancers for GT via sequential transformation strategy was also investigated. These enhancers and their combinations were expected to show an increase in GT efficiency in the sequential transformation strategy, similar to previous reports of all-in-one strategies, but only a maximum twofold increase was observed. These results indicate that the frequency of double strand breaks (DSBs) at the target site is one of the most important factors determining the efficiency of genetic GT in plants. On the other hand, a higher frequency of DSBs does not always lead to higher efficiency of GT, suggesting that some additional factors are required for GT via HDR. Therefore, the increase in DSB can no longer be expected to improve GT efficiency, and a new strategy needs to be established in the future. This research opens up a wide range of applications for precise and heritable GT technology in plants.

Asthma is a widespread airway disorder where GATA3-dependent Type-2 helper T (Th2) cells and group 2 innate lymphoid cells (ILC2s) play vital roles. Asthma-associated single nucleotide polymorphisms (SNPs) are enriched in a region located 926-970 kb downstream from GATA3 in the 10p14 (hG900). However, it is unknown how hG900 affects the pathogenesis of allergic airway inflammation. To investigate the roles of the asthma-associated GATA3 enhancer region in experimental allergic airway inflammation, we first examined the correlation between GATA3 expression and the activation of the hG900 region was analyzed by flow cytometry and ChIP-qPCR. We found that The activation of enhancers in the hG900 region was strongly correlated to the levels of GATA3 in human peripheral T cell subsets. We next generated mice lacking the mG900 region (mG900KO mice) were generated by the CRISPR-Cas9 system, and the development and function of helper T cells and ILCs in mG900KO mice were analyzed in steady-state conditions and allergic airway inflammation induced by papain or house dust mite (HDM). The deletion of the mG900 did not affect the development of lymphocytes in steady-state conditions or allergic airway inflammation induced by papain. However, mG900KO mice exhibited reduced allergic inflammation and Th2 differentiation in the HDM-induced allergic airway inflammation. The analysis of the chromatin conformation around Gata3 by circular chromosome conformation capture coupled to high-throughput sequencing (4C-seq) revealed that the mG900 region interacted with the transcription start site of Gata3 with an influencing chromatin conformation in Th2 cells. These findings indicate that the mG900 region plays a pivotal role in Th2 differentiation and thus enhances allergic airway inflammation.

Mammalian blastocyst formation involves the specification of the trophectoderm followed by the differentiation of the inner cell mass into embryonic epiblast and extra-embryonic primitive endoderm (PrE). During this time, the embryo maintains a window of plasticity and can redirect its cellular fate when challenged experimentally. In this context, we found that the PrE alone was sufficient to regenerate a complete blastocyst and continue post-implantation development. We identify an in vitro population similar to the early PrE in vivo that exhibits the same embryonic and extra-embryonic potency and can form complete stem cell-based embryo models, termed blastoids. Commitment in the PrE is suppressed by JAK/STAT signaling, collaborating with OCT4 and the sustained expression of a subset of pluripotency-related transcription factors that safeguard an enhancer landscape permissive for multi-lineage differentiation. Our observations support the notion that transcription factor persistence underlies plasticity in regulative development and highlight the importance of the PrE in perturbed development.

BACKGROUND: Recognition of enhancer-promoter Interactions (EPIs) is crucial for human development. EPIs in the genome play a key role in regulating transcription. However, experimental approaches for classifying EPIs are too expensive in terms of effort, time, and resources. Therefore, more and more studies are being done on developing computational techniques, particularly using deep learning and other machine learning techniques, to address such problems. Unfortunately, the majority of current computational methods are based on convolutional neural networks, recurrent neural networks, or a combination of them, which don\'t take into consideration contextual details and the long-range interactions between the enhancer and promoter sequences. A new transformer-based model called EPI-Trans is presented in this study to overcome the aforementioned limitations. The multi-head attention mechanism in the transformer model automatically learns features that represent the long interrelationships between enhancer and promoter sequences. Furthermore, a generic model is created with transferability that can be utilized as a pre-trained model for various cell lines. Moreover, the parameters of the generic model are fine-tuned using a particular cell line dataset to improve performance.
RESULTS: Based on the results obtained from six benchmark cell lines, the average AUROC for the specific, generic, and best models is 94.2%, 95%, and 95.7%, while the average AUPR is 80.5%, 66.1%, and 79.6% respectively.
CONCLUSIONS: This study proposed a transformer-based deep learning model for EPI prediction. The comparative results on certain cell lines show that EPI-Trans outperforms other cutting-edge techniques and can provide superior performance on the challenge of recognizing EPI.

BACKGROUND: Enhancers are important gene regulatory elements that promote the expression of critical genes in development and disease. Aberrant enhancer can modulate cancer risk and activate oncogenes that lead to the occurrence of various cancers. However, the underlying mechanism of most enhancers in cancer remains unclear. Here, we aim to explore the function and mechanism of a crucial enhancer in melanoma.
METHODS: Multi-omics data were applied to identify an enhancer (enh17) involved in melanoma progression. To evaluate the function of enh17, CRISPR/Cas9 technology were applied to knockout enh17 in melanoma cell line A375. RNA-seq, ChIP-seq and Hi-C data analysis integrated with luciferase reporter assay were performed to identify the potential target gene of enh17. Functional experiments were conducted to further validate the function of the target gene ETV4. Multi-omics data integrated with CUT&Tag sequencing were performed to validate the binding profile of the inferred transcription factor STAT3.
RESULTS: An enhancer, named enh17 here, was found to be aberrantly activated and involved in melanoma progression. CRISPR/Cas9-mediated deletion of enh17 inhibited cell proliferation, migration, and tumor growth of melanoma both in vitro and in vivo. Mechanistically, we identified ETV4 as a target gene regulated by enh17, and functional experiments further support ETV4 as a target gene that is involved in cancer-associated phenotypes. In addition, STAT3 acts as a transcription factor binding with enh17 to regulate the transcription of ETV4.
CONCLUSIONS: Our findings revealed that enh17 plays an oncogenic role and promotes tumor progression in melanoma, and its transcriptional regulatory mechanisms were fully elucidated, which may open a promising window for melanoma prevention and treatment.