Chromatin architecture influences transcription by modulating the physical access of regulatory factors to DNA, playing fundamental roles in cell identity. Studies on dopaminergic differentiation have identified coding genes, but the relationship with non-coding genes or chromatin accessibility remains elusive. Using RNA-Seq and ATAC-Seq we profiled differentially expressed transcripts and open chromatin regions during early dopaminergic neuron differentiation. Hierarchical clustering of differentially expressed genes, resulted in 6 groups with unique characteristics. Surprisingly, the abundance of long non-coding RNAs (lncRNAs) was high in the most downregulated transcripts, and depicted positive correlations with target mRNAs. We observed that open chromatin regions decrease upon differentiation. Enrichment analyses of accessibility depict an association between open chromatin regions and specific functional pathways and gene-sets. A bioinformatic search for motifs allowed us to identify transcription factors and structural nuclear proteins that potentially regulate dopaminergic differentiation. Interestingly, we also found changes in protein and mRNA abundance of the CCCTC-binding factor, CTCF, which participates in genome organization and gene expression. Furthermore, assays demonstrated co-localization of CTCF with Polycomb-repressed chromatin marked by H3K27me3 in pluripotent cells, progressively decreasing in neural precursor cells and differentiated neurons. Our work provides a unique resource of transcription factors and regulatory elements, potentially involved in the acquisition of human dopaminergic neuron cell identity.
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http://dx.doi.org/10.1038/s41598-021-96263-1 | DOI Listing |
Neural Netw
December 2024
Norwegian University of Science and Technology, Trondheim, Norway; Jinhua Institute of Zhejiang University, Hangzhou, China.
Accurate modeling of DNA sequences requires capturing distant semantic relationships between the nucleotide acid bases. Most existing deep neural network models face two challenges: (1) they are limited to short DNA fragments and cannot capture long-range interactions, and (2) they require many supervised labels, which is often expensive in practice. We propose a new neural network model called SwanDNA to address the above challenges.
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December 2024
Università Vita-Salute San Raffaele, Via Olgettina 58, 20132 Milan, Italy; IRCCS Ospedale San Raffaele, Experimental Imaging Center, Via Olgettina 58, 20132 Milan, Italy. Electronic address:
The genome is traditionally divided into condensed heterochromatin and open euchromatin. However, recent findings challenge this binary classification and the notion that chromatin condensation solely governs the accessibility of transcription factors (TFs) and, consequently, gene expression. Instead, chromatin accessibility is emerging as a factor-specific property that is influenced by multiple determinants.
View Article and Find Full Text PDFJ Dent Res
December 2024
Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY, USA.
Head and neck squamous cell carcinoma (HNSCC) is one of the deadliest human cancers, with the overall 5-year survival rate stagnating in recent decades due to the lack of innovative treatment approaches. Apart from the recently Food and Drug Administration-approved epidermal growth factor receptor inhibitor and immune checkpoint inhibitor, alternative therapeutic strategies that target epigenetic abnormalities, an emerging cancer hallmark, remain to be fully explored. A pathological epigenetic landscape, characterized by widespread reprogramming of chromatin modifications such as DNA methylation and histone modifications, which drives transcription deregulation and genome reorganization, has been extensively documented in numerous cancers, including HNSCC.
View Article and Find Full Text PDFFront Genet
December 2024
School of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Open chromatin regions (OCRs) play a crucial role in transcriptional regulation and gene expression. In recent years, there has been a growing interest in using plasma cell-free DNA (cfDNA) sequencing data to detect OCRs. By analyzing the characteristics of cfDNA fragments and their sequencing coverage, researchers can differentiate OCRs from non-OCRs.
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November 2024
Facultad de Ciencias Químicas e Ingeniería, Universidad Autónoma de Baja California, Tijuana 22390, Mexico.
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