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4See: A Flexible Browser to Explore 4C Data

It is established that transcription of many metazoan genes is regulated by distal regulatory sequences beyond the promoter. Enhancers have been identified at up to megabase distances from their regulated genes, and/or proximal to or within the introns of unregulated genes. The unambiguous identific...

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Detalles Bibliográficos
Autores principales: Ben Zouari, Yousra, Platania, Angeliki, Molitor, Anne M., Sexton, Tom
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6985583/
https://www.ncbi.nlm.nih.gov/pubmed/32038719
http://dx.doi.org/10.3389/fgene.2019.01372
Descripción
Sumario:It is established that transcription of many metazoan genes is regulated by distal regulatory sequences beyond the promoter. Enhancers have been identified at up to megabase distances from their regulated genes, and/or proximal to or within the introns of unregulated genes. The unambiguous identification of the target genes of newly identified regulatory elements can thus be challenging. Well-studied enhancers have been found to come into direct physical proximity with regulated genes, presumably by the formation of chromatin loops. Chromosome conformation capture (3C) derivatives that assess the frequency of proximity between different genetic elements is thus a popular method for exploring gene regulation by distal regulatory elements. For studies of chromatin loops and promoter-enhancer communication, 4C (circular chromosome conformation capture) is one of the methods of choice, optimizing cost (required sequencing depth), throughput, and resolution. For ease of visual inspection of 4C data we present 4See, a versatile and user-friendly browser. 4See allows 4C profiles from the same bait to be flexibly plotted together, allowing biological replicates to either be compared, or pooled for comparisons between different cell types or experimental conditions. 4C profiles can be integrated with gene tracks, linear epigenomic profiles, and annotated regions of interest, such as called significant interactions, allowing rapid data exploration with limited computational resources or bioinformatics expertise.