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Classification and characterization of alternative promoters in 26 lung adenocarcinoma cell lines

BACKGROUND: Genome-wide landscape of alternative promoter use remains unknown. We determined expression profiles of promoters in 26 lung adenocarcinoma cell lines using the transcriptional start site-sequencing data and proposed an index ‘canonical promoter usage’ to quantify the diversity of altern...

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Detalles Bibliográficos
Autores principales: Hamaya, Yamato, Suzuki, Ayako, Suzuki, Yutaka, Tsuchihara, Katsuya, Yamashita, Riu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885743/
https://www.ncbi.nlm.nih.gov/pubmed/36465011
http://dx.doi.org/10.1093/jjco/hyac175
Descripción
Sumario:BACKGROUND: Genome-wide landscape of alternative promoter use remains unknown. We determined expression profiles of promoters in 26 lung adenocarcinoma cell lines using the transcriptional start site-sequencing data and proposed an index ‘canonical promoter usage’ to quantify the diversity of alternative promoter usage. METHODS: Transcriptional start site-sequencing and other datasets were obtained from the DataBase of Transcriptional Start Sites. Transcriptional start site-sequencing read clusters were mapped onto RefGene to determine the promoters. Commonly used promoters were designated as canonical promoters. The sequence logos, CpG islands, DNA methylation and histone modifications of canonical and non-canonical promoters were examined. Canonical promoter usage was calculated by dividing ‘read counts of a canonical promoter’ by ‘read counts of all the units of promoters’ on each gene. The expressed genes were subjected to hierarchical clustering according to their canonical promoter usage. RESULTS: Among 104 455 promoters for 14 297 genes, 8659 canonical and 68 197 non-canonical promoters were identified. Corresponding to higher expression, canonical promoters showed core promoter sequences, higher CpG island positivity, less DNA methylation and higher transcription-promoting histone modifications. Gene ontology enrichment analysis revealed that the clusters with lower canonical promoter usage were related to signalling pathways, whereas clusters of tightly regulated genes with higher canonical promoter usage were related to housekeeping genes. CONCLUSION: Canonical promoters were regulated by conventional transcriptional machinery, while non-canonical promoters would be targets of ‘leaky’ expression. Further investigation is warranted to analyse the correlation between alternative promoter usage and biological characteristics contributing to carcinogenesis.