Global Quantitative Mapping of Enhancers in Rice by STARR-seq / 基因组蛋白质组与生物信息学报·英文版
Genomics, Proteomics & Bioinformatics
; (4): 140-153, 2019.
Article
em En
| WPRIM
| ID: wpr-772940
Biblioteca responsável:
WPRO
ABSTRACT
Enhancers activate transcription in a distance-, orientation-, and position-independent manner, which makes them difficult to be identified. Self-transcribing active regulatory region sequencing (STARR-seq) measures the enhancer activity of millions of DNA fragments in parallel. Here we used STARR-seq to generate a quantitative global map of rice enhancers. Most enhancers were mapped within genes, especially at the 5' untranslated regions (5'UTR) and in coding sequences. Enhancers were also frequently mapped proximal to silent and lowly-expressed genes in transposable element (TE)-rich regions. Analysis of the epigenetic features of enhancers at their endogenous loci revealed that most enhancers do not co-localize with DNase I hypersensitive sites (DHSs) and lack the enhancer mark of histone modification H3K4me1. Clustering analysis of enhancers according to their epigenetic marks revealed that about 40% of identified enhancers carried one or more epigenetic marks. Repressive H3K27me3 was frequently enriched with positive marks, H3K4me3 and/or H3K27ac, which together label enhancers. Intergenic enhancers were also predicted based on the location of DHS regions relative to genes, which overlap poorly with STARR-seq enhancers. In summary, we quantitatively identified enhancers by functional analysis in the genome of rice, an important model plant. This work provides a valuable resource for further mechanistic studies in different biological contexts.
Palavras-chave
Texto completo:
1
Base de dados:
WPRIM
Assunto principal:
Acetilação
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Oryza
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Transcrição Gênica
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Sequência de Bases
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Histonas
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Sequências Repetitivas de Ácido Nucleico
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Elementos Facilitadores Genéticos
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Regiões Promotoras Genéticas
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Análise de Sequência de DNA
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Genes de Plantas
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Genomics, Proteomics & Bioinformatics
Ano de publicação:
2019
Tipo de documento:
Article