Intron-capture RNA-seq reveals the landscape of intronic RNAs in Arabidopsis.

Li, Han; Zhang, Yimai; Bing, Jianhao; Han, Jinyu; Hu, Jiming; Zhao, Hongwei; Sun, Xiaoyong

Li, Han; Zhang, Yimai; Bing, Jianhao; Han, Jinyu; Hu, Jiming; Zhao, Hongwei; Sun, Xiaoyong.

Afiliação

Li H; Agricultural Big-Data Research Center, College of Information Science and Engineering, Shandong Agricultural University, Taian, China.
Zhang Y; Department of Plant Pathology, College of Plant Protection, Nanjing Agricultural University, Nanjing, China.
Bing J; Agricultural Big-Data Research Center, College of Information Science and Engineering, Shandong Agricultural University, Taian, China.
Han J; Agricultural Big-Data Research Center, College of Information Science and Engineering, Shandong Agricultural University, Taian, China.
Hu J; Agricultural Big-Data Research Center, College of Information Science and Engineering, Shandong Agricultural University, Taian, China.
Zhao H; Department of Plant Pathology, College of Plant Protection, Nanjing Agricultural University, Nanjing, China. Electronic address: hzhao@njau.edu.cn.
Sun X; Agricultural Big-Data Research Center, College of Information Science and Engineering, Shandong Agricultural University, Taian, China. Electronic address: sunx1@sdau.edu.cn.

Plant Physiol Biochem ; 196: 75-88, 2023 Mar.

Article em En | MEDLINE | ID: mdl-36701993

Assuntos

Arabidopsis; Íntrons/genética; Arabidopsis/genética; RNA-Seq; RNA Circular/genética

Palavras-chave

GC pattern; Intronic RNAs; Pathogen infection; RNA sequencing; Time course

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Arabidopsis Tipo de estudo: Prognostic_studies Idioma: En Revista: Plant Physiol Biochem Ano de publicação: 2023 Tipo de documento: Article

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