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Digital Inventory of Arabidopsis Transcripts Revealed by 61 RNA Sequencing Samples

文献类型: 外文期刊

作者: Sun, Xiaoyong 1 ; Yang, Qiuying 2 ; Deng, Zhiping 3 ; Ye, Xinfu 4 ;

作者机构: 1.Shandong Agr Univ, Coll Informat Sci & Engn, Agr Big Data Res Ctr, Tai An 271018, Shandong, Peoples R China

2.Univ Texas SW Med Ctr Dallas, Dept Physiol, Dallas, TX 75235 USA

3.Zhejiang Acad Agr Sci, Inst Virol & Biotechnol, State Key Lab Breeding Base Zhejiang Sustainable, Hangzhou 310021, Zhejiang, Peoples R China

4.Fujian Acad Agr Sci, Fruit Res Inst, Fuzhou 350013, Fujian, Peoples R China

关键词: Digital;Inventory;of;Arabidopsis

期刊名称:PLANT PHYSIOLOGY ( 影响因子:8.34; 五年影响因子:8.972 )

ISSN:

年卷期:

页码:

收录情况: SCI

摘要: Alternative splicing is an essential biological process to generate proteome diversity and phenotypic complexity. Recent improvements in RNA sequencing accuracy and computational algorithms have provided unprecedented opportunities to examine the expression levels of Arabidopsis (Arabidopsis thaliana) transcripts. In this article, we analyzed 61 RNA sequencing samples from 10 totally independent studies of Arabidopsis and calculated the transcript expression levels in different tissues, treatments, developmental stages, and varieties. These data provide a comprehensive profile of Arabidopsis transcripts with single-base resolution. We quantified the expression levels of 40,745 transcripts annotated in The Arabidopsis Information Resource 10, comprising 73% common transcripts, 15% rare transcripts, and 12% nondetectable transcripts. In addition, we investigated diverse common transcripts in detail, including ubiquitous transcripts, dominant/subordinate transcripts, and switch transcripts, in terms of their expression and transcript ratio. Interestingly, alternative splicing was the highly enriched function for the genes related to dominant/subordinate transcripts and switch transcripts. In addition, motif analysis revealed that TC motifs were enriched in dominant transcripts but not in subordinate transcripts. These motifs were found to have a strong relationship with transcription factor activity. Our results shed light on the complexity of alternative splicing and the diversity of the contributing factors.

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