Ribosome profiling reveals the translational landscape and allele-specific translation efficiency in rice

Abstract Translational regulation is a critical step in the process of gene expression and governs the synthesis of proteins from mRNAs. Many studies have revealed the translational regulation in plants in response to various environmental stimuli. However, there has been no comprehensive landscape of translational regulation and allele-specific translation efficiency in multiple tissues of plants, especially in rice, a main staple crop feeding nearly half of the world population. Here, we used RNA-seq and Ribo-seq data to analyze the transcriptome and translatome of an elite hybrid rice SY63 and its parental varieties ZS97 and MH63. The results revealed that gene expression patterns varied more significantly between tissues than between varieties at both transcriptional and translational levels. Besides, we identified 3,392 upstream open reading frames (uORFs), and most of the uORF-containing genes were enriched for transcription factors. Only 668 long non-coding RNAs could be translated into peptides. Finally, we discovered numerous genes with allele-specific translation efficiency in SY63, and further demonstrated that somecis-regulatory elements (secondary structures of mRNAs and the binding of miRNAs) may contribute to allelic divergence in translation efficiency. Overall, our findings may improve the understanding of translational regulation in rice and provide information for the molecular basis of breading research..

Medienart:

Preprint

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

bioRxiv.org - (2023) vom: 18. Nov. Zur Gesamtaufnahme - year:2023

Sprache:

Englisch

Beteiligte Personen:

Zhu, Xi-Tong [VerfasserIn]
Zhou, Run [VerfasserIn]
Che, Jian [VerfasserIn]
Zheng, Yu-Yu [VerfasserIn]
Qamar, Muhammad Tahir ul [VerfasserIn]
Feng, Jia-Wu [VerfasserIn]
Zhang, Jianwei [VerfasserIn]
Gao, Junxiang [VerfasserIn]
Chen, Ling-Ling [VerfasserIn]

Links:

Volltext [kostenfrei]

Themen:

570
Biology

doi:

10.1101/2022.02.22.481533

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XBI035338202