Suppr超能文献

一个翻译组学-转录组学多组学基因调控网络揭示了玉米复杂的功能景观。

A translatome-transcriptome multi-omics gene regulatory network reveals the complicated functional landscape of maize.

机构信息

National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.

HuBei HongShan Laboratory, Wuhan, 430070, China.

出版信息

Genome Biol. 2023 Mar 29;24(1):60. doi: 10.1186/s13059-023-02890-4.

Abstract

BACKGROUND

Maize (Zea mays L.) is one of the most important crops worldwide. Although sophisticated maize gene regulatory networks (GRNs) have been constructed for functional genomics and phenotypic dissection, a multi-omics GRN connecting the translatome and transcriptome is lacking, hampering our understanding and exploration of the maize regulatome.

RESULTS

We collect spatio-temporal translatome and transcriptome data and systematically explore the landscape of gene transcription and translation across 33 tissues or developmental stages of maize. Using this comprehensive transcriptome and translatome atlas, we construct a multi-omics GRN integrating mRNAs and translated mRNAs, demonstrating that translatome-related GRNs outperform GRNs solely using transcriptomic data and inter-omics GRNs outperform intra-omics GRNs in most cases. With the aid of the multi-omics GRN, we reconcile some known regulatory networks. We identify a novel transcription factor, ZmGRF6, which is associated with growth. Furthermore, we characterize a function related to drought response for the classic transcription factor ZmMYB31.

CONCLUSIONS

Our findings provide insights into spatio-temporal changes across maize development at both the transcriptome and translatome levels. Multi-omics GRNs represent a useful resource for dissection of the regulatory mechanisms underlying phenotypic variation.

摘要

背景

玉米(Zea mays L.)是全球最重要的作物之一。尽管已经构建了复杂的玉米基因调控网络(GRN)用于功能基因组学和表型剖析,但缺乏连接翻译组和转录组的多组学 GRN,这阻碍了我们对玉米调控组的理解和探索。

结果

我们收集了时空翻译组和转录组数据,并系统地研究了玉米 33 种组织或发育阶段的基因转录和翻译全景。利用这个全面的转录组和翻译组图谱,我们构建了一个多组学 GRN,整合了 mRNA 和翻译后的 mRNA,结果表明,翻译组相关的 GRN 优于仅使用转录组数据的 GRN,而在大多数情况下,组间 GRN 优于组内 GRN。借助多组学 GRN,我们协调了一些已知的调控网络。我们发现了一个新的转录因子 ZmGRF6,它与生长有关。此外,我们还对经典转录因子 ZmMYB31 的一个与干旱响应相关的功能进行了描述。

结论

我们的研究结果提供了在转录组和翻译组水平上对玉米发育时空变化的深入了解。多组学 GRN 为剖析表型变异的调控机制提供了一个有用的资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6167/10053466/bf26393a0d5b/13059_2023_2890_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验