4.8 Article

A comprehensive strategy for identifying long-distance mobile peptides in xylem sap

期刊

PLANT JOURNAL
卷 84, 期 3, 页码 611-620

出版社

WILEY
DOI: 10.1111/tpj.13015

关键词

long-distance; xylem sap; peptidomics; CLV3/ESR-related; C-terminally encoded peptide; sulfated peptide

资金

  1. NIBB
  2. Japan Society for the Promotion of Science (JSPS) [A2406127, 15K18553]
  3. Ministry of Education, Culture, Sports, Science and Technology [22128006, 25221105]
  4. MEXT [15H05957]
  5. Grants-in-Aid for Scientific Research [15H05957, 15K18553] Funding Source: KAKEN

向作者/读者索取更多资源

There is a growing awareness that secreted peptides mediate organ-to-organ communication in higher plants. Xylem sap peptidomics is an effective but challenging approach for identifying long-distance mobile peptides. In this study we developed a simple, gel-free purification system that combines o-chlorophenol extraction with HPLC separation. Using this system, we successfully identified seven oligopeptides from soybean xylem sap exudate that had one or more post-transcriptional modifications: glycosylation, sulfation and/or hydroxylation. RNA sequencing and quantitative PCR analyses showed that the peptide-encoding genes are expressed in multiple tissues. We further analyzed the long-distance translocation of four of the seven peptides using gene-encoding peptides with single amino acid substitutions, and identified these four peptides as potential root-to-shoot mobile oligopeptides. Promoter-GUS analysis showed that all four peptide-encoding genes were expressed in the inner tissues of the root endodermis. Moreover, we found that some of these peptide-encoding genes responded to biotic and/or abiotic factors. These results indicate that our purification system provides a comprehensive approach for effectively identifying endogenous small peptides and reinforce the concept that higher plants employ various peptides in root-to-shoot signaling.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据