全奖读博 | 英国伦敦大学

A PLATFORM TO ENHANCE THE PRODUCTION AND ACTIVITY OF EXUDATES FROM ALLELOPATHIC AND NON-ALLELOPATHIC RICE TO IDENTIFY NEW HERBICIDAL LEAD COMPOUNDS (PEA RICE)

提高化感和非化感水稻分泌物产量和活性以鉴定新除草先导化合物的平台

导师

Prof. Alessandra Devoto,

Alessandra.Devoto@rhul.ac.uk, Professor of Plant Molecular Sciences, Royal Holloway, University of London

Dr Stuart Snowden,

Stuart.Snowden@rhul.ac.uk, Lecturer in Metabolomics, Royal Holloway, University of London

项目简介

Plants detect neighbouring plants by the chemical signals they secrete, and their responses include increased secretion of phytotoxic compounds (“allelopathy”) and root growth architecture alteration. Responses can be enhanced by exogenous application of jasmonates (JAs), methyl salicylate, competing weeds root exudates. Biotic and abiotic stimuli signalling can also regulate soilborne signals for neighbour detection.

Rice is a key staple crop globally, arguably the most important crop for global food security. Herbicide resistance to known enzymes is increasing, leading to search for novel and sustainable approaches to weed control. Allelopathy has been investigated in the rice-Echinochloa system, and this project will provide and innovative way to investigate the phenomenon in a system without interference from external factors which has many advantages (e.g. sterility, lack of soil for bioavailability). The platform will favour stable production for phytochemicals. The system will be used to analyse gene circuitries and biosynthetic pathways. The approach will also offer an environmentally sustainable route to compounds sources.

In this interdisciplinary project, spanning plant biology, analytical chemistry, high-throughput genomics and transcriptomics as well as bioinformatics, species-specific signals between rice and the infestant weed barnyard grass (Echinochloa sp.), and their underlying mechanisms, yet uncovered due to methodological limitations and root-soil interactions, will be investigated. The project provides elements of fundamental sciences aligned with clear commercial applications for SYNGENTA.

The Devoto laboratory, Department of Biological Sciences (DBS) at RHUL has developed over 20 years, in-depth knowledge on plant responses to biotic and abiotic stress and is world-renowned for their expertise in JAs signalling, the induced specialized metabolism (and associated analytical platforms), cross-talk with other pathways and epigenetic regulation, with particular regard to growth/stress responses trade-off. The lab has developed biotechnological applications for plant and animal health, has extensive expertise in high- throughput functional genomics, CRISPR/Cas genome editing, as well as hydroponics and in vitro cultures from medicinal and non-medicinal plants. Bioanalytical approaches for measuring metabolite profiles will be developed jointly with the Snowden laboratory at RHUL.

The international industrial partner, SYNGENTA provides products and solutions for farmers to achieve global food security for a growing population, sustainably. SYNGENTA applies world-class science to develop crop protection products. The SYNGENTA supervisory Team has a wealth of expertise in both allelopathy, rice agronomy and the discovery of new active ingredients and rice traits for crop protection.

Training will be through research, and it will include transferable skills. The student will take part in studies related to plant physiology and molecular analyses at RHUL and SYNGENTA (3-month placement) and will be integrated in the research teams, gaining experience also in functional genomics, gene editing, transcriptomics and bioinformatics. The student will experience both academic and industrial research environments where they will develop technical and research skills while planning and managing own work gaining soft skills (eg, communication, teamwork) and working in international settings.

申请链接

长按或扫码直达原文：

一起关注植物科学，

促进学术研究与科普宣传！

-- 植物生理生态

扫二维码，关注我们

公众号ID：yanli19-

投稿及转载：li.yan@uwa.edu.au；

guangruwang77@163.com

👇

在看

http://mp.weixin.qq.com/s?__biz=MzI0NjY2ODM0NQ==&mid=2247490831&idx=1&sn=9110e4abb66be9fe04104e080f91fec2