Related Experiment Video
Updated: Oct 9, 2025

Maintaining Biological Cultures and Measuring Gene Expression in Aphis nerii: A Non-model System for Plant-insect Interactions
Published on: August 31, 2018
Combined Transcriptome and Metabolome Analysis of Alfalfa Response to Thrips Infection
Zhiqiang Zhang1,2, Qi Chen1, Yao Tan3
1Key Laboratory of Grassland Resources of the Ministry of Education, Technology Engineering Center of Drought and Cold-Resistant Grass Breeding in North of the National Forestry and Grassland Administration, College of Grassland, Resources and Environment, Inner Mongolia Agricultural University, Hohhot 010011, China.
Abstract:
Thrips (Thysanoptera: Thripidae) is a major insect pest for alfalfa which can result in decreased plant nutrients, low yields, and even plant death. To identify the differentially expressed genes and metabolites in response to thrips in alfalfa, a combination of metabolomics and transcriptomics was employed using alfalfa (Caoyuan No. 2) with and without thrips infestation. The results showed that the flavonoid biosynthesis and isoflavonoid biosynthesis pathways were the most significantly enriched pathways in response to thrips infection, as shown by the combined transcriptome and metabolome analysis. The transcriptome results showed that SA and JA signal transduction and PAPM-triggered immunity and the MAPK signaling pathway-plant pathways played a crucial role in thrips-induced plant resistance in alfalfa. In addition, we found that thrips infestation could also induce numerous changes in plant primary metabolism, such as carbohydrate and amino acid metabolism as compared to the control. Overall, our results described here should improve fundamental knowledge of molecular responses to herbivore-inducible plant defenses and contribute to the design of strategies against thrips in alfalfa.
More Related Videos
06:46Collection of Alfalfa Root Exudates to Study the Impact of Di2-ethylhexyl Phthalate on Metabolite Production
Published on: June 2, 2023
08:22IR-TEx: An Open Source Data Integration Tool for Big Data Transcriptomics Designed for the Malaria Vector Anopheles gambiae
Published on: January 15, 2020