RNA interference in the Asian Longhorned Beetle:Identification of Key RNAi Genes and Reference Genes for RT-qPCR

被引:0
|
作者
Thais B. Rodrigues
Ramesh Kumar Dhandapani
Jian J. Duan
Subba Reddy Palli
机构
[1] Department of Entomology,
[2] University of Kentucky,undefined
[3] College of Agriculture,undefined
[4] Food and Environment,undefined
[5] USDA ARS Beneficial Insects Introduction Research Unit,undefined
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Asian Longhorned Beetle (ALB) Anoplophora glabripennis is a serious invasive forest pest in several countries including the United States, Canada, and Europe. RNA interference (RNAi) technology is being developed as a novel method for pest management. Here, we identified the ALB core RNAi genes including those coding for Dicer, Argonaute, and double-stranded RNA-binding proteins (dsRBP) as well as for proteins involved in dsRNA transport and the systemic RNAi. We also compared expression of six potential reference genes that could be used to normalize gene expression and selected gapdh and rpl32 as the most reliable genes among different tissues and stages of ALB. Injection of double-stranded RNA (dsRNA) targeting gene coding for inhibitor of apoptosis (IAP) into larvae and adults resulted in a significant knockdown of this gene and caused the death of 90% of the larvae and 100% of adults. No mortality of both larvae and adults injected with dsRNA targeting gene coding for green fluorescence protein (GFP, as a negative control) was observed. These data suggest that functional RNAi machinery exists in ALB and a potential RNAi-based method could be developed for controlling this insect.
引用
收藏
相关论文
共 50 条
  • [31] Identification of Reference Genes for RT-qPCR Data Normalization in Cannabis sativa Stem Tissues
    Mangeot-Peter, Lauralie
    Legay, Sylvain
    Hausman, Jean-Francois
    Esposito, Sergio
    Guerriero, Gea
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2016, 17 (09):
  • [32] Identification and Selection of the Internal Reference Genes of Ceracris kiangsu (Orthoptera: Arcypteridae) by RT-qPCR
    Fang L.
    Li Z.
    Zhang S.
    Zhang W.
    Shu J.
    Wang H.
    Linye Kexue/Scientia Silvae Sinicae, 2022, 58 (01): : 70 - 77
  • [33] Identification and validation of stable reference genes for RT-qPCR analyses of Kobresia littledalei seedlings
    Sun, Haoyang
    Li, Chunping
    Li, Siyu
    Ma, Jiaxin
    Li, Shuo
    Li, Xin
    Gao, Cai
    Yang, Rongchen
    Ma, Nan
    Yang, Jing
    Yang, Peizhi
    He, Xueqing
    Hu, Tianming
    BMC PLANT BIOLOGY, 2024, 24 (01):
  • [34] RefGenes: identification of reliable and condition specific reference genes for RT-qPCR data normalization
    Tomas Hruz
    Markus Wyss
    Mylene Docquier
    Michael W Pfaffl
    Sabine Masanetz
    Lorenzo Borghi
    Phebe Verbrugghe
    Luba Kalaydjieva
    Stefan Bleuler
    Oliver Laule
    Patrick Descombes
    Wilhelm Gruissem
    Philip Zimmermann
    BMC Genomics, 12
  • [35] Identification of optimal reference genes for RT-qPCR in the rat hypothalamus and intestine for the study of obesity
    B Li
    E K Matter
    H T Hoppert
    B E Grayson
    R J Seeley
    D A Sandoval
    International Journal of Obesity, 2014, 38 : 192 - 197
  • [36] RNA-seq validation: software for selection of reference and variable candidate genes for RT-qPCR
    de Brito, Marcio Wilson Dias
    de Carvalho, Stephanie Serafim
    Mota, Maria Beatriz dos Santos
    Mesquita, Rafael Dias
    BMC GENOMICS, 2024, 25 (01):
  • [37] Selection of Stable Reference Genes for RT-qPCR in Mouse Intestinal Tissue
    Young, Jonathan
    Jara, Adam
    Kopchick, John J.
    ENDOCRINE REVIEWS, 2014, 35 (03)
  • [38] Assessment of suitable reference genes for RT-qPCR studies in chronic rhinosinusitis
    Nakayama, Tsuguhisa
    Okada, Naoko
    Yoshikawa, Mamoru
    Asaka, Daiya
    Kuboki, Akihito
    Kojima, Hiromi
    Tanaka, Yasuhiro
    Haruna, Shin-ichi
    SCIENTIFIC REPORTS, 2018, 8
  • [39] Evaluation of reference genes for RT-qPCR analysis in wild and cultivated Cannabis
    Guo, Rong
    Guo, Hongyan
    Zhang, Qingying
    Guo, Mengbi
    Xu, Yanping
    Zeng, Min
    Lv, Pin
    Chen, Xuan
    Yang, Ming
    BIOSCIENCE BIOTECHNOLOGY AND BIOCHEMISTRY, 2018, 82 (11) : 1902 - 1910
  • [40] Assessment of brain reference genes for RT-qPCR studies in neurodegenerative diseases
    Rasmus Rydbirk
    Jonas Folke
    Kristian Winge
    Susana Aznar
    Bente Pakkenberg
    Tomasz Brudek
    Scientific Reports, 6