Validation and Evaluation of Reference Genes for Quantitative Real-Time PCR Analysis in Mythimna loreyi (Lepidoptera: Noctuidae).
Liuyang WangChaoxia YangQingyu LiuXiaofang ZhangXiangdong MeiTao ZhangJun NingPublished in: Insects (2024)
Quantitative real-time PCR (qRT-PCR) is a widely applied technique for accurately assessing the expression of target genes. In practice, the evaluation of gene expression requires appropriate reference genes. To screen reliable reference genes for evaluating gene expression via qRT-PCR in Mythimna loreyi , a notorious migratory pest across Asia, Africa, Europe, and Australia, we assessed the expression stability of 13 candidate reference genes in M. loreyi using the ΔCt method, BestKeeper, Normfinder, GeNorm, and the web-based comprehensive platform RefFinder. These reference genes include RPL10 , RPL27 , RPL32 , RPS3 , TATA-box , GAPDH , AK , Actin , EF , α-tubulin , SOD , 18S rRNA , and FTZ-F1 , which is frequently employed in Lepidoptera insects. Our findings revealed that the performance of the candidate reference gene depended on experimental conditions. Specifically, RPL27 and RPL10 were the most suitable for evaluating expression changes across developmental stages, tissues, and adult ages. The optimal reference genes were recommended in specific experiment conditions, for instance, EF and RPS3 were recommended for mating status, AK and RPL10 were recommended for temperature treatments, RPL27 and FTZ - F1 were recommended for larva diet, and EF and RPL27 were recommended for adult diet treatments. Additionally, expression profiles of pheromone-binding protein 2 ( MlorPBP2 ) and glutathione S-transferase ( MlorGST1 ) were used to validate the reference genes. This study provides reference genes for the accurate normalization of qRT-PCR data, laying the groundwork for studying the expression of target genes in M. loreyi .
Keyphrases
- genome wide
- gene expression
- genome wide identification
- bioinformatics analysis
- binding protein
- real time pcr
- poor prognosis
- genome wide analysis
- high resolution
- computed tomography
- healthcare
- physical activity
- primary care
- magnetic resonance imaging
- magnetic resonance
- copy number
- machine learning
- high throughput
- weight loss
- big data