Dataset Information

Selection of Reference Genes for Normalization of Real-Time PCR Data in Calliptamus italicus (Orthoptera: Acrididae) Under Different Temperature Conditions.

ABSTRACT: Global warming has dominated worldwide climate change trends, and adaptability to high temperatures is the main factor underlying the spread of the pest Calliptamus italicus in Xinjiang Province, China. However, knowledge about the molecular mechanisms responsible for this adaptability and other related biological properties of C. italicus remain relatively unclear. Real-time quantitative polymerase chain reaction (RT-qPCR) is a key tool for gene expression analysis associated with various biological processes. Reference genes are necessary for normalizing gene expression levels across samples taken from specific experimental conditions. In this study, transcript level of five genes (GAPDH, 18S, TUB, ACT, and EF1?), commonly used as reference genes, were evaluated under nine different temperatures (27, 30, 33, 36, 39, 42, 45, 48, and 51°C) to assess their expression stability and further select the most suitable to be used on normalization of target gene expression data. Gene expression profiles were analyzed using geNorm, NormFinder, and BestKeeper software packages. The combined results demonstrated that the best-ranked reference genes for C. italicus are EF1?, GAPDH, and ACT under different thermal stress conditions. This is the first study that assesses gene expression analysis across a range of temperatures to select the most appropriate reference genes for RT-qPCR data normalization in C. italicus. These results should assist target gene expression analysis associated with heat stress in C. italicus.

SUBMITTER: Hu H

PROVIDER: S-EPMC6871914 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Selection of Reference Genes for Normalization of Real-Time PCR Data in Calliptamus italicus (Orthoptera: Acrididae) Under Different Temperature Conditions.

Hu Hongxia H Ye Xiaofang X Wang Han H Ji Rong R

Journal of insect science (Online) 20191101 6

Global warming has dominated worldwide climate change trends, and adaptability to high temperatures is the main factor underlying the spread of the pest Calliptamus italicus in Xinjiang Province, China. However, knowledge about the molecular mechanisms responsible for this adaptability and other related biological properties of C. italicus remain relatively unclear. Real-time quantitative polymerase chain reaction (RT-qPCR) is a key tool for gene expression analysis associated with various biolo ...[more]

PMID: 31752021

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Project description:BackgroundCalliptamus italicus is a dominant species in the desert and semi-desert grassland. It is widely distributed throughout many regions such as Asia, Europe, North Africa and the Mediterranean, and has enormous destructive potential for agriculture and animal husbandry. The C. italicus overwintering as eggs in the soil through diapause, and the cold tolerance of locust eggs is the key to their ability to survive the winter smoothly to maintain the population.ResultsTranscriptome analysis of C. italicus eggs was carried out in this paper in constant low temperature acclimation, natural low temperature acclimation and room temperature. The differentially expressed genes related to cold tolerance were screened out, the differences in expression patterns under different low temperature acclimation were analyzed, and the genes in the significantly up-regulated pathways may play an important role in cold tolerance. The results show that different domestication modes can induce C. italicus eggs to express a large number of genes to alleviate low temperature damage, but C. italicus eggs are more sensitive to changes in temperature. Compared with the control, there are 8689 DEGs at constant low temperature and 14,994 DEGs at natural low temperature. KEGG analysis showed that DEGs were mainly enriched in pathways related to metabolism and biological systems under constant low temperature, and were mainly enriched in pathways related to biological systems and environmental information processing under natural low temperature. In addition, RNAi technology was used to further verify the regulation of genes in the significantly enriched up-regulated pathways on C. italicus eggs, and it was confirmed that the hatching rate of C. italicus eggs at low temperature was significantly reduced after interference.ConclusionsTranscriptome analysis of C. italicus eggs treated at different temperatures provided a theoretical basis for further understanding the adaptation mechanism of C. italicus eggs to low temperature. In addition, four potential RNAi target genes were verified in the eggs of C. italicus for the first time, providing new ideas for effective control of this species.

Project description:BackgroundNormalization in real-time qRT-PCR is necessary to compensate for experimental variation. A popular normalization strategy employs reference gene(s), which may introduce additional variability into normalized expression levels due to innate variation (between tissues, individuals, etc). To minimize this innate variability, multiple reference genes are used. Current methods of selecting reference genes make an assumption of independence in their innate variation. This assumption is not always justified, which may lead to selecting a suboptimal set of reference genes.ResultsWe propose a robust approach for selecting optimal subset(s) of reference genes with the smallest variance of the corresponding normalizing factors. The normalizing factor variance estimates are based on the estimated unstructured covariance matrix of all available candidate reference genes, adjusting for all possible correlations. Robustness is achieved through bootstrapping all candidate reference gene data and obtaining the bootstrap upper confidence limits for the variances of the log-transformed normalizing factors. The selection of the reference gene subset is optimized with respect to one of the following criteria: (A) to minimize the variability of the normalizing factor; (B) to minimize the number of reference genes with acceptable upper limit on variability of the normalizing factor, (C) to minimize the average rank of the variance of the normalizing factor. The proposed approach evaluates all gene subsets of various sizes rather than ranking individual reference genes by their stability, as in the previous work. In two publicly available data sets and one new data set, our approach identified subset(s) of reference genes with smaller empirical variance of the normalizing factor than in subsets identified using previously published methods. A small simulation study indicated an advantage of the proposed approach in terms of sensitivity to identify the true optimal reference subset in the presence of even modest, especially negative correlation among the candidate reference genes.ConclusionsThe proposed approach performs comprehensive and robust evaluation of the variability of normalizing factors based on all possible subsets of candidate reference genes. The results of this evaluation provide flexibility to choose from important criteria for selecting the optimal subset(s) of reference genes, unless one subset meets all the criteria. This approach identifies gene subset(s) with smaller variability of normalizing factors than current standard approaches, particularly if there is some nontrivial innate correlation among the candidate genes.

Dataset Information

Selection of Reference Genes for Normalization of Real-Time PCR Data in Calliptamus italicus (Orthoptera: Acrididae) Under Different Temperature Conditions.

Publications

Selection of Reference Genes for Normalization of Real-Time PCR Data in Calliptamus italicus (Orthoptera: Acrididae) Under Different Temperature Conditions.

Similar Datasets

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