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Open Access Highly Accessed Research article

Assessment and validation of a suite of reverse transcription-quantitative PCR reference genes for analyses of density-dependent behavioural plasticity in the Australian plague locust

Marie-Pierre Chapuis123*, Donya Tohidi-Esfahani1, Tim Dodgson1, Laurence Blondin2, Fleur Ponton1, Darron Cullen1, Stephen J Simpson1 and Gregory A Sword14

Author Affiliations

1 School of Biological Sciences, University of Sydney, Sydney, NSW 2006, Australia

2 Centre de coopération internationale en recherche agronomique pour le développement Acridologie, TA A-50/D, F-34398, Montpellier, France

3 Centre de Biologie et de Gestion des Populations, INRA, Campus International de Baillarguet CS 30016, 34988 Montferrier/Lez, France

4 Department of Entomology, Texas A&M University, College Station, TX 77842-2475 USA

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BMC Molecular Biology 2011, 12:7  doi:10.1186/1471-2199-12-7

Published: 16 February 2011

Abstract

Background

The Australian plague locust, Chortoicetes terminifera, is among the most promising species to unravel the suites of genes underling the density-dependent shift from shy and cryptic solitarious behaviour to the highly active and aggregating gregarious behaviour that is characteristic of locusts. This is because it lacks many of the major phenotypic changes in colour and morphology that accompany phase change in other locust species. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is the most sensitive method available for determining changes in gene expression. However, to accurately monitor the expression of target genes, it is essential to select an appropriate normalization strategy to control for non-specific variation between samples. Here we identify eight potential reference genes and examine their expression stability at different rearing density treatments in neural tissue of the Australian plague locust.

Results

Taking advantage of the new orthologous DNA sequences available in locusts, we developed primers for genes encoding 18SrRNA, ribosomal protein L32 (RpL32), armadillo (Arm), actin 5C (Actin), succinate dehydrogenase (SDHa), glyceraldehyde-3P-dehydrogenase (GAPDH), elongation factor 1 alpha (EF1a) and annexin IX (AnnIX). The relative transcription levels of these eight genes were then analyzed in three treatment groups differing in rearing density (isolated, short- and long-term crowded), each made up of five pools of four neural tissue samples from 5th instar nymphs. SDHa and GAPDH, which are both involved in metabolic pathways, were identified as the least stable in expression levels, challenging their usefulness in normalization. Based on calculations performed with the geNorm and NormFinder programs, the best combination of two genes for normalization of gene expression data following crowding in the Australian plague locust was EF1a and Arm. We applied their use to studying a target gene that encodes a Ca2+ binding glycoprotein, SPARC, which was previously found to be up-regulated in brains of gregarious desert locusts, Schistocerca gregaria. Interestingly, expression of this gene did not vary with rearing density in the same way in brains of the two locust species. Unlike S. gregaria, there was no effect of any crowding treatment in the Australian plague locust.

Conclusion

Arm and EF1a is the most stably expressed combination of two reference genes of the eight examined for reliable normalization of RT-qPCR assays studying density-dependent behavioural change in the Australian plague locust. Such normalization allowed us to show that C. terminifera crowding did not change the neuronal expression of the SPARC gene, a gregarious phase-specific gene identified in brains of the desert locust, S. gregaria. Such comparative results on density-dependent gene regulation provide insights into the evolution of gregarious behaviour and mass migration of locusts. The eight identified genes we evaluated are also candidates as normalization genes for use in experiments involving other Oedipodinae species, but the rank order of gene stability must necessarily be determined on a case-by-case basis.