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Sexual Dimorphism in Growth Rate and Gene Expression Throughout Immature Development in Wild Type Chrysomya rufifacies (Diptera: Calliphoridae) Macquart

NCJ Number
310035
Journal
Frontiers in Ecology and Evolution Volume: 9 Dated: July 2021 Pages: 696638
Author(s)
Meaghan L. Pimsler; Carl E. Hjelmen; Michelle M. Jonika; Anika Sharma; Shuhua Fu; Madhu Bala; Sing-Hoi Sze; Jeffery K. Tomberlin; Aaron M. Tarone
Date Published
July 2021
Length
25 pages
Annotation

This study examines sexual dimorphism in growth rate and gene expression in Chrysomya rufifacies.

Abstract

Using modified breeding procedures (to ensure single-female egg clutches) and transcriptomics, the authors of this study investigated sexual dimorphism in Chrysomya rufifacies  (Diptera: Calliphoridae) Macquart in terms of development rate and gene expression. The researchers found that 98.4% of assembled nodes exhibited sex-specific, stage-specific, to sex-by-stage specific patterns of expression. However, the greatest signal in the expression data is differentiation by developmental stage, indicating that sexual dimorphism in gene expression during development may not be relevant and that markers of age may be relatively independent of sex. Subtle differences in these gene expression patterns can be detected as early as 4 hours post-oviposition, and 12 of these nodes demonstrate homology with key Drosophila sex determination genes, providing clues regarding the distinct sex determination mechanism of C. rufifacies. Finally, researchers validated the transcriptome analyses through qPCR and have identified five genes that are developmentally informative within and between sexes. Chrysomya rufifacies has a monogenic sex determination system, meaning females have only a single-sex of offspring throughout their life. Females develop slower than males even at 30°C, with an average egg-to-eclosion time of 225 h for males and 234 h for females. Given that many key genes rely on sex-specific splicing for the development and maintenance of sexually dimorphic traits, researchers used a transcriptomic approach to identify different expression of gene splice variants. (Published Abstract Provided)