Transcriptome profiling with focus on potential key genes for wing development and evolution in Megaloprepus caerulatus, the damselfly species with the world's largest wings

Abstract

The evolution, development and coloration of insect wings remains a puzzling subject in evolutionary research. In basal flying insects such as Odonata, genomic research regarding bauplan evolution is still rare. Here we focus on the world’s largest odonate species—the “forest giant” Megaloprepus caerulatus, to explore its potential for looking deeper into the development and evolution of wings. A recently discovered cryptic species complex in this genus previously considered monotypic is characterized by morphological differences in wing shape and color patterns. As a first step toward understanding wing pattern divergence and pathways involved in adaptation and speciation at the genomic level, we present a transcriptome profiling of M. caerulatus using RNA-Seq and compare these data with two other odonate species. The de novo transcriptome assembly consists of 61,560 high quality transcripts and is approximately 93% complete. For almost 75% of the identified transcripts a possible function could be assigned: 48,104 transcripts had a hit to an InterPro protein family or domain, and 28,653 were mapped to a Gene Ontology term. In particular, we focused on genes related to wing development and coloration. The comparison with two other species revealed larva-specific genes and a conserved ‘core’ set of over 8,000 genes forming orthologous clusters with Ischnura elegans and Ladona fulva. This transcriptome may provide a first point of reference for future research in odonates addressing questions surrounding the evolution of wing development, wing coloration and their role in speciation.

Metals and metal isotopes in insect wings: Implications for diet, geolocation and pollution exposure

“…Molybdenum showed a negative correlation to body mass (Table 1). Molybdenum is an essential metal that acts as a co-factor for many oxidase enzymes (Dow 2017), some of which relate to wing pigmentation (Feindt et al . 2018) and immune processes (Selvey 2020).…”

“…Molybdenum showed a negative correlation to body mass (Table 1). Molybdenum is an essential metal that acts as a co-factor for many oxidase enzymes (Dow 2017), some of which relate to wing pigmentation (Feindt et al 2018) and immune processes (Selvey 2020). The decrease in Mo concentration in wings with increasing body size might be related to differential regulation of the metal relative to body size, energy reserves, or sex (Orłowski et al 2020).…”

Good Citizenship Made Easy: A Step‐by‐Step Guide to Submitting RNA‐Seq Data to NCBI

“…Grahnen, Benkman, & Buerkle, 2010), novel gene identification (e.g., Feindt, Oppenheim, DeSalle, Goldstein, & Hadrys, 2018;Gruber et al, 2015;Mehr et al, 2013;, and gene expression profiling (Alves-Carvalho et al, 2015;Lopez-Maestre et al, 2016;Simon et al, 2017). Yet in spite of this diversity, all RNA-Seq studies share one feature: the generation of enormous amounts of sequence data.…”

“…The vast amount of data obtained from NGS studies has the potential to change the way we understand genomic and phenotypic variation, organismal development, speciation, and the origin and maintenance of biodiversity. Grahnen, Benkman, & Buerkle, 2010), novel gene identification (e.g., Feindt, Oppenheim, DeSalle, Goldstein, & Hadrys, 2018;Gruber et al, 2015;Mehr et al, 2013;, and gene expression profiling (Alves-Carvalho et al, 2015;Lopez-Maestre et al, 2016;Simon et al, 2017). The goals of such studies are diverse, and include the generation of EST databases (e.g., Jeukens, Renaut, St-Cyr, Nolte, & Bernatchez, 2010;Kumar & Blaxter, 2010), functional annotation (e.g., Crawford et al, 2010), SNP discovery (e.g., Novaes et al, 2008;Parchman, Geist, Figure 1 Overview of all necessary steps for submission of raw sequence reads and Transcriptome assemblies to NCBI.…”

“…The goals of such studies are diverse, and include the generation of EST databases (e.g., Jeukens, Renaut, St-Cyr, Nolte, & Bernatchez, 2010;Kumar & Blaxter, 2010), functional annotation (e.g., Crawford et al, 2010), SNP discovery (e.g., Novaes et al, 2008;Parchman, Geist, Figure 1 Overview of all necessary steps for submission of raw sequence reads and Transcriptome assemblies to NCBI. Grahnen, Benkman, & Buerkle, 2010), novel gene identification (e.g., Feindt, Oppenheim, DeSalle, Goldstein, & Hadrys, 2018;Gruber et al, 2015;Mehr et al, 2013;, and gene expression profiling (Alves-Carvalho et al, 2015;Lopez-Maestre et al, 2016;Simon et al, 2017). Yet in spite of this diversity, all RNA-Seq studies share one feature: the generation of enormous amounts of sequence data.…”