Brain de novo transcriptome assembly of a toad species showing polymorphic anti-predatory behavior

Abstract

Understanding the genomic underpinnings of antipredatory behaviors is a hot topic in eco-evolutionary research. Yellow-bellied toad of the genus Bombina are textbook examples of the deimatic display, a time-structured behavior aimed at startling predators. Here, we generated the first de novo brain transcriptome of the Apennine yellow-bellied toad Bombina pachypus, a species showing inter-individual variation in the deimatic display. Through Rna-Seq experiments on a set of individuals showing distinct behavioral phenotypes, we generated 316,329,573 reads, which were assembled and annotated. The high-quality assembly was confirmed by assembly validators and by aligning the contigs against the de novo transcriptome with a mapping percentage higher than 91.0%. The homology annotation with DIAMOND (blastx) led to 77,391 contigs annotated on Nr, Swiss Prot and TrEMBL, whereas the domain and site protein prediction made with InterProScan led to 4747 GO-annotated and 1025 KEGG-annotated contigs. The B. pachypus transcriptome described here will be a valuable resource for further studies on the genomic underpinnings of behavioral variation in amphibians.

Integrated de novo transcriptome of Culex pipiens mosquito larvae as a resource for genetic control strategies

“…The resulting data was then uploaded to figshare for further analysis (see Datafile 2 on Table 2). Subsequently, we employed Corset (v. 1.06) 50 , a tool that has demonstrated its efficacy in a previous study 51 , to generate the final assembly. The Corset output showed an N50 of 2208 bp (Table 3).…”

De novo transcriptome assembly and annotation for gene discovery in Salamandra salamandra at the larval stage

“…Here, we focused transcriptome analyses on tissues extracted from the cephalic region, as the brain is a target tissue for investigating the genetic background of behavior 13 , 14 . In fact, there is evidence showing that brain gene expression patterns can reflect behavioral state in response to environmental stimuli 15 , 16 .…”