Comparative analysis of phenotypic plasticity sheds light on the evolution and molecular underpinnings of locust phase polyphenism

Files can be found here: https://doi.org/10.5061/dryad.dz08kprwz Supplementary Data File 1: Differentially expressed genes for the head tissue of piceifrons, and their annotation. This table lists all differentially expressed genes for the head tissue of piceifrons, discovered by either DEseq2 or edgeR, and their annotation by Blast2GO. For both DEseq2 and edgeR, the Log2FoldChange (Log2FC) and adjusted p value (padj) were given for each contig. Additionally, gene annotation was obtained with Blast2GO, and the following outputs were given: the gene description, based on BLAST hits (Gene description), contig length (Length), the Expect value associated with the best BLAST hit (E value), the mean similarity at the nucleotide level to its BLAST hits (Similarity), the Gene Ontology IDs (GO IDs) and Gene Ontology names (GO names), and finally the annotation confidence level, for which ‘interpro’ refers to sequences with a hit to the interpro database, ‘blasted’ refers to sequences with at least one BLAST hit to the arthropod nr database, ‘mapped’ was given to sequences for which gene ontology information could be retrieved from its BLAST hit(s), and ‘annotated’ was only given to sequences for which the mapped GO terms also scored above the default thresholds for annotation. Supplementary Data File 2: Differentially expressed genes for the thorax tissue of piceifrons, and their annotation. This table lists all differentially expressed genes for the thorax tissue of piceifrons, discovered by either DEseq2 or edgeR, and their annotation by Blast2GO. For both DEseq2 and edgeR, the Log2FoldChange (Log2FC) and adjusted p value (padj) were given for each contig. Additionally, gene annotation was obtained with Blast2GO, and the following outputs were given: the gene description, based on BLAST hits (Gene description), contig length (Length), the Expect value associated with the best BLAST hit (E value), the mean similarity at the nucleotide level to its BLAST hits (Similarity), the Gene Ontology IDs (GO IDs) and Gene Ontology names (GO names), and finally the annotation confidence level, for which ‘interpro’ refers to sequences with a hit to the interpro database, ‘blasted’ refers to sequences with at least one BLAST hit to the arthropod nr database, ‘mapped’ was given to sequences for which gene ontology information could be retrieved from its BLAST hit(s), and ‘annotated’ was only given to sequences for which the mapped GO terms also scored above the default thresholds for annotation. Supplementary Data File 3: Differentially expressed genes for the head tissue of americana, and their annotation. This table lists all differentially expressed genes for the head tissue of americana, discovered by either DEseq2 or edgeR, and their annotation by Blast2GO. For both DEseq2 and edgeR, the Log2FoldChange (Log2FC) and adjusted p value (padj) were given for each contig. Additionally, gene annotation was obtained with Blast2GO, and the following outputs were given: the gene description, based on BLAST hits (Gene description), contig length (Length), the Expect value associated with the best BLAST hit (E value), the mean similarity at the nucleotide level to its BLAST hits (Similarity), the Gene Ontology IDs (GO IDs) and Gene Ontology names (GO names), and finally the annotation confidence level, for which ‘interpro’ refers to sequences with a hit to the interpro database, ‘blasted’ refers to sequences with at least one BLAST hit to the arthropod nr database, ‘mapped’ was given to sequences for which gene ontology information could be retrieved from its BLAST hit(s), and ‘annotated’ was only given to sequences for which the mapped GO terms also scored above the default thresholds for annotation. Supplementary Data File 4: Differentially expressed genes for the thorax tissue of americana, and their annotation. This table lists all differentially expressed genes for the thorax tissue of americana, discovered by either DEseq2 or edgeR, and their annotation by Blast2GO. For both DEseq2 and edgeR, the Log2FoldChange (Log2FC) and adjusted p value (padj) were given for each contig. Additionally, gene annotation was obtained with Blast2GO, and the following outputs were given: the gene description, based on BLAST hits (Gene description), contig length (Length), the Expect value associated with the best BLAST hit (E value), the mean similarity at the nucleotide level to its BLAST hits (Similarity), the Gene Ontology IDs (GO IDs) and Gene Ontology names (GO names), and finally the annotation confidence level, for which ‘interpro’ refers to sequences with a hit to the interpro database, ‘blasted’ refers to sequences with at least one BLAST hit to the arthropod nr database, ‘mapped’ was given to sequences for which gene ontology information could be retrieved from its BLAST hit(s), and ‘annotated’ was only given to sequences for which the mapped GO terms also scored above t ...

Locusts exhibit one of nature’s most spectacular examples of complex phenotypic plasticity, in which changes in density cause solitary and cryptic individuals to transform into gregarious and conspicuous locusts forming large migrating swarms. We investigated how these coordinated alternative phenotypes might have evolved by studying the Central American locust and three closely related non-swarming grasshoppers in a comparative framework. By experimentally isolating and crowding during nymphal development, we induced density-dependent phenotypic plasticity and quantified the resulting behavioural, morphological, and molecular reaction norms. All four species exhibited clear plasticity, but the individual reaction norms varied among species and showed different magnitudes. Transcriptomic responses were species-specific, but density-responsive genes were functionally similar across species. There were modules of co-expressed genes that were highly correlated with plastic reaction norms, revealing a potential molecular basis of density-dependent phenotypic plasticity. These findings collectively highlight the importance of studying multiple reaction norms from a comparative perspective.

Details about the data collection and processing are found in the Supplementary Information file.