Ultraconserved elements from transcriptome and genome data provide insight into the phylogenomics of Sternorrhyncha (Insecta: Hemiptera).
Cladistics
; 2024 May 29.
Article
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| MEDLINE
| ID: mdl-38808591
ABSTRACT
Sternorrhyncha, one of the four major suborders of Hemiptera, is a phytophagous taxon inclusive of nearly 18 000 described species. The phylogenetic relationships within the taxon and the earliest-branching lineage of its infraorders remain incompletely understood. This study attempted to illuminate the phylogenetic relationships within Sternorrhyncha through the use of maximum likelihood, Bayesian inference and maximum parsimony analyses, employing ultraconserved element (UCE) data from 39 genomic and 62 transcriptomic datasets and thereby representing most families within the taxon. The probe set Hemiptera 2.7Kv1 was used to recover a total of 2731 UCE loci from 547 to 1699 (with an average of 1084) across all genomic datasets and from 108 to 849 (with an average of 329) across all transcriptomic datasets. All three types of phylogenetic analyses employed in this study produced robust statistical support for Sternorrhyncha being a monophyletic group. The different methods of phylogenetic analysis produced inconsistent descriptions of topological structure at the infraorder level while maximum likelihood and Bayesian inference analyses produced strong statistical evidence (100%) indicating the clade Psylloidea + Aleyrodoidea to be a sister of the clade Aphidoidea (Aphidomorpha) + Coccoidea (Coccomorpha), the maximum parsimony analysis failed to recover a similar result. Our results also provide detail on the phylogenetic relationships within each infraorder. This study presents the first use of UCE data to investigate the phylogeny of Sternorrhyncha. It also shows the viability of amalgamating genomic and transcriptomic data in studies of phylogenetic relationships, potentially highlighting a resource-efficient approach for future inquiries into diverse taxa through the integration of varied data sources.
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01-internacional
Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article