Multigenetic phylogeny of the subfamily Larentiinae (Lepidoptera: Geometridae)
Data files
Mar 06, 2024 version files 1.42 MB
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README.md
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Xchloe_Outgroup_7genes_275samp.fas
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Xchloe_Outgroup_7genes_275samp.fas.contree
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Abstract
This dataset is part of a paper, which demonstrates how micro-CT can be applied to provide unambiguous illustrations of diagnostic morphological characters for new taxa description and to understand how micro-CT imaging may complement other imaging techniques. Following micro-CT scanning, a semi-automatic segmentation and volume rendering protocol was used to portray the wing venation and diagnostic structures and ornamentation of male genitalia from multiple angles. Using micro-CT images, we describe a conspicuous geometrid moth from southern Africa (Lepidoptera: Geometridae), which has been present in collections since 1894 but left without an available name. Using a multigenetic dataset comprising 273 terminal taxa from the superfamily Geometroidea, we constructed a molecular phylogeny to place our study species to an isolated lineage in Geometridae: Larentiinae, tribe Xanthorhoini sensu lato. We describe it as Chloecolora vergetaria new genus, new species Englund & Staude, and provide diverse ecological information on its distribution, habitat, host plant, adult and immature stages, and parasites.
README: Larentiinae_Full_Tree_FigS4; Multigenetic phylogeny of the subfamily Larentiinae (Lepidoptera: Geometridae)
https://doi.org/10.5061/dryad.kd51c5bd1
The data file contains fasta and tree files used to construct a molecular phylogeny of the subfamily Larentiinae (Lepidoptera: Geometridae). It is part of the manuscript "130 years from discovery to description: micro-CT scanning applied to construct the integrative taxonomy of a forgotten moth from Southern Africa (Lepidoptera: Geometridae)" that was submitted for referral in a scientific journal as of 2.11.2023.
Description of the data and file structure
The tree consists of 275 protein-coding nuclear and mitochondrial sequences from 273 terminal taxa from the superfamily Geometroidae (Lepidoptera); 2 of them from Uranidae forming an outgroup and the rest from Geometridae, 195 from the subfamily Larentiinae.
Sharing/Access information
The tree contains novel sequences from three specimens of a new Larentine moth species, Chloecolora vergetaria sp.n., the rest originating from previously published datasets. More specific data-sharing info will become available upon publication of the original article.
Code/Software
References for the used software can be found in the forthcoming original article.
Methods
One entire mid-leg or femur, when no complete leg was available, was detached from the Chloecolora vergetaria sp. n. specimens for DNA extraction. Genomic DNA was extracted using the Qiagen DNeasy Blood and Tissue Kit following the manufacturer’s protocol at the Finnish Museum of Natural History (FMNH) molecular laboratory. DNA amplification and sequencing were carried out following protocols proposed by Wahlberg and Wheat (2008): one mitochondrial gene (mtCOI) and six protein-coding nuclear gene regions, Arginine Kinase (ArgK), sarco/endoplasmic reticulum calcium ATPase (Ca-ATPase), Elongation Factor 1 alpha (EF-1alpha), sorting Nexin-9-like (Nex9), Ribosomal Protein (RpS5), and wingless (wgl).
The molecular data extracted from three specimens were included in the dataset of a total of 273 terminal taxa. The remaining 272 terminal taxa, with up to 11 genes per species, were obtained from published data by Murillo-Ramos (Murillo-Ramos et al., 2019). All subfamilies of the family Geometridae were represented in the dataset, and two species from the family Uraniidae were set as an outgroup.
To construct the phylogenetic trees, we applied the maximum likelihood approach as implemented in the IQ-TREE web server (Trifinopoulos et al., 2016). Best-fitting substitution models were selected by ModelFinder (Kalyaanamoorthy et al., 2017) with the “-m MFP+MERGE” option. The phylogenetic analyses were carried out with the “-spp” option (edge proportional), which allowed each partition to have its own evolutionary rate. We evaluated the node supports with ultrafast bootstrap approximations (UFBoot2) and SH-like approximate likelihood ratio test (Guindon et al., 2010; Hoang et al., 2018) using the “-B 1000 -alrt 1000” option. To minimize the risk of overestimating branch supports in ultrafast bootstrap approximation analysis, we used the “-bnni” option, which optimized each bootstrap tree using a hill-climbing nearest-neighbour-interchange (NNI) search.