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- W2964915706 abstract "Abstract The hemipteran suborder Auchenorrhyncha is a highly diverse, ecologically and agriculturally important group of primarily phytophagous insects which has been a source of phylogenetic contention for many years. Here, we have used transcriptome sequencing to assemble 2139 orthologues from 84 auchenorrhynchan species representing 27 families; this is the largest and most taxonomically comprehensive phylogenetic dataset for this group to date. We used both maximum likelihood and multispecies coalescent analyses to reconstruct the evolutionary history in this group using amino acid, nucleotide, and degeneracy‐coded nucleotide orthologue data. Although many relationships at the superfamily level were consistent between analyses, several differing, highly supported topologies were recovered using different datasets and reconstruction methods, most notably the differential placement of Cercopoidea as sister to either Cicadoidea or Membracoidea. To further interrogate the recovered topologies, we explored the contribution of genes as partitioned by third‐codon‐position guanine‐cytosine (GC) content and heterogeneity. We found consistent support for several relationships, including Cercopoidea + Cicadoidea, most often in genes that would be expected to be enriched for the true species tree if recombination‐based dynamics in GC content have contributed to the observed GC heterogeneity. Our results provide a generally well‐supported framework for future studies of auchenorrhynchan phylogeny and suggest that transcriptome sequencing is likely to be a fruitful source of phylogenetic data for resolving its clades. However, we caution that future work should account for the potential effects of GC content heterogeneity on relationships recovered in this group." @default.
- W2964915706 created "2019-08-13" @default.
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- W2964915706 date "2019-07-31" @default.
- W2964915706 modified "2023-10-13" @default.
- W2964915706 title "Phylogenomics of Auchenorrhyncha (Insecta: Hemiptera) using transcriptomes: examining controversial relationships via degeneracy coding and interrogation of gene conflict" @default.
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