ArticleGenome biology and evolution2015
The Utility of Genome Skimming for Phylogenomic Analyses as Demonstrated for Glycerid Relationships (Annelida, Glyceridae).
Article in Genome biology and evolution, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed, 84 citations in OpenAlex.
- Functional Anatomy of the Pharynx of Glycera tridactyla Schmarda, 1861 (Annelida: Glyceriformia: Glyceridae).Journal of morphology · 2026Article
- Extensive transcriptome data providing great efficacy in genetic research and adaptive gene discovery: a case study ofFrontiers in plant science · 2024Article
- ORFans in Mitochondrial Genomes of Marine Polychaete Polydora.Genome biology and evolution · 2023Article
- Patchwork: Alignment-Based Retrieval and Concatenation of Phylogenetic Markers from Genomic Data.Genome biology and evolution · 2023Article
- Shallow Whole-Genome Sequencing ofInsects · 2023Article
- First report of the mitogenome of the invasive reef-building polychaete Ficopomatus enigmaticus (Annelida: Serpulidae) and a cryptic lineage from the Japanese Archipelago.Molecular biology reports · 2023Article
- Mitochondrial Genome Evolution in Annelida-A Systematic Study on Conservative and Variable Gene Orders and the Factors Influencing its Evolution.Systematic biology · 2023Article
- Mitochondrial genome ofMitochondrial DNA. Part B, Resources · 2023Article
- Article
- Confirmation of the first intronic sequence in the bivalvian mitochondrial genome ofBiology letters · 2022Article
- Unprecedented frequency of mitochondrial introns in colonial bilaterians.Scientific reports · 2022Article
- Mitogenome of a stink worm (Annelida: Travisiidae) includes degenerate group II intron that is also found in five congeneric species.Scientific reports · 2022Article
- First mitochondrial genomes of Capitellidae and Opheliidae (Annelida) and their phylogenetic placement.Mitochondrial DNA. Part B, Resources · 2022Article
- Genomic skimming and nanopore sequencing uncover cryptic hybridization in one of world's most threatened primates.Scientific reports · 2021Article
- Mitochondrial genomes of two Polydora (Spionidae) species provide further evidence that mitochondrial architecture in the Sedentaria (Annelida) is not conserved.Scientific reports · 2021Article
- Sequence Comparison Without Alignment: The SpaM Approaches.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Extensive gene rearrangements in the mitogenomes of congeneric annelid species and insights on the evolutionary history of the genus Ophryotrocha.BMC genomics · 2020Article
- Article
- Culicidae evolutionary history focusing on the Culicinae subfamily based on mitochondrial phylogenomics.Scientific reports · 2020Article
- Museomics Unveil the Phylogeny and Biogeography of the Neglected Juan Fernandez ArchipelagoFrontiers in plant science · 2020Article
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Authors and funding
5 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glyceridae (Annelida) are a group of venomous annelids distributed worldwide from intertidal to abyssal depths. To trace the evolutionary history and complexity of glycerid venom cocktails, a solid backbone phylogeny of this group is essential. We therefore aimed to reconstruct the phylogenetic relationships of these annelids using Illumina sequencing technology. We constructed whole-genome shotgun libraries for 19 glycerid specimens and 1 outgroup species (Glycinde armigera). The chosen target genes comprise 13 mitochondrial proteins, 2 ribosomal mitochondrial genes, and 4 nuclear loci (18SrRNA, 28SrRNA, ITS1, and ITS2). Based on partitioned maximum likelihood as well as Bayesian analyses of the resulting supermatrix, we were finally able to resolve a robust glycerid phylogeny and identified three clades comprising the majority of taxa. Furthermore, we detected group II introns inside the cox1 gene of two analyzed glycerid specimens, with two different insertions in one of these species. Moreover, we generated reduced data sets comprising 10 million, 4 million, and 1 million reads from the original data sets to test the influence of the sequencing depth on assembling complete mitochondrial genomes from low coverage genome data. We estimated the coverage of mitochondrial genome sequences in each data set size by mapping the filtered Illumina reads against the respective mitochondrial contigs. By comparing the contig coverage calculated in all data set sizes, we got a hint for the scalability of our genome skimming approach. This allows estimating more precisely the number of reads that are at least necessary to reconstruct complete mitochondrial genomes in Glyceridae and probably non-model organisms in general.
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