Combining morphological and genomic evidence to resolve species diversity and study speciation processes of the Pallenopsis patagonica (Pycnogonida) species complex

Background: Pallenopsis patagonica (Hoek, 1881) is a morphologically and genetically variable sea spider species whose taxonomic classification is challenging. Currently, it is considered as a species complex including several genetic lineages, many of which have not been formally described as species. Members of this species complex occur on the Patagonian and Antarctic continental shelves as well as around sub-Antarctic islands. These habitats have been strongly influenced by historical large-scale glaciations and previous studies suggested that communities were limited to very few refugia during glacial maxima. Therefore, allopatric speciation in these independent refugia is regarded as a common mechanism leading to high biodiversity of marine benthic taxa in the high-latitude Southern Hemisphere. However, other mechanisms such as ecological speciation have rarely been considered or tested. Therefore, we conducted an integrative morphological and genetic study on the P. patagonica species complex to i) resolve species diversity using a target hybrid enrichment approach to obtain multiple genomic markers, ii) find morphological characters and analyze morphometric measurements to distinguish species, and iii) investigate the speciation processes that led to multiple lineages within the species complex. Results: Phylogenomic results support most of the previously reported lineages within the P. patagonica species complex and morphological data show that several lineages are distinct species with diagnostic characters. Two lineages are proposed as new species, P. aulaeturcarum sp. nov. Dömel & Melzer, 2019 and P. obstaculumsuperavit sp. nov. Dömel, 2019, respectively. However, not all lineages could be distinguished morphologically and thus likely represent cryptic species that can only be identified with genetic tools. Further, morphometric data of 135 measurements showed a high amount of variability within and between species without clear support of adaptive divergence in sympatry. Conclusions: We generated an unprecedented molecular data set for members of the P. patagonica sea spider species complex with a target hybrid enrichment approach, which we combined with extensive morphological and morphometric analyses to investigate the taxonomy, phylogeny and biogeography of this group. The extensive data set enabled us to delineate species boundaries, on the basis of which we formally described two new species. No consistent evidence for positive selection was found, rendering speciation in allopatric glacial refugia as the most likely model of speciation

Sea spiders (Arthropoda, Pycnogonida) from ten recent research expeditions to the Antarctic Peninsula, Scotia Arc and Weddell Sea - data

This dataset contains information on specimens of Southern Ocean Pycnogonida (Arthropoda), that were collected from ten different research cruises, spanning 13 years. The individual aims and objectives of each cruise can be found in their cruise reports. The specimens have been collated into a single dataset, forming the basis of J. Maxwell’s PhD. The dataset will be used to investigate the community structure of Antarctic pycnogonids and the factors which influence its composition. This dataset is published by SCAR-AntOBIS under the licence CC-BY 4.0. Please follow the guidelines from the SCAR and IPY Data Policies (https://www.scar.org/excom-meetings/xxxi-scar-delegates-2010-buenos-aires-argentina/4563-scar-xxxi-ip04b-scar-data-policy/file/) when using the data. If you have any questions regarding this dataset, please do not hesitate to contact us via the contact information provided in the metadata or via [email protected]

Exploring Pandora's Box: potential and pitfalls of low coverage genome surveys for evolutionary biology

High throughput sequencing technologies are revolutionizing genetic research. With this ‘‘rise of the machines’’, genomic sequences can be obtained even for unknown genomes within a short time and for reasonable costs. This has enabled evolutionary biologists studying genetically unexplored species to identify molecular markers or genomic regions of interest (e.g. micro- and minisatellites, mitochondrial and nuclear genes) by sequencing only a fraction of the genome. However, when using such datasets from non-model species, it is possible that DNA from non-target contaminant species such as bacteria, viruses, fungi, or other eukaryotic organisms may complicate the interpretation of the results. In this study we analysed 14 genomic pyrosequencing libraries of aquatic non-model taxa from four major evolutionary lineages. We quantified the amount of suitable micro- and minisatellites, mitochondrial genomes, known nuclear genes and transposable elements and searched for contamination from various sources using bioinformatic approaches. Our results show that in all sequence libraries with estimated coverage of about 0.02–25%, many appropriate micro- and minisatellites, mitochondrial gene sequences and nuclear genes from different KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways could be identified and characterized. These can serve as markers for phylogenetic and population genetic analyses. A central finding of our study is that several genomic libraries suffered from different biases owing to non-target DNA or mobile elements. In particular, viruses, bacteria or eukaryote endosymbionts contributed significantly (up to 10%) to some of the libraries analysed. If not identified as such, genetic markers developed from high-throughput sequencing data for non-model organisms may bias evolutionary studies or fail completely in experimental tests. In conclusion, our study demonstrates the enormous potential of low-coverage genome survey sequences and suggests bioinformatic analysis workflows. The results also advise a more sophisticated filtering for problematic sequences and non-target genome sequences prior to developing markers

Hits of nuclear genes against KEGG BRITE Ontology database using the KAAS pipeline for the 16 genomic libraries.

<p>The number of hits is listed below the species name. Colours assigned according to the highest level of KEGG Orthology hierarchy (different organismal/cellular pathway groups/ecosystem processes).</p

Percentage of contigs with candidate microsatellites found in the non-enriched libraries with three different search parameter settings.

<p>Search parameter settings were adapted from the three studies <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049202#pone.0049202-Gardner1" target="_blank">[4]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049202#pone.0049202-Santana1" target="_blank">[15]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049202#pone.0049202-Mayer2" target="_blank">[48]</a> and used in Phobos <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049202#pone.0049202-Mayer1" target="_blank">[47]</a> runs. Numbers on top of the columns represent the total number of perfect microsatellites retained after restrictive filtering for quality criteria.</p

Characteristics of contigs with homology to viral protein sequences in the libraries.

<p>Characteristics of contigs with homology to viral protein sequences in the libraries.</p

Correlation between genomic library size (y-axis) and total length of mitochondrial genome recovered (x-axis).

<p>A significantly positive linear correlation (Pearson r = 0.6049, P = 0.0219) between the number of base pairs sequenced and the proportion of the mitochondrial genome recovered was found.</p

rRNA genes found in the different libraries.

<p>The total number of reads, the number of assembled contigs with coverage and the total unique rRNA gene bp are listed.</p

Workflow showing the methodological approach followed in this study.

<p>In this study we used a MySQL database (*) for storing the contigs. Other database formats are possible or reads can also be stored locally without a specific database.</p

Characteristics of contigs with homology to known transposable elements in the libraries.

<p>Characteristics of contigs with homology to known transposable elements in the libraries.</p