RESUMEN
Background: 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 data-biodiversity-aq@naturalsciences.be. New information: This dataset adds vital occurrence and abundance data for pycnogonids from 10 previously unexamined research cruises from the Weddell Sea, Antarctic Penisula and the islands of the Scotia Arc. It includes the first pycnogonid data from the Prince Gustav Channel. The 197 sampling stations within this dataset represent an 11% increase in the number of stations where pycnogonids have been recorded in the Southern Ocean, southern South America and New Zealand waters and an 18% increase for above 60 degrees latitude. Presence data for any observed epifauna are also included.
RESUMEN
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.