PumaPlex 1.0: Data generated during the development of the SNP markers and SNP genotypes of pumas

Pumas are one of the most studied terrestrial mammals because of their widespread distribution, substantial ecological impacts, and conflicts with humans. Extensive efforts, often employing genetic methods, are undertaken to manage this species. However, the comparison of population genetic data is difficult because few of the microsatellite loci chosen are shared across research programs. Here, we describe the development of PumaPlex, a high-throughput assay to genotype 25 single nucleotide polymorphisms in pumas. We validated PumaPlex in more than 700 North American pumas (Puma concolor couguar), and demonstrated its ability to generate reproducible genotypes and accurately identify individuals. Furthermore, we compared PumaPlex with traditional genotyping of 12 microsatellite loci in fecal DNA samples and found that PumaPlex produced significantly more genotypes with fewer false alleles. PumaPlex promotes the cross-laboratory comparison of genotypes, is easily expandable in the future, and is a valuable tool for the genetic monitoring and management of North American puma populations.

Maize Stress DIESI-MS Data and R Script

Climatic change is an increasing challenge for agriculture that is driving the development of suitable crops in order to ensure supply for both human nutrition and animal feed. In this context, it is increasingly important to understand the biochemical responses of cells to environmental cues at the whole system level, an aim that is being brought closer by advances in high throughput, cost-efficient plant metabolomics. To support molecular breeding activities, we have assessed the economic, technical and statistical feasibility of using direct mass spectrometry methods to evaluate the physiological state of maize (Zea mays L.) plants grown under different stress conditions.

Coastal plankton communities under elevated CO2: community barcoding results, link to data files in FASTA format

The acidification of the oceans could potentially alter marine plankton communities with consequences for ecosystem functioning. While several studies have investigated effects of ocean acidifications on communities using traditional methods, few have used genetic analyses. Here, we use community barcoding to assess the impact of ocean acidification on the composition of a coastal plankton community in a large scale, in situ, long-term mesocosm experiment. High-throughput sequencing resulted in the identification of a wide range of planktonic taxa (Alveolata, Cryptophyta, Haptophyceae, Fungi, Metazoa, Hydrozoa, Rhizaria, Straminipila, Chlorophyta). Analyses based on predicted operational taxonomical units as well as taxonomical compositions revealed no differences between communities in high CO2 mesocosms (~760 µatm) and those exposed to present day CO2 conditions. Observed shifts in the planktonic community composition were mainly related to seasonal changes in temperature and nutrients.

Fragilariopsis kerguelensis images from sediment core PS1768-8

Background: Light microscopic analysis of diatom frustules is widely used both in basic and applied research, notably taxonomy, morphometrics, water quality monitoring and paleo-environmental studies. In these applications, usually large numbers of frustules need to be identified and / or measured. Although there is a need for automation in these applications, and image processing and analysis methods supporting these tasks have previously been developed, they did not become widespread in diatom analysis. While methodological reports for a wide variety of methods for image segmentation, diatom identification and feature extraction are available, no single implementation combining a subset of these into a readily applicable workflow accessible to diatomists exists. Results: The newly developed tool SHERPA offers a versatile image processing workflow focused on the identification and measurement of object outlines, handling all steps from image segmentation over object identification to feature extraction, and providing interactive functions for reviewing and revising results. Special attention was given to ease of use, applicability to a broad range of data and problems, and supporting high throughput analyses with minimal manual intervention. Conclusions: Tested with several diatom datasets from different sources and of various compositions, SHERPA proved its ability to successfully analyze large amounts of diatom micrographs depicting a broad range of species. SHERPA is unique in combining the following features: application of multiple segmentation methods and selection of the one giving the best result for each individual object; identification of shapes of interest based on outline matching against a template library; quality scoring and ranking of resulting outlines supporting quick quality checking; extraction of a wide range of outline shape descriptors widely used in diatom studies and elsewhere; minimizing the need for, but enabling manual quality control and corrections. Although primarily developed for analyzing images of diatom valves originating from automated microscopy, SHERPA can also be useful for other object detection, segmentation and outline-based identification problems.

Geochemistry of pockmark sediments from the inner Oslofjord

Pockmarks are geological features that are found on the bottom of lakes and oceans all over the globe. Some are active, seeping oil or methane, while others are inactive. Active pockmarks are well studied since they harbor specialized microbial communities that proliferate on the seeping compounds. Such communities are not found in inactive pockmarks. Interestingly, inactive pockmarks are known to have different macrofaunal communities compared to the surrounding sediments. It is undetermined what the microbial composition of inactive pockmarks is and if it shows a similar pattern as the macrofauna. The Norwegian Oslo Fjord contains many inactive pockmarks and they are well suited to study the influence of these geological features on the microbial community in the sediment. Here we present a detailed analysis of the microbial communities found in three inactive pockmarks and two control samples at two core depth intervals. The communities were analyzed using high-throughput amplicon sequencing of the 16S rRNA V3 region. Microbial communities of surface pockmark sediments were indistinguishable from communities found in the surrounding seabed. In contrast, pockmark communities at 40 cm sediment depth had a significantly different community structure from normal sediments at the same depth. Statistical analysis of chemical variables indicated significant differences in the concentrations of total carbon and non-particulate organic carbon between 40 cm pockmark and reference sample sediments. We discuss these results in comparison with the taxonomic classification of the OTUs identified in our samples. Our results indicate that microbial surface sediment communities are affect by the water column, while the 40 cm communities are affect by local conditions within the sediment.