390 research outputs found
Biodiversity changes and their functional consequences in the pelagic ecosystems of the central Baltic Sea, cruise AL522, 15 May â 30 May 2019, Kiel (Germany) â Kiel (Germany)
Cruise Report AL509 R.V. Alkor
Dates of Cruise: 15.05. â 30.05.2018
Areas of Research: Physical, chemical, biological and fishery oceanography
Port Calls: Riga. Latvia, 22.05.201
1. Wochenbericht AL522
Wochenbericht FS Alkor Reise 522 "Ostsee Mai", 1. Fahrtabschnitt 15.05 â 25.05.201
Audioâvisual document and popularisation publication for communicating the projects activities and main achievements to a nonâspecialist audience
Blue mussels Mytilus edulis do not interfere with eelgrass Zostera marina but fertilize shoot growth through biodeposition
Eco-Evolutionary Interaction in Competing Phytoplankton: Nutrient Driven Genotype Sorting Likely Explains Dominance Shift and Species Responses to CO2
How ecological and evolutionary processes interact and together determine species and community responses to climate change is poorly understood. We studied long-term dynamics (over approximately 200 asexual generations) in two phytoplankton species, a coccolithophore (Emiliania huxleyi), and a diatom (Chaetoceros affinis), to increased CO2 growing alone, or competing with one another in co-occurrence. To allow for rapid evolutionary responses, the experiment started with a standing genetic variation of nine genotypes in each of the species. Under co-occurrence of both species, we observed a dominance shift from C. affinis to E. huxleyi after about 120 generations in both CO2 treatments, but more pronounced under high CO2. Associated with this shift, we only found weak adaptation to high CO2 in the diatom and none in the coccolithophore in terms of speciesâ growth rates. In addition, no adaptation to interspecific competition could be observed by comparing the single to the two-species treatments in reciprocal assays, regardless of the CO2 treatment. Nevertheless, highly reproducible genotype sorting left only one genotype remaining for each of the species among all treatments. This strong evolutionary selection coincided with the dominance shift from C. affinis to E. huxleyi. Since all other conditions were kept constant over time, the most parsimonious explanation for the dominance shift is that the strong evolutionary selection was driven by the experimental nutrient conditions, and in turn potentially altered competitive ability of the two species. Thus, observed changes in the simplest possible two-species phytoplankton âcommunityâ demonstrated that eco-evolutionary interactions can be critical for predicting community responses to climate change in rapidly dividing organisms such as phytoplankton
An improved filtering algorithm for big read datasets and its application to single-cell assembly
Background: For single-cell or metagenomic sequencing projects, it is necessary to sequence with a very high mean coverage in order to make sure that all parts of the sample DNA get covered by the reads produced. This leads to huge datasets with lots of redundant data. A filtering of this data prior to assembly is advisable. Brown et al. (2012) presented the algorithm Diginorm for this purpose, which filters reads based on the abundance of their k-mers. Methods: We present Bignorm, a faster and quality-conscious read filtering algorithm. An important new algorithmic feature is the use of phred quality scores together with a detailed analysis of the k-mer counts to decide which reads to keep. Results: We qualify and recommend parameters for our new read filtering algorithm. Guided by these parameters, we remove in terms of median 97.15% of the reads while keeping the mean phred score of the filtered dataset high. Using the SDAdes assembler, we produce assemblies of high quality from these filtered datasets in a fraction of the time needed for an assembly from the datasets filtered with Diginorm. Conclusions: We conclude that read filtering is a practical and efficient method for reducing read data and for speeding up the assembly process. This applies not only for single cell assembly, as shown in this paper, but also to other projects with high mean coverage datasets like metagenomic sequencing projects. Our Bignorm algorithm allows assemblies of competitive quality in comparison to Diginorm, while being much faster. Bignorm is available for download at https://git.informatik.uni-kiel.de/axw/Bignorm
An improved filtering algorithm for big read datasets and its application to single-cell assembly
Background: For single-cell or metagenomic sequencing projects, it is necessary to sequence with a very high mean coverage in order to make sure that all parts of the sample DNA get covered by the reads produced. This leads to huge datasets with lots of redundant data. A filtering of this data prior to assembly is advisable. Brown et al. (2012) presented the algorithm Diginorm for this purpose, which filters reads based on the abundance of their k-mers. Methods: We present Bignorm, a faster and quality-conscious read filtering algorithm. An important new algorithmic feature is the use of phred quality scores together with a detailed analysis of the k-mer counts to decide which reads to keep. Results: We qualify and recommend parameters for our new read filtering algorithm. Guided by these parameters, we remove in terms of median 97.15% of the reads while keeping the mean phred score of the filtered dataset high. Using the SDAdes assembler, we produce assemblies of high quality from these filtered datasets in a fraction of the time needed for an assembly from the datasets filtered with Diginorm. Conclusions: We conclude that read filtering is a practical and efficient method for reducing read data and for speeding up the assembly process. This applies not only for single cell assembly, as shown in this paper, but also to other projects with high mean coverage datasets like metagenomic sequencing projects. Our Bignorm algorithm allows assemblies of competitive quality in comparison to Diginorm, while being much faster. Bignorm is available for download at https://git.informatik.uni-kiel.de/axw/Bignorm
Salinity change impairs pipefish immune defence
a b s t r a c t Global change is associated with fast and severe alterations of environmental conditions. Superimposed onto existing salinity variations in a semi-enclosed brackish water body such as the Baltic Sea, a decrease in salinity is predicted due to increased precipitation and freshwater inflow. Moreover, we predict that heavy precipitation events will accentuate salinity fluctuations near shore. Here, we investigated how the immune function of the broad-nosed pipefish (Syngnathus typhle), an ecologically important teleost with sex-role reversal, is influenced by experimentally altered salinities (control: 18 PSU, lowered: 6 PSU, increased: 30 PSU) upon infection with bacteria of the genus Vibrio. Salinity changes resulted in increased activity and proliferation of immune cells. However, upon Vibrio infection, individuals at low salinity were unable to mount specific immune response components, both in terms of monocyte and lymphocyte cell proliferation and immune gene expression compared to pipefish kept at ambient salinities. We interpret this as resource allocation trade-off, implying that resources needed for osmoregulation under salinity stress are lacking for subsequent activation of the immune defence upon infection. Our data suggest that composition of small coastal fish communities may change due to elevated environmental stress levels and the incorporated consequences thereof
- âŠ