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Properly designed (randomized and/or balanced) experiments are standard in ecological research. Molecular methods are increasingly used in ecology, but studies generally do not report the detailed design of sample processing in the laboratory. This may strongly influence the interpretability of results if the laboratory procedures do not account for the confounding effects of unexpected laboratory events. We demonstrate this with a simple experiment where unexpected differences in laboratory processing of samples would have biased results if randomization in DNA extraction and PCR steps do not provide safeguards. We emphasize the need for proper experimental design and reporting of the laboratory phase of molecular ecology research to ensure the reliability and interpretability of results.
Retrieval of water constituents from hyperspectral in-situ measurements under variable cloud cover
(2018)
Remote sensing and field spectroscopy of natural waters is typically performed under clear skies, low wind speeds and low solar zenith angles. Such measurements can also be made, in principle, under clouds and mixed skies using airborne or in-situ measurements; however, variable illumination conditions pose a challenge to data analysis. In the present case study, we evaluated the inversion of hyperspectral in-situ measurements for water constituent retrieval acquired under variable cloud cover. First, we studied the retrieval of Chlorophyll-a (Chl-a) concentration and colored dissolved organic matter (CDOM) absorption from in-water irradiance measurements. Then, we evaluated the errors in the retrievals of the concentration of total suspended matter (TSM), Chl-a and the absorption coefficient of CDOM from above-water reflectance measurements due to highly variable reflections at the water surface. In order to approximate cloud reflections, we extended a recent three-component surface reflectance model for cloudless atmospheres by a constant offset and compared different surface reflectance correction procedures. Our findings suggest that in-water irradiance measurements may be used for the analysis of absorbing compounds even under highly variable weather conditions. The extended surface reflectance model proved to contribute to the analysis of above-water reflectance measurements with respect to Chl-a and TSM. Results indicate the potential of this approach for all-weather monitoring.
Epigenetic modifications are a mechanism conveying environmental information to subsequent generations via parental germ lines. Research on epigenetic responses to environmental changes in wild mammals has been widely neglected, as well as studies that compare responses to changes in different environmental factors. Here, we focused on the transmission of DNA methylation changes to naive male offspring after paternal exposure to either diet (~40% less protein) or temperature increase (10 °C increased temperature). Because both experiments focused on the liver as the main metabolic and thermoregulation organ, we were able to decipher if epigenetic changes differed in response to different environmental changes. Reduced representation bisulfite sequencing (RRBS) revealed differentially methylated regions (DMRs) in annotated genomic regions in sons sired before (control) and after the fathers’ treatments. We detected both a highly specific epigenetic response dependent on the environmental factor that had changed that was reflected in genes involved in specific metabolic pathways, and a more general response to changes in outer stimuli reflected by epigenetic modifications in a small subset of genes shared between both responses. Our results indicated that fathers prepared their offspring for specific environmental changes by paternally inherited epigenetic modifications, suggesting a strong paternal contribution to adaptive processes.
In this study we compared the phylogeographic patterns of two Rusa species, Rusa unicolor and Rusa timorensis, in order to understand what drove and maintained differentiation between these two geographically and genetically close species and investigated the route of introduction of individuals to the islands outside of the Sunda Shelf. We analyzed full mitogenomes from 56 archival samples from the distribution areas of the two species and 18 microsatellite loci in a subset of 16 individuals to generate the phylogeographic patterns of both species. Bayesian inference with fossil calibration was used to estimate the age of each species and major divergence events. Our results indicated that the split between the two species took place during the Pleistocene, similar to 1.8Mya, possibly driven by adaptations of R. timorensis to the drier climate found on Java compared to the other islands of Sundaland. Although both markers identified two well-differentiated clades, there was a largely discrepant pattern between mitochondrial and nuclear markers. While nDNA separated the individuals into the two species, largely in agreement with their museum label, mtDNA revealed that all R. timorensis sampled to the east of the Sunda shelf carried haplotypes from R. unicolor and one Rusa unicolor from South Sumatra carried a R. timorensis haplotype. Our results show that hybridization occurred between these two sister species in Sundaland during the Late Pleistocene and resulted in human-mediated introduction of hybrid descendants in all islands outside Sundaland.
Genetic studies of the Eurasian brown bear (Ursus arctos) have so far focused on populations from Europe and North America, although the largest distribution area of brown bears is in Asia. In this study, we reveal population genetic parameters for the brown bear population inhabiting the Grand Kackar Mountains (GKM) in the north east of Turkey, western Lesser Caucasus. Using both hair (N = 147) and tissue samples (N = 7) collected between 2008 and 2014, we found substantial levels of genetic variation (10 microsatellite loci). Bear samples (hair) taken from rubbing trees worked better for genotyping than those from power poles, regardless of the year collected. Genotyping also revealed that bears moved between habitat patches, despite ongoing massive habitat alterations and the creation of large water reservoirs. This population has the potential to serve as a genetic reserve for future reintroduction in the Middle East. Due to the importance of the GKM population for on-going and future conservation actions, the impacts of habitat alterations in the region ought to be minimized; e.g., by establishing green bridges or corridors over reservoirs and major roads to maintain habitat connectivity and gene flow among populations in the Lesser Caucasus.
Epigenetic modifications, of which DNA methylation is the most stable, are a mechanism conveying environmental information to subsequent generations via parental germ lines. The paternal contribution to adaptive processes in the offspring might be crucial, but has been widely neglected in comparison to the maternal one. To address the paternal impact on the offspring’s adaptability to changes in diet composition, we investigated if low protein diet (LPD) in F0 males caused epigenetic alterations in their subsequently sired sons. We therefore fed F0 male Wild guinea pigs with a diet lowered in protein content (LPD) and investigated DNA methylation in sons sired before and after their father’s LPD treatment in both, liver and testis tissues. Our results point to a ‘heritable epigenetic response’ of the sons to the fathers’ dietary change. Because we detected methylation changes also in the testis tissue, they are likely to be transmitted to the F2 generation. Gene-network analyses of differentially methylated genes in liver identified main metabolic pathways indicating a metabolic reprogramming (‘metabolic shift’). Epigenetic mechanisms, allowing an immediate and inherited adaptation may thus be important for the survival of species in the context of a persistently changing environment, such as climate change.
Recovering genomics clusters of secondary metabolites from lakes using genome-resolved metagenomics
(2018)
Metagenomic approaches became increasingly popular in the past decades due to decreasing costs of DNA sequencing and bioinformatics development. So far, however, the recovery of long genes coding for secondary metabolites still represents a big challenge. Often, the quality of metagenome assemblies is poor, especially in environments with a high microbial diversity where sequence coverage is low and complexity of natural communities high. Recently, new and improved algorithms for binning environmental reads and contigs have been developed to overcome such limitations. Some of these algorithms use a similarity detection approach to classify the obtained reads into taxonomical units and to assemble draft genomes. This approach, however, is quite limited since it can classify exclusively sequences similar to those available (and well classified) in the databases. In this work, we used draft genomes from Lake Stechlin, north-eastern Germany, recovered by MetaBat, an efficient binning tool that integrates empirical probabilistic distances of genome abundance, and tetranucleotide frequency for accurate metagenome binning. These genomes were screened for secondary metabolism genes, such as polyketide synthases (PKS) and non-ribosomal peptide synthases (NRPS), using the Anti-SMASH and NAPDOS workflows. With this approach we were able to identify 243 secondary metabolite clusters from 121 genomes recovered from our lake samples. A total of 18 NRPS, 19 PKS, and 3 hybrid PKS/NRPS clusters were found. In addition, it was possible to predict the partial structure of several secondary metabolite clusters allowing for taxonomical classifications and phylogenetic inferences. Our approach revealed a high potential to recover and study secondary metabolites genes from any aquatic ecosystem.
Maize (Zea mays L.) is a staple food whose production relies on seed stocks that largely comprise hybrid varieties. Therefore, knowledge about the molecular determinants of hybrid performance (HP) in the field can be used to devise better performing hybrids to address the demands for sustainable increase in yield. Here, we propose and test a classification-driven framework that uses metabolic profiles from in vitro grown young roots of parental lines from the Dent x Flint maize heterotic pattern to predict field HP. We identify parental analytes that best predict the metabolic inheritance patterns in 328 hybrids. We then demonstrate that these analytes are also predictive of field HP (0.64 >= r >= 0.79) and discriminate hybrids of good performance (accuracy of 87.50%). Therefore, our approach provides a cost-effective solution for hybrid selection programs.
The availability of high-throughput data from transcriptomics and metabolomics technologies provides the opportunity to characterize the transcriptional effects on metabolism. Here we propose and evaluate two computational approaches rooted in data reduction techniques to identify and categorize transcriptional effects on metabolism by combining data on gene expression and metabolite levels. The approaches determine the partial correlation between two metabolite data profiles upon control of given principal components extracted from transcriptomics data profiles. Therefore, they allow us to investigate both data types with all features simultaneously without doing preselection of genes. The proposed approaches allow us to categorize the relation between pairs of metabolites as being under transcriptional or post-transcriptional regulation. The resulting classification is compared to existing literature and accumulated evidence about regulatory mechanism of reactions and pathways in the cases of Escherichia coil, Saccharomycies cerevisiae, and Arabidopsis thaliana.
Cells and organelles are not homogeneous but include microcompartments that alter the spatiotemporal characteristics of cellular processes. The effects of microcompartmentation on metabolic pathways are however difficult to study experimentally. The pyrenoid is a microcompartment that is essential for a carbon concentrating mechanism (CCM) that improves the photosynthetic performance of eukaryotic algae. Using Chlamydomonas reinhardtii, we obtained experimental data on photosynthesis, metabolites, and proteins in CCM-induced and CCM-suppressed cells. We then employed a computational strategy to estimate how fluxes through the Calvin-Benson cycle are compartmented between the pyrenoid and the stroma. Our model predicts that ribulose-1,5-bisphosphate (RuBP), the substrate of Rubisco, and 3-phosphoglycerate (3PGA), its product, diffuse in and out of the pyrenoid, respectively, with higher fluxes in CCM-induced cells. It also indicates that there is no major diffusional barrier to metabolic flux between the pyrenoid and stroma. Our computational approach represents a stepping stone to understanding microcompartmentalized CCM in other organisms.