Biology subjects

Kunze, S.

Publications and source records attributed to Kunze, S..

6 recordsLinked to original sources

bioRxiv2024

Impact of land-use intensity, productivity, and aboveground richness on seed rain in temperate grasslands

O_LISeed rain, the amount of seeds reaching an area via primary or secondary dispersal, affects the regeneration of plant communities and shapes the trajectory of future community composition. In agricultural grasslands, the composition and density in seed rain are mainly driven by land use, but drivers of seed rain quality and quantity along land-use gradients are poorly understood. We studied the effects of land-use intensity (LUI), its components (i.e. fertilization, mowing, and grazing), productivity, and aboveground vegetation composition and richness on seed rain. C_LIO_LIWe collected the seed rain over a five-month period in 142 grasslands and identified emerging seedlings. Grass seedlings dominated seed rain most likely due to their high abundance in vegetation and intense and early seed set. Only ten species accounted for approximately 80 % of seedlings, with grasses such as Lolium perenne and Alopecurus pratensis being most abundant. Forbs such as Cerastium holosteoides and Veronica arvensis were abundant in seed rain despite lower cover, probably due to early and prolonged flowering and high seed production. C_LIO_LISeed rain of grasses and forbs reacted differently to LUI and vegetation richness, LUI effects on grass seed rain mainly determined total seed density. Seed rain richness first increased with LUI, but decreased at higher LUI levels. Consequently, seed rain richness consistently increased with vegetation richness. This is reflected by a decrease in the abundance of stress strategists and an increase in ruderals in seed rain with increasing LUI and decreasing vegetation richness. C_LIO_LIAmong LUI components, fertilization intensity most strongly affected seed rain density and composition, with negative effects at intermediate fertilization intensities. Mowing once a year increased seed rain density, whereas it decreased at higher mowing frequencies. Grazing intensity reduced overall seed density and richness by reducing grass seed density, while forb seed density remained unaffected. C_LI Synthesis: Land-use intensity and aboveground productivity significantly influence the species composition and seed densities in the seed rain of temperate agricultural grasslands. Higher land-use intensity and productivity increased seed production but reduced taxonomic and functional diversity in seed rain and may negatively impact ecosystem stability and resilience.

ecology↗

bioRxiv2020

Treated wastewater irrigation promotes the spread of antibiotic resistance into subsoil pore-water.

In the present study, we investigated the impact of treated wastewater (TWW) irrigation on the prevalence of antibiotic resistance genes (ARGs) in subsoil pore-water, a so-far under-appreciated matrix. We hypothesized that TWW irrigation increases ARG prevalence in subsoil pore-water. This hypothesis was tested using a multiphase approach, which consisted of sampling percolated subsoil pore-water from lysimeter-wells of a real-scale TWW-irrigated field, operated for commercial farming practices, and controlled, laboratory mesocosms irrigated with freshwater or TWW. We monitored the abundance of six selected ARGs (sul1, blaOXA-58, tetM, qnrS, blaCTX-M-32 and blaTEM), the intI1 gene associated with mobile genetic elements and an indicator for anthropogenic pollution and bacterial abundance (16S rRNA gene) by qPCR. The bacterial load of subsoil pore water was independent of both, irrigation intensity in the field study and irrigation water type in the mesocosms. Among the tested genes in the field study, sul1 and intI1 exhibited constantly higher relative abundances. Their abundance was further positively correlated with increasing irrigation intensity. Controlled mesocosm experiments verified the observed field study results: the relative abundance of several genes, including sul1 and intI1, increased significantly when irrigating with TWW compared to freshwater irrigation. Overall, TWW irrigation promoted the spread of ARGs and intI1 in the subsoil pore-water, while the bacterial load was maintained. The combined results from the real-scale agricultural field and the controlled lab mesocosms indicate that the dissemination of ARGs in various subsurface environments needs to be taken into account during TWW irrigation scenarios. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/222497v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@19b130corg.highwire.dtl.DTLVardef@1ffb733org.highwire.dtl.DTLVardef@1548ff0org.highwire.dtl.DTLVardef@b60361_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LITWW irrigation intensity and sul1 & intI1 abundance correlate in a real-scale field C_LIO_LIARGs & intI1 increase in subsoil pore-water during TWW irrigation in mesocosms C_LIO_LINo increase of ARGs & intI1 in freshwater irrigated mesocosms C_LIO_LITWW irrigation does not affect the bacterial load of subsoil pore-water C_LI

microbiology↗

bioRxiv2020

Network reconstruction for trans acting genetic loci using multi-omics data and prior information

BackgroundMolecular multi-omics data provide an in-depth view on biological systems, and their integration is crucial to gain insights in complex regulatory processes. These data can be used to explain disease related genetic variants by linking them to intermediate molecular traits (quantitative trait loci, QTL). Molecular networks regulating cellular processes leave footprints in QTL results as so-called trans -QTL hotspots. Reconstructing these networks is a complex endeavor and use of biological prior information has been proposed to alleviate network inference. However, previous efforts were limited in the types of priors used or have only been applied to model systems. In this study, we reconstruct the regulatory networks underlying trans -QTL hotspots using human cohort data and data-driven prior information. ResultsWe devised a strategy to integrate QTL with human population scale multi-omics data and comprehensively curated prior information from large-scale biological databases. State-of-the art network inference methods applied to these data and priors were used to recover the regulatory networks underlying trans -QTL hotspots. We benchmarked inference methods and showed, that Bayesian strategies using biologically-informed priors outperform methods without prior data in simulated data and show better replication across datasets. Application of our approach to human cohort data highlighted two novel regulatory networks related to schizophrenia and lean body mass for which we generated novel functional hypotheses. ConclusionWe demonstrate, that existing biological knowledge can be leveraged for the integrative analysis of networks underlying trans associations to deduce novel hypotheses on cell regulatory mechanisms.

bioinformatics↗

bioRxiv2019

A genome-wide analysis of DNA methylation identifies a novel association signal for Lp(a) concentrations in the LPA promoter

Lipoprotein(a) [Lp(a)] is a major cardiovascular risk factor, which is largely genetically determined by one major gene locus, the LPA gene. Many aspects of the transcriptional regulation of LPA are poorly understood and the role of epigenetics has not been addressed yet. Therefore, we conducted an epigenome-wide analysis of DNA methylation on Lp(a) levels in two population-based studies (total n=2208). We identified a CpG site in the LPA promoter which was significantly associated with Lp(a) concentrations. Surprisingly, the identified CpG site was found to overlap the SNP rs76735376. We genotyped this SNP de-novo in three studies (total n=7512). The minor allele of rs76735376 (1.1% minor allele frequency) was associated with increased Lp(a) values (p=1.01e-59) and explained 3.5% of the variation of Lp(a). Statistical mediation analysis showed that the effect on Lp(a) is rather originating from the base change itself and is not mediated by DNA methylation levels. This finding is supported by eQTL data from 153 liver tissue samples from the GTEx project, which shows a significant association of the rs76735376 minor allele with increased LPA expression. In summary, our data supports a functional role of rs76735376 in the regulation of LPA expression.

genetics↗

bioRxiv2018

Epigenetic derepression of FKBP5 by aging and stress contributes to NF-kB-driven inflammation and cardiovascular risk

Aging and psychosocial stress are associated with increased inflammation and disease risk, but the underlying molecular mechanisms are poorly understood. Because both aging and stress are also associated with lasting epigenetic changes, a plausible hypothesis is that stress exposure along the lifespan could confer disease risk by epigenetically deregulating molecules involved in inflammatory processes. Here, by combining large-scale analyses in human cohorts with mechanistic in vitro investigations, we found that FKBP5, a protein implicated in stress physiology, contributes to these relations. Across independent human cohorts (total n=3,131), aging and stress-related phenotypes were synergistically associated with epigenetic derepression of FKBP5. These age/stress-related epigenetic effects were recapitulated in an in vitro model of replicative senescence, whereby we exposed replicating human fibroblasts to stress (glucocorticoid) hormones. Unbiased genome-wide analyses in human blood linked higher FKBP5 mRNA with a proinflammatory profile and altered NF-{kappa}B-related gene networks. Accordingly, experiments in immune cells showed that FKBP5 overexpression promotes inflammation by strengthening the interactions of NF-{kappa}B regulatory kinases, whereas opposing FKBP5 either by genetic deletion (CRISPR/Cas9-mediated) or selective pharmacological inhibition prevented the effects on NF-{kappa}B. Further, the age/stress-related epigenetic signature enhanced FKBP5 responsivity to NF-{kappa}B through a positive feedback loop and was present in individuals with a history of acute myocardial infarction, a disease state linked to peripheral inflammation. These findings suggest that FKBP5-NF-{kappa}B signaling mediates inflammation associated with aging and stress, potentially contributing to cardiovascular risk, and may thus point to novel biomarker and treatment possibilities.\n\nSignificanceDiseases of the aging are the leading cause of morbidity and mortality. Elucidating the molecular mechanisms through which modifiable factors, such as psychosocial stress, confer risk for aging-related disease can have profound implications. Here, by combining studies in humans with experiments in cells, we find that aging and stress synergize to epigenetically derepress FKBP5, a protein implicated in stress physiology. Higher FKBP5 promotes inflammation by activating the master immune regulator NF-{kappa}B, whereas opposing FKBP5 - either genetically or pharmacologically- prevents the effects on NF-{kappa}B. Further, the age/stress-related epigenetic signature of FKBP5 is associated with history of myocardial infarction, a disease state linked to inflammation. These findings provide molecular insights into stress-related disease and may point to novel biomarker and treatment possibilities.

genomics↗

bioRxiv2017

An exact and efficient score test for variance components models

Testing for the existence of variance components in linear mixed models is a fundamental task in many applicative fields. In statistical genetics, the score test has recently become instrumental in the task of testing an association between a set of genetic markers and a phenotype. With few markers, this amounts to set-based variance component tests, which attempt to increase power in association studies by aggregating weak individual effects. When the entire genome is considered, it allows testing for the heritability of a phenotype, defined as the proportion of phenotypic variance explained by genetics. In the popular score-based Sequence Kernel Association Test (SKAT) method, the assumed distribution of the score test statistic is uncalibrated in small samples, with a correction being computationally expensive. This may cause severe inflation or deflation of p-values, even when the null hypothesis is true. Here, we characterize the conditions under which this discrepancy holds, and show it may occur also in large real datasets, such as a dataset from the Wellcome Trust Case Control Consortium 2 (n=13,950) study, and in particular when the individuals in the sample are unrelated. In these cases the SKAT approximation tends to be highly over-conservative and therefore underpowered. To address this limitation, we suggest an efficient method to calculate exact p-values for the score test in the case of a single variance component and a continuous response vector, which can speed up the analysis by orders of magnitude. Our results enable fast and accurate application of the score test in heritability and in set-based association tests. Our method is available in http://github.com/cozygene/RL-SKAT.

genetics↗