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Climate forecasts show that in many regions the temporal distribution of precipitation events will become less predictable. Root traits may play key roles in dealing with changes in precipitation predictability, but their functional plastic responses, including transgenerational processes, are scarcely known. We investigated root trait plasticity of Papaver rhoeas with respect to higher versus lower intra-seasonal and inter-seasonal precipitation predictability (i.e., the degree of temporal autocorrelation among precipitation events) during a four-year outdoor multi-generation experiment. We first tested how the simulated predictability regimes affected intra-generational plasticity of root traits and allocation strategies of the ancestors, and investigated the selective forces acting on them. Second, we exposed three descendant generations to the same predictability regime experienced by their mothers or to a different one. We then investigated whether high inter-generational predictability causes root trait differentiation, whether transgenerational root plasticity existed and whether it was affected by the different predictability treatments. We found that the number of secondary roots, root biomass and root allocation strategies of ancestors were affected by changes in precipitation predictability, in line with intra-generational plasticity. Lower predictability induced a root response, possibly reflecting a fast-acquisitive strategy that increases water absorbance from shallow soil layers. Ancestors’ root traits were generally under selection, and the predictability treatments did neither affect the strength nor the direction of selection. Transgenerational effects were detected in root biomass and root weight ratio (RWR). In presence of lower predictability, descendants significantly reduced RWR compared to ancestors, leading to an increase in performance. This points to a change in root allocation in order to maintain or increase the descendants’ fitness. Moreover, transgenerational plasticity existed in maximum rooting depth and root biomass, and the less predictable treatment promoted the lowest coefficient of variation among descendants’ treatments in five out of six root traits. This shows that the level of maternal predictability determines the variation in the descendants’ responses, and suggests that lower phenotypic plasticity evolves in less predictable environments. Overall, our findings show that roots are functional plastic traits that rapidly respond to differences in precipitation predictability, and that the plasticity and adaptation of root traits may crucially determine how climate change will affect plants.
Climate change affects ecosystems worldwide and is threatening biodiversity. Insects, as ectotherm organisms, are strongly dependent on the thermal environment. Yet, little is known about the effects of summer heat and drought on insect diversity. In the Mediterranean climate zone, a region strongly affected by climate change, hot summers might have severe effects on insect communities. Especially the larval stage might be sensitive to thermal variation, as larvae—compared to other life stages—cannot avoid hot temperatures and drought by dormancy. Here we ask, whether inter-annual fluctuations in Mediterranean moth diversity can be explained by temperature (TLarv) and precipitation during larval development (HLarv). To address our question, we analyzed moth communities of a Mediterranean coastal forest during the last 20 years. For species with summer-developing larvae, species richness was significantly negatively correlated with TLarv, while the community composition was affected by both, TLarv and HLarv. Therefore, summer-developing larvae seem particularly sensitive to climate change, as hot summers might exceed the larval temperature optima and drought reduces food plant quality. Increasing frequency and severity of temperature and drought extremes due to climate change, therefore, might amplify insect decline in the future.
Biodiversity patterns of marine crustaceans are still unknown in many locations or might have been overlooked due to our knowledge gaps, despite increasing sampling and data sharing efforts during the last decades. By analysing big data extracted from open portals such as Ocean Biodiversity Information System (OBIS) and Global Biodiversity Information System (GBIF), we aim to revisit the distribution and biodiversity patterns of the highly speciose and abundant Crustacea in the Northwest Pacific (NWP) from shallowest depths to the deep sea. This study focussed on selected benthic and pelagic crustacean (sub) classes and their species richness, sampling effort, and expected species richness (ES50) using equal/sized hexagonal cells, 5° latitudinal bands, 500 m depth intervals were analyzed. Crustacean species richness was highest in the tropical Philippines as well as around the Japanese islands. Pelagic crustacean species richness peaked at 30° latitude and declined beyond that. Benthic taxa; however, depicted high levels of species richness across most of the latitudinal gradient, reaching its highest point at 45° latitude. Due to the prevalence of certain crustacean orders in the deep sea, benthic species richness showed a distribution pattern with two distinct peaks across bathymetric gradients; with highest species richness recorded at shallow-water depths and also at abyssal depths. The most important environmental drivers of benthic and pelagic crustacean species richness were primary productivity (positive correlation) and salinity (negative correlation). Our study provides first insights into biodiversity patterns of the highly diverse Crustacea in the NWP and highlights strong differences between benthic and pelagic taxa. The results presented here could help us to better understand whether benthic or pelagic taxa might respond differently to climate changes in the NWP based on their distinct physiological and biological characteristics. This information is crucial in establishing species management strategies and ecosystem restorations in both shallow water and deep-sea environments.
Mining is one of the major pollution sources worldwide, causing huge disturbances to the environment. Industrial and artisanal mining activities are widespread in Mexico, a major global producer of various metals. This study aimed to assess the ecological impairments resulting from mining activities using aquatic macroinvertebrates assemblages (MA). A multiple co-inertia analysis was applied to determine the relationships between environmental factors, habitat quality, heavy metals, and aquatic macroinvertebrates in 15 study sites in two different seasons (dry and wet) along two rivers running across the Central Plateau of Mexico. The results revealed three contrasting environmental conditions associated with different MAs. High concentrations of heavy metals, nutrients, and salinity limit the presence of several families of seemingly sensitive macroinvertebrates. These factors were found to influence structural changes in MAs, showing that not only mining activities, but also agriculture and presence of villages in the basin, exert adverse effects on macroinvertebrate assemblages. Diversity indices showed that the lowest diversity matched both the most polluted and the most saline rivers. The rivers studied displayed high alkalinity and hardness levels, which can reduce the availability of metals and cause adverse effects on periphyton by inhibiting photosynthesis and damaging MAs. Aquatic biomonitoring in rivers, impacted by mining and other human activities, is critical for detecting the effect of metals and other pollutants to improve management and conservation strategies. This study supports the design of cost-effective and accurate water quality biomonitoring protocols in developing countries.
The ability of wild animals to navigate and survive in complex and dynamic environments depends on their ability to store relevant information and place it in a spatial context. Despite the centrality of spatial memory, and given our increasing ability to observe animal movements in the wild, it is perhaps surprising how difficult it is to demonstrate spatial memory empirically. We present a cognitive analysis of movements of several wolves (Canis lupus) in Finland during a summer period of intensive hunting and den-centered pup-rearing. We tracked several wolves in the field by visiting nearly all GPS locations outside the den, allowing us to identify the species, location and timing of nearly all prey killed. We then developed a model that assigns a spatially explicit value based on memory of predation success and territorial marking. The framework allows for estimation of multiple cognitive parameters, including temporal and spatial scales of memory. For most wolves, fitted memory-based models outperformed null models by 20 to 50% at predicting locations where wolves chose to forage. However, there was a high amount of individual variability among wolves in strength and even direction of responses to experiences. Some wolves tended to return to locations with recent predation success—following a strategy of foraging site fidelity—while others appeared to prefer a site switching strategy. These differences are possibly explained by variability in pack sizes, numbers of pups, and features of the territories. Our analysis points toward concrete strategies for incorporating spatial memory in the study of animal movements while providing nuanced insights into the behavioral strategies of individual predators.
Forest wildflowers bloom earlier as Europe warms: lessons from herbaria and spatial modelling
(2022)
Today plants often flower earlier due to climate warming. Herbarium specimens are excellent witnesses of such long-term changes. However, the magnitude of phenological shifts may vary geographically, and the data are often clustered. Therefore, large-scale analyses of herbarium data are prone to pseudoreplication and geographical biases.
We studied over 6000 herbarium specimens of 20 spring-flowering forest understory herbs from Europe to understand how their phenology had changed during the last century. We estimated phenology trends with or without taking spatial autocorrelation into account.
On average plants now flowered over 6 d earlier than at the beginning of the last century. These changes were strongly associated with warmer spring temperatures. Flowering time advanced 3.6 d per 1°C warming. Spatial modelling showed that, in some parts of Europe, plants flowered earlier or later than expected. Without accounting for this, the estimates of phenological shifts were biased and model fits were poor.
Our study indicates that forest wildflowers in Europe strongly advanced their phenology in response to climate change. However, these phenological shifts differ geographically. This shows that it is crucial to combine the analysis of herbarium data with spatial modelling when testing for long-term phenology trends across large spatial scales.
In (eco-)toxicological studies the light/dark transition (LDT) test is one of the most frequently used behaviour assays with zebrafish eleutheroembryos. However, study results vary regarding data presentation and analysis and mostly focus on a limited amount of the recorded data. In this study, we investigated whether monitoring two behavioural outcomes (time and distance moved) together with analysing multiple parameters can improve test sensitivity and data interpretation. As a proof of principle 5-day old zebrafish (Danio rerio) eleutheroembryos exposed to either endocrine disruptors (EDs) or acetylcholine esterase (AChE) inhibitors were investigated. We analysed conventional parameters such as mean and sum and implemented additional endpoints such as minimum or maximum distance moved and new parameters assessing the bursting response of eleutheroembryos. Furthermore, changes in eleutheroembryonic behaviour during the moment of the light to dark transition were added. To improve data presentation control-normalised results were displayed in radar charts, enabling the simultaneous presentation of different parameters in relation to each other. This enabled us to identify parameters most relevant to a certain behavioural response. A cut off threshold using control data was applied to identify parameters that were altered in a biological relevant manner. Our approach was able to detect effects on different parameters that remained undetected when analysis was done using conventional bar graphs on - in most cases analysed - averaged, mean distance moved values. By combining the radar charts with additional parameters and by using control-based thresholds, we were able to increase the test sensitivity and promote a deeper understanding of the behaviour response of zebrafish eleutheroembryos in the LDT test and thereby increased its usability for behavioural toxicity studies.
Highlights
• Enables immunostaining and visualization of epitopes deep within brain slices
• Utilizes expansion microscopy to increase imaging resolution
• Optimized for brain organotypic slice cultures and tested in acute brain slices
• Analysis workflow for protein distribution (surface vs. intracellular pool) using Imaris
Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.
Summary
Assessing protein distribution with super-resolution in tissue is often complicated and restrictive. Here, we describe a protocol for immunostaining and expansion microscopy imaging of mouse brain organotypic slice cultures. We detail an Imaris analysis workflow to analyze the surface vs intracellular distribution of AMPA receptors at super-resolution during homeostatic plasticity. We have optimized the protocol for brain organotypic slice culture and tested in acute brain slices. This protocol is suitable to study protein distribution under multiple plasticity paradigms.
Nanoplastics affect the inflammatory cytokine release by primary human monocytes and dendritic cells
(2022)
So far, the human health impacts of nano- and microplastics are poorly understood. Thus, we investigated whether nanoplastics exposure induces inflammatory processes in primary human monocytes and monocyte-derived dendritic cells. We exposed these cells in vitro to nanoplastics of different shapes (irregular vs. spherical), sizes (50–310 nm and polydisperse mixtures) and polymer types (polystyrene; polymethyl methacrylate; polyvinyl chloride, PVC) using concentrations of 30–300 particles cell−1. Our results show that irregular PVC particles induce the strongest cytokine release of these nanoplastics. Irregular polystyrene triggered a significantly higher pro-inflammatory response compared to spherical nanoplastics. The contribution of chemicals leaching from the particles was minor. The effects were concentration-dependent but varied markedly between cell donors. We conclude that nanoplastics exposure can provoke human immune cells to secrete cytokines as key initiators of inflammation. This response is specific to certain polymers (PVC) and particle shapes (fragments). Accordingly, nanoplastics cannot be considered one homogenous entity when assessing their health implications and the use of spherical polystyrene nanoplastics may underestimate their inflammatory effects.
The maintenance of cellular homeostasis over time is essential to avoid the degeneration of biological systems leading to aging and disease. Several interconnected pathways are active in this kind of quality control. One of them is autophagy, the vacuolar degradation of cellular components. The absence of the sorting nexin PaATG24 (SNX4 in other organisms) has been demonstrated to result in impairments in different types of autophagy and lead to a shortened lifespan. In addition, the growth rate and the size of vacuoles are strongly reduced. Here, we report how an oleic acid diet leads to longevity of the wild type and a PaAtg24 deletion mutant (ΔPaAtg24). The lifespan extension is linked to altered membrane trafficking, which abrogates the observed autophagy defects in ΔPaAtg24 by restoring vacuole size and the proper localization of SNARE protein PaSNC1. In addition, an oleic acid diet leads to an altered use of the mitochondrial respiratory chain: complex I and II are bypassed, leading to reduced reactive oxygen species (ROS) production. Overall, our study uncovers multiple effects of an oleic acid diet, which extends the lifespan of P. anserina and provides perspectives to explain the positive nutritional effects on human aging.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions, using signals from nanopore direct RNA sequencing. CHEUI processes observed and expected signals with convolutional neural networks to achieve high single-molecule accuracy and outperform other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
Establishing management programs to preserve the benthic communities along the NW Pacific and the Arctic Ocean (AO) requires a deep understanding of the composition of communities and their responses to environmental stressors. In this study, we thus examine patterns of benthic community composition and patterns of species richness along the NW Pacific and Arctic Seas and investigate the most important environmental drivers of those patterns. Overall we found a trend of decreasing species richness toward higher latitudes and deeper waters, peaking in coastal waters of the eastern Philippines. The most dominant taxa along the entire study area were Arthropoda, Mollusca, Cnidaria, Echinodermata, and Annelida. We found that depth, not temperature, was the main driver of community composition along the NW Pacific and neighboring Arctic Seas. Depth has been previously suggested as a factor driving species distribution in benthic fauna. Following depth, the most influential environmental drivers of community composition along the NW Pacific and the Arctic Ocean were silicate, light, and currents. For example, silicate in Hexactinellida, Holothuroidea, and Ophiuroidea; and light in Cephalopoda and Gymnolaemata had the highest correlations with community composition. In this study, based on a combination of new samples and open-access data, we show that different benthic communities might respond differently to future climatic changes based on their taxon-specific biological, physiological, and ecological characteristics. International conservation efforts and habitat preservation should take an adaptive approach and apply measures that take the differences among benthic communities in responding to future climate change into account. This facilitates implementing appropriate conservation management strategies and sustainable utilization of the NW Pacific and Arctic marine ecosystems.
Insects with aquatic life stages can transfer sediment and water pollutants to terrestrial ecosystems, which has been described for metals, polyaromatic hydrocarbons, and polychlorinated chemicals. However, knowledge of the transfer of aquatic micropollutants released by wastewater treatment plants is scarce despite some preliminary studies on their occurrence in riparian spiders. In our study, we address a major analytical gap focusing on the transfer of the micropollutant carbamazepine from the larvae to the adult midges of Chironomus riparius using an optimized QuEChERS extraction method and HPLC–MS/MS applicable to both life stages down to the level of about three individuals. We show that the uptake of carbamazepine by larvae is concentration-dependent and reduces the emergence rate. Importantly, the body burden remained constant in adult midges. Using this information, we estimated the daily exposure of insectivorous tree swallows as terrestrial predators to carbamazepine using the energy demand of the predator and the energy content of the prey. Assuming environmentally relevant water concentrations of about 1 μg/L, the daily dose per kilogram of body weight for tree swallows was estimated to be 0.5 μg/kg/day. At places of high water contamination of 10 μg/L, the exposure may reach 5 μg/kg/day for this micropollutant of medium polarity. Considering body burden changes upon metamorphosis, this study fills the missing link between aquatic contamination and exposure in terrestrial habitats showing that wastewater pollutants can impact birds’ life. Clearly, further analytical methods for biota analysis in both habitats are urgently required to improve risk assessment.
Bird-mediated seed dispersal is crucial for the regeneration and viability of ecosystems, often resulting in complex mutualistic species networks. Yet, how this mutualism drives the evolution of seed dispersing birds is still poorly understood. In the present study we combine whole genome re-sequencing analyses and morphometric data to assess the evolutionary processes that shaped the diversification of the Eurasian nutcracker (Nucifraga), a seed disperser known for its mutualism with pines (Pinus). Our results show that the divergence and phylogeographic patterns of nutcrackers resemble those of other non-mutualistic passerine birds and suggest that their early diversification was shaped by similar biogeographic and climatic processes. The limited variation in foraging traits indicates that local adaptation to pines likely played a minor role. Our study shows that close mutualistic relationships between bird and plant species might not necessarily act as a primary driver of evolution and diversification in resource-specialized birds.
Abstract
Natural plant populations often harbour substantial heritable variation in DNA methylation. However, a thorough understanding of the genetic and environmental drivers of this epigenetic variation requires large-scale and high-resolution data, which currently exist only for a few model species. Here, we studied 207 lines of the annual weed Thlaspi arvense (field pennycress), collected across a large latitudinal gradient in Europe and propagated in a common environment. By screening for variation in DNA sequence and DNA methylation using whole-genome (bisulfite) sequencing, we found significant epigenetic population structure across Europe. Average levels of DNA methylation were strongly context-dependent, with highest DNA methylation in CG context, particularly in transposable elements and in intergenic regions. Residual DNA methylation variation within all contexts was associated with genetic variants, which often co-localized with annotated methylation machinery genes but also with new candidates. Variation in DNA methylation was also significantly associated with climate of origin, with methylation levels being lower in colder regions and in more variable climates. Finally, we used variance decomposition to assess genetic versus environmental associations with differentially methylated regions (DMRs). We found that while genetic variation was generally the strongest predictor of DMRs, the strength of environmental associations increased from CG to CHG and CHH, with climate-of-origin as the strongest predictor in about one third of the CHH DMRs. In summary, our data show that natural epigenetic variation in Thlaspi arvense is significantly associated with both DNA sequence and environment of origin, and that the relative importance of the two factors strongly depends on the sequence context of DNA methylation. T. arvense is an emerging biofuel and winter cover crop; our results may hence be relevant for breeding efforts and agricultural practices in the context of rapidly changing environmental conditions.
Author summary
Variation within species is an important level of biodiversity, and it is key for future adaptation. Besides variation in DNA sequence, plants also harbour heritable variation in DNA methylation, and we want to understand the evolutionary significance of this epigenetic variation, in particular how much of it is under genetic control, and how much is associated with the environment. We addressed these questions in a high-resolution molecular analysis of 207 lines of the common plant field pennycress (Thlaspi arvense), which we collected across Europe, propagated under standardized conditions, and sequenced for their genetic and epigenetic variation. We found large geographic variation in DNA methylation, associated with both DNA sequence and climate of origin. Genetic variation was generally the stronger predictor of DNA methylation variation, but the strength of environmental association varied between different sequence contexts. Climate-of-origin was the strongest predictor in about one third of the differentially methylated regions in the CHH context, which suggests that epigenetic variation may play a role in the short-term climate adaptation of pennycress. As pennycress is currently being domesticated as a new biofuel and winter cover crop, our results may be relevant also for agriculture, particularly in changing environments.
Abstract
Natural plant populations often harbour substantial heritable variation in DNA methylation. However, a thorough understanding of the genetic and environmental drivers of this epigenetic variation requires large-scale and high-resolution data, which currently exist only for a few model species. Here, we studied 207 lines of the annual weed Thlaspi arvense (field pennycress), collected across a large latitudinal gradient in Europe and propagated in a common environment. By screening for variation in DNA sequence and DNA methylation using whole-genome (bisulfite) sequencing, we found significant epigenetic population structure across Europe. Average levels of DNA methylation were strongly context-dependent, with highest DNA methylation in CG context, particularly in transposable elements and in intergenic regions. Residual DNA methylation variation within all contexts was associated with genetic variants, which often co-localized with annotated methylation machinery genes but also with new candidates. Variation in DNA methylation was also significantly associated with climate of origin, with methylation levels being higher in warmer regions and lower in more variable climates. Finally, we used variance decomposition to assess genetic versus environmental associations with differentially methylation regions (DMRs). We found that while genetic variation was generally the strongest predictor of DMRs, the strength of environmental associations increased from CG to CHG and CHH, with climate-of-origin as the strongest predictor in about one third of the CHH DMRs. In summary, our data show that natural epigenetic variation in Thlaspi arvense is significantly associated with both DNA sequence and environment of origin, and that the relative importance of the two factors strongly depends on the sequence context of DNA methylation. T. arvense is an emerging biofuel and winter cover crop; our results may hence be relevant for breeding efforts and agricultural practices in the context of rapidly changing environmental conditions.
Author Summary: Variation within species is an important level of biodiversity, and it is key for future adaptation. Besides variation in DNA sequence, plants also harbour heritable variation in DNA methylation, and we want to understand the evolutionary significance of this epigenetic variation, in particular how much of it is under genetic control, and how much is associated with the environment. We addressed these questions in a high-resolution molecular analysis of 207 lines of the common plant field pennycress (Thlaspi arvense), which we collected across Europe, propagated under standardized conditions, and sequenced for their genetic and epigenetic variation. We found large geographic variation in DNA methylation, associated with both DNA sequence and climate of origin. Genetic variation was generally the stronger predictor of DNA methylation variation, but the strength of environmental association varied between different sequence contexts. Climate-of-origin was the strongest predictor in about one third of the differentially methylated regions in the CHH context, which suggests that epigenetic variation may play a role in the short-term climate adaptation of pennycress. As pennycress is currently being domesticated as a new biofuel and winter cover crop, our results may be relevant also for agriculture, particularly in changing environments.
RNA-binding proteins (RBPs) control every RNA metabolic process by multiple protein-RNA and protein-protein interactions. Their roles have largely been analyzed by crude mutations, which abrogate multiple functions at once and likely impact the structural integrity of the large ribonucleoprotein particles (RNPs) these proteins function in. Using UV-induced RNA-protein crosslinking of entire cells, protein complex purification and mass spectrometric analysis, we identified >100 in vivo RNA crosslinks in 16 nuclear mRNP components in Saccharomyces cerevisiae. For functional analysis, we chose Npl3, which displayed crosslinks in its two RNA recognition motifs (RRMs) and in the connecting flexible linker region. Both RRM domains and the linker uniquely contribute to RNA recognition as revealed by NMR and structural analyses. Interestingly, mutations in these regions cause different phenotypes, indicating distinct functions of the different RNA-binding domains. Notably, an npl3-Linker mutation strongly impairs recruitment of several mRNP components to chromatin and incorporation of other mRNP components into nuclear mRNPs, establishing a so far unknown function of Npl3 in nuclear mRNP assembly. Taken together, our integrative analysis uncovers a specific function of the RNA-binding activity of the nuclear mRNP component Npl3. This approach can be readily applied to RBPs in any RNA metabolic process.