The microRNAs of Caenorhabditis elegans

The soil nematode, Caenorhabditis elegans, occupies a central place in the short history of microRNA (miRNA) research. The converse is also true: miRNAs have emerged as key regulatory components in the life cycle of the worm, as well as numerous other organisms. Since the landmark discovery in 1993 of the first miRNA gene, lin-4, several other miRNAs have been characterized in detail in C. elegans and shown to participate in diverse biological processes. Moreover, the worm has provided, by virtue of its ease of genetic manipulation and amenability to high-throughput methods, an ideal platform for elucidating many general and conserved aspects of miRNA biology, namely mechanisms of biogenesis, target recognition, gene silencing, and regulation thereof. In this review, we summarize both the contribution of miRNAs to C. elegans physiology and development, as well as the contribution of C. elegans research to our understanding of general features of miRNA biology.     

Multi-species richness of boreal agricultural landscapes: effects of climate, biotope, soil and geographical location

Aim To assess the relative importance of climate, biotope and soil variables as well as geographical location for the species richness of plants, butterflies, day‐active macromoths and wild bees in boreal agricultural landscapes. Location A total of 68 agricultural landscapes located in southern Finland. Methods Generalized linear mixed models were used to analyse the effects of environmental (climate, biotope and soil) and spatial (latitude and longitude) variables on species richness of four taxa in 136 study squares of 0.25 km². Using partial regression, the variation in species richness was decomposed into the purely environmental fraction; the spatially structured environmental fraction; and the purely spatial fraction, including variables retained in cubic trend surface regression. Results Species richness of all taxa was positively correlated with temperature. Species richness of plants and butterflies was also positively correlated with the heterogeneity of landscape. The extent of low‐intensity agricultural land and forest had a positive effect, and the extent of cultivated field a negative effect on the species richness of these taxa. The effect of soil characteristics on the number of observed species was negligible for all taxa. The greatest part of the explained variation for all taxa was accounted for by the pure effect of geographical location. To a somewhat lesser extent, the species richness of plants, butterflies and bees was also related to the effects of spatially structured environmental variables, and the species richness of macromoths to the effects of environmental variables. Main conclusions Multi‐species richness of boreal agricultural landscapes at the scale of 0.25 km² was associated with the heterogeneity of the local landscape. However, large‐scale geographical variation in species richness was also observed, which indicates the importance of climate and geographical location for the taxa studied. These results highlight the fact that, even on a landscape scale, geographical factors should be taken into account in biodiversity studies. Heterogeneous agricultural landscapes, including forest and non‐crop biotopes, should be preserved or restored to maintain biodiversity.     

Biotic interactions drive species occurrence and richness in dynamic beach environments

Biotic interactions are predicted to have the strongest influence on species assemblages in extreme environments. We therefore test the hypothesis that in abiotically-severe beaches plant–plant interactions, specifically facilitation, are important relative to abiotic conditions. This hypothesis is tested by assessing the influence of dominant vascular plant species on the fine-scale occurrence and richness of vascular and cryptogam species using a unique dataset of boreal beaches along the Finnish Baltic Sea, characterized by strong post-glacial land uplift and large environmental gradients. We studied three different levels of vegetation patterns across a broad geographical scale; individual species, functional groups and the entire community. Results showed that dominant vascular species strongly drive species occurrence and richness in dynamic beach environments, with some species having an influence similar to that of key abiotic variables. In contrast to expectations, facilitative effects did not dominate in these harsh environments. Instead, the outcomes of biotic interactions were species-specific, and also differed between vascular and cryptogam species, with the former group most strongly influenced by a pioneer species and the latter by a late succession generalist. Our study highlights the importance of incorporating biotic interaction effects into models of multiple vegetation properties and cautions against overly simplistic generalizations to describe relatively idiosyncratic interaction effects.     

RNA-binding protein GLD-1/quaking genetically interacts with the mir-35 and the let-7 miRNA pathways in Caenorhabditis elegans

Messenger RNA translation is regulated by RNA-binding proteins and small non-coding RNAs called microRNAs. Even though we know the majority of RNA-binding proteins and microRNAs that regulate messenger RNA expression, evidence of interactions between the two remain elusive. The role of the RNA-binding protein GLD-1 as a translational repressor is well studied during Caenorhabditis elegans germline development and maintenance. Possible functions of GLD-1 during somatic development and the mechanism of how GLD-1 acts as a translational repressor are not known. Its human homologue, quaking (QKI), is essential for embryonic development. Here, we report that the RNA-binding protein GLD-1 in C. elegans affects multiple microRNA pathways and interacts with proteins required for microRNA function. Using genome-wide RNAi screening, we found that nhl-2 and vig-1, two known modulators of miRNA function, genetically interact with GLD-1. gld-1 mutations enhance multiple phenotypes conferred by mir-35 and let-7 family mutants during somatic development. We used stable isotope labelling with amino acids in cell culture to globally analyse the changes in the proteome conferred by let-7 and gld-1 during animal development. We identified the histone mRNA-binding protein CDL-1 to be, in part, responsible for the phenotypes observed in let-7 and gld-1 mutants. The link between GLD-1 and miRNA-mediated gene regulation is further supported by its biochemical interaction with ALG-1, CGH-1 and PAB-1, proteins implicated in miRNA regulation. Overall, we have uncovered genetic and biochemical interactions between GLD-1 and miRNA pathways.     

The importance of biotic interactions for modelling species distributions under climate change

Aim There is a debate as to whether biotic interactions exert a dominant role in governing species distributions at macroecological scales. The prevailing idea is that climate is the key limiting factor; thus models that use present‐day climate–species range relationships are expected to provide reasonable means to quantify the impacts of climate change on species distributions. However, there is little empirical evidence that biotic interactions would not constrain species distributions at macroecological scales. We examine this idea, for the first time, and provide tests for two null hypotheses: (H₀ 1) – biotic interactions do not exert a significant role in explaining current distributions of a particular species of butterfly (clouded Apollo, Parnassius mnemosyne) in Europe; and (H₀ 2) – biotic interactions do not exert a significant role in predictions of altered species’ ranges under climate change. Location Europe. Methods Generalized additive modelling (GAM) was used to investigate relationships between species and climate; species and host plants; and species and climate + host plants. Because models are sensitive to the variable selection strategies utilised, four alternative approaches were used: AIC (Akaike's Information Criterion), BIC (Bayesian Information Criterion), BRUTO (Adaptive Backfitting), and CROSS (Cross Selection). Results In spite of the variation in the variables selected with different methods, both hypotheses (H₀ 1 and H₀ 2) were falsified, providing support for the proposition that biotic interactions significantly affect both the explanatory and predictive power of bioclimatic envelope models at macro scales. Main conclusions Our results contradict the widely held view that the effects of biotic interactions on individual species distributions are not discernible at macroecological scales. Results are contingent on the species, type of interaction and methods considered, but they call for more stringent evidence in support of the idea that purely climate‐based modelling would be sufficient to quantify the impacts of climate change on species distributions.     

Inclusion of explicit measures of geodiversity improve biodiversity models in a boreal landscape

Measures of geodiversity may provide a potentially useful surrogate for biodiversity patterns in insufficiently surveyed areas. However, their reliability in modelling the spatial variation in species richness is inadequately understood. We investigated whether the explanatory and predictive power of species richness models can be improved by considering explicit measures of geodiversity (variability of earth surface materials, forms and processes) in addition to climate and topography variables. Vascular plant species richness was modelled in two study areas in Northern Europe, Finland at the resolution of 500 or 1000?m, and as a function of three geodiversity (geological, geomorphological and hydrological diversity) variables, and six climate and topography variables. Variation partitioning was used to identify the independent and shared contributions of the geodiversity, climate and topography variable groups in explaining the spatial patterns of species richness. Generalized additive models were used to explore the ability of the different explanatory variables in predicting plant species richness within and between the study areas. In both the study areas, the inclusion of measures of geodiversity improved the explanatory power, predictive ability and robustness of the plant species richness models. In conclusion, the explicit measures of geodiversity appear to be promising surrogates of biodiversity, which reflect important abiotic resource factors, and may thus provide an equally, or even more reliable basis for transferring biodiversity models to new areas than models based on climate and topography variables.