Seiðr: Efficient calculation of robust ensemble gene networks.

Gene regulatory and gene co-expression networks are powerful research tools for identifying biological signal within high-dimensional gene expression data. In recent years, research has focused on addressing shortcomings of these techniques with regard to the low signal-to-noise ratio, non-linear interactions and dataset dependent biases of published methods. Furthermore, it has been shown that aggregating networks from multiple methods provides improved results. Despite this, few useable and scalable software tools have been implemented to perform such best-practice analyses. Here, we present Seidr (stylized Seiðr), a software toolkit designed to assist scientists in gene regulatory and gene co-expression network inference. Seidr creates community networks to reduce algorithmic bias and utilizes noise corrected network backboning to prune noisy edges in the networks. Using benchmarks in real-world conditions across three eukaryotic model organisms, Saccharomyces cerevisiae, Drosophila melanogaster, and Arabidopsis thaliana, we show that individual algorithms are biased toward functional evidence for certain gene-gene interactions. We further demonstrate that the community network is less biased, providing robust performance across different standards and comparisons for the model organisms. Finally, we apply Seidr to a network of drought stress in Norway spruce (Picea abies (L.) H. Krast) as an example application in a non-model species. We demonstrate the use of a network inferred using Seidr for identifying key components, communities and suggesting gene function for non-annotated genes.

Metatranscriptomics captures dynamic shifts in mycorrhizal coordination in boreal forests.

Carbon storage and cycling in boreal forests-the largest terrestrial carbon store-is moderated by complex interactions between trees and soil microorganisms. However, existing methods limit our ability to predict how changes in environmental conditions will alter these associations and the essential ecosystem services they provide. To address this, we developed a metatranscriptomic approach to analyze the impact of nutrient enrichment on Norway spruce fine roots and the community structure, function, and tree-microbe coordination of over 350 root-associated fungal species. In response to altered nutrient status, host trees redefined their relationship with the fungal community by reducing sugar efflux carriers and enhancing defense processes. This resulted in a profound restructuring of the fungal community and a collapse in functional coordination between the tree and the dominant Basidiomycete species, and an increase in functional coordination with versatile Ascomycete species. As such, there was a functional shift in community dominance from Basidiomycetes species, with important roles in enzymatically cycling recalcitrant carbon, to Ascomycete species that have melanized cell walls that are highly resistant to degradation. These changes were accompanied by prominent shifts in transcriptional coordination between over 60 predicted fungal effectors, with more than 5,000 Norway spruce transcripts, providing mechanistic insight into the complex molecular dialogue coordinating host trees and their fungal partners. The host-microbe dynamics captured by this study functionally inform how these complex and sensitive biological relationships may mediate the carbon storage potential of boreal soils under changing nutrient conditions.

Candidate regulators and target genes of drought stress in needles and roots of Norway spruce.

Drought stress impacts seedling establishment, survival and whole-plant productivity. Molecular responses to drought stress have been most extensively studied in herbaceous species, mostly considering only aboveground tissues. Coniferous tree species dominate boreal forests, which are predicted to be exposed to more frequent and acute drought as a result of ongoing climate change. The associated impact at all stages of the forest tree life cycle is expected to have large-scale ecological and economic impacts. However, the molecular response to drought has not been comprehensively profiled for coniferous species. We assayed the physiological and transcriptional response of Picea abies (L.) H. Karst seedling needles and roots after exposure to mild and severe drought. Shoots and needles showed an extensive reversible plasticity for physiological measures indicative of drought-response mechanisms, including changes in stomatal conductance (gs), shoot water potential and abscisic acid (ABA). In both tissues, the most commonly observed expression profiles in response to drought were highly correlated with the ABA levels. Still, root and needle transcriptional responses contrasted, with extensive root-specific down-regulation of growth. Comparison between previously characterized Arabidopsis thaliana L. drought-response genes and P. abies revealed both conservation and divergence of transcriptional response to drought. In P. abies, transcription factors belonging to the ABA responsive element(ABRE) binding/ABRE binding factors ABA-dependent pathway had a more limited role. These results highlight the importance of profiling both above- and belowground tissues, and provide a comprehensive framework to advance the understanding of the drought response of P. abies. The results demonstrate that a short-term, severe drought induces severe physiological responses coupled to extensive transcriptome modulation and highlight the susceptibility of Norway spruce seedlings to such drought events.