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Additional file 3: Figure S10. Comparison with previous expression QTL studies. Heatmap comparing the top contributing genes of the axes H, D, GD, and GH with eQTL experiments from studies using C. elegans at various ages and treatments. Figure S11. Enrichment of the top contributors of axes H, D, GD, and GH with genes containing polymorphisms between N2 and CB4856. Figure S12. Projections of RIL data on GD and GH vs. the effect of a 4h heat-stress on lifespan. The effect of heat-stress on lifespan was given as the average lifespan in control conditions divided by average lifespan when exposed to a short heat-stress. Each point represents a different genotype. Correlations marked with a red cross were significant (i.e. Spearman; p < 0.05). Figure S13. Projections of IL data on axis GD and axis GH vs. the effect of heat-stress on lifespan. Figure S14. Projection of RIL data on D and H vs. the effect of heat-stress on lifespan. Figure S15. Projections of IL data on D and H vs. the effect of heat-stress on lifespan.

The role of species interactions in controlling the interplay between the stability of ecosystems and their biodiversity is still not well understood. The ability of ecological communities to recover after small perturbations of the species abundances (local asymptotic stability) has been well studied, whereas the likelihood of a community to persist when the conditions change (structural stability) has received much less attention. Our goal is to understand the effects of diversity, interaction strengths and ecological network structure on the volume of parameter space leading to feasible equilibria. We develop a geometrical framework to study the range of conditions necessary for feasible coexistence. We show that feasibility is determined by few quantities describing the interactions, yielding a nontrivial complexity-feasibility relationship. Analysing more than 100 empirical networks, we show that the range of coexistence conditions in mutualistic systems can be analytically predicted. Finally, we characterize the geometric shape of the feasibility domain, thereby identifying the direction of perturbations that are more likely to cause extinctions.

Parasitism is the most common consumer strategy among organisms, yet only recently has there been a call for the inclusion of infectious disease agents in food webs. The value of this effort hinges on whether parasites affect food-web properties. Increasing evidence suggests that parasites have the potential to uniquely alter food-web topology in terms of chain length, connectance and robustness. In addition, parasites might affect food-web stability, interaction strength and energy flow. Food-web structure also affects infectious disease dynamics because parasites depend on the ecological networks in which they live. Empirically, incorporating parasites into food webs is straightforward. We may start with existing food webs and add parasites as nodes, or we may try to build food webs around systems for which we already have a good understanding of infectious processes. In the future, perhaps researchers will add parasites while they construct food webs. Less clear is how food-web theory can accommodate parasites. This is a deep and central problem in theoretical biology and applied mathematics. For instance, is representing parasites with complex life cycles as a single node equivalent to representing other species with ontogenetic niche shifts as a single node? Can parasitism fit into fundamental frameworks such as the niche model? Can we integrate infectious disease models into the emerging field of dynamic food-web modelling? Future progress will benefit from interdisciplinary collaborations between ecologists and infectious disease biologists.