Oaks, a genus comprising c. 700 species of deciduous and evergreen trees, are widely distributed across the northern hemisphere, ranging from Asia and Europe to central and north America. They are an integral part of our landscape, providing many ecological services and harboring a species-rich assemblage of organisms below and above ground (Brändle & Brandl, 2001). Several thousand species, mainly bacteria, insects and fungi, but also reptiles, amphibians, mammals and birds, depend on oaks entirely or at least for some part of their life cycle. Oaks, as a foundation species, interact with many organisms within the species co-evolving networks that constitute forest ecosystems. Suppressing oaks from forests will thus jeopardize species interactions in ecosystems. Oaks impact biotic interactions but the whole community of interacting species, in turn, influences their fitness, positively and negatively, generating a diversity of outcomes beyond escalating arms races or obligate mutualisms. Studying the mechanisms underlying such biotic interactions is therefore crucial to understanding both sides of the interactions. One side relies on the influence of tree genotypes on associated communities, the other relies on the effect of these communities on tree genotypes and is nicely illustrated in this issue of New Phytologist by Tarkka et al. (pp. 529–540) at the molecular scale. Because climate change could modify every species selection's trajectory, it could impact the structure and composition of these co-evolving networks and ultimately lead us to questions about the adaptability of forest ecosystems.
‘The emerging field of ecological genomics … provides a multidisciplinary platform to understand how great oaks from little acorns grow – Parvis e glandibus quercus – and how they interact with their environment.’
The emerging field of ecological genomics (Song & Mitchell-Olds, 2011) provides a multidisciplinary platform to understand how great oaks from little acorns grow – Parvis e glandibus quercus – and how they interact with their environment. Indeed, fields and tools from ecology to genetics and genomics interact in a mutually beneficial manner, especially as sequencing and genotyping technologies show continuous declining costs (Wall et al., 2009) and become affordable for individual laboratories. Thus, ecologists are rapidly harnessing the genomic toolbox to study rules that govern processes influencing the distribution and abundance of organisms (Ekblom & Galindo, 2011). Through molecular approaches they can now easily study short-term responses of organisms to their biotic (Barakat et al., 2009) and abiotic environments (Dassanayake et al., 2009) and make inferences on how these molecular factors matter for adaptation (Hohenlohe et al., 2010).
The ecology of below-ground and above-ground communities is connected via induced plant responses. It is now recognized that the ecology and evolution of species within a community are inter-related and this is a central point in studies of eco-evolutionary dynamics and community genetics (Whitham et al., 2006; Johnson & Stinchcombe, 2007; Pelletier et al., 2009). Manipulating interactions using experimental communities has proven to be useful to study adaptation in this context. However, very few studies combine artificial trophic network with quantitative genetics, genomics, or transcriptomics to propose inferences about how organisms functionally respond to reciprocal interactions within a community (but see Tetard-Jones et al., 2011). The study by Tarkka et al. is one of these. They elegantly established a controlled system in Petri dish soil microcosms ‘TrophinOak, www.TrophinOak.de’ to study resource allocation and gene expression in multitrophic interactions. Interacting species included ectomycorrhiza (EM), root pathogenic microorganisms, rhizospheric invertebrate consumers, mycorrhization helper bacteria, leaf pathogenic fungi and leaf invertebrate herbivores. Every species from their experimental community can interact with each other either directly or indirectly through pedunculate oak (Quercus robur) microcuttings. This study illustrates how technological advances (i.e. new generation sequencing technologies to shed more light onto the molecular machinery underlying ecological processes, bioinformatics and computer science for the analysis of huge datasets) have become indispensable for revisiting ‘what happens’ between communities of living organisms and their environment. In this context, Tarkka et al.'s paper consists of two main achievements:
- The construction of a gene catalog for oak. High-throughput sequencing technologies are now routinely applied in plant, animal and microbial biology to address important ecological questions that were impossible to address previously. To achieve their first objective ‘establish a gene catalog for oak’, Tarkka et al. collected leaves and roots of each interaction type, prepared normalized cDNA libraries for deep sequencing and assembled this vast amount of sequence data in a 66k oak gene index, enabling the identification of differential gene expression in biotically challenged oak tissues. This collection of transcribed genes supplements the first catalog of oak transcripts mainly developed from abiotically challenged oaks (Ueno et al., 2010). Both datasets have now been merged into the most comprehensive annotated gene catalog for oak (I. Lesur et al., unpublished) and this genomic resource will be used to identify gene loci and annotating the exon/intron structure of the pedunculate oak genomic sequence that is being assembled by a French consortium (Kremer et al., 2012). As it has been shown in model species (Turner et al., 2010), a well-annotated genome sequence will be instrumental for evolutionary biologists that are poised to answer classic questions in ecology and evolution, such as the role of gene regulation and structural polymorphism in defining ecotypes or species’ boundaries.
- The discovery of specific molecular mechanisms involved in the regulation of oak EM. The use of genomics to address some of the long-standing questions in the ecology of plant–microorganism interactions is expanding rapidly: What are the gene networks involved in interacting partners? Are these genes conserved across species or do they differ according to the environment or species? How do fungal genes differ with respect to a saprotrophy–biotrophy continuum? And from the plant perspective what are the genes involved in symbiosis interaction (symbiogenetic factors) that have presumably been crucial in the adaptation to terrestrial life (Heckman et al., 2001)? All these exciting questions are now being explored in non-model plants including forest trees. In this context, Tarkka et al. investigated the effect of mycorrhiza formation with Piloderman croceum by RNA-seq analysis (a method that uses high-throughput sequencing to sequence cDNA in order to obtain information about transcript accumulation in a sample) to deepen their knowledge about the regulation of gene expression in EM roots of oak, and to identify key molecular players involved in EM formation. Their main findings concern the ontogeny of gene expression in oak with the interaction with EM. Indeed, they showed that in mature oak, EM plant defense genes are attenuated, ethylene signaling is enhanced, auxin-related genes are down-regulated, and gene encoding for cell wall remodeling are either down- (extensins, peroxidases) or up- (prolin-rich proteins, expansins) regulated indicating a reduced potential for cross-linking of cell wall components in EM roots. In addition, they found for the first time a remorin encoding gene over-expressed in EM roots, and suggested from the pattern of transcript accumulation of genes associated with several metabolic pathways (e.g. nitrogen, phosphorus and sugar transporters) the presence of specific mechanisms in oak EM compared with other forest trees. Such species dependency of EM symbiosis genes illustrates the complexity of developmental reprogramming mechanisms underlying plant–microorganism interactions and call for a more systematic characterization of the plant genes to understand host responses to different interacting partners.
Understanding how natural selection drives evolution is a key challenge in evolutionary biology. Studies of adaptation usually focus on how a single environmental factor, either physical (i.e. water availability), or biotic (i.e. pathogen infection) affects evolution within a single species. But nature is much more complex and species are embedded within communities of thousands of species that interact with one another and with the physical environment. Experiments such as those of Tarkka et al. represent a very first step in addressing the complexity of the evolutionary significance of such ecological complexity, and in testing the evolutionary impact of interactions among multiple species during adaptation.
What to expect next? Examination of naturally occurring genetic variation of molecular phenotypes and test for their relative fitness, since selection acts within species and inferences about adaptation can only be made while testing among individual differences for fitness-related traits. To this end, comparing oak transcriptome/proteome/metabolome, as well as structural genomic differences between different gene-pools in relation to biotic interaction, should help towards a better understanding of the genetic basis underlying complex interactions and adaptation: do tree-associated communities select for the dynamic of ontogeny in the regulatory landscape of plant genomes, or do they select for different allelic combinations, or both? Moving from Petri dish experiments (i.e. highly controlled laboratory settings) with limited genetic diversity to the wild with high genetic diversity and a much higher number of interactions is an obvious prerequisite to understand ecological adaptation and fitness. In this context, the European white oak species complex offers contrasted genetic resources (segregating mapping pedigrees, locally adapted populations, sister species undergoing incipient speciation, hybrids between sympatric species) to answer key questions in evolutionary ecology.