Genetic basis behind complex traits is the key question in biology. In this project, we construct a nested association mapping (NAM) population for silver birch that is used to identify loci associated with the traits, quantified in controlled conditions. Combined with accurate functional annotation of the genome, we identify loci which are key regulators of traits related to forest tree biology, more specifically to natural variation in silver birch. First application is to
identify loci associated with wood quality.
Correct interpretation of environmental cues is a matter of life and death for plants, because as sessile organisms they cannot escape unfavorable conditions. For example, pines and birches have the ability to measure the day-length and to use it for determining the end of the growing season and to start making preparations for winter. Gene expression and its control have an important role in observing these signals and converting them to actual functional and physiological changes.
In this project, we study how genomic regions controlling gene expression affect physiological responses driven by the environment and how these reactions differ among two tree species having very different genome sizes and large evolutionary distance from each other. We will also inspect how populations from different European locations differ in their genomic response to environmental change.
We concentrate on Scots pine and silver birch because they have similar adaptations at the phenotypic level, even though they are phylogenetically very distant and differ in genome size: birch has a small genome in comparison to gigantic conifer genomes. Both species are ecologically and economically important and already have been studied extensively, which provides a lot of necessary background information. Our results will help to understand how plants genetically adapt to environmental change and how fast responses we can expect from them. The results can be also utilized in forest tree breeding, optimal deployment of regeneration material and predicting the impact of breeding.
To answer these questions, we will carry out both greenhouse and field experiments, DNA sequencing to identify genetic diversity, RNA sequencing to asses gene expression levels and novel molecular methods to identify active, regulatory regions of the genome. New analytical and statistical methods are developed during the project to optimally combine different types of large datasets.
This project is carried out in collaboration with Tanja Pyhäjärvi and Mikko Sillanpää from University of Oulu and Katri Kärkkäinen from Luke.
Uptake of nutrients from the soil is an essential factor of plant growth. For this means, plants have developed symbioses with soil microbiota, such as arbuscular mycorrhizal (AM), ectomycorrhizal (EM), and nitrogen-fixing root nodule symbioses (RNS). First land plants developed arbuscular mycorrhizal (AM) symbiosis with Glomeromycota roughly 450 million years ago (Mya), possibly accompanied with another symbiosis with Mucoromycotina.Root nodule nitrogen-fixing symbiosis (RNS) is most recent, originating from a single evolutionary innovation event in the common ancestor of Fabales, Fagales, Cucurbitales and Rosales ca. 100 Mya. However, RNS has been independently lost in most plant lineages within these clades, possibly because with the decreased global CO2-levels in the Cenozoic era the uptake of nitrogen is not the limiting factor for plant growth. Climate change is projected to rapidly alter the CO2-levels in the atmosphere, contributing to altered environmental conditions and thus selection pressure. As a result, RNS may be more advantageous strategy in the future.
Here we will carry out a comparative population genomics study in a family where RNS species still exist. Comparison of the genomic patterns between RNS species and related non-RNS species will illustrate the differences in historical population sizes due to differing strategies as well as genes under selective sweeps.