Forest Tree Evolution Via Expression Regulation
Collaboration with Katri Kärkkäinen (Natural Resources Institute Finland), Jarkko Salojärvi (University of Helsinki) and Mikko Sillanpää (University of Oulu)
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 com- parison 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.
Haploid selection in gymnosperms
Also diploid organisms have life stages where some genes are expressed in a haploid manner. In these situations, natural selection can directly affect also recessive alleles. In this project, I will use Scots pine (Pinus sylvestris) seed tissues to investigate this phenomenon.
Adaptive breeding for productive, sustainable and resilient forests under climate change
As a part of B4EST Horizon 2020 project, we will develope new large scale genotyping tools for Scots pine. In addition, in collaboration with NERC and Luke we will delve into possibilities of genomic prediciton in Scots pine. We will also investigate the correlation among different resilience and growth rates nationally and by comparing Finnish and Scottish breeding and natural Scots pine populations.
Genomics of adaptation in Pinus sylvestris
Coniferous trees thrill me, because they are an important part of forest ecosystems of the northern hemisphere and they are often genetically adapted in their local environments yet not much is known about how different evolutionary forces affect their huge genomes. As a part of ProCoGen, our aim in University of Oulu is to use population level sampling and exome sequencing data to identify genetic variation underlying adaptation in Pinus sylvestris
Evolutionary genomics in Betula pendula
As a part of GenTree project, we are investigating genome wide patterns of variation in Betula pendula and other European forest trees.
In this project, together with Mikko Sillanpää and Outi Savolainen, we develop and apply new statistical methods for analysis of molecular (gene expression and genetic variation) data.
Genomic selection in northern Europan Pinus sylvestris
In a collaborative GenoWood project, led by Teemu Teeri (University of Helsinki), Outi Savolainen (University of Oulu), Katri Kärkkäinen (Luke) and Fred Asiegbu (University of Helsinki) we are developing methods and best practices for applying genomic prediction in Scots pine. In recently funded B4EST H2020 project, we are part of a European collaboration of bringing new genomic techniques into practive in forest tree breeding and management.
Last updated: 7.8.2020