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The role of structural variants in rapid adaptation

The role of structural variants in rapid adaptation
结构变异在快速适应中的作用
批准号:
NE/X015351/1
负责人:
Laura Kelly
金额:
$91.68万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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英文摘要
Wild species are under growing pressure from a range of different threats. These include increased temperatures as a result of climate change and new pests and diseases arriving as a consequence of global trade and travel. Many trees around the world currently face such threats, causing them to become stressed and rendering them less able to perform functions that we all benefit from, such as capturing and storing carbon dioxide or reducing flooding risk by decreasing surface water run-off. Ultimately, individuals that are unable to cope with these threats will decline and die, which can not only place whole tree species at risk but also the associated biodiversity that depends on these species. However, despite being large and often long-lived organisms, we know that tree species have the potential to adapt quickly to new challenges in their environment. Large differences between the DNA of individuals, structural variants, may be particularly important for rapid adaptation because they can result in more dramatic changes in phenotype than is the case for small changes to DNA. Until recently it has not been possible to properly evaluate the contribution of SVs to genetic adaptation at the population level - advances in genome sequencing and analysis methods mean this ambitious goal can now be pursued.This project will look at whether structural variants play a key role in how species are able to rapidly adapt to new threats. To test this, we will use the case of ash dieback disease (ADB) in native UK populations of European ash, which presents an exceptional opportunity to analyse the genomic changes involved in evolutionary response to newly imposed sources of stress. The European ash tree is one of the most common woodland trees in the UK and, in last ten years, has suffered severe damage from the invasive fungus that causes ADB. Although most ash eventually die once they are infected with the disease, a small percentage of individuals are resistant and remain healthy even when surrounded by diseased and dying trees. We will sample multiple natural UK populations of ash trees where both healthy and diseased adults that predate the ADB epidemic and healthy and diseased juveniles that established since the disease arrived are present. We will perform whole genome sequencing for hundreds of individuals from each population and also score them for their level of resistance to the disease. Using these data, first we will test for associations between SVs and resistance to ADB to estimate the relative contribution of SVs to resistance, compared with that of single nucleotide variants (SNPs). For SVs or SNPs significantly associated with resistance, we will test for allele frequency shifts between generations in each population and analyse if this is associated with increased resistance to ADB among the younger cohort - a sign that the species is starting to adapt to the disease. This will allow us to establish the comparative importance of SVs for ongoing adaptation. We will then examine the relationship between disease pressure and SV formation rate. Stress may stimulate an elevated rate of SV formation, which by exposing more adaptive mutations to selection could provide a path for rapid adaptive evolution. Finally, we will determine if the accuracy with which genomic data can be used to predict individuals with the greatest level of resistance to the disease (genomic prediction) can be significantly improved by incorporating information on SVs.By advancing understanding of the role of SVs in adaptive evolution to newly imposed selection pressures, and through developing effective strategies for improving genomic prediction, this project will also enhance our ability to predict which individuals are most likely to survive future threats and help to inform actions to manage natural populations for increased resilience and protect biodiversity.
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