A group of researchers from the University of Melbourne reviewed how global climate changes threaten biodiversity. Genomic vulnerabilities can help researchers assess if certain species will make the necessary genetic changes to adapt to
future extreme temperatures, rainfall and other climate conditions.
Changes in temperature and rain patterns are putting increasing pressure on many species’
genotypes and phenotypes (i.e. physical traits). Therefore, it is important to study and predict how these climate changes may negatively affect these species and their ability to adapt.
Professor Arya Hoffmann and his group of scientists from the University of Melbourne study climatic stress and aim to
understand how this stress affects organisms’ genetic traits. Assessing and understanding evolutionary adaptation is complicated. The genome has millions of
highly variable genetic markers (single-nucleotide polymorphisms or SNPs), but only some of these will
contribute to climatic adaptation.
Genomic vulnerability (GV) focuses on those genetic markers that may contribute to adaptation. GV relies on the association between alleles and genotypes with the environment; also known as the genetic-environment associations (GEAs). For example,
changes in temperatures (high or low) or rainfall can generate GEAs一such associations often appear after hundreds of generations.
‘Genomic vulnerability (GV) focuses on those genetic markers that may contribute to adaptation.’
The GEA displays how species adapt to local climate conditions or habitats but, unfortunately, these associations may become vulnerable when there is a limitation in their GEA variation. A study on yellow warblers (Setophaga petechia), a North
American species of songbird, found that genetic markers linked to migratory behaviours have put the population at risk.
Through genome-wide association methods, researchers found a genetic marker with a strong association with environmental variables, all rainfall-related. Additionally, this marker was found at close proximity with the DRD4 and
DEAF1 migratory behaviour genes.
Due to severe and rapid climatic changes, in particular rainfall, the researchers predict that the warbler’s current populations do not match the genetic changes required to adapt to future climate changes. This is an example of a
population identified as ‘genomically vulnerable’ which is predicted to lead to further population decline.
Identifying genes associated with genomic vulnerability
How can scientists identify genes or candidate genes for GV? These studies attempt to narrow down highly variable genes, then identify those that vary along environmental gradients. As previously mentioned, DRD4 and
DEAF1 migratory genes of yellow warblers are key candidates due to their proximity to genetic markers with strong associations with rainfall.
Similarly, a study on the balsam poplar (Populus balsamifera) plant considered the GIGANTEA-5 (GI5) as a candidate genedue to its known connection to climate and their association with SNPs. GI5 genes interact
with the circadian clock response pathways and respond to warmer temperatures (starting from 12°C and 15°C)一thus, GI5 is a strong candidate gene for environmental adaptation and potential GV.
Other methods involve looking into highly variable genome sections not traditionally connected with GV. For example, kangaroo grass (Themeda triandra), a plant commonly found in Australia, is well-adapted to its environment thanks to
Polyploidy is the condition of having more than two sets of chromosomes (humans have diploid cells, meaning we have a pair of each). Through polyploidy, these plants have a reduced vulnerability (they are more resilient) to hotter climates.
‘Through polyploidy, these plants have a reduced vulnerability (they are more resilient) to hotter climates.’
How can future genomic vulnerability be predicted?
GV may be predicted by using the methods presented by Fitzpatrick and Keller in 2014. Using gradient forest analysis, researchers can assess if the current genomic variations match or mismatch future climate conditions. Populations with the
highest GV have the least chances of adapting and thus survival.
Similarly to the example of yellow warblers, the researchers found genes with GEA that will likely not show the necessary variability shifts overtime to catch up with fast-paced climate changes.
This approach is useful in identifying species with the greatest adaptation pressure and a way to tackle real-world conservation problems. A simplified guide to calculating GV can be found on The G-Cat Blog, in which they combine genetic data in the form
of allele frequencies with environmental data.
Another benefit of GV analysis involves identifying species at risk, especially ‘keystone species’一those which define an ecosystem. Due to their ecological importance, GV analysis should, therefore, help conservationists prioritise keystone
species when protecting biodiversity. Another example of GV applied to agricultural practises is seen in the pearl millet plant, commonly grown in West Africa due to its importance in food production.
Despite its usefulness, this methodology has many limitations, including the misinterpretation of results due to the complexity of genomics and the unpredictability of future climate changes.
‘Due to their ecological importance, GV analysis should, therefore, help conservationists prioritise keystone species when protecting biodiversity.’
Identifying genomic vulnerable populations is an important process of understanding how climate change may negatively impact these populations in the coming decades. Species, such as the yellow warbler, have already been in decline for the
past 50 years due to genomic vulnerability. If we aim to protect biodiversity, we must use every resource to better understand how extreme climate conditions will affect vulnerable plants and animals.
Featured Image: Jason H | Vincent Ledvina | Geoff Brooks | Felipe Simo | Unsplash / Mdf | Wikimedia Commons
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