Résumé
Understanding vulnerabilities of plant populations to climate change could
help preserve their biodiversity and reveal new elite parents for future
breeding programs. To this end, landscape genomics is a useful approach
for assessing putative adaptations to future climatic conditions,
especially in long-lived species such as trees. We conducted a population
genomics study of 207 Coffea canephora trees from seven forests along
different climate gradients in Uganda. For this, we sequenced 323
candidate genes involved in key metabolic and defense pathways in coffee.
Seventy-one SNPs were found to be significantly associated with
bioclimatic variables, and were thereby considered as putatively adaptive
loci. These SNPs were linked to key candidate genes, including
transcription factors, like DREB-like and MYB family genes controlling
plant responses to abiotic stresses, as well as other genes of
organoleptic interest, like the DXMT gene involved in caffeine
biosynthesis and a putative pest repellent. These climate-associated
genetic markers were used to compute genetic offsets, predicting
population responses to future climatic conditions based on local climate
change forecasts. Using these measures of maladaptation to future
conditions, substantial levels of genetic differentiation between present
and future diversity were estimated for all populations and scenarios
considered. The populations from the forests Zoka and Budongo, in the
northernmost zone of Uganda, appeared to have the lowest genetic offsets
under all predicted climate change patterns, while populations from
Kalangala and Mabira, in the Lake Victoria region, exhibited the highest
genetic offsets. The potential of these findings in terms of ex-situ
conservation strategies are discussed.