Candidate genes for the high-altitude adaptations of two mountain pine taxa

Julia Zaborowska, Bartosz Łabiszak, Annika Perry, Stephen Cavers, Witold Wachowiak

Research output: Contribution to journalArticlepeer-review

Abstract

Mountain plants, challenged by vegetation time contractions and dynamic changes in environmental conditions, developed adaptations that help them to balance their growth, reproduction, survival, and regeneration. However, knowledge regarding the genetic basis of species adaptation to higher altitudes remain scarce for most plant species. Here, we attempted to identify such corresponding genomic regions of high evolutionary importance in two closely related European pines, Pinus mugo and P. uncinata, contrasting them with a reference lowland relative—P. sylvestris. We genotyped 438 samples at thousands of single nucleotide polymorphism (SNP) markers, tested their genetic differentiation and population structure followed by outlier detection and gene ontology annotations. Markers clearly differentiated the species and uncovered patterns of population structure in two of them. In P. uncinata three Pyrenean sites were grouped together, while two outlying populations constituted a separate cluster. In P. sylvestris, Spanish population appeared distinct from the remaining four European sites. Between mountain pines and the reference species, 35 candidate genes for altitude-dependent selection were identified, including such encoding proteins responsible for photosynthesis, photorespiration and cell redox homeostasis, regulation of transcription, and mRNA processing. In comparison between two mountain pines, 75 outlier SNPs were found in proteins involved mainly in the gene expression and metabolism.
Original languageEnglish
JournalInternational Journal of Molecular Sciences
Volume22
Issue number7
DOIs
Publication statusPublished - 27 Mar 2021

Fingerprint

Dive into the research topics of 'Candidate genes for the high-altitude adaptations of two mountain pine taxa'. Together they form a unique fingerprint.

Cite this