Landscape genetics reveals that adaptive genetic divergence in Pinus bungeana (Pinaceae) is driven by environmental variables relating to ecological habitats

Abstract

Background Understanding the genetic basis of local adaptation has long been the concern of biologists. Identifying these adaptive genetic variabilities is crucial not only to improve our knowledge of the genetic mechanism of local adaptation but also to explore the adaptation potential of species. Results Using 10 natural populations and 12 start codon targeted (SCoT) markers, a total of 430 unambiguous loci were yielded. The Bayesian analysis of population structure clearly demonstrated that the 10 populations of P. bungeana could be subdivided into three groups. Redundancy analysis showed that this genetic divergence was caused by divergence selection from environmental variables related to the ecological habitats of “avoidance of flooding” and “avoidance of high temperature and humidity.” LFMM results indicated that Bio1, Bio5, Bio8, Bio12, Bio14, and Bio16, which are related to the ecological habitat of P. bungeana , were correlated with the highest numbers of environment-associated loci (EAL). Conclusions The results of EAL characterization in P. bungeana clearly supported the hypothesis that environmental variations related to the ecological habitat of species are the key drivers of species adaptive divergence. Moreover, a method to calculate the species landscape adaptation index and quantify the adaptation potential of species was proposed and verified using ecological niche modeling. This model could estimate climatically suitable areas of species spatial distribution. Taking the results together, this study improves the current understanding on the genetic basis of local adaptation. Electronic supplementary material The online version of this article (10.1186/s12862-019-1489-x) contains supplementary material, which is available to authorized users.

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EST‐SSR‐based landscape genetics ofPseudotaxus chienii, a tertiary relict conifer endemic to China

“…As for endangered plants, the integration may facilitate the prediction of suitable ranges under climatic change and inform conservation measures. For instance, a combination of the two methods has been used to modeling the climatically suitable areas of Pinus bungeana (Zhang et al., 2019).…”

Landscape genomics reveals genetic evidence of local adaptation in a widespread tree, the Chinese wingnut (Pterocarya stenoptera)

“…Evolving under diverse selection pressures may lead to the genetic differentiation on a genome-wide scale, which eventually produce physiological, phenotypic or phenological changes (Rellstab et al, 2015). Adaptive phenotypic changes may confer adaptability for species to cope with changing ecological niches and climates (Zhang et al, 2019). Therefore, identification of the genetic variants associated with local adaptation is critical to elucidate the underlying molecular mechanisms of adaptive evolution (Ahrens et al, 2019;Li et al, 2020).…”