Landscape genomics reveal that ecological character determines adaptation: a case study in smoke tree (Cotinus coggygria Scop.)

Abstract

BackgroundThe adaptive evolution of species response to environment are the key issues in molecular ecology and evolutionary biology. The direction of adaptive differentiation of species in regions lacking strong selection pressure is usually diverse. However, the driving mechanism of the diverse adaptive differentiation for regional species is still undetermined to date. In this study, we used landscape genomics modelling to infer the adaptive evolution of Cotinus coggygria in China’s warm-temperate zone.ResultsUsing fifteen natural populations and nine start codon targeted (SCoT) markers, a total of 1131 unambiguous loci were yielded. Our results showed two genetic groups existed in the fifteen natural populations of C. coggygria, which is due to the divergent selection driven by six environmental factors. Environmental association analyses revealed the environmental variables related to precipitation were associated with high numbers of environment-associated loci.ConclusionsOur results indicated that the ecological characters of C. coggygria, i.e. avoiding wetness and tolerating drought, determine its adaptive evolution. This study provides a reference that ecological character determines the adaptive evolution of species in regions lacking strong selection pressure.Electronic supplementary materialThe online version of this article (10.1186/s12862-017-1055-3) contains supplementary material, which is available to authorized users.

Adaptive genetic differentiation in Pterocarya stenoptera (Juglandaceae) driven by multiple environmental variables were revealed by landscape genomics

“…Here, the results of LFMM analysis showed that Sr6, Bio6, Bio4, and Wvp1 were associated with the highest numbers of EAL, which suggested that these environmental variables play a major role on the genetic differentiation of P. stenoptera genome. Recent landscape genomic studies have proposed a hypothesis that environmental variables related to ecological habitats of species play key roles in driving adaptive differentiation of species genome [ 2 , 14 , 15 ]. Among the four environmental variables associated with the largest number of adaptive loci, Sr6 was associated with the ecological habitat of “prefered light”, and Bio6 and Wvp1 were associated with the ecological habitat of “warm and humid environment”.…”

“…All individuals were genotyped using SCoT markers. Despite its inherent defects lacking DNA sequence information, the SCoT marker has been used for landscape genomic studies because it has the advantages of non-requirement for genomic information, high repeatability, and high throughput [ 2 , 14 , 15 ]. After preliminary screening of the polymorphism and reproducibility of all SCoT primers [ 25 ], nine primers (SCoT5, SCoT9, SCoT16, SCoT18, SCoT25, SCoT27, SCoT30, SCoT31, and SCoT35) were selected for polymerase chain reactions (PCRs).…”

“…Are there common reasons behind these differences? Several recent landscape genomic studies have proposed a hypothesis that environmental variables related to ecological habitats play key roles in driving species adaptive evolution; in other words, the genes associated with these environmental variables will undergo adaptive differentiation [ 2 , 14 , 15 ]. More landscape genomic research is needed to test whether this hypothesis applies to other species as well.…”

Genome sequencing and population genomics modeling provide insights into the local adaptation of weeping forsythia

“…This raises the fundamental question of which environmental factors play key roles in promoting adaptive divergence. Recent studies have suggested that environmental factors related to ecological niche dimensions are the main forces driving adaptive differentiation 17,18 .…”

Ten Years of Landscape Genomics: Challenges and Opportunities

“…Different from landscape genetics, landscape genomics requires a sufficient number of molecular markers to cover the entire genome. Emphasis is placed on adaptive evolution at the genome level ( Miao et al, 2017 ). Landscape genetics, however, is biased toward using a relatively small number of molecular markers to reveal the relationship between environmental factors and the spatial genetic structure of populations ( Dionne et al, 2008 ; Poelchau and Hamrick, 2012 ; Manel and Holderegger, 2013 ).…”