Landscape genomics is a relatively new discipline that aims to reveal the relationship between adaptive genetic imprints in genomes and environmental heterogeneity among natural populations. Although the interest in landscape genomics has increased since this term was coined, studies on this topic remain scarce. Landscape genomics has become a powerful method to scan and determine the genes responsible for the complex adaptive evolution of species at population (mostly) and individual (more rarely) level. This review outlines the sampling strategies, molecular marker types and research categories in 37 articles published during the first 10 years of this field (i.e., 2007–2016). We also address major challenges and future directions for landscape genomics. This review aims to promote interest in conducting additional studies in landscape genomics.

Understanding the genetic mechanisms of adaptation to environmental variables is a key concern in molecular ecology and evolutionary biology. Determining the adaptive evolutionary direction and evaluating the adaptation status of species can improve our understanding of these mechanisms. In this study, we sampled 20 populations of Forsythia suspensa to infer the relationship between environmental variables and adaptive genetic variations. Population structure analysis revealed that four genetic groups of F. suspensa exist resulting from divergent selection driven by seven environmental variables. A total of 26 outlier loci were identified by both BayeScan and FDIST2, 23 of which were environment-associated loci (EAL). Environmental association analysis revealed that the environmental variables related to the ecological habitats of F. suspensa are associated with high numbers of EAL. Results of EAL characterization in F. suspensa are consistent with the hypothesis that ecological habitats determine the adaptive evolution of this species. Moreover, a model of species adaptation to environmental variables was proposed in this study. The adaptation model was used to further evaluate the adaptation status of F. suspensa to environmental variables. This study will be useful to help us in understanding the adaptive evolution of species in regions lacking strong selection pressure.

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.

Knowledge on adaptive genetic variation in response to environmental variation is the key to understanding the adaptive evolution potential of species. China's warm‐temperate zone is an important climatic zone, but only a few landscape genomics studies have been conducted to understand the adaptive evolution of regional vegetation. In this study, natural populations of Achyranthes bidentata Blume were sampled in China's warm‐temperate zone to infer its adaptive evolution using landscape genomics methods. Four SCoT primers were used to investigate the adaptive evolution of A. bidentata in response to environmental variation across the warm‐temperate zone of China. A total of 126 individuals from fifteen natural populations were successfully scored, and 202 unambiguous fragments were obtained. Twenty‐three outlier loci were identified, eighteen outlier loci were significantly associated with environmental variables. Redundancy analytical results suggested that four environmental variables related to temperature and precipitation remarkably influenced the distribution of loci. The results provide empirical evidence that molecular markers with bias toward candidate functional genes might be suitable for landscape genomics studies. Temperature and precipitation jointly drive the adaptive evolution of A. bidentata. The key driving environmental factors identified in this study are mostly related to the ecological habit of A. bidentata. The species personality, i.e., ecological habit, seems to play an important role in the adaptive differentiation on A. bidentata.

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