Population Transcriptomes Reveal the Interspecific Adaptive Genetic Differentiation of Liriodendron by Landscape Genetics

Background: Adaptive genetic differentiation is a hotspot in the research of speciation mechanisms in evolutionary biology. Genomic resources are important for detecting ecological adaptive evolution of non-model plants. Using RNA-seq for non-model plants is a good approach to obtain their genomic resources. The combination of population transcriptome resources and environmental data can provide insights into the genetic mechanism of adaptive genetic differentiation.Results: Based on the population transcriptome data, we investigated the spatial distribution of genetic variations in Liriodendron to detect relationships between ecological factors and genetic differentiation. Environmental data and genetic variations from 17 populations were integrated to detect the population structure, adaptive genes and key environmental factors that shape the population genetic structure by landscape genetic approach. Here, we identified 16592 high-quality single nucleotide polymorphisms (SNPs). The population structure analysis results showed that 17 populations were divided into three groups: L. tulipifera, eastern group and western group of L. chinense. Redundancy analysis and latent factor mixed model analysis suggested that precipitation seasonality, precipitation in the driest quarter, diurnal temperature, and solar radiation in May were closely associated with the adaptive genetic differentiation of Liriodendron. Ecological niche differentiation analysis implied significant ecological niche divergence between L. chinense and L. tulipifera habitats. In total, 858 environment-related loci were identified, which were associated with 464 genes. Pathway enrichment analysis revealed that these genes were significantly enriched in multiple biological pathways. Related studies confirmed that these biological pathways play vital roles in plant growth, development, stress, immune response and photosynthesis.Conclusions: Our research provided empirical evidence that environmental factors may play a key role in driving adaptive genetic differentiation of species. Furthermore, the combination of population transcriptome resources and environmental datasets provides new insights into the study of adaptive genetic differentiation of species.