Site and ecotype gene expression differences of an ecologically-dominant prairie grass Andropogon gerardii across the Great Plains’ climate gradient

Background/Question/Methods

Ecologists have long pondered the role of environment and genetics in adaptation. Reciprocal gardens offer an opportunity to assess genetic x environment interactions. In the genomic era, it is now possible to investigate gene expression across environments for foundational, non-model plants. The main question is what is the extent of environment vs gene expression in conveying adaptation of dominant grass of the Great Plains, Andropogon gerardii, big bluestem to the sharp precipitation gradient across the Great Plains? To address this, two ecotypes (dry ecotype native to Central KS, 500 mm rain per year) and wet ecotype native to Illinois, 1200 mm rain per year) were reciprocally planted in Central KS and Illinois. Measurements of cover, and physiological responses were also made. De novo transcriptome assembly was performed using Trinity. Contigs were clustered with CD-HIT EST followed by TransDecoder to identify coding regions within contigs. STAR was used to align reads to the de novo assembly and produce gene counts. Gene expression was performed using DeSeq2 and genes were annotated using BlastX and Blast2Go. Functional enrichments were performed using REVIGO. Plants were also genotyped, single nucleotide polymorphisms were identified and genetic outlier analyses were performed.

Results/Conclusions

Both site and ecotype showed differential regulation of genes—that is, when sites were compared, we detected differential regulation of genes between wet and dry sites. Looking for ecotype specific genes, when the dry ecotype was compared with the wet ecotype, we found differential regulation between wet and dry ecotypes, regardless of site. Both site and ecotype were of similar magnitude of importance in controlling gene expression. In terms of plant cover, the dry site shows reduced plant cover of the wet ecotype and conversely the wet site shows reduced cover of the dry ecotype, and these differences became more distinct over time. For physiological measurements, generally, the dry ecotype had a higher photosynthetic rate than the wet ecotype in Central KS. Genetic PCoA corroborates the shows strong separation between dry and wet ecotypes. Outlier analysis in BayeScan and Bayenv2 identified 64 outlier genes showing differentiation among ecotypes. One outlier gene of interest, GA1, is involved with gibberellic acid metabolism and is well known in controlling plant height. Using the power of reciprocal gardens combined with gene expression analyses and ecological response variables provide an integrative picture of how plants respond and adapt to the environment in the long term.