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EECG Embarkation: Measuring local adaptation through constitutive gene expression



About the Blog Author

Shelby Tisinai is a PhD Candidate with Dr. Jeremiah Busch at Washington State University. She is currently using molecular techniques to explore environmental and genomic drivers of local adaptation in plant populations endemic to steep elevational gradients. Follow Shelby on Twitter @s_tisinai for updates on her work.




One of the primary goals in evolutionary ecology is to understand how the environment shapes populations and drives local adaptation. Mountain habitats have often been used as a backdrop for teasing apart important differences between populations. Differences in slope, aspect, exposure, and solar radiation create microclimates throughout mountainous regions, creating a mosaic effect across the landscape. Elevation change plays a role, too, leading to distinct elevational regions or “life zones” (Holdridge 1947). All these factors influence the seasonal and diurnal climatic conditions experienced by plants and exert various selective pressures on populations, driving population differentiation and local adaptation (Körner 2003).


Commonly, studies investigating local adaptation will invoke provenance trials (Hamann, Wagymar, and Anderson 2021) or reciprocal transplants (Bemmels and Anderson 2019) to track conserved phenotypes and fitness landscapes in populations from distinct regions. As technology advances and DNA sequencing of non-model species becomes more feasible, an increasing number of studies have tracked SNP variants among populations (FST) to reveal nucleotide differences that may be important for adaptation to the local environment. Each of these methods — tracking phenotypes and revealing genotypes — can tell us much about the long-term evolutionary history of an organism but tend to fall short in revealing more recent adaptations since selective sweeps require a long time to increase in frequency in a population and rare variants are harder to detect with FST (Bahtia et al. 2013).


Gene expression (GE) has been posited to evolve faster than allele frequencies (Wilson and King 1975). Under scenarios where observable differences in phenology or fitness are not strikingly obvious and FST implies weak differentiation among populations, gene expression analyses might be the smoking gun for revealing recent local adaptation (Wilson and King 1975). Gene expression analyses can also provide opportunity for learning how populations have dealt with recent environments and how those responses differ among populations. Mountains have been feeling the effects of climate change at a faster clip than other regions of the world; evidence has also indicated that the effects are also not uniform between elevations (Hock et al. 2019). It stands to reason that GE has been altered to meet conditions that have been increasing in novelty and variety since the late 19th century. My Ph.D. work is focused on revealing molecular adaptation to mountain habitats and how plant populations are responding to environmental change. The AGA EECG grant is enabling me to discover how constitutive GE varies along an elevational gradient. By growing plants in common garden settings and sequencing total RNA extracted from leaf tissue, we’ll be able to measure constitutive expression of=most genes in the genome. Genes with significant differences in constitutive expression may be important for local adaptation. If populations from different elevations demonstrate highly differentiated GE patterns, what does that tell us about the dynamics of past environments? How might those populations respond to future environments? I’ll report back in my Epilogue post on how constitutive gene expression contributes to local adaptation in mountain habitats.


Bhatia G, Patterson N, Sankararaman S,  Price AL (2013) Estimating and interpreting FST: the impact of rare variants. Genome research. 23(9): 1514-1521.

Bremmels JB, Anderson JT (2019) Climate change shifts natural selection and the adaptive potential of the perennial forb Boechera stricta in the Rocky Mountains. Evolution. 73(11): 2247-2262.

Hamann E, Wadgymar SM, Anderson JT (2021) Costs of reproduction under experimental climate change across elevations in the perennial forb Boechera stricta. Proceedings of the Royal Society B. 288:1948.

Hock R, Rasul G, Adler C, Cáceres B, Gruber S, Hirabayashi Y, Jackson M, Kääb A, Kang S, Kutuzov S, Milner A, Molau U, Morin S, Orlove B, Steltzer H (2019) High Mountain Areas. In: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate [Pörtner H-O, Roberts DC, Masson-Delmotte V, Zhai P, Tignor M, Poloczanska E, Mintenbeck K, Alegría A, Nicolai M, Okem A, Petzold J, Rama B, Weyer NM(eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA, pp. 131-202.

Holdridge LR (1947) Determination of world plant formations from simple climatic data. Science. 105 (2727): 367-8.

Körner C (2003) Alpine plant life: functional plant ecology of high mountain ecosystems. Springer.

Wilson AC, King M-C (1975) Evolution at Two Levels in Humans and Chimpanzees: Their macromolecules are so alike that regulatory mutations may account for their biological differences. Science. 188(4184): 107-116.

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