Department of Botany

College of Agriculture, Life Sciences and Natural Resources

Research Emphasis

The majority of variation segregating in natural populations is quantitative, and its expression depends on genetic background, environment, and interactions with these two factors. Traditionally, the evolution of quantitative traits has been described using statistical genetic techniques. However, one of the greatest advantages of these approaches is also one of their primary limitations: it is possible to estimate genetic variation and covariation in traits without any direct knowledge of the underlying loci or molecular genetic details. In like fashion, it is possible to estimate the pattern of natural selection on quantitative traits in the absence of knowledge of loci that determine fitness. Advances in collecting and analyzing molecular data promise to reveal the molecular genetic basis of quantitative trait variation. In our research, we use a combination of statistical and molecular genetic analyses to evaluate questions related to adaptation in heterogeneous natural environments.

Current Research Projects

Current externally funded projects focus on understanding 1) the transcriptomic and physiological mechanisms by which growth is promoted by the rhizosphere microbiome in Brassica rapa (NSF), 2) the effects of host plant genetic pathways on microbial community composition and the ecological consequences of microbial communities within the state of Wyoming (NSF), 3) the role of the circadian clock in adaptation to heterogeneous natural settings in Arabidopsis thaliana and Boechera stricta (NSF), and 4) the influence of shade-avoidance responses on yield in sugar beet (USDA).

Recent Publications (last 5 years)

McMinn, R, MJ Salmela, and C Weinig. 2022. Naturally segregating genetic variation in circadian period exhibits a regional elevational and climatic cline. Plant, Cell & Environment https://doi.org/10.1111/pce.14377 

 

Klasek, SA, MT Brock, WJ Calder, HG Morrison, C Weinig, L Maïgnien. 2022. Spatiotemporal heterogeneity and intragenus variability in rhizobacterial associations with Brassica rapa growth. Msystems https://doi.org/10.1128/msystems.00060-22 

 

Ponsford, JCB, CJ Hubbard, JG Harrison, L Maignien, CA Buerkle, and C. Weinig. 2022. Whole-genome duplication and host genotype affect rhizosphere microbial communities. Msystems https://doi.org/10.1128/msystems.00973-21 

 

DeWolf, EI, WJ Calder, JG Harrison, GD Randolph, BE Noren, and C Weinig. 2022. Aquatic macrophytes are associated with variation in biogeochemistry and bacterial assemblages of mountain lakes. Frontiers in Microbiology https://doi.org/10.3389/fmicb.2021.777084 

 

Hubbard, CJ, R McMinn, and C Weinig. 2021. Rhizosphere microbes influence host circadian clock function. Phytobiomes Journal https://doi.org/10.1094/PBIOMES-01-21-0005-SC 

 

Adjesiwor, AT, JG Ballenger, C Weinig, BE Ewers, and AR Kniss. 2021. Plastic response to early shade avoidance cues has season‐long effect on Beta vulgaris growth and development. Plant, Cell & Environment https://doi.org/10.1111/pce.14171 

 

Dibner, RR, AM Weaver, MT Brock, GF Custer, HG Morrison, L Maignien, and C Weinig. 2021. Time outweighs the effect of host developmental stage on microbial community composition. FEMS Microbiology Ecology https://doi.org/10.1093/femsec/fiab102 

 

Klasek, SA, MT Brock, HG Morrison, C Weinig, L Maignien. 2021. Soil microsite outweighs cultivar genotype contribution to Brassica rhizobacterial community structure. Frontiers in Microbiology https://doi.org/10.3389/fmicb.2021.645784 

 

Ta, J. C. Palmer, M.T. Brock, M.J. Rubin, C. Weinig, J. Maloof, and D. Runcie. 2020. Multiple loci control variation in plasticity to foliar shade throughout development in Arabidopsis thaliana. G3: Genes, Genomes, Genetics 10 (11), 4103-4114 

 

Brock, M.T., M.J. Rubin, D. DellaPenna, and C. Weinig. 2020. A nested association mapping panel in Arabidopsis thaliana for mapping and characterizing genetic architecture. 2020. G3: Genes, Genomes, Genetics 10 (10), 3701-3708 

 

Guadagno, C.R., D. Millar, R. Lai, D.S. Mackay, J.R. Pleban, C.R. McClung, and C. Weinig. 2020. Use of transcriptomic data to inform biophysical models via Bayesian networks. Ecological Modelling 429, 109086 

 

Pleban, J.R., C.R. Guadagno, D.S. Mackay, and C. Weinig, and B.E. Ewers. 2020. Rapid Chlorophyll a Fluorescence light response curves mechanistically inform photosynthesis modeling. Plant physiology 183 (2), 602-619 

 

Baker, RL, W.F. Leong, M.T. Brock, M.J. Rubin, R.J.C. Markelz, S. Welch and C. Weinig. 2019. Integrating transcriptomic network reconstruction and eQTL analyses reveals mechanistic connections between genomic architecture and Brassica rapa development. PLoS Genetics 15 (9), e1008367 

 

Salmela, M.J. and C. Weinig. 2019. The fitness benefits of genetic variation in circadian clock regulation. Current opinion in plant biology 49, 86-93 

 

Wang, DR, CR Guadagno, X Mao, DS Mackay, JR Pleban, RL Baker, and C. Weinig. 2019. A framework for genomics-informed ecophysiological modeling in plants. Journal of Experimental Botany 70 (9), 2561-2574 

 

Hubbard, C.J., B. Li, R. McMinn, M.T. Brock, L. Maignien, B.E. Ewers, and C. Weinig. 2019. The effect of rhizosphere microbes outweighs host plant genetics in reducing insect herbivory. Molecular Ecology 28 (7) 1801-1811 

 

Rubin, M.J., M.T. Brock, S.J. Davis, and C. Weinig. 2019. QTL underlying circadian clock parameters under seasonally variable field settings in Arabidopsis thaliana. G3: Genes, Genomes, Genetics 9 (4), 1131-1139 

 

Baker, R.L., W.F. Leong, S.M. Welch, and C. Weinig. 2018. Mapping and predicting non-linear Brassica rapa growth phenotypes based on Bayesian and frequentist complex trait estimation. G3: Genes, Genomes, Genetics doi.org/10.1534/g3.117.300350 

 

Guadagno, C.R., B.E. Ewers, and C. Weinig. 2018. Circadian rhythms and redox state in plants: Till stress do us part. Frontiers in Plant Science. doi: 10.3389/fpls.2018.00247 

 

Pleben, J.R., D.S. Mackay, T.L. Aston, B.E. Ewers,and C. Weinig. 2018. Phenotypic trait identification using a multimodel Bayesian method: A case study using photosynthesis in Brassica rapa genotypes. Frontiers in Plant Science. https://doi.org/10.3389/fpls.2018.00448 

 

Rubin, M.J., M.T. Brock, R.L. Baker, S. Wilcox, K. Anderson, S.J. Davis, and C. Weinig. 2018. Circadian rhythms are associated with shoot architecture in natural settings. New Phytologist. https://doi.org/10.1111/nph.15162 

 

Salmela M.J., R.L. McMinn, C.R. Guadagno, B.E. Ewers BE, and C. Weinig. 2018. Circadian rhythms and reproductive phenology covary in a natural plant population. J Biol Rhythms. doi: 10.1177/0748730418764525 

 

Yarkhunova, Y., C.R. Guadagno, M.J. Rubin, S.J. Davis, B.E.Ewers, and C. Weinig. 2018. Circadian rhythms are associated with variation in photosystem II function and photoprotective mechanisms. Plant Cell and Environment. https://doi.org/10.1111/pce.13216