Dataset: Metadata for studies from meta-analysis investigating covariance between genetic and environmental (CovGE) effects in phenotypic results

Final no updates expectedDOI: 10.26008/1912/bco-dmo.877414.1Version 1 (2022-08-09)Dataset Type:model results

Principal Investigator: Katie Lotterhos (Northeastern University)

Co-Principal Investigator: Geoffrey C. Trussell (Northeastern University)

Contact: Molly Albecker (Northeastern University)

BCO-DMO Data Manager: Taylor Heyl (Woods Hole Oceanographic Institution)

BCO-DMO Data Manager: Shannon Rauch (Woods Hole Oceanographic Institution)


Project: RCN: Evolution in Changing Seas (RCN ECS)


Abstract

Covariance can exist between the genetic and environmental influences on phenotype (CovGE) and can have an important role in ecological and evolutionary processes in nature and population responses to environmental change. CovGE is commonly called countergradient variation (CnGV; negative CovGE)or cogradient variation (CoGV; positive CovGE)and has been recognized in classic studies that have established several long-standing hypotheses about CnGV and CoGV. For instance, it is hypothesized that ...

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We searched the Web of Science database for experimental studies that evaluated differences in phenotypic responses across different genotypes and environments. We conducted the initial search on June 24, 2019. We used the search terms, ("cogradient variation" OR "countergradient variation" OR" cogradient selection" OR "countergradient selection" OR "co-gradient variation" OR "counter-gradient variation" OR "co-gradient selection" OR "counter-gradient selection") OR ("GxE" OR "genotype by environment" or "gene by environment") OR ("nonadaptive plast*" OR "non-adaptive plast*" OR "maladaptive plast*" OR "adaptive plast*") OR ("phenotypic plast*" AND "adapt*") AND ("common garden" OR "reciprocal transplant"). Initial searches returned approximately 5,900 hits. Results were further refined by including only those articles within Web of Science categories that related to ecology, evolution, or any ecological or evolutionary subdiscipline (e.g., papers categorized as engineering or biomedical were excluded). Refining reduced the search results to 4,458 studies. We also added studies that were included in previously published meta-analyses by Murren et al. (2015) and Hereford (2009) for screening.

After compiling studies, we measured CovGE and GxE magnitude on phenotypic data. More methods can be found in the manuscript published in Ecology Letters in 2022.

See Related Dataset Albecker et al. (2022) for model code.


Related Datasets

IsRelatedTo

Dataset: CovGE meta-analysis methodology comparison
Relationship Description: These "Metadata from a meta-analysis on CovGE in phenotypic results" (doi:10.26008/1912/bco-dmo.877414.1) data were used in the "CovGE MetaAnalysis" (doi:
Albecker, M., Lotterhos, K., Trussell, G. C., Bittar, T. (2024) Model code and output for a comparison of methods for meta-analysis investigating covariance between genetic and environmental (CovGE) effects in phenotypic results. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2024-08-06 doi:10.26008/1912/bco-dmo.934896.1
IsRelatedTo

Dataset: Results of meta-analysis on CovGE in phenotypic results
Albecker, M., Trussell, G., Lotterhos, K. (2022) Results from a meta-analysis investigating covariance between genetic and environmental (CovGE) effects in phenotypic results in published literature. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2022-10-14 doi:10.26008/1912/bco-dmo.877425.1
IsRelatedTo

Dataset: Power output results
Albecker, M., Trussell, G., Lotterhos, K. (2022) Results using simulated data used to conduct power analyses. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2022-10-14 doi:10.26008/1912/bco-dmo.877456.1
Software

Dataset: https://doi.org/10.5281/zenodo.6470547
Albecker, M. A., Casalott, &amp; Lotterhos, K. (2022). <i>RCN-ECS/CnGV: Archived CGV data and code - April 2022</i> (Version 1.0) [Computer software]. Zenodo. https://doi.org/10.5281/ZENODO.6470547

Related Publications

Results

Albecker, M. A., Trussell, G. C., & Lotterhos, K. E. (2022). A novel analytical framework to quantify co‐gradient and countergradient variation. Ecology Letters, 25(6), 1521–1533. Portico. https://doi.org/10.1111/ele.14020