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Using genomic prediction to detect microevolutionary change of a quantitative trait

Cite this dataset

Slate, Jon (2022). Using genomic prediction to detect microevolutionary change of a quantitative trait [Dataset]. Dryad.


Detecting microevolutionary responses to natural selection by observing temporal changes in individual breeding values is challenging. The collection of suitable datasets can take many years and disentangling the contributions of the environment and genetics to phenotypic change is not trivial. Furthermore, pedigree-based methods of obtaining individual breeding values have known biases. Here, we apply a genomic prediction approach to estimate breeding values of adult weight in a 35-year dataset of Soay sheep (Ovis aries). Comparisons are made with a traditional pedigree-based approach. During the study period adult body weight decreased, but the underlying genetic component of body weight increased, at a rate that is unlikely to be attributable to genetic drift. Thus cryptic microevolution of greater adult body weight has probably occurred. Genomic and pedigree-based approaches gave largely consistent results. Thus, using genomic prediction to study microevolution in wild populations can remove the requirement for pedigree data, potentially opening up new study systems for similar research.


The data includes a combination of field data and genomic and pedigree-derived estimated breeding values (GEBVs/PEBVs) of weight, collected from a wild population of Soay sheep (Ovis aries).

R code to reproduce the results in the paper is also included.

Usage notes

There are no missing data, although users are encouraged to contact the authors for further information about the biology of the study system.


Natural Environment Research Council, Award: NE/M002896/1

European Research Council, Award: Wild Evolutionary Genomics