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Multivariate quantitative genetics provides a powerful framework for understanding patterns and processes of phenotypic evolution. Quantitative genetics parameters, like trait heritability or the G-matrix for sets of traits, can be used to predict evolutionary response or to understand the evolutionary history of a population. These population-level approaches have proven to be extremely successful, but the underlying genetics of multivariate variation and evolutionary change typically remain a black box. Establishing a deeper empirical understanding of how individual genetic effects lead to genetic (co)variation is then crucial to our understanding of the evolutionary process. To delve into this black box, we exploit an experimental population of mice composed from lineages derived by artificial selection. We develop an approach to estimate the multivariate effect of loci and characterize these vectors of effects in terms of their magnitude and alignment with the direction of evolutionary divergence. Using these estimates, we reconstruct the traits in the ancestral populations and quantify how much of the divergence is due to genetic effects. Finally, we also use these vectors to decompose patterns of genetic covariation and examine the relationship between these components and the corresponding distribution of pleiotropic effects. We find that additive effects are much larger than dominance effects and are more closely aligned with the direction of selection and divergence, with larger effects being more aligned than smaller effects. Pleiotropic effects are highly variable but are, on average, modular. These results are consistent with pleiotropy being partly shaped by selection while reflecting underlying developmental constraints.
This article was published in the following journal.
Name: The Journal of heredity
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A set of techniques used when variation in several variables has to be studied simultaneously. In statistics, multivariate analysis is interpreted as any analytic method that allows simultaneous study of two or more dependent variables.
Contiguous large-scale (1000-400,000 basepairs) differences in the genomic DNA between individuals, due to SEQUENCE DELETION; SEQUENCE INSERTION; or SEQUENCE INVERSION.
The interdisciplinary science that studies evolutionary biology, including the origin and evolution of the major elements required for life, their processing in the interstellar medium and in protostellar systems. This field also includes the study of chemical evolution and the subsequent interactions between evolving biota and planetary evolution as well as the field of biology that deals with the study of extraterrestrial life.
Evolution at the molecular level of DNA sequences and proteins. (Rieger et al., Glossary of Genetics: Classical and Molecular, 5th ed)
A method of analyzing the variation in utilization of health care in small geographic or demographic areas. It often studies, for example, the usage rates for a given service or procedure in several small areas, documenting the variation among the areas. By comparing high- and low-use areas, the analysis attempts to determine whether there is a pattern to such use and to identify variables that are associated with and contribute to the variation.