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UNDERSTANDING THE EVOLUTION AND STABILITY OF THE G‐MATRIX
Author(s) -
Arnold Stevan J.,
Bürger Reinhard,
Hohenlohe Paul A.,
Ajie Beverley C.,
Jones Adam G.
Publication year - 2008
Publication title -
evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.84
H-Index - 199
eISSN - 1558-5646
pISSN - 0014-3820
DOI - 10.1111/j.1558-5646.2008.00472.x
Subject(s) - selection (genetic algorithm) , stability (learning theory) , biology , matrix (chemical analysis) , inheritance (genetic algorithm) , evolutionary biology , centrality , biological system , statistical physics , computer science , genetics , mathematics , statistics , artificial intelligence , machine learning , physics , materials science , composite material , gene
The G ‐matrix summarizes the inheritance of multiple, phenotypic traits. The stability and evolution of this matrix are important issues because they affect our ability to predict how the phenotypic traits evolve by selection and drift. Despite the centrality of these issues, comparative, experimental, and analytical approaches to understanding the stability and evolution of the G ‐matrix have met with limited success. Nevertheless, empirical studies often find that certain structural features of the matrix are remarkably constant, suggesting that persistent selection regimes or other factors promote stability. On the theoretical side, no one has been able to derive equations that would relate stability of the G ‐matrix to selection regimes, population size, migration, or to the details of genetic architecture. Recent simulation studies of evolving G ‐matrices offer solutions to some of these problems, as well as a deeper, synthetic understanding of both the G ‐matrix and adaptive radiations.