Effect of regulatory architecture on broad versus narrow sense heritability.

PLoS Comput Biol

Centre for Integrative Genetics (CIGENE), Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, Ås, Norway.

Published: March 2014

AI Article Synopsis

  • Additive genetic variance (VA) and total genetic variance (VG) are important concepts in genetics that influence studies in various biological fields.
  • The variation in VA/VG ratios observed in line-cross experiments is not well understood, and this research explores how these ratios change based on the regulatory architecture of genotype-to-phenotype (GP) maps.
  • Through the examination of five dynamic biological models, the study finds that systems with positive feedback and cyclic dynamics produce lower VA/VG ratios, indicating that some regulatory architectures create clearer genotype-to-phenotype relationships, while others produce more complex interactions.

Article Abstract

Additive genetic variance (VA ) and total genetic variance (VG ) are core concepts in biomedical, evolutionary and production-biology genetics. What determines the large variation in reported VA /VG ratios from line-cross experiments is not well understood. Here we report how the VA /VG ratio, and thus the ratio between narrow and broad sense heritability (h(2) /H(2) ), varies as a function of the regulatory architecture underlying genotype-to-phenotype (GP) maps. We studied five dynamic models (of the cAMP pathway, the glycolysis, the circadian rhythms, the cell cycle, and heart cell dynamics). We assumed genetic variation to be reflected in model parameters and extracted phenotypes summarizing the system dynamics. Even when imposing purely linear genotype to parameter maps and no environmental variation, we observed quite low VA /VG ratios. In particular, systems with positive feedback and cyclic dynamics gave more non-monotone genotype-phenotype maps and much lower VA /VG ratios than those without. The results show that some regulatory architectures consistently maintain a transparent genotype-to-phenotype relationship, whereas other architectures generate more subtle patterns. Our approach can be used to elucidate these relationships across a whole range of biological systems in a systematic fashion.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3649986PMC
http://dx.doi.org/10.1371/journal.pcbi.1003053DOI Listing

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