TY - JOUR
T1 - Genetic and environmental factors affecting cryptic variations in gene regulatory networks
AU - Iwasaki, Watal M.
AU - Tsuda, Masaki E.
AU - Kawata, Masakado
N1 - Funding Information:
We are grateful to Takashi Makino and Yukari Ohno for their valuable comments on this study. We thank Satoshi Kato, Wakako Yamaguchi, Mitsuhiko Sato, and Satoshi Tamate for their assistance with the maintenance of the computer environment. WMI is supported by a Japan Society for the Promotion of Science (JSPS) Research Fellowship. This research was supported by a Grant-in-Aid for JSPS Fellows (10J56112) to WMI and partially by the Global COE Program “Center for ecosystem management adapting to global change” (J03) of the Ministry of Education, Culture, Sports, Science and Technology of Japan granted to MK.
PY - 2013
Y1 - 2013
N2 - Background: Cryptic genetic variation (CGV) is considered to facilitate phenotypic evolution by producing visible variations in response to changes in the internal and/or external environment. Several mechanisms enabling the accumulation and release of CGVs have been proposed. In this study, we focused on gene regulatory networks (GRNs) as an important mechanism for producing CGVs, and examined how interactions between GRNs and the environment influence the number of CGVs by using individual-based simulations. Results: Populations of GRNs were allowed to evolve under various stabilizing selections, and we then measured the number of genetic and phenotypic variations that had arisen. Our results showed that CGVs were not depleted irrespective of the strength of the stabilizing selection for each phenotype, whereas the visible fraction of genetic variation in a population decreased with increasing strength of selection. On the other hand, increasing the number of different environments that individuals encountered within their lifetime (i.e., entailing plastic responses to multiple environments) suppressed the accumulation of CGVs, whereas the GRNs with more genes and interactions were favored in such heterogeneous environments. Conclusions: Given the findings that the number of CGVs in a population was largely determined by the size (order) of GRNs, we propose that expansion of GRNs and adaptation to novel environments are mutually facilitating and sustainable sources of evolvability and hence the origins of biological diversity and complexity.
AB - Background: Cryptic genetic variation (CGV) is considered to facilitate phenotypic evolution by producing visible variations in response to changes in the internal and/or external environment. Several mechanisms enabling the accumulation and release of CGVs have been proposed. In this study, we focused on gene regulatory networks (GRNs) as an important mechanism for producing CGVs, and examined how interactions between GRNs and the environment influence the number of CGVs by using individual-based simulations. Results: Populations of GRNs were allowed to evolve under various stabilizing selections, and we then measured the number of genetic and phenotypic variations that had arisen. Our results showed that CGVs were not depleted irrespective of the strength of the stabilizing selection for each phenotype, whereas the visible fraction of genetic variation in a population decreased with increasing strength of selection. On the other hand, increasing the number of different environments that individuals encountered within their lifetime (i.e., entailing plastic responses to multiple environments) suppressed the accumulation of CGVs, whereas the GRNs with more genes and interactions were favored in such heterogeneous environments. Conclusions: Given the findings that the number of CGVs in a population was largely determined by the size (order) of GRNs, we propose that expansion of GRNs and adaptation to novel environments are mutually facilitating and sustainable sources of evolvability and hence the origins of biological diversity and complexity.
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U2 - 10.1186/1471-2148-13-91
DO - 10.1186/1471-2148-13-91
M3 - Article
C2 - 23622056
AN - SCOPUS:84876664542
VL - 13
JO - BMC Evolutionary Biology
JF - BMC Evolutionary Biology
SN - 1471-2148
IS - 1
M1 - 91
ER -