Genome complexity, robustness and genetic interactions in digital organisms

被引:194
作者
Lenski, RE [1 ]
Ofria, C
Collier, TC
Adami, C
机构
[1] Michigan State Univ, Ctr Microbial Ecol, E Lansing, MI 48824 USA
[2] CALTECH, Kellogg Radiat Lab, Pasadena, CA 91125 USA
[3] Univ Calif Los Angeles, Dept Organism Biol Ecol & Evolut, Los Angeles, CA 90095 USA
关键词
D O I
10.1038/23245
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Digital organisms are computer programs that self-replicate, mutate and adapt by natural selection(1-3). They offer an opportunity to test generalizations about living systems that may extend beyond the organic life that biologists usually study. Here we have generated two classes of digital organism: simple programs selected solely for rapid replication, and complex programs selected to perform mathematical operations that accelerate replication through a set of defined 'metabolic' rewards., To examine the differences in their genetic architecture, we introduced millions of single and multiple mutations into each organism and measured the effects on the organism's fitness. The complex organisms are more robust than the simple ones with respect to the average effects of single mutations. Interactions among mutations are common and usually yield higher fitness than predicted from the component mutations assuming multiplicative effects; such interactions are especially important in the complex organisms. Frequent interactions among mutations have also been seen in bacteria, fungi and fruitflies(4-6). Our findings support the view that interactions are a general feature of genetic systems(7-9).
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页码:661 / 664
页数:4
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