Complexity Not So Costly After All: Moderately Complex Plants and Animals Can Be Better Equipped to Adapt
ScienceDaily (Sep. 27, 2010) — The more complex a plant or animal, the more difficulty it should have adapting to changes in the environment. That's been a maxim of evolutionary theory since biologist Ronald Fisher put forth the idea in 1930.
Hummingbird and an orchid. (Cr[edit: iStockphoto)
But if that tenet is true, how do you explain all the well-adapted, complex organisms -- from orchids to bower birds to humans -- in this world?
This "cost of complexity" conundrum puzzles biologists and offers ammunition to proponents of intelligent design, who hold that such intricacy could arise only through the efforts of a divine designer [NOTA DESTE BLOGGER: A TDI não propõe isso, mas tão-somente que sinais de inteligência são empiricamente detectados na natureza.], not through natural selection.
A new analysis by Jianzhi "George" Zhang and coworkers at the University of Michigan and Taiwan's National Health Research Institutes reveals flaws in the models from which the cost of complexity idea arose and shows that complexity can, indeed, develop through evolutionary processes. In fact, a moderate amount of complexity best equips organisms to adapt to environmental change, the research suggests. The findings will be published online in the Proceedings of the National Academy of Sciences.
The study focused on a genetic phenomenon called pleiotropy, in which a single gene affects more than one trait. Examples of pleiotropy are well known in certain human diseases, and the effect also has been documented in experimental animals such as fruit flies. Biologists also recognize its importance in development, aging and many evolutionary processes. However, pleiotropy is difficult to measure, and its general patterns are poorly understood, said Zhang, a professor of ecology and evolutionary biology.
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Read more here/Leia mais aqui: Science Daily
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Genomic patterns of pleiotropy and the evolution of complexity
Zhi Wang a,1, Ben-Yang Liao b, and Jianzhi Zhang a,2
-Author Affiliations
aDepartment of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109; and
bDivision of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Miaoli County 350, Taiwan, Republic of China
↵1Present address: Sage Bionetworks, Seattle, WA 98109.
Edited by Günter P. Wagner, Yale University, New Haven, CT, and accepted by the Editorial Board August 31, 2010 (received for review April 6, 2010)
Abstract
Pleiotropy refers to the phenomenon of a single mutation or gene affecting multiple distinct phenotypic traits and has broad implications in many areas of biology. Due to its central importance, pleiotropy has also been extensively modeled, albeit with virtually no empirical basis. Analyzing phenotypes of large numbers of yeast, nematode, and mouse mutants, we here describe the genomic patterns of pleiotropy. We show that the fraction of traits altered appreciably by the deletion of a gene is minute for most genes and the gene–trait relationship is highly modular. The standardized size of the phenotypic effect of a gene on a trait is approximately normally distributed with variable SDs for different genes, which gives rise to the surprising observation of a larger per-trait effect for genes affecting more traits. This scaling property counteracts the pleiotropy-associated reduction in adaptation rate (i.e., the “cost of complexity”) in a nonlinear fashion, resulting in the highest adaptation rate for organisms of intermediate complexity rather than low complexity. Intriguingly, the observed scaling exponent falls in a narrow range that maximizes the optimal complexity. Together, the genome-wide observations of overall low pleiotropy, high modularity, and larger per-trait effects from genes of higher pleiotropy necessitate major revisions of theoretical models of pleiotropy and suggest that pleiotropy has not only allowed but also promoted the evolution of complexity.
genetics, adaptation, modularity, yeast, phenotype
Footnotes
2To whom correspondence should be addressed. E-mail: jianzhi@umich.edu.
Author contributions: Z.W. and J.Z. designed research; Z.W. and B.-Y.L. performed research; Z.W. and J.Z. analyzed data; and Z.W. and J.Z. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission. G.P.W. is a guest editor invited by the Editorial Board.
This article contains supporting information online at
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PDF gratuito deste artigo aqui.
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NOTA DESTE BLOGGER:
Segundo Popper, uma teoria somente é científica se for submetida ao teste de falseamento. Aparentemente, Wang et al, falseram a tese de complexidade do Design Inteligente.
Um momento, devagar com o andor, pois a tese de complexidade que os teóricos e proponentes da TDI defendem é a complexidade irredutível de sistemas bióticos.
Um momento, devagar com o andor, pois a tese de complexidade que os teóricos e proponentes da TDI defendem é a complexidade irredutível de sistemas bióticos.
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