达尔文自然选择学说的核心内容是“适者生存”。毋庸置疑,自然选择偏爱最合适的生物体,但一直以来进化生物学家并不清楚,从长远来看这种选择是否也具有最优性。美国科学家近日发展了一种新理论认为,选择出的生命可能并不一定是最佳的。相关论文发表在《公共科学图书馆 计算生物学》(PLoS Computational Biology)上。
遗传突变为自然选择创造了赖以行事的原料。突变的短期命运相当清楚——制造更合适的生物体的突变能一代代持续下去,有害的突变更易于随着生物体消亡;突变的长期结果则并没有被进化生物学家很好地理解。新的研究表明,短期有利的选择可能会阻碍长期的进化。
美国德州大学奥斯汀分校的Matthew Cowperthwaite和Lauren Ancel Meyers领导研究小组创建了由突变和自然选择进化而来的RNA分子的计算机模型。RNA在许多关键的生命过程扮演重要角色,是流感、HIV等病毒的遗传材料。
模型显示,最佳生物体的进化往往需要一段长的相互作用的突变序列,每个突变都是偶然产生,并能在自然选择中存活下来。Cowperthwaite解释说:“一些特征很容易进化——它们由突变的许多不同联合构成;另外一些特征则很难进化——它们由不太可能的遗传‘处方’构成。进化选择了容易的,即使它们并不是最好的。”
研究人员分析了大量不同物种的RNA分子,结果表明,生命确实由“容易”的特征所支配,或许以牺牲最好的为代价。(生物谷Bioon.com)
生物谷推荐原始出处:
PLoS Computational Biology,doi:10.1371/journal.pcbi.1000110,Matthew C. Cowperthwaite,Lauren Ancel Meyers
The Ascent of the Abundant: How Mutational Networks Constrain Evolution
Matthew C. Cowperthwaite1*, Evan P. Economo2, William R. Harcombe2, Eric L. Miller2, Lauren Ancel Meyers1,2
1 Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, United States of America2 Section for Integrative Biology, University of Texas at Austin, Austin, Texas, United States of America
Abstract
Evolution by natural selection is fundamentally shaped by the fitness landscapes in which it occurs. Yet fitness landscapes are vast and complex, and thus we know relatively little about the long-range constraints they impose on evolutionary dynamics. Here, we exhaustively survey the structural landscapes of RNA molecules of lengths 12 to 18 nucleotides, and develop a network model to describe the relationship between sequence and structure. We find that phenotype abundance—the number of genotypes producing a particular phenotype—varies in a predictable manner and critically influences evolutionary dynamics. A study of naturally occurring functional RNA molecules using a new structural statistic suggests that these molecules are biased toward abundant phenotypes. This supports an “ascent of the abundant” hypothesis, in which evolution yields abundant phenotypes even when they are not the most fit.