进化中的时间和信息

W. Ewert, W. Dembski, A. Gauger, R. Marks
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摘要

威尔夫和埃文斯在最近的一篇论文中认为,进化有足够的时间发生。他们基于一个数学模型,在这个模型中,有益的突变同时独立地积累,从而允许在相对较短的时间内进化出需要大量突变的变化。因为变化是独立地、并行地而不是顺序地发展的,所以它们的模型是以对数而不是指数方式扩展的。然而,由于两个主要原因,这种方法并不能准确地反映生物进化。首先,在他们的模型中有隐含的信息源,包括相当于一个高度知情的先知,预言什么时候突变是“正确的”,从而加速了进化过程的搜索。相比之下,自然选择无法获得关于特定突变的未来利益的信息,或者在全球适应性景观中特定突变相对于特定目标的位置。它只能根据突变对当地适应性景观的当前影响来评估突变。因此,这个神谕的存在使得他们的模型从根本上不同于通过适应度空间进行的真实生物搜索。威尔夫和埃文斯还做了一些不切实际的生物学假设,这些假设实际上简化了搜索。他们假设有益突变之间没有上位性,位点之间没有连锁,种群规模和碱基突变率不切实际,从而增加了待搜索的有益突变库。他们忽略了遗传漂变对固定概率的影响以及同时积累有害突变的负面影响。最后,在他们的模型中,他们用一个字母表示每个基因位点。通过这样做,他们忽略了实际基因座的巨大序列复杂性(通常是数百或数千个核苷酸长),并且大大简化了对功能变体的搜索。以类似的方式,他们假设每一次进化“进步”只需要改变一个基因座,尽管有明确的证据表明,大多数生物功能是多个基因产物共同作用的产物。忽略这些生物现实会给他们的模型注入相当多的活跃信息,并简化模型的进化过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time and Information in Evolution
Wilf and Ewens argue in a recent paper that there is plenty of time for evolution to occur. They base this claim on a mathematical model in which beneficial mutations accumulate simultaneously and independently, thus allowing changes that require a large number of mutations to evolve over comparatively short time periods. Because changes evolve independently and in parallel rather than sequentially, their model scales logarithmically rather than exponentially. This approach does not accurately reflect biological evolution, however, for two main reasons. First, within their model are implicit information sources, including the equivalent of a highly informed oracle that prophesies when a mutation is “correct,” thus accelerating the search by the evolutionary process. Natural selection, in contrast, does not have access to information about future benefits of a particular mutation, or where in the global fitness landscape a particular mutation is relative to a particular target. It can only assess mutations based on their current effect on fitness in the local fitness landscape. Thus the presence of this oracle makes their model radically different from a real biological search through fitness space. Wilf and Ewens also make unrealistic biological assumptions that, in effect, simplify the search. They assume no epistasis between beneficial mutations, no linkage between loci, and an unrealistic population size and base mutation rate, thus increasing the pool of beneficial mutations to be searched. They neglect the effects of genetic drift on the probability of fixation and the negative effects of simultaneously accumulating deleterious mutations. Finally, in their model they represent each genetic locus as a single letter. By doing so, they ignore the enormous sequence complexity of actual genetic loci (typically hundreds or thousands of nucleotides long), and vastly oversimplify the search for functional variants. In similar fashion, they assume that each evolutionary “advance” requires a change to just one locus, despite the clear evidence that most biological functions are the product of multiple gene products working together. Ignoring these biological realities infuses considerable active information into their model and eases the model’s evolutionary process.
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