Analysis of information sources in references of the Wikipedia article "Bias in the introduction of variation" in English language version.
The process of adaptation occurs on two timescales. In the short term, natural selection merely sorts the variation already present in a population, whereas in the longer term genotypes quite different from any that were initially present evolve through the cumulation of new mutations. The first process is described by the mathematical theory of population genetics. However, this theory begins by defining a fixed set of genotypes and cannot provide a satisfactory analysis of the second process because it does not permit any genuinely new type to arise.
Almost every theoretical model in population genetics can be classified into one of two major types. In one type of model, mutations with stipulated selective effects are assumed to be present in the population as an initial condition ... The second major type of models does allow mutations to occur at random intervals of time, but the mutations are assumed to be selectively neutral or nearly neutral.
in evolution, selection may decide the winner of a given game but development non-randomly defines the players (p. 665)
Developmental biologists variously stress: (1) how indirect any genetic control is during certain stages of epigenesis; (2) that the system determines by downward causation which genomic constituents are stored in unexpressed form versus those which are expressed in the phenotype; (3) that bias in the introduction of phenotypic variation may be more important to directional phenotypic evolution than sorting by selection.
Since the classic work of Fisher (1930) and Haldane (1932) established the weakness of directional mutation as compared to selection, it has been generally held that directional bias in variation will not produce evolutionary change in the face of opposing selection. This position deserves reexamination.
Some analogies may be helpful here. In explaining why certain traits predominate in nature rather than conceivable others, evolutionary biologists act a little like physicists who study stable states in thermodynamic systems or astronomers who study spatial arrangements of stars and galaxies' In each case, the researcher examines the products of historical processes that unfold over centuries due to the interactions of particular entities. The products of these processes are explicable, sometimes even predictable, without a detailed knowledge of each entity's individual history. This is so because, for a given set of conditions, a large number of distinct individual histories tend to converge on a small number of stable states. For example, the observation that boulders collect in mountain valleys can be explained without knowing each boulder's precise trajectory.
what amazes me is, in how much of the current literature that [proximate-ultimate] distinction is still ignored or confused. I must have read in the last two years four or five papers and one book on development and evolution. Now development, the decoding of the genetic program, is clearly a matter of proximate causations. Evolution, equally clearly, is a matter of evolutionary causations. And yet, in all these papers and that book the two kinds of causations were hopelessly mixed up
In a wide range of taxa, mutation bias explains a non-negligible proportion of cases of parallel genetic evolution (Stern & Orgogozo 2008, Bailey et al. 2017, 2018, Stoltzfus & McCandlish 2017). For instance, an elegant study on adaptation to high altitudes in birds found parallel evolution, in part due to mutation bias at CpG sites (Storz et al. 2019). When highly beneficial mutations are under-sampled due to the existing mutational bias, other smaller-effect but more frequent mutations may fix instead. Such a pattern was observed in replicated evolving populations of bacteriophage (Sackman et al. 2017) where the mutation with the largest fitness effect was not the one that reached fixation most often, because its mutation rate was lower than that of other mutations with smaller fitness effects.
{{cite journal}}: CS1 maint: numeric names: authors list (link){{cite journal}}: CS1 maint: numeric names: authors list (link)The process of adaptation occurs on two timescales. In the short term, natural selection merely sorts the variation already present in a population, whereas in the longer term genotypes quite different from any that were initially present evolve through the cumulation of new mutations. The first process is described by the mathematical theory of population genetics. However, this theory begins by defining a fixed set of genotypes and cannot provide a satisfactory analysis of the second process because it does not permit any genuinely new type to arise.
in evolution, selection may decide the winner of a given game but development non-randomly defines the players (p. 665)
Developmental biologists variously stress: (1) how indirect any genetic control is during certain stages of epigenesis; (2) that the system determines by downward causation which genomic constituents are stored in unexpressed form versus those which are expressed in the phenotype; (3) that bias in the introduction of phenotypic variation may be more important to directional phenotypic evolution than sorting by selection.
In a wide range of taxa, mutation bias explains a non-negligible proportion of cases of parallel genetic evolution (Stern & Orgogozo 2008, Bailey et al. 2017, 2018, Stoltzfus & McCandlish 2017). For instance, an elegant study on adaptation to high altitudes in birds found parallel evolution, in part due to mutation bias at CpG sites (Storz et al. 2019). When highly beneficial mutations are under-sampled due to the existing mutational bias, other smaller-effect but more frequent mutations may fix instead. Such a pattern was observed in replicated evolving populations of bacteriophage (Sackman et al. 2017) where the mutation with the largest fitness effect was not the one that reached fixation most often, because its mutation rate was lower than that of other mutations with smaller fitness effects.
The process of adaptation occurs on two timescales. In the short term, natural selection merely sorts the variation already present in a population, whereas in the longer term genotypes quite different from any that were initially present evolve through the cumulation of new mutations. The first process is described by the mathematical theory of population genetics. However, this theory begins by defining a fixed set of genotypes and cannot provide a satisfactory analysis of the second process because it does not permit any genuinely new type to arise.
in evolution, selection may decide the winner of a given game but development non-randomly defines the players (p. 665)
In a wide range of taxa, mutation bias explains a non-negligible proportion of cases of parallel genetic evolution (Stern & Orgogozo 2008, Bailey et al. 2017, 2018, Stoltzfus & McCandlish 2017). For instance, an elegant study on adaptation to high altitudes in birds found parallel evolution, in part due to mutation bias at CpG sites (Storz et al. 2019). When highly beneficial mutations are under-sampled due to the existing mutational bias, other smaller-effect but more frequent mutations may fix instead. Such a pattern was observed in replicated evolving populations of bacteriophage (Sackman et al. 2017) where the mutation with the largest fitness effect was not the one that reached fixation most often, because its mutation rate was lower than that of other mutations with smaller fitness effects.
{{cite journal}}: CS1 maint: numeric names: authors list (link){{cite journal}}: CS1 maint: numeric names: authors list (link)In a wide range of taxa, mutation bias explains a non-negligible proportion of cases of parallel genetic evolution (Stern & Orgogozo 2008, Bailey et al. 2017, 2018, Stoltzfus & McCandlish 2017). For instance, an elegant study on adaptation to high altitudes in birds found parallel evolution, in part due to mutation bias at CpG sites (Storz et al. 2019). When highly beneficial mutations are under-sampled due to the existing mutational bias, other smaller-effect but more frequent mutations may fix instead. Such a pattern was observed in replicated evolving populations of bacteriophage (Sackman et al. 2017) where the mutation with the largest fitness effect was not the one that reached fixation most often, because its mutation rate was lower than that of other mutations with smaller fitness effects.
{{cite journal}}: CS1 maint: numeric names: authors list (link){{cite journal}}: CS1 maint: numeric names: authors list (link)If correct, Behe's calculations would at a stroke confound generations of mathematical geneticists, who have repeatedly shown that evolutionary rates are not limited by mutation. Single-handedly, Behe is taking on Ronald Fisher, Sewall Wright, J.B.S. Haldane, Theodosius Dobzhansky, Richard Lewontin, John Maynard Smith and hundreds of their talented co-workers and intellectual descendants. Notwithstanding the inconvenient existence of dogs, cabbages and pouter pigeons, the entire corpus of mathematical genetics, from 1930 to today, is flat wrong. Michael Behe, the disowned biochemist of Lehigh University, is the only one who has done his sums right. You think? The best way to find out is for Behe to submit a mathematical paper to The Journal of Theoretical Biology, say, or The American Naturalist, whose editors would send it to qualified referees.
The process of adaptation occurs on two timescales. In the short term, natural selection merely sorts the variation already present in a population, whereas in the longer term genotypes quite different from any that were initially present evolve through the cumulation of new mutations. The first process is described by the mathematical theory of population genetics. However, this theory begins by defining a fixed set of genotypes and cannot provide a satisfactory analysis of the second process because it does not permit any genuinely new type to arise.
Almost every theoretical model in population genetics can be classified into one of two major types. In one type of model, mutations with stipulated selective effects are assumed to be present in the population as an initial condition ... The second major type of models does allow mutations to occur at random intervals of time, but the mutations are assumed to be selectively neutral or nearly neutral.
in evolution, selection may decide the winner of a given game but development non-randomly defines the players (p. 665)
Developmental biologists variously stress: (1) how indirect any genetic control is during certain stages of epigenesis; (2) that the system determines by downward causation which genomic constituents are stored in unexpressed form versus those which are expressed in the phenotype; (3) that bias in the introduction of phenotypic variation may be more important to directional phenotypic evolution than sorting by selection.
Since the classic work of Fisher (1930) and Haldane (1932) established the weakness of directional mutation as compared to selection, it has been generally held that directional bias in variation will not produce evolutionary change in the face of opposing selection. This position deserves reexamination.
Some analogies may be helpful here. In explaining why certain traits predominate in nature rather than conceivable others, evolutionary biologists act a little like physicists who study stable states in thermodynamic systems or astronomers who study spatial arrangements of stars and galaxies' In each case, the researcher examines the products of historical processes that unfold over centuries due to the interactions of particular entities. The products of these processes are explicable, sometimes even predictable, without a detailed knowledge of each entity's individual history. This is so because, for a given set of conditions, a large number of distinct individual histories tend to converge on a small number of stable states. For example, the observation that boulders collect in mountain valleys can be explained without knowing each boulder's precise trajectory.
what amazes me is, in how much of the current literature that [proximate-ultimate] distinction is still ignored or confused. I must have read in the last two years four or five papers and one book on development and evolution. Now development, the decoding of the genetic program, is clearly a matter of proximate causations. Evolution, equally clearly, is a matter of evolutionary causations. And yet, in all these papers and that book the two kinds of causations were hopelessly mixed up