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我们能从等位基因频率中多好地推断选择益处和突变率?

How Well Can We Infer Selection Benefits and Mutation Rates from Allele Frequencies?

作者信息

Soriano Jonathan, Marzen Sarah

机构信息

W. M. Keck Science Department, Pitzer, Scripps, and Claremont McKenna College, Claremont, CA 91711, USA.

出版信息

Entropy (Basel). 2023 Apr 4;25(4):615. doi: 10.3390/e25040615.

DOI:10.3390/e25040615
PMID:37190403
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10137336/
Abstract

Experimentalists observe allele frequency distributions and try to infer mutation rates and selection coefficients. How easy is this? We calculate limits to their ability in the context of the Wright-Fisher model by first finding the maximal amount of information that can be acquired using allele frequencies about the mutation rate and selection coefficient- at least 2 bits per allele- and then by finding how the organisms would have shaped their mutation rates and selection coefficients so as to maximize the information transfer.

摘要

实验人员观察等位基因频率分布,并试图推断突变率和选择系数。这有多容易呢?我们在赖特 - 费希尔模型的背景下计算了他们的能力极限,首先通过找到利用等位基因频率可获取的关于突变率和选择系数的最大信息量——每个等位基因至少2比特,然后通过研究生物体如何塑造其突变率和选择系数以最大化信息传递。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc4/10137336/b7df49527c30/entropy-25-00615-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc4/10137336/2743dc1501fa/entropy-25-00615-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc4/10137336/1623419103b5/entropy-25-00615-g0A2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc4/10137336/290ce53701ff/entropy-25-00615-g0A3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc4/10137336/e255cab57d5a/entropy-25-00615-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc4/10137336/d97a26a8b901/entropy-25-00615-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc4/10137336/b7df49527c30/entropy-25-00615-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc4/10137336/2743dc1501fa/entropy-25-00615-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc4/10137336/1623419103b5/entropy-25-00615-g0A2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc4/10137336/290ce53701ff/entropy-25-00615-g0A3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc4/10137336/e255cab57d5a/entropy-25-00615-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc4/10137336/d97a26a8b901/entropy-25-00615-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc4/10137336/b7df49527c30/entropy-25-00615-g003.jpg

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本文引用的文献

1
Accumulation and maintenance of information in evolution.信息在进化中的积累和保持。
Proc Natl Acad Sci U S A. 2022 Sep 6;119(36):e2123152119. doi: 10.1073/pnas.2123152119. Epub 2022 Aug 29.
2
Optimized bacteria are environmental prediction engines.优化后的细菌是环境预测引擎。
Phys Rev E. 2018 Jul;98(1-1):012408. doi: 10.1103/PhysRevE.98.012408.
3
Bayesian Inference of Natural Selection from Allele Frequency Time Series.基于等位基因频率时间序列的自然选择贝叶斯推断
Genetics. 2016 May;203(1):493-511. doi: 10.1534/genetics.116.187278. Epub 2016 Mar 23.
4
Time resolution dependence of information measures for spiking neurons: scaling and universality.脉冲神经元信息度量的时间分辨率依赖性:标度与普遍性
Front Comput Neurosci. 2015 Aug 28;9:105. doi: 10.3389/fncom.2015.00105. eCollection 2015.
5
Systems biology. Accurate information transmission through dynamic biochemical signaling networks.系统生物学。通过动态生化信号网络进行准确的信息传递。
Science. 2014 Dec 12;346(6215):1370-3. doi: 10.1126/science.1254933.
6
The empirical codon mutation matrix as a communication channel.经验密码子突变矩阵作为一种通讯信道。
BMC Bioinformatics. 2014 Mar 22;15:80. doi: 10.1186/1471-2105-15-80.
7
Statistical mechanics of Monod-Wyman-Changeux (MWC) models.莫诺-维曼-居内变换(MWC)模型的统计力学。
J Mol Biol. 2013 May 13;425(9):1433-60. doi: 10.1016/j.jmb.2013.03.013. Epub 2013 Mar 14.
8
Estimating selection coefficients in spatially structured populations from time series data of allele frequencies.从等位基因频率的时间序列数据估计空间结构群体中的选择系数。
Genetics. 2013 Mar;193(3):973-84. doi: 10.1534/genetics.112.147611. Epub 2013 Jan 10.
9
Trade-offs and constraints in allosteric sensing.变构感应中的权衡与约束。
PLoS Comput Biol. 2011 Nov;7(11):e1002261. doi: 10.1371/journal.pcbi.1002261. Epub 2011 Nov 3.
10
Information transduction capacity of noisy biochemical signaling networks.噪声生化信号网络的信息传递能力。
Science. 2011 Oct 21;334(6054):354-8. doi: 10.1126/science.1204553. Epub 2011 Sep 15.