Can Evolutionary Rate Matrices be Estimated from Allele Frequencies?

Conrad J. Burden

2015

Abstract

This paper is a work in progress in which aims to combine the principles of population genetics and continuous-time Markovian evolutionary models to estimate evolutionary rate matrices from the current observed state of a single genome. A model is proposed in which sections of the genome which are not susceptible to natural selection are considered to be a statistical ensemble of individual genomic sites. Each site is a representative from a stationary distribution of allele frequencies 0 = ? = 1 within the population. Simulations of this distribution via a finite-state Markov model based on a finite effective population size are compared with the stationary solution to the continuum Fokker-Planck equation. Parameters of the evolutionary rate matrix introduced via mutation rates within the Fokker-Planck equation are estimated for simulated data in a number of exploratory examples.

References

  1. Ewens, W. J. (2004). Mathematical population genetics, volume 27 of Interdisciplinary Applied Mathematics. Springer, New York, 2nd edition.
  2. Hasegawa, M., Kishino, H., and Yano, T. (1985). Dating of the human-ape splitting by a molecular clock of mitochondrial dna. J Mol Evol, 22(2):160-74.
  3. Johnson, N. L., Kotz, S., and Kemp, A. W. (1992). Univariate Discrete Distributions. Wiley, New York, 2nd edition.
  4. Lynch, M. (2009). Estimation of allele frequencies from high-coverage genome-sequencing projects. Genetics, 182(1):295-301.
  5. Messer, P. W. (2009). Measuring the rates of spontaneous mutation from deep and large-scale polymorphism data. Genetics, 182(4):1219-32.
  6. Nevarez, P. A., DeBoever, C. M., Freeland, B. J., Quitt, M. A., and Bush, E. C. (2010). Context dependent substitution biases vary within the human genome. BMC Bioinformatics, 11:462.
  7. Wright, S. (1931). Evolution in mendelian populations. Genetics, 16:97-159.
  8. Zhao, Z. and Boerwinkle, E. (2002). Neighboringnucleotide effects on single nucleotide polymorphisms: a study of 2.6 million polymorphisms across the human genome. Genome Res, 12(11):1679-86.
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Paper Citation


in Harvard Style

J. Burden C. (2015). Can Evolutionary Rate Matrices be Estimated from Allele Frequencies? . In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2015) ISBN 978-989-758-070-3, pages 183-188. DOI: 10.5220/0005253701830188


in Bibtex Style

@conference{bioinformatics15,
author={Conrad J. Burden},
title={Can Evolutionary Rate Matrices be Estimated from Allele Frequencies?},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2015)},
year={2015},
pages={183-188},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005253701830188},
isbn={978-989-758-070-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2015)
TI - Can Evolutionary Rate Matrices be Estimated from Allele Frequencies?
SN - 978-989-758-070-3
AU - J. Burden C.
PY - 2015
SP - 183
EP - 188
DO - 10.5220/0005253701830188