Covariance Distributions in Single Particle Tracking

6 Oct 2020  ·  Mary Lou P Bailey, Hao Yan, Ivan Surovtsev, Jessica F Williams, Megan C King, Simon G J Mochrie ·

Several recent experiments, including our own in the fission yeast, S. pombe, have characterized the motions of gene loci within living nuclei by measuring the locus position over time, then proceeding to obtain the statistical properties of this motion. To address the question of whether a population of single particle tracks, obtained from many different cells, corresponds to a single mode of diffusion, we derive theoretical equations describing the probability distribution of the displacement covariance, assuming the displacement is a zero-mean multivariate Gaussian random variable. We also determine the corresponding theoretical means, variances, and third central moments. Bolstering the theory is good agreement between its predictions and the results obtained for various simulated and measured data sets, including simulated particle trajectories of simple and anomalous diffusion, and the measured trajectories of an optically-trapped bead in water, and in a viscoelastic solution. We also show that, for sufficiently long tracks, each covariance distribution in these examples is well-described by a skew-normal distribution with mean, variance, and skewness given by theory. For experimental S. pombe gene locus data, however, we find that the first two covariance distributions are wider than predicted, although the third and subsequent covariances are well-described by theory. This suggests that the origin of the theory-experiment discrepancy is associated with localization noise, which influences only the first two covariances. Thus, we hypothesize that the discrepancy is caused by locus-to-locus heterogeneity in the localization noise. Further simulations reveal excess covariance widths can be largely recreated on the basis of heterogeneous noise. We conclude that the motion of gene loci in fission yeast is consistent with a single mode of diffusion.

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Biological Physics