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Inversion symmetry of DNA k-mer counts: validity and deviations.

Sagi Shporer¹, Benny Chor¹, Saharon Rosset²

¹Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, 69978, Israel.

|September 2, 2016

Summary

This summary is machine-generated.

Inversion Symmetry (IS) holds for human chromosomes up to k=10, following a universal logarithmic length dependence. Minute deviations correlate with gene distribution, offering new insights into genome organization.

Keywords:

Chromosome k-mer distributions Generalized Chargaff rules Inversion symmetry

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

The second Chargaff rule generalizes to Inversion Symmetry (IS), where nucleotide k-mer counts match their reverse-complement counts.
IS has been observed in various species, with its validity range (k-limit) depending on chromosome length.

Purpose of the Study:

To investigate Inversion Symmetry (IS) in the human genome.
To define and analyze the k-limit (KL) for IS in human chromosomes.
To develop a statistical model for IS and explore deviations from it.

Main Methods:

Numerical analysis of IS in human chromosomes up to k=10.
Introduction of a numerical IS criterion and definition of the k-limit (KL).
Development of a statistical IS-Poisson model to assess confidence measures and analyze deviations.

Main Results:

IS holds up to k=10 in the human genome, even with low-complexity masking.
A universal logarithmic relationship (KL ≈ 0.7 ln(L)) was found between the k-limit and chromosome length (L).
Minute but significant deviations from the IS-Poisson model were observed for low k, including strand-specific nucleotide biases and a correlation with gene distribution.

Conclusions:

The IS-Poisson model accurately describes IS behavior and the universal k-limit dependence on chromosome length.
Deviations from the model in human chromosomes reveal strand-specific nucleotide excesses (T vs A, G vs C) that correlate with gene distribution.
These findings provide novel insights into genome organization and potential strand-specific functional biases.