Mathematical model infers telomere dynamics parameters from long-read sequencing

Researchers have developed a mathematical framework that treats telomere shortening and telomerase-mediated elongation as an ergodic Markov chain with an explicit steady-state distribution of telomere lengths. This allows the biochemical parameters governing telomere length dynamics to be uniquely inferred from long-read sequencing data. The pipeline was verified on synthetic data with known parameters and on wild-type and mutant yeast strains carrying telomere regulator mutations. Applied to 66 natural Saccharomyces cerevisiae strains, it revealed diverse regulation parameters across strains, and chromosome-end-specific regulation in some cases. The work is a preprint in genomics; open questions include how the approach performs in other organisms and how inferred parameters map to specific molecular regulators.

Written by a model from the reports · updated 2 hours ago

Not enough continuous observation yet to draw a trend.