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Stinchcombe, A. R.

Publications and source records attributed to Stinchcombe, A. R..

2 recordsLinked to original sources

The chronology of developing cells: are epigenomic and transcriptomic oscillations linked to their linear trajectories?

BackgroundDuring development, the specification of individual cell types requires orchestrated shifts in the activity of thousands of genes, each following precise and coordinated trajectories. The ability of this process to succeed with remarkable reliability, despite its immense complexity, suggests that at least some underlying principles of development are fundamentally simple. Building on recent findings from epigenetic aging research, we hypothesize that linear trajectories in developing cells are influenced by concurrent oscillatory dynamics, which may help ensure synchrony and robustness. ResultsSupporting this model, we demonstrate an association between oscillatory and linear dynamics in cytosine modifications in mouse intestinal organoids, as well as in the transcriptomes of C. elegans. Furthermore, we show that transcriptomes of single cells exhibited developmental chrono-heterogeneity, enabling reconstruction of oscillatory cycles which also correlate with linear changes. ConclusionsOscillation-mediated linear dynamics may represent an evolutionary invention for encoding molecular time and orchestrating developmental processes.

molecular biology↗

Oscillation detection with period uncertainty and a limited sampling budget

Equally spaced temporal sampling is the standard protocol for the study of biological rhythms. These equispaced designs perform well when calibrated to an oscillators period yet can have systematic detection biases when applied to rhythms of unknown periodicity. Here, we present a broadly-applicable set of computational methods for seeking optimal measurement schedules for rhythm detection. Our PowerCHORD methods generate experimental designs by maximizing a closed-form expression for the statistical power of the cosinor model using a black-box optimization method (differential evolution), a brute-force search, or mixed-integer conic programming. Application of these three methods showed numerically that they improve upon equispaced designs under many experimental contexts. Our numerical results also revealed an intuitive approach for achieving optimal power for simultaneous investigation of circadian, circalunar, and circannual rhythms. Our findings suggest that timing optimization is an effective yet under-explored tool for improving biological rhythm discovery.

bioinformatics↗