PT - JOURNAL ARTICLE
AU - Johnson, Joshua
AU - Chen, Xin
AU - Xu, Xiao
AU - Emerson, John W.
TI - ŌvSim: a Simulation of the Population Dynamics of Mammalian Ovarian Follicles
AID - 10.1101/034249
DP - 2016 Jan 01
TA - bioRxiv
PG - 034249
4099 - http://biorxiv.org/content/early/2016/09/12/034249.short
4100 - http://biorxiv.org/content/early/2016/09/12/034249.full
AB - No two ovaries are alike, and indeed, the same ovary can change its architecture from day to day. This is because ovarian follicles are present in different numbers, positions, and states of maturation throughout reproductive life. All possible developmental states of follicles can be represented at any time, along with follicles that have committed to death (termed follicle atresia). Static histological and whole-mount imaging approaches allow snapshots of what is occurring within ovaries, but our views of dynamic follicle growth and death have been limited to these tools. We present a simple Markov chain model of the complex mouse ovary, called “ŌvSim”. In the model, follicles can exist in one of three Markov states with stationary probabilities, Hold (growth arrest), Grow, and Die. The probability that individual primordial follicles can growth activate daily, the fraction of granulosa cells that survive as follicles grow, and the probability that individual follicles can commit to atresia daily are user definable parameters. When the probability of daily growth activation is stationary at 0.005, the probability of atresia for all follicles is near 0.1, and the probability of granulosa cell survival is modeled around 0.88, ŌvSim simulates the growth and fate of each of the approximately 3000 postpubertal mouse ovarian follicles in a fashion that approximates actual biological measurements (e.g., follicle counts). ŌvSim thus offers a starting platform to simulate mammalian ovaries and to explore factors that might impact follicle development and global organ function.Author Summary ŌvSim is a computer simulation of the dynamic growth of mouse ovarian follicles. The program is offered as the beginning of a research and teaching platform to model asynchronous follicle growth and survival or death.