BMC Research Notes (Oct 2023)

Expansions to the MGDrivE suite for simulating the efficacy of novel gene-drive constructs in the control of mosquito-borne diseases

  • Jared B. Bennett,
  • Sean L. Wu,
  • Pratima R. Chennuri,
  • Kevin M. Myles,
  • Martial L. Ndeffo-Mbah

DOI
https://doi.org/10.1186/s13104-023-06533-6
Journal volume & issue
Vol. 16, no. 1
pp. 1 – 6

Abstract

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Abstract Objective The MGDrivE (MGDrivE 1 and MGDrivE 2) modeling framework provides a flexible and expansive environment for testing the efficacy of novel gene-drive constructs for the control of mosquito-borne diseases. However, the existing model framework did not previously support several features necessary to simulate some types of intervention strategies. Namely, current MGDrivE versions do not permit modeling of small molecule inducible systems for controlling gene expression in gene drive designs or the inheritance patterns of self-eliminating gene drive mechanisms. Results Here, we demonstrate a new MGDrivE 2 module that permits the simulation of gene drive strategies incorporating small molecule-inducible systems and self-eliminating gene drive mechanisms. Additionally, we also implemented novel sparsity-aware sampling algorithms for improved computational efficiency in MGDrivE 2 and supplied an analysis and plotting function applicable to the outputs of MGDrivE 1 and MGDrivE 2.

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