Unknown

Dataset Information

0

Current CRISPR gene drive systems are likely to be highly invasive in wild populations.


ABSTRACT: Recent reports have suggested that self-propagating CRISPR-based gene drive systems are unlikely to efficiently invade wild populations due to drive-resistant alleles that prevent cutting. Here we develop mathematical models based on existing empirical data to explicitly test this assumption for population alteration drives. Our models show that although resistance prevents spread to fixation in large populations, even the least effective drive systems reported to date are likely to be highly invasive. Releasing a small number of organisms will often cause invasion of the local population, followed by invasion of additional populations connected by very low rates of gene flow. Hence, initiating contained field trials as tentatively endorsed by the National Academies report on gene drive could potentially result in unintended spread to additional populations. Our mathematical results suggest that self-propagating gene drive is best suited to applications such as malaria prevention that seek to affect all wild populations of the target species.

SUBMITTER: Noble C 

PROVIDER: S-EPMC6014726 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

altmetric image

Publications

Current CRISPR gene drive systems are likely to be highly invasive in wild populations.

Noble Charleston C   Adlam Ben B   Church George M GM   Esvelt Kevin M KM   Nowak Martin A MA  

eLife 20180619


Recent reports have suggested that self-propagating CRISPR-based gene drive systems are unlikely to efficiently invade wild populations due to drive-resistant alleles that prevent cutting. Here we develop mathematical models based on existing empirical data to explicitly test this assumption for population alteration drives. Our models show that although resistance prevents spread to fixation in large populations, even the least effective drive systems reported to date are likely to be highly in  ...[more]

Similar Datasets

| S-EPMC10567717 | biostudies-literature
| S-EPMC6934693 | biostudies-literature
| S-EPMC7068947 | biostudies-literature
| S-EPMC3260013 | biostudies-literature
| S-EPMC10810878 | biostudies-literature
| S-EPMC7382497 | biostudies-literature
| S-EPMC5518997 | biostudies-literature
| S-EPMC6358215 | biostudies-literature
| S-EPMC7218562 | biostudies-literature
| S-EPMC10666174 | biostudies-literature