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Adversarial interspecies relationships facilitate population suppression by gene drive in spatially explicit models.
Liu, Yiran; Teo, WeiJian; Yang, Haochen; Champer, Jackson.
Afiliación
  • Liu Y; Center for Bioinformatics, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
  • Teo W; Center for Bioinformatics, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
  • Yang H; Center for Bioinformatics, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
  • Champer J; Center for Bioinformatics, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
Ecol Lett ; 26(7): 1174-1185, 2023 Jul.
Article en En | MEDLINE | ID: mdl-37162099
ABSTRACT
Suppression gene drives bias their inheritance to spread through a population, potentially eliminating it when they reach high frequency. CRISPR homing suppression drives have already seen success in the laboratory, but several models predict that success may be elusive in population with realistic spatial structure due to extinction-recolonization cycles. Here, we extend our continuous space framework to include two competing species or predator-prey pairs. We find that in both general and mosquito-specific models, competing species or predators can facilitate drive-based suppression, albeit at the cost of an increased rate of drive loss outcomes. These results are robust in mosquito models with seasonal fluctuations. Our study illustrates the difficulty of predicting outcomes in complex ecosystems. However, our results are promising for the prospects of less powerful suppression gene drives to successfully eliminate target mosquito and other pest populations.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Ecosistema / Tecnología de Genética Dirigida Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: Ecol Lett Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Ecosistema / Tecnología de Genética Dirigida Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: Ecol Lett Año: 2023 Tipo del documento: Article País de afiliación: China