Bull James J, Remien Christopher H, Krone Stephen M
Department of Integrative Biology, University of Texas, Austin, TX, USA.
Department of Mathematics, University of Idaho, Moscow, ID, USA.
Evol Med Public Health. 2019 May 11;2019(1):66-81. doi: 10.1093/emph/eoz014. eCollection 2019.
Genetic engineering combined with CRISPR technology has developed to the point that gene drives can, in theory, be engineered to cause extinction in countless species. Success of extinction programs now rests on the possibility of resistance evolution, which is largely unknown. Depending on the gene-drive technology, resistance may take many forms, from mutations in the nuclease target sequence (e.g. for CRISPR) to specific types of non-random population structures that limit the drive (that may block potentially any gene-drive technology).
We develop mathematical models of various deviations from random mating to consider escapes from extinction-causing gene drives. A main emphasis here is sib mating in the face of recessive-lethal and Y-chromosome drives.
Sib mating easily evolves in response to both kinds of gene drives and maintains mean fitness above 0, with equilibrium fitness depending on the level of inbreeding depression. Environmental determination of sib mating (as might stem from population density crashes) can also maintain mean fitness above 0. A version of Maynard Smith's haystack model shows that pre-existing population structure can enable drive-free subpopulations to be maintained against gene drives.
Translation of mean fitness into population size depends on ecological details, so understanding mean fitness evolution and dynamics is merely the first step in predicting extinction. Nonetheless, these results point to possible escapes from gene-drive-mediated extinctions that lie beyond the control of genome engineering.
Recent gene drive technologies promise to suppress and even eradicate pests and disease vectors. Simple models of gene-drive evolution in structured populations show that extinction-causing gene drives can be thwarted both through the evolution of sib mating as well as from purely demographic processes that cluster drive-free individuals.
基因工程与CRISPR技术的结合已发展到理论上可设计基因驱动,导致无数物种灭绝的程度。灭绝计划的成功如今取决于抗性进化的可能性,而这在很大程度上尚不清楚。根据基因驱动技术的不同,抗性可能有多种形式,从核酸酶靶序列中的突变(例如CRISPR的情况)到限制驱动的特定类型的非随机种群结构(这可能会阻碍任何潜在的基因驱动技术)。
我们建立了各种偏离随机交配的数学模型,以考虑从导致灭绝的基因驱动中逃脱的情况。这里的一个主要重点是面对隐性致死和Y染色体驱动时的同胞交配。
同胞交配很容易因这两种基因驱动而进化,并使平均适合度维持在0以上,平衡适合度取决于近亲繁殖衰退的程度。同胞交配的环境决定因素(可能源于种群密度骤降)也可使平均适合度维持在0以上。梅纳德·史密斯的干草堆模型的一个版本表明,预先存在的种群结构可使无驱动的亚种群抵御基因驱动得以维持。
平均适合度转化为种群大小取决于生态细节,因此理解平均适合度的进化和动态只是预测灭绝的第一步。尽管如此,这些结果指出了可能存在基因驱动介导的灭绝无法控制的逃脱途径。
最近的基因驱动技术有望抑制甚至根除害虫和疾病媒介。结构化种群中基因驱动进化的简单模型表明,导致灭绝的基因驱动可通过同胞交配的进化以及使无驱动个体聚集的纯粹人口统计学过程而受到阻碍。