Evolutionary dynamics of CRISPR gene drives in natural populations

自然群体中 CRISPR 基因驱动的进化动力学

• 批准号: 10461022
• 负责人: Philipp W Messer
• 金额: $ 32.3万
• 依托单位: CORNELL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10461022
• 关键词: Address; Affect; Alleles; Area; CRISPR gene drive; Cells; Complex; Demography; Development; Disease Vectors; Embryo; Engineering; Environment; Ethics; Event; Evolution; Genes; Genetic; Genetic Models; Genetic Variation; Genotype; Geography; Goals; Guide RNA; Homozygote; Individual; Inherited; Life Cycle Stages; Measures; Modeling; Molecular; Outcome; Pattern; Performance; Population; Population Dynamics; Population Genetics; Population Heterogeneity; Population Sizes; Population Study; Process; Research; Resistance; Risk; Safety; Side; Structure; System; Target Populations; Theoretical model; Transgenes; Uncertainty; Variant; Vector-transmitted infectious disease; Work; base; cost; design; experience; fitness; gene drive system; genetic evolution; genetic payload; homing gene drive; improved; individual variation; insight; migration; new technology; novel strategies; pathogen; real world application; resistance allele; resistance mechanism; simulation; simulation software; theories; transmission process; underdominance; vector; vector control

Project Summary CRISPR gene drives can efficiently convert heterozygous cells with one copy of the drive allele into homozygotes, thereby enabling super-Mendelian inheritance. Such a mechanism could be used, for example, to rapidly disseminate a genetic payload through a disease-vector population that reduces pathogen transmission or directly suppresses the vector, promising novel strategies for the control of vector-borne diseases. However, our current understanding of how such an approach would perform in a natural population is at best rudimentary. CRISPR gene drive is a complex evolutionary process that depends on various factors such as the likelihood that resistance evolves against the drive, the spatial structure and migration patterns of the target population, and genetic variation among individuals. The overarching goal of this proposal is to gain a better understanding of the evolutionary dynamics of CRISPR gene drive strategies in realistic models of target populations that take these complexities into account. In Specific Aim 1 we will develop a comprehensive modeling framework for CRISPR gene drives that will be informed by our recent experimental findings on drive mechanisms, resistance allele formation, and variation in resistance rates in genetically diverse populations. This framework will allow us to explore the performance of different drive strategies aimed at reducing resistance potential, such as the use of multiple gRNAs and the targeting of haploinsufficient genes. In Specific Aim 2 we will utilize cutting-edge simulation approaches developed in our lab to study how CRISPR gene drives will perform in spatially explicit population models, in which individuals move across a continuous landscape and can experience complex interactions with each other and their local environment. We hypothesize that these spatial models will give rise to new phenomena that are not present in panmictic population models, such as the elimination of a drive that has already spread into a large fraction of the population when populations collapse locally due to the fitness cost of the drive. In Specific Aim 3 we will use the modeling framework developed in the first two aims to study whether recently proposed safety measures can reliably confine and control a drive after it has been released into a target population, focusing on the complex interplay between drive genetics, the evolution of resistance, and the migration dynamics of individuals over realistic landscapes. Our framework will allow us to probe and predict the population dynamics of CRISPR gene drive approaches under specific empirical conditions, which will be integral to any informed discussion about the feasibility, robustness, and risks of such approaches.

项目摘要 CRISPR基因驱动可以有效地将具有一个驱动等位基因拷贝的杂合细胞转化为 纯合子，从而使超孟德尔遗传。可以使用这种机制，因为 例如，通过病媒群体迅速传播遗传有效载荷， 病原体传播或直接抑制载体，有希望的新策略， 病媒传播的疾病。然而，我们目前对这种方法在 自然种群最多也就是最原始的。CRISPR基因驱动是一个复杂的进化过程， 这取决于各种因素，如抵抗力与驱力相对抗的可能性，空间 目标种群的结构和迁移模式，以及个体间的遗传变异。的 本提案的首要目标是更好地了解 CRISPR基因驱动策略在目标人群的现实模型中， 帐户.在具体目标1中，我们将为CRISPR基因开发一个全面的建模框架。 我们最近关于驱动机制、抗性等位基因、 形成和遗传多样性群体中抗性率的变化。该框架将允许 我们探讨不同的驱动策略，旨在减少阻力的潜力，如性能 多个gRNA的使用和单倍不足基因的靶向。在具体目标2中，我们将利用 我们实验室开发的尖端模拟方法，用于研究CRISPR基因驱动将如何执行 在空间明确的人口模型中，个体在连续的景观中移动， 他们彼此之间以及与当地环境的复杂互动。我们假设这些 空间模型将产生在泛混合种群模型中不存在的新现象，例如 作为消除一种驱动器，已经蔓延到一大部分人口， 种群由于驱动器的适应性成本而局部崩溃。在具体目标3中，我们将使用建模 在前两个框架中开发的目的是研究最近提出的安全措施是否可以 可靠地限制和控制驱动器后，它已被释放到目标人群，重点是 驱动遗传学，抗性进化和迁移动力学之间的复杂相互作用 个人对现实的风景。我们的框架将使我们能够探测和预测 CRISPR基因驱动方法在特定经验条件下的动力学，这将是不可或缺的， 关于这些方法的可行性、稳健性和风险的任何知情讨论。

项目成果

Modeling CRISPR gene drives for suppression of invasive rodents using a supervised machine learning framework.

• DOI: 10.1371/journal.pcbi.1009660
• 发表时间: 2021-12
• 期刊: PLoS computational biology
• 影响因子: 4.3
• 作者: Champer SE;Oakes N;Sharma R;García-Díaz P;Champer J;Messer PW
• 通讯作者: Messer PW

Predicting the genomic resolution of bulk segregant analysis.

• DOI: 10.1093/g3journal/jkac012
• 发表时间: 2022-03-04
• 期刊: G3 (Bethesda, Md.)
• 作者: Shen R;Messer PW
• 通讯作者: Messer PW

A framework for identifying fertility gene targets for mammalian pest control.

确定哺乳动物害虫控制的生育基因目标的框架。

• DOI: 10.1101/2023.05.30.542751
• 发表时间: 2023
• 期刊: bioRxiv : the preprint server for biology
• 作者: Clark,AnnaC;Alexander,Alana;Edison,Rey;Esvelt,Kevin;Kamau,Sebastian;Dutoit,Ludovic;Champer,Jackson;Champer,SamuelE;Messer,PhilippW;Gemmell,NeilJ
• 通讯作者: Gemmell,NeilJ