Daisy-chain gene drives for the alteration of local populations

Abstract

If they are able to spread in wild populations, CRISPR-based gene-drive elements would provide new ways to address ecological problems by altering the traits of wild organisms, but the potential for uncontrolled spread tremendously complicates ethical development and use. Here, we detail a self-exhausting form of CRISPR-based drive system comprising genetic elements arranged in a daisy chain such that each drives the next. “Daisy-drive” systems can locally duplicate any effect achievable by using an equivalent self-propagating drive system, but their capacity to spread is limited by the successive loss of nondriving elements from one end of the chain. Releasing daisy-drive organisms constituting a small fraction of the local wild population can drive a useful genetic element nearly to local fixation for a wide range of fitness parameters without self-propagating spread. We additionally report numerous highly active guide RNA sequences sharing minimal homology that may enable evolutionarily stable daisy drive as well as self-propagating CRISPR-based gene drive. Especially when combined with threshold dependence, daisy drives could simplify decision-making and promote ethical use by enabling local communities to decide whether, when, and how to alter local ecosystems.

Document Details

Document Type
Pub Defense Publication
Publication Date
Apr 02, 2019
Source ID
10.1073/pnas.1716358116

Entities

People

  • Alejandro Chavez
  • Andrea Smidler
  • Charleston Noble
  • Erika Alden DeBenedictis
  • George M. Church
  • Jason Olejarz
  • Joanna Buchthal
  • John Min
  • Kevin M. Esvelt
  • Martin A. Nowak

Organizations

  • Burroughs Wellcome Fund
  • Harvard Medical School
  • Harvard T.H. Chan School of Public Health
  • Harvard University
  • Massachusetts General Hospital
  • Massachusetts Institute of Technology
  • National Institute of Diabetes and Digestive and Kidney Diseases
  • National Science Foundation

Tags

Fields of Study

  • Biology

Readers

  • Molecular Genetics
  • Systems Analysis and Design

Technology Areas

  • Biotechnology