Lab

John M Marshall's lab

About the lab

We are a collaborative group of researchers motivated by our interest in quantitative science and our desire to improve public health, both locally and globally. Our expertise span applied mathematics, applied statistics, computational genetics, epidemiology, ecology, population genetics and molecular biology. Many of the projects we work on have a strong social dimension. We maintain an active interest in the ethical, cultural and regulatory aspects of our work.

Featured projects (1)

Project
Creating a flexible and comprehensive framework in which gene-drive releases can be simulated and assessed.

Featured research (3)

The discovery of CRISPR-based gene editing and its application to homing-based gene drive has been greeted with excitement, for its potential to control mosquito-borne diseases on a wide scale, and concern, for the invasiveness and potential irreversibility of a release. At the same time, CRISPR-based gene editing has enabled a range of self-limiting gene drive systems to be engineered with much greater ease, including (1) threshold-dependent systems, which tend to spread only when introduced above a certain threshold population frequency, and (2) temporally self-limiting systems, which display transient drive activity before being eliminated by virtue of a fitness cost. As these CRISPR-based gene drive systems are yet to be field-tested, plenty of open questions remain to be addressed, and insights can be gained from precedents set by field trials of other novel genetics-based and biological control systems, such as trials of Wolbachia-transfected mosquitoes, intended for either population replacement or suppression, and trials of genetically sterile male mosquitoes, either using the RIDL system (release of insects carrying a dominant lethal gene) or irradiation. We discuss lessons learned from these field trials and implications for a phased exploration of gene drive technology, including homing-based gene drive, chromosomal translocations, and split gene drive as a system potentially suitable for an intermediate release.
CRISPR-based gene drives can spread through wild populations by biasing their own transmission above the 50% value predicted by Mendelian inheritance. These technologies offer population-engineering solutions for combating vector-borne diseases, managing crop pests, and supporting ecosystem conservation efforts. Current technologies raise safety concerns for unintended gene propagation. Herein, we address such concerns by splitting the drive components, Cas9 and gRNAs, into separate alleles to form a trans-complementing split–gene-drive (tGD) and demonstrate its ability to promote super-Mendelian inheritance of the separate transgenes. This dual-component configuration allows for combinatorial transgene optimization and increases safety by restricting escape concerns to experimentation windows. We employ the tGD and a small–molecule-controlled version to investigate the biology of component inheritance and resistant allele formation, and to study the effects of maternal inheritance and impaired homology on efficiency. Lastly, mathematical modeling of tGD spread within populations reveals potential advantages for improving current gene-drive technologies for field population modification.
1.Malaria, dengue, Zika, and other mosquito‐borne diseases continue to pose a major global health burden through much of the world, despite the widespread distribution of insecticide‐based tools and antimalarial drugs. The advent of CRISPR/Cas9‐based gene editing and its demonstrated ability to streamline the development of gene drive systems has reignited interest in the application of this technology to the control of mosquitoes and the diseases they transmit. The versatility of this technology has enabled a wide range of gene drive architectures to be realized, creating a need for their population‐level and spatial dynamics to be explored. 2.We present MGDrivE (Mosquito Gene Drive Explorer): a simulation framework designed to investigate the population dynamics of a variety of gene drive architectures and their spread through spatially‐explicit mosquito populations. A key strength of the MGDrivE framework is its modularity: a) a genetic inheritance module accommodates the dynamics of gene drive systems displaying userdefined inheritance patterns, b) a population dynamic module accommodates the life history of a variety of mosquito disease vectors and insect agricultural pests, and c) a landscape module generates the metapopulation model by which insect populations are connected via migration over space. 3.Example MGDrivE simulations are presented to demonstrate the application of the framework to CRISPR/Cas9‐based homing gene drive for: a) driving a disease‐refractory gene into a population (i.e. population replacement), and b) disrupting a gene required for female fertility (i.e. population suppression), incorporating homing‐resistant alleles in both cases. Further documentation and use examples are provided at the project's Github repository. 4.MGDrivE is an open‐source R package freely available on CRAN. We intend the package to provide a flexible tool capable of modeling novel inheritance‐modifying constructs as they are proposed and become available. The field of gene drive is moving very quickly, and we welcome suggestions for future development.

Lab head

John M Marshall
Department
  • Division of Biostatistics

Members (3)

Héctor Manuel Sánchez Castellanos
  • University of California, Berkeley
Valeri Vasquez
  • University of California, Berkeley
Yogita Sharma
  • University of California, Berkeley
Agastya Mondal
Agastya Mondal
  • Not confirmed yet
Rodrigo Corder
Rodrigo Corder
  • Not confirmed yet