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

Invasive species female fertility genes gene conservation gene drive targets identification framework male fertility genes pest control

Journal

bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187

Informations de publication

Date de publication:
01 Jun 2023
Historique:
pubmed: 3 7 2023
medline: 3 7 2023
entrez: 3 7 2023
Statut: epublish

Résumé

Fertility-targeted gene drives have been proposed as an ethical genetic approach for managing wild populations of vertebrate pests for public health and conservation benefit.This manuscript introduces a framework to identify and evaluate target gene suitability based on biological gene function, gene expression, and results from mouse knockout models.This framework identified 16 genes essential for male fertility and 12 genes important for female fertility that may be feasible targets for mammalian gene drives and other non-drive genetic pest control technology. Further, a comparative genomics analysis demonstrates the conservation of the identified genes across several globally significant invasive mammals.In addition to providing important considerations for identifying candidate genes, our framework and the genes identified in this study may have utility in developing additional pest control tools such as wildlife contraceptives.

Identifiants

pubmed: 37398071
doi: 10.1101/2023.05.30.542751
pmc: PMC10312551
pii:
doi:

Types de publication

Preprint

Langues

eng

Subventions

Organisme : NIGMS NIH HHS
ID : R01 GM127418
Pays : United States

Commentaires et corrections

Type : UpdateIn

Déclaration de conflit d'intérêts

CONFLICT OF INTEREST The authors have no conflicts of interest to declare.

Auteurs

Anna C Clark (AC)

Department of Anatomy, School of Biomedical Sciences, University of Otago, 270 Great King Street, Central Dunedin, Dunedin 9016, New Zealand.
Department of Computational Biology, Cornell University, 102 Tower Rd, Ithaca, NY 14853, United States.

Alana Alexander (A)

Department of Anatomy, School of Biomedical Sciences, University of Otago, 270 Great King Street, Central Dunedin, Dunedin 9016, New Zealand.

Rey Edison (R)

Media Laboratory, Massachusetts Institute of Technology, 75 Amherst St, Cambridge, United States.

Kevin Esvelt (K)

Media Laboratory, Massachusetts Institute of Technology, 75 Amherst St, Cambridge, United States.

Sebastian Kamau (S)

Media Laboratory, Massachusetts Institute of Technology, 75 Amherst St, Cambridge, United States.

Ludovic Dutoit (L)

Department of Zoology, University of Otago, 340 Great King Street, Dunedin 9016, New Zealand.

Jackson Champer (J)

Center for Bioinformatics, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.

Samuel E Champer (SE)

Department of Computational Biology, Cornell University, 102 Tower Rd, Ithaca, NY 14853, United States.

Philipp W Messer (PW)

Department of Computational Biology, Cornell University, 102 Tower Rd, Ithaca, NY 14853, United States.

Neil J Gemmell (NJ)

Department of Anatomy, School of Biomedical Sciences, University of Otago, 270 Great King Street, Central Dunedin, Dunedin 9016, New Zealand.

Classifications MeSH