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Nestin-Cre Mouse Lines: A User Guide for CNS Genetics

Sep 2026 · Journal of Neuroscience · Vol 46, pp. e0537262026 · 0 citations · 58 references
Medicine

TL;DR

A consolidated, decision-oriented framework for reproducible CNS-targeted genetic experiments, converts the thesis into bench practice, and reduces wasted cohorts is offered.

Abstract

Nestin-Cre is the most widely used Cre driver for conditional genetic manipulation in the central nervous system (CNS), underpinning hundreds of studies in neurodevelopment, lineage tracing, brain tumor modeling, and circuit analysis. Despite its dominant role, divergent recombination outcomes—spanning developmental onset, penetrance, mosaicism, and ectopic activity—are frequently reported, creating substantial interpretive challenges across the field. Here we provide a practical guide to selecting and using Nestin-Cre and Nestin-CreER(T2) mouse lines for CNS research. We systematically examine 22 independently generated lines (1996–2025), synthesizing data from >400 published studies. Rather than cataloguing line histories, we organize this knowledge around the decisions experimentalists actually face: whether to use a constitutive or inducible system, which lines best target specific CNS compartments and developmental windows, and how to achieve uniform versus sparse recombination. We show that reported variability is not an intrinsic limitation of Nestin-based drivers but arises from definable, controllable factors—construct architecture, transgene integration context, reporter sensitivity, breeding configuration, and, for inducible systems, tamoxifen formulation and dosing. Each factor is addressed with specific guidance. For inducible lines, we provide a comparative ranking of recombination efficiency against background leakiness to inform line selection. We highlight breeding strategy as a critical and frequently mismanaged variable, discuss Cre-dosage effects on neural progenitor survival, and address reporter-dependent differences in apparent recombination efficiency. Together, this TechSight article offers a consolidated, decision-oriented framework for reproducible CNS-targeted genetic experiments, converts the thesis into bench practice, and reduces wasted cohorts.

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