In a new paper, scientists of the Earth Commission argue how today’s scenarios are falling short of providing solutions to the climate crisis. They call for a rethink that puts justice, diverse knowledge, and systemic change at the heart of modelling.

Climate change is widely understood as an environmental and economic threat, but new research from the University of Sydney shows it is also a growing social crisis, weakening the relationships people rely on to survive.

In a large survey of laboratory mouse strains held by major research repositories, Fernando Pardo Manuel de Villena and colleagues found that nearly half of the samples showed discrepancies between their reported identities and their actual genetic profiles, revealing a critical gap in genetic quality control (GQC). While many inconsistencies were relatively minor, some had the potential to undermine experimental validity and reproducibility by introducing hidden genetic variables that could alter biological outcomes. According to the authors, an improved GQC process could help address these inconsistencies and ensure that laboratory mouse models are consistent, reliable, and reproducible in biomedical research. “True replication studies require an exact match with the materials, methods, and design used in the original study,” write the authors.  “Laboratory mouse–based replication studies that lack proper GQC of the mice used in both the original report and the replication study should be treated with caution.”

In this Policy Article, Pardo Manuel de Villena et al. used the sophisticated and standardized GCQ system known as MiniMUGA (Mouse Universal Genotyping Array) to genotype 611 samples from 341 mouse model strains held by Mutant Mouse Resource and Research Centers (MMRRCs) to determine whether the animals’ reported identities accurately matched their genetic makeup. Although the expected engineered mutation was generally present, the authors found that half of the samples contained discrepancies between their official strain names and their actual genomic profiles. Most inconsistencies involved mismatches between the reported and detected substrains, incorrect classification of strain type, or failures to indicate the presence of important genetic constructs. In some cases, strains proved to be genetically more uniform and reproducible than their names suggested, while others contained unexpected genetic variation that could significantly affect experimental outcomes. Particularly concerning were hidden genetic elements that could alter biological results and compromise the rigor and reproducibility of studies. In practice, only about 20% of the examined strains fully met the expectations associated with their names. To address this, Pardo Manuel de Villena et al. propose a standardized, high-resolution GQC framework and call for coordinated efforts among repositories, journals, and funders to improve quality and consistency. “The lack of consistency and low rate of expectations met as presented here are not due to fundamental failures of past research but are the consequence of the unavailability heretofore of widely applicable, cost-effective, and accessible tools for mouse GQC,” Pardo Manuel de Villena et al. write. “The process highlighted here addresses this knowledge gap.”