Make sure that experimental cohort is derived from a variety of litters and randomised appropriately – this will control for environmental factors in individual litters that may affect the outcome of the experiment. In some instances, it may be critical to include litter as a factor in the analysis.

One option is also to conduct your study using block designs that can introduce variation in a controlled manner to help identify more generalisable results. Below, AstraZeneca's Natasha Karp highlights how this technique can help boost reproducibility (excerpt from a BNA webinar on embracing variation for in vivo research).

This is especially important in relation to genetically modified animals. When working with knock-out animals it's always essential to use the corresponding wild-type littermate control. When it comes to conditional knockouts, the control groups that should be tested also includes LoxP-ready line alone, and the Cre-driver line alone. This is because the Cre-line may have a phenotype already

(for instance Nestin-cre [4]).

You can reduce bias and build confidence in the study by preregistering a time-stamped account of your research plans prior to starting the study, clearly and openly stating your experimental rational, hypothesis, and methods, including the intended statistical analysis. This helps to demostrate not only the rigorous planning, but also that these aspects of the study were not shaped during or after data collection and that the results are not selectively reported.

The easiest way to preregister a study is via a registry. There are all-purpose registries for a range of scientific disciplines, such as the Open Science Framework, and specific in vivo registries such as the Animal Study Registry [6]. 

You can also preregister a study through a journal that offers Registered Reports, such as the BNA's Journal Brain and Neuroscience Advances.

Watch Ulrich Dirnagl from the QUEST Center for Responsible Research explain the preregistration options below (excerpt from a BNA webinar on preregistering in vivo studies).

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7. Have a plan for managing the data you collect

There are simple steps that you can take to improve the structure of how you manage data collection throughout your study. This can not only help you further down the line when it comes to remembering the processes you used, but also provides transparency on how your raw data are turned into your final results. Retaining all raw data is also useful in case at a latter point you discover a error in the data processing or analysis that you need to trace back to the original data.

Setting up a lab strategy for data-gathering can ensure everyone in the lab adopts the same approaches, which can improve continuity when you have staff turnover and help keep your data safe. Having a structure where data is managed well throughout the study can also help with making the data shareable after the study is completed.

Electronic Lab Notebooks offer one tool to help keep track of your project and enable better research processes [7]. In the video below, Kaitlyn Hair from CAMARADES at the University of Edinburgh highlights the benefits ELNs can bring to data management in your study (excerpt from a BNA webinar on handling in vivo data).

Neuroscientists have been “ahead-of-the-game” in understanding the contribution of genetic background to the phenotype [8] and reporting this in our research papers. However, we can improve this further. For instance, are your in-house bred C57BL/6 mice the same C57BL/6 mice others are using? In this regard, it is important when starting out with a new colony of mice to source them from a standard well-trusted supplier.

If you are working on a well-established in-house colony, it is important that the genetic strain is routinely genotyped (and reported), as you may find that this has deviated from the original background strain over successive breading/generations. Of course, this is also true for rats.

9. Handle your rodents correctly

If your study involves looking at rodent behaviour, it is particularly important to understand how your handling can affect the animal. For instance, picking up mice by the tail can compromise their welfare and affect scientific outcomes, and all animals should be handled using non-stressful methods – see the NC3Rs guide on how to pick up a mouse correctly. Also it is important to minimise day-to-day experimenter differences – rodents are particular sensitive to olfactory cues and so it is important to be consistent in glove-type, and even deodorant and perfume use. 

10. Be mindful of circadian rhythms and the effects of light

Another consideration if using rodents is that their physiology is guided by circadian rhythms and they are nocturnal. Therefore, it is important to be aware of how time of day affects the outcomes of a study. Conduct experiments (especially repeat experiments) at similar and well-considered times of the day and ensure a study does not span a light change (lights on/off). Data collected in the “dark phase” when the animals are naturally awake is often more robust.

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