Exploring reported genes of microglia RNA-sequencing data: Uses and considerations.

The advent of RNA-sequencing techniques has made it possible to generate large, unbiased gene expression datasets of tissues and cell types. Several studies describing gene expression data of microglia from Alzheimer's disease or multiple sclerosis have been published, aiming to generate more insight into the role of microglia in these neurological diseases. Though the raw sequencing data are often deposited in open access databases, the most accessible source of data for scientists is what is reported in published manuscripts. We observed a relatively limited overlap in reported differentially expressed genes between various microglia RNA-sequencing studies from multiple sclerosis or Alzheimer's diseases. It was clear that differences in experimental set up influenced the number of overlapping reported genes. However, even when the experimental set up was very similar, we observed that overlap in reported genes could be low. We identified that papers reporting large numbers of differentially expressed microglial genes generally showed higher overlap with other papers. In addition, though the pathology present within the tissue used for sequencing can greatly influence microglia gene expression, often the pathology present in samples used for sequencing was underreported, leaving it difficult to assess the data. Whereas reanalyzing every raw dataset could reduce the variation that contributes to the observed limited overlap in reported genes, this is not feasible for labs without (access to) bioinformatic expertise. In this study, we thus provide an overview of data present in manuscripts and their supplementary files and how these data can be interpreted.

Longitudinal Assessment of Working Memory Performance in the APPswe/PSEN1dE9 Mouse Model of Alzheimer's Disease Using an Automated Figure-8-Maze.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder, with a long preclinical and prodromal phase. To enable the study of disease mechanisms, AD has been modeled in many transgenic animal lines and cognitive functioning has been tested using several widely used behavioral tasks. These tasks, however, are not always suited for repeated longitudinal testing and are often associated with acute stress such as animal transfer, handling, novelty, or stress related to the task itself. This makes it challenging to relate cognitive dysfunction in animal models to cognitive decline observed in AD patients. Here, we designed an automated figure-8-maze (F8M) to test mice in a delayed alternation task (DAT) in a longitudinal manner. Mice were rewarded when they entered alternate sides of the maze on subsequent trials. Automation as well as connection of the F8M set-up with a home cage reduces experimenter interference and minimizes acute stress, thus making it suitable for longitudinal testing and facilitating clinical translation. In the present study, we monitored cognitive functioning of 2-month-old APPswe/PSEN1dE9 (APP/PS1) mice over a period of 4 months. The percentage of correct responses in the DAT did not differ between wild-type and transgenic mice from 2 to 6 months of age. However, 6-month-old mice displayed an increase in the number of consecutive incorrect responses. These results demonstrate the feasibility of longitudinal testing using an automated F8M and suggest that APP/PS1 mice are not impaired at delayed spatial alternation until 6 months of age under the current experimental conditions.