Work performed from the beginning of the project (September 2020) included management of the APPPS1 transgenic mouse colony as at least 12 male mice of each age group (6 weeks, 3, 9 and 18 months) were required to cover the project's objectives. Priority were given of course to the oldest cohort, which was established before the beginning of the project. At the beginning of the project the cohorts were expanded to a 6 months and 12 months cohort to better cover the lifetime of mice for the phenotypic analysis with immunohistochemistry stainings. Due to the Corona Virus Pandemic breeding of mice during 2020 was quite limited and could only expanded to the required levels in 2021. Therefore, collection of the required brain samples from the APPPS1 transgenic and wildtype control mice began in summer of 2021 and commenced in autumn of 2022. Collection of brain samples continued throughout the 1 year break of the project, which allowed me to run at least some of the planned experiments described in the proposal. In total 12-15 frozen cortex and hippocampus samples for all six age groups could be collected until October 2022. In addition, cortex and hippocampus samples from wildtype mice were collected at post-natal day 21 (hippocampus development in mice completed, high level of synapse pruning occurs) and 25 months of age. These samples were included in the single nuclei RNA-seq and ATAC-seq assays to allow for comparison with the APPPS1 mice to determine if we see molecular evidence of early aging or de-differentiation.
I successfully completed sorting of nuclei and ATAC-seq library preparation in autumn of 2022. ATAC-seq libraries were sequenced at the beginning of 2023 and analysis is currently ongoing.
In the spring of 2022 (after re-start of the project) I focused my efforts on improving the scRNA-seq/SPLiT-seq as described in Objective 1 to allow assessment of transposable element expression in the SPLiT-seq dataset. I switched the analysis pipeline to use the STAR aligner STARsolo options for scRNA-seq for barcode deconvolution and determination of read counts, which allows quantification based on exons only and whole genes (exons and introns) as well as on spliced and unspliced transcripts, which allows analysis of RNA velocity. RNA velocity can be used for the analysis of time-resolved phenomena such as embryogenesis and as in my case neurodegeneration. I implemented the new analysis pipeline using published SPLiT-seq data of 100 mouse brain nuclei to have a limited dataset that can be easily monitored. Next, I applied the new analysis pipeline to small SPLiT-seq dataset of mouse hippocampus, which I had generated previously. The main idea behind this approach was to determine if I can map a SPLiT-seq-based snRNA-seq dataset onto a reference dataset created by integrating different 10X-based snRNA-seq datasets of the mouse hippocampus. To create the reference dataset, I used two datasets: 1) dentate gyrus development and 2) adult mouse hippocampus. Next I mapped my own SPLiT-seq dataset onto this reference, which confirmed previous marker-based cell type annotations (see attached Figure).
For completion of Aim 1.1 we decided to switch to the commercial SPLiT-seq kit offered by Parse Biosciences, which offers many advantages to the home-brewed version and many groups working on single cell or single nuclei RNA-seq are switching to from using the more costly and limited 10X Genomics sequencing kits. In this case I selected hippocampi (3 biological replicates each) from the following sample groups: 1) P21 C57BL/6J wildtype mice, 2) 3 months old C57BL/6J wildtype mice, 3) 9 months old C57BL/6J wildtype mice, 4) 3 months old APP/PS1 mice, 5) 6 months old APP/PS1 mice, 6) 9 months old APP/PS1 mice, 7) 18 months old APP/PS1 mice and 8) 25 months old C57BL/6J wildtype mice. Nuclei from these samples were isolated as recommended, fixed and single nuclei RNA-seq libraries were prepared according to Parse Biosciences. The eight final libraries, which should provide data from about 100,000 nuclei, were finally sequenced this September and analysis will commence as soon as possible, but after the funding period had ended.
