![]() The contamination mainly originated from damaged neuronal nuclei, but could be reduced largely using the in silico approaches. The ambient RNAs are more predominant in the BCAS group than the sham group. Finally, further bioinformatic analyses were performed. Next, the comparison of ambient RNA contamination was performed using irGSEA analysis before and after the in silico approaches. ![]() Then, after removing ambient RNAs in each sample using the in silico approaches, the combination of CellBender and subcluster cleaning, single-nuclei transcriptomes were reconstructed. Single-nuclei transcriptomes were described informatically by the R package Seurat, and ambient RNA markers of were identified in each library. MethodsĪfter the sham and BCAS mice were established, cortex-specific single-nuclei libraries were constructed. More importantly, the BCAS mice can also offer an excellent model to examine the signatures of ambient RNAs contamination in damaged tissues when performing snRNA-seq. Cognitive impairments and white/gray matter injuries are characteristic of deeper cerebral hypoperfusion mouse models induced by bilateral carotid artery stenosis (BCAS), but the molecular mechanisms still need to be further explored. To process the samples appropriately, users need to add the oligonucleotide sequence used for each sample to the sample submission form they deliver to the IGL.Ambient RNAs contamination in single-nuclei RNA sequencing (snRNA-seq) is a challenging problem, but the consequences of ambient RNAs contamination of damaged and/or diseased tissues are poorly understood. The IGL is able to complete the libraries for these protocols. It is the responsibility of each user to select their tagging method, to treat their cells, and to mix them prior to delivery to the IGL for processing. Cells that have hashtags are identified informatically after alignment to the reference genome. Details on each of these are available from the appropriate vendor. Alternatively, a lipid-based oligonucleotide tagging system is available from 10x Genomics. Oligonucleotide-antibody conjugates are available for this from external vendors, for example, BioLegend (TotalSeq A and B). It is possible to combine these samples into one library by tagging the cells in each sample with a unique identifier. Occasionally users may have a set of samples that individually have fewer than 10,000 cells each, but that can add up to 10,000 cells (so, for example, sample A has 2000 cells, sample B has 3000 cells, and sample C has 5000 cells). ![]() Generally, most users will assay 10,000 cells from one sample. The standard 10x Genomics recommendation for the library preparation protocol is that the maximum number of cells per library is 10,000. See below for more information on services and the 10x Genomics workflow in the IGL. The MPSSR also accepts cDNAs from users and can finish the library preparation for them, and can prepare hashtag and CITE-seq libraries. Training on the Chromium Controller is provided through the GPSR following which researchers can schedule use of the Chromium system for their direct use. If you prefer to prepare your own single cell DNA and libraries, the IGL Chromium platform is available for Shared Access use once you have received training from a member of the IGL. 10x Genomics library preparation and sequencing is performed through the Massively Parallel Sequencing Shared Resource.įor a Full Service 10x Genomics single cell analysis project from sample submission through sequencing, please go to the MPSSR iLab page to request a project. The Gene Profiling Shared Resource maintains the Chromium Controller system and provides support for preparation of single cell cDNA and gDNA for 10x Genomics applications. ![]() The Integrated Genomics Lab (IGL) provides support for single cell and nuclei DNA preparation and sequencing using the 10x Genomics Chromium single cell platform. ![]()
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