BioProject

In many gene expression studies, cells are extracted by tissue dissociation and Fluorescence-Activated Cell Sorting (FACS), but the effect of these protocols on cellular transcriptomes is not well characterized and often ignored. More...

In many gene expression studies, cells are extracted by tissue dissociation and Fluorescence-Activated Cell Sorting (FACS), but the effect of these protocols on cellular transcriptomes is not well characterized and often ignored. Here, we applied single-cell mRNA sequencing (scRNA-seq) to muscle stem cells, and unexpectedly found a subpopulation that is strongly affected by the widely-used dissociation protocol that we employed. One implication of this finding is that several published transcriptomics studies may need to be reinterpreted. Importantly, we detected similar subpopulations in other single-cell datasets, suggesting that cells from other tissues might be affected by this artefact as well. Overall design: Mouse satellite cells and zebrafish fin cells were extracted from Tibialis Anterior muscles of Pax7nGFP mice and wildtype zebrafish fins, respectively. For cell extraction, traditional (Supplementary Methods) dissociation protocols that combine mechanical and enzymatic dissociation were employed, and live cells were subsequently sorted into plates using FACS. Next, single-cell mRNA sequencing (CEL-Seq or SORT-Seq (robotized version of CEL-Seq2)) was applied, and data was analyzed with RaceID2 to identify clusters. CEL-Seq samples: Manual CEL-Seq; Satellite cells (unstained); Male Pax7nGFP mice (5-7 months old); 1h collagenase-treated (default dissociation protocol); 96 cells per plate with 96 different barcodes (see "Cel-seq_barcodes_96.csv"); some primes numbers are bulk samples (see "BulkSamples_BarcodesAndNrOfCellsUsed_perCEL-Seq1-library"); Spike-ins included (see "ERCC92.fa"); No mitochondrial reads in count tables; Sequencing lanes not concatenated in fastq-files uploaded here; "Merged_CEL-Seq_AllMiceAndLibrariesMerged.csv"-file is count table with reads from all mice and libraries merged (Annotation of columns: Zx.y, where Z = mouse, x = library and y = cell barcode; bulk samples are not included any more in this file); See Supplementary Methods for details. SORT-Seq 1h and 2h dissociated samples: Robotized CEL-Seq2; Satellite cells (unstained); Male Pax7nGFP mice (5-7 months old; 8 muscles from 4 mice); One plate of 1h (default dissociation protocol) and one plate of 2h collagenase-treated cells; 384 cells per plate with each of the 96 barcodes (see "Cel-seq_barcodes_96.csv") used 4 times per plate (therefore, each plate has 4 libraries); No bulk samples included; Spike-ins included (see "ERCC92.fa"); No mitochondrial reads in count table; In some wells, we sorted no cell (internal negative control; barcodes #95 and #96 were used for empty wells); Sequencing lanes not concatenated in fastq-files uploaded here; "Merged_SORT-Seq_DissociationTimecourse.csv"-file is count table were reads from all dissociation timepoints are merged (Annotation columns: DZhx_y, where Z = 1 or 2 hours collagenase-treated, x = library and y = cell barcode); See Supplementary Methods for details. SORT-Seq MitoTracker stained samples (pilot and repeat): Robotized CEL-Seq2 samples; Satellite cells stained with MitoTracker; Female Pax7nGFP mice (1 4.7-months old mouse for pilot experiment; 3 6-months old mice for repeat experiment); 1h collagenase-treated (default dissociation protocol); 384 cells per plate with each of the 384 barcodes (see "Cel-seq_barcodes_384.csv") used 1 times per plate (therefore, each plate has 1 library); Note: pilot experiment has 263 cells (so plate was partly empty), repeat experiment done with 4 full plates; No bulk samples included; Spike-ins included (see "ERCC92.fa"); Mitochondrial reads (rows named "*__chrM") included in count tables (these were removed prior to RaceID2); In some wells, we sorted no cell (barcodes #357-#360 and #381-#384 were used for empty wells); Sequencing lanes concatenated in fastq-files uploaded here; No merged file was generated for pilot experiment (as only one library), "Merged_MitoTracker_Repeat.csv"-file is count table were reads from all plates of repeat experiment were merged (Annotation of columns: Plx_Welly, where x = plate number (1-4) and x = cell barcode); See Supplementary Methods for details. SORT-Seq zebrafish fin samples: Robotized CEL-Seq2; Fin cells (unstained; all live cells); Wildtype zebrafish; Dissociated using default fin dissociation protocol (Supplementary Methods); 384 cells per plate with each of the 384 barcodes (see "Cel-seq_barcodes_384.csv") used 1 times per plate (therefore, each plate has 1 library); Note: only merged count table file ("fin_C_E_count_table.csv", Annotation columns: Xx.py.prim.finZ, where x = cell barcode, y = plate number and Z is fish (C or E)) and no individual library count table files were uploaded to GEO for zebrafish fin data; No bulk samples included; Spike-ins not included in merged count tables file; Mitochondrial reads not included in merged count tables file; In some wells, we sorted no cell (barcodes #357-#360 and #381-#384 were used for empty wells); Sequencing lanes concatenated in fastq-files uploaded here; See Supplementary Methods for details. Less...