Briefly, for each library, the expression matrix was loaded using the Read10X function, and the default log-normalization was performed using the NormalizeData function, followed by a cantering and scaling of the normalized values by using the ScaleData function
January 29, 2022
Briefly, for each library, the expression matrix was loaded using the Read10X function, and the default log-normalization was performed using the NormalizeData function, followed by a cantering and scaling of the normalized values by using the ScaleData function. provide additional valuable information facilitating the development of statistical methods for data normalization and batch effect correction. with Epstein-Barr virus (EBV). The viral infection selectively immortalizes resting B cells, giving rise to an actively proliferating B cell population2. LCLs exhibit a low somatic mutation rate in continuous culture, making them the preferred choice of storage for individuals genetic material3. As one of the most reliable, inexpensive, and convenient sources of cells, LCLs have been used by several large-scale genomic DNA sequencing efforts such as the International HapMap and the 1,000 Genomes projects4,5, in which a large collection of LCLs were derived from individuals of different genetic backgrounds, to document the extensive genetic variation in human populations. LCLs are also an model system for a variety of molecular and functional assays, contributing to studies in immunology, cellular biology, genetics, and other research areas6C12. It is also believed that gene expression in LCLs encompasses a wide range of metabolic pathways specific to individuals where the cells originated13. LCLs have been used in population-scale RNA sequencing projects14C16, as well as epigenomic projects17. For many LCLs used as reference strains, both genomic and transcriptomic information is available, making it possible to detect the correlation between genotype and expression level of genes and infer the potential causative function of genetic variants18. Furthermore, comparisons of gene expression profiles of LCLs between populations such as between Centre dEtude du Polymorphisme Humain C Utah (CEPH/CEU) and Yoruba in Gypenoside XVII Ibadan, Nigeria (YRI), have revealed the genetic basis underlying the differences in transcriptional activity between the two populations16,19. With the advent of single-cell RNA sequencing (scRNA-seq) technology20,21, our approach for understanding the origin, global distribution, and functional consequences of gene expression variation is ready to be extended. For example, data generated from scRNA-seq provide an unprecedented resolution of the gene expression profiles at single cell level, which allows the identification Gypenoside XVII of previously unknown subpopulations of cells and functional heterogeneity in a cell population22C24. In this study, we used scRNA-seq to assess the gene expression across thousands of cells from two LCLs: GM12878 and GM18502. Cells were prepared using a Chromium Controller (10x Genomics, Pleasanton, CA) Gypenoside XVII as described previously21 and sequenced using an Illumina Rabbit Polyclonal to Retinoic Acid Receptor beta Novaseq. 6000 sequencer. We present this dataset on the single-cell gene expression profile for more than 7,000 cells from GM12878 and more than 5,000 from GM18502. GM12878 is a popular sample that has been widely used in genomic studies. For example, it is one of three Tier 1 cell lines of the Encyclopedia of DNA Elements Gypenoside XVII (ENCODE) project17,25. GM18502, derived from the donor of African ancestry, serves as a representative sample from the divergent population. The two cell lines are part of the International HapMap project, and genotypic information is available for both of them4. We also processed and sequenced an additional sample of 1 1:1 mixture of GM12878 and GM18502 using the same scRNA-seq procedure. Our dataset presented here provides a suitable reference for Gypenoside XVII those researchers interested in performing between-populations comparisons in gene appearance on the single-cell level, aswell for those developing fresh statistical algorithms and options for scRNA-seq data analysis. Methods Cell lifestyle GM12878 and GM18502 cell lines had been purchased in the Coriell Institute for Medical Analysis. Cells had been cultured in the Roswell Recreation area Memorial Institute (RPMI) Moderate 1640 supplemented with 2mM L-glutamine and 20% of non-inactivated fetal bovine serum in T25 tissues lifestyle flasks. Flasks with 20?mL moderate were incubated over the vertical position in 37?C under 5% of skin tightening and. Cell cultures had been divide every three times for maintenance. Remember that authentication ensure that you mycoplasm contamination screening process on these newly bought cell lines weren’t undertaken within this research. Development curve Four lifestyle flasks for every cell line had been started with around 200,000 practical cells/mL to gauge the development rate of every cell line. Cells were cultured and prepared seeing that described over. Viable cellular number was approximated on a regular basis for four times. Briefly, 100 uL suspended cells from each flask had been used every complete time, to visualize the practical cells, the examples had been stained using 10 uL of Trypan Blue (0.4%), and live.