Project description:The generation of germline cell types from human induced pluripotent stem cells (hiPSCs) represents a key milestone toward in vitro gametogenesis, which has the potential to transform reproductive modeling and medicine. Methods to recapitulate advanced germline cell specification in vitro have relied on extensive, long term culture methods, the most notable of which is a four-month culture protocol employing xenogeneic reconstituted ovaries with mouse embryonic ovarian somatic cells. Recently, transcription factor (TF)-based methods have demonstrated the feasibility of exogenous factor expression to directly differentiate hiPSCs into cell types of interest, including various ovarian cell types. The protocols leveraged in these studies, however, utilize more local methods of factor selection, such as basic differential gene expression analysis, and lower-throughput screening strategies via iterative testing of a small set of TFs. In this work, we integrate our recently-described graph theory pipeline and highly-parallelized screening protocols to globally identify and screen 46 oogenesis-regulating TFs for their role in human germline formation. We identify ZNF281, LHX8, SOHLH1, ZGLP1, and ANHX whose combinatorial overexpression drives DDX4+ induced oogonia-like cell (iOLC) formation from hiPSCs. In contrast to previous methods, our protocol employs a simple four-day, feeder-free monolayer culture condition. We additionally demonstrate a method of post-isolation, feeder-free expansion of DDX4+ iOLCs that shows retained cell identity in vitro. We additionally identify DLX5, HHEX, and FIGLA whose individual overexpression enhances hPGCLC formation from hiPSCs. We characterize these TF-based iOLCs and hPGCLCs via gene and protein expression analyses and demonstrate their broad similarity to in vivo and in vitro-derived oogonia and primordial germ cells. Together, these results identify new regulatory factors that enhance in vitro human germ cell specification and further establish unique computational and experimental tools for human in vitro oogenesis research.

Project description:Barcode swapping results in the mislabeling of sequencing reads between multiplexed samples on the new patterned flow cell Illumina sequencing machines. This may compromise the validity of numerous genomic assays, especially for single-cell studies where many samples are routinely multiplexed together. The severity and consequences of barcode swapping for single-cell transcriptomic studies remain poorly understood. We have used two statistical approaches to robustly quantify the fraction of swapped reads in each of two plate-based single-cell RNA sequencing datasets. We found that approximately 2.5% of reads were mislabeled between samples on the HiSeq 4000 machine, which is lower than previous reports. We observed no correlation between the swapped fraction of reads and the concentration of free barcode across plates. Further- more, we have demonstrated that barcode swapping may generate complex but artefactual cell libraries in droplet-based single-cell RNA sequencing studies. To eliminate these artefacts, we have developed an algorithm to exclude individual molecules that have swapped between samples in 10X Genomics experiments, exploiting the combinatorial complexity present in the data. This permits the continued use of cutting-edge sequencing machines for droplet-based experiments while avoiding the confounding effects of barcode swapping. This data repository contains the sequencing files associated with the droplet based scRNA-seq dataset in Griffiths et al. (2018). The data presented here should purely used for technical analysis, the biological motivation is nonetheless briefly described in the following: The mammary gland is a unique organ as it undergoes most of its development during puberty and adulthood. Characterising the hierarchy of the various mammary epithelial cells and how they are regulated in response to gestation, lactation and involution is important for understanding how breast cancer develops. Recent studies have used numerous markers to enrich, isolate and characterise the different epithelial cell compartments within the adult mammary gland. However, in all of these studies only a handful of markers were used to define and trace cell populations. Therefore, there is a need for an unbiased and comprehensive description of mammary epithelial cells within the gland at different developmental stages. To this end we used single cell RNA sequencing (scRNAseq) to determine the gene expression profile of individual mammary epithelial cells across four adult developmental stages; nulliparous, mid gestation, lactation and post weaning (full natural involution).

			Action	DRS
	SRR30085152.fastq.gz	Fastqsanger.gz
	SRR30085153.fastq.gz	Fastqsanger.gz
	SRR30085154.fastq.gz	Fastqsanger.gz
	SRR30085155.fastq.gz	Fastqsanger.gz
	SRR30085156.fastq.gz	Fastqsanger.gz

Dataset Information

Rapid Human Oogonia-like Cell Specification via Combinatorial Transcription Factor-Directed Differentiation [barcode]

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