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      Stem cell differentiation trajectories in Hydra resolved at single-cell resolution

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          Abstract

          The adult Hydra polyp continually renews all of its cells using three separate stem cell populations, but the genetic pathways enabling this homeostatic tissue maintenance are not well understood. We sequenced 24,985 Hydra single-cell transcriptomes and identified the molecular signatures of a broad spectrum of cell states, from stem cells to terminally differentiated cells. We constructed differentiation trajectories for each cell lineage and identified gene modules and putative regulators expressed along these trajectories, thus creating a comprehensive molecular map of all developmental lineages in the adult animal. In addition, we built a gene expression map of the Hydra nervous system. Our work constitutes a resource for addressing questions regarding the evolution of metazoan developmental processes and nervous system function.

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          Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo

          High-throughput mapping of cellular differentiation hierarchies from single-cell data promises to empower systematic interrogations of vertebrate development and disease. Here, we applied single-cell RNA sequencing to >92,000 cells from zebrafish embryos during the first day of development. Using a graph-based approach, we mapped a cell state landscape that describes axis patterning, germ layer formation, and organogenesis. We tested how clonally related cells traverse this landscape by developing a transposon-based barcoding approach ("TracerSeq") for reconstructing single-cell lineage histories. Clonally related cells were often restricted by the state landscape, including a case in which two independent lineages converge on similar fates. Cell fates remained restricted to this landscape in chordin-deficient embryos. We provide web-based resources for further analysis of the single-cell data.
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            Is Open Access

            Biases in Illumina transcriptome sequencing caused by random hexamer priming

            Generation of cDNA using random hexamer priming induces biases in the nucleotide composition at the beginning of transcriptome sequencing reads from the Illumina Genome Analyzer. The bias is independent of organism and laboratory and impacts the uniformity of the reads along the transcriptome. We provide a read count reweighting scheme, based on the nucleotide frequencies of the reads, that mitigates the impact of the bias.
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              Diffusion maps for high-dimensional single-cell analysis of differentiation data.

              Single-cell technologies have recently gained popularity in cellular differentiation studies regarding their ability to resolve potential heterogeneities in cell populations. Analyzing such high-dimensional single-cell data has its own statistical and computational challenges. Popular multivariate approaches are based on data normalization, followed by dimension reduction and clustering to identify subgroups. However, in the case of cellular differentiation, we would not expect clear clusters to be present but instead expect the cells to follow continuous branching lineages.
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                Author and article information

                Journal
                Science
                Science
                American Association for the Advancement of Science (AAAS)
                0036-8075
                1095-9203
                July 25 2019
                July 26 2019
                July 25 2019
                July 26 2019
                : 365
                : 6451
                : eaav9314
                Article
                10.1126/science.aav9314
                7104783
                31346039
                9a761bd2-f1ed-4fb3-b27a-b59c6cb3eb92
                © 2019

                http://www.sciencemag.org/about/science-licenses-journal-article-reuse

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