Molecular allocation of lineage allocation and tissue group in early mouse embryos
Smith, A. Formative pluripotency: the chief section in a improvement continuum. Growth 144, 365-373 (2017).
Lawson, Ok.A., Meneses, J.J. and Pedersen, R. A. Clonal evaluation of the destiny of epiblasts throughout germline formation within the mouse embryo. Growth 113, 891-911 (1991).
Rivera-Pérez, J. A. and Hadjantonakis, A. Ok. The dynamics of morphogenesis within the early mouse embryo. Chilly Harb Spring. Perspective. Biol. 7, a015867 (2014).
Tam, P. P. & Loebel, D. A. Gene perform in mouse embryogenesis: prepare for gastrulation. Nat. Rev. Broom. eight, 368-381 (2007).
Arnold, S. J. and E. J. Roberts. Make a dedication: attribution of the cell line and structuring of the axes within the early mouse embryo. Nat. Rev. Mol. Cell Biol. 10, 91-103 (2009).
Irie, N. & Kuratani, S. The Hourglass Developmental Mannequin: A Predictor of the Fundamental Physique Plan? Growth 141, 4649-4655 (2014).
Tam, P. P. & Behringer, R. R. Mouse gastrulation: the formation of a mammalian physique plan. Mech. Dev. 68, p. 25 (1997).
Tam, P. P. & Quinlan, G. A. Mapping of vertebrate embryos. Curr. Biol. 6, 104-106 (1996).
Griffiths, J.A., Scialdone, A. and Marioni, J.C. Use of unicellular genomics to know improvement processes and selections about their destiny. Mol. Syst. Biol. 14, e 8046 (2018).
Kumar, P., Tan, Y. and Cahan, P. Understanding improvement and stem cells with the assistance of single cell gene expression analyzes. Growth 144, 17-32 (2017).
Pijuan-Sala, B. et al. A unicellular molecular map of mouse gastrulation and early organogenesis. Nature 566, 490-495 (2019).
Cao, J. et al. The monocellular transcriptional panorama of mammalian organogenesis. Nature 566, 496-502 (2019).
Nowotschin, S. et al. Emergent panorama from the endoderm of the mouse gut to the single-cell decision. Nature 569, 361-367 (2019).
Peng, G. et al. Spatial transcriptome for the molecular annotation of lineage destiny and cell id within the mid-gastrula mouse embryo. Dev. Cell 36, 681-697 (2016).
Boroviak, T. et al. Lineage-specific profiling defines the emergence and development of naive pluripotency in mammalian embryogenesis. Dev. Cell 35, 366-382 (2015).
Aibar, S. et al. SCENIC: Inference and clustering in a single-cell regulatory community. Nat. Strategies 14, 1083-1086 (2017).
Viotti, M., Nowotschin, S. and Hadjantonakis, A. Ok. SOX17 connects the morphogenesis of the intestinal endoderm and the segregation of the germinal layer. Nat. Cell Biol. 16, 1146-1156 (2014).
Fuxman Bass, J.I. et al. Use of networks to measure the similarity between genes: choice of affiliation indices. Nat. Strategies 10, 1169-1176 (2013).
Robb, L. & Tam, organizer P. P. Gastrula and embryonic construction in mice. Semin. Cell Dev. Biol. 15, 543-554 (2004).
Balmer, S., Nowotschin, S. & Hadjantonakis, A. Ok. Morphogenesis of Notochord in mice: present understanding and open questions. Dev. Dyn. 245, 547-557 (2016).
Henrique, D., E. Abranches, Verrier, L. & Storey, Ok. G. The neuromesodermal progenitors and the manufacture of the spinal twine. Growth 142, 2864-2875 (2015).
Kwon, G.S., Viotti, M. and Hadjantonakis, A.Ok. The endoderm of the mouse embryo is shaped by a large-scale dynamic intercalation of embryonic and extraembryonic lineages. Dev. Cell 15, 509-520 (2008).
Chan, M.M. et al. Molecular registration of mammalian embryogenesis. Nature 570, 77-82 (2019).
Nishioka, N. et al. The parts of the hippopotamus signaling pathway, Lats and Yap, kind a Tead4 exercise to tell apart the mouse trophectoderm from the internal cell mass. Dev. Cell 16, 398-410 (2009).
Wilson, V. & Beddington, R. S. Destiny of cells and morphogenetic motion in early primitive sequence of mice. Mech. Dev. 55, 79-89 (1996).
Briggs, J.A. et al. The dynamics of gene expression in embryogenesis of vertebrates on the single-cell decision. Science 360, eaar5780 (2018).
Peng, G., Tam, P.P., L. and Jing, N. Specification of the Early Embryo Lineage and Embryonic Stem Cells on the Daybreak of Enabling Applied sciences. Natl. Sci. Rev. four, 533-542 (2017).
Rivera-Pérez, J.A., Jones, V. and Tam, P. P. Tradition of complete mouse embryos at early phases of implantation and organogenesis: staging of improvement and strategies. Enzymol strategies. 476, 185-203 (2010).
Downs, Ok. M. & Davies, T. Staging of mouse embryos gobbling up utilizing morphological landmarks beneath a dissecting microscope. Growth 118, 1255-1266 (1993).
Chen, J. et al. Spatial transcriptomic evaluation of cryosectioned tissue samples with Geo-seq. Nat. Protoc. 12, 566-580 (2017).
Cui, G. et al. Spatiotemporal transcriptome development of early mouse embryos with Geo-seq and Auto-seq. Protoc. Exch., Https://doi.org/10.21203/rs.2.10081/v1 (2019).
Wells, J. M. and Melton, D. A. The early mouse endoderm is modeled by soluble elements derived from adjoining germ layers. Growth 127, 1563-1572 (2000).
Liu, Q. et al. Regeneration of the lungs by multipotent stem cells residing on the junction of the bronchioalveolar canals. Nat. Broom. 51, 728-738 (2019).
Kim, D. et al. TopHat2: Correct alignment of transcriptomes within the presence of insertions, deletions and gene fusions. Genome Biol. 14, R36 (2013).
Trapnell, C. et al. Differential evaluation of gene regulation at transcript decision with RNA-seq. Nat. Biotechnol. 31, 46-53 (2013).
Langfelder, P. & Horvath, S. WGCNA: an R bundle for the evaluation of weighted correlation networks. BMC Bioinformatics 9, 559 (2008).
Shannon, P. et al. Cytoscape: a software program atmosphere for built-in fashions of networks of biomolecular interactions. Genome Res. 13, 2498-2504 (2003).
from Hoon, M.J., Imoto, S., Nolan, J. and Miyano, S. Open Supply Clustering Software program. Bioinformatics 20, 1453-1454 (2004).
Kumar, S., Stecher, G. and Tamura, Ok. MEGA7: Evolutionary Molecular Genetic Evaluation Model 7.zero for Bigger Knowledge Units. Mol. Biol. Evol. 33, 1870-1874 (2016).
Qiu, X. et al. Inverted incorporation of graphs solves complicated single-cell trajectories. Nat. Strategies 14, 979-982 (2017).
Klein, C.A. et al. Mixed transcriptome and genome evaluation of distinctive micrometastatic cells. Nat. Biotechnol. 20, 387-392 (2002).
Leek, J.T., Johnson, W.E., Parker, H., Jaffe, A.E. & Storey, J., D. The sva bundle makes it doable to suppress batch results and different undesirable variations in excessive throughput experiments. Bioinformatics 28, 882-883 (2012).
Chung, N. C. & Storey, J. D. Statistical significance of the variables on the origin of the systematic variation of enormous knowledge. Bioinformatics 31, 545-554 (2015).
Zhang, W. et al. The combination of genomic, epigenomic and transcriptomic options reveals modular signatures underlying a poor prognosis in ovarian most cancers. Cell Rep. four, 542-553 (2013).
Pertea, M., Kim, D., Pertea, G.M., Leek, J.T. & Salzberg, S.L. Expression evaluation on the transcript degree of experiments on RNA-seq with HISAT, StringTie and Ballgown. Nat. Protocols 11, 1650-1667 (2016).
Stuart, T. et al. Full integration of single-cell knowledge. Cell 177, 1888-1902 (2019).
Newman, A.M. et al. Strong enumeration of cell subsets from tissue expression profiles. Nat. Strategies 12, 453-457 (2015).
Reimand, J. et al. g: Profiler – an online server for the purposeful interpretation of gene lists (replace 2016). Nucleic Acids Res. 44 (W1), W83 – W89 (2016).
Weng, M. P. & Liao, B. Y. modPhEA: mannequin organism Enrichment of the phenotype Evaluation of eukaryotic gene units. Bioinformatics 33, 3505-3507 (2017).
Cabili, M.N. et al. The integrative annotation of enormous non-coding human intergenic RNAs reveals international properties and particular subclasses. Genes Dev. 25, 1915-1927 (2011).
Harrow, J. et al. GENCODE: the reference annotation of the human genome for the ENCODE venture. Genome Res. 22, 1760-1774 (2012).
Hong, F. et al. RankProd: a bioconductive software program bundle for the detection of differentially expressed genes in a meta-analysis. Bioinformatics 22, 2825-2827 (2006).
van der Maaten, L. & Hinton, G. Viewing knowledge with the assistance of t-SNE. J. Mach. Study. Res. 9, 2579-2605 (2008).
Walker, M. G., W. Volkmuth, E. Sprinzak, D. Hodgson and T. Klingler. Prediction of the perform of a gene by evaluation of genomic expression: genes related to prostate most cancers. Genome Res. 9, 1198-1203 (1999).
Peng, H., Ruan, Z., Lengthy, F., Simpson, JH and Myers, EW V3D allow real-time 3D visualization and quantitative evaluation of organic picture datasets in massive scale. Nat. Biotechnol. 28, 348-353 (2010).
Richardson, L. et al. Database on Gene Expression in EmAGE Mouse Embryo: (2014 replace). Nucleic Acids Res. 42, D835 to D844 (2014).