The DOI matches its Crossref record; 67 of the 67 references it cites were found in a registry or an index.
Cell fate inclination within 2-cell and 4-cell mouse embryos revealed by single-cell RNA sequencing
Open accessAbstract
It remains an open question when and how the first cell fate decision is made in mammals. Using deep single-cell RNA-seq of matched sister blastomeres, we report highly reproducible inter-blastomere differences among 10 2-cell and five 4-cell mouse embryos. Inter-blastomere gene expression differences dominated between-embryo differences and noise, and were sufficient to cluster sister blastomeres into distinct groups. Dozens of protein-coding genes exhibited reproducible bimodal expression in sister blastomeres, which cannot be explained by random fluctuations. The protein expression of one gene out of four of these bimodal genes tested, Gadd45a, exhibited clear inter-blastomeric contrasts. We traced some of the bimodal mRNA expressions to embryonic genome activation, and others to blastomere-specific RNA depletion. Inter-blastomere differences created coexpression gene networks that were much stronger and larger than those that can possibly be created by random noise. The highly correlated gene pairs at the 4-cell stage overlapped with those showing the same directions of differential expression between inner cell mass (ICM) and trophectoderm (TE). These data substantiate the hypothesis of inter-blastomere differences in 2- and 4-cell mouse embryos, and associate these differences with ICM/TE differences.
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Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
Trapnell, C., Roberts, A., Goff, L., Pertea, G., Kim, D., Kelley, D. R., Pimentel, H., Salzberg, S. L., Rinn, J. L., & Pachter, L. (2012) · Nature Protocols · doi:10.1038/nprot.2012.016 · Cited by 12,116
The Human Genome Browser at UCSC
Kent, W. J., Sugnet, C. W., Furey, T. S., Roskin, K. M., Pringle, T. H., Zahler, A. M., & Haussler, A. D. (2002) · Genome Research · doi:10.1101/gr.229102 · Cited by 10,400
mRNA-Seq whole-transcriptome analysis of a single cell
Tang, F., Barbacioru, C., Wang, Y., Nordman, E., Lee, C., Xu, N., Wang, X., Bodeau, J., Tuch, B. B., Siddiqui, A., et al. (2009) · Nature Methods · doi:10.1038/nmeth.1315 · Cited by 3,969
Nature, Nurture, or Chance: Stochastic Gene Expression and Its Consequences
Raj, A., & van Oudenaarden, A. (2008) · Cell · doi:10.1016/j.cell.2008.09.050 · Cited by 2,593
Multipotent cell lineages in early mouse development depend on SOX2 function
Avilion, A. A., Nicolis, S. K., Pevny, L. H., Perez, L., Vivian, N., & Lovell-Badge, R. (2003) · Genes & Development · doi:10.1101/gad.224503 · Cited by 2,369
Hartigan, J. A., & Hartigan, P. M. (1985) · The Annals of Statistics · doi:10.1214/aos/1176346577 · Cited by 1,973
Single-cell RNA-Seq profiling of human preimplantation embryos and embryonic stem cells
Yan, L., Yang, M., Guo, H., Yang, L., Wu, J., Li, R., Liu, P., Lian, Y., Zheng, X., Yan, J., et al. (2013) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.2660 · Cited by 1,740
Zebrafish MiR-430 Promotes Deadenylation and Clearance of Maternal mRNAs
Giraldez, A. J., Mishima, Y., Rihel, J., Grocock, R. J., Van Dongen, S., Inoue, K., Enright, A. J., & Schier, A. F. (2006) · Science · doi:10.1126/science.1122689 · Cited by 1,647
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SC3: consensus clustering of single-cell RNA-seq data
Kiselev, V. Y., Kirschner, K., Schaub, M. T., Andrews, T., Yiu, A., Chandra, T., Natarajan, K. N., Reik, W., Barahona, M., Green, A. R., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4236 · Cited by 1,500
Classification of low quality cells from single-cell RNA-seq data
Ilicic, T., Kim, J. K., Kolodziejczyk, A. A., Bagger, F. O., McCarthy, D. J., Marioni, J. C., & Teichmann, S. A. (2016) · Genome Biology · doi:10.1186/s13059-016-0888-1 · Cited by 693
Heterogeneity in Oct4 and Sox2 Targets Biases Cell Fate in 4-Cell Mouse Embryos
Goolam, M., Scialdone, A., Graham, S. J. L., Macaulay, I. C., Jedrusik, A., Hupalowska, A., Voet, T., Marioni, J. C., & Zernicka-Goetz, M. (2016) · Cell · doi:10.1016/j.cell.2016.01.047 · Cited by 484
A test metric for assessing single-cell RNA-seq batch correction
Büttner, M., Miao, Z., Wolf, F. A., Teichmann, S. A., & Theis, F. J. (2019) · Nature Methods · doi:10.1038/s41592-018-0254-1 · Cited by 511
Dynamics of the epigenetic landscape during the maternal-to-zygotic transition
Eckersley-Maslin, M. A., Alda-Catalinas, C., & Reik, W. (2018) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-018-0008-z · Cited by 431
Metadata
- Authors
- Biase, F. H., Cao, X., & Zhong, S.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2014-08-05
- Volume
- 24
- Issue
- 11
- Pages
- 1787-1796
- ISSN
- 1088-9051 (ISSN-L)
- 1549-5469
- OpenAlex
- W2120205807
- Cited by
- 313
- References
- 67
- Type
- posted content
- Language
- en
- Open access
- bronze
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- Biase, F. H., Cao, X., & Zhong, S. (2014). Cell fate inclination within 2-cell and 4-cell mouse embryos revealed by single-cell RNA sequencing. Genome Research. https://doi.org/10.1101/gr.177725.114
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