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Cited by 368

The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.

Investigating stem cells in human colon by using methylation patterns

Open access
Yatabe, Yasushi, Tavaré, Simon, Shibata, Darryl·2001·Proceedings of the National Academy of Sciences

Abstract

The stem cells that maintain human colon crypts are poorly characterized. To better determine stem cell numbers and how they divide, epigenetic patterns were used as cell fate markers. Methylation exhibits somatic inheritance and random changes that potentially record lifelong stem cell division histories as binary strings or tags in adjacent CpG sites. Methylation tag contents of individual crypts were sampled with bisulfite sequencing at three presumably neutral loci. Methylation increased with aging but varied between crypts and was mosaic within single crypts. Some crypts appeared to be quasi-clonal as they contained more unique tags than expected if crypts were maintained by single immortal stem cells. The complex epigenetic patterns were more consistent with a crypt niche model wherein multiple stem cells were present and replaced through periodic symmetric divisions. Methylation tags provide evidence that normal human crypts are long-lived, accumulate random methylation errors, and contain multiple stem cells that go through “bottlenecks” during life.

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Crossref · 10.1073/pnas.191225998

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Metadata

Authors
Yatabe, Y., Tavaré, S., & Shibata, D.
Venue
Proceedings of the National Academy of Sciences
Published
2001-08-21
Volume
98
Issue
19
Pages
10839-10844
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W1965766641
Cited by
368
References
31
FWCI
4.99
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Investigating stem cells in human colon by using methylation patterns. https://app.cochat.ai/papers/10.1073/pnas.191225998
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Yatabe, Y., Tavaré, S., & Shibata, D. (2001). Investigating stem cells in human colon by using methylation patterns. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.191225998

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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