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Cited by 531Cancer-related molecular mechanisms researchGenomics and Chromatin DynamicsRNA Research and Splicing

The Antisense Transcriptomes of Human Cells

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He, Yiping, Vogelstein, Bert, Velculescu, Victor E., Papadopoulos, Nickolas, Kinzler, Kenneth W.·2008·Science
DOI 10.1126/science.1163853PMC PMC2824178
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Abstract

Transcription in mammalian cells can be assessed at a genome-wide level, but it has been difficult to reliably determine whether individual transcripts are derived from the plus or minus strands of chromosomes. This distinction can be critical for understanding the relationship between known transcripts (sense) and the complementary antisense transcripts that may regulate them. Here, we describe a technique that can be used to (i) identify the DNA strand of origin for any particular RNA transcript, and (ii) quantify the number of sense and antisense transcripts from expressed genes at a global level. We examined five different human cell types and in each case found evidence for antisense transcripts in 2900 to 6400 human genes. The distribution of antisense transcripts was distinct from that of sense transcripts, was nonrandom across the genome, and differed among cell types. Antisense transcripts thus appear to be a pervasive feature of human cells, which suggests that they are a fundamental component of gene regulation.

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  • NATs are categorized into two groups: one complementary in situ with its sense counterpart partially or completely, and one non-overlapping with the sense transcript but complementary to DNA at specific gene boundaries.

    “Initially, they have been categorized within two different groups: On the one hand, there is the NAT group, which is complementary in situ with its sense counterpart, partially or completely. The second group is non-overlapping with the sense transcript, but still complementary to the DNA at specific gene boundaries.”

    From Revisiting Epigenetics Fundamentals and Its Biomedical Implications (2024) · cites this paper as [65]

    The passages labeled Abstract (page unavailable) report antisense tags in exons and near gene promoters and terminators, supporting the claim’s general distinction between transcribed regions and gene boundaries. They do not classify NATs into the two stated groups or establish that boundary-associated antisense transcripts do not overlap their sense counterparts. The paper’s three S, AS, and SAS classes categorize genes by tag ratios, not NATs by overlap. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • Sense transcripts of NATs can be imprinted, polyadenylated, and spliced, but this may be less common than conventional sense and protein-coding pairs.

    “In the same manner, their sense transcripts can be imprinted, polyadenylated, and spliced; however, this event might become less common than the conventional sense and protein-coding pairs [65].”

    From Revisiting Epigenetics Fundamentals and Its Biomedical Implications (2024) · cites this paper as [65]

    The supplied passage on imprinted genes (section labeled Abstract; page unavailable) notes examples of antisense transcripts associated with imprinted genes. The splicing passage reports that about 1% of antisense fragments, versus more than 20% of sense fragments, showed a spliced pattern. Neither passage establishes that the sense transcripts of NATs are polyadenylated or that the claimed features are less common than in conventional sense protein-coding pairs. (LLM, conf=0.79)

    Experimental — accuracy not yet measured

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Cites

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Research works printed but not linked: 25

  1. [1]Brown PO Botstein D Nat Genet 1999 21 33 9915498
  2. [2]Velculescu VE Cell 1997 88 243 9008165
  3. [3]Lapidot M Pilpel Y EMBO Rep 2006 7 1216 17139297 PMC1794690
  4. [4]Mazo A Hodgson JW Petruk S Sedkov Y Brock HW J Cell Sci 2007 120 2755 17690303
  5. [5]Timmons JA Good L Biochem Soc Trans 2006 34 1148 17073772
  6. [6]Kapranov P Willingham AT Gingeras TR Nat Rev Genet 2007 8 413 17486121
  7. [7]Yazgan O Krebs JE Biochem Cell Biol 2007 85 484 17713583
  8. [8]Chen J Nucleic Acids Res 2004 32 4812 15356298 PMC519112
  9. [9]Fahey ME Moore TF Higgins DG Comp Funct Genomics 2002 3 244 18628857 PMC2447278
  10. [10]Lehner B Williams G Campbell RD Sanderson CM Trends Genet 2002 18 63 11818131
  11. [11]Shendure J Church GM Genome Biol 2002 3 RESEARCH0044 PMC126869 12225583
  12. [12]Yelin R Nat Biotechnol 2003 21 379 12640466
  13. [13]Kiyosawa H Yamanaka I Osato N Kondo S Hayashizaki Y Genome Res 2003 13 1324 12819130 PMC403655
  14. [14]Lipman DJ Nucleic Acids Res 1997 25 3580 9278476 PMC146938
  15. [15]Carmichael GG Nat Biotechnol 2003 21 371 12665819
  16. [17]Okazaki Y Nature 2002 420 563 12466851
  17. [18]Kampa D Genome Res 2004 14 331 14993201 PMC353210
  18. [20]Simpson AJ de Souza SJ Camargo AA Brentani RR Comp Funct Genomics 2001 2 169 18628909 PMC2447206
  19. [21]Peters BA Genome Res 2007 17 287 17267814 PMC1800919
  20. [22]Sultan M Science 2008 321 956 18599741
  21. [23]Mortazavi A Williams BA McCue K Schaeffer L Wold B Nat Methods 2008 5 621 18516045 PMC13303166
  22. [24]Wu JQ Genome Biol 2008 9 R3 18173853 PMC2395237
  23. [25]Johnson JM Edwards S Shoemaker D Schadt EE Trends Genet 2005 21 93 15661355
  24. [26]Struhl K Nat Struct Mol Biol 2007 14 103 17277804
  25. [27]We thank Wayne Yu for assistance with microarrays. Supported by The Virginia and D.K. Ludwig Fund for Cancer Research and NIH grants CA57345, CA 43460, CA 62924 and CA121113. Under a licensing agreement between the Johns Hopkins University and Genzyme, technologies related to SAGE were licensed to Genzyme for commercial purposes, and B.V., V.V. and K.W.K. are entitled to a share of the royalties received by the university from the sales of the licensed technologies. The university and researchers (B.V. and K.W.K.) own Genzyme stock, which is subject to certain restrictions under university policy. The terms of these arrangements are being managed by the university in accordance with its conflict of interest policies.

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Authors
He, Y., Vogelstein, B., Velculescu, V. E., Papadopoulos, N., & Kinzler, K. W.
Affiliations
Howard Hughes Medical Institute (US)
Corresponding author
Papadopoulos, Nickolas
ORCID
Venue
Science
Publisher
American Association for the Advancement of Science (AAAS)
Published
2008-12-19
Volume
322
Issue
5909
Pages
1855-1857
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
DOI
10.1126/science.1163853
PMC
PMC2824178
OpenAlex
W2037064308
Cited by
531
References
1
Citations by year
2026: 8 · 2025: 12 · 2024: 15 · 2023: 13 · 2022: 8 · 2021: 20 · 2020: 16 · 2019: 16 · 2018: 24 · 2017: 18 · 2016: 29 · 2015: 29 · 2014: 34 · 2013: 50 · 2012: 47
FWCI
21.75
Type
journal article
Language
en
Open access
Locations
  • Science (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institutes of Health (5r01ca121113-15)
  • National Cancer Institute (CA 57345, CA-121113, CA43460, P50CA062924, R37CA057345, CA 62924)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer-related molecular mechanisms research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
Keywords
antisense transcripts, transcriptome, gene expression regulation, human cell types
MeSH terms
Cell Line, Exons, Humans, Introns, Leukocytes, Mononuclear, Promoter Regions, Genetic, RNA, Messenger, Transcription, Genetic, Gene Expression, Genome, Human, RNA, Antisense, Gene Expression Profiling, Cell Line, Tumor

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