CoChat
Sign Up
Cited by 215

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Genome-wide survey of tissue-specific microRNA and transcription factor regulatory networks in 12 tissues.

Guo, Zhiyun, Maki, Miranda, Ding, Ruofan, Yang, Yalan, zhang, Bao, Xiong, Lili·2014·Scientific Reports
DOI 10.1038/srep05150PMC PMC5381490
Open this paper in CoChat — free account

Abstract

Tissue-specific miRNAs (TS miRNA) specifically expressed in particular tissues play an important role in tissue identity, differentiation and function. However, transcription factor (TF) and TS miRNA regulatory networks across multiple tissues have not been systematically studied. Here, we manually extracted 116 TS miRNAs and systematically investigated the regulatory network of TF-TS miRNA in 12 human tissues. We identified 2,347 TF-TS miRNA regulatory relations and revealed that most TF binding sites tend to enrich close to the transcription start site of TS miRNAs. Furthermore, we found TS miRNAs were regulated widely by non-tissue specific TFs and the tissue-specific expression level of TF have a close relationship with TF-genes regulation. Finally, we describe TSmiR (http://bioeng.swjtu.edu.cn/TSmiR), a novel and web-searchable database that houses interaction maps of TF-TS miRNA in 12 tissues. Taken together, these observations provide a new suggestion to better understand the regulatory network and mechanisms of TF-TS miRNAs underlying different tissues.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/srep05150

Cites

9 of 9 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Show all 9 references

Research works printed but not linked: 49

  1. Yu, H. & Gerstein, M. Genomic analysis of the hierarchical structure of regulatory networks. Proc Natl Acad Sci U S A. 103, 14724–14731 (2006). · DOI
  2. Hobert, O. Gene regulation by transcription factors and microRNAs. Science. 319, 1785–1786 (2008). · DOI · Paper page
  3. Saito, Y., Suzuki, H. & Hibi, T. The role of microRNAs in gastrointestinal cancers. J Gastroenterol. 44 Suppl 19, 18–22 (2009). · DOI
  4. Bartel, D. P. MicroRNAs: genomics, biogenesis, mechanism and function. Cell. 116, 281–297 (2004). · DOI
  5. Filipowicz, W., Bhattacharyya, S. N. & Sonenberg, N. Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight? Nat Rev Genet. 9, 102–114 (2008). · DOI
  6. Niehrs, C. & Pollet, N. Synexpression groups in eukaryotes. Nature. 402, 483–487 (1999). · DOI
  7. Calin, G. A. et al. Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers. Proc Natl Acad Sci U S A. 101, 2999–3004 (2004). · DOI
  8. van Rooij, E. et al. A signature pattern of stress-responsive microRNAs that can evoke cardiac hypertrophy and heart failure. Proc Natl Acad Sci U S A. 103, 18255–18260 (2006). · DOI
  9. Esquela-Kerscher, A. & Slack, F. J. Oncomirs - microRNAs with a role in cancer. Nat Rev Cancer. 6, 259–269 (2006). · DOI
  10. Odom, D. T. et al. Core transcriptional regulatory circuitry in human hepatocytes. Mol Syst Biol. 2, 2006 0017 (2006). · DOI
  11. Tan, K., Tegner, J. & Ravasi, T. Integrated approaches to uncovering transcription regulatory networks in mammalian cells. Genomics. 91, 219–231 (2008). · DOI
  12. Liao, Y. L. et al. Transcriptional regulation of miR-196b by ETS2 in gastric cancer cells. Carcinogenesis. 33, 760–769 (2012). · DOI
  13. Re, A., Cora, D., Taverna, D. & Caselle, M. Genome-wide survey of microRNA-transcription factor feed-forward regulatory circuits in human. Mol Biosyst. 5, 854–867 (2009). · DOI
  14. Shalgi, R., Lieber, D., Oren, M. & Pilpel, Y. Global and local architecture of the mammalian microRNA-transcription factor regulatory network. PLoS Comput Biol. 3, e131 (2007). · DOI
  15. Saini, H. K., Griffiths-Jones, S. & Enright, A. J. Genomic analysis of human microRNA transcripts. Proc Natl Acad Sci U S A. 104, 17719–17724 (2007). · DOI
  16. Gerstein, M. B. et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 489, 91–100 (2012). · DOI
  17. Hsu, S. D. et al. miRNAMap 2.0: genomic maps of microRNAs in metazoan genomes. Nucleic Acids Res. 36, D165–169 (2008). · DOI
  18. Megraw, M. et al. MicroRNA promoter element discovery in Arabidopsis. RNA. 12, 1612–1619 (2006). · DOI
  19. Chien, C. H. et al. Identifying transcriptional start sites of human microRNAs based on high-throughput sequencing data. Nucleic Acids Res. 39, 9345–9356 (2011). · DOI
  20. Corcoran, D. L. et al. Features of mammalian microRNA promoters emerge from polymerase II chromatin immunoprecipitation data. PLoS One. 4, e5279 (2009). · DOI
  21. Ozsolak, F. et al. Chromatin structure analyses identify miRNA promoters. Genes Dev. 22, 3172–3183 (2008). · DOI
  22. Alexiou, P. et al. miRGen 2.0: a database of microRNA genomic information and regulation. Nucleic Acids Res. 38, D137–141 (2010). · DOI
  23. Bi, Y., Kim, H., Gupta, R. & Davuluri, R. V. Tree-based position weight matrix approach to model transcription factor binding site profiles. PLoS One. 6, e24210 (2011). · DOI
  24. Johnson, D. S., Mortazavi, A., Myers, R. M. & Wold, B. Genome-wide mapping of in vivo protein-DNA interactions. Science. 316, 1497–1502 (2007). · DOI · Paper page
  25. Tabach, Y. et al. Wide-scale analysis of human functional transcription factor binding reveals a strong bias towards the transcription start site. PLoS One. 2, e807 (2007). · DOI
  26. Franco, L. O., de, O. M. C. L., Hamdi, S., Sachetto-Martins, G. & de Oliveira, D. E. Distal regulatory regions restrict the expression of cis-linked genes to the tapetal cells. FEBS Lett. 517, 13–18 (2002). · DOI
  27. Jelinic, P., Stehle, J. C. & Shaw, P. The testis-specific factor CTCFL cooperates with the protein methyltransferase PRMT7 in H19 imprinting control region methylation. PLoS Biol. 4, e355 (2006). · DOI
  28. Virtue, A., Wang, H. & Yang, X. F. MicroRNAs and toll-like receptor/interleukin-1 receptor signaling. J Hematol Oncol. 5, 66 (2012). · DOI
  29. Yu, X., Lin, J., Zack, D. J. & Qian, J. Computational analysis of tissue-specific combinatorial gene regulation: predicting interaction between transcription factors in human tissues. Nucleic Acids Res. 34, 4925–4936 (2006). · DOI
  30. Lagos-Quintana, M. et al. Identification of tissue-specific microRNAs from mouse. Curr Biol. 12, 735–739 (2002). · DOI · Paper page
  31. Chen, J. F. et al. The role of microRNA-1 and microRNA-133 in skeletal muscle proliferation and differentiation. Nat Genet. 38, 228–233 (2006). · DOI
  32. Wienholds, E. et al. MicroRNA expression in zebrafish embryonic development. Science. 309, 310–311 (2005). · DOI · Paper page
  33. Liang, Y., Ridzon, D., Wong, L. & Chen, C. Characterization of microRNA expression profiles in normal human tissues. BMC Genomics. 8, 166 (2007). · DOI · Paper page
  34. Lee, E. J. et al. Systematic evaluation of microRNA processing patterns in tissues, cell lines and tumors. RNA. 14, 35–42 (2008). · DOI · Paper page
  35. Beuvink, I. et al. A novel microarray approach reveals new tissue-specific signatures of known and predicted mammalian microRNAs. Nucleic Acids Res. 35, e52 (2007). · DOI
  36. Bostjancic, E., Zidar, N., Stajer, D. & Glavac, D. MicroRNAs miR-1, miR-133a, miR-133b and miR-208 are dysregulated in human myocardial infarction. Cardiology. 115, 163–169 (2010). · DOI
  37. Fu, H. et al. Identification of human fetal liver miRNAs by a novel method. FEBS Lett. 579, 3849–3854 (2005). · DOI
  38. Bargaje, R., Hariharan, M., Scaria, V. & Pillai, B. Consensus miRNA expression profiles derived from interplatform normalization of microarray data. RNA. 16, 16–25 (2010). · DOI · Paper page
  39. Townley-Tilson, W. H., Callis, T. E. & Wang, D. MicroRNAs 1, 133 and 206: critical factors of skeletal and cardiac muscle development, function and disease. Int J Biochem Cell Biol. 42, 1252–1255 (2010). · DOI
  40. Liu, C. G. et al. An oligonucleotide microchip for genome-wide microRNA profiling in human and mouse tissues. Proc Natl Acad Sci U S A. 101, 9740–9744 (2004). · DOI · Paper page
  41. Barad, O. et al. MicroRNA expression detected by oligonucleotide microarrays: system establishment and expression profiling in human tissues. Genome Res. 14, 2486–2494 (2004). · DOI · Paper page
  42. Ramkissoon, S. H. et al. Hematopoietic-specific microRNA expression in human cells. Leuk Res. 30, 643–647 (2006). · DOI
  43. Mestdagh, P. et al. The microRNA body map: dissecting microRNA function through integrative genomics. Nucleic Acids Res. 39, e136 (2011). · DOI
  44. Baskerville, S. & Bartel, D. P. Microarray profiling of microRNAs reveals frequent coexpression with neighboring miRNAs and host genes. RNA. 11, 241–247 (2005). · DOI · Paper page
  45. Hsu, S. D. et al. miRTarBase: a database curates experimentally validated microRNA-target interactions. Nucleic Acids Res. 39, D163–169 (2011). · DOI
  46. Xiao, F. et al. miRecords: an integrated resource for microRNA-target interactions. Nucleic Acids Res. 37, D105–110 (2009). · DOI
  47. Grimson, A. et al. MicroRNA targeting specificity in mammals: determinants beyond seed pairing. Mol Cell. 27, 91–105 (2007). · DOI · Paper page
  48. Liu, X., Yu, X., Zack, D. J., Zhu, H. & Qian, J. TiGER: a database for tissue-specific gene expression and regulation. BMC Bioinformatics. 9, 271 (2008). · DOI
  49. Stark, C. et al. BioGRID: a general repository for interaction datasets. Nucleic Acids Res. 34, D535–539 (2006). · DOI · Paper page

Cited by

Sorted by citations

See all 215

Metadata

Authors
Guo, Z., Maki, M., Ding, R., Yang, Y., zhang, B., & Xiong, L.
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2014-06-03
Volume
4
Issue
1
ISSN
2045-2322
DOI
10.1038/srep05150
PMC
PMC5381490
Cited by
215
References
9
Language
en
Licence

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review