IsomiRs – the overlooked repertoire in the dynamic microRNAome
Abstract
The development of deep sequencing has enabled the identification of novel microRNAs (miRNAs), leading to a growing appreciation for the fact that individual miRNAs can be heterogeneous in length and/or sequence. These variants, termed isomiRs, can be expressed in a cell-specific manner, and numerous recent studies suggest that at least some isomiRs may affect target selection, miRNA stability, or loading into the RNA-induced silencing complex (RISC). Reports indicating differential functionality for isomiRs are currently confined to several specific variants, and although isomiRs are common, their broader biological significance is yet to be fully resolved. Here we review the growing body of evidence suggesting that isomiRs have functional differences, of which at least some appear biologically relevant, and caution researchers to take miRNA isoforms into consideration in their experiments.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
IsomiRs are related sequences with mostly 5′ and 3′ nucleotide modifications that collectively make up the totality of a given microRNA.
“IsomiRs are related sequences with mostly 5′ and 3′ nucleotide modifications that collectively make up the totality of a given microRNA (Neilsen et al. 2012).”
From Toward the human cellular microRNAome (2017) · cites this paper as Neilsen et al. 2012
Due to inexact cutting of DICER1 and DROSHA and nucleotide additions/modifications, a collection of mostly similar sequences (with most diversity on the 3′ end) make up the isomiR family of a microRNA.
“Due to the inexact cutting of DICER1 and DROSHA and nucleotide additions/modifications, a collection of mostly similar sequences (with most diversity on the 3′ end) make up the isomiR family of a microRNA (Morin et al. 2008; Neilsen et al. 2012).”
From Toward the human cellular microRNAome (2017) · cites this paper as Neilsen et al. 2012
Across the 126 cell types, 56% of nontemplate additions were adenines, followed by 41% uracils, 1% guanines, and 3% cytosines.
“Across the 126 cell types, 56% of nontemplate additions were adenines, followed by 41% uracils, 1% guanines, and 3% cytosines (Neilsen et al. 2012).”
From Toward the human cellular microRNAome (2017) · cites this paper as Neilsen et al. 2012
Cites
A Mammalian microRNA Expression Atlas Based on Small RNA Library Sequencing
Landgraf, P., Rusu, M., Sheridan, R., Sewer, A., Iovino, N., Aravin, A., Pfeffer, S., Rice, A., Kamphorst, A. O., Landthaler, M., et al. (2007) · Cell · doi:10.1016/j.cell.2007.04.040 · Cited by 3,626 · see citing works
MicroRNAs and their isomiRs function cooperatively to target common biological pathways
Cloonan, N., Wani, S., Xu, Q., Gu, J., Lea, K., Heater, S., Barbacioru, C., Steptoe, A. L., Martin, H. C., Nourbakhsh, E., et al. (2011) · Genome Biology · doi:10.1186/gb-2011-12-12-r126 · Cited by 345 · see citing works
An alternative mode of microRNA target recognition
Chi, S. W., Hannon, G. J., & Darnell, R. B. (2012) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.2230 · Cited by 328 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Regulation of miRNA strand selection: follow the leader?
Meijer, H. A., Smith, E. M., & Bushell, M. (2014) · Biochemical Society Transactions · doi:10.1042/bst20140142 · Cited by 233 · see citing works
Toward the human cellular microRNAome
McCall, M. N., Kim, M.-S., Adil, M., Patil, A. H., Lu, Y., Mitchell, C. J., Leal-Rojas, P., Xu, J., Kumar, M., Dawson, V. L., et al. (2017) · Genome Research · doi:10.1101/gr.222067.117 · Cited by 151 · see citing works
Abe, M., Naqvi, A., Hendriks, G.-J., Feltzin, V., Zhu, Y., Grigoriev, A., & Bonini, N. M. (2014) · Genes & Development · doi:10.1101/gad.226654.113 · Cited by 68 · see citing works
Bioinformatic Interrogation of 5p-arm and 3p-arm Specific miRNA Expression Using TCGA Datasets
Kuo, W.-T., Su, M.-W., Lee, Y., Chen, C.-H., Wu, C.-W., Fang, W.-L., Huang, K.-H., & Lin, W.-C. (2015) · Journal of Clinical Medicine · doi:10.3390/jcm4091798 · Cited by 30 · see citing works
Oliveira, A. C. D., Bovolenta, L. A., Figueiredo, L., Ribeiro, A. D. O., Pereira, B. J. A., de Almeida, T. R. A., Campos, V. F., Patton, J. G., & Pinhal, D. (2024) · Evolutionary Bioinformatics · doi:10.1177/11769343241263230 · Cited by 2 · see citing works
- Authors
- Neilsen, C. T., Goodall, G. J., & Bracken, C. P.
- Venue
- Trends in Genetics
- Publisher
- Elsevier BV
- Published
- 2012-11
- Volume
- 28
- Issue
- 11
- Pages
- 544-549
- ISSN
- 0168-9525
- Cited by
- 453
- References
- 3
- Language
- en
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
