The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Deep sequencing of tomato short RNAs identifies microRNAs targeting genes involved in fruit ripening
Open accessAbstract
In plants there are several classes of 21–24-nt short RNAs that regulate gene expression. The most conserved class is the microRNAs (miRNAs), although some miRNAs are found only in specific species. We used high-throughput pyrosequencing to identify conserved and nonconserved miRNAs and other short RNAs in tomato fruit and leaf. Several conserved miRNAs showed tissue-specific expression, which, combined with target gene validation results, suggests that miRNAs may play a role in fleshy fruit development. We also identified four new nonconserved miRNAs. One of the validated targets of a novel miRNA is a member of the CTR family involved in fruit ripening. However, 62 predicted targets showing near perfect complementarity to potential new miRNAs did not validate experimentally. This suggests that target prediction of plant short RNAs could have a high false-positive rate and must therefore be validated experimentally. We also found short RNAs from a Solanaceae-specific foldback transposon, which showed a miRNA/miRNA*-like distribution, suggesting that this element may function as a miRNA gene progenitor. The other Solanaceae-specific class of short RNA was derived from an endogenous pararetrovirus sequence inserted into the tomato chromosomes. This study opens a new avenue in the field of fleshy fruit biology by raising the possibility that fruit development and ripening may be under miRNA regulation.
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.
Integrity signals
Registry
Cites
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.
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
MicroRNAs AND THEIR REGULATORY ROLES IN PLANTS
Jones-Rhoades, M. W., Bartel, D. P., & Bartel, B. (2006) · Annual Review of Plant Biology · doi:10.1146/annurev.arplant.57.032905.105218 · Cited by 2,686
Prediction of Plant MicroRNA Targets
Rhoades, M. W., Reinhart, B. J., Lim, L. P., Burge, C. B., Bartel, B., & Bartel, D. P. (2002) · Cell · doi:10.1016/s0092-8674(02)00863-2 · Cited by 2,283
microRNA-Directed Phasing during Trans-Acting siRNA Biogenesis in Plants
Allen, E., Xie, Z., Gustafson, A. M., & Carrington, J. C. (2005) · Cell · doi:10.1016/j.cell.2005.04.004 · Cited by 2,268
Reinhart, B. J., Weinstein, E. G., Rhoades, M. W., Bartel, B., & Bartel, D. P. (2002) · Genes & Development · doi:10.1101/gad.1004402 · Cited by 1,948
Novel and Stress-Regulated MicroRNAs and Other Small RNAs from Arabidopsis[W]
Sunkar, R., & Zhu, J.-K. (2004) · The Plant Cell · doi:10.1105/tpc.104.022830 · Cited by 1,935
A MicroRNA as a Translational Repressor of APETALA2 in Arabidopsis Flower Development
Chen, X. (2004) · Science · doi:10.1126/science.1088060 · Cited by 1,770
Cleavage of Scarecrow-like mRNA Targets Directed by a Class of Arabidopsis miRNA
Llave, C., Xie, Z., Kasschau, K. D., & Carrington, J. C. (2002) · Science · doi:10.1126/science.1076311 · Cited by 1,627
A uniform system for microRNA annotation
AMBROS, V., BARTEL, B., BARTEL, D. P., BURGE, C. B., CARRINGTON, J. C., CHEN, X., DREYFUSS, G., EDDY, S. R., GRIFFITHS-JONES, S., MARSHALL, M., et al. (2003) · RNA · doi:10.1261/rna.2183803 · Cited by 1,553
Manning, K., Tör, M., Poole, M., Hong, Y., Thompson, A. J., King, G. J., Giovannoni, J. J., & Seymour, G. B. (2006) · Nature Genetics · doi:10.1038/ng1841 · Cited by 1,310
A diverse and evolutionarily fluid set of microRNAs in Arabidopsis thaliana
Rajagopalan, R., Vaucheret, H., Trejo, J., & Bartel, D. P. (2006) · Genes & Development · doi:10.1101/gad.1476406 · Cited by 1,298
Metadata
- Authors
- Moxon, S., Jing, R., Szittya, G., Schwach, F., Rusholme Pilcher, R. L., Moulton, V., & Dalmay, T.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2008-07-24
- Volume
- 18
- Issue
- 10
- Pages
- 1602-1609
- ISSN
- 1088-9051 (ISSN-L)
- OpenAlex
- W2102681779
- Cited by
- 470
- References
- 47
- Type
- posted content
- Language
- en
- Open access
- bronze
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Deep sequencing of tomato short RNAs identifies microRNAs targeting genes involved in fruit ripening. https://app.cochat.ai/papers/10.1101/gr.080127.108
- The paper
- Moxon, S., Jing, R., Szittya, G., Schwach, F., Rusholme Pilcher, R. L., Moulton, V., & Dalmay, T. (2008). Deep sequencing of tomato short RNAs identifies microRNAs targeting genes involved in fruit ripening. Genome Research. https://doi.org/10.1101/gr.080127.108
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.