Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 251

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

A deep survey of alternative splicing in grape reveals changes in the splicing machinery related to tissue, stress condition and genotype

Open access
Vitulo, Nicola, Forcato, Claudio, Carpinelli, Elisa Corteggiani, Telatin, Andrea, Campagna, Davide, D'Angelo, Michela, Zimbello, Rosanna, Corso, Massimiliano, Vannozzi, Alessandro, Bonghi, Claudio, Lucchin, Margherita, Valle, Giorgio·2014·BMC Plant Biology

Abstract

BACKGROUND: Alternative splicing (AS) significantly enhances transcriptome complexity. It is differentially regulated in a wide variety of cell types and plays a role in several cellular processes. Here we describe a detailed survey of alternative splicing in grape based on 124 SOLiD RNAseq analyses from different tissues, stress conditions and genotypes. RESULTS: We used the RNAseq data to update the existing grape gene prediction with 2,258 new coding genes and 3,336 putative long non-coding RNAs. Several gene structures have been improved and alternative splicing was described for about 30% of the genes. A link between AS and miRNAs was shown in 139 genes where we found that AS affects the miRNA target site. A quantitative analysis of the isoforms indicated that most of the spliced genes have one major isoform and tend to simultaneously co-express a low number of isoforms, typically two, with intron retention being the most frequent alternative splicing event. CONCLUSIONS: As described in Arabidopsis, also grape displays a marked AS tissue-specificity, while stress conditions produce splicing changes to a minor extent. Surprisingly, some distinctive splicing features were also observed between genotypes. This was further supported by the observation that the panel of Serine/Arginine-rich splicing factors show a few, but very marked differences between genotypes. The finding that a part the splicing machinery can change in closely related organisms can lead to some interesting hypotheses for evolutionary adaptation, that could be particularly relevant in the response to sudden and strong selective pressures.

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 · 10.1186/1471-2229-14-99

Cites

7 of 7 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

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

Show all 7 references

Cited by

See all 251

Metadata

Authors
Vitulo, N., Forcato, C., Carpinelli, E. C., Telatin, A., Campagna, D., D'Angelo, M., Zimbello, R., Corso, M., Vannozzi, A., Bonghi, C., Lucchin, M., & Valle, G.
Venue
BMC Plant Biology
Published
2014-04-17
Volume
14
Issue
1
Pages
99-99
ISSN
1471-2229 (ISSN-L)
OpenAlex
W2165405863
Cited by
251
References
7
FWCI
9.86
Type
journal article
Language
en
Open access
gold

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: A deep survey of alternative splicing in grape reveals changes in the splicing machinery related to tissue, stress condition and genotype. https://app.cochat.ai/papers/10.1186/1471-2229-14-99
The paper
Vitulo, N., Forcato, C., Carpinelli, E. C., Telatin, A., Campagna, D., D'Angelo, M., Zimbello, R., Corso, M., Vannozzi, A., Bonghi, C., Lucchin, M., & Valle, G. (2014). A deep survey of alternative splicing in grape reveals changes in the splicing machinery related to tissue, stress condition and genotype. BMC Plant Biology. https://doi.org/10.1186/1471-2229-14-99

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.