The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Unveiling the complexity of the maize transcriptome by single-molecule long-read sequencing
Open accessAbstract
Zea mays is an important genetic model for elucidating transcriptional networks. Uncertainties about the complete structure of mRNA transcripts limit the progress of research in this system. Here, using single-molecule sequencing technology, we produce 111,151 transcripts from 6 tissues capturing ∼70% of the genes annotated in maize RefGen_v3 genome. A large proportion of transcripts (57%) represent novel, sometimes tissue-specific, isoforms of known genes and 3% correspond to novel gene loci. In other cases, the identified transcripts have improved existing gene models. Averaging across all six tissues, 90% of the splice junctions are supported by short reads from matched tissues. In addition, we identified a large number of novel long non-coding RNAs and fusion transcripts and found that DNA methylation plays an important role in generating various isoforms. Our results show that characterization of the maize B73 transcriptome is far from complete, and that maize gene expression is more complex than previously thought.
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
Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method
Livak, K. J., & Schmittgen, T. D. (2001) · Methods · doi:10.1006/meth.2001.1262 · Cited by 180,860
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
Pan, Q., Shai, O., Lee, L. J., Frey, B. J., & Blencowe, B. J. (2008) · Nature Genetics · doi:10.1038/ng.259 · Cited by 3,951
Mutation of the mouse klotho gene leads to a syndrome resembling ageing
Kuro-o, M., Matsumura, Y., Aizawa, H., Kawaguchi, H., Suga, T., Utsugi, T., Ohyama, Y., Kurabayashi, M., Kaname, T., Kume, E., et al. (1997) · Nature · doi:10.1038/36285 · Cited by 3,837
Alternative splicing and evolution: diversification, exon definition and function
Keren, H., Lev-Maor, G., & Ast, G. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2776 · Cited by 1,082
Cartography of neurexin alternative splicing mapped by single-molecule long-read mRNA sequencing
Treutlein, B., Gokce, O., Quake, S. R., & Südhof, T. C. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1403244111 · Cited by 348
Characterization of the human ESC transcriptome by hybrid sequencing
Au, K. F., Sebastiano, V., Afshar, P. T., Durruthy, J. D., Lee, L., Williams, B. A., van Bakel, H., Schadt, E. E., Reijo-Pera, R. A., Underwood, J. G., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1320101110 · Cited by 341
Cited by
Improved maize reference genome with single-molecule technologies
Jiao, Y., Peluso, P., Shi, J., Liang, T., Stitzer, M. C., Wang, B., Campbell, M. S., Stein, J. C., Wei, X., Chin, C.-S., et al. (2017) · Nature · doi:10.1038/nature22971 · Cited by 1,210
Self-citationThe Third Revolution in Sequencing Technology
van Dijk, E. L., Jaszczyszyn, Y., Naquin, D., & Thermes, C. (2018) · Trends in Genetics · doi:10.1016/j.tig.2018.05.008 · Cited by 1,057
Piercing the dark matter: bioinformatics of long-range sequencing and mapping
Sedlazeck, F. J., Lee, H., Darby, C. A., & Schatz, M. C. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0003-4 · Cited by 530
Anvar, S. Y., Allard, G., Tseng, E., Sheynkman, G. M., de Klerk, E., Vermaat, M., Yin, R. H., Johansson, H. E., Ariyurek, Y., den Dunnen, J. T., et al. (2018) · Genome Biology · doi:10.1186/s13059-018-1418-0 · Cited by 118
Self-citationBanerjee, S., Bhandary, P., Woodhouse, M., Sen, T. Z., Wise, R. P., & Andorf, C. M. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-04120-9 · Cited by 35
Metadata
- Authors
- Wang, B., Tseng, E., Regulski, M., Clark, T. A., Hon, T., Jiao, Y., Lu, Z., Olson, A., Stein, J. C., & Ware, D.
- Venue
- Nature Communications
- Published
- 2016-06-24
- Volume
- 7
- Issue
- 1
- Pages
- 11708-11708
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W2463761386
- Cited by
- 591
- References
- 7
- FWCI
- 26.63
- 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: Unveiling the complexity of the maize transcriptome by single-molecule long-read sequencing. https://app.cochat.ai/papers/10.1038/ncomms11708
- The paper
- Wang, B., Tseng, E., Regulski, M., Clark, T. A., Hon, T., Jiao, Y., Lu, Z., Olson, A., Stein, J. C., & Ware, D. (2016). Unveiling the complexity of the maize transcriptome by single-molecule long-read sequencing. Nature Communications. https://doi.org/10.1038/ncomms11708
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.
