Evidence map›Paper›PMID 24682209›Full record

ArticleScientific reports2014

A near complete snapshot of the Zea mays seedling transcriptome revealed from ultra-deep sequencing.

Jeffrey A Martin, Nicole V Johnson, Stephen M Gross, James Schnable, Xiandong Meng, Mei Wang, Devin Coleman-Derr, Erika Lindquist, Chia-Lin Wei, Shawn Kaeppler and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.6field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 29 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

Jeffrey A MartinDepartment of Energy, Joint Genome Institute, Walnut Creek, CA 94598, USA.
Nicole V JohnsonDepartment of Energy, Joint Genome Institute, Walnut Creek, CA 94598, USA.
Stephen M GrossDepartment of Energy, Joint Genome Institute, Walnut Creek, CA 94598, USA.
James SchnableDepartment of Plant and Microbial Biology, University of California, Berkeley, CA, 94720, USA.
Xiandong MengDepartment of Energy, Joint Genome Institute, Walnut Creek, CA 94598, USA.
Mei WangDepartment of Energy, Joint Genome Institute, Walnut Creek, CA 94598, USA.
Devin Coleman-DerrDepartment of Energy, Joint Genome Institute, Walnut Creek, CA 94598, USA.
Erika LindquistDepartment of Energy, Joint Genome Institute, Walnut Creek, CA 94598, USA.
Chia-Lin WeiDepartment of Energy, Joint Genome Institute, Walnut Creek, CA 94598, USA.
Shawn KaepplerDepartment of Agronomy and Great Lakes Bioenergy Research Center, University of Wisconsin, 1575 Linden Drive, Madison, WI 53706, USA.
Feng ChenDepartment of Energy, Joint Genome Institute, Walnut Creek, CA 94598, USA.
Zhong Wang1] Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA [2] Department of Energy, Joint Genome Institute, Walnut Creek, CA 94598, USA.
Joint Genome Institute · USGreat Lakes Bioenergy Research Center · USUniversity of California, Berkeley · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA-sequencing (RNA-seq) enables in-depth exploration of transcriptomes, but typical sequencing depth often limits its comprehensiveness. In this study, we generated nearly 3 billion RNA-Seq reads, totaling 341 Gb of sequence, from a Zea mays seedling sample. At this depth, a near complete snapshot of the transcriptome was observed consisting of over 90% of the annotated transcripts, including lowly expressed transcription factors. A novel hybrid strategy combining de novo and reference-based assemblies yielded a transcriptome consisting of 126,708 transcripts with 88% of expressed known genes assembled to full-length. We improved current annotations by adding 4,842 previously unannotated transcript variants and many new features, including 212 maize transcripts, 201 genes, 10 genes with undocumented potential roles in seedlings as well as maize lineage specific gene fusion events. We demonstrated the power of deep sequencing for large transcriptome studies by generating a high quality transcriptome, which provides a rich resource for the research community.

Indexed as

High-Throughput Nucleotide SequencingSeedlingsSequence Analysis, RNATranscription FactorsTranscriptomeZea maysTranscription Factors

Identifiers

PMID24682209
PMCPMC3970191
OpenAlexW2124110196

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.