Evidence map›Paper›PMID 25713814›Full record

ArticleBioMed research international2015

De novo assembly and characterization of Oryza officinalis leaf transcriptome by using RNA-seq.

Ying Bao, Si Xu, Xiang Jing, Lu Meng, Zongyan Qin

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 26% 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

6 citing papers in PubMed, 17 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

5 authors at 1 institution in 1 country.

Ying BaoSchool of Life Science, Qufu Normal University, Qufu, Shandong 273165, China.
Si XuSchool of Life Science, Qufu Normal University, Qufu, Shandong 273165, China.
Xiang JingSchool of Life Science, Qufu Normal University, Qufu, Shandong 273165, China.
Lu MengSchool of Life Science, Qufu Normal University, Qufu, Shandong 273165, China.
Zongyan QinSchool of Life Science, Qufu Normal University, Qufu, Shandong 273165, China.
Qufu Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although endeavors have been made to identify useful wild rice genes that can be used to improve cultivated rice, the virtual reservoir of genetic variation hidden within the wild relatives of cultivated rice is largely untapped. Here, using next-generation sequencing technology, we investigated the leaf transcriptome of a wild rice O. officinalis with CC genome. Approximately 23 million reads were produced in the species leaf transcriptome analysis and de novo assembly methods constructed 68,132 unigenes. Functional annotations for the unigenes were conducted using sequence similarity comparisons against the following databases: the nonredundant nucleotide database, the nonredundant protein database, the SWISS-PROT database, the Clusters of Orthologous Groups of proteins database, the Kyoto Encyclopedia of Genes and Genomes database, the Gene Ontology Consortium database, and the InterPro domains database. In addition, a total of 476 unigenes related to disease resistance were identified in O. officinalis, and these unigenes can serve as important genetic resources for cultivated rice breeding and quality improvement. The present study broadens our understanding of the genetic background of non-AA genomic wild rice species and it also provides a bridge to extend studies to other Oryza species with CC genomes.

Indexed as

Base SequenceChromosome MappingGene Expression ProfilingGenome, PlantMolecular Sequence DataOryzaPlant LeavesPlant ProteinsRNA, PlantSequence Analysis, RNATranscriptomePlant ProteinsRNA, Plant

Identifiers

PMID25713814
PMCPMC4332758
OpenAlexW2018633437

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.