Evidence map›Paper›PMID 24160180›Full record

ArticleBMC genomics2013

Codon usage patterns in Chinese bayberry (Myrica rubra) based on RNA-Seq data.

Chao Feng, Chang-jie Xu, Yue Wang, Wen-li Liu, Xue-ren Yin, Xian Li, Ming Chen, Kun-song Chen

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
1.5field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

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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

20 citing papers in PubMed, 55 citations in OpenAlex.

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  13. The Complete Chloroplast Genomes ofInternational journal of molecular sciences · 2019
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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

8 authors at 2 institutions in 1 country.

Chao Feng
Chang-jie Xu
Yue Wang
Wen-li Liu
Xue-ren Yin
Xian Li
Ming Chen
Kun-song ChenLaboratory of Fruit Quality Biology / The State Agriculture Ministry Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Zhejiang University, Hangzhou, 310058, China. akun@zju.edu.cn.
Zhejiang University · CNZheJiang Academy of Agricultural Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCodon usage analysis has been a classical topic for decades and has significances for studies of evolution, mRNA translation, and new gene discovery, etc. While the codon usage varies among different members of the plant kingdom, indicating the necessity for species-specific study, this work has mostly been limited to model organisms. Recently, the development of deep sequencing, especial RNA-Seq, has made it possible to carry out studies in non-model species.

resultRNA-Seq data of Chinese bayberry was analyzed to investigate the bias of codon usage and codon pairs. High frequency codons (AGG, GCU, AAG and GAU), as well as low frequency ones (NCG and NUA codons) were identified, and 397 high frequency codon pairs were observed. Meanwhile, 26 preferred and 141 avoided neighboring codon pairs were also identified, which showed more significant bias than the same pairs with one or more intervening codons. Codon patterns were also analyzed at the plant kingdom, organism and gene levels. Changes during plant evolution were evident using RSCU (relative synonymous codon usage), which was even more significant than GC3s (GC content of 3rd synonymous codons). Nine GO categories were differentially and independently influenced by CAI (codon adaptation index) or GC3s, especially in 'Molecular function' category. Within a gene, the average CAI increased from 0.720 to 0.785 in the first 50 codons, and then more slowly thereafter. Furthermore, the preferred as well as avoided codons at the position just following the start codon AUG were identified and discussed in relation to the key positions in Kozak sequences.

conclusionA comprehensive codon usage Table and number of high-frequency codon pairs were established. Bias in codon usage as well as in neighboring codon pairs was observed, and the significance of this in avoiding DNA mutation, increasing protein production and regulating protein synthesis rate was proposed. Codon usage patterns at three levels were revealed and the significance in plant evolution analysis, gene function classification, and protein translation start site predication were discussed. This work promotes the study of codon biology, and provides some reference for analysis and comprehensive application of RNA-Seq data from other non-model species.

Indexed as

CodonGenome, PlantBiological EvolutionCluster AnalysisCodon, InitiatorMyricaOpen Reading FramesPrincipal Component AnalysisSequence Analysis, RNACodonCodon, Initiator

Identifiers

PMID24160180
PMCPMC4008310
OpenAlexW2024543539

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LicenceCC BY
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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.