Evidence map›Paper›PMID 32591023›Full record

ArticleBMC biology2020

A genome-wide survey of copy number variations reveals an asymmetric evolution of duplicated genes in rice.

Fengli Zhao, Yuexing Wang, Jianshu Zheng, Yanling Wen, Minghao Qu, Shujing Kang, Shigang Wu, Xiaojuan Deng, Kai Hong, Sanfeng Li and 13 more

Open access · goldAbstract read
In one paragraph

Article in BMC biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.6field-weighted citation impact, top 14% 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

13 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
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  5. GrameneOryza: a comprehensive resource for Oryza genomes, genetic variation, and functional data.Database : the journal of biological databases and curation · 2025
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  12. In-Depth Sequence Analysis of Bread WheatInternational journal of molecular sciences · 2021
    Article
  13. Review
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

23 authors at 4 institutions in 1 country.

Fengli ZhaoShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Yuexing WangState Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China.
Jianshu ZhengShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Yanling WenKey Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China.
Minghao QuShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Shujing KangShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Shigang WuShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Xiaojuan DengShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Kai HongShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Sanfeng LiState Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China.
Xing QinShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Zhichao WuShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Xiaobo WangShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Cheng AiShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Alun LiShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Longjun ZengShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Jiang HuState Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China.
Dali ZengState Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China.
Lianguang ShangShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Quan WangShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Qian QianShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Jue RuanShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China. ruanjue@caas.cn.
Guosheng XiongShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China. gsxiong@njau.edu.cn.ORCID 0000-0002-4312-1676
Agricultural Genomics Institute at Shenzhen · CNChina National Rice Research Institute · CNNanjing Agricultural University · CNChinese Academy of Sciences · CN

Funding

Ministry of Science and Technology of the People's Republic of China 2016YFD0101801
6 · The paper itself

Abstract

backgroundCopy number variations (CNVs) are an important type of structural variations in the genome that usually affect gene expression levels by gene dosage effect. Understanding CNVs as part of genome evolution may provide insights into the genetic basis of important agricultural traits and contribute to the crop breeding in the future. While available methods to detect CNVs utilizing next-generation sequencing technology have helped shed light on prevalence and effects of CNVs, the complexity of crop genomes poses a major challenge and requires development of additional tools.

resultsHere, we generated genomic and transcriptomic data of 93 rice (Oryza sativa L.) accessions and developed a comprehensive pipeline to call CNVs in this large-scale dataset. We analyzed the correlation between CNVs and gene expression levels and found that approximately 13% of the identified genes showed a significant correlation between their expression levels and copy numbers. Further analysis showed that about 36% of duplicate pairs were involved in pseudogenetic events while only 5% of them showed functional differentiation. Moreover, the offspring copy mainly contributed to the expression levels and seemed more likely to become a pseudogene, whereas the parent copy tended to maintain the function of ancestral gene.

conclusionWe provide a high-accuracy CNV dataset that will contribute to functional genomics studies and molecular breeding in rice. We also showed that gene dosage effect of CNVs in rice is not exponential or linear. Our work demonstrates that the evolution of duplicated genes is asymmetric in both expression levels and gene fates, shedding a new insight into the evolution of duplicated genes.

Indexed as

DNA Copy Number VariationsEvolution, MolecularGene DuplicationGenes, PlantGenome, PlantOryzaTranscriptomeAsymmetric evolutionCopy number variationDuplicated geneEvolutionary fateGene expression

Identifiers

PMID32591023
PMCPMC7318451
OpenAlexW3037835913

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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.