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Genetic variation and association mapping for 12 agronomic traits in indica rice

Overview of attention for article published in BMC Genomics, December 2015
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Title
Genetic variation and association mapping for 12 agronomic traits in indica rice
Published in
BMC Genomics, December 2015
DOI 10.1186/s12864-015-2245-2
Pubmed ID
Authors

Qing Lu, Mengchen Zhang, Xiaojun Niu, Shan Wang, Qun Xu, Yue Feng, Caihong Wang, Hongzhong Deng, Xiaoping Yuan, Hanyong Yu, Yiping Wang, Xinghua Wei

Abstract

Increasing rice (Oryza sativa L.) yield is a crucial challenge for modern agriculture. The ideal plant architecture is considered to be critical to enhance rice yield. Elite plant morphological traits should include compact plant type, short stature, few unproductive tillers, thick and sturdy stems and erect leaves. To reveal the genetic variations of important morphological traits, 523 germplasm accessions were genotyped using the Illumina custom-designed array containing 5,291 single nucleotide polymorphisms (SNPs) and phenotyped in two independent environments. Genome-wide association studies were performed to uncover the genotypic and phenotypic variations using a mixed linear model. In total, 126 and 172 significant loci were identified and these loci explained an average of 34.45 % and 39.09 % of the phenotypic variance in two environments, respectively, and 16 of 298 (~5.37 %) loci were detected across the two environments. For the 16 loci, 423 candidate genes were predicted in a 200-kb region (±100 kb of the peak SNP). Expression-level analyses identified four candidate genes as the most promising regulators of tiller angle. Known (NAL1 and Rc) and new significant loci showed pleiotropy and gene linkage. In addition, a long genome region covering ~1.6 Mb on chromosome 11 was identified, which may be critical for rice leaf architecture because of a high association with flag leaf length and the ratio of flag leaf length and width. The pyramid effect of the elite alleles indicated that these significant loci could be beneficial for rice plant architecture improvements in the future. Finally, 37 elite varieties were chosen as breeding donors for further rice plant architectural modifications. This study detected multiple novel loci and candidate genes related to rice morphological traits, and the work demonstrated that genome-wide association studies are powerful strategies for uncovering the genetic variations of complex traits and identifying candidate genes in rice, even though the linkage disequilibrium decayed slowly in self-pollinating species. Future research will focus on the biological validation of the candidate genes, and elite varieties will also be of interest in genome selection and breeding by design.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Philippines 1 1%
France 1 1%
Switzerland 1 1%
Unknown 68 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 21%
Student > Ph. D. Student 11 15%
Student > Master 11 15%
Student > Doctoral Student 7 10%
Student > Postgraduate 3 4%
Other 13 18%
Unknown 11 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 44 62%
Biochemistry, Genetics and Molecular Biology 11 15%
Unspecified 2 3%
Environmental Science 1 1%
Business, Management and Accounting 1 1%
Other 1 1%
Unknown 11 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 December 2015.
All research outputs
#17,778,896
of 22,835,198 outputs
Outputs from BMC Genomics
#7,569
of 10,655 outputs
Outputs of similar age
#265,188
of 390,452 outputs
Outputs of similar age from BMC Genomics
#268
of 326 outputs
Altmetric has tracked 22,835,198 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,655 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 23rd percentile – i.e., 23% of its peers scored the same or lower than it.
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