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Development of Genome-Wide Insertion and Deletion Polymorphism Markers from Next-Generation Sequencing Data in Rice

Overview of attention for article published in Rice, August 2015
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Title
Development of Genome-Wide Insertion and Deletion Polymorphism Markers from Next-Generation Sequencing Data in Rice
Published in
Rice, August 2015
DOI 10.1186/s12284-015-0063-4
Pubmed ID
Authors

Jian Liu, Jingwei Li, Jingtao Qu, Shuangyong Yan

Abstract

Next-generation sequencing technologies enable the re-sequencing of a large number of genomes and provide an unprecedented opportunity to discover numerous DNA polymorphisms throughout the genome of a species. As the second most abundant form of genetic variation, InDels, with characteristics of co-dominance, multiple alleles and high stability and density and that are easy to genotype, have received an increasing amount attention. In this work, a total of 2,329,544 InDels were identified in 1767 rice genomes; these InDels were dispersed across all 12 rice chromosomes, with one InDel marker found, on average, every 160.22 bp. There were 162,380 highly polymorphic InDels with a polymorphism information content (PIC) ≥ 0.5, contributing 1.81 % to the unique primer set. Of these highly polymorphic InDels, we also selected InDels with major allele differences (the size difference between the most and second most frequent alleles) ≥ 3 bp or 8 bp for primer design, which provided a more flexible choice for researchers. Finally, we experimentally validated 100 highly polymorphic InDels for accuracy and polymorphism. The PCR results showed that the accuracy of the InDel markers was 95.70 %, while the average PIC value was 0.56, with a range of 0.19 to 0.78; the average allele number was 3.02, with a range of 2 to 5. Our genome-wide and easily used InDel markers with high polymorphism and density in both cultivated and wild rice will undoubtedly have practical implications in rice marker-assisted breeding and will also meet the need of fine-scale genetic mapping in map-based rice gene cloning.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Indonesia 1 4%
France 1 4%
Unknown 26 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 29%
Student > Ph. D. Student 5 18%
Student > Doctoral Student 3 11%
Lecturer 1 4%
Other 1 4%
Other 3 11%
Unknown 7 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 54%
Biochemistry, Genetics and Molecular Biology 4 14%
Neuroscience 1 4%
Unknown 8 29%
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 15 August 2015.
All research outputs
#20,288,585
of 22,824,164 outputs
Outputs from Rice
#303
of 385 outputs
Outputs of similar age
#221,650
of 264,379 outputs
Outputs of similar age from Rice
#7
of 7 outputs
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So far Altmetric has tracked 385 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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