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Identification and characterization of a high kernel weight mutant induced by gamma radiation in wheat (Triticum aestivum L.)

Overview of attention for article published in BMC Genomic Data, October 2015
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Title
Identification and characterization of a high kernel weight mutant induced by gamma radiation in wheat (Triticum aestivum L.)
Published in
BMC Genomic Data, October 2015
DOI 10.1186/s12863-015-0285-x
Pubmed ID
Authors

Xuejiao Cheng, Lingling Chai, Zhaoyan Chen, Lu Xu, Huijie Zhai, Aiju Zhao, Huiru Peng, Yingyin Yao, Mingshan You, Qixin Sun, Zhongfu Ni

Abstract

Inducing mutations are considered to be an effective way to create novel genetic variations and hence novel agronomical traits in wheat. This study was conducted to assess the genetic differences between Shi4185 and its mutant line Fu4185, produced by gamma radiation with larger grain, and to identify quantitative trait loci (QTLs) for thousand kernel weight (TKW). Phenotypic analysis revealed that the TKW of Fu4185 was much higher than that of Shi4185 under five different environments. At the genomic level, 110 of 2019 (5.4 %) simple sequence repeats (SSR) markers showed polymorphism between Shi4185 and Fu4185. Notably, 30 % (33 out of 110) polymorphic SSR markers were located on the D-genome, which was higher than the percentage of polymorphisms among natural allohexaploid wheat genotypes, indicating that mutations induced by gamma radiation could be a potential resource to enrich the genetic diversity of wheat D-genome. Moreover, one QTL, QTkw.cau-5D, located on chromosome 5DL, with Fu4185 contributing favorable alleles, was detected under different environments, especially under high temperature conditions. QTkw.cau-5D is an environmental stable QTL, which may be a desired target for genetic improvement of wheat kernel weight.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 31%
Student > Bachelor 3 8%
Student > Doctoral Student 3 8%
Professor > Associate Professor 3 8%
Student > Master 3 8%
Other 5 13%
Unknown 10 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 51%
Biochemistry, Genetics and Molecular Biology 4 10%
Environmental Science 1 3%
Arts and Humanities 1 3%
Unspecified 1 3%
Other 1 3%
Unknown 11 28%
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 21 June 2016.
All research outputs
#20,656,820
of 25,374,647 outputs
Outputs from BMC Genomic Data
#861
of 1,204 outputs
Outputs of similar age
#216,441
of 295,276 outputs
Outputs of similar age from BMC Genomic Data
#20
of 28 outputs
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So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
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We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.