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Modelling the genetic architecture of flowering time control in barley through nested association mapping

Overview of attention for article published in BMC Genomics, April 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

blogs
1 blog
twitter
2 tweeters

Citations

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122 Dimensions

Readers on

mendeley
173 Mendeley
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1 CiteULike
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Title
Modelling the genetic architecture of flowering time control in barley through nested association mapping
Published in
BMC Genomics, April 2015
DOI 10.1186/s12864-015-1459-7
Pubmed ID
Authors

Andreas Maurer, Vera Draba, Yong Jiang, Florian Schnaithmann, Rajiv Sharma, Erika Schumann, Benjamin Kilian, Jochen Christoph Reif, Klaus Pillen

Abstract

Barley, globally the fourth most important cereal, provides food and beverages for humans and feed for animal husbandry. Maximizing grain yield under varying climate conditions largely depends on the optimal timing of flowering. Therefore, regulation of flowering time is of extraordinary importance to meet future food and feed demands. We developed the first barley nested association mapping (NAM) population, HEB-25, by crossing 25 wild barleys with one elite barley cultivar, and used it to dissect the genetic architecture of flowering time. Upon cultivation of 1,420 lines in multi-field trials and applying a genome-wide association study, eight major quantitative trait loci (QTL) were identified as main determinants to control flowering time in barley. These QTL accounted for 64% of the cross-validated proportion of explained genotypic variance (pG). The strongest single QTL effect corresponded to the known photoperiod response gene Ppd-H1. After sequencing the causative part of Ppd-H1, we differentiated twelve haplotypes in HEB-25, whereof the strongest exotic haplotype accelerated flowering time by 11 days compared to the elite barley haplotype. Applying a whole genome prediction model including main effects and epistatic interactions allowed predicting flowering time with an unmatched accuracy of 77% of cross-validated pG. The elaborated causal models represent a fundamental step to explain flowering time in barley. In addition, our study confirms that the exotic biodiversity present in HEB-25 is a valuable toolbox to dissect the genetic architecture of important agronomic traits and to replenish the elite barley breeding pool with favorable, trait-improving exotic alleles.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 173 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
France 1 <1%
Norway 1 <1%
Canada 1 <1%
Mexico 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 166 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 45 26%
Student > Ph. D. Student 41 24%
Student > Master 23 13%
Student > Bachelor 15 9%
Student > Doctoral Student 14 8%
Other 21 12%
Unknown 14 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 128 74%
Biochemistry, Genetics and Molecular Biology 16 9%
Sports and Recreations 2 1%
Immunology and Microbiology 1 <1%
Computer Science 1 <1%
Other 6 3%
Unknown 19 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 17 July 2019.
All research outputs
#1,923,231
of 15,456,178 outputs
Outputs from BMC Genomics
#874
of 8,730 outputs
Outputs of similar age
#42,344
of 264,531 outputs
Outputs of similar age from BMC Genomics
#9
of 52 outputs
Altmetric has tracked 15,456,178 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,730 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 264,531 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.