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Transcriptomic analysis of wheat near-isogenic lines identifies PM19-A1 and A2 as candidates for a major dormancy QTL

Overview of attention for article published in Genome Biology, May 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Average Attention Score compared to outputs of the same age and source

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blogs
1 blog
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8 X users
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1 Facebook page

Citations

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123 Dimensions

Readers on

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132 Mendeley
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1 CiteULike
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Title
Transcriptomic analysis of wheat near-isogenic lines identifies PM19-A1 and A2 as candidates for a major dormancy QTL
Published in
Genome Biology, May 2015
DOI 10.1186/s13059-015-0665-6
Pubmed ID
Authors

Jose M. Barrero, Colin Cavanagh, Klara L. Verbyla, Josquin F.G. Tibbits, Arunas P. Verbyla, B. Emma Huang, Garry M. Rosewarne, Stuart Stephen, Penghao Wang, Alex Whan, Philippe Rigault, Matthew J. Hayden, Frank Gubler

Abstract

Next-generation sequencing technologies provide new opportunities to identify the genetic components responsible for trait variation. However, in species with large polyploid genomes, such as bread wheat, the ability to rapidly identify genes underlying quantitative trait loci (QTL) remains non-trivial. To overcome this, we introduce a novel pipeline that analyses, by RNA-sequencing, multiple near-isogenic lines segregating for a targeted QTL. We use this approach to characterize a major and widely utilized seed dormancy QTL located on chromosome 4AL. It exploits the power and mapping resolution afforded by large multi-parent mapping populations, whilst reducing complexity by using multi-allelic contrasts at the targeted QTL region. Our approach identifies two adjacent candidate genes within the QTL region belonging to the ABA-induced Wheat Plasma Membrane 19 family. One of them, PM19-A1, is highly expressed during grain maturation in dormant genotypes. The second, PM19-A2, shows changes in sequence causing several amino-acid changes between dormant and non-dormant genotypes. We confirm that PM19 genes are positive regulators of seed dormancy. The efficient identification of these strong candidates demonstrates the utility of our transcriptomic pipeline for rapid QTL to gene mapping. By using this approach we are able to provide a comprehensive genetic analysis of the major source of grain dormancy in wheat. Further analysis across a diverse panel of bread and durum wheats indicates that this important dormancy QTL predates hexaploid wheat. The use of these genes by wheat breeders could assist in the elimination of pre-harvest sprouting in wheat.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 132 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 2 2%
Australia 2 2%
Chile 1 <1%
Brazil 1 <1%
United Kingdom 1 <1%
Argentina 1 <1%
United States 1 <1%
Unknown 123 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 31%
Researcher 31 23%
Student > Doctoral Student 11 8%
Professor > Associate Professor 7 5%
Student > Bachelor 6 5%
Other 12 9%
Unknown 24 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 87 66%
Biochemistry, Genetics and Molecular Biology 15 11%
Unspecified 1 <1%
Business, Management and Accounting 1 <1%
Computer Science 1 <1%
Other 2 2%
Unknown 25 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 27 February 2016.
All research outputs
#3,111,959
of 25,373,627 outputs
Outputs from Genome Biology
#2,307
of 4,467 outputs
Outputs of similar age
#38,476
of 279,127 outputs
Outputs of similar age from Genome Biology
#42
of 73 outputs
Altmetric has tracked 25,373,627 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 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
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 279,127 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 86% of its contemporaries.
We're also able to compare this research output to 73 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.