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Resistance gene enrichment sequencing (RenSeq) enables reannotation of the NB-LRR gene family from sequenced plant genomes and rapid mapping of resistance loci in segregating populations

Overview of attention for article published in Plant Journal, October 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

policy
1 policy source
twitter
57 tweeters
patent
2 patents
facebook
1 Facebook page

Citations

dimensions_citation
235 Dimensions

Readers on

mendeley
420 Mendeley
citeulike
4 CiteULike
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Title
Resistance gene enrichment sequencing (RenSeq) enables reannotation of the NB-LRR gene family from sequenced plant genomes and rapid mapping of resistance loci in segregating populations
Published in
Plant Journal, October 2013
DOI 10.1111/tpj.12307
Pubmed ID
Authors

Florian Jupe, Kamil Witek, Walter Verweij, Jadwiga Śliwka, Leighton Pritchard, Graham J. Etherington, Dan Maclean, Peter J. Cock, Richard M. Leggett, Glenn J. Bryan, Linda Cardle, Ingo Hein, Jonathan D.G. Jones

Abstract

RenSeq is a NB-LRR (nucleotide binding-site leucine-rich repeat) gene-targeted, Resistance gene enrichment and sequencing method that enables discovery and annotation of pathogen resistance gene family members in plant genome sequences. We successfully applied RenSeq to the sequenced potato Solanum tuberosum clone DM, and increased the number of identified NB-LRRs from 438 to 755. The majority of these identified R gene loci reside in poorly or previously unannotated regions of the genome. Sequence and positional details on the 12 chromosomes have been established for 704 NB-LRRs and can be accessed through a genome browser that we provide. We compared these NB-LRR genes and the corresponding oligonucleotide baits with the highest sequence similarity and demonstrated that ~80% sequence identity is sufficient for enrichment. Analysis of the sequenced tomato S. lycopersicum 'Heinz 1706' extended the NB-LRR complement to 394 loci. We further describe a methodology that applies RenSeq to rapidly identify molecular markers that co-segregate with a pathogen resistance trait of interest. In two independent segregating populations involving the wild Solanum species S. berthaultii (Rpi-ber2) and S. ruiz-ceballosii (Rpi-rzc1), we were able to apply RenSeq successfully to identify markers that co-segregate with resistance towards the late blight pathogen Phytophthora infestans. These SNP identification workflows were designed as easy-to-adapt Galaxy pipelines.

Twitter Demographics

The data shown below were collected from the profiles of 57 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 420 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 5 1%
United States 3 <1%
United Kingdom 3 <1%
Sweden 3 <1%
India 1 <1%
Austria 1 <1%
Australia 1 <1%
Norway 1 <1%
Canada 1 <1%
Other 4 <1%
Unknown 397 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 122 29%
Student > Ph. D. Student 115 27%
Student > Master 37 9%
Student > Bachelor 34 8%
Other 23 5%
Other 56 13%
Unknown 33 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 301 72%
Biochemistry, Genetics and Molecular Biology 60 14%
Engineering 7 2%
Computer Science 3 <1%
Environmental Science 2 <1%
Other 4 <1%
Unknown 43 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 39. 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 24 November 2020.
All research outputs
#713,240
of 19,151,080 outputs
Outputs from Plant Journal
#102
of 6,281 outputs
Outputs of similar age
#6,824
of 171,231 outputs
Outputs of similar age from Plant Journal
#1
of 107 outputs
Altmetric has tracked 19,151,080 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,281 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has done particularly well, scoring higher than 98% 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 171,231 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.