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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 (94th percentile)

Mentioned by

policy
3 policy sources
twitter
31 X users
patent
28 patents
facebook
1 Facebook page

Readers on

mendeley
559 Mendeley
citeulike
4 CiteULike
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Article details
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
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.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 31 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 559 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Netherlands 5 <1%
United States 3 <1%
Sweden 3 <1%
United Kingdom 3 <1%
Slovenia 1 <1%
Norway 1 <1%
Japan 1 <1%
Denmark 1 <1%
Germany 1 <1%
Other 3 <1%
Unknown 537 96%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 138 25%
Student > Ph. D. Student 135 24%
Student > Bachelor 47 8%
Student > Master 44 8%
Other 26 5%
Other 64 11%
Unknown 105 19%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 337 60%
Biochemistry, Genetics and Molecular Biology 78 14%
Engineering 8 1%
Environmental Science 5 <1%
Immunology and Microbiology 4 <1%
Other 10 2%
Unknown 117 21%
Attention Score in Context

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 09 September 2026.
All research outputs
#1,334,320
of 34,362,729 outputs
Outputs from Plant Journal
#165
of 8,896 outputs
Outputs of similar age
#10,156
of 257,960 outputs
Outputs of similar age from Plant Journal
#3
of 56 outputs
Altmetric has tracked 34,362,729 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 8,896 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. 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 257,960 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 56 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 94% of its contemporaries.