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BSTA: a targeted approach combines bulked segregant analysis with next- generation sequencing and de novo transcriptome assembly for SNP discovery in sunflower

Overview of attention for article published in BMC Genomics, September 2013
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Title
BSTA: a targeted approach combines bulked segregant analysis with next- generation sequencing and de novo transcriptome assembly for SNP discovery in sunflower
Published in
BMC Genomics, September 2013
DOI 10.1186/1471-2164-14-628
Pubmed ID
Authors

Maren Livaja, Yu Wang, Silke Wieckhorst, Grit Haseneyer, Michael Seidel, Volker Hahn, Steven J Knapp, Stefan Taudien, Chris-Carolin Schön, Eva Bauer

Abstract

Sunflower belongs to the largest plant family on earth, the genomically poorly explored Compositae. Downy mildew Plasmopara halstedii (Farlow) Berlese & de Toni is one of the major diseases of cultivated sunflower (Helianthus annuus L.). In the search for new sources of downy mildew resistance, the locus Pl(ARG)on linkage group 1 (LG1) originating from H. argophyllus is promising since it confers resistance against all known races of the pathogen. However, the mapping resolution in the Pl(ARG) region is hampered by significantly suppressed recombination and by limited availability of polymorphic markers. Here we examined a strategy developed for the enrichment of molecular markers linked to this specific genomic region. We combined bulked segregant analysis (BSA) with next-generation sequencing (NGS) and de novo assembly of the sunflower transcriptome for single nucleotide polymorphism (SNP) discovery in a sequence resource combining reads originating from two sunflower species, H. annuus and H. argophyllus.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Argentina 2 2%
Australia 1 1%
Germany 1 1%
Sweden 1 1%
United States 1 1%
Unknown 88 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 31%
Researcher 28 30%
Student > Master 9 10%
Lecturer 4 4%
Student > Doctoral Student 4 4%
Other 11 12%
Unknown 9 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 68 72%
Biochemistry, Genetics and Molecular Biology 12 13%
Medicine and Dentistry 2 2%
Unspecified 1 1%
Environmental Science 1 1%
Other 0 0%
Unknown 10 11%
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 18 September 2013.
All research outputs
#17,286,645
of 25,374,917 outputs
Outputs from BMC Genomics
#7,120
of 11,244 outputs
Outputs of similar age
#133,409
of 213,541 outputs
Outputs of similar age from BMC Genomics
#107
of 199 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 27th percentile – i.e., 27% 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 213,541 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 199 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.