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Genetic architecture of cyst nematode resistance revealed by genome-wide association study in soybean

Overview of attention for article published in BMC Genomics, August 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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Title
Genetic architecture of cyst nematode resistance revealed by genome-wide association study in soybean
Published in
BMC Genomics, August 2015
DOI 10.1186/s12864-015-1811-y
Pubmed ID
Authors

T. D. Vuong, H. Sonah, C. G. Meinhardt, R. Deshmukh, S. Kadam, R. L. Nelson, J. G. Shannon, H. T. Nguyen

Abstract

Bi-parental mapping populations have been commonly utilized to identify and characterize quantitative trait loci (QTL) controlling resistance to soybean cyst nematode (SCN, Heterodera glycines Ichinohe). Although this approach successfully mapped a large number of SCN resistance QTL, it captures only limited allelic diversity that exists in parental lines, and it also has limitations for genomic resolution. In this study, a genome-wide association study (GWAS) was performed using a diverse set of 553 soybean plant introductions (PIs) belonging to maturity groups from III to V to detect QTL/genes associated with SCN resistance to HG Type 0. Over 45,000 single nucleotide polymorphism (SNP) markers generated by the SoySNP50K iSelect BeadChip (http// www.soybase.org ) were utilized for analysis. GWAS identified 14 loci distributed over different chromosomes comprising 60 SNPs significantly associated with SCN resistance. Results also confirmed six QTL that were previously mapped using bi-parental populations, including the rhg1 and Rhg4 loci. GWAS identified eight novel QTL, including QTL on chromosome 10, which we have previously mapped by using a bi-parental population. In addition to the known loci for four simple traits, such as seed coat color, flower color, pubescence color, and stem growth habit, two traits, like lodging and pod shattering, having moderately complex inheritance have been confirmed with great precision by GWAS. The study showed that GWAS can be employed as an effective strategy for identifying complex traits in soybean and for narrowing GWAS-defined genomic regions, which facilitates positional cloning of the causal gene(s).

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 1%
Brazil 1 1%
Unknown 96 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 19%
Student > Master 17 17%
Researcher 13 13%
Student > Doctoral Student 7 7%
Student > Bachelor 4 4%
Other 14 14%
Unknown 24 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 52 53%
Biochemistry, Genetics and Molecular Biology 7 7%
Engineering 3 3%
Computer Science 2 2%
Medicine and Dentistry 2 2%
Other 3 3%
Unknown 29 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 06 May 2016.
All research outputs
#5,582,872
of 23,079,238 outputs
Outputs from BMC Genomics
#2,230
of 10,704 outputs
Outputs of similar age
#63,789
of 265,072 outputs
Outputs of similar age from BMC Genomics
#54
of 254 outputs
Altmetric has tracked 23,079,238 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,704 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 79% 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 265,072 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 75% of its contemporaries.
We're also able to compare this research output to 254 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.