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SNP identification and marker assay development for high-throughput selection of soybean cyst nematode resistance

Overview of attention for article published in BMC Genomics, April 2015
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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Title
SNP identification and marker assay development for high-throughput selection of soybean cyst nematode resistance
Published in
BMC Genomics, April 2015
DOI 10.1186/s12864-015-1531-3
Pubmed ID
Authors

Zi Shi, Shiming Liu, James Noe, Prakash Arelli, Khalid Meksem, Zenglu Li

Abstract

Soybean cyst nematode (SCN) is the most economically devastating pathogen of soybean. Two resistance loci, Rhg1 and Rhg4 primarily contribute resistance to SCN race 3 in soybean. Peking and PI 88788 are the two major sources of SCN resistance with Peking requiring both Rhg1 and Rhg4 alleles and PI 88788 only the Rhg1 allele. Although simple sequence repeat (SSR) markers have been reported for both loci, they are linked markers and limited to be applied in breeding programs due to accuracy, throughput and cost of detection methods. The objectives of this study were to develop robust functional marker assays for high-throughput selection of SCN resistance and to differentiate the sources of resistance. Based on the genomic DNA sequences of 27 soybean lines with known SCN phenotypes, we have developed Kompetitive Allele Specific PCR (KASP) assays for two Single nucleotide polymorphisms (SNPs) from Glyma08g11490 for the selection of the Rhg4 resistance allele. Moreover, the genomic DNA of Glyma18g02590 at the Rhg1 locus from 11 soybean lines and cDNA of Forrest, Essex, Williams 82 and PI 88788 were fully sequenced. Pairwise sequence alignment revealed seven SNPs/insertion/deletions (InDels), five in the 6th exon and two in the last exon. Using the same 27 soybean lines, we identified one SNP that can be used to select the Rhg1 resistance allele and another SNP that can be employed to differentiate Peking and PI 88788-type resistance. These SNP markers have been validated and a strong correlation was observed between the SNP genotypes and reactions to SCN race 3 using a panel of 153 soybean lines, as well as a bi-parental population, F5-derived recombinant inbred lines (RILs) from G00-3213 x LG04-6000. Three functional SNP markers (two for Rhg1 locus and one for Rhg4 locus) were identified that could provide genotype information for the selection of SCN resistance and differentiate Peking from PI 88788 source for most germplasm lines. The robust KASP SNP marker assays were developed. In most contexts, use of one or two of these markers is sufficient for high-throughput marker-assisted selection of plants that will exhibit SCN resistance.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 <1%
Unknown 107 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 20%
Student > Ph. D. Student 20 19%
Student > Master 15 14%
Student > Doctoral Student 6 6%
Student > Bachelor 6 6%
Other 13 12%
Unknown 26 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 62 57%
Biochemistry, Genetics and Molecular Biology 6 6%
Computer Science 3 3%
Business, Management and Accounting 2 2%
Immunology and Microbiology 2 2%
Other 7 6%
Unknown 26 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 12 May 2015.
All research outputs
#6,204,813
of 22,800,560 outputs
Outputs from BMC Genomics
#2,693
of 10,649 outputs
Outputs of similar age
#73,602
of 265,109 outputs
Outputs of similar age from BMC Genomics
#79
of 271 outputs
Altmetric has tracked 22,800,560 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 10,649 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 74% 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 265,109 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 271 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.