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Comparison of Kompetitive Allele Specific PCR (KASP) and genotyping by sequencing (GBS) for quality control analysis in maize

Overview of attention for article published in BMC Genomics, November 2015
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  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

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Title
Comparison of Kompetitive Allele Specific PCR (KASP) and genotyping by sequencing (GBS) for quality control analysis in maize
Published in
BMC Genomics, November 2015
DOI 10.1186/s12864-015-2180-2
Pubmed ID
Authors

Berhanu Tadesse Ertiro, Veronica Ogugo, Mosisa Worku, Biswanath Das, Michael Olsen, Maryke Labuschagne, Kassa Semagn

Abstract

Quality control (QC) analysis is an important component in maize breeding and seed systems. Genotyping by next-generation sequencing (GBS) is an emerging method of SNP genotyping, which is being increasingly adopted for discovery applications, but its suitability for QC analysis has not been explored. The objectives of our study were 1) to evaluate the level of genetic purity and identity among two to nine seed sources of 16 inbred lines using 191 Kompetitive Allele Specific PCR (KASP) and 257,268 GBS markers, and 2) compare the correlation between the KASP-based low and the GBS-based high marker density on QC analysis. Genetic purity within each seed source varied from 49 to 100 % for KASP and from 74 to 100 % for GBS. All except one of the inbred lines obtained from CIMMYT showed 98 to 100 % homogeneity irrespective of the marker type. On the contrary, only 16 and 21 % of the samples obtained from EIAR and partners showed ≥95 % purity for KASP and GBS, respectively. The genetic distance among multiple sources of the same line designation varied from 0.000 to 0.295 for KASP and from 0.004 to 0.230 for GBS. Five lines from CIMMYT showed ≤ 0.05 distance among multiple sources of the same line designation; the remaining eleven inbred lines, including two from CIMMYT and nine from Ethiopia showed higher than expected genetic distances for two or more seed sources. The correlation between the 191 KASP and 257,268 GBS markers was 0.88 for purity and 0.93 for identity. A reduction in the number of GBS markers to 1,343 decreased the correlation coefficient only by 0.03. Our results clearly showed high discrepancy both in genetic purity and identity by the origin of the seed sources (institutions) irrespective of the type of genotyping platform and number of markers used for analyses. Although there were some numerical differences between KASP and GBS, the overall conclusions reached from both methods was basically similar, which clearly suggests that smaller subset of preselected and high quality markers are sufficient for QC analysis that can easily be done using low marker density genotyping platforms, such as KASP. Results from this study would be highly relevant for plant breeders and seed system specialists.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 154 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
Chile 1 <1%
Italy 1 <1%
Brazil 1 <1%
Benin 1 <1%
Unknown 149 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 38 25%
Student > Ph. D. Student 23 15%
Student > Master 22 14%
Student > Bachelor 12 8%
Student > Postgraduate 8 5%
Other 23 15%
Unknown 28 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 101 66%
Biochemistry, Genetics and Molecular Biology 18 12%
Nursing and Health Professions 2 1%
Unspecified 1 <1%
Environmental Science 1 <1%
Other 2 1%
Unknown 29 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 July 2016.
All research outputs
#13,375,401
of 22,832,057 outputs
Outputs from BMC Genomics
#4,960
of 10,655 outputs
Outputs of similar age
#134,062
of 285,670 outputs
Outputs of similar age from BMC Genomics
#180
of 392 outputs
Altmetric has tracked 22,832,057 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,655 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 53% 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 285,670 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 52% of its contemporaries.
We're also able to compare this research output to 392 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 54% of its contemporaries.