↓ Skip to main content

Population structure and genetic diversity characterization of a sunflower association mapping population using SSR and SNP markers

Overview of attention for article published in BMC Plant Biology, February 2015
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
76 Dimensions

Readers on

mendeley
189 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Population structure and genetic diversity characterization of a sunflower association mapping population using SSR and SNP markers
Published in
BMC Plant Biology, February 2015
DOI 10.1186/s12870-014-0360-x
Pubmed ID
Authors

Carla V Filippi, Natalia Aguirre, Juan G Rivas, Jeremias Zubrzycki, Andrea Puebla, Diego Cordes, Maria V Moreno, Corina M Fusari, Daniel Alvarez, Ruth A Heinz, Horacio E Hopp, Norma B Paniego, Veronica V Lia

Abstract

Argentina has a long tradition of sunflower breeding, and its germplasm is a valuable genetic resource worldwide. However, knowledge of the genetic constitution and variability levels of the Argentinean germplasm is still scarce, rendering the global map of cultivated sunflower diversity incomplete. In this study, 42 microsatellite loci and 384 single nucleotide polymorphisms (SNPs) were used to characterize the first association mapping population used for quantitative trait loci mapping in sunflower, along with a selection of allied open-pollinated and composite populations from the germplasm bank of the National Institute of Agricultural Technology of Argentina. The ability of different kinds of markers to assess genetic diversity and population structure was also evaluated. The analysis of polymorphism in the set of sunflower accessions studied here showed that both the microsatellites and SNP markers were informative for germplasm characterization, although to different extents. In general, the estimates of genetic variability were moderate. The average genetic diversity, as quantified by the expected heterozygosity, was 0.52 for SSR loci and 0.29 for SNPs. Within SSR markers, those derived from non-coding regions were able to capture higher levels of diversity than EST-SSR. A significant correlation was found between SSR and SNP- based genetic distances among accessions. Bayesian and multivariate methods were used to infer population structure. Evidence for the existence of three different genetic groups was found consistently across data sets (i.e., SSR, SNP and SSR + SNP), with the maintainer/restorer status being the most prevalent characteristic associated with group delimitation. The present study constitutes the first report comparing the performance of SSR and SNP markers for population genetics analysis in cultivated sunflower. We show that the SSR and SNP panels examined here, either used separately or in conjunction, allowed consistent estimations of genetic diversity and population structure in sunflower breeding materials. The generated knowledge about the levels of diversity and population structure of sunflower germplasm is an important contribution to this crop breeding and conservation.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 189 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 <1%
Argentina 1 <1%
Unknown 187 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 46 24%
Researcher 40 21%
Student > Master 26 14%
Student > Doctoral Student 23 12%
Student > Bachelor 8 4%
Other 19 10%
Unknown 27 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 121 64%
Biochemistry, Genetics and Molecular Biology 25 13%
Environmental Science 2 1%
Nursing and Health Professions 2 1%
Pharmacology, Toxicology and Pharmaceutical Science 1 <1%
Other 5 3%
Unknown 33 17%
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 08 April 2015.
All research outputs
#20,273,512
of 22,805,349 outputs
Outputs from BMC Plant Biology
#2,511
of 3,244 outputs
Outputs of similar age
#302,004
of 358,560 outputs
Outputs of similar age from BMC Plant Biology
#66
of 87 outputs
Altmetric has tracked 22,805,349 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,244 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 1st percentile – i.e., 1% 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 358,560 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 87 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.