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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, January 2015
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Title
Population structure and genetic diversity characterization of a sunflower association mapping population using SSR and SNP markers
Published in
BMC Plant Biology, January 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.

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

Mendeley readers

The data shown below were compiled from readership statistics for 158 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 156 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 42 27%
Researcher 37 23%
Student > Master 22 14%
Student > Doctoral Student 19 12%
Student > Postgraduate 6 4%
Other 13 8%
Unknown 19 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 105 66%
Biochemistry, Genetics and Molecular Biology 19 12%
Environmental Science 3 2%
Nursing and Health Professions 2 1%
Social Sciences 1 <1%
Other 4 3%
Unknown 24 15%

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
#4,159,217
of 4,973,997 outputs
Outputs from BMC Plant Biology
#682
of 862 outputs
Outputs of similar age
#138,971
of 167,928 outputs
Outputs of similar age from BMC Plant Biology
#44
of 49 outputs
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