Evidence map›Paper›PMID 25848813›Full record

ArticleBMC plant biology2015

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

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 and 3 more

Open access · goldAbstract read
In one paragraph

Article in BMC plant biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
16.0field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 113 citations in OpenAlex.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

13 authors at 3 institutions in 2 countries.

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
National Agricultural Technology Institute · ARConsejo Nacional de Investigaciones Científicas y Técnicas · ARUniversity of Buenos Aires · AR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArgentina 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.

resultsThe 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.

conclusionThe 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.

Indexed as

Expressed Sequence TagsGenetics, PopulationGenetic VariationMicrosatellite RepeatsPolymorphism, Single NucleotideArgentinaBayes TheoremHelianthusMultivariate AnalysisPlant BreedingPolymorphism, Genetic

Identifiers

PMID25848813
PMCPMC4351844
OpenAlexW2015682850

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.