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.

Development of microsatellite markers for sunflower (Helianthus annuus L.) was performed to estimate their frequency, nature (structure), levels of polymorphism, usefulness for genotype identification, and calculation of genetic relationships between inbred lines representing the species diversity. Isolation was performed from a small-insert genomic library followed by hybridization screening using oligonucleotide probes containing different nucleotide arrays. In this work, 503 unique microsatellite clones were sequenced and 271 PCR primer sequences bordering the microsatellite repeat were designed. For polymorphism assessment, 16 H. annuus germplasm accessions were checked and 170 of the primers tested were shown to be polymorphic for the selected lines. The polymorphic microsatellites produced an average of 3.5 alleles/locus and an average polymorphism information content (PIC) of 0.55. The most frequently found motifs within polymorphic simple-sequence repeats (SSRs) were: (GA)_n, (GT)_n, (AT)_n, followed by trinucleotides (ATT)_n, (TGG)_nand (ATC)_n, and the tetranucleotide (CATA)_n. Most of the 170 SSRs obtained showed important differences in the 16 reference inbred lines used for their characterization. In this work, 20 of the most informative SSRs destined to sunflower genotyping and legal fingerprinting purposes are fully described.Key words: sunflower, molecular markers, microsatellites, simple-sequence repeats.

The selection and validation of reference genes constitute a key point for gene expression analysis based on qPCR, requiring efficient normalization approaches. In this work, the expression profiles of eight genes were evaluated to identify novel reference genes for transcriptional studies associated to the senescence process in sunflower. Three alternative strategies were applied for the evaluation of gene expression stability in leaves of different ages and exposed to different treatments affecting the senescence process: algorithms implemented in geNorm, BestKeeper software, and the fitting of a statistical linear mixed model (LMModel). The results show that geNorm suggested the use of all combined genes, although identifying α-TUB1 as the most stable expressing gene. BestKeeper revealed α-TUB and β-TUB as stable genes, scoring β-TUB as the most stable one. The statistical LMModel identified α-TUB, actin, PEP, and EF-1α as stable genes in this order. The model-based approximation allows not only the estimation of systematic changes in gene expression, but also the identification of sources of random variation through the estimation of variance components, considering the experimental design applied. Validation of α-TUB and EF-1α as reference genes for expression studies of three sunflower senescence associated genes showed that the first one was more stable for the assayed conditions. We conclude that, when biological replicates are available, LMModel allows a more reliable selection under the assayed conditions. This study represents the first analysis of identification and validation of genuine reference genes for use as internal control in qPCR expression studies in sunflower, experimentally validated throughout six different controlled leaf senescence conditions.

Considering that sunflower production is expanding to arid regions, tolerance to abiotic stresses as drought, low temperatures and salinity arises as one of the main constrains nowadays. Differential organ-specific sunflower ESTs (expressed sequence tags) were previously generated by a subtractive hybridization method that included a considerable number of putative abiotic stress associated sequences. The objective of this work is to analyze concerted gene expression profiles of organ-specific ESTs by fluorescence microarray assay, in response to high sodium chloride concentration and chilling treatments with the aim to identify and follow up candidate genes for early responses to abiotic stress in sunflower.