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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-014-0360-x) contains supplementary material, which is available to authorized users.

Restriction site-associated DNA sequencing (RADseq) and its derived protocols, such as double digest RADseq (ddRADseq), offer a flexible and highly cost-effective strategy for efficient plant genome sampling. This has become one of the most popular genotyping approaches for breeding, conservation, and evolution studies in model and non-model plant species. However, universal protocols do not always adapt well to non-model species. Herein, this study reports the development of an optimized and detailed ddRADseq protocol in Eucalyptus dunnii, a non-model species, which combines different aspects of published methodologies. The initial protocol was established using only two samples by selecting the best combination of enzymes and through optimal size selection and simplifying lab procedures. Both single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs) were determined with high accuracy after applying stringent bioinformatics settings and quality filters, with and without a reference genome. To scale it up to 24 samples, we added barcoded adapters. We also applied automatic size selection, and therefore obtained an optimal number of loci, the expected SNP locus density, and genome-wide distribution. Reliability and cross-sequencing platform compatibility were verified through dissimilarity coefficients of 0.05 between replicates. To our knowledge, this optimized ddRADseq protocol will allow users to go from the DNA sample to genotyping data in a highly accessible and reproducible way.

Sclerotinia Head Rot (SHR), a disease caused by Sclerotinia sclerotiorum, is one of the most limiting factors in sunflower production. In this study, we identified genomic loci associated with resistance to SHR to support the development of assisted breeding strategies. We genotyped 114 Recombinant Inbred Lines (RILs) along with their parental lines (PAC2 –partially resistant–and RHA266 –susceptible–) by using a 384 single nucleotide polymorphism (SNP) Illumina Oligo Pool Assay to saturate a sunflower genetic map. Subsequently, we tested these lines for SHR resistance using assisted inoculations with S. sclerotiorum ascospores. We also conducted a randomized complete-block assays with three replicates to visually score disease incidence (DI), disease severity (DS), disease intensity (DInt) and incubation period (IP) through four field trials (2010–2014). We finally assessed main effect quantitative trait loci (M-QTLs) and epistatic QTLs (E-QTLs) by composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM), respectively. As a result of this study, the improved map incorporates 61 new SNPs over candidate genes. We detected a broad range of narrow sense heritability (h2) values (1.86–59.9%) as well as 36 M-QTLs and 13 E-QTLs along 14 linkage groups (LGs). On LG1, LG10, and LG15, we repeatedly detected QTLs across field trials; which emphasizes their putative effectiveness against SHR. In all selected variables, most of the identified QTLs showed high determination coefficients, associated with moderate to high heritability values. Using markers shared with previous Sclerotinia resistance studies, we compared the QTL locations in LG1, LG2, LG8, LG10, LG11, LG15 and LG16. This study constitutes the largest report of QTLs for SHR resistance in sunflower. Further studies focusing on the regions in LG1, LG10, and LG15 harboring the detected QTLs are necessary to identify causal alleles and contribute to unraveling the complex genetic basis governing the resistance.

SARS-CoV-2 variants with concerning characteristics have emerged since the end of 2020. Surveillance of SARS-CoV-2 variants was performed on a total of 4,851 samples from the capital city and 10 provinces of Argentina, during 51 epidemiological weeks (EWs) that covered the end of the first wave and the ongoing second wave of the COVID-19 pandemic in the country (EW 44/2020 to EW 41/2021). The surveillance strategy was mainly based on Sanger sequencing of a Spike coding region that allows the identification of signature mutations associated with variants. In addition, whole-genome sequences were obtained from 637 samples. The main variants found were Gamma and Lambda, and to a lesser extent, Alpha, Zeta, and Epsilon, and more recently, Delta. Whereas, Gamma dominated in different regions of the country, both Gamma and Lambda prevailed in the most populated area, the metropolitan region of Buenos Aires. The lineages that circulated on the first wave were replaced by emergent variants in a term of a few weeks. At the end of the ongoing second wave, Delta began to be detected, replacing Gamma and Lambda. This scenario is consistent with the Latin American variant landscape, so far characterized by a concurrent increase in Delta circulation and a stabilization in the number of cases. The cost-effective surveillance protocol presented here allowed for a rapid response in a resource-limited setting, added information on the expansion of Lambda in South America, and contributed to the implementation of public health measures to control the disease spread in Argentina.