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Sugarcane (Saccharum sp.), a world-wide known feedstock for producing sugar, bioethanol, and energy, has an extremely complex genome due to its highly polyploid and aneuploid nature. A double digestion restriction site-associated DNA sequencing protocol (ddRADseq) was tested in four commercial sugarcane hybrids and one high-fibre biotype for the detection and potential application of single nucleotide polymorphisms (SNPs) in genetic breeding. This genotyping approach compared two Illumina sequencing platforms and different filtering schemes, with and without a reference genome. A greater number of reads were obtained with Illumina platform Novaseq6000 than with Nextseq500, being this consistent with a greater number of SNPs determined with high accuracy. Additionally, more SNPs were found using a denovo pipeline compared to de refmap pipeline of the Stacks software. Longer read size, paired-end reads and 4M reads per individual represent the most efficient combination in recovering SNPs. The optimal combination of filter parameters varied depending on the different matrices created based on the different platforms. In both matrices, the highest number of SNPs localized in the longest chromosome 1, whereas the fewest landed in the shortest chromosomes 5 and 8. Multivariate comparisons of the SNPs matrices showed closer relationships among commercial hybrids than with the high-fibre biotype. Functional analysis of the obtained SNPs, performed with the Variant Effect Predictor, demonstrated the appearance of variants throughout the sugarcane genome. The pipeline applied in this study can be exploited to identify useful molecular markers that can be used in sugarcane breeding programs to reduce selection cycles.

33 páginas, 2 tablas, 4 figuras, Background and aims: The number of plastome sequences has increased exponentially during the last decade. However, there is still little knowledge of the levels and distribution of intraspecific variation. The aims of this study were to estimate plastome diversity within Zea mays and analyse the distribution of haplotypes in connection with the landrace groups previously delimited for South American maize based on nuclear markers. Methods: We obtained the complete plastomes of 30 South American maize landraces and three teosintes by means of next-generation sequencing (NGS) and used them in combination with data from public repositories. After quality filtering, the curated data were employed to search for single-nucleotide polymorphisms, indels and chloroplast simple sequence repeats. Exact permutational contingency tests were performed to assess associations between plastome and nuclear variation. Network and Bayesian phylogenetic analyses were used to infer evolutionary relationships among haplotypes. Key results: Our analyses identified a total of 124 polymorphic plastome loci, with the intergenic regions psbE-rps18, petN-rpoB, trnL_UAG-ndhF and rpoC2-atpI exhibiting the highest marker densities. Although restricted in number, these markers allowed the discrimination of 27 haplotypes in a total of 51 Zea mays individuals. Andean and lowland South American landraces differed significantly in haplotype distribution. However, overall differentiation patterns were not informative with respect to subspecies diversification, as evidenced by the scattered distribution of maize and teosinte plastomes in both the network and Bayesian phylogenetic reconstructions. Conclusions: Knowledge of intraspecific plastome variation provides the framework for a more comprehensive understanding of evolutionary processes at low taxonomic levels and may become increasingly important for future plant barcoding efforts. Whole-plastome sequencing provided useful variability to contribute to maize phylogeographic studies. The structuring of haplotype diversity in the maize landraces examined here clearly reflects the distinction between the Andean and South American lowland gene pools previously inferred based on nuclear markers., This work was supported by the Agencia Nacional de Promoción Científica y Técnica (PICT 2012 0325, PICT 2016 1101), the Consejo Nacional de Investigaciones Científicas y Tecnológicas (PIP 11220120100416CO 2013–2015), the Instituto Nacional de Tecnología Agropecuaria (PNBIO 1131044) and the DEANN Project.