@article{da silva pereira_mollinari_schumann_clough_zeng_yencho_2021, title={The recombination landscape and multiple QTL mapping in a Solanum tuberosum cv. ‘Atlantic’-derived F1 population}, volume={126}, ISSN={0018-067X 1365-2540}, url={http://dx.doi.org/10.1038/s41437-021-00416-x}, DOI={10.1038/s41437-021-00416-x}, abstractNote={AbstractThere are many challenges involved with the genetic analyses of autopolyploid species, such as the tetraploid potato,Solanum tuberosum(2n = 4x = 48). The development of new analytical methods has made it valuable to re-analyze an F1population (n = 156) derived from a cross involving ‘Atlantic’, a widely grown chipping variety in the USA. A fully integrated genetic map with 4285 single nucleotide polymorphisms, spanning 1630 cM, was constructed with MAPpoly software. We observed that bivalent configurations were the most abundant ones (51.0~72.4% depending on parent and linkage group), though multivalent configurations were also observed (2.2~39.2%). Seven traits were evaluated over four years (2006–8 and 2014) and quantitative trait loci (QTL) mapping was carried out using QTLpoly software. Based on a multiple-QTL model approach, we detected 21 QTL for 15 out of 27 trait-year combination phenotypes. A hotspot on linkage group 5 was identified with co-located QTL for maturity, plant yield, specific gravity, and internal heat necrosis resistance evaluated over different years. Additional QTL for specific gravity and dry matter were detected with maturity-corrected phenotypes. Among the genes around QTL peaks, we found those on chromosome 5 that have been previously implicated in maturity (StCDF1) and tuber formation (POTH1). These analyses have the potential to provide insights into the biology and breeding of tetraploid potato and other autopolyploid species.}, number={5}, journal={Heredity}, publisher={Springer Science and Business Media LLC}, author={da Silva Pereira, Guilherme and Mollinari, Marcelo and Schumann, Mitchell J. and Clough, Mark E. and Zeng, Zhao-Bang and Yencho, G. Craig}, year={2021}, month={Mar}, pages={817–830} }
 @article{chavarria-perez_giordani_gracas dias_costa_massena ribeiro_benedetti_cauz-santos_pereira_bachega feijo rosa_franco garcia_et al._2020, title={Improving yield and fruit quality traits in sweet passion fruit: Evidence for genotype by environment interaction and selection of promising genotypes}, volume={15}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0232818}, abstractNote={Breeding for yield and fruit quality traits in passion fruits is complex due to the polygenic nature of these traits and the existence of genetic correlations among them. Therefore, studies focused on crop management practices and breeding using modern quantitative genetic approaches are still needed, especially for Passiflora alata, an understudied crop, popularly known as the sweet passion fruit. It is highly appreciated for its typical aroma and flavor characteristics. In this study, we aimed to reevaluate 30 genotypes previously selected for fruit quality from a 100 full-sib sweet passion fruit progeny in three environments, with a view to estimating the heritability and genetic correlations, and investigating the GEI and response to selection for nine fruit traits (weight, diameter and length of the fruit; thickness and weight of skin; weight and yield of fruit pulp; soluble solids, and yield). Pairwise genetic correlations among the fruit traits showed mostly intermediate to high values, especially those associated with fruit size and shape. Different genotype rankings were obtained regarding the predicted genetic values of weight of skin, thickness of skin and weight of pulp in each environment. Finally, we used a multiplicative selection index to select simultaneously for weight of pulp and against fruit skin thickness and weight. The response to selection was positive for all traits except soluble solids, and the 20% superior (six) genotypes were ranked. Based on the assumption that incompatibility mechanisms exist in P. alata, the selected genotypes were intercrossed in a complete diallel mating scheme. It is worth noting that all genotypes produced fruits, which is essential to guarantee yields in commercial orchards.}, number={5}, journal={PLOS ONE}, author={Chavarria-Perez, Lourdes Maria and Giordani, Willian and Gracas Dias, Kaio Olimpio and Costa, Zirlane Portugal and Massena Ribeiro, Carolina Albuquerque and Benedetti, Anderson Roberto and Cauz-Santos, Luiz Augusto and Pereira, Guilherme Silva and Bachega Feijo Rosa, Joao Ricardo and Franco Garcia, Antonio Augusto and et al.}, year={2020}, month={May} }
 @article{gemenet_lindqvist-kreuze_de boeck_da silva pereira_mollinari_zeng_craig yencho_campos_2020, title={Sequencing depth and genotype quality: accuracy and breeding operation considerations for genomic selection applications in autopolyploid crops}, volume={133}, ISSN={0040-5752 1432-2242}, url={http://dx.doi.org/10.1007/s00122-020-03673-2}, DOI={10.1007/s00122-020-03673-2}, abstractNote={Key messagePolypoid crop breeders can balance resources between density and sequencing depth, dosage information and fewer highly informative SNPs recommended, non-additive models and QTL advantages on prediction dependent on trait architecture.AbstractThe autopolyploid nature of potato and sweetpotato ensures a wide range of meiotic configurations and linkage phases leading to complex gene-action and pose problems in genotype data quality and genomic selection analyses. We used a 315-progeny biparentalF1population of hexaploid sweetpotato and a diversity panel of 380 tetraploid potato, genotyped using different platforms to answer the following questions: (i) do polyploid crop breeders need to invest more for additional sequencing depth? (ii) how many markers are required to make selection decisions? (iii) does considering non-additive genetic effects improve predictive ability (PA)? (iv) does considering dosage or quantitative trait loci (QTL) offer significant improvement to PA? Our results show that only a small number of highly informative single nucleotide polymorphisms (SNPs; ≤ 1000) are adequate for prediction in the type of populations we analyzed. We also show that considering dosage information and models considering only additive effects had the best PA for most traits, while the comparative advantage of considering non-additive genetic effects and including known QTL in the predictive model depended on trait architecture. We conclude that genomic selection can help accelerate the rate of genetic gains in potato and sweetpotato. However, application of genomic selection should be considered as part of optimizing the entire breeding program. Additionally, since the predictions in the current study are based on single populations, further studies on the effects of haplotype structure and inheritance on PA should be studied in actual multi-generation breeding populations.}, number={12}, journal={Theoretical and Applied Genetics}, publisher={Springer Science and Business Media LLC}, author={Gemenet, Dorcus C. and Lindqvist-Kreuze, Hannele and De Boeck, Bert and da Silva Pereira, Guilherme and Mollinari, Marcelo and Zeng, Zhao-Bang and Craig Yencho, G. and Campos, Hugo}, year={2020}, month={Sep}, pages={3345–3363} }
 @article{lara_santos_jank_chiari_vilela_amadeu_santos_pereira_zeng_garcia_2019, title={Genomic Selection with Allele Dosage in Panicum maximum Jacq.}, volume={9}, ISSN={["2160-1836"]}, DOI={10.1534/g3.118.200986}, abstractNote={Abstract
               Genomic selection is an efficient approach to get shorter breeding cycles in recurrent selection programs and greater genetic gains with selection of superior individuals. Despite advances in genotyping techniques, genetic studies for polyploid species have been limited to a rough approximation of studies in diploid species. The major challenge is to distinguish the different types of heterozygotes present in polyploid populations. In this work, we evaluated different genomic prediction models applied to a recurrent selection population of 530 genotypes of Panicum maximum, an autotetraploid forage grass. We also investigated the effect of the allele dosage in the prediction, i.e., considering tetraploid (GS-TD) or diploid (GS-DD) allele dosage. A longitudinal linear mixed model was fitted for each one of the six phenotypic traits, considering different covariance matrices for genetic and residual effects. A total of 41,424 genotyping-by-sequencing markers were obtained using 96-plex and Pst1 restriction enzyme, and quantitative genotype calling was performed. Six predictive models were generalized to tetraploid species and predictive ability was estimated by a replicated fivefold cross-validation process. GS-TD and GS-DD models were performed considering 1,223 informative markers. Overall, GS-TD data yielded higher predictive abilities than with GS-DD data. However, different predictive models had similar predictive ability performance. In this work, we provide bioinformatic and modeling guidelines to consider tetraploid dosage and observed that genomic selection may lead to additional gains in recurrent selection program of P. maximum.}, number={8}, journal={G3-GENES GENOMES GENETICS}, author={Lara, Leticia A. de C. and Santos, Mateus F. and Jank, Liana and Chiari, Lucimara and Vilela, Mariane de M. and Amadeu, Rodrigo R. and Santos, Jhonathan P. R. and Pereira, Guilherme da S. and Zeng, Zhao-Bang and Garcia, Antonio Augusto F.}, year={2019}, month={Aug}, pages={2463–2475} }