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Early selection in segregating common bean plants for resistance to bacterial wilt
Published in Revista Ceres, 2012
The objective of this study were both the estimation of the efficiency of selection in segregating populations of common bean for the resistance to Curtobacterium and also the indication of the best time of the cycle to make the selection of resistant plants. To this end, we used converging crosses between IAC-Carioca Aruã x SCS Guará, IACCarioca Pyatã x IAC-Carioca and SCS Guará x Pérola, originating filial generations (F1, F2, F2:3 and F3:4) which were subsequently inoculated with Curtobacterium flaccumfaciens pv. Flaccumfaciens, isolate 2634, and evaluated according to a scale related to the common symptoms of the disease at 20, 40 and 60 days after inoculation. The results showed that the segregating generations of Aruã x Guará, Pyatã x Guará and Pyatã x Pérola had similar behavior in relation to resistance to the Curtobacterium symptoms. The selection is effective for the coming generations of Aruã x Guará and Pyatã x Pérola and the favorable time for distinguishing and selecting reliably segregating plants occurs between 40 and 60 days after inoculation.
Recommended citation: Morais PPP, Toaldo D, **de Andrade LRB**, Guidolin AF, and Coimbra JLM (2012) Seleção precoce em plantas segregantes de feijoeiro para resistência à murcha de Curtobacterium. [Portuguese] Revista Ceres 59(6): 803-808. https://doi.org/10.1590/S0034-737X2012000600010 https://doi.org/10.1590/S0034-737X2012000600010
Agronomic potential of genebank landrace elite accessions for common bean
Published in Scientia Agricola, 2013
Plant breeding efficiency relies mainly on genetic diversity and selection to release new cultivars. This study aimed to identify landraces with favorable characteristics that can be used as parents of segregating populations in common bean (Phaseolus vulgaris L.) breeding programs. Firstly, ten bean genotypes were selected because they showed promising agronomic performance, and the following seven adaptive traits of four commercial bean cultivars were evaluated: i) plant height; ii) diameter of the stem; iii) height of the insertion of the first pod; iv) pod number per plant; v) grain number per pod; vi) weight of a thousand grains and vii) grain yield. The accessions BAF 07, BAF 44, and BAF 45 are promising in terms of increasing plant height, and accession BAF 01, in terms of reducing plant height. The accession BAF 07 was also the most promising in terms of a plant ideotype that combines higher plant height, maximum height of the insertion of the first pod, and increment in grain yield. Moreover, the selection can be made between and within accessions, because genetic variability is also present within landraces.
Recommended citation: Bertoldo JG, Coimbra JLM, Guidolin AF, **de Andrade LRB** and Nodari RO (2014) Agronomic potential of genebank landrace elite accessions for common bean. Sci. Agric. 71: 120–125. https://www.scielo.br/pdf/sa/v71n2/a05v71n2.pdf
Genetic Vulnerability and the Relationship of Commercial Germplasms of Maize in Brazil with the Nested Association Mapping Parents
Published in PLOS ONE, 2016
A few breeding companies dominate the maize (Zea mays L.) hybrid market in Brazil: Monsanto® (35%), DuPont Pioneer® (30%), Dow Agrosciences® (15%), Syngenta® (10%) and Helix Sementes (4%). Therefore, it is important to monitor the genetic diversity in commercial germplasms as breeding practices, registration and marketing of new cultivars can lead to a significant reduction of the genetic diversity. Reduced genetic variation may lead to crop vulnerabilities, food insecurity and limited genetic gains following selection. The aim of this study was to evaluate the genetic vulnerability risk by examining the relationship between the commercial Brazilian maize germplasms and the Nested Association Mapping (NAM) Parents. For this purpose, we used the commercial hybrids with the largest market share in Brazil and the NAM parents. The hybrids were genotyped for 768 single nucleotide polymorphisms (SNPs), using the Illumina Goldengate® platform. The NAM parent genomic data, comprising 1,536 SNPs for each line, were obtained from the Panzea data bank. The population structure, genetic diversity and the correlation between allele frequencies were analyzed. Based on the estimated effective population size and genetic variability, it was found that there is a low risk of genetic vulnerability in the commercial Brazilian maize germplasms. However, the genetic diversity is lower than those found in the NAM parents. Furthermore, the Brazilian germplasms presented no close relations with most NAM parents, except B73. This indicates that B73, or its heterotic group (Iowa Stiff Stalk Synthetic), contributed to the development of the commercial Brazilian germplasms.
Recommended citation: **de Andrade LRB**, Fritsche-Neto R, Granato ISC, Sant’Ana GC, Morais PPP, Borém A (2016) Genetic Vulnerability and the Relationship of Commercial Germplasms of Maize in Brazil with the Nested Association Mapping Parents. PLOS ONE 11(10): e0163739. https://doi.org/10.1371/journal.pone.0163739 https://doi.org/10.1371/journal.pone.0163739
Identification of duplicates in cassava germplasm banks based on single-nucleotide polymorphisms (SNPs)
Published in Scientia Agricola, 2018
Genetic redundancy in cassava (Manihot esculenta Crantz) presents a challenge to efficient management of genetic resources. This study aimed to identify and define the genetic structure of duplicates in cassava germplasm from various Embrapa research units, using single-nucleotide polymorphism (SNP) markers. We evaluated 2,371 accessions with 20,712 SNPs. The identification of duplicates was performed based on multilocus genotypes (MLG), adopting a maximum genetic distance threshold of 0.05. The population structure was defined based on discriminant analysis of principal components (DAPC). A total of 1,757 unique and 614 duplicate accessions were identified. The redundancy of the collections ranged from 17 % (Belém, PA – Brazil) to 39 % (Petrolina, PE – Brazil), with an average of 21 %. This redundancy between different research units is probably due to the historical sharing of accessions, as well as collections carried out in the same region, or even to the intense germplasm exchange between farmers with different genotype names. In terms of genetic structure, the 250 principal components explained 88 % of the genetic variation of the SNP markers and defined the hierarchical structure of the duplicate cassava germplasm in 12 groups. Since heterotic groups have not yet been identified for cassava, crosses between accessions of the 12 DAPC groups may be promising. All MLGs were allocated within the same DAPC group, corroborating duplicate analyses yet still revealing high variability between groups that were quite distinct based on the first two discriminant functions. Our results contribute to optimizing the conservation of genetic resources, together with understanding diversity and its use in crop improvement.
Recommended citation: Albuquerque HYG, Oliveira EJ, Brito AC, **de Andrade LRB*, do Carmo CD, Morgante CV, Vieira EA, Moura EF, Faleiro FG (2019) de et al. Identification of duplicates in cassava germplasm banks based on single-nucleotide polymorphisms (SNPs). Scientia Agricola [online] 76(4): 328-336. https://doi.org/10.1590/1678-992X-2017-0389 https://doi.org/10.1590/1678-992X-2017-0389
Yield components and reproductive, physiological, and root traits used in early selection for nitrogen use efficiency in corn
Published in Pesquisa Agropecuária Brasileira, 2018
The objective of this work was to examine the possibility of using yield components and reproductive, physiological, and root traits in early selection for nitrogen use efficiency (NUE) in corn. Sixty-four inbred lines were evaluated under two nitrogen fertilization levels: ideal and low. The evaluations were performed at three phenological stages: eight fully-expanded leaves, tasseling stage, and physiological maturity. It is possible to select superior lines for NUE, but the yield components did not show differential behavior under the different nitrogen levels evaluated. Root, reproductive, and physiological traits are not promising for early selection of corn lines with high NUE. Likewise, the eight-leaves and tasseling stages were not promising for this purpose, since NUE should be estimated taking grain yield into account. However, indirect selection for NUE can be performed via number of ears or using the selection index considering number and weight of ears.
Recommended citation: Morais, PPP, e Sousa MB, Galli G, **de Andrade LRB**, Fritsche-Neto R, Borém A (2018) Yield components and reproductive, physiological, and root traits used in early selection for nitrogen use efficiency in corn. Pesquisa Agropecuária Brasileira [online]. 53(5): 620-632. https://doi.org/10.1590/S0100-204X2018000500011 https://doi.org/10.1590/S0100-204X2018000500011
Cassava yield traits predicted by genomic selection methods
Published in PLOS ONE, 2019
Genomic selection (GS) has been used to optimize genetic gains when phenotypic selection is considered costly and difficult to measure. The objective of this work was to evaluate the efficiency and consistency of GS prediction for cassava yield traits (Manihot esculenta Crantz) using different methods, taking into account the effect of population structure. BLUPs and deregressed BLUPs were obtained for 888 cassava accessions and evaluated for fresh root yield, dry root yield and dry matter content in roots in 21 trials conducted from 2011 to 2016. The deregressed BLUPs obtained for the accessions from a 48K single nucleotide polymorphism dataset were used for genomic predictions based on the BayesB, BLASSO, RR-BLUP, G-BLUP and RKHS methods. The accessions’ BLUPs were used in the validation step using four cross-validation strategies, taking into account population structure and different GS methods. Similar estimates of predictive ability and bias were identified for the different genomic selection methods in the first cross-validation strategy. Lower predictive ability was observed for fresh root yield (0.4569 –RR-BLUP to 0.4756—RKHS) and dry root yield (0.4689–G-BLUP to 0.4818—RKHS) in comparison with dry matter content (0.5655–BLASSO to 0.5670–RKHS). However, the RKHS method exhibited higher efficiency and consistency in most of the validation scenarios in terms of prediction ability for fresh root yield and dry root yield. The correlations of the genomic estimated breeding values between the genomic selection methods were quite high (0.99–1.00), resulting in high coincidence of clone selection regardless of the genomic selection method. The deviance analyses within and between the validation clusters formed by the discriminant analysis of principal components were significant for all traits. Therefore, this study indicated that i) the prediction of dry matter content was more accurate compared to that of yield traits, possibly as a result of the smaller influence of non-additive genetic effects; ii) the RKHS method resulted in high and stable prediction ability in most of the validation scenarios; and iii) some kinship between the validation and training populations is desirable in order for genomic selection to succeed due to the significant effect of population structure on genomic selection predictions.
Recommended citation: **de Andrade LRB**, e Sousa MB, Oliveira EJ, de Resende MDV, Azevedo CF (2019) Cassava yield traits predicted by genomic selection methods. PLOS ONE 14(11): e0224920. https://doi.org/10.1371/journal.pone.0224920 https://doi.org/10.1371/journal.pone.0224920
Using public databases for genomic prediction of tropical maize lines
Published in Plant Breeding, 2020
In this paper, the aims were (a) to test the usefulness of using genomic and phenotypic information from public databases (open access) to predict genetic values for tropical maize inbred lines regarding plant and ear height; (b) to identify how the population structure, the use of optimized training sets (OTSs) and the amount of information originating from public databases affect the predictive ability. Thus, 29 training sets (TSs) were defined considering three diversity panels: the University of São Paulo (USP—validation set (VS)) and the ASSO and USDA North Central Regional Plant Introduction Station (NCRPIS) (external public panels—predictors), which were divided into four scenarios with different TS configurations. We showed that it is possible to use public datasets as a primary TS and that population structure can modify the predictive abilities of GS. In the four scenarios proposed, very large or very small sets did not provide predictive abilities over 0.53 for GS. However, OTSs composed of 250 individuals were sufficient to achieve predictive abilities over this limit.
Recommended citation: Morais PPP, Akdemir D, **de Andrade LRB**, Jannink JL, Fritsche-Neto R, Borém A, Alves FC, Lyra DH, Granato ISC (2020) Using public databases for genomic prediction of tropical maize lines. Plant Breeding. https://doi.org/10.1111/pbr.12827 https://doi.org/10.1111/pbr.12827
Large-scale genome-wide association study, using historical data, identifies conserved genetic architecture of cyanogenic glucoside content in cassava (Manihot esculenta Crantz) root
Published in The Plant Journal, 2020
Manihot esculenta (cassava) is a root crop originating from South America that is a major staple in the tropics, including in marginal environments. This study focused on South American and African germplasm and investigated the genetic architecture of hydrogen cyanide (HCN), a major component of root quality. HCN, representing total cyanogenic glucosides, is a plant defense component against herbivory but is also toxic for human consumption. We genotyped 3354 landraces and modern breeding lines originating from 26 Brazilian states and 1389 individuals were phenotypically characterized across multi-year trials for HCN. All plant material was subjected to high-density genotyping using genotyping by sequencing. We performed genome-wide association mapping to characterize the genetic architecture and gene mapping of HCN. Field experiments revealed strong broad- and narrow-sense trait heritability (0.82 and 0.41, respectively). Two major loci were identified, encoding for an ATPase and a MATE protein, and contributing up to 7 and 30% of the HCN concentration in roots, respectively. We developed diagnostic markers for breeding applications, validated trait architecture consistency in African germplasm and investigated further evidence for the domestication of sweet and bitter cassava. Fine genomic characterization revealed: (i) the major role played by vacuolar transporters in regulating HCN content; (ii) the co-domestication of sweet and bitter cassava major alleles are dependent upon geographical zone; and (iii) the major loci allele for high HCN in M. esculenta Crantz seems to originate from its ancestor, M. esculenta subsp. flabellifolia. Taken together, these findings expand our insights into cyanogenic glucosides in cassava roots and its glycosylated devatives in plants.
Recommended citation: Ogbonna AC, de Andrade LRB, Rabbi IY, Mueller LA, Oliveira EJ, Bauchet GJ (2020) Large-scale genome-wide association study, using historical data, identifies conserved genetic architecture of cyanogenic glucoside content in cassava (*Manihot esculenta* Crantz) root. Plant J. https://doi.org/10.1111/tpj.15071 https://doi.org/10.1111/tpj.15071
Comprehensive genotyping of a Brazilian cassava (Manihot esculenta Crantz) germplasm bank: insights into diversification and domestication
Published in Theoretical and Applied Genetics, 2021
Cassava (Manihot esculenta Crantz) is a major staple root crop of the tropics, originating from the Amazonian region. In this study, 3354 cassava landraces and modern breeding lines from the Embrapa Cassava Germplasm Bank (CGB) were characterized. All individuals were subjected to genotyping-by-sequencing (GBS), identifying 27,045 single-nucleotide polymorphisms (SNPs). Identity-by-state and population structure analyses revealed a unique set of 1536 individuals and 10 distinct genetic groups with heterogeneous linkage disequilibrium (LD). On this basis, a density of 1300–4700 SNP markers were selected for large-effect quantitative trait loci (QTL) detection. Identified genetic groups were further characterized for population genetics parameters including minor allele frequency (MAF), observed heterozygosity (𝐻𝑜), effective population size estimate (𝑁𝑒) and polymorphism information content (PIC). Selection footprints and introgressions of M. glaziovii were detected. Spatial population structure analysis revealed five ancestral populations related to distinct Brazilian ecoregions. Estimation of historical relationships among identified populations suggests an early population split from Amazonian to Atlantic forest and Caatinga ecoregions and active gene flows. This study provides a thorough genetic characterization of ex situ germplasm resources from cassava’s center of origin, South America, with results shedding light on Brazilian cassava characteristics and its biogeographical landscape. These findings support and facilitate the use of genetic resources in modern breeding programs including implementation of association mapping and genomic selection strategies.
Recommended citation: Ogbonna AC, de Andrade LRB, Mueller LA, Oliveira EJ, and Bauchet GJ (2021) Comprehensive genotyping of a Brazilian cassava (*Manihot esculenta* Crantz) germplasm bank: insights into diversification and domestication. Theor Appl Genet 134, 1343–1362. https://doi.org/10.1007/s00122-021-03775-5 https://doi.org/10.1007/s00122-021-03775-5
Optimizing Genomic-Enabled Prediction in Small-Scale Maize Hybrid Breeding Programs: A Roadmap Review
Published in Frontiers in Plant Science, 2021
The usefulness of genomic prediction (GP) for many animal and plant breeding programs has been highlighted for many studies in the last 20 years. In maize breeding programs, mostly dedicated to delivering more highly adapted and productive hybrids, this approach has been proved successful for both large- and small-scale breeding programs worldwide. Here, we present some of the strategies developed to improve the accuracy of GP in tropical maize, focusing on its use under low budget and small-scale conditions achieved for most of the hybrid breeding programs in developing countries. We highlight the most important outcomes obtained by the University of São Paulo (USP, Brazil) and how they can improve the accuracy of prediction in tropical maize hybrids. Our roadmap starts with the efforts for germplasm characterization, moving on to the practices for mating design, and the selection of the genotypes that are used to compose the training population in field phenotyping trials. Factors including population structure and the importance of non-additive effects (dominance and epistasis) controlling the desired trait are also outlined. Finally, we explain how the source of the molecular markers, environmental, and the modeling of genotype–environment interaction can affect the accuracy of GP. Results of 7 years of research in a public maize hybrid breeding program under tropical conditions are discussed, and with the great advances that have been made, we find that what is yet to come is exciting. The use of open-source software for the quality control of molecular markers, implementing GP, and envirotyping pipelines may reduce costs in an efficient computational manner. We conclude that exploring new models/tools using high-throughput phenotyping data along with large-scale envirotyping may bring more resolution and realism when predicting genotype performances. Despite the initial costs, mostly for genotyping, the GP platforms in combination with these other data sources can be a cost-effective approach for predicting the performance of maize hybrids for a large set of growing conditions.
Recommended citation: Fritsche-Neto R, Galli G, Borges KLR, Costa-Neto G, Alves FC, Sabadin F, Lyra DH, Morais PPP, de Andrade LRB, Granato I and Crossa J (2021) Optimizing Genomic-Enabled Prediction in Small-Scale Maize Hybrid Breeding Programs: A Roadmap Review. Front. Plant Sci. 12:658267. doi: 10.3389/fpls.2021.658267 https://doi.org/10.3389/fpls.2021.658267
Reproductive barriers in cassava: Factors and implications for genetic improvement
Published in PLOS ONE, 2021
Cassava breeding is hampered by high flower abortion rates that prevent efficient recombination among promising clones. To better understand the factors causing flower abortion and propose strategies to overcome them, we 1) analyzed the reproductive barriers to intraspecific crossing, 2) evaluated pollen-pistil interactions to maximize hand pollination efficiency, and 3) identified the population structure of elite parental clones. From 2016 to 2018, the abortion and fertilization rates of 5,748 hand crossings involving 91 parents and 157 progenies were estimated. We used 16,300 single nucleotide polymorphism markers to study the parents’ population structure via discriminant analysis of principal components, and three clusters were identified. To test for male and female effects, we used a mixed model in which the environment (month and year) was fixed, while female and male (nested to female) were random effects. Regardless of the population structure, significant parental effects were identified for abortion and fertilization rates, suggesting the existence of reproductive barriers among certain cassava clones. Matching ability between cassava parents was significant for pollen grains that adhered to the stigma surface, germinated pollen grains, and the number of fertilized ovules. Non-additive genetic effects were important to the inheritance of these traits. Pollen viability and pollen-pistil interactions in cross- and self-pollination were also investigated to characterize pollen-stigma compatibility. Various events related to pollen tube growth dynamics indicated fertilization abnormalities. These abnormalities included the reticulated deposition of callose in the pollen tube, pollen tube growth cessation in a specific region of the stylet, and low pollen grain germination rate. Generally, pollen viability and stigma receptivity varied depending on the clone and flowering stage and were lost during flowering. This study provides novel insights into cassava reproduction that can assist in practical crossing and maximize the recombination of contrasting clones.
Recommended citation: e Sousa MB, de Andrade LRB, de Souza EH, Alves AAC, de Oliveira EJ (2021) Reproductive barriers in cassava: Factors and implications for genetic improvement. PLOS ONE 16(11). https://doi.org/10.1371/journal.pone.0260576 https://doi.org/10.1371/journal.pone.0260576
Increasing cassava root yield: Additive-dominant genetic models for selection of parents and clones
Published in Frontiers in Plant Science, 2022
Genomic selection has been promising in situations where phenotypic assessments are expensive, laborious, and/or inefficient. This work evaluated the efficiency of genomic prediction methods combined with genetic models in clone and parent selection with the goal of increasing fresh root yield, dry root yield, as well as dry matter content in cassava roots. The bias and predictive ability of the combinations of prediction methods Genomic Best Linear Unbiased Prediction (G-BLUP), Bayes B, Bayes Cπ, and Reproducing Kernel Hilbert Spaces with additive and additive-dominant genetic models were estimated. Fresh and dry root yield exhibited predominantly dominant heritability, while dry matter content exhibited predominantly additive heritability. The combination of prediction methods and genetic models did not show significant differences in the predictive ability for dry matter content. On the other hand, the prediction methods with additive-dominant genetic models had significantly higher predictive ability than the additive genetic models for fresh and dry root yield, allowing higher genetic gains in clone selection. However, higher predictive ability for genotypic values did not result in differences in breeding value predictions between additive and additive-dominant genetic models. G-BLUP with the classical additive-dominant genetic model had the best predictive ability and bias estimates for fresh and dry root yield. For dry matter content, the highest predictive ability was obtained by G-BLUP with the additive genetic model. Dry matter content exhibited the highest heritability, predictive ability, and bias estimates compared with other traits. The prediction methods showed similar selection gains with approximately 67% of the phenotypic selection gain. By shortening the breeding cycle time by 40%, genomic selection may overcome phenotypic selection by 10%, 13%, and 18% for fresh root yield, dry root yield, and dry matter content, respectively, with a selection proportion of 15%. The most suitable genetic model for each trait allows for genomic selection optimization in cassava with high selection gains, thereby accelerating the release of new varieties.
Recommended citation: **de Andrade LRB**, Sousa MBe, Wolfe M, Jannink JL, de Resende MDV, Azevedo CF and de Oliveira EJ (2022) Increasing cassava root yield: Additive-dominant genetic models for selection of parents and clones. Front. Plant Sci. 13:1071156. doi: 10.3389/fpls.2022.1071156 https://doi.org/10.3389/fpls.2022.1071156
Near-infrared spectroscopy for early selection of waxy cassava clones via seed analysis
Published in Frontiers in Plant Science, 2023
Cassava (Manihot esculenta Crantz) starch consists of amylopectin and amylose, with its properties determined by the proportion of these two polymers. Waxy starches contain at least 95% amylopectin. In the food industry, waxy starches are advantageous, with pastes that are more stable towards retrogradation, while high-amylose starches are used as resistant starches. This study aimed to associate near-infrared spectrophotometry (NIRS) spectra with the waxy phenotype in cassava seeds and develop an accurate classification model for indirect selection of plants. A total of 1127 F2 seeds were obtained from controlled crosses performed between 77 F1 genotypes (wild-type, Wx_). Seeds were individually identified, and spectral data were obtained via NIRS using a benchtop NIRFlex N-500 and a portable SCiO device spectrometer. Four classification models were assessed for waxy cassava genotype identification: k-nearest neighbor algorithm (KNN), C5.0 decision tree (CDT), parallel random forest (parRF), and eXtreme Gradient Boosting (XGB). Spectral data were divided between a training set (80%) and a testing set (20%). The accuracy, based on NIRFlex N-500 spectral data, ranged from 0.86 (parRF) to 0.92 (XGB). The Kappa index displayed a similar trend as the accuracy, considering the lowest value for the parRF method (0.39) and the highest value for XGB (0.71). For the SCiO device, the accuracy (0.88−0.89) was similar among the four models evaluated. However, the Kappa index was lower than that of the NIRFlex N-500, and this index ranged from 0 (parRF) to 0.16 (KNN and CDT). Therefore, despite the high accuracy these last models are incapable of correctly classifying waxy and non-waxy clones based on the SCiO device spectra. A confusion matrix was performed to demonstrate the classification model results in the testing set. For both NIRS, the models were efficient in classifying non-waxy clones, with values ranging from 96−100%. However, the NIRS differed in the potential to predict waxy genotype class. For the NIRFlex N-500, the percentage ranged from 30% (parRF) to 70% (XGB). In general, the models tended to classify waxy genotypes as non-waxy, mainly SCiO. Therefore, the use of NIRS can perform early selection of cassava seeds with a waxy phenotype.
Recommended citation: Sousa MBe, Filho JSS, **de Andrade LRB** and de Oliveira EJ (2023) Near-infrared spectroscopy for early selection of waxy cassava clones via seed analysis. Front. Plant Sci. 14:1089759. doi: 10.3389/fpls.2023.1089759 https://doi.org/10.3389/fpls.2023.1089759
Development of cassava core collections based on morphological and agronomic traits and SNPS markers
Published in Frontiers in Plant Science, 2023
Cassava (Manihot esculenta Crantz) holds significant importance as one of the world’s key starchy crop species. This study aimed to develop core collections by utilizing both phenotypic data (15 quantitative and 33 qualitative descriptors) and genotypic data (20,023 single-nucleotide polymorphisms) obtained from 1,486 cassava accessions. Six core collections were derived through two optimization strategies based on genetic distances: Average accession-to-nearest-entry and Average entry-to-nearest-entry, along with combinations of phenotypic and genotypic data. The quality of the core collections was evaluated by assessing genetic parameters such as genetic diversity Shannon-Weaver Index, inbreeding (Fis), observed (Ho), and expected (Hs) heterozygosity. While the selection of accessions varied among the six core collections, a seventh collection (consolidated collection) was developed, comprising accessions selected by at least two core collections. Most collections exhibited genetic parameters similar to the complete collection, except for those developed by the Average accession-to-nearest-entry algorithm. However, the variations in the maximum and minimum values of Ho, Hs, and Fis parameters closely resembled the complete collection. The consolidated collection and the collection constructed using genotypic data and the Average entry-to-nearest-entry algorithm (GenEN) retained the highest number of alleles (>97%). Although the differences were not statistically significant (above 5%), the consolidated collection demonstrated a distribution profile and mean trait values most similar to the complete collection, with a few exceptions. The Shannon-Weaver Index of qualitative traits exhibited variations exceeding ±10% when compared to the complete collection. Principal component analysis revealed that the consolidated collection selected cassava accessions with a more uniform dispersion in all four quadrants compared to the other core collections. These findings highlight the development of optimized and valuable core collections for efficient breeding programs and genomic association studies.
Recommended citation: Santos CCd, **Andrade LRBd**, Carmo CDd and Oliveira EJd (2023) Development of cassava core collections based on morphological and agronomic traits and SNPS markers. Front. Plant Sci. 14:1250205. doi: 10.3389/fpls.2023.1250205 https://doi.org/10.3389/fpls.2023.1250205
The Development of Thematic Core Collections in Cassava Based on Yield, Disease Resistance, and Root Quality Traits
Published in Plants, 2023
Thematic collections (TCs), which are composed of genotypes with superior agronomic traits and reduced size, offer valuable opportunities for parental selection in plant breeding programs. Three TCs were created to focus on crucial attributes: root yield (CC_Yield), pest and disease resistance (CC_Disease), and root quality traits (CC_Root_quality). The genotypes were ranked using the best linear unbiased predictors (BLUP) method, and a truncated selection was implemented for each collection based on specific traits. The TCs exhibited minimal overlap, with each collection comprising 72 genotypes (CC_Disease), 63 genotypes (CC_Root_quality), and 64 genotypes (CC_Yield), representing 4%, 3.5%, and 3.5% of the total individuals in the entire collection, respectively. The Shannon–Weaver Diversity Index values generally varied but remained below 10% when compared to the entire collection. Most TCs exhibited observed heterozygosity, genetic diversity, and the inbreeding coefficient that closely resembled those of the entire collection, effectively retaining 90.76%, 88.10%, and 88.99% of the alleles present in the entire collection (CC_Disease, CC_Root_quality, and CC_Disease, respectively). A PCA of molecular and agro-morphological data revealed well-distributed and dispersed genotypes, while a discriminant analysis of principal components (DAPC) displayed a high discrimination capacity among the accessions within each collection. The strategies employed in this study hold significant potential for advancing crop improvement efforts.
Recommended citation: dos Santos CC, **de Andrade LRB**, do Carmo CD, de Oliveira EJ. The Development of Thematic Core Collections in Cassava Based on Yield, Disease Resistance, and Root Quality Traits. Plants. 2023; 12(19):3474. https://doi.org/10.3390/plants12193474 https://doi.org/10.3390/plants12193474
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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