Development of a cassava core collection based on single nucleotide polymorphism markers

Oliveira, Eder Jorge de; Ferreira, Cláudia Fortes; Santos, Vinícius Silva dos; Oliveira, Gilmara Alvarenga Fachardo

doi:10.4238/2014.august.25.11

Cited by 17 publications

(16 citation statements)

References 27 publications

(34 reference statements)

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“…Cassava ( Manihot esculenta Crantz) is of great worldwide importance as a food security crop. In Brazil, it is cultivated all over the country in adverse and quite contrasting conditions with respect to water and nutrient availability, and in many cases where of commodities crops is not recommended [1]. Despite the economic and social importance of cassava, the use of quantitative genetics and plant breeding knowledge to develop this crop was initiated only a few decades ago.…”

Section: Introductionmentioning

confidence: 99%

Cassava yield traits predicted by genomic selection methods

et al. 2019

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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.

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Section: Introductionmentioning

confidence: 99%

Cassava yield traits predicted by genomic selection methods

et al. 2019

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“…In the present study, four groups were the optimum number for classification of the accessions, based on both quantitative and joint analyses. In a study of cassava, Oliveira et al (2014) found that the number of groups in the joint analysis was less than the number for the quantitative trait analysis. This difference was possibly caused by there being a higher number of qualitative variables (35) than quantitative variables (13) in classifying the genotypes.…”

Section: Joint Analysis Of Quantitative and Qualitative Traitsmentioning

confidence: 97%

Short Communication: Preliminary characterization of groundcherry (Physalis angulata) from East Java Province, Indonesia based on morpho-agronomic traits

et al. 2020

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Abstract. Sadiyah H, Soegianto A, Waluyo B, Ashari S. 2020. Short Communication: Preliminary characterization of groundcherry (Physalis angulata) from East Java Province, Indonesia based on morpho-agronomic traits. Biodiversitas 21: 759-769. Accurate knowledge of the genetic relationships between different germplasms is important for successful crop improvement programs through breeding. This work aimed to i) characterize the groundcherry germplasm collected from the field of eastern Java and Madura Island based on their morpho-agronomic performance, ii) investigate the relationships among the different germplasms, and iii) verify whether simultaneous analysis of quantitative-qualitative data (joint analysis) can reveal new clustering patterns. A total of 26 quantitative and 31 qualitative traits were measured and evaluated for 28 accessions. Principal Component Analysis (PCA) was used to select variables that had significant loading, based on a t-test, for inclusion in cluster analysis. The first clustering method was the Unweighted Pair Group Method with Arithmetic Mean (UPGMA), which only involved quantitative variables using the Manhattan distance. This method was followed by a joint analysis using Gower dissimilarity. Nonparametric multivariate analysis of variance test showed that four clusters were the optimum number for both methods, but the clusters for each method had different members. The coefficient of variation ranged from 3.9 (fruit pH) to 45.5 (productivity per plant), indicating that improvement in the productivity in groundcherry was promising. The mean values of the morpho-agronomic traits for accessions from eastern Java and Madura Island were not significantly different, except for fruit firmness and the mean length of two internodes. In general, geographic isolation did not have much influence on the characteristics of an accession, since there were accessions from these two regions that were members of the same group, identified by the clustering analysis.

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“…Measures that aim to optimize the conservation and use of cassava germplasm are necessary to avoid losses and to guarantee the security of these genetic resources (Oliveira et al, 2014a). Landrace characterization studies of cassava grown on farms may be a strategy to facilitate management and increase the use of these genetic resources in breeding programs.…”

Section: Introductionmentioning

confidence: 99%

Genetic diversity in cassava landraces grown on farms in Alta Floresta-MT, Brazil

Tiago¹,

Rossi²,

Tiago³

et al. 2016

Genet. Mol. Res.

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ABSTRACT. Brazil is considered one of the domestication centers of cassava (Manihot esculenta), containing a large part of the biological diversity and traditional knowledge of the species. The aim of the present study was to evaluate the genetic diversity of cassava landraces grown by farmers in the north of Mato Grosso State, Brazil, using inter simple sequence repeat (ISSR) molecular markers. The study was carried out in the municipality of Alta Floresta, MT, on farms located in two rural areas. Seventeen cassava landraces were selected. The DNA was extracted and polymerase chain reaction amplifications were performed using 15 ISSR primers. Genetic similarity estimates were calculated using Jaccard's index and the generated matrix was used for clustering the genotypes by using UPGMA and Tocher's methods. The 15 ISSR primers amplified 120 fragments, revealing 61.67% polymorphism. The polymorphism information content ranged from 0.04 to 0.61, averaging 0.39. The most similar genotypes were AF5 and AF8, whereas the least similar were AF1 and AF16. The UPGMA clustering method formed five groups. Group I included twelve landraces, Group II contained two, and the other groups contained one landrace each. Tocher's method resulted in six groups: 12 landraces clustered in one group, and the other groups each contained one landrace. The ISSR markers proved efficient in revealing genetic diversity among the cassava landraces. The landraces grown by farmers in the two rural areas of Alta Floresta have a great variability and, thus, can be exploited in programs for breeding and preservation of the species.

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Development of a cassava core collection based on single nucleotide polymorphism markers

Cited by 17 publications

References 27 publications

Cassava yield traits predicted by genomic selection methods

Cassava yield traits predicted by genomic selection methods

Short Communication: Preliminary characterization of groundcherry (Physalis angulata) from East Java Province, Indonesia based on morpho-agronomic traits

Genetic diversity in cassava landraces grown on farms in Alta Floresta-MT, Brazil

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