Comparative analysis of infected cassava root transcriptomics reveals candidate genes for root rot disease resistance.

Cassava root-rot incited by soil-borne pathogens is one of the major diseases that reduces root yield. Although the use of resistant cultivars is the most effective method of management, the genetic basis for root-rot resistance remains poorly understood. Therefore, our work analyzed the transcriptome of two contrasting genotypes (BRS Kiriris/resistant and BGM-1345/susceptible) using RNA-Seq to understand the molecular response and identify candidate genes for resistance. Cassava seedlings (resistant and susceptible to root-rot) were both planted in infested and sterilized soil and samples from Initial-time and Final-time periods, pooled. Two controls were used: (i) seedlings collected before planting in infested soil (absolute control) and, (ii) plants grown in sterilized soil (mock treatments). For the differentially expressed genes (DEGs) analysis 23.912 were expressed in the resistant genotype, where 10.307 were differentially expressed in the control treatment, 15 DEGs in the Initial Time-period and 366 DEGs in the Final Time-period. Eighteen candidate genes from the resistant genotype were related to plant defense, such as the MLP-like protein 31 and the peroxidase A2-like gene. This is the first model of resistance at the transcriptional level proposed for the cassava × root-rot pathosystem. Gene validation will contribute to screening for resistance of germplasm, segregating populations and/or use in gene editing in the pursuit to develop most promising cassava clones with resistance to root-rot.

Exploiting DNA methylation in cassava under water deficit for crop improvement.

DNA methylation plays a key role in the development and plant responses to biotic and abiotic stresses. This work aimed to evaluate the DNA methylation in contrasting cassava genotypes for water deficit tolerance. The varieties BRS Formosa (bitter) and BRS Dourada (sweet) were grown under greenhouse conditions for 50 days, and afterwards, irrigation was suspended. The stressed (water deficit) and non-stressed plants (negative control) consisted the treatments with five plants per variety. The DNA samples of each variety and treatment provided 12 MethylRAD-Seq libraries (two cassava varieties, two treatments, and three replicates). The sequenced data revealed methylated sites covering 18 to 21% of the Manihot esculenta Crantz genome, depending on the variety and the treatment. The CCGG methylated sites mapped mostly in intergenic regions, exons, and introns, while the CCNGG sites mapped mostly intergenic, upstream, introns, and exons regions. In both cases, methylated sites in UTRs were less detected. The differentially methylated sites analysis indicated distinct methylation profiles since only 12% of the sites (CCGG and CCNGG) were methylated in both varieties. Enriched gene ontology terms highlighted the immediate response of the bitter variety to stress, while the sweet variety appears to suffer more potential stress-damages. The predicted protein-protein interaction networks reinforced such profiles. Additionally, the genomes of the BRS varieties uncovered SNPs/INDELs events covering genes stood out by the interactomes. Our data can be useful in deciphering the roles of DNA methylation in cassava drought-tolerance responses and adaptation to abiotic stresses.

Multi-trait selection in multi-environments for performance and stability in cassava genotypes.

Genotype-environment interaction (GEI) presents challenges when aiming to select optimal cassava genotypes, often due to biased genetic estimates. Various strategies have been proposed to address the need for simultaneous improvements in multiple traits, while accounting for performance and yield stability. Among these methods are mean performance and stability (MPS) and the multi-trait mean performance and stability index (MTMPS), both utilizing linear mixed models. This study's objective was to assess genetic variation and GEI effects on fresh root yield (FRY), along with three primary and three secondary traits. A comprehensive evaluation of 22 genotypes was conducted using a randomized complete block design with three replicates across 47 distinct environments (year x location) in Brazil. The broad-sense heritability (H2) averaged 0.37 for primary traits and 0.44 for secondary traits, with plot-based heritability (hmÉ¡2) consistently exceeding 0.90 for all traits. The high extent of GEI variance (σÉ¡xe2) demonstrates the GEI effect on the expression of these traits. The dominant analytic factor (FA3) accounted for over 85% of the total variance, and the communality (ɧ) surpassed 87% for all traits. These values collectively suggest a substantial capacity for genetic variance explanation. In Cluster 1, composed of remarkably productive and stable genotypes for primary traits, genotypes BRS Novo Horizonte and BR11-34-69 emerged as prime candidates for FRY enhancement, while BRS Novo Horizonte and BR12-107-002 were indicated for optimizing dry matter content. Moreover, MTMPS, employing a selection intensity of 30%, identified seven genotypes distinguished by heightened stability. This selection encompassed innovative genotypes chosen based on regression variance index (Sdi2, R2, and RMSE) considerations for multiple traits. In essence, incorporating methodologies that account for stability and productive performance can significantly bolster the credibility of recommendations for novel cassava cultivars.

Flowering induction in cassava using photoperiod extension premature pruning and plant growth regulators.

Cassava (Manihot esculenta Crantz) is a vital crop for food and economic security in many regions of the world. Despite the economic and social importance of cassava, challenges persist in developing superior varieties that meet the needs of farmers in terms of agronomic performance, nutritional quality, and resistance to pests and diseases. One of the main obstacles for genetic improvement is the lack of synchronization in flowering and the abortion of young flowers, making planned crosses and progeny production difficult. Therefore, the aim of this study was to evaluate the effect of photoperiod, premature pruning, and growth regulators on cassava flowering under low-altitude conditions in Brazil. Eight cassava clones with contrasting flowering capacity were assessed in Cruz das Almas, Bahia, using two photoperiods (ambient condition and extended photoperiod with red light for 12 hours), premature pruning at the first and second branching levels (with and without pruning), and the application of growth regulators: 0.5 mM 6-benzyladenine (BA) and 4.0 mM silver thiosulfate (STS) (with and without). Plots were assessed weekly for the number of female (NFF) and male (NMF) flowers, height of the first branching (H1B, in cm), number of days to the first branching (ND1B), and the number of branching events up to 240 days after planting (NOB). The extended photoperiod did not promote an increase in the number of flowers but allowed for precocity in cassava flowering, reducing the onset of flowering by up to 35 days, and significantly increasing the number of branches, which is closely related to flowering. The use of pruning and plant growth regulators (PGR) resulted in an increase in NFF from 2.2 (control) to 4.6 and NMF from 8.1 to 21.1 flowers. Therefore, under hot and humid tropical conditions at low altitudes in the Recôncavo of Bahia, manipulating the photoperiod and using premature pruning and plant growth regulators can accelerate cassava flowering, benefiting genetic improvement programs.

The Development of Thematic Core Collections in Cassava Based on Yield, Disease Resistance, and Root Quality Traits.

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.

Development of cassava core collections based on morphological and agronomic traits and SNPS markers.

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.

New protocol for rapid cassava multiplication in field conditions: a perspective on speed breeding.

Despite the economic and social importance, high-yielding cassava cultivars are only released after extensive research, mainly due to the low multiplication rate. This study aimed to assess the impact of using smaller-sized seed cuttings treated with agrochemicals (8MP) compared to the conventional planting size (16 cm) on genetic parameters, agronomic performance, and the ranking of cassava clones based on yield and growth attributes. The evaluation was carried out in clonal evaluation trial (CET), preliminary yield trial (PYT), and uniform yield trials (UYT). Additionally, a new selection scheme for cassava breeding programs was proposed. A total of 169 clones were evaluated, including 154 improved clones at different stages of selection and 15 local varieties used as checks. Field trials were conducted using both sizes of propagative material (8MP and 16 cm) in each phase of the breeding program. The data were analyzed using mixed models, considering the random effects of genotype and genotype-environment interaction (G×E) to determine variances and heritabilities. Bland-Altman concordance and correlation analysis of selection indices were employed to examine the consistency in the ranking of cassava clones using different seed cutting sizes. The distribution of variance components, heritabilities, means, and range of the 8MP and 16 cm trials in different phases of the cassava breeding program exhibited remarkable similarity, thereby enabling a comparative assessment of similar genetic effects. With a selection intensity of 30%, the concordance in clone ranking was 0.41, 0.57, and 0.85 in CET, PYT, and UYT trials, respectively, when comparing the selection based on 8MP and 16 cm trials. It is worth noting that the ranking of the top 15% remained largely unchanged. Based on the findings, proposed changes in the cassava selection scheme involve increasing the number of trials starting from the CET phase, early incorporation of G×E interaction, elimination of the PYT trial, reduction of the breeding cycle from 5 to 3 years, and a decrease in the time required for variety development from 11 to 9 years. These modifications are expected to lead to cost reduction and enhance the effectiveness of cassava breeding programs.

Volatile Organic Compounds from Cassava Plants Confer Resistance to the Whitefly Aleurothrixus aepim (Goeldi, 1886).

Cassava is an essential tuber crop used to produce food, feed, and beverages. Whitefly pests, including Aleurothrixus aepim (Goeldi, 1886) (Hemiptera: Aleyrodidae), significantly affect cassava-based agroecosystems. Plant odours have been described as potential pest management tools, and the cassava clone M Ecuador 72 has been used by breeders as an essential source of resistance. In this study, we analysed and compared the volatile compounds released by this resistant clone and a susceptible genotype, BRS Jari. Constitutive odours were collected from young plants and analysed using gas chromatography-mass spectrometry combined with chemometric tools. The resistant genotype released numerous compounds with previously described biological activity and substantial amounts of the monoterpene (E)-ß-ocimene. Whiteflies showed non-preferential behaviour when exposed to volatiles from the resistant genotype but not the susceptible genotype. Furthermore, pure ocimene caused non-preferential behaviour in whiteflies, indicating a role for this compound in repellence. This report provides an example of the intraspecific variation in odour emissions from cassava plants alongside information on odorants that repel whiteflies; these data can be used to devise whitefly management strategies. A better understanding of the genetic variability in cassava odour constituents and emissions under field conditions may accelerate the development of more resistant cassava varieties.

Near-infrared spectroscopy for early selection of waxy cassava clones via seed analysis.

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.

Phenotypic diversity and selection in biofortified cassava germplasm for yield and quality root traits.

Increasing carotenoid content and improving other root quality traits has been the focus of cassava biofortification. This study aimed to (i) evaluate the genetic variability for total carotenoid content (TCC), as well as for root yield and root quality attributes; (ii) estimate potentially useful correlations for selection; and (iii) select parents for breeding and estimate the genetic gain. Data from 2011 to 2020 of 265 cassava genotypes with cream and yellow roots were analyzed for dry matter content (DMC), shoot yield, fresh root yield (FRY), dry root yield (DRY), harvest index, average number of roots per plant, starch content, root pulp color, cyanogenic compounds, and TCC. The best linear unbiased predictions showed great phenotypic variation for all traits. Six distinct groups were formed for productive characteristics of root quality, mainly TCC, DMC and FRY. Only TCC showed high broad-sense heritability ( h 2 = 0.72), while the other traits had low to medium magnitude (0.21 ≤ h 2 ≤ 0.60). TCC was strongly correlated with pulp color (r = 0.70), but null significance for DMC. The network analysis identified a clear separation between the agronomic and quality attributes of cassava roots. The selection of the 30 genotypes for recombination in the breeding program has the potential to raise TCC by 27.05% and reduce the cyanogenic compounds content by 23.03%, in addition to increasing FRY and DRY by 22.72% and 22.95%, respectively. This is the first consolidated study on the potential of germplasm for the development biofortified cassava cultivars in Brazil.

Genome-wide association study and selection for field resistance to cassava root rot disease and productive traits.

Cassava root rot disease is caused by a complex of soil-borne pathogens and has high economic impacts because it directly affects the tuberous roots, which are the main commercial product. This study aimed to evaluate cassava genotypes for resistance to root rot disease in a field with a previous history of high disease incidence. It also aimed to identify possible genomic regions associated with field resistance based on genome-wide association studies. A total of 148 genotypes from Embrapa Mandioca and Fruticultura were evaluated over two years, including improved materials and curated germplasms. Analysis of phenotypic data was conducted, as well as a genomic association analysis, based on the general linear model, mixed linear model, and fixed and random model circulating probability unification. The observed high disease index (ω) was directly correlated with genotype survival, affecting plant height, shoot yield, and fresh root yield. The genotypes were grouped into five clusters, which were classified according to level of root rot resistance (i.e., extremely susceptible, susceptible, moderately susceptible, moderately resistant, and resistant). The 10 genotypes with the best performance in the field were selected as potential progenitors for the development of segregating progenies. Estimates of genomic kinship between these genotypes ranged from -0.183 to 0.671. The genotypes BGM-1171 and BGM-1190 showed the lowest degree of kinship with the other selected sources of resistance. The genotypes BGM-0209, BGM-0398, and BGM-0659 showed negative kinship values with most elite varieties, while BGM-0659 presented negative kinship with all landraces. A genome-wide association analysis detected five significant single nucleotide polymorphisms related to defense mechanisms against biotic and abiotic stresses, with putative association with fresh root yield in soil infested with root rot pathogens. These findings can be utilized to develop molecular selection for root rot resistance in cassava.

Genome-wide association study of cassava starch paste properties.

An understanding of cassava starch paste properties (CSPP) can contribute to the selection of clones with differentiated starches. This study aimed to identify genomic regions associated with CSPP using different genome-wide association study (GWAS) methods (MLM, MLMM, and Farm-CPU). The GWAS was performed using 23,078 single-nucleotide polymorphisms (SNPs). The rapid viscoanalyzer (RVA) parameters were pasting temperature (PastTemp), peak viscosity (PeakVisc), hot-paste viscosity (Hot-PVisc), cool-paste viscosity (Cold-PVisc), final viscosity (FinalVis), breakdown (BreDow), and setback (Setback). Broad phenotypic and molecular diversity was identified based on the genomic kinship matrix. The broad-sense heritability estimates (h2) ranged from moderate to high magnitudes (0.66 to 0.76). The linkage disequilibrium (LD) declined to between 0.3 and 2.0 Mb (r2 <0.1) for most chromosomes, except chromosome 17, which exhibited an extensive LD. Thirteen SNPs were found to be significantly associated with CSPP, on chromosomes 3, 8, 17, and 18. Only the BreDow trait had no associated SNPs. The regional marker-trait associations on chromosome 18 indicate a LD block between 2907312 and 3567816 bp and that SNP S18_3081635 was associated with SetBack, FinalVis, and Cold-PVisc (all three GWAS methods) and with Hot-PVisc (MLM), indicating that this SNP can track these four traits simultaneously. The variance explained by the SNPs ranged from 0.13 to 0.18 for SetBack, FinalVis, and Cold-PVisc and from 0.06 to 0.09 for PeakVisc and Hot-PVisc. The results indicated additive effects of the genetic control of Cold-PVisc, FinalVis, Hot-PVisc, and SetBack, especially on the large LD block on chromosome 18. One transcript encoding the glycosyl hydrolase family 35 enzymes on chromosome 17 and one encoding the mannose-p-dolichol utilization defect 1 protein on chromosome 18 were the most likely candidate genes for the regulation of CSPP. These results underline the potential for the assisted selection of high-value starches to improve cassava root quality through breeding programs.

Image-based phenotyping of cassava roots for diversity studies and carotenoids prediction.

Phenotyping to quantify the total carotenoids content (TCC) is sensitive, time-consuming, tedious, and costly. The development of high-throughput phenotyping tools is essential for screening hundreds of cassava genotypes in a short period of time in the biofortification program. This study aimed to (i) use digital images to extract information on the pulp color of cassava roots and estimate correlations with TCC, and (ii) select predictive models for TCC using colorimetric indices. Red, green and blue images were captured in root samples from 228 biofortified genotypes and the difference in color was analyzed using L*, a*, b*, hue and chroma indices from the International Commission on Illumination (CIELAB) color system and lightness. Colorimetric data were used for principal component analysis (PCA), correlation and for developing prediction models for TCC based on regression and machine learning. A high positive correlation between TCC and the variables b* (r = 0.90) and chroma (r = 0.89) was identified, while the other correlations were median and negative, and the L* parameter did not present a significant correlation with TCC. In general, the accuracy of most prediction models (with all variables and only the most important ones) was high (R2 ranging from 0.81 to 0.94). However, the artificial neural network prediction model presented the best predictive ability (R2 = 0.94), associated with the smallest error in the TCC estimates (root-mean-square error of 0.24). The structure of the studied population revealed five groups and high genetic variability based on PCA regarding colorimetric indices and TCC. Our results demonstrated that the use of data obtained from digital image analysis is an economical, fast, and effective alternative for the development of TCC phenotyping tools in cassava roots with high predictive ability.

Increasing cassava root yield: Additive-dominant genetic models for selection of parents and clones.

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.

Can Cross-Country Genomic Predictions Be a Reasonable Strategy to Support Germplasm Exchange? - A Case Study With Hydrogen Cyanide in Cassava.

Genomic prediction (GP) offers great opportunities for accelerated genetic gains by optimizing the breeding pipeline. One of the key factors to be considered is how the training populations (TP) are composed in terms of genetic improvement, kinship/origin, and their impacts on GP. Hydrogen cyanide content (HCN) is a determinant trait to guide cassava's products usage and processing. This work aimed to achieve the following objectives: (i) evaluate the feasibility of using cross-country (CC) GP between germplasm's of Embrapa Mandioca e Fruticultura (Embrapa, Brazil) and The International Institute of Tropical Agriculture (IITA, Nigeria) for HCN; (ii) provide an assessment of population structure for the joint dataset; (iii) estimate the genetic parameters based on single nucleotide polymorphisms (SNPs) and a haplotype-approach. Datasets of HCN from Embrapa and IITA breeding programs were analyzed, separately and jointly, with 1,230, 590, and 1,820 clones, respectively. After quality control, ∼14K SNPs were used for GP. The genomic estimated breeding values (GEBVs) were predicted based on SNP effects from analyses with TP composed of the following: (i) Embrapa genotypic and phenotypic data, (ii) IITA genotypic and phenotypic data, and (iii) the joint datasets. Comparisons on GEBVs' estimation were made considering the hypothetical situation of not having the phenotypic characterization for a set of clones for a certain research institute/country and might need to use the markers' effects that were trained with data from other research institutes/country's germplasm to estimate their clones' GEBV. Fixation index (FST) among the genetic groups identified within the joint dataset ranged from 0.002 to 0.091. The joint dataset provided an improved accuracy (0.8-0.85) compared to the prediction accuracy of either germplasm's sources individually (0.51-0.67). CC GP proved to have potential use under the present study's scenario, the correlation between GEBVs predicted with TP from Embrapa and IITA was 0.55 for Embrapa's germplasm, whereas for IITA's it was 0.1. This seems to be among the first attempts to evaluate the CC GP in plants. As such, a lot of useful new information was provided on the subject, which can guide new research on this very important and emerging field.

Reproductive barriers in cassava: Factors and implications for genetic improvement.

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.

Comprehensive genotyping of a Brazilian cassava (Manihot esculenta Crantz) germplasm bank: insights into diversification and domestication.

KEY MESSAGE: Brazilian cassava diversity was characterized through population genetics and clustering approaches, highlighting contrasted genetic groups and spatial genetic differentiation. 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 [Formula: see text], effective population size estimate [Formula: see text]) 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.

Identification and validation of mutation points associated with waxy phenotype in cassava.

BACKGROUND: The granule-bound starch synthase I (GBSSI) enzyme is responsible for the synthesis of amylose, and therefore, its absence results in individuals with a waxy starch phenotype in various amylaceous crops. The validation of mutation points previously associated with the waxy starch phenotype in cassava, as well as the identification of alternative mutant alleles in the GBSSI gene, can allow the development of molecular-assisted selection to introgress the waxy starch mutation into cassava breeding populations. RESULTS: A waxy cassava allele has been identified previously, associated with several SNPs. A particular SNP (intron 11) was used to develop SNAP markers for screening heterozygote types in cassava germplasm. Although the molecular segregation corresponds to the expected segregation at 3:1 ratio (dominant gene for the presence of amylose), the homozygotes containing the SNP associated with the waxy mutation did not show waxy phenotypes. To identify more markers, we sequenced the GBSS gene from 89 genotypes, including some that were segregated from a cross with a line carrying the known waxy allele. As a result, 17 mutations in the GBSSI gene were identified, in which only the deletion in exon 6 (MeWxEx6-del-C) was correlated with the waxy phenotype. The evaluation of mutation points by discriminant analysis of principal component analysis (DAPC) also did not completely discriminate the waxy individuals. Therefore, we developed Kompetitive Allele Specific PCR (KASP) markers that allowed discrimination between WX and wx alleles. The results demonstrated the non-existence of heterozygous individuals of the MeWxEx6-del-C deletion in the analyzed germplasm. Therefore, the deletion MeWxEx6-del-C should not be used for assisted selection in genetic backgrounds different from the original source of waxy starch. Also, the alternative SNPs identified in this study were not associated with the waxy phenotype when compared to a panel of accessions with high genetic diversity. CONCLUSION: Although the GBSSI gene can exhibit several mutations in cassava, only the deletion in exon 6 (MeWxEx6-del-C) was correlated with the waxy phenotype in the original AM206-5 source.

A novel seed treatment-based multiplication approach for cassava planting material.

Cassava (Manihot esculenta Crantz) is an important food security crop in many parts of the developing world. The crop's high yield potential and multitude of uses-both for nutrition and processing-render cassava a promising driver for the development of rural value chains. It is traditionally propagated from stem cuttings of up to 30 cm in length, giving a multiplication rate as low as 1:10. Propagating cassava traditionally is very inefficient, which leads to challenges in the production and distribution of quality planting material and improved cultivars, greatly limiting the impact of investments in crop breeding. The work described in the present study aimed to develop a seed treatment approach to facilitate the use of shorter seed pieces, increasing the multiplication rate of cassava and thus making the crop's seed systems more efficient. After several tests, formulation was identified, consisting of thiamethoxam 21 g ha-1, mefenoxam 1.0 g ha-1, fludioxonil 1.3 g ha-1, thiabendazole 7.5 g ha-1 and Latex 2% as a binder. Plant growing from seed pieces treated with this formulation displayed increased crop establishment and early crop vigor, leading to an improved productivity throughout a full growing cycle. This allowed to reduce the cassava seed piece size to 8 cm with no negative effects on germination and crop establishment, leading to yields comparable to those from untreated 16 cm pieces. This, in turn, will allow to increase the multiplication ratio of cassava by a factor of up to 3. Notably, this was possible under regular field conditions and independently of any specialised treatment facilities. Compared with existing seed production protocols, the increased multiplication rates allowed for efficiency gains of between 1 to 1.9 years compared to conventional five-year cycles. We believe that the technology described here holds considerable promise for developing more reliable and remunerative delivery channels for quality cassava planting material and improved genetics.

Genomic selection for productive traits in biparental cassava breeding populations.

Cassava improvement using traditional breeding strategies is slow due to the species' long breeding cycle. However, the use of genomic selection can lead to a shorter breeding cycle. This study aimed to estimate genetic parameters for productive traits based on pedigree (pedigree and phenotypic information) and genomic (markers and phenotypic information) analyses using biparental crosses at different stages of selection. A total of 290 clones were genotyped and phenotyped for fresh root yield (FRY), dry matter content (DMC), dry yield (DY), fresh shoot yield (FSY) and harvest index (HI). The clones were evaluated in clonal evaluation trials (CET), preliminary yield trials (PYT), advanced yield trials (AYT) and uniform yield trials (UYT), from 2013 to 2018 in ten locations. The breeding stages were analyzed as follows: one stage (CET), two stages (CET and PYT), three stages (CET, PYT and AYT) and four stages (CET, PYT, AYT and UYT). The genomic predictions were analyzed via k-fold cross-validation based on the genomic best linear unbiased prediction (GBLUP) considering a model with genetic additive effects and genotype × location interactions. Genomic and pedigree accuracies were moderate to high (0.56-0.72 and 0.62-0.78, respectively) for important starch-related traits such as DY and FRY; when considering one breeding stage (CET) with the aim of early selection, the genomic accuracies ranged from 0.60 (DMC) to 0.71 (HI). Moreover, the correlations between the genomic estimation breeding values of one-stage genomic analysis and the estimated breeding values of the four-stage (full data set) pedigree analysis were high for all traits as well as for a selection index including all traits. The results indicate great possibilities for genomic selection in cassava, especially for selection early in the breeding cycle (saving time and effort).