Cassava yield traits predicted by genomic selection methods

Enhancing grapevine breeding efficiency through genomic prediction and selection index

Grapevine (Vitis vinifera) breeding reaches a critical point. New cultivars are released every year with resistance to powdery and downy mildews. However, the traditional process remains time-consuming, taking 20-25 years, and demands the evaluation of new traits to enhance grapevine adaptation to climate change. Until now, the selection process has relied on phenotypic data and a limited number of molecular markers for simple genetic traits such as resistance to pathogens, without a clearly defined ideotype, and was carried out on a large scale. To accelerate the breeding process and address these challenges, we investigated the use of genomic prediction, a methodology using molecular markers to predict genotypic values. In our study, we focused on 2 existing grapevine breeding programs: Rosé wine and Cognac production. In these programs, several families were created through crosses of emblematic and interspecific resistant varieties to powdery and downy mildews. Thirty traits were evaluated for each program, using 2 genomic prediction methods: Genomic Best Linear Unbiased Predictor and Least Absolute Shrinkage Selection Operator. The results revealed substantial variability in predictive abilities across traits, ranging from 0 to 0.9. These discrepancies could be attributed to factors such as trait heritability and trait characteristics. Moreover, we explored the potential of across-population genomic prediction by leveraging other grapevine populations as training sets. Integrating genomic prediction allowed us to identify superior individuals for each program, using multivariate selection index method. The ideotype for each breeding program was defined collaboratively with representatives from the wine-growing sector.

Development of Methods for Improving Flowering and Seed Set of Diverse Germplasm in Cassava Breeding

Cassava breeding faces obstacles due to late flowering and poor flower and seed set. The acceleration of breeding processes and the reduction in each cycle's duration hinge upon efficiently conducting crosses to yield ample progeny for subsequent cycles. Our primary objective was to identify methods that provide tools for cassava breeding programs, enabling them to consistently and rapidly generate offspring from a wide array of genotypes. In greenhouse trials, we examined the effects of the anti-ethylene silver thiosulfate (STS) and the cytokinin benzyladenine (BA). STS, administered via petiole infusion, and BA, applied as an apical spray, combined with the pruning of young branches, significantly augmented the number of flowers. Controls produced no flowers, whereas treatments with pruning plus either BA or STS alone produced an average maximum of 86 flowers per plant, and the combination of pruning, BA and STS yielded 168 flowers per plant. While STS had its primary effect on flower numbers, BA increased the fraction of female flowers from less than 20% to ≥87%, thus increasing the number of progeny from desired parents. Through field studies, we devised an optimal protocol that maintained acceptable levels of phytodamage ratings while substantially increasing seed production per plant compared to untreated plants. This protocol involves adjusting the dosage and timing of treatments to accommodate genotypic variations. As a result, cassava breeding programs can effectively leverage a diverse range of germplasm to develop cultivars with the desired traits.

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.

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.

Utilization of a publicly available diversity panel in genomic prediction of Fusarium head blight resistance traits in wheat

Fusarium head blight (FHB) is an economically and environmentally concerning disease of wheat (Triticum aestivum L). A two-pronged approach of marker-assisted selection coupled with genomic selection has been suggested when breeding for FHB resistance. A historical dataset comprised of entries in the Southern Uniform Winter Wheat Scab Nursery (SUWWSN) from 2011 to 2021 was partitioned and used in genomic prediction. Two traits were curated from 2011 to 2021 in the SUWWSN: percent Fusarium damaged kernels (FDK) and deoxynivalenol (DON) content. Heritability was estimated for each trait-by-environment combination. A consistent set of check lines was drawn from each year in the SUWWSN, and k-means clustering was performed across environments to assign environments into clusters. Two clusters were identified as FDK and three for DON. Cross-validation on SUWWSN data from 2011 to 2019 indicated no outperforming training population in comparison to the combined dataset. Forward validation for FDK on the SUWWSN 2020 and 2021 data indicated a predictive accuracyr ≈ 0.58 $r \approx 0.58$ andr ≈ 0.53 $r \approx 0.53$ , respectively. Forward validation for DON indicated a predictive accuracy ofr ≈ 0.57 $r \approx 0.57$ andr ≈ 0.45 $r \approx 0.45$ , respectively. Forward validation using environments in cluster one for FDK indicated a predictive accuracy ofr ≈ 0.65 $r \approx 0.65$ andr ≈ 0.60 $r \approx 0.60$ , respectively. Forward validation using environments in cluster one for DON indicated a predictive accuracy ofr ≈ 0.67 $r \approx 0.67$ andr ≈ 0.60 $r \approx 0.60$ , respectively. These results indicated that selecting environments based on check performance may produce higher forward prediction accuracies. This work may be used as a model for utilizing public resources for genomic prediction of FHB resistance traits across public wheat breeding programs.

Genomic selection and genome-wide association studies in tetraploid chipping potatoes

Potato is a major food crop in the United States and around the world. Most potatoes grown in the United States are destined for processing. Genomic selection can speed up breeding progress for important traits, including those with complex inheritance by guiding the identification of the best parents and guiding selection to advance clones in the breeding program. However, the application of genomic selection in polyploid species has been challenging. In this study, we obtained breeding values of 384 chipping clones evaluated in Texas between 2017 and 2020. The mean reliability of the genomic-estimated breeding values obtained were 0.77, 0.41, 0.61, 0.71, and 0.24 for chip color, chip quality, specific gravity, vine maturity, and total yield, respectively. Potato clones with good chip quality, high yield, high specific gravity, and light-color chips were identified using a multi-trait selection index based on weighted standardized genomic-estimated breeding values. Genome-wide association studies identified quantitative trait loci on chromosome 5 for vine maturity and chromosomes 1, 3, and 7 for chip color. This research has laid the groundwork for implementing genomic selection in tetraploid potato breeding and understanding the genetic basis of chip processing traits in potatoes.

Comparative Transcriptome Profiling of Cassava Tuberous Roots in Response to Postharvest Physiological Deterioration

Cassava is one of the most versatile tuberous-root crops on Earth. However, the postharvest storage properties of cassava tuberous root mean that it is perishable through a process known as postharvest physiological deterioration (PPD), which seriously affects its starch quality. Therefore, a comprehensive understanding of the transcriptional regulatory activity of cassava against the PPD response is necessary in order to extract key molecular mechanisms related to PPD tolerance. In this study, we found that RYG1 tuberous roots showed delayed PPD compared to those of SC8. In addition, RYG1 roots maintained a more stable cell wall structure after storage than those of SC8. The transcriptome changes in tuberous roots were analyzed for both RYG1 and SC8 after 21 days of storage (SR and SS) compared to fresh (FR and FS) by the RNA-Seq method. The total number of differentially expressed genes (DEGs) in the various comparisons of these four samples ranged from 68 to 3847. Of these, a total of 2008 co-DEGs in SR vs. SS were shared by either SR vs. FR or SS vs. FS. GO and KEGG enrichment analysis revealed that upregulated co-DEGs in SR vs. SS were mainly enriched in photosynthesis, protein processing, hormone and cutin, suberine and wax biosynthesis. By contrast, the downregulated co-DEGs were mainly related to cell wall organization, starch and sucrose metabolism, galactose metabolism, phenylpropanoid biosynthesis, diterpenoid biosynthesis, cysteine and methionine metabolism and flavonoid biosynthesis. The protein-protein interaction (PPI) networks of the co-DEGs showed a complex interaction of genes in different pathways, and 16 hub genes were characterized to have a degree in excess of 15, among which eight genes were associated with photosynthesis. These results provide new information for the study of cassava resistance to PPD and lay a foundation for the further molecular breeding of storage-tolerant cassava varieties.

Evaluation of the pasting characteristics of cassava roots grown in different locations in Nigeria from the Genetic Gain Assessment trial

The cooking quality, especially the pasting properties, is essential in cassava starch applications or successfully utilizing cassava in food industries and at the household level. This study evaluated the cassava roots from the Genetic Gain Assessment trial grown in three locations for dry matter (DM) and the pasting characteristics. Four hundred cassava genotypes were planted under IVS (Dry season in Inland Valley Hydromorphic area) and Upland (rain-fed conditions) trials at IITA Research Farms, Nigeria. The harvested cassava roots (12 months after planting) were analyzed for DM, and the dried-milled roots were analyzed for pasting properties using standard laboratory methods. The DM ranged from 25.04 to 38.72%, with a mean of 31.97 ± 2.41%. The pasting properties (peak, trough, breakdown, setback and final viscosities) ranged from 140.36–570.93 RVU (mean 241.71 ± 38.17), 6.74–173.32 RVU (mean 96.65 ± 23.45), 66.97–482.35 RVU (mean 142.44 ± 30.16), 60.06–231.74RVU (mean 134.42 ± 30.52), and 5.22–135.69 RVU (mean 37.78 ± 12.96), respectively. The genotypes had no significant effect (P > 0.05) on the DM and pasting properties, but the growing location showed a highly significant effect (P < 0.05) on all the parameters studied. The cluster analysis grouped the genotypes into 2 clusters where clusters 1 and 2 had 115 and 285 genotypes, respectively. Knowing the impact of genotype and grown location on the pasting behavior could help the breeders select the best genotypes with excellent qualities that could adapt to different environments and identify the suitable growing area for the best cooking quality.

Validation of KASP-SNP markers in cassava germplasm for marker-assisted selection of increased carotenoid content and dry matter content

Provitamin A biofortification and increased dry matter content are important breeding targets in cassava improvement programs worldwide. Biofortified varieties contribute to the alleviation of provitamin A deficiency, a leading cause of preventable blindness common among pre-school children and pregnant women in developing countries particularly Africa. Dry matter content is a major component of dry yield and thus underlies overall variety performance and acceptability by growers, processors, and consumers. Single nucleotide polymorphism (SNP) markers linked to these traits have recently been discovered through several genome-wide association studies but have not been deployed for routine marker-assisted selection (MAS). This is due to the lack of useful information on markers' performances in diverse genetic backgrounds. To overcome this bottleneck, technical and biological validation of the loci associated with increased carotenoid content and dry matter content were carried out using populations independent of the marker discovery population. In the present study, seven previously identified markers for these traits were converted to a robust set of uniplex allele-specific polymerase chain reaction (PCR) assays and validated in two independent pre-breeding and breeding populations. These assays were efficient in discriminating marker genotypic classes and had an average call rate greater than 98%. A high correlation was observed between the predicted and observed carotenoid content as inferred by root yellowness intensity in the breeding (r = 0.92) and pre-breeding (r = 0.95) populations. On the other hand, dry matter content-markers had moderately low predictive accuracy in both populations (r< 0.40) due to the more quantitative nature of the trait. This work confirmed the markers' effectiveness in multiple backgrounds, therefore, further strengthening their value in cassava biofortification to ensure nutritional security as well as dry matter content productivity. Our study provides a framework to guide future marker validation, thus leading to the more routine use of markers in MAS in cassava improvement programs.

Long-day photoperiod and cool temperature induce flowering in cassava: Expression of signaling genes

Cassava is a staple food crop in the tropics, and is of particular importance in Africa. Recent development of genomic selection technology have improved the speed of cassava breeding; however, cassava flower initiation and development remains a bottleneck. The objectives of the current studies were to elucidate the effect of photoperiod, temperature and their interactions on the time of flowering and flower development in controlled environments, and to use RNA-sequencing to identify transcriptome expression underlying these environmental responses. Compared to a normal tropical day-length of 12 h, increasing the photoperiod by 4 h or decreasing the air temperature from 34/31 to 22°/19°C (day/night) substantially hastened the time to flowering. For both photoperiod and temperature, the environment most favorable for flowering was opposite the one for storage root harvest index. There was a pronounced treatment interaction: at warm day-time temperatures, percent flowering was low, and photoperiod had little effect. In contrast, at cooler temperatures, percent flowering increased, and long-day (LD) photoperiod had a strong effect in hastening flowering. In response to temperature, many differentially expressed genes in the sugar, phase-change, and flowering-time-integrator pathways had expression/flowering patterns in the same direction as in Arabidopsis (positive or negative) even though the effect of temperature on flowering operates in the reverse direction in cassava compared to Arabidopsis. Three trehalose-6-phosphate-synthase-1 (TPS1) genes and four members of the SPL gene family had significantly increased expression at cool temperature, suggesting sugar signaling roles in flower induction. In response to LD photoperiod, regulatory genes were expressed as in Arabidopsis and other LD flowering plants. Several hormone-related genes were expressed in response to both photoperiod and temperature. In summary, these findings provide insight on photoperiod and temperature responses and underlying gene expression that may assist breeding programs to manipulate flowering for more rapid crop improvement.

Advances in Genetic Analysis and Breeding of Cassava (Manihot esculenta Crantz): A Review

Cassava (Manihot esculenta Crantz) is the sixth most important food crop and consumed by 800 million people worldwide. In Africa, cassava is the second most important food crop after maize and Africa is the worlds' largest producer. Though cassava is not one of the main commodity crops in South Africa, it is becoming a popular crop among farming communities in frost-free areas, due to its climate-resilient nature. This necessitated the establishment of a multi-disciplinary research program at the Agricultural Research Council of South Africa. The objective of this review is to highlight progress made in cassava breeding and genetic analysis. This review highlights the progress of cassava research worldwide and discusses research findings on yield, quality, and adaptability traits in cassava. It also discusses the limitations and the prospects of the cassava R&D program towards development of the cassava industry in South Africa.

Current status and impending progress for cassava structural genomics

We demystify recent advances in genome assemblies for the heterozygous staple crop cassava (Manihot esculenta), and highlight key cassava genomic resources. Cassava, Manihot esculenta Crantz, is a crop of societal and agricultural importance in tropical regions around the world. Genomics provides a platform for accelerated improvement of cassava's nutritional and agronomic traits, as well as for illuminating aspects of cassava's history including its path towards domestication. The highly heterozygous nature of the cassava genome is widely recognized. However, the full extent and context of this heterozygosity has been difficult to reveal because of technological limitations within genome sequencing. Only recently, with several new long-read sequencing technologies coming online, has the genomics community been able to tackle some similarly difficult genomes. In light of these recent advances, we provide this review to document the current status of the cassava genome and genomic resources and provide a perspective on what to look forward to in the coming years.

Genome-wide association mapping and genomic prediction of yield-related traits and starch pasting properties in cassava

GWAS identified eight yield-related, peak starch type of waxy and wild-type starch and 21 starch pasting property-related traits (QTLs). Prediction ability of eight GS models resulted in low to high predictability, depending on trait, heritability, and genetic architecture. Cassava is both a food and an industrial crop in Africa, South America, and Asia, but knowledge of the genes that control yield and starch pasting properties remains limited. We carried out a genome-wide association study to clarify the molecular mechanisms underlying these traits and to explore marker-based breeding approaches. We estimated the predictive ability of genomic selection (GS) using parametric, semi-parametric, and nonparametric GS models with a panel of 276 cassava genotypes from Thai Tapioca Development Institute, International Center for Tropical Agriculture, International Institute of Tropical Agriculture, and other breeding programs. The cassava panel was genotyped via genotyping-by-sequencing, and 89,934 single-nucleotide polymorphism (SNP) markers were identified. A total of 31 SNPs associated with yield, starch type, and starch properties traits were detected by the fixed and random model circulating probability unification (FarmCPU), Bayesian-information and linkage-disequilibrium iteratively nested keyway and compressed mixed linear model, respectively. GS models were developed, and forward predictabilities using all the prediction methods resulted in values of - 0.001-0.71 for the four yield-related traits and 0.33-0.82 for the seven starch pasting property traits. This study provides additional insight into the genetic architecture of these important traits for the development of markers that could be used in cassava breeding programs.

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 (F_ST) 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.

Genomic mating in outbred species: predicting cross usefulness with additive and total genetic covariance matrices

Diverse crops are both outbred and clonally propagated. Breeders typically use truncation selection of parents and invest significant time, land, and money evaluating the progeny of crosses to find exceptional genotypes. We developed and tested genomic mate selection criteria suitable for organisms of arbitrary homozygosity level where the full-sibling progeny are of direct interest as future parents and/or cultivars. We extended cross variance and covariance variance prediction to include dominance effects and predicted the multivariate selection index genetic variance of crosses based on haplotypes of proposed parents, marker effects, and recombination frequencies. We combined the predicted mean and variance into usefulness criteria for parent and variety development. We present an empirical study of cassava (Manihot esculenta), a staple tropical root crop. We assessed the potential to predict the multivariate genetic distribution (means, variances, and trait covariances) of 462 cassava families in terms of additive and total value using cross-validation. Most variance (89%) and covariance (70%) prediction accuracy estimates were greater than zero. The usefulness of crosses was accurately predicted with good correspondence between the predicted and the actual mean performance of family members breeders selected for advancement as new parents and candidate varieties. We also used a directional dominance model to quantify significant inbreeding depression for most traits. We predicted 47,083 possible crosses of 306 parents and contrasted them to those previously tested to show how mate selection can reveal the new potential within the germplasm. We enable breeders to consider the potential of crosses to produce future parents (progeny with top breeding values) and varieties (progeny with top own performance).

Environmental responsiveness of flowering time in cassava genotypes and associated transcriptome changes

Cassava is an important food security crop in tropical regions of the world. Cassava improvement by breeding is limited by its delayed and poor production of flowers, such that cassava flowering under field conditions indirectly lengthens the breeding cycle. By studying genotype and environment interaction under two Nigerian field conditions (Ubiaja and Ibadan) and three controlled temperature conditions (22°C/18°C, 28/24°C and 34/30°C (day/night)), we found that while early flowering genotypes flowered at similar times and rates under all growing conditions (unfavorable and favorable field and controlled-temperature environments), late flowering genotypes were environmentally sensitive such that they were substantially delayed in unfavorable environments. On the basis of nodes-to-flower, flowering of late genotypes approached the flowering time of early flowering genotypes under relatively cool Ubiaja field conditions and in growth chambers at 22°C, whereas warmer temperatures elicited a delaying effect. Analysis of transcriptomes from leaves of field and controlled-temperature environments revealed that conditions which promote early flowering in cassava have low expression of the flowering repressor gene TEMPRANILLO 1 (TEM1), before and after flowering. Expression data of field plants showed that the balance between flower stimulatory and inhibitory signaling appeared to correlate with flowering time across the environments and genotypes.

Technological Innovations for Improving Cassava Production in Sub-Saharan Africa

Cassava is crucial for food security of millions of people in sub-Saharan Africa. The crop has great potential to contribute to African development and is increasing its income-earning potential for small-scale farmers and related value chains on the continent. Therefore, it is critical to increase cassava production, as well as its quality attributes. Technological innovations offer great potential to drive this envisioned change. This paper highlights genomic tools and resources available in cassava. The paper also provides a glimpse of how these resources have been used to screen and understand the pattern of cassava genetic diversity on the continent. Here, we reviewed the approaches currently used for phenotyping cassava traits, highlighting the methodologies used to link genotypic and phenotypic information, dissect the genetics architecture of key cassava traits, and identify quantitative trait loci/markers significantly associated with those traits. Additionally, we examined how knowledge acquired is utilized to contribute to crop improvement. We explored major approaches applied in the field of molecular breeding for cassava, their promises, and limitations. We also examined the role of national agricultural research systems as key partners for sustainable cassava production.

Factors Influencing Genomic Prediction Accuracies of Tropical Maize Resistance to Fall Armyworm and Weevils

Genomic selection (GS) can accelerate variety improvement when training set (TS) size and its relationship with the breeding set (BS) are optimized for prediction accuracies (PAs) of genomic prediction (GP) models. Sixteen GP algorithms were run on phenotypic best linear unbiased predictors (BLUPs) and estimators (BLUEs) of resistance to both fall armyworm (FAW) and maize weevil (MW) in a tropical maize panel. For MW resistance, 37% of the panel was the TS, and the BS was the remainder, whilst for FAW, random-based training sets (RBTS) and pedigree-based training sets (PBTSs) were designed. PAs achieved with BLUPs varied from 0.66 to 0.82 for MW-resistance traits, and for FAW resistance, 0.694 to 0.714 for RBTS of 37%, and 0.843 to 0.844 for RBTS of 85%, and these were at least two-fold those from BLUEs. For PBTS, FAW resistance PAs were generally higher than those for RBTS, except for one dataset. GP models generally showed similar PAs across individual traits whilst the TS designation was determinant, since a positive correlation (R = 0.92***) between TS size and PAs was observed for RBTS, and for the PBTS, it was negative (R = 0.44**). This study pioneered the use of GS for maize resistance to insect pests in sub-Saharan Africa.