Maximizing efficiency of genomic selection in CIMMYT's tropical maize breeding program.

KEY MESSAGE: Historical data from breeding programs can be efficiently used to improve genomic selection accuracy, especially when the training set is optimized to subset individuals most informative of the target testing set. The current strategy for large-scale implementation of genomic selection (GS) at the International Maize and Wheat Improvement Center (CIMMYT) global maize breeding program has been to train models using information from full-sibs in a "test-half-predict-half approach." Although effective, this approach has limitations, as it requires large full-sib populations and limits the ability to shorten variety testing and breeding cycle times. The primary objective of this study was to identify optimal experimental and training set designs to maximize prediction accuracy of GS in CIMMYT's maize breeding programs. Training set (TS) design strategies were evaluated to determine the most efficient use of phenotypic data collected on relatives for genomic prediction (GP) using datasets containing 849 (DS1) and 1389 (DS2) DH-lines evaluated as testcrosses in 2017 and 2018, respectively. Our results show there is merit in the use of multiple bi-parental populations as TS when selected using algorithms to maximize relatedness between the training and prediction sets. In a breeding program where relevant past breeding information is not readily available, the phenotyping expenditure can be spread across connected bi-parental populations by phenotyping only a small number of lines from each population. This significantly improves prediction accuracy compared to within-population prediction, especially when the TS for within full-sib prediction is small. Finally, we demonstrate that prediction accuracy in either sparse testing or "test-half-predict-half" can further be improved by optimizing which lines are planted for phenotyping and which lines are to be only genotyped for advancement based on GP.

Bridging old and new: diversity and evaluation of high iron-associated stress response of rice cultivated in West Africa.

Adoption of rice varieties that perform well under high iron-associated (HIA) stress environments can enhance rice production in West Africa. This study reports the genetic characterization of 323 rice accessions and breeding lines cultivated in West Africa using genotyping-by-sequencing and their phenotypic response to HIA treatments in hydroponic solution (1500 mg l-1 FeSO4·7H2O) and hot-spot fields. The germplasm consisted of four genetic subpopulations: Oryza glaberrima (14%), O. sativa-japonica (7%), O. sativa-indica Group 1 (45%), and O. sativa-indica Group 2 (25%). Severe versus mild stress in the field was associated with a reduced SPAD value (12%), biomass (56%), and grain yield (57%), with leaf bronzing explaining 30% and 21% of the variation for biomass and grain yield, respectively. Association mapping using 175 indica genotypes identified 23 significant single nucleotide polymorphism (SNP) markers that mapped to 14 genomic regions. Genome-wide association study (GWAS) signals associated with leaf bronzing, a routinely used indicator of HIA stress, differed in hydroponic compared with field conditions. Contrastingly, six significant SNPs on chromosomes 8 and 9 were associated with the SPAD value under HIA stress in both field and hydroponic experiments, and a candidate potassium transporter gene mapped under the peak on chromosome 8. This study helps define criteria for assessing rice performance under HIA environments.

Molecular and phenotypic diversity of groundnut (Arachis hypogaea L.) cultivars in Togo.

Diversity assessment of 94 groundnut accessions from Togo and Senegal, using agro-morphological and SNP markers, revealed high variability for many quantitative traits such as late leaf spot (LLS) incidence, number of pods per plant and yield per plant. For qualitative traits, the Simpson Index showed high diversity for primary seed colour (0.75), stem pigmentation (0.60), and Growth habit (0.59). Principal component analysis underscored quantitative traits such as hundred seed weight, days to maturity, and LLS incidence, as the main traits contributing to the divergence. Correlation and path coefficient analysis showed that the number of pods per plant was the main yield-related trait positively affecting yield (r = 0.95, PC = 0.84; p = 0.01). Overall, 990 SNP markers revealed moderate genetic variability in the genotypes and the percentage of heterozygous genotypes varied from 0 to 50% for all loci. Analysis of molecular variance revealed that only 1.1% of the total molecular variance accounted for geographical contribution to the diversity. Co-analysis of phenotypic and SNP data delineated three clusters harbouring useful alleles and interesting phenotypic features such as LLS resistance, large number of pods per plant and early maturity indicating that differences observed at the phenotypic level are underlined by genotypic differences. The phenotypic and genotypic diversity observed could be exploited for the identification of parents with preferred traits for use in the breeding program. However, the low population structure highlights the necessity to improve groundnut diversity in Togo through introduction from various sources.

Genetic characterization of cassava (Manihot esculenta Crantz) genotypes using agro-morphological and single nucleotide polymorphism markers.

Dearth of information on extent of genetic variability in cassava limits the genetic improvement of cassava genotypes in Sierra Leone. The aim of this study was to assess the genetic diversity and relationships within 102 cassava genotypes using agro-morphological and single nucleotide polymorphism markers. Morphological classification based on qualitative traits categorized the germplasm into five different groups, whereas the quantitative trait set had four groups. The SNP markers classified the germplasm into three main cluster groups. A total of seven principal components (PCs) in the qualitative and four PCs in the quantitative trait sets accounted for 79.03% and 72.30% of the total genetic variation, respectively. Significant and positive correlations were observed between average yield per plant and harvest index (r = 0.76***), number of storage roots per plant and harvest index (r = 0.33*), height at first branching and harvest index (0.26*), number of storage roots per plant and average yield per plant (r = 0.58*), height at first branching and average yield per plant (r = 0.24*), length of leaf lobe and petiole length (r = 0.38*), number of leaf lobe and petiole length (r = 0.31*), width of leaf lobe and length of leaf lobe (r = 0.36*), number of leaf lobe and length of leaf lobe (r = 0.43*), starch content and dry matter content (r = 0.99***), number of leaf lobe and root dry matter (r = 0.30*), number of leaf lobe and starch content (r = 0.28*), and height at first branching and plant height (r = 0.45**). Findings are useful for conservation, management, short term recommendation for release and genetic improvement of the crop.

Allelic diversity of S-RNase alleles in diploid potato species.

KEY MESSAGE: The S-ribonuclease sequences of 16 S-alleles derived from diploid types of Solanum are presented. A phylogenetic analysis and partial phenotypic analysis support the conclusion that these are functional S-alleles. S-Ribonucleases (S-RNases) control the pistil specificity of the self-incompatibility (SI) response in the genus Solanum and several other members of the Solanaceae. The nucleotide sequences of S-RNases corresponding to a large number of S-alleles or S-haplotypes have been characterised. However, surprisingly, few S-RNase sequences are available for potato species. The identification of new S-alleles in diploid potato species is desirable as these stocks are important sources of traits such as biotic and abiotic resistance. S-RNase sequences are reported here from three distinct diploid types of potato: cultivated Solanum tuberosum Group Phureja, S. tuberosum Group Stenotomum, and the wild species Solanum okadae. Partial S-RNase sequences were obtained from pistil RNA by RT-PCR or 3'RACE (Rapid Amplification of cDNA Ends) using a degenerate primer. Full-length sequences were obtained for two alleles by 5'RACE. Database searches with these sequences identified 16 S-RNases in total, all of which are novel. The sequence analysis revealed all the expected features of functional S-RNases. Phylogenetic analysis with selected published S-RNase and S-like-RNase sequences from the Solanaceae revealed extensive trans-generic evolution of the S-RNases and a clear distinction from S-like-RNases. Pollination tests were used to confirm the self-incompatibility status and cross-compatibility relationships of the S. okadae accessions. All the S. okadae accessions were found to be self-incompatible as expected with crosses amongst them exhibiting both cross-compatibility and semi-compatibility consistent with the S-genotypes determined from the S-RNase sequence data. The progeny analysis of four semi-compatible crosses examined by allele-specific PCR provided further confirmation that these are functional S-RNases.

Novel SNP markers and other stress-related genomic regions associated with nitrogen use efficiency in cassava.

Cassava productivity is constrained by low soil nitrogen, which is predominant in most cassava-growing regions in the tropics and subtropical agroecology. Improving the low nitrogen tolerance of cassava has become an important breeding objective. The current study aimed to develop cassava varieties with improved nitrogen use efficiency by identifying genomic regions and candidate genes linked to nitrogen use efficiency in cassava. A genome-wide association study (GWAS) was performed using the Genome Association and Prediction Integrated Tool (GAPIT). A panel of 265 diverse cassava genotypes was phenotyped for 10 physiological and agronomic traits under optimum and low-nitrogen regimes. Whole-genome genotyping of these cassava cloneswas performed using the Diversity Arrays Technology (DArTseq) sequencing platform. A total of 68,814 single nucleotide polymorphisms (SNPs) were identified, which were spread across the entire 18 chromosomes of the cassava genome, of which 52 SNPs at various densities were found to be associated with nitrogen use efficiency in cassava and other yield-related traits. The putative genes identified through GWAS, especially those with significant associated SNP markers for NUE and related traits have the potential, if deployed appropriately, to develop cassava varieties with improved nitrogen use efficiency, which would translate to a reduction in the economic and environmental cost of cassava production.

Genotype-by-environment interaction and stability of root mealiness and other organoleptic properties of boiled cassava roots.

Genetic enhancement of cassava aimed at improving cooking and eating quality traits is a major goal for cassava breeders to address the demand for varieties that are desirable for the fresh consumption market segment. Adoption of such cassava genotypes by consumers will largely rely not only on their agronomic performance, but also on end-user culinary qualities such as root mealiness. The study aimed to examine genotype × environment interaction (GEI) effects for root mealiness and other culinary qualities in 150 cassava genotypes and detect genotypes combining stable performance with desirable mealiness values across environments using GGE biplot analysis. Experiments were conducted using an alpha-lattice design with three replications for two years in three locations in Nigeria. The analysis of variance revealed a significant influence of genotype, environment, and GEI on the performance of genotypes. Mealiness scores showed no significant relationship with firmness values of boiled roots assessed by a penetration test, implying that large-scale rapid and accurate phenotyping of mealiness of boiled cassava roots remains a major limitation for the effective development of varieties with adequate mealiness, a good quality trait for direct consumption (boil-and-eat) as well as for pounding into 'fufu'. The moderate broad-sense heritability estimate and relatively high genetic advance observed for root mealiness suggest that significant genetic gains can be achieved in a future hybridization program. The genotype main effects plus genotype × environment interaction (GGE) biplot analysis showed that the different test environments discriminated among the genotypes. Genotypes G80 (NR100265) and G120 (NR110512) emerged as the best performers for root mealiness in Umudike, whereas G13 (B1-50) and the check, G128 (TMEB693) performed best in Igbariam and Otobi. Based on the results of this study, five genotypes, G13 (B1-50), G34 (COB6-4), G46 (NR010161), the check, G128 (TMEB693), and G112 (NR110376), which were found to combine stability with desirable mealiness values, were the most suitable candidates to recommend for use as parents to improve existing cassava germplasm for root mealiness.

Combining ability studies of grain Fe and Zn contents of pearl millet (Pennisetum glaucum L.) in West Africa.

Micronutrient malnutrition is a major challenge in Africa, where half a million children die each year because of lack of micronutrients in their food. Pearl millet is an important food and fodder crop for the people living in the Semi-Arid regions of West Africa. The present study was conducted to determine the stability, combining ability, and gene action conditions of the high level of Fe and Zn content in grain and selected agronomic traits. Hence, eight genotypes were selected based on the availability of grain Fe and Zn contents and crossed in a full diallel mating design. Progenies from an 8 × 8 diallel mating along with the parents were evaluated in an alpha lattice design with three replications in three locations for two years. The parental lines Jirani, LCIC 9702 and MORO, had positive significant general combining ability (GCA) effects for grain Fe concentration, while Jirani and MORO had positive significant GCA effects for grain Zn concentration. For the specific combining ability (SCA), among the 56 hybrids evaluated, only the hybrids LCIC 9702 × Jirani and MORO × ZANGO had positive significant SCA effects for grain Fe concentration across locations, and for grain Zn concentration, the hybrids Gamoji × MORO, LCIC 9702 × Jirani, and ICMV 167006 × Jirani had positive significant SCA effects. The reciprocal effects were significant for grain Zn concentration, grain yield, flowering time, plant height, test weight, and downy mildew incidence, suggesting that the choice of a female or male parent is critical in hybrid production. Grain Fe and Zn concentration, flowering time, plant height, panicle length, panicle girth, panicle compactness, and downy mildew incidence were found to be predominantly under additive gene action, while grain yield and test weight were predominantly under non-additive gene action. A highly positive correlation was found between grain Fe and Zn concentrations, which implies that improving grain Fe trait automatically improves the grain Zn content. The stability analysis revealed that the hybrid ICMV 167006 × Jirani was the most stable and high-yielding with a high level of grain Fe and Zn micronutrients.

Genome-Wide Association Study of Root Mealiness and Other Texture-Associated Traits in Cassava.

Cassava breeders have made significant progress in developing new genotypes with improved agronomic characteristics such as improved root yield and resistance against biotic and abiotic stresses. However, these new and improved cassava (Manihot esculenta Crantz) varieties in cultivation in Nigeria have undergone little or no improvement in their culinary qualities; hence, there is a paucity of genetic information regarding the texture of boiled cassava, particularly with respect to its mealiness, the principal sensory quality attribute of boiled cassava roots. The current study aimed at identifying genomic regions and polymorphisms associated with natural variation for root mealiness and other texture-related attributes of boiled cassava roots, which includes fibre, adhesiveness (ADH), taste, aroma, colour, and firmness. We performed a genome-wide association (GWAS) analysis using phenotypic data from a panel of 142 accessions obtained from the National Root Crops Research Institute (NRCRI), Umudike, Nigeria, and a set of 59,792 high-quality single nucleotide polymorphisms (SNPs) distributed across the cassava genome. Through genome-wide association mapping, we identified 80 SNPs that were significantly associated with root mealiness, fibre, adhesiveness, taste, aroma, colour and firmness on chromosomes 1, 4, 5, 6, 10, 13, 17 and 18. We also identified relevant candidate genes that are co-located with peak SNPs linked to these traits in M. esculenta. A survey of the cassava reference genome v6.1 positioned the SNPs on chromosome 13 in the vicinity of Manes.13G026900, a gene recognized as being responsible for cell adhesion and for the mealiness or crispness of vegetables and fruits, and also known to play an important role in cooked potato texture. This study provides the first insights into understanding the underlying genetic basis of boiled cassava root texture. After validation, the markers and candidate genes identified in this novel work could provide important genomic resources for use in marker-assisted selection (MAS) and genomic selection (GS) to accelerate genetic improvement of root mealiness and other culinary qualities in cassava breeding programmes in West Africa, especially in Nigeria, where the consumption of boiled and pounded cassava is low.

Scalable Sparse Testing Genomic Selection Strategy for Early Yield Testing Stage.

To enable a scalable sparse testing genomic selection (GS) strategy at preliminary yield trials in the CIMMYT maize breeding program, optimal approaches to incorporate genotype by environment interaction (GEI) in genomic prediction models are explored. Two cross-validation schemes were evaluated: CV1, predicting the genetic merit of new bi-parental populations that have been evaluated in some environments and not others, and CV2, predicting the genetic merit of half of a bi-parental population that has been phenotyped in some environments and not others using the coefficient of determination (CDmean) to determine optimized subsets of a full-sib family to be evaluated in each environment. We report similar prediction accuracies in CV1 and CV2, however, CV2 has an intuitive appeal in that all bi-parental populations have representation across environments, allowing efficient use of information across environments. It is also ideal for building robust historical data because all individuals of a full-sib family have phenotypic data, albeit in different environments. Results show that grouping of environments according to similar growing/management conditions improved prediction accuracy and reduced computational requirements, providing a scalable, parsimonious approach to multi-environmental trials and GS in early testing stages. We further demonstrate that complementing the full-sib calibration set with optimized historical data results in improved prediction accuracy for the cross-validation schemes.

Farmers' knowledge, perception, and use of phosphorus fertilization for cowpea production in Northern Guinea Savannah of Nigeria.

Cowpea (Vigna unguiculata L. Walp) is an important legume crop, especially in sub-Saharan Africa. Poor soil fertility is among the major abiotic factors that contribute to this crop's low yield. Phosphorus (P)-based fertilizers significantly increase cowpea yields but these fertilizers are not well adopted by smallholder cowpea farmers. To understand why, we surveyed 420 farmers across three major cowpea-producing states in Nigeria: first, we assessed the cowpea farmers' knowledge and perception of the need for fertilizers, especially P fertilizers; and, second, we identified factors that determine the use - or non-use - of P-based fertilizers. Although over 80% of farmers surveyed were aware of the value of fertilizers as a yield-increasing factor and were able to identify crops suffering from nutrient deficiency, only 10% used P-based fertilizers like single super phosphate (SSP) and another 11% used combinations of nitrogen, phosphorus, and potassium compound fertilizers and SSP for cowpeas. Reasons for not using P-containing fertilizers included high cost, poor availability in rural markets, and lack of awareness on the need to use P fertilizers. Additionally, many growers believed that cowpeas do not require fertilizers, especially if the previous crop had been maize. Our findings are important for strategies to increase the productivity of cowpeas among smallholder growers especially in the northern regions of Nigeria and beyond, where subsistence farming systems are prevalent. Increased cowpea production through the adequate use of inputs like P fertilizers will support Nigeria's effort to reduce its large imports of cowpea grain from neighboring countries. Our survey further demonstrated that P-containing fertilizers are crucial production inputs for increased cowpea production in these regions and in areas with similar traditional farming practices. Our results will benefit breeders, development partners, extension personnel, and other stakeholders in cowpea value chains.

Groundnut production constraints and farmers' trait preferences: a pre-breeding study in Togo.

BACKGROUND: Groundnut is an important legume crop in Togo. However, groundnut yield has been steadily decreasing for decades as a result of lack of organized breeding program to address production constraints. Though, low yielding varieties and late leaf spot have been often reported as the most important constraints, there is no documented evidence. Identifying and documenting the major production constraints is a prerequisite for establishing a good breeding program with clearly defined priority objectives and breeding strategies. Thus, the objectives of this study were to identify groundnut production constraints and assess farmers' preferred traits. METHODS: A participatory rural appraisal approach was used to collect data on agronomic practices, farmers' preferences, and possible threats to production through individual and group interviews. Three regions and three villages per region were selected based on the representativeness of groundnut production systems. In each village, 20 farmers were randomly selected and interviewed; thus, a total of 180 farmers were interviewed. Content analysis was carried out for qualitative data and for quantitative data generated within and across regions, comparative descriptive statistics were carried out. Differences in perception and preferences were assessed using chi-square tests. RESULTS: The study has revealed that, though there were some variation across the regions, traits pertaining to yield such as pod yield (66.66%) and pod size (12.12%) were the most important. Leaf spot diseases, rosette and peanut bud necrosis (37.77%) and insects such as pod sucking bug and bruchid (27.77%) were considered to be the most important constraints limiting groundnut production. Among diseases, farmers in all the three regions indicated that late leaf spot is of economic importance which they associated to various causes such as maturity, drought, or insects. No gender differences were observed for the perception of constraints and groundnut traits preferences. Land size is significantly influenced by age and gender. Besides, farmers have pointed the lack of improved varieties and the unavailability of groundnut seeds highlighting the necessity of a sustainable groundnut seed system linked with a strong breeding program. CONCLUSION: This study has enabled understanding of the farming practices, constraints, and farmers preferred characteristics, thus providing the basis for a participatory breeding program in Togo which should consider that farmers perceive low yielding varieties and diseases as major constraints to production.

Cross-species gene expression analysis of species specific differences in the preclinical assessment of pharmaceutical compounds.

Animals are frequently used as model systems for determination of safety and efficacy in pharmaceutical research and development. However, significant quantitative and qualitative differences exist between humans and the animal models used in research. This is as a result of genetic variation between human and the laboratory animal. Therefore the development of a system that would allow the assessment of all molecular differences between species after drug exposure would have a significant impact on drug evaluation for toxicity and efficacy. Here we describe a cross-species microarray methodology that identifies and selects orthologous probes after cross-species sequence comparison to develop an orthologous cross-species gene expression analysis tool. The assumptions made by the use of this orthologous gene expression strategy for cross-species extrapolation is that; conserved changes in gene expression equate to conserved pharmacodynamic endpoints. This assumption is supported by the fact that evolution and selection have maintained the structure and function of many biochemical pathways over time, resulting in the conservation of many important processes. We demonstrate this cross-species methodology by investigating species specific differences of the peroxisome proliferator-activator receptor (PPAR) α response in rat and human.