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.

Development of sequence-based markers for seed protein content in pigeonpea.

Pigeonpea is an important source of dietary protein to over a billion people globally, but genetic enhancement of seed protein content (SPC) in the crop has received limited attention for a long time. Use of genomics-assisted breeding would facilitate accelerating genetic gain for SPC. However, neither genetic markers nor genes associated with this important trait have been identified in this crop. Therefore, the present study exploited whole genome re-sequencing (WGRS) data of four pigeonpea genotypes (~ 12X coverage) to identify sequence-based markers and associated candidate genes for SPC. By combining a common variant filtering strategy on available WGRS data with knowledge of gene functions in relation to SPC, 108 sequence variants from 57 genes were identified. These genes were assigned to 19 GO molecular function categories with 56% belonging to only two categories. Furthermore, Sanger sequencing confirmed presence of 75.4% of the variants in 37 genes. Out of 30 sequence variants converted into CAPS/dCAPS markers, 17 showed high level of polymorphism between low and high SPC genotypes. Assay of 16 of the polymorphic CAPS/dCAPS markers on an F2 population of the cross ICP 5529 (high SPC) × ICP 11605 (low SPC), resulted in four of the CAPS/dCAPS markers significantly (P < 0.05) co-segregated with SPC. In summary, four markers derived from mutations in four genes will be useful for enhancing/regulating SPC in pigeonpea crop improvement programs.

Agronomic Performance and Economics of Yield Loss Associated With Angular Leaf Spot Disease of Common Bean in the Southern Highlands of Tanzania.

Angular leaf spot (ALS) caused by Pseudocercospora griseola is among the devastating diseases of common bean (Phaseolus vulgaris L.) in the Southern Highlands of Tanzania (SHT). This study was conducted to assess the agronomic performance and economics of yield loss associated with the disease on five bean cultivars that are widely grown by farmers. The cultivars were evaluated in a split plot design with a randomized complete block arrangement during 2012/2013 and 2013/2014. The main plots were two rates of fungicide and a control whereas the subplots consisted of cultivars. Data were collected on disease severity, yield, and yield components. Analysis of variance was done and marginal rate of returns determined using partial budget. Results indicated significant decrease in yields, number of pods, seeds, and seed weight at P < 0.05 for untreated plots. Decreases in yield were associated with ALS disease severity that in turn was influenced by cultivar and rate of fungicide used. Higher grain yield losses of as much as 61% and the lowest marginal rate of returns were recorded for unsprayed plots during heavy rains. Fungicide usage at the recommended rates should be considered during heavy rains and breeding for resistance should be taken as an economical and sustainable strategy for managing the disease.

Mapping QTL conferring resistance in maize to gray leaf spot disease caused by Cercospora zeina.

BACKGROUND: Gray leaf spot (GLS) is a globally important foliar disease of maize. Cercospora zeina, one of the two fungal species that cause the disease, is prevalent in southern Africa, China, Brazil and the eastern corn belt of the USA. Identification of QTL for GLS resistance in subtropical germplasm is important to support breeding programmes in developing countries where C. zeina limits production of this staple food crop. RESULTS: A maize RIL population (F7:S6) from a cross between CML444 and SC Malawi was field-tested under GLS disease pressure at five field sites over three seasons in KwaZulu-Natal, South Africa. Thirty QTL identified from eleven field trials (environments) were consolidated to seven QTL for GLS resistance based on their expression in at least two environments and location in the same core maize bins. Four GLS resistance alleles were derived from the more resistant parent CML444 (bin 1.10, 4.08, 9.04/9.05, 10.06/10.07), whereas the remainder were from SC Malawi (bin 6.06/6.07, 7.02/7.03, 9.06). QTLs in bin 4.08 and bin 6.06/6.07 were also detected as joint QTLs, each explained more than 11% of the phenotypic variation, and were identified in four and seven environments, respectively. Common markers were used to allocate GLS QTL from eleven previous studies to bins on the IBM2005 map, and GLS QTL "hotspots" were noted. Bin 4.08 and 7.02/7.03 GLS QTL from this study overlapped with hotspots, whereas the bin 6.06/6.07 and bin 9.06 QTLs appeared to be unique. QTL for flowering time (bin 1.07, 4.09) in this population did not correspond to QTL for GLS resistance. CONCLUSIONS: QTL mapping of a RIL population from the subtropical maize parents CML444 and SC Malawi identified seven QTL for resistance to gray leaf spot disease caused by C. zeina. These QTL together with QTL from eleven studies were allocated to bins on the IBM2005 map to provide a basis for comparison. Hotspots of GLS QTL were identified on chromosomes one, two, four, five and seven, with QTL in the current study overlapping with two of these. Two QTL from this study did not overlap with previously reported QTL.

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.

Genomic Prediction of The Performance of Tropical Doubled Haploid Maize Lines under Artificial Striga hermonthica (Del.) Benth. Infestation.

Striga hermonthica (Del.) Benth., a parasitic weed, causes substantial yield losses in maize production in sub-Saharan Africa (SSA). Breeding for Striga resistance in maize is constrained by limited genetic diversity for Striga resistance within the elite germplasm and phenotyping capacity under artificial Striga infestation. Genomics-enabled approaches have the potential to accelerate identification of Striga resistant lines for hybrid development. The objectives of this study were to evaluate the accuracy of genomic selection for traits associated with Striga resistance and grain yield (GY) and to predict genetic values of tested and untested doubled haploid (DH) maize lines. We genotyped 606 DH lines with 8,439 rAmpSeq markers. A training set of 116 DH lines crossed to two testers was phenotyped under artificial Striga infestation at three locations in Kenya. Heritability for Striga resistance parameters ranged from 0.38‒0.65 while that for GY was 0.54. The prediction accuracies for Striga resistance-associated traits across locations, as determined by cross validation (CV) were 0.24 to 0.53 for CV0 and from 0.20 to 0.37 for CV2. For GY, the prediction accuracies were 0.59 and 0.56 for CV0 and CV2, respectively. The results revealed 300 DH lines with desirable genomic estimated breeding values (GEBVs) for reduced number of emerged Striga plants (STR) at 8, 10, and 12 weeks after planting. The GEBVs of DH lines for Striga resistance associated traits in the training and testing sets were similar in magnitude. These results highlight the potential application of genomic selection in breeding for Striga resistance in maize. The integration of genomic-assisted strategies and DH technology for line development coupled with forward breeding for major adaptive traits will enhance genetic gains in breeding for Striga resistance in maize.

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.

Factors influencing rice production in the south-eastern belt of Ghana.

Ghana has great potential to produce rice for local consumption, however, the average rice produced barely meets half of the country's consumption needs. Focus group discussions (FGDs) and surveys were held within the coastal lowland rice production belt in Ghana. The FGDs were held at Okyereko and Afife followed by surveys in the two communities in addition to Dawenya and Ashaiman. The objectives were to assess the production challenges faced by farmers in the four communities and determine the rice traits preferred by the farmers. Twenty farmers were involved in each of the FGDs while 227 respondents were selected through convenient sampling for the interviews. Sixty-nine percent of respondent farmers were male, 53% were above 50 years while 44% had varied levels of education. Farmers preferences mainly related to marketable traits such as aroma (87%), taste (83%) and yield potential (78%). There was special preference for Jasmine 85 (62.8%) and Togo Marshal l (25%), an indication of the high adoption of aromatic rice varieties in the study areas. Challenges such as securing credit, input supplies, soil salinity and ageing work force were matters of grave concern to respondent farmers. Given the importance of rice cultivation in the study areas to Ghana's quest to achieve self-sufficiency in rice, targeted and coordinated support from relevant governmental and non-governmental organizations is needed to sustain a higher level of production in the study areas.

Genome-Wide Association Study Reveals Genetic Architecture and Candidate Genes for Yield and Related Traits under Terminal Drought, Combined Heat and Drought in Tropical Maize Germplasm.

Maize (Zea mays L.) production is constrained by drought and heat stresses. The combination of these two stresses is likely to be more detrimental. To breed for maize cultivars tolerant of these stresses, 162 tropical maize inbred lines were evaluated under combined heat and drought (CHD) and terminal drought (TD) conditions. The mixed linear model was employed for the genome-wide association study using 7834 SNP markers and several phenotypic data including, days to 50% anthesis (AD) and silking (SD), husk cover (HUSKC), and grain yield (GY). In total, 66, 27, and 24 SNPs were associated with the traits evaluated under CHD, TD, and their combined effects, respectively. Of these, four single nucleotide polymorphism (SNP) markers (SNP_161703060 on Chr01, SNP_196800695 on Chr02, SNP_195454836 on Chr05, and SNP_51772182 on Chr07) had pleiotropic effects on both AD and SD under CHD conditions. Four SNPs (SNP_138825271 (Chr03), SNP_244895453 (Chr04), SNP_168561609 (Chr05), and SNP_62970998 (Chr06)) were associated with AD, SD, and HUSKC under TD. Twelve candidate genes containing phytohormone cis-acting regulating elements were implicated in the regulation of plant responses to multiple stress conditions including heat and drought. The SNPs and candidate genes identified in the study will provide invaluable information for breeding climate smart maize varieties under tropical conditions following validation of the SNP markers.

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.

Combining Ability and Heterotic Patterns of Tropical Early-Maturing Maize Inbred Lines under Individual and Combined Heat and Drought Environments.

Information on combining ability and heterotic patterns of multiple stress-tolerant inbred lines are fundamental prerequisites for devising appropriate breeding strategies for the development of climate-resilient maize hybrids. In the present study, we evaluated 150 single cross hybrids derived from the North Carolina Design II (NCD II) along with six commercial checks under terminal drought stress (TDS), heat stress (HS), and combined drought and heat stress (CHDS)conditions. The objectives of the study were to: (i) determine the combining ability of the inbred lines and identify the best testers across the stresses; (ii) classify the inbred lines into heterotic groups (HGs) based on the general combining ability of multiple traits (HGCAMT) and sequencing-based diversity array technology (DArTseq) and (iii) assess the performance and stability of the lines in hybrid combinations. The inbred lines showed significantly (p < 0.01 and p < 0.05) positive and negative general combining ability (GCA) and specific combining ability (SCA) effects for grain yield (GY) and most other measured traits. The inbred line TZEI 135 displayed relatively larger positive GCA effects for GY when mated either as male or female and was identified as the best tester. TZEI 135 × TZEI 182 was identified as the best single-cross tester across environments. Results of the assessment of the relative importance of GCA and SCA effects revealed the predominance of additive gene action over the non-additive. Six HGs of inbreds were identified using the HGCAMT and three, based on the DArTseq marker genetic distance method, were the most efficient. The best hybrids in this study significantly out-yielded the best checks by 21, 46, and 70% under CHDS, HS, and TDS, respectively. These hybrids should be extensively tested in on-farm trials for possible commercialization in sub-Saharan Africa.

Identification of Genomic Regions Associated with Agronomic and Disease Resistance Traits in a Large Set of Multiple DH Populations.

Breeding maize lines with the improved level of desired agronomic traits under optimum and drought conditions as well as increased levels of resistance to several diseases such as maize lethal necrosis (MLN) is one of the most sustainable approaches for the sub-Saharan African region. In this study, 879 doubled haploid (DH) lines derived from 26 biparental populations were evaluated under artificial inoculation of MLN, as well as under well-watered (WW) and water-stressed (WS) conditions for grain yield and other agronomic traits. All DH lines were used for analyses of genotypic variability, association studies, and genomic predictions for the grain yield and other yield-related traits. Genome-wide association study (GWAS) using a mixed linear FarmCPU model identified SNPs associated with the studied traits i.e., about seven and eight SNPs for the grain yield; 16 and 12 for anthesis date; seven and eight for anthesis silking interval; 14 and 5 for both ear and plant height; and 15 and 5 for moisture under both WW and WS environments, respectively. Similarly, about 13 and 11 SNPs associated with gray leaf spot and turcicum leaf blight were identified. Eleven SNPs associated with senescence under WS management that had depicted drought-stress-tolerant QTLs were identified. Under MLN artificial inoculation, a total of 12 and 10 SNPs associated with MLN disease severity and AUDPC traits, respectively, were identified. Genomic prediction under WW, WS, and MLN disease artificial inoculation revealed moderate-to-high prediction accuracy. The findings of this study provide useful information on understanding the genetic basis for the MLN resistance, grain yield, and other agronomic traits under MLN artificial inoculation, WW, and WS conditions. Therefore, the obtained information can be used for further validation and developing functional molecular markers for marker-assisted selection and for implementing genomic prediction to develop superior elite lines.

Grain Yield and Heterosis of Maize Hybrids under Nematode Infested and Nematicide Treated Conditions.

Plant-parasitic nematodes are present on maize but resistant genotypes have not been identified in Uganda. This study was aimed at determining the level of nematode resistance among F(1) hybrids, and to estimate grain yield, heterosis and yield losses associated with maize hybrids under nematode infestation. The 30 F(1) hybrids and two local checks were evaluated in a split plot design with nematode treatment (nematode infested versus nematicide treated) as the whole plot factor, and the hybrids as subplot factors arranged in an 8 x 4 alpha-lattice design. The experiment was conducted simultaneously at three sites. The hybrids were also evaluated in a split plot design under greenhouse conditions at IITA-Namulonge. Results revealed 24 P. zeae susceptible hybrids compared to only six P. zeae resistant hybrids. Grain yield across sites was higher by about 400 kg ha(-1) under nematicide treatment than under nematode infestation. The nematode tolerant/resistant hybrids exhibited yields ranging from 5.0 to 8.4 t ha(-1) compared to 5.0 t ha(-1) obtained from the best check. Grain yield loss was up to 28% among susceptible hybrids, indicating substantial economic yield losses due to nematodes. Under field conditions, desired heterosis was recorded on 18 hybrids for P. zeae, and on three hybrids for Meloidogyne spp. Under nematode infestation, only 16 hybrids had higher relative yield compared to the mean of both checks, the best check and the trial mean, whereas it was 20 hybrids under nematicide treated plots. Overall, most outstanding hybrids under nematode infestation were CML395/MP709, CML312/5057, CML312/CML206, CML312/CML444, CML395/CML312 and CML312/CML395. Therefore, grain yield loss due to nematodes is existent but can be significantly reduced by growing nematode resistant hybrids.

Drought Tolerance and Application of Marker-Assisted Selection in Sorghum.

Sorghum is an important staple food crop in drought prone areas of Sub-Saharan Africa, which is characterized by erratic rainfall with poor distribution. Sorghum is a drought-tolerant crop by nature with reasonable yield compared to other cereal crops, but such abiotic stress adversely affects the productivity. Some sorghum varieties maintain green functional leaves under post-anthesis drought stress referred to as stay-green, which makes it an important crop for food and nutritional security. Notwithstanding, it is difficult to maintain consistency of tolerance over time due to climate change, which is caused by human activities. Drought in sorghum is addressed by several approaches, for instance, breeding drought-tolerant sorghum using conventional and molecular technologies. The challenge with conventional methods is that they depend on phenotyping stay-green, which is complex in sorghum, as it is constituted by multiple genes and environmental effects. Marker assisted selection, which involves the use of DNA molecular markers to map QTL associated with stay-green, has been useful to supplement stay-green improvement in sorghum. It involves QTL mapping associated with the stay-green trait for introgression into the senescent sorghum varieties through marker-assisted backcrossing by comparing with phenotypic field data. Therefore, this review discusses mechanisms of drought tolerance in sorghum focusing on physiological, morphological, and biochemical traits. In addition, the review discusses the application of marker-assisted selection techniques, including marker-assisted backcrossing, QTL mapping, and QTL pyramiding for addressing post-flowering drought in sorghum.

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.

Genetic diversity and inter-trait relationship of tropical extra-early maturing quality protein maize inbred lines under low soil nitrogen stress.

Information on the genetic diversity, population structure, and trait associations of germplasm resources is crucial for predicting hybrid performance. The objective of this study was to dissect the genetic diversity and population structure of extra-early yellow and orange quality protein maize (QPM) inbred lines and identify secondary traits for indirect selection for enhanced grain yield under low-soil nitrogen (LN). One hundred and ten inbred lines were assessed under LN (30 kg ha -1) and assayed for tryptophan content. The lines were genotyped using 2500 single nucleotide polymorphism (SNP) markers. Majority (85.4%) of the inbred lines exhibited wide pairwise genetic distances between 0.4801 and 0.600. Genetic distances were wider between yellow and orange endosperm lines and predicted high heterosis in crosses between parents of different endosperm colors. The unweighted pair group method with arithmetic mean (UPGMA) and the admixture model-based population structure method both grouped the lines into five clusters. The clustering was based on endosperm color, pedigree, and selection history but not on LN tolerance or tryptophan content. Genotype by trait biplot analysis revealed association of grain yield with plant height and ear height. TZEEQI 394 and TZEEIORQ 73A had high expressivity for these traits. Indirect selection for high grain yield among the inbred lines could be achieved using plant and ear heights as selection criteria. The wide genetic variability observed in this study suggested that the inbred lines could be important sources of beneficial alleles for LN breeding programs in SSA.

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.

Introgression of Maize Lethal Necrosis Resistance Quantitative Trait Loci Into Susceptible Maize Populations and Validation of the Resistance Under Field Conditions in Naivasha, Kenya.

Maize lethal necrosis (MLN), resulting from co-infection by maize chlorotic mottle virus (MCMV) and sugarcane mosaic virus (SCMV) can cause up to 100% yield losses in maize in Africa under serious disease conditions. Maize improvement through conventional backcross (BC) takes many generations but can significantly be shortened when molecular tools are utilized in the breeding process. We used a donor parent (KS23-6) to transfer quantitative trait loci (QTL) for resistance to MLN into nine adapted but MLN susceptible lines. Nurseries were established in Kiboko, Kenya during 2015-2017 seasons and BC3F2 progeny were developed using marker assisted backcrossing (MABC) approach. Six single nucleotide polymorphism (SNP) markers linked to QTL for resistance to MLN were used to genotype 2,400 BC3F2 lines using Kompetitive Allele Specific PCR (KASP) platform. We detected that two of the six QTL had major effects for resistance to MLN under artificial inoculation field conditions in 56 candidate BC3F2 lines. To confirm whether these two QTL are reproducible under different field conditions, the 56 BC3F2 lines including their parents were evaluated in replicated trials for two seasons under artificial MLN inoculations in Naivasha, Kenya in 2018. Strong association of genotype with phenotype was detected. Consequently, 19 superior BC3F2 lines with favorable alleles and showing improved levels of resistance to MLN under artificial field inoculation were identified. These elite lines represent superior genetic resources for improvement of maize hybrids for resistance to MLN. However, 20 BC3F2 lines were fixed for both KASP markers but were susceptible to MLN under field conditions, which could suggest weak linkage between the KASP markers and target genes. The validated two major QTL can be utilized to speed up the breeding process but additional loci need to be identified between the KASP markers and the resistance genes to strengthen the linkage.