Unravelling marker trait associations linking nutritional value with pigmentation in rice seed

Open Access JournalWhile considerable breeding effort has focused on increasing the yields of staple crops such as rice and the levels of micronutrients such as iron and zinc, breeding to address the problems of the double-burden of malnutrition has received less attention. Pigmented rice has higher nutritional value and greater health benefits compared to white rice. However, the genetic associations underlying pericarp coloration and accumulation of nutritionally valuable compounds is still poorly understood. Here we report the targeted genetic analysis of 364 rice accessions, assessing the genetic relationship between pericarp coloration (measured using multi-spectral imaging) and a range of phenolic compounds with potential nutritional and health-promoting characteristics. A genome-wide association study resulted in the identification of over 280 single nucleotide polymorphisms (SNPs) associated with the traits of interest. Many of the SNPs were associated with more than one trait, colocalization occurring between nutritional traits, and nutritional and color-related traits. Targeted association analysis identified 67 SNPs, located within 52 candidate genes and associated with 24 traits. Six haplotypes identified within the genes Rc/bHLH17 and OsIPT5 indicated that these genes have an important role in the regulation of a wide range of phenolic compounds, and not only those directly conferring pericarp color. These identified genetic linkages between nutritionally valuable phenolic compounds and pericarp color present not only a valuable resource for the enhancement of the nutritional value of rice but an easy method of selection of suitable genotypes

Technological innovations for improving cassava production in sub-Saharan Africa

Open Access Journal; Published online: 21 Jan 2021Cassava 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

Low-cost, handheld near-infrared spectroscopy for root dry matter content prediction in cassava

Open Access Journal; Published online: 31 Mar 2022Over 800 million people across the tropics rely on cassava (Manihot esculenta Crantz) as a major source of calories. While the root dry matter content (RDMC) of this starchy root crop is important for both producers and consumers, characterization of RDMC by traditional methods is time-consuming and laborious for breeding programs. Alternate phenotyping methods have been proposed but lack the accuracy, cost, or speed ultimately needed for cassava breeding programs. For this reason, we investigated the use of a low-cost, handheld near-infrared spectrometer (740–1070 nm) for field-based RDMC prediction in cassava. Oven-dried measurements of RDMC were paired with 21,044 scans of roots of 376 diverse genotypes from 10 field trials in Nigeria and grouped into training and test sets based on cross-validation schemes relevant to plant breeding programs. Mean partial least squares regression model performance ranged from R2P = 0.62–0.89 for within-trial predictions, which is within the range achieved with laboratory-grade spectrometers in previous studies. Relative to other factors, model performance was highly affected by the inclusion of samples from the same environment in both the training and test sets. With appropriate model calibration, the tested spectrometer will allow for field-based collection of spectral data with a smartphone for accurate RDMC prediction and potentially other quality traits, a step that could be easily integrated into existing harvesting workflows of cassava breeding programs

Conversion and validation of uniplex SNP markers for selection of resistance to Cassava Mosaic Disease in Cassava breeding programs

Open Access journal; Published online: 25 Feb 2021Cassava mosaic disease (CMD) is a major viral disease adversely affecting cassava production in Africa and Asia. Genomic regions conferring resistance to the disease have been mapped in African cassava germplasm through biparental quantitative trait loci (QTL) mapping and genome-wide association studies. To facilitate the utilization of these markers in breeding pipelines to support selections, proof-of-concept technical and biological validation research was carried out using independent pre-breeding and breeding populations. Kompetitive Allele-Specific Polymerase Chain Reaction (KASP) assays were designed from three single nucleotide polymorphism (SNP) markers linked to a major resistance locus on chromosome 12 (S12_7926132, S12_7926163) and a minor locus on chromosome 14 (S14_4626854). The designed assays were robust and easy to score with >99% genotype call rate. The overall predictive accuracy (proportion of true positives and true negatives) of the markers (S12_7926132 and S14_4626854) was 0.80 and 0.78 in the pre-breeding and breeding population, respectively. On average, genotypes that carried at least one copy of the resistant allele at the major CMD2 locus had a significantly higher yield advantage. Nevertheless, variation was observed in prediction accuracies for the major locus (S12_7926132) among sub-families from the two populations, suggesting the need for context-specific utilization, for example, by screening for co-segregation of favorable SNP alleles with resistance in the parents being used for crosses. Availability of these validated SNP markers on the uniplex KASP genotyping platform represents an important step in translational genetics toward marker-assisted selection to accelerate introgression of favorable resistant alleles in breeding populations

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

Open Access Journal; Published online: 12 Oct 2022Provitamin 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

Breeding schemes: what are they, how to formalize them, and how to improve them?

Open Access Journal; Published online: 21 Jan 2022Formalized breeding schemes are a key component of breeding program design and a gateway to conducting plant breeding as a quantitative process. Unfortunately, breeding schemes are rarely defined, expressed in a quantifiable format, or stored in a database. Furthermore, the continuous review and improvement of breeding schemes is not routinely conducted in many breeding programs. Given the rapid development of novel breeding methodologies, it is important to adopt a philosophy of continuous improvement regarding breeding scheme design. Here, we discuss terms and definitions that are relevant to formalizing breeding pipelines, market segments and breeding schemes, and we present a software tool, Breeding Pipeline Manager, that can be used to formalize and continuously improve breeding schemes. In addition, we detail the use of continuous improvement methods and tools such as genetic simulation through a case study in the International Institute of Tropical Agriculture (IITA) Cassava east-Africa pipeline. We successfully deploy these tools and methods to optimize the program size as well as allocation of resources to the number of parents used, number of crosses made, and number of progeny produced. We propose a structured approach to improve breeding schemes which will help to sustain the rates of response to selection and help to deliver better products to farmers and consumers

Predicting starch content in cassava fresh roots using near-infrared spectroscopy

Open Access Journal; Published online: 08 Nov 2022The cassava starch market is promising in sub-Saharan Africa and increasing rapidly due to the numerous uses of starch in food industries. More accurate, high-throughput, and cost-effective phenotyping approaches could hasten the development of cassava varieties with high starch content to meet the growing market demand. This study investigated the effectiveness of a pocket-sized SCiO™ molecular sensor (SCiO) (740−1070 nm) to predict starch content in freshly ground cassava roots. A set of 344 unique genotypes from 11 field trials were evaluated. The predictive ability of individual trials was compared using partial least squares regression (PLSR). The 11 trials were aggregated to capture more variability, and the performance of the combined data was evaluated using two additional algorithms, random forest (RF) and support vector machine (SVM). The effect of pretreatment on model performance was examined. The predictive ability of SCiO was compared to that of two commercially available near-infrared (NIR) spectrometers, the portable ASD QualitySpec® Trek (QST) (350−2500 nm) and the benchtop FOSS XDS Rapid Content™ Analyzer (BT) (400−2490 nm). The heritability of NIR spectra was investigated, and important spectral wavelengths were identified. Model performance varied across trials and was related to the amount of genetic diversity captured in the trial. Regardless of the chemometric approach, a satisfactory and consistent estimate of starch content was obtained across pretreatments with the SCiO (correlation between the predicted and the observed test set, (R2 P): 0.84−0.90; ratio of performance deviation (RPD): 2.49−3.11, ratio of performance to interquartile distance (RPIQ): 3.24−4.08, concordance correlation coefficient (CCC): 0.91−0.94). While PLSR and SVM showed comparable prediction abilities, the RF model yielded the lowest performance. The heritability of the 331 NIRS spectra varied across trials and spectral regions but was highest (H2 > 0.5) between 871−1070 nm in most trials. Important wavelengths corresponding to absorption bands associated with starch and water were identified from 815 to 980 nm. Despite its limited spectral range, SCiO provided satisfactory prediction, as did BT, whereas QST showed less optimal calibration models. The SCiO spectrometer may be a cost-effective solution for phenotyping the starch content of fresh roots in resource-limited cassava breeding programs

Molecular and cytological characterization of the global Musa germplasm collection provides insights into the treasure of banana diversity

© 2016, The Author(s). Bananas (Musa spp.) are one of the main fruit crops grown worldwide. With the annual production reaching 144 million tons, their production represents an important contribution to the economies of many countries in Asia, Africa, Latin-America and Pacific Islands. Most importantly, bananas are a staple food for millions of people living in the tropics. Unfortunately, sustainable banana production is endangered by various diseases and pests, and the breeding for resistant cultivars relies on a far too small base of genetic variation. Greater diversity needs to be incorporated in breeding, especially of wild species. Such work requires a large and thoroughly characterized germplasm collection, which also is a safe depository of genetic diversity. The largest ex situ Musa germplasm collection is kept at the International Transit Centre (ITC) in Leuven (Belgium) and currently comprises over 1500 accessions. This report summarizes the results of systematic cytological and molecular characterization of the Musa ITC collection. By December 2015, 630 accessions have been genotyped. The SSR markers confirmed the previous morphological based classification for 84% of ITC accessions analyzed. The remaining 16% of the genotyped entries may need field verification by taxonomist to decide if the unexpected classification by SSR genotyping was correct. The ploidy level estimation complements the molecular data. The genotyping continues for the entire ITC collection, including newly introduced accessions, to assure that the genotype of each accession is known in the largest global Musa gene bank. Open Access ispartof: Biodiversity and Conservation vol:26 issue:4 pages:801-824 status: publishe

Molecular markerbased genetic linkage map of a diploid banana population (Musa acuminata Colla)

A well-saturated genetic linkage map is valuable for fundamental and applied genetic research. Genetic linkage maps of two half-sib diploid banana populations were constructed using allele-specific-polymerase chain reactions (AS-PCRs), diversity array technology (DArT), and simple sequence repeat (SSR) markers. Molecular maps were produced for each parent using the pseudo-testcross mapping strategy. The first maternal map (6142-1, 81 individuals) consisted of 231 markers divided as followed: 121 DArT, 106 SSR and 4 AS-PCR markers in 15 linkage groups (LGs) covering 670 cM. The second maternal map (6142-1-S, 58 individuals) contained a total of 152 markers including 71 DArTs, 79 SSRs, and 2 AS-PCRs mapped to 16 LGs that spanned 698 cM. The combined paternal map (139 individuals) comprised 316 markers (196 DArTs, 117 SSRs and 3 AS-PCRs) distributed over 15 LGs with a total map length of 1,004 cM. While distorted segregation of some markers was observed in all maps, this was much more frequent for the male parent. Homology between maps was assessed using common markers. While there was generally good congruity with regard to marker order across maps, incongruity in other cases may reflect chromosomal rearrangement events such as inversions, translocations, or deletions. The new banana map can provide a better understanding of the Musa genome and could be used for the identification of economically important traits and improvement of breeding strategies

The Plant Journal

Summary Brown rice possesses various nutritionally dense bioactive phytochemicals exhibiting wide range of antioxidant, anticancer and antidiabetic properties known to promote various human health benefits. However, despite the wide claims made about the importance of brown rice for human nutrition the underlying metabolic diversity not systematically explored. Non-targeted metabolite profiling of developing and mature seeds of a diverse genetic panel of 320 rice cultivars allowed quantification of 117 metabolites. The metabolite genome-wide association study (mGWAS) detected genetic variants influencing diverse metabolic targets in developing and mature seeds. We further interlinked genetic variants on chromosome 7 (6.06-6.43 Mb region) with complex epistatic genetic interactions impacting multi-dimensional nutritional targets, including complex carbohydrate starch quality, glycemic index, antioxidant catechin and rice grain colour. Through this nutrigenomics approach rare gene bank accessions possessing genetic variants in bHLH and IPT5 genes were identified through haplotype enrichment. These variants were associated with low glycemic index, higher catechin, elevated total flavonoid contents and heightened antioxidant activity in the whole grain with elevated anti-cancer properties being confirmed on cancer cell lines. This multi-disciplinary nutrigenomics approach thus allowed us to discover the genetic basis of human-health conferring diversity in the metabolome of brown rice