Genome-Wide Association Studies of 11 Agronomic Traits in Cassava (Manihot esculenta Crantz)

Modern Breeding Strategies and Tools for Durable Late Blight Resistance in Potato

Cultivated potato (Solanum tuberosum) is a major crop worldwide. It occupies the second place after cereals (corn, rice, and wheat). This important crop is threatened by the Oomycete Phytophthora infestans, the agent of late blight disease. This pathogen was first encountered during the Irish famine during the 1840s and is a reemerging threat to potatoes. It is mainly controlled chemically by using fungicides, but due to health and environmental concerns, the best alternative is resistance. When there is no disease, no treatment is required. In this study, we present a summary of the ongoing efforts concerning resistance breeding of potato against this devastating pathogen, P. infestans. This work begins with the search for and selection of resistance genes, whether they are from within or from outside the species. The genetic methods developed to date for gene mining, such as effectoromics and GWAS, provide researchers with the ability to identify genes of interest more efficiently. Once identified, these genes are cloned using molecular markers (MAS or QRL) and can then be introduced into different cultivars using somatic hybridization or recombinant DNA technology. More innovative technologies have been developed lately, such as gene editing using the CRISPR system or gene silencing, by exploiting iRNA strategies that have emerged as promising tools for managing Phytophthora infestans, which can be employed. Also, gene pyramiding or gene stacking, which involves the accumulation of two or more R genes on the same individual plant, is an innovative method that has yielded many promising results. All these advances related to the development of molecular techniques for obtaining new potato cultivars resistant to P. infestans can contribute not only to reducing losses in agriculture but especially to ensuring food security and safety.

Overexpression of cassava melatonin receptor PMTR1 plays dual roles in development under light and dark conditions in Arabidopsis

KEY MESSAGE

MePMTR1 is involved in plant development and production as well as photosynthesis in plant. Melatonin is widely involved in plant growth and development as well as stress responses. Compared with the extending studies of melatonin in stress responses, the direct link between melatonin and plant development in the whole stages remains unclear. With the identification of phytomelatonin receptor PMTR1 in plants, melatonin signalling is becoming much clearer. However, the function of MePMTR1 in tropical crop cassava remains elusive. In this study, we found that overexpression of MePMTR1 showed larger biomass than wild type (WT), including higher number and area of leaves, weight, and accompanying with higher photosynthetic efficiency. Consistently, exogenous melatonin accelerated photosynthetic rate in Arabidopsis. In addition, MePMTR1-overexpressed plants exhibited more resistance to dark-induced senescence compared with WT, demonstrated by higher chlorophyll, lower hydrogen peroxide and superoxide content. In summary, this study illustrated that melatonin and its receptor regulate growth, development and senescence in plants, highlighting the potential application of melatonin and its receptor in improving crop yield and photosynthesis.

Identification of Genomic Regions for Traits Associated with Flowering in Cassava (Manihot esculenta Crantz)

Flowering in cassava (Manihot esculenta Crantz) is crucial for the generation of botanical seed for breeding. However, genotypes preferred by most farmers are erect and poor at flowering or never flower. To elucidate the genetic basis of flowering, 293 diverse cassava accessions were evaluated for flowering-associated traits at two locations and seasons in Uganda. Genotyping using the Diversity Array Technology Pty Ltd. (DArTseq) platform identified 24,040 single-nucleotide polymorphisms (SNPs) distributed on the 18 cassava chromosomes. Population structure analysis using principal components (PCs) and kinships showed three clusters; the first five PCs accounted for 49.2% of the observed genetic variation. Linkage disequilibrium (LD) estimation averaged 0.32 at a distance of ~2850 kb (kilo base pairs). Polymorphism information content (PIC) and minor allele frequency (MAF) were 0.25 and 0.23, respectively. A genome-wide association study (GWAS) analysis uncovered 53 significant marker-trait associations (MTAs) with flowering-associated traits involving 27 loci. Two loci, SNPs S5_29309724 and S15_11747301, were associated with all the traits. Using five of the 27 SNPs with a Phenotype_Variance_Explained (PVE) ≥ 5%, 44 candidate genes were identified in the peak SNP sites located within 50 kb upstream or downstream, with most associated with branching traits. Eight of the genes, orthologous to Arabidopsis and other plant species, had known functional annotations related to flowering, e.g., eukaryotic translation initiation factor and myb family transcription factor. This study identified genomic regions associated with flowering-associated traits in cassava, and the identified SNPs can be useful in marker-assisted selection to overcome hybridization challenges, like unsynchronized flowering, and candidate gene validation.

Climate change challenges, plant science solutions

Climate change is a defining challenge of the 21st century, and this decade is a critical time for action to mitigate the worst effects on human populations and ecosystems. Plant science can play an important role in developing crops with enhanced resilience to harsh conditions (e.g. heat, drought, salt stress, flooding, disease outbreaks) and engineering efficient carbon-capturing and carbon-sequestering plants. Here, we present examples of research being conducted in these areas and discuss challenges and open questions as a call to action for the plant science community.

Genome-wide association studies reveal genetic basis of ionomic variation in cassava

As one of the most important food crops, cassava (Manihot esculenta) is the main dietary source of micronutrients for about 1 billion people. However, the ionomic variation in cassava and the underlying genetic mechanisms remain unclear so far. Herein, genome-wide association studies were performed to reveal the specific single nucleotide polymorphisms (SNPs) that affect the ionomic variation in cassava. We identified 164 SNPs with P-values lower than the threshold located in 88 loci associated with divergent ionomic variations. Among them, 13 SNPs are related to both calcium (Ca) and magnesium (Mg), and many loci for different ionomic traits seem to be clustered on specific chromosome regions. Moreover, we identified the peak SNPs in the promoter regions of Sc10g003170 (encoding methionyl-tRNA synthetase [MetRS]) and Sc18g015190 (encoding the transcriptional regulatory protein AlgP) for nitrogen (N) and phosphorus (P) accumulation, respectively. Notably, these two SNPs (chr10_32807962 and chr18_31343738) were directly correlated with the transcript levels of Sc10g003170 (MetRS) and Sc18g015190 (AlgP), which positively modulated N accumulation and P concentration in cassava, respectively. Taken together, this study provides important insight into the genetic basis of cassava natural ionomic variation, which will promote genetic breeding to improve nutrient use and accumulation of elements in cassava.

PP2C1 fine-tunes melatonin biosynthesis and phytomelatonin receptor PMTR1 binding to melatonin in cassava

Melatonin is an important molecule in both animals and plants, regulating circadian rhythms and stress responses. Therefore, the improvement of melatonin accumulation not only strengthens the function of melatonin but also improves stress resistance in crops. Although melatonin biosynthetic enzymes have been identified through reverse genetics previously, an investigation of melatonin level-related genes through forward genetics in plants has yet to be performed. In this study, a genome-wide association study using cassava natural population of 298 genetic resources identified melatonin accumulation 1 (MA1), which regulates the natural variation of melatonin levels in cassava. We found that MA1 encodes type 2C protein phosphatase 1 (PP2C1), which serves as a negative regulator of melatonin levels in cassava. MePP2C1 physically interacts with MeRAV1/2 and MeWRKY20 and dephosphorylates them at serine (S) 35 residue, S34 residue, and S176 residue, respectively, thereby hindering their transcriptional activation on downstream melatonin biosynthetic genes. Notably, MePP2C1 interacts with phytomelatonin receptor MePMTR1 and dephosphorylates it at S11 residue, repressing its binding to melatonin. In summary, this study demonstrates that MePP2C1 as MA1 plays dual roles in negatively regulating both melatonin accumulation and signaling, extending the understanding of the molecular mechanism underlying melatonin accumulation and signaling through forward genetics in plants.

High-quality reference genome sequences of two Cannaceae species provide insights into the evolution of Cannaceae

Canna edulis Ker-Gawl and Canna indica L. are species belonging to the Cannaceae family and both have a very high economic value. Here, we aimed to assemble genomes of C. edulis and C. indica at the chromosome level to generate a reference genome for the Cannaceae family. We also comparatively analyzed the genomes of C. edulis and C. indica and examined the molecular mechanisms responsible for the remarkable differences in plant characteristics in C. edulis varieties. Our results indicated that genome-wide duplication events had recently occurred in C. edulis and C. indica. The comparative analysis of the genomes of C. edulis and C. indica revealed that C. edulis exhibited a remarkable level of replication of genes in the starch and sucrose metabolic pathways, especially during sucrose hydrolysis. This finding is consistent with the fact that the starch content of the C. edulis tuber is higher than that of C. indica. Simplified genome re-sequencing revealed the population structure of 241 C. edulis genes, and a genome-wide association study of leaf traits revealed the location of key genes related to leaf color and morphology. These findings extend our understanding of Cannaceade at the molecular level, and provide an effective theoretical basis for further study and utilization of Cannaceae plants.

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.

Cassava root crown phenotyping using three-dimension (3D) multi-view stereo reconstruction

Phenotypic analysis of cassava root crowns (CRCs) so far has been limited to visual inspection and very few measurements due to its laborious process in the field. Here, we developed a platform for acquiring 3D CRC models using close-range photogrammetry for phenotypic analysis. The state of the art is a low cost and easy to set up 3D acquisition requiring only a background sheet, a reference object and a camera, compatible with field experiments in remote areas. We tested different software with CRC samples, and Agisoft and Blender were the most suitable software for generating high-quality 3D models and data analysis, respectively. We optimized the workflow by testing different numbers of images for 3D reconstruction and found that a minimum of 25 images per CRC can provide high quality 3D models. Up to ten traits, including 3D crown volumes, 3D crown surface, root density, surface-to-volume ratio, root numbers, root angle, crown diameter, cylinder soil volume, CRC compactness and root length can be extracted providing novel parameters for studying cassava storage roots. We applied this platform to partial-inbred cassava populations and demonstrated that our platform provides reliable 3D CRC modelling for phenotypic analysis, analysis of genetic variances and supporting breeding selection.

Beyond a reference genome: pangenomes and population genomics of underutilized and orphan crops for future food and nutrition security

Underutilized crops are, by definition, under-researched compared to staple crops yet come with traits that may be especially important given climate change and the need to feed a globally increasing population. These crops are often stress-tolerant, and this combined with unique and beneficial nutritional profiles. Whilst progress is being made by generating reference genome sequences, in this Tansley Review, we show how this is only the very first step. We advocate that going 'beyond a reference genome' should be a priority, as it is only at this stage one can identify the specific genes and the adaptive alleles that underpin the valuable traits. We sum up how population genomic and pangenomic approaches have led to the identification of stress- and disease-tolerant alleles in staple crops and compare this to the small number of examples from underutilized crops. We also demonstrate how previously underutilized crops have benefitted from genomic advances and that many breeding targets in underutilized crops are often well studied in staple crops. This cross-crop population-level resequencing could lead to an understanding of the genetic basis of adaptive traits in underutilized crops. This level of investment may be crucial for fully understanding the value of these crops before they are lost.

Genome-wide association analysis reveals new insights into the genetic architecture of defensive, agro-morphological and quality-related traits in cassava

More than 40 QTLs associated with 14 stress-related, quality and agro-morphological traits were identified. A catalogue of favourable SNP markers for MAS and a list of candidate genes are provided. Cassava (Manihot esculenta) is one of the most important starchy root crops in the tropics due to its adaptation to marginal environments. Genetic progress in this clonally propagated crop can be accelerated through the discovery of markers and candidate genes that could be used in cassava breeding programs. We carried out a genome-wide association study (GWAS) using a panel of 5130 clones developed at the International Institute of Tropical Agriculture-Nigeria. The population was genotyped at more than 100,000 SNP markers via genotyping-by-sequencing (GBS). Genomic regions underlying genetic variation for 14 traits classified broadly into four categories: biotic stress (cassava mosaic disease and cassava green mite severity); quality (dry matter content and carotenoid content) and plant agronomy (harvest index and plant type) were investigated. We also included several agro-morphological traits related to leaves, stems and roots with high heritability. In total, 41 significant associations were uncovered. While some of the identified loci matched with those previously reported, we present additional association signals for the traits. We provide a catalogue of favourable alleles at the most significant SNP for each trait-locus combination and candidate genes occurring within the GWAS hits. These resources provide a foundation for the development of markers that could be used in cassava breeding programs and candidate genes for functional validation.

The future of cassava in the era of biotechnology in Southern Africa

Cassava (Manihot esculenta) is a major staple food and the world's fourth source of calories. Biotechnological contributions to enhancing this crop, its advances, and present issues must be assessed regularly. Functional genomics, genomic-assisted breeding, molecular tools, and genome editing technologies, among other biotechnological approaches, have helped improve the potential of economically important crops like cassava by addressing some of its significant constraints, such as nutrient deficiency, toxicity, poor starch quality, disease susceptibility, low yield capacity, and postharvest deterioration. However, the development, improvement, and subsequent acceptance of the improved cultivars have been challenging and have required holistic approaches to solving them. This article provides an update of trends and gaps in cassava biotechnology, reviewing the relevant strategies used to improve cassava crops and highlighting the potential risk and acceptability of improved cultivars in Southern Africa.

Feature Compression Applications of Genetic Algorithm

With the rapid development of molecular breeding technology and many new varieties breeding, a method is urgently needed to identify different varieties accurately and quickly. Using this method can not only help farmers feel convenient and efficient in the normal cultivation and breeding process but also protect the interests of breeders, producers and users. In this study, single nucleotide polymorphism (SNP) data of 533 Oryza sativa, 284 Solanum tuberosum and 247 Sus scrofa and 544 Manihot esculenta Crantz were used. The original SNPs were filtered and screened to remove the SNPs with deletion number more than 1% or the homozygous genotype 0/0 and 1/1 number less than 2. The correlation between SNPs were calculated, and the two adjacent SNPs with correlation R² > 0.95 were retained. The genetic algorithm program was developed to convert the genotype format and randomly combine SNPs to calculate a set of a small number of SNPs which could distinguish all varieties in different species as fingerprint data, using Matlab platform. The successful construction of three sets of fingerprints showed that the method developed in this study was effective in animals and plants. The population structure analysis showed that the genetic algorithm could effectively obtain the core SNPs for constructing fingerprints, and the fingerprint was practical and effective. At present, the two-dimensional code of Manihot esculenta Crantz fingerprint obtained by this method has been applied to field planting. This study provides a novel idea for the Oryza sativa, Solanum tuberosum, Sus scrofa and Manihot esculenta Crantz identification of various species, lays foundation for the cultivation and identification of new varieties, and provides theoretical significance for many other species fingerprints construction.

Genetic Diversity and Association Analysis for Carotenoid Content among Sprouts of Cowpea (Vigna unguiculata L. Walp)

The development and promotion of biofortified foods plants are a sustainable strategy for supplying essential micronutrients for human health and nutrition. We set out to identify quantitative trait loci (QTL) associated with carotenoid content in cowpea sprouts. The contents of carotenoids, including lutein, zeaxanthin, and β-carotene in sprouts of 125 accessions were quantified via high-performance liquid chromatography. Significant variation existed in the profiles of the different carotenoids. Lutein was the most abundant (58 ± 12.8 mg/100 g), followed by zeaxanthin (14.7 ± 3.1 mg/100 g) and β-carotene (13.2 ± 2.9 mg/100 g). A strong positive correlation was observed among the carotenoid compounds (r ≥ 0.87), indicating they can be improved concurrently. The accessions were distributed into three groups, following their carotenoid profiles, with accession C044 having the highest sprout carotenoid content in a single cluster. A total of 3120 genome-wide SNPs were tested for association analysis, which revealed that carotenoid biosynthesis in cowpea sprouts is a polygenic trait controlled by genes with additive and dominance effects. Seven loci were significantly associated with the variation in carotenoid content. The evidence of variation in carotenoid content and genomic regions controlling the trait creates an avenue for breeding cowpea varieties with enhanced sprouts carotenoid content.

Orphan Crops: A Best Fit for Dietary Enrichment and Diversification in Highly Deteriorated Marginal Environments

Orphan crops are indigenous and invariably grown by small and marginal farmers under subsistence farming systems. These crops, which are common and widely accepted by local farmers, are highly rich in nutritional profile, good for medicinal purposes, and well adapted to suboptimal growing conditions. However, these crops have suffered neglect and abandonment from the scientific community because of very low or no investments in research and genetic improvement. A plausible reason for this is that these crops are not traded internationally at a rate comparable to that of the major food crops such as wheat, rice, and maize. Furthermore, marginal environments have poor soils and are characterized by extreme weather conditions such as heat, erratic rainfall, water deficit, and soil and water salinity, among others. With more frequent extreme climatic events and continued land degradation, orphan crops are beginning to receive renewed attention as alternative crops for dietary diversification in marginal environments and, by extension, across the globe. Increased awareness of good health is also a major contributor to the revived attention accorded to orphan crops. Thus, the introduction, evaluation, and adaptation of outstanding varieties of orphan crops for dietary diversification will contribute not only to sustained food production but also to improved nutrition in marginal environments. In this review article, the concept of orphan crops vis-à-vis marginality and food and nutritional security is defined for a few orphan crops. We also examined recent advances in research involving orphan crops and the potential of these crops for dietary diversification within the context of harsh marginal environments. Recent advances in genomics coupled with molecular breeding will play a pivotal role in improving the genetic potential of orphan crops and help in developing sustainable food systems. We concluded by presenting a potential roadmap to future research engagement and a policy framework with recommendations aimed at facilitating and enhancing the adoption and sustainable production of orphan crops under agriculturally marginal conditions.

Genome-wide association study of cassava starch paste properties

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

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.

Identification of quantitative trait nucleotides and candidate genes for tuber yield and mosaic virus tolerance in an elite population of white guinea yam (Dioscorea rotundata) using genome-wide association scan

BACKGROUND

Improvement of tuber yield and tolerance to viruses are priority objectives in white Guinea yam breeding programs. However, phenotypic selection for these traits is quite challenging due to phenotypic plasticity and cumbersome screening of phenotypic-induced variations. This study assessed quantitative trait nucleotides (QTNs) and the underlying candidate genes related to tuber yield per plant (TYP) and yam mosaic virus (YMV) tolerance in a panel of 406 white Guinea yam (Dioscorea rotundata) breeding lines using a genome-wide association study (GWAS).

RESULTS

Population structure analysis using 5,581 SNPs differentiated the 406 genotypes into seven distinct sub-groups based delta K. Marker-trait association (MTA) analysis using the multi-locus linear model (mrMLM) identified seventeen QTN regions significant for TYP and five for YMV with various effects. The seveteen QTNs were detected on nine chromosomes, while the five QTNs were identified on five chromosomes. We identified variants responsible for predicting higher yield and low virus severity scores in the breeding panel through the marker-effect prediction. Gene annotation for the significant SNP loci identified several essential putative genes associated with the growth and development of tuber yield and those that code for tolerance to mosaic virus.

CONCLUSION

Application of different multi-locus models of GWAS identified 22 QTNs. Our results provide valuable insight for marker validation and deployment for tuber yield and mosaic virus tolerance in white yam breeding. The information on SNP variants and genes from the present study would fast-track the application of genomics-informed selection decisions in breeding white Guinea yam for rapid introgression of the targeted traits through markers validation.

Genome-Wide Association Mapping of Late Blight Tolerance Trait in Potato (Solanum tuberosum L.)

Uncovering the genetic basis and optimizing the late blight tolerance trait in potatoes (Solanum tuberosum L.) are crucial for potato breeding. Late blight disease is one of the most significant diseases hindering potato production. The traits of late blight tolerance were evaluated for 284 potato cultivars to identify loci significantly associated with the late blight tolerance trait. Of all, 37 and 15 were the most tolerant to disease, and 107 and 30 were the most susceptible. A total of 22,489 high-quality single-nucleotide polymorphisms and indels were identified in 284 potato cultivars. All the potato cultivars were clustered into eight subgroups using population structure analysis and principal component analysis, which were consistent with the results of the phylogenetic tree analysis. The average genetic diversity for all 284 potato cultivars was 0.216, and the differentiation index of each subgroup was 0.025–0.149. Genome-wide linkage disequilibrium (LD) analysis demonstrated that the average LD was about 0.9 kb. A genome-wide association study using a mixed linear model identified 964 loci significantly associated with the late blight tolerance trait. Fourteen candidate genes for late blight tolerance traits were identified, including genes encoding late blight tolerance protein, chitinase 1, cytosolic nucleotide-binding site–leucine-rich repeat tolerance protein, protein kinase, ethylene-responsive transcription factor, and other potential plant tolerance-related proteins. This study provides novel insights into the genetic architecture of late blight tolerance traits and will be helpful for late blight tolerance in potato breeding.

Genome-wide association screening and verification of potential genes associated with root architectural traits in maize (Zea mays L.) at multiple seedling stages

Background

Breeding for new maize varieties with propitious root systems has tremendous potential in improving water and nutrients use efficiency and plant adaptation under suboptimal conditions. To date, most of the previously detected root-related trait genes in maize were new without functional verification. In this study, seven seedling root architectural traits were examined at three developmental stages in a recombinant inbred line population (RIL) of 179 RILs and a genome-wide association study (GWAS) panel of 80 elite inbred maize lines through quantitative trait loci (QTL) mapping and genome-wide association study.

Results

Using inclusive composite interval mapping, 8 QTLs accounting for 6.44–8.83 % of the phenotypic variation in root traits, were detected on chromosomes 1 (qRDW_v3-1-1 and qRDW/SDW_v3-1-1), 2 (qRBN_v1-2-1), 4 (qSUA_v1-4-1, qSUA_v2-4-1, and qROV_v2-4-1), and 10 (qTRL_v1-10-1, qRBN_v1-10-1). GWAS analysis involved three models (EMMAX, FarmCPU, and MLM) for a set of 1,490,007 high-quality single nucleotide polymorphisms (SNPs) obtained via whole genome next-generation sequencing (NGS). Overall, 53 significant SNPs with a phenotypic contribution rate ranging from 5.10 to 30.2 % and spread all over the ten maize chromosomes exhibited associations with the seven root traits. 17 SNPs were repeatedly detected from at least two growth stages, with several SNPs associated with multiple traits stably identified at all evaluated stages. Within the average linkage disequilibrium (LD) distance of 5.2 kb for the significant SNPs, 46 candidate genes harboring substantial SNPs were identified. Five potential genes viz. Zm00001d038676, Zm00001d015379, Zm00001d018496, Zm00001d050783, and Zm00001d017751 were verified for expression levels using maize accessions with extreme root branching differences from the GWAS panel and the RIL population. The results showed significantly (P < 0.001) different expression levels between the outer materials in both panels and at all considered growth stages.

Conclusions

This study provides a key reference for uncovering the complex genetic mechanism of root development and genetic enhancement of maize root system architecture, thus supporting the breeding of high-yielding maize varieties with propitious root systems.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07874-x.

MultiGWAS: An integrative tool for Genome Wide Association Studies in tetraploid organisms

The genome-wide association studies (GWASs) are essential to determine the genetic bases of either ecological or economic phenotypic variation across individuals within populations of the model and nonmodel organisms. For this research question, the GWAS replication testing different parameters and models to validate the results' reproducibility is common. However, straightforward methodologies that manage both replication and tetraploid data are still missing. To solve this problem, we designed the MultiGWAS, a tool that does GWAS for diploid and tetraploid organisms by executing in parallel four software packages, two designed for polyploid data (GWASpoly and SHEsis) and two designed for diploid data (GAPIT and TASSEL). MultiGWAS has several advantages. It runs either in the command line or in a graphical interface; it manages different genotype formats, including VCF. Moreover, it allows control for population structure, relatedness, and several quality control checks on genotype data. Besides, MultiGWAS can test for additive and dominant gene action models, and, through a proprietary scoring function, select the best model to report its associations. Finally, it generates several reports that facilitate identifying false associations from both the significant and the best-ranked association Single Nucleotide Polymorphisms (SNPs) among the four software packages. We tested MultiGWAS with public tetraploid potato data for tuber shape and several simulated data under both additive and dominant models. These tests demonstrated that MultiGWAS is better at detecting reliable associations than using each of the four software packages individually. Moreover, the parallel analysis of polyploid and diploid software that only offers MultiGWAS demonstrates its utility in understanding the best genetic model behind the SNP association in tetraploid organisms. Therefore, MultiGWAS probed to be an excellent alternative for wrapping GWAS replication in diploid and tetraploid organisms in a single analysis environment.

Recent Large-Scale Genotyping and Phenotyping of Plant Genetic Resources of Vegetatively Propagated Crops

Several recent national and international projects have focused on large-scale genotyping of plant genetic resources in vegetatively propagated crops like fruit and berries, potatoes and woody ornamentals. The primary goal is usually to identify true-to-type plant material, detect possible synonyms, and investigate genetic diversity and relatedness among accessions. A secondary goal may be to create sustainable databases that can be utilized in research and breeding for several years ahead. Commonly applied DNA markers (like microsatellite DNA and SNPs) and next-generation sequencing each have their pros and cons for these purposes. Methods for large-scale phenotyping have lagged behind, which is unfortunate since many commercially important traits (yield, growth habit, storability, and disease resistance) are difficult to score. Nevertheless, the analysis of gene action and development of robust DNA markers depends on environmentally controlled screening of very large sets of plant material. Although more time-consuming, co-operative projects with broad-scale data collection are likely to produce more reliable results. In this review, we will describe some of the approaches taken in genotyping and/or phenotyping projects concerning a wide variety of vegetatively propagated crops.

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.

Orphan Crops and their Wild Relatives in the Genomic Era

More than half of the calories consumed by humans are provided by three major cereal crops (rice, maize, and wheat). Orphan crops are usually well adapted to low-input agricultural conditions, and they not only play vital roles in local areas but can also contribute to food and nutritional needs worldwide. Interestingly, many wild relatives of orphan crops are important weeds of major crops. Although orphan crops and their wild relatives have received little attentions from researchers for many years, genomic studies have recently been performed on these plants. Here, we provide an overview of genomic studies on orphan crops, with a focus on orphan cereals and their wild relatives. The genomes of at least 12 orphan cereals and/or their wild relatives have been sequenced. In addition to genomic benefits for orphan crop breeding, we discuss the potential ways for mutual utilization of genomic data from major crops, orphan crops, and their wild relatives (including weeds) and provide perspectives on genetic improvement of both orphan and major crops (including de novo domestication of orphan crops) in the coming genomic era.

Xylem systems genetics analysis reveals a key regulator of lignin biosynthesis in Populus deltoides

Despite the growing resources and tools for high-throughput characterization and analysis of genomic information, the discovery of the genetic elements that regulate complex traits remains a challenge. Systems genetics is an emerging field that aims to understand the flow of biological information that underlies complex traits from genotype to phenotype. In this study, we used a systems genetics approach to identify and evaluate regulators of the lignin biosynthesis pathway in Populus deltoides by combining genome, transcriptome, and phenotype data from a population of 268 unrelated individuals of P. deltoides The discovery of lignin regulators began with the quantitative genetic analysis of the xylem transcriptome and resulted in the detection of 6706 and 4628 significant local- and distant-eQTL associations, respectively. Among the locally regulated genes, we identified the R2R3-MYB transcription factor MYB125 (Potri.003G114100) as a putative trans-regulator of the majority of genes in the lignin biosynthesis pathway. The expression of MYB125 in a diverse population positively correlated with lignin content. Furthermore, overexpression of MYB125 in transgenic poplar resulted in increased lignin content, as well as altered expression of genes in the lignin biosynthesis pathway. Altogether, our findings indicate that MYB125 is involved in the control of a transcriptional coexpression network of lignin biosynthesis genes during secondary cell wall formation in P. deltoides.

Genome-Wide Association Analysis for Tuber Dry Matter and Oxidative Browning in Water Yam (Dioscorea alata L.)

Yam (Dioscorea spp.) is a nutritional and medicinal staple tuber crop grown in the tropics and sub-tropics. Among the food yam species, water yam (Dioscorea alata L.) is the most widely distributed and cultivated species worldwide. Tuber dry matter content (DMC) and oxidative browning (OxB) are important quality attributes that determine cultivar acceptability in water yam. This study used a single nucleotide polymorphism (SNP) assay from a diversity arrays technology (DArT) platform for a genome-wide association study (GWAS) of the two quality traits in a panel of 100 water yam clones grown in three environments. The marker-trait association analysis identified significant SNPs associated with tuber DMC on chromosomes 6 and 19 and with OxB on chromosome 5. The significant SNPs cumulatively explained 45.87 and 12.74% of the total phenotypic variation for the tuber DMC and OxB, respectively. Gene annotation for the significant SNP loci identified important genes associated in the process of the proteolytic modification of carbohydrates in the dry matter accumulation pathway as well as fatty acid β-oxidation in peroxisome for enzymatic oxidation. Additional putative genes were also identified in the peak SNP sites for both tuber dry matter and enzymatic oxidation with unknown functions. The results of this study provide valuable insight for further dissection of the genetic architecture of tuber dry matter and enzymatic oxidation in water yam. They also highlight SNP variants and genes useful for genomics-informed selection decisions in the breeding process for improving food quality traits in water yam.

PANOMICS meets germplasm

Genotyping-by-sequencing has enabled approaches for genomic selection to improve yield, stress resistance and nutritional value. More and more resource studies are emerging providing 1000 and more genotypes and millions of SNPs for one species covering a hitherto inaccessible intraspecific genetic variation. The larger the databases are growing, the better statistical approaches for genomic selection will be available. However, there are clear limitations on the statistical but also on the biological part. Intraspecific genetic variation is able to explain a high proportion of the phenotypes, but a large part of phenotypic plasticity also stems from environmentally driven transcriptional, post-transcriptional, translational, post-translational, epigenetic and metabolic regulation. Moreover, regulation of the same gene can have different phenotypic outputs in different environments. Consequently, to explain and understand environment-dependent phenotypic plasticity based on the available genotype variation we have to integrate the analysis of further molecular levels reflecting the complete information flow from the gene to metabolism to phenotype. Interestingly, metabolomics platforms are already more cost-effective than NGS platforms and are decisive for the prediction of nutritional value or stress resistance. Here, we propose three fundamental pillars for future breeding strategies in the framework of Green Systems Biology: (i) combining genome selection with environment-dependent PANOMICS analysis and deep learning to improve prediction accuracy for marker-dependent trait performance; (ii) PANOMICS resolution at subtissue, cellular and subcellular level provides information about fundamental functions of selected markers; (iii) combining PANOMICS with genome editing and speed breeding tools to accelerate and enhance large-scale functional validation of trait-specific precision breeding.

PANOMICS meets germplasm

Genotyping-by-sequencing has enabled approaches for genomic selection to improve yield, stress resistance and nutritional value. More and more resource studies are emerging providing 1000 and more genotypes and millions of SNPs for one species covering a hitherto inaccessible intraspecific genetic variation. The larger the databases are growing, the better statistical approaches for genomic selection will be available. However, there are clear limitations on the statistical but also on the biological part. Intraspecific genetic variation is able to explain a high proportion of the phenotypes, but a large part of phenotypic plasticity also stems from environmentally driven transcriptional, post-transcriptional, translational, post-translational, epigenetic and metabolic regulation. Moreover, regulation of the same gene can have different phenotypic outputs in different environments. Consequently, to explain and understand environment-dependent phenotypic plasticity based on the available genotype variation we have to integrate the analysis of further molecular levels reflecting the complete information flow from the gene to metabolism to phenotype. Interestingly, metabolomics platforms are already more cost-effective than NGS platforms and are decisive for the prediction of nutritional value or stress resistance. Here, we propose three fundamental pillars for future breeding strategies in the framework of Green Systems Biology: (i) combining genome selection with environment-dependent PANOMICS analysis and deep learning to improve prediction accuracy for marker-dependent trait performance; (ii) PANOMICS resolution at subtissue, cellular and subcellular level provides information about fundamental functions of selected markers; (iii) combining PANOMICS with genome editing and speed breeding tools to accelerate and enhance large-scale functional validation of trait-specific precision breeding.

Recommendations for Choosing the Genotyping Method and Best Practices for Quality Control in Crop Genome-Wide Association Studies

High-throughput genotyping boosts genome-wide association studies (GWAS) in crop species, leading to the identification of single-nucleotide polymorphisms (SNPs) associated with economically important traits. Choosing a cost-effective genotyping method for crop GWAS requires careful examination of several aspects, namely, the purpose and the scale of the study, crop-specific genomic features, and technical and economic matters associated with each genotyping option. Once genotypic data have been obtained, quality control (QC) procedures must be applied to avoid bias and false signals in genotype–phenotype association tests. QC for human GWAS has been extensively reviewed; however, QC for crop GWAS may require different actions, depending on the GWAS population type. Here, we review most popular genotyping methods based on next-generation sequencing (NGS) and array hybridization, and report observations that should guide the investigator in the choice of the genotyping method for crop GWAS. We provide recommendations to perform QC in crop species, and deliver an overview of bioinformatics tools that can be used to accomplish all needed tasks. Overall, this work aims to provide guidelines to harmonize those procedures leading to SNP datasets ready for crop GWAS.

Modernising breeding for orphan crops: tools, methodologies, and beyond

In spite of the limited investment in orphan crops, access to new technologies such as bioinformatics and low-cost genotyping opens new doors to modernise their breeding effectively. Innovation in plant breeding is imperative to meet the world's growing demand for staple food and feed crops, and orphan crops can play a significant role in increasing productivity and quality, especially in developing countries. The short breeding history of most orphan crops implies that genetic gain should be achievable through easy-to-implement approaches such as forward breeding for simple traits or introgression of elite alleles at key target trait loci. However, limited financial support and access to sufficient, relevant and reliable phenotypic data continue to pose major challenges in terms of resources and capabilities. Digitalisation of orphan-crop breeding programmes can help not only to improve data quality and management, but also to mitigate data scarcity by allowing data to be accumulated and analysed over time and across teams. Bioinformatics tools and access to technologies such as molecular markers, some of them provided as services via specific platforms, allow breeders to implement modern strategies to improve breeding efficiency. In orphan crops, more marker-trait associations relevant to breeding germplasm are generally needed, but implementing digitalization, marker-based quality control or simple trait screening and introgression will help modernising breeding. Finally, the development of local capacities-of both people and infrastructure-remains a necessity to ensure the sustainable adoption of modern breeding approaches.

Orphan crops: their importance and the urgency of improvement

Due to significant contributions of orphan crops in the economy of the developing world, scientific studies need to be promoted on these little researched but vital crops of smallholder farmers and consumers. Food security is the main challenge in the developing world, particularly in the least developed countries. Orphan crops play a vital role in the food security and livelihood of resource-poor farmers and consumers in these countries. Like major crops, there are members of all food types-cereals, legumes, vegetables and root and tuber crops, that are considered to be orphan crops. Despite their huge importance for present and future agriculture, orphan crops have generally received little attention by the global scientific community. Due to this, they produce inferior yields in terms of both quantity and quality. The major bottlenecks affecting the productivity of these crops are little or no selection of improved genetic traits, extreme environmental conditions and unfavorable policy. However, some orphan crops have recently received the attention of the global and national scientific community where advanced research and development initiatives have been launched. These initiatives which implement a variety of genetic and genomic tools targeted major constraints affecting productivity and/or nutritional quality of orphan crops. In this paper, some of these initiatives are briefly described. Here, I provide key suggestions to relevant stakeholders regarding improvement of orphan crops. Concerted efforts are urgently needed to advance the research and development of both the major and orphan crops so that food security will be achieved and ultimately the livelihood of the population will be improved.

The Future of Digital Sequence Information for Plant Genetic Resources for Food and Agriculture

The recent debates on the legal status of "digital sequence information" (DSI) at the international level could have extensive consequences for the future of agriculture and food security. A large majority of recent advances in biology, medicine, or agriculture were achieved by sharing and mining of freely accessible sequencing data. It is most probably because of the tremendous success of modern genomics and advances of synthetic biology that concerns were raised about possible fair and equitable ways of sharing data. The DSI concept is relatively new, and all concerned parties agreed upon the need for a clear definition. For example, the extent to which DSI understanding is limited only to genetic sequence data has to be clarified. In this paper, I focus on a subset of DSI essential to humankind: the DSI originating from plant genetic resources for food and agriculture (PGRFA). Two international agreements shape the conservation and use of plant genetic resources: the Convention on Biodiversity and the International Treaty for Plant Genetic Resources for Food and Agriculture. In an attempt to mobilize DSI users and producers involved in research, breeding, and conservation, I describe here how the increasing amount of genomic data, information, and studies interact with the existing legal framework at the global level. Using possible scenarios, I will emphasize the complexity of the issues surrounding DSI for PGRFA and propose potential ways forward for developing an inclusive governance and fair use of these genetic resources.