Genomic Resources for Water Yam (Dioscorea alata L.): Analyses of EST-Sequences, De Novo Sequencing and GBS Libraries

Identification of diagnostic KASP-SNP markers for routine breeding activities in yam (Dioscorea spp.)

Maintaining genetic purity and true-to-type clone identification are important action steps in breeding programs. This study aimed to develop a universal set of kompetitive allele-specific polymerase chain reaction (KASP)-based single nucleotide polymorphism (SNP) markers for routine breeding activities. Ultra-low-density SNP markers were created using an initial set of 173,675 SNPs that were obtained from whole-genome resequencing of 333 diverse white Guinea yam (Dioscorea rotundata Poir) genotypes. From whole-genome resequencing data, 99 putative SNP markers were found and successfully converted to high-throughput KASP genotyping assays. The markers set was validated on 374 genotypes representing six yam species. Out of the 99 markers, 50 were highly polymorphic across the species and could distinguish different yam species and pedigree origins. The selected SNP markers classified the validation population based on the different yam species and identified potential duplicates within yam species. Through penalized analysis, the male parent of progenies involved in polycrosses was successfully predicted and validated. Our research was a trailblazer in validating KASP-based SNP assays for species identification, parental fingerprinting, and quality control (QC) and quality assurance (QA) in yam breeding programs.

Variability and genetic merits of white Guinea yam landraces in Nigeria

INTRODUCTION

Landraces represent a significant gene pool of African cultivated white Guinea yam diversity. They could, therefore, serve as a potential donor of important traits such as resilience to stresses as well as food quality attributes that may be useful in modern yam breeding. This study assessed the pattern of genetic variability, quantitative trait loci (QTLs), alleles, and genetic merits of landraces, which could be exploited in breeding for more sustainable yam production in Africa.

METHODS

A total of 86 white Guinea yam landraces representing the popular landraces in Nigeria alongside 16 elite clones were used for this study. The yam landraces were genotyped using 4,819 DArTseq SNP markers and profiled using key productivity and food quality traits.

RESULTS AND DISCUSSION

Genetic population structure through admixture and hierarchical clustering methods revealed the presence of three major genetic groups. Genome-wide association scan identified thirteen SNP markers associated with five key traits, suggesting that landraces constitute a source of valuable genes for productivity and food quality traits. Further dissection of their genetic merits in yam breeding using the Genomic Prediction of Cross Performance (GPCP) allowed identifying several landraces with high crossing merit for multiple traits. Thirteen landraces were identified as potential genitors to develop segregating progenies to improve multiple traits simultaneously for desired gains in yam breeding. Results of this study provide valuable insights into the patterns and the merits of local genetic diversity which can be utilized for identifying desirable genes and alleles of interest in yam breeding for Africa.

Chromosome evolution and the genetic basis of agronomically important traits in greater yam

The nutrient-rich tubers of the greater yam, Dioscorea alata L., provide food and income security for millions of people around the world. Despite its global importance, however, greater yam remains an orphan crop. Here, we address this resource gap by presenting a highly contiguous chromosome-scale genome assembly of D. alata combined with a dense genetic map derived from African breeding populations. The genome sequence reveals an ancient allotetraploidization in the Dioscorea lineage, followed by extensive genome-wide reorganization. Using the genomic tools, we find quantitative trait loci for resistance to anthracnose, a damaging fungal pathogen of yam, and several tuber quality traits. Genomic analysis of breeding lines reveals both extensive inbreeding as well as regions of extensive heterozygosity that may represent interspecific introgression during domestication. These tools and insights will enable yam breeders to unlock the potential of this staple crop and take full advantage of its adaptability to varied environments.

A Review of Viruses Infecting Yam (Dioscorea spp.)

Yam is an important food staple for millions of people globally, particularly those in the developing countries of West Africa and the Pacific Islands. To sustain the growing population, yam production must be increased amidst the many biotic and abiotic stresses. Plant viruses are among the most detrimental of plant pathogens and have caused great losses of crop yield and quality, including those of yam. Knowledge and understanding of virus biology and ecology are important for the development of diagnostic tools and disease management strategies to combat the spread of yam-infecting viruses. This review aims to highlight current knowledge on key yam-infecting viruses by examining their characteristics, genetic diversity, disease symptoms, diagnostics, and elimination to provide a synopsis for consideration in developing diagnostic strategy and disease management for yam.

Identification of QTLs Controlling Resistance to Anthracnose Disease in Water Yam (Dioscorea alata)

Anthracnose disease caused by a fungus Colletotrichum gloeosporioides is the primary cause of yield loss in water yam (Dioscorea alata), the widely cultivated species of yam. Resistance to yam anthracnose disease (YAD) is a prime target in breeding initiatives to develop durable-resistant cultivars for sustainable management of the disease in water yam cultivation. This study aimed at tagging quantitative trait loci (QTL) for anthracnose disease resistance in a bi-parental mapping population of D. alata. Parent genotypes and their recombinant progenies were genotyped using the Genotyping by Sequencing (GBS) platform and phenotyped in two crop cycles for two years. A high-density genetic linkage map was built with 3184 polymorphic Single Nucleotide Polymorphism (NSP) markers well distributed across the genome, covering 1460.94 cM total length. On average, 163 SNP markers were mapped per chromosome with 0.58 genetic distances between SNPs. Four QTL regions related to yam anthracnose disease resistance were identified on three chromosomes. The proportion of phenotypic variance explained by these QTLs ranged from 29.54 to 39.40%. The QTL regions identified showed genes that code for known plant defense responses such as GDSL-like Lipase/Acylhydrolase, Protein kinase domain, and F-box protein. The results from the present study provide valuable insight into the genetic architecture of anthracnose resistance in water yam. The candidate markers identified herewith form a relevant resource to apply marker-assisted selection as an alternative to a conventional labor-intensive screening for anthracnose resistance in water yam.

Strategies to combat the problem of yam anthracnose disease: Status and prospects

Yam (Dioscorea spp.) anthracnose, caused by Colletotrichum alatae, is the most devastating fungal disease of yam in West Africa, leading to 50%-90% of tuber yield losses in severe cases. In some instances, plants die without producing any tubers or each shoot may produce several small tubers before it dies if the disease strikes early. C. alatae affects all parts of the yam plant at all stages of development, including leaves, stems, tubers, and seeds of yams, and it is highly prevalent in the yam belt region and other yam-producing countries in the world. Traditional methods adopted by farmers to control the disease have not been very successful. Fungicides have also failed to provide long-lasting control. Although conventional breeding and genomics-assisted breeding have been used to develop some level of resistance to anthracnose in Dioscorea alata, the appearance of new and more virulent strains makes the development of improved varieties with broad-spectrum and durable resistance critical. These shortcomings, coupled with interspecific incompatibility, dioecy, polyploidy, poor flowering, and the long breeding cycle of the crop, have prompted researchers to explore biotechnological techniques to complement conventional breeding to speed up crop improvement. Modern biotechnological tools have the potential of producing fungus-resistant cultivars, thereby bypassing the natural bottlenecks of traditional breeding. This article reviews the existing biotechnological strategies and proposes several approaches that could be adopted to develop anthracnose-resistant yam varieties for improved food security in West Africa.

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.

A reference high-density genetic map of greater yam (Dioscorea alata L.)

This study generated the first high-density genetic map for D. alata based on genotyping-by-sequencing and provides new insight on sex determination in yam. Greater yam (Dioscorea alata L.) is a major staple food in tropical and subtropical areas. This study aimed to produce the first reference genetic map of this dioecious species using genotyping-by-sequencing. In this high-density map combining information of two F1 outcrossed populations, 20 linkage groups were resolved as expected and 1579 polymorphic markers were ordered. The consensus map length was 2613.5 cM with an average SNP interval of 1.68 cM. An XX/XY sex determination system was identified on LG6 via the study of sex ratio, homology of parental linkage groups and the identification of a major QTL for sex determination. Homology with the sequenced D. rotundata is described, and the median physical distance between SNPs was estimated at 139.1 kb. The effects of segregation distortion and the presence of heteromorphic sex chromosomes are discussed. This D. alata linkage map associated with the available genomic resources will facilitate quantitative trait mapping, marker-assisted selection and evolutionary studies in the important yet scarcely studied yam species.

Development of a cost-effective single nucleotide polymorphism genotyping array for management of greater yam germplasm collections

Using genome-wide single nucleotide polymorphism (SNP) discovery in greater yam (Discorea alata L.), 4,593 good quality SNPs were identified in 40 accessions. One hundred ninety six of these SNPs were selected to represent the overall dataset and used to design a competitive allele specific PCR array (KASPar). This array was validated on 141 accessions from the Tropical Plants Biological Resources Centre (CRB-PT) and CIRAD collections that encompass worldwide D. alata diversity. Overall, 129 SNPs were successfully converted as cost-effective genotyping tools. The results showed that the ploidy levels of accessions could be accurately estimated using this array. The rate of redundant accessions within the collections was high in agreement with the low genetic diversity of D. alata and its diversification by somatic clone selection. The overall diversity resulting from these 129 polymorphic SNPs was consistent with the findings of previously published studies. This KASPar array will be useful in collection management, ploidy level inference, while complementing accurate agro-morphological descriptions.

Genetic diversity and population structure of trifoliate yam (Dioscorea dumetorum Kunth) in Cameroon revealed by genotyping-by-sequencing (GBS)

BACKGROUND

Yams (Dioscorea spp.) are economically important food for millions of people in the humid and sub-humid tropics. Dioscorea dumetorum (Kunth) is the most nutritious among the eight-yam species, commonly grown and consumed in West and Central Africa. Despite these qualities, the storage ability of D. dumetorum is restricted by severe postharvest hardening of the tubers that can be addressed through concerted breeding efforts. The first step of any breeding program is bound to the study of genetic diversity. In this study, we used the Genotyping-By-Sequencing of Single Nucleotide Polymorphism (GBS-SNP) to investigate the genetic diversity and population structure of 44 accessions of D. dumetorum in Cameroon. Ploidy was inferred using flow cytometry and gbs2ploidy.

RESULTS

We obtained on average 6371 loci having at least information for 75% accessions. Based on 6457 unlinked SNPs, our results demonstrate that D. dumetorum is structured into four populations. We clearly identified, a western/north-western, a western, and south-western populations, suggesting that altitude and farmers-consumers preference are the decisive factors for differential adaptation and separation of these populations. Bayesian and neighbor-joining clustering detected the highest genetic variability in D. dumetorum accessions from the south-western region. This variation is likely due to larger breeding efforts in the region as shown by gene flow between D. dumetorum accessions from the south-western region inferred by maximum likelihood. Ploidy analysis revealed diploid and triploid levels in D. dumetorum accessions with mostly diploid accessions (77%). Male and female accessions were mostly triploid (75%) and diploid (69%), respectively. The 1C genome size values of D. dumetorum accessions were on average 0.333 ± 0.009 pg and 0.519 ± 0.004 pg for diploids and triploids, respectively.

CONCLUSIONS

Germplasm characterization, population structure and ploidy are an essential basic information in a breeding program as well as for conservation of intraspecific diversity. Thus, results obtained in this study provide valuable information for the improvement and conservation of D. dumetorum. Moreover, GBS appears as an efficient powerful tool to detect intraspecific variation.

An EST-SSR based genetic linkage map and identification of QTLs for anthracnose disease resistance in water yam (Dioscorea alata L.)

Water yam (Dioscorea alata L.) is one of the most important food yams with wide geographical distribution in the tropics. One of the major constraints to water yam production is anthracnose disease caused by a fungus, Colletotrichum gloeosporioides (Penz.). There are no economically feasible solutions as chemical sprays or cultural practices, such as crop rotation are seldom convenient for smallholder farmers for sustainable control of the disease. Breeding for development of durable genetic resistant varieties is known to offer lasting solution to control endemic disease threats to crop production. However, breeding for resistance to anthracnose has been slow considering the biological constraints related to the heterozygous and vegetative propagation of the crop. The development of saturated linkage maps with high marker density, such as SSRs, followed by identification of QTLs can accelerate the speed and precision of resistance breeding in water yam. In a previous study, a total of 1,152 EST-SSRs were developed from >40,000 EST-sequences generated from two D. alata genotypes. A set of 380 EST-SSRs were validated as polymorphic when tested on two diverse parents targeted for anthracnose disease and were used to generate a saturated linkage map. Majority of the SSRs (60.2%) showed Mendelian segregation pattern and had no effect on the construction of linkage map. All 380 EST-SSRs were mapped into 20 linkage groups, and covered a total length of 3229.5 cM. Majority of the markers were mapped on linkage group 1 (LG 1) comprising of 97 EST-SSRs. This is the first genetic linkage map of water yam constructed using EST-SSRs. QTL localization was based on phenotypic data collected over a 3-year period of inoculating the mapping population with the most virulent strain of C. gloeosporioides from West Africa. Based on threshold LOD scores, one QTL was consistently observed on LG 14 in all the three years and average score data. This QTL was found at position interval of 71.1-84.8 cM explaining 68.5% of the total phenotypic variation in the average score data. The high marker density allowed identification of QTLs and association for anthracnose disease, which could be validated in other mapping populations and used in marker-assisted breeding in D. alata improvement programmes.

Complete genome sequence of a putative new secovirus infecting yam (Dioscorea) plants

The complete genome sequence of a new virus infecting yam plants exhibiting mosaic symptom in Brazil was determined. The genome of this virus is composed of two molecules of positive-sense RNAs of 5979 and 3809 nucleotides in length, excluding the poly(A) tails. One large open reading frame (ORF) in each genomic segment (RNA1-ORF1 and RNA2-ORF2) was predicted. The highest amino acid sequence similarity in the Pro-Pol core region of RNA1 and the CP region of RNA2 was observed with chocolate lily virus A (a putative member of the family Secoviridae), with 54.6 and 27.7 % identity, respectively. This virus is thus likely to be a new member of the family Secoviridae, and we propose the tentative name "dioscorea mosaic-associated virus" (DMaV) for this virus.