Assessment of Cultivar Distinctness in Alfalfa: A Comparison of Genotyping-by-Sequencing, Simple-Sequence Repeat Marker, and Morphophysiological Observations

Genome-wide genotyping data renew knowledge on genetic diversity of a worldwide alfalfa collection and give insights on genetic control of phenology traits

China's and Europe's dependence on imported protein is a threat to the food self-sufficiency of these regions. It could be solved by growing more legumes, including alfalfa that is the highest protein producer under temperate climate. To create productive and high-value varieties, the use of large genetic diversity combined with genomic evaluation could improve current breeding programs. To study alfalfa diversity, we have used a set of 395 alfalfa accessions (i.e. populations), mainly from Europe, North and South America and China, with fall dormancy ranging from 3 to 7 on a scale of 11. Five breeders provided materials (617 accessions) that were compared to the 400 accessions. All accessions were genotyped using Genotyping-by-Sequencing (GBS) to obtain SNP allele frequency. These genomic data were used to describe genetic diversity and identify genetic groups. The accessions were phenotyped for phenology traits (fall dormancy and flowering date) at two locations (Lusignan in France, Novi Sad in Serbia) from 2018 to 2021. The QTL were detected by a Multi-Locus Mixed Model (mlmm). Subsequently, the quality of the genomic prediction for each trait was assessed. Cross-validation was used to assess the quality of prediction by testing GBLUP, Bayesian Ridge Regression (BRR), and Bayesian Lasso methods. A genetic structure with seven groups was found. Most of these groups were related to the geographical origin of the accessions and showed that European and American material is genetically distinct from Chinese material. Several QTL associated with fall dormancy were found and most of these were linked to genes. In our study, the infinitesimal methods showed a higher prediction quality than the Bayesian Lasso, and the genomic prediction achieved high (>0.75) predicting abilities in some cases. Our results are encouraging for alfalfa breeding by showing that it is possible to achieve high genomic prediction quality.

RAD-seq as an effective strategy for heterogenous variety identification in plants-a case study in Italian Ryegrass (Lolium multiflorum)

The primary approach for variety distinction in Italian ryegrass is currently the DUS (distinctness, uniformity and stability) test based on phenotypic traits. Considering the diverse genetic background within the population and the complexity of the environment, however, it is challenging to accurately distinguish varieties based on DUS criteria alone. In this study, we proposed the application of high-throughput RAD-seq to distinguish 11 Italian ryegrass varieties with three bulks of 50 individuals per variety. Our findings revealed significant differences among the 11 tested varieties. The PCA, DAPC and STRUCTURE analysis indicated a heterogeneous genetic background for all of them, and the AMOVA analysis also showed large genetic variance among these varieties (Φ_ST = 0.373), which were clearly distinguished based on phylogenetic analysis. Further nucleotide diversity (Pi) analysis showed that the variety 'Changjiang No.2' had the best intra-variety consistency among 11 tested varieties. Our findings suggest that the RAD-seq could be an effectively alternative method for the variety distinction of Italian ryegrass, as well as a potential tool for open-pollinated varieties (OPVs) of other allogamous species.

Plant Variety Protection: Current Practices and Insights

Breeders persistently supply farmers with the best varieties in order to exceed consumer demand through plant-breeding processes that are resource-intensive. In order to motivate continuous innovation in variety development, a system needs to provide incentives for plant breeders to develop superior varieties, for example, exclusive ownership to produce and market those varieties. The most common system is the acquisition of intellectual property protection through plant variety protection, also known as the breeder’s right. Most countries have adopted the system established by the International Union for the Protection of New Varieties of Plants (UPOV). To be granted plant variety protection, the variety should prove to be unique by meeting three requirements: distinctness, uniformity, and stability. This review summarizes (1) the plant variety protection via UPOV convention, (2) technical methods for distinctness, uniformity, and stability testing via phenotype, molecular markers, and sequencing as well as their challenges and potentiality, and (3) additional discussions in essentially derived variety, value for cultivation and use testing, and open source seed initiative.

Molecular-Assisted Distinctness and Uniformity Testing Using SLAF-Sequencing Approach in Soybean

Distinctness, uniformity and stability (DUS) testing of cultivars through morphological descriptors is an important and compulsory part of soybean breeding. Molecular markers are usually more effective and accurate in describing the genetic features for the identification and purity assessment of cultivars. In the present study, we assessed the distinctness and uniformity of five soybean cultivars using both single nucleotide polymorphism (SNP) markers developed by specific-locus amplified fragment sequencing (SLAF-seq) technology, and simple sequence repeat (SSR) markers. The phylogenetic tree and principal component analysis (PCA) from both the SLAF-seq and SSR methods showed a clear distinction among cultivars Zhonghuang 18, Zhonghuang 68 and Zhonghuang 35, while no clear distinction was observed between cultivars Zhonghuang 13 and Hedou 13. Using the SLAF-seq method, we determined the proportion of homozygous loci for the five soybean cultivars. The heterozygosity of each individual plant was estimated for the assessment of cultivar purity and the purity levels of the five soybean cultivars ranged from 91.89% to 93.96%. To further validate the applicability of the SLAF-seq approach for distinctness testing, we used the SNP information of 150 soybean cultivars with different origins. The cultivars were also distinguished clearly. Taken together, SLAF-seq can be used as an accurate and reliable method in the assessment of the distinctness and uniformity of soybean cultivars.

Insights into deployment of DNA markers in plant variety protection and registration

The efficiency of phenotype-based assessments of plant variety protection and registration could be improved by the integration of DNA-based testing. We review the current and proposed models in the era of next-generation breeding. The current plant variety protection system relies on morphological description of plant varieties. Distinctness, uniformity, and stability (DUS) assessments determine whether a new variety is distinguishable from common knowledge varieties and exhibits sufficient phenotypic uniformity and stability during two independent growing cycles. However, DUS assessment can be costly, time-consuming and often restricted to a relatively small number of traits that can be influenced by environmental conditions. This calls for the adoption of a DNA-based system which is endorsed by the International Union for the Protection of New Varieties of Plants (UPOV). This could enable examiners to deploy trait-specific DNA markers in DUS testing as well as using such genetic markers to manage reference collections. Within UPOV's system, breeders can freely use protected varieties in breeding programs. However, breeders of protected varieties may seek sharing in ownership of essentially derived varieties once it is proven that they, with the exception of a few distinctive DUS trait(s), conform to parental varieties in essential characteristics. As well as their complementary role in DUS testing, DNA markers have been known as a good replacement of morphological traits in defining boundaries between independently and essentially derived varieties. With the advent of new breeding technologies that allow minor modification in varieties with outcomes of specific merit or utility, detecting distinctness between varieties may become increasingly challenging. This, together with the ever-increasing number of varieties with which to compare new candidate varieties, supports the potential utility of using DNA-based approaches in variety description.

Resolving relationships and phylogeographic history of the Nyssa sylvatica complex using data from RAD-seq and species distribution modeling

Nyssa sylvatica complex consists of several woody taxa occurring in eastern North America. These taxa were recognized as two or three species including three or four varieties by different authors. Due to high morphological similarities and complexity of morphological variation, classification and delineation of taxa in the group have been difficult and controversial. Here we employ data from RAD-seq to elucidate the genetic structure and phylogenetic relationships within the group. Using the genetic evidence, we evaluate previous classifications and delineate species. We also employ Species Distribution Modeling (SDM) to evaluate impacts of climatic changes on the ranges of the taxa and to gain insights into the relevant refugia in eastern North America. Results from Molecular Variance Analysis (AMOVA), STRUCTURE, phylogenetic analyses using Maximum likelihood, Bayesian Inference, and Splittree methods of RAD-seq data strongly support a two-clade pattern, largely separating samples of N. sylvatica from those of N. biflora-N. ursina mix. Divergence time analysis with BEAST suggests the two clades diverged in the mid Miocene. The ancestor of the present trees of N. sylvatica was suggested to be in the Pliocene and that of N. biflora-N. ursina mix in the end of the Miocene. Results from SDM predicted a smaller range in the southern part of the species present range of each clade during the Last Glacial Maximum (LGM). A northward expansion of the ranges during interglacial period and a northward shift of the ranges in the future under a model of global warming were also predicted. Our results support the recognition of two species in the complex, N. sylvatica and N. biflora, following the phylogenetic species concept. We found no genetic evidence supporting recognitions of intraspecific taxa. However, we propose subsp. ursina and subsp. biflora within N. biflora due to their distinction in habits, distributions, and habitats. Our results further support movements of trees in eastern North America in response to climatic changes. Finally, our study demonstrates that RAD-seq data and a combination of population genomics and SDM are valuable in resolving relationship and biogeographic history of closely related species that are taxonomically difficult.

LinkImputeR: user-guided genotype calling and imputation for non-model organisms

Background

Genomic studies such as genome-wide association and genomic selection require genome-wide genotype data. All existing technologies used to create these data result in missing genotypes, which are often then inferred using genotype imputation software. However, existing imputation methods most often make use only of genotypes that are successfully inferred after having passed a certain read depth threshold. Because of this, any read information for genotypes that did not pass the threshold, and were thus set to missing, is ignored. Most genomic studies also choose read depth thresholds and quality filters without investigating their effects on the size and quality of the resulting genotype data. Moreover, almost all genotype imputation methods require ordered markers and are therefore of limited utility in non-model organisms.

Results

Here we introduce LinkImputeR, a software program that exploits the read count information that is normally ignored, and makes use of all available DNA sequence information for the purposes of genotype calling and imputation. It is specifically designed for non-model organisms since it requires neither ordered markers nor a reference panel of genotypes. Using next-generation DNA sequence (NGS) data from apple, cannabis and grape, we quantify the effect of varying read count and missingness thresholds on the quantity and quality of genotypes generated from LinkImputeR. We demonstrate that LinkImputeR can increase the number of genotype calls by more than an order of magnitude, can improve genotyping accuracy by several percent and can thus improve the power of downstream analyses. Moreover, we show that the effects of quality and read depth filters can differ substantially between data sets and should therefore be investigated on a per-study basis.

Conclusions

By exploiting DNA sequence data that is normally ignored during genotype calling and imputation, LinkImputeR can significantly improve both the quantity and quality of genotype data generated from NGS technologies. It enables the user to quickly and easily examine the effects of varying thresholds and filters on the number and quality of the resulting genotype calls. In this manner, users can decide on thresholds that are most suitable for their purposes. We show that LinkImputeR can significantly augment the value and utility of NGS data sets, especially in non-model organisms with poor genomic resources.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3873-5) contains supplementary material, which is available to authorized users.

Large-scale SNP discovery and construction of a high-density genetic map of Colossoma macropomum through genotyping-by-sequencing

Colossoma macropomum, or tambaqui, is the largest native Characiform species found in the Amazon and Orinoco river basins, yet few resources for genetic studies and the genetic improvement of tambaqui exist. In this study, we identified a large number of single-nucleotide polymorphisms (SNPs) for tambaqui and constructed a high-resolution genetic linkage map from a full-sib family of 124 individuals and their parents using the genotyping by sequencing method. In all, 68,584 SNPs were initially identified using minimum minor allele frequency (MAF) of 5%. Filtering parameters were used to select high-quality markers for linkage analysis. We selected 7,734 SNPs for linkage mapping, resulting in 27 linkage groups with a minimum logarithm of odds (LOD) of 8 and maximum recombination fraction of 0.35. The final genetic map contains 7,192 successfully mapped markers that span a total of 2,811 cM, with an average marker interval of 0.39 cM. Comparative genomic analysis between tambaqui and zebrafish revealed variable levels of genomic conservation across the 27 linkage groups which allowed for functional SNP annotations. The large-scale SNP discovery obtained here, allowed us to build a high-density linkage map in tambaqui, which will be useful to enhance genetic studies that can be applied in breeding programs.

Diversity analysis of cotton (Gossypium hirsutum L.) germplasm using the CottonSNP63K Array

BACKGROUND

Cotton germplasm resources contain beneficial alleles that can be exploited to develop germplasm adapted to emerging environmental and climate conditions. Accessions and lines have traditionally been characterized based on phenotypes, but phenotypic profiles are limited by the cost, time, and space required to make visual observations and measurements. With advances in molecular genetic methods, genotypic profiles are increasingly able to identify differences among accessions due to the larger number of genetic markers that can be measured. A combination of both methods would greatly enhance our ability to characterize germplasm resources. Recent efforts have culminated in the identification of sufficient SNP markers to establish high-throughput genotyping systems, such as the CottonSNP63K array, which enables a researcher to efficiently analyze large numbers of SNP markers and obtain highly repeatable results. In the current investigation, we have utilized the SNP array for analyzing genetic diversity primarily among cotton cultivars, making comparisons to SSR-based phylogenetic analyses, and identifying loci associated with seed nutritional traits.

RESULTS

The SNP markers distinctly separated G. hirsutum from other Gossypium species and distinguished the wild from cultivated types of G. hirsutum. The markers also efficiently discerned differences among cultivars, which was the primary goal when designing the CottonSNP63K array. Population structure within the genus compared favorably with previous results obtained using SSR markers, and an association study identified loci linked to factors that affect cottonseed protein content.

CONCLUSIONS

Our results provide a large genome-wide variation data set for primarily cultivated cotton. Thousands of SNPs in representative cotton genotypes provide an opportunity to finely discriminate among cultivated cotton from around the world. The SNPs will be relevant as dense markers of genome variation for association mapping approaches aimed at correlating molecular polymorphisms with variation in phenotypic traits, as well as for molecular breeding approaches in cotton.

The Impact of Genotyping-by-Sequencing Pipelines on SNP Discovery and Identification of Markers Associated with Verticillium Wilt Resistance in Autotetraploid Alfalfa (Medicago sativa L.)

Verticillium wilt (VW) of alfalfa is a soilborne disease causing severe yield loss in alfalfa. To identify molecular markers associated with VW resistance, we used an integrated framework of genome-wide association study (GWAS) with high-throughput genotyping by sequencing (GBS) to identify loci associated with VW resistance in an F1 full-sib alfalfa population. Phenotyping was performed using manual inoculation of the pathogen to cloned plants of each individual and disease severity was scored using a standard scale. Genotyping was done by GBS, followed by genotype calling using three bioinformatics pipelines including the TASSEL-GBS pipeline (TASSEL), the Universal Network Enabled Analysis Kit (UNEAK), and the haplotype-based FreeBayes pipeline (FreeBayes). The resulting numbers of SNPs, marker density, minor allele frequency (MAF) and heterozygosity were compared among the pipelines. The TASSEL pipeline generated more markers with the highest density and MAF, whereas the highest heterozygosity was obtained by the UNEAK pipeline. The FreeBayes pipeline generated tetraploid genotypes, with the least number of markers. SNP markers generated from each pipeline were used independently for marker-trait association. Markers significantly associated with VW resistance identified by each pipeline were compared. Similar marker loci were found on chromosomes 5, 6, and 7, whereas different loci on chromosome 1, 2, 3, and 4 were identified by different pipelines. Most significant markers were located on chromosome 6 and they were identified by all three pipelines. Of those identified, several loci were linked to known genes whose functions are involved in the plants' resistance to pathogens. Further investigation on these loci and their linked genes would provide insight into understanding molecular mechanisms of VW resistance in alfalfa. Functional markers closely linked to the resistance loci would be useful for MAS to improve alfalfa cultivars with enhanced resistance to the disease.