Barcode System for Genetic Identification of Soybean [Glycine max (L.) Merrill] Cultivars Using InDel Markers Specific to Dense Variation Blocks

Development of a Gene-Based Soybean-Origin Discrimination Method Using Allele-Specific Polymerase Chain Reaction

A low soybean self-sufficiency rate in South Korea has caused a high import dependence and considerable price variation between domestic and foreign soybeans, causing the false labeling of foreign soybeans as domestic. Conventional soybean origin discrimination methods prevent a single-grain analysis and rely on the presence or absence of several compounds or concentration differences. This limits the origin discrimination of mixed samples, demonstrating the need for a method that analyzes individual grains. Therefore, we developed a method for origin discrimination using genetic analysis. The whole-genome sequencing data of the Williams 82 reference cultivar and 15 soybean varieties cultivated in South Korea were analyzed to identify the dense variation blocks (dVBs) with a high single-nucleotide polymorphism density. The PCR primers were prepared and validated for the insertion-deletion (InDel) sequences of the dVBs to discriminate each soybean variety. Our method effectively discriminated domestic and foreign soybean varieties, eliminating their false labeling.

Characterisation of the Complete Chloroplast Genomes of Seven Hyacinthus orientalis L. Cultivars: Insights into Cultivar Phylogeny

To improve agricultural performance and obtain potential economic benefits, an understanding of phylogenetic relationships of Hyacinthus cultivars is needed. This study aims to revisit the phylogenetic relationships of Hyacinthus cultivars using complete chloroplast genomes. Nine chloroplast genomes were de novo sequenced, assembled and annotated from seven cultivars of Hyacinthus orientalis and two Scilloideae species including Bellevalia paradoxa and Scilla siberica. The chloroplast genomes of Hyacinthus cultivars ranged from 154,458 bp to 154,641 bp, while those of Bellevalia paradoxa and Scilla siberica were 154,020 bp and 154,943 bp, respectively. Each chloroplast genome was annotated with 133 genes, including 87 protein-coding genes, 38 transfer RNA genes and 8 ribosomal RNA genes. Simple sequence repeats AAGC/CTTG and ACTAT/AGTAT were identified only in ‘Eros’, while AAATC/ATTTG were identified in all cultivars except ‘Eros’. Five haplotypes were identified based on 460 variable sites. Combined with six other previously published chloroplast genomes of Scilloideae, a sliding window analysis and a phylogenetic analysis were performed. Divergence hotspots ndhA and trnG-UGC were identified with a nucleotide diversity threshold at 0.04. The phylogenetic positions of Hyacinthus cultivars were different from the previous study using ISSR. Complete chloroplast genomes serve as new evidence in Hyacinthus cultivar phylogeny, contributing to cultivar identification, preservation and breeding.

Effective identification of varieties by nucleotide polymorphisms and its application for essentially derived variety identification in rice

BACKGROUND

Plant variety identification is the one most important of agricultural systems. Development of DNA marker profiles of released varieties to compare with candidate variety or future variety is required. However, strictly speaking, scientists did not use most existing variety identification techniques for "identification" but for "distinction of a limited number of cultivars," of which generalization ability always not be well estimated. Because many varieties have similar genetic backgrounds, even some essentially derived varieties (EDVs) are involved, which brings difficulties for identification and breeding progress. A fast, accurate variety identification method, which also has good performance on EDV determination, needs to be developed.

RESULTS

In this study, with the strategy of "Divide and Conquer," a variety identification method Conditional Random Selection (CRS) method based on SNP of the whole genome of 3024 rice varieties was developed and be applied in essentially derived variety (EDV) identification of rice. CRS is a fast, efficient, and automated variety identification method. Meanwhile, in practical, with the optimal threshold of identity score searched in this study, the set of SNP (including 390 SNPs) showed optimal performance on EDV and non-EDV identification in two independent testing datasets.

CONCLUSION

This approach first selected a minimal set of SNPs to discriminate non-EDVs in the 3000 Rice Genome Project, then united several simplified SNP sets to improve its generalization ability for EDV and non-EDV identification in testing datasets. The results suggested that the CRS method outperformed traditional feature selection methods. Furthermore, it provides a new way to screen out core SNP loci from the whole genome for DNA fingerprinting of crop varieties and be useful for crop breeding.

MFCIS: an automatic leaf-based identification pipeline for plant cultivars using deep learning and persistent homology

Recognizing plant cultivars reliably and efficiently can benefit plant breeders in terms of property rights protection and innovation of germplasm resources. Although leaf image-based methods have been widely adopted in plant species identification, they seldom have been applied in cultivar identification due to the high similarity of leaves among cultivars. Here, we propose an automatic leaf image-based cultivar identification pipeline called MFCIS (Multi-feature Combined Cultivar Identification System), which combines multiple leaf morphological features collected by persistent homology and a convolutional neural network (CNN). Persistent homology, a multiscale and robust method, was employed to extract the topological signatures of leaf shape, texture, and venation details. A CNN-based algorithm, the Xception network, was fine-tuned for extracting high-level leaf image features. For fruit species, we benchmarked the MFCIS pipeline on a sweet cherry (Prunus avium L.) leaf dataset with >5000 leaf images from 88 varieties or unreleased selections and achieved a mean accuracy of 83.52%. For annual crop species, we applied the MFCIS pipeline to a soybean (Glycine max L. Merr.) leaf dataset with 5000 leaf images of 100 cultivars or elite breeding lines collected at five growth periods. The identification models for each growth period were trained independently, and their results were combined using a score-level fusion strategy. The classification accuracy after score-level fusion was 91.4%, which is much higher than the accuracy when utilizing each growth period independently or mixing all growth periods. To facilitate the adoption of the proposed pipelines, we constructed a user-friendly web service, which is freely available at http://www.mfcis.online .

Development of 50 InDel-based barcode system for genetic identification of tartary buckwheat resources

Tartary buckwheat (Fagopyrum tataricum Gartn.) is a highly functional crop that is poised to be the target of many future breeding efforts. The reliable ex situ conservation of various genetic resources is essential for the modern breeding of tartary buckwheat varieties. We developed PCR-based co-dominant insertion/deletion (InDel) markers to discriminate tartary buckwheat genetic resources. First, we obtained the whole genome from 26 accessions across a superscaffold-scale reference genome of 569.37 Mb for tartary buckwheat cv. "Daegwan 3-7." Next, 171,926 homogeneous and 53,755 heterogeneous InDels were detected by comparing 26 accessions with the "Daegwan 3-7" reference sequence. Of these, 100 candidate InDels ranging from 5-20 bp in length were chosen for validation, and 50 of them revealed polymorphisms between the 26 accessions and "Daegwan 3-7." The validated InDels were further tested through the assessment of their likelihood to give rise to a single or a few PCR products in 50 other accessions, covering most tartary buckwheat genome types. The major allele frequencies ranged from 0.5616 at the TB42 locus to 0.9863 at the TB48 locus, with the average PIC value of 0.1532 with a range of 0.0267-0.3712. To create a user-friendly system, the homology of the genotypes between and among the accessions were visualized in both one- (1D) and two-dimensional (2D) barcode types by comparing amplicon polymorphisms with the reference variety, "Daegwan 3-7." A phylogenetic tree and population structure of the 76 accessions according to amplicon polymorphisms for the 50 InDel markers corresponded to those using non-synonymous single nucleotide polymorphism variants, indicating that the barcode system based on the 50 InDels was a useful tool to improve the reliability of identification of tartary buckwheat accessions in the germplasm stocks.

Proteolytic enzyme arbitrated antagonization of helminthiasis by Cinnamomum cappara leaf extract in Pheretima posthuma

Background

There have been several studies carried out to irradiate Helminthiasis however very little research have been carried out where in the enzymatic activity of plants are exploited to antagonize infections. Here we are analyzing the anthelmintic activity of Cinnamomum cappara leaf extract against Pheretima posthuma complimented by proteolytic action.

Results

The fresh leaves of Cinnamomum cappara was collected from local areas of Thrissur during December 2019. Plants were identified and authenticated by morphological and molecular characterization. The enzymatic action was analyzed by plotting Lineweaver–Burk plot which suggested that the extract possess the Km 185.77 μM for casein as substrate and obeyed Michaelis–Menten kinetics with typical hyperbolic relation with enzyme and increasing concentration of substrate. The effect of extract upon study subject was in directly proportional with concentration of antagonist where higher activities were obtained in high concentrations. The anatomical and histological studies suggested that the activity of extract was due to the degradation of muscular bundle of subject that resulted in the leakage of ceolomic fluid.

Conclusions

Cinnamomum cappara leaf extract possessed high degree of protease intervened anthelmintic activity against Pheretima posthuma. As the study subject show immense morphological and physiological resemblance with all other helminthic parasites, this results shall be adopted to further clinical and pharmacological applications.

A cost-effective barcode system for maize genetic discrimination based on bi-allelic InDel markers

BACKGROUND

Maize is one of the most important cereal crop all over the world with a complex genome of about 2.3 gigabase, and exhibits tremendous phenotypic and molecular diversity among different germplasms. Along with the phenotype identification, molecular markers have been accepted extensively as an alternative tool to discriminate different genotypes.

RESULTS

By using previous re-sequencing data of 205 lines, bi-allelic insertions and deletions (InDels) all over maize genome were screened, and a barcode system was constructed consisting of 37 bi-allelic insertion-deletion markers with high polymorphism information content (PIC) values, large discriminative size among varieties. The barcode system was measured and determined, different maize hybrids and inbreds were clearly discriminated efficiently with these markers, and hybrids responding parents were accurately determined. Compared with microarray data of more than 200 maize lines, the barcode system can discriminate maize varieties with 1.57% of different loci as a threshold. The barcode system can be used in standardized easy and quick operation with very low cost and minimum equipment requirements.

CONCLUSION

A barcode system was constructed for genetic discrimination of maize lines, including 37 InDel markers with high PIC values and user-friendly. The barcode system was measured and determined for efficient identification of maize lines.

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.

Investigating appropriate molecular and chemical methods for ingredient identity testing of plant-based protein powder dietary supplements

Plant-based protein powders are rapidly growing in popularity, and outdated quality assurance tools expose vulnerabilities to adulteration via different methods of "protein spiking". Adequate diagnostic tools are urgently needed to be able to authenticate protein source ingredients and screen for potential adulterants. We explored the application of three diagnostic tools for ingredient identification: targeted PCR with Sanger sequencing, NGS, and LC-MS/MS. We collected 33 samples of common commercial products from the plant-based protein powder market and sought to identify botanical components using the three technologies. We found success in detection with all approaches, with at least one main protein source being identified by at least one approach in all samples. The investigation uncovered challenges to data collection or result interpretation with each technology including but not limited to amplification biases with PCR technologies, potential influence of DNA degradation, and issues with protein solubility during isolation. Ultimately, each platform demonstrated utility along with certain caveats, which epitomized the importance of orthogonality of testing.

Soybean-VCF2Genomes: a database to identify the closest accession in soybean germplasm collection

BACKGROUND

The development of next generation sequencer (NGS) and the analytical methods allowed the researchers to profile their samples more precisely and easier than before. Especially for agriculture, the certification of the genomic background of their plant materials would be important for the reliability of seed market and stable yield as well as for quarantine procedure. However, the analysis of NGS data is still difficult for non-computational researchers or breeders to verify their samples because majority of current softwares for NGS analysis require users to access unfamiliar Linux environment.

MAIN BODY

Here, we developed a web-application, "Soybean-VCF2Genomes", http://pgl.gnu.ac.kr/soy_vcf2genome/ to map single sample variant call format (VCF) file against known soybean germplasm collection for identification of the closest soybean accession. Based on principal component analysis (PCA), we simplified genotype matrix for lowering computational burden while maintaining accurate clustering. With our web-application, users can simply upload single sample VCF file created by more than 10x resequencing strategy to find the closest samples along with linkage dendrogram of the reference genotype matrix.

CONCLUSION

The information of the closest soybean cultivar will allow breeders to estimate relative germplasmic position of their query sample to determine soybean breeding strategies. Moreover, our VCF2Genomes scheme can be extended to other plant species where the whole genome sequences of core collection are publicly available.