Identification of pummelo cultivars by using a panel of 25 selected SNPs and 12 DNA segments

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.

Portuguese wild hop diversity assessment by fast SNP genotyping using high-resolution melting

A set of seven SNP markers was used to evaluate the genetic diversity of wild Portuguese hops in comparison with commercial cultivars. A collection of 110 wild genotypes and 33 cultivars was characterized by a high-resolution melting analysis of short amplicons targeting SNP loci. Most of the 143 genotypes (75%) could be differentiated. Phylogenetic analysis showed three main clusters, one included almost exclusively (98%) wild accessions, being the others constituted of both wild and commercial genotypes. The study of population genetic structure placed the accessions into three genetic units, being one exclusively of Portuguese genotypes. The study showed the great biodiversity of the Portuguese hop germplasm and the notable differences (F_ST = 0.163, p<0.00001) from commercial hops. Results support the usefulness of the use of these seven markers for hop discrimination, with the fast and high-throughput HRMA technique for allele calling and contribute to the affirmation of the high richness breeding potential of Portuguese wild hops.

Identification of a delayed leaf greening gene from a mutation of pummelo

Delayed greening of young leaves is an unusual phenomenon of plants in nature. Citrus are mostly evergreen tree species. Here, a natural mutant of "Guanxi" pummelo (Citrus maxima), which shows yellow leaves at the young stage, was characterized to identify the genes underlying the trait of delayed leaf greening in plants. A segregating population with this mutant as the seed parent and a normal genotype as the pollen parent was generated. Two DNA pools respectively from the leaves of segregating seedlings with extreme phenotypes of normal leaf greening and delayed leaf greening were collected for sequencing. Bulked segregant analysis (BSA) and InDel marker analysis demonstrated that the delayed leaf greening trait is governed by a 0.3 Mb candidate region on chromosome 6. Gene expression analysis further identified a key candidate gene (Citrus Delayed Greening gene 1, CDG1) in the 0.3 Mb region, which showed significantly differential expression between the genotypes with delayed and normal leaf greening phenotypes. There was a 67 bp InDel region difference in the CDG1 promoter and the InDel region contains a TATA-box element. Confocal laser-scanning microscopy revealed that the CDG1-GFP fusion protein signals were co-localized with the chloroplast signals in the protoplasts. Overexpression of CDG1 in tobacco and Arabidopsis led to the phenotype of delayed leaf greening. These results suggest that the CDG1 gene is involved in controlling the delayed leaf greening phenotype with important functions in chloroplast development.

Molecular identification and evolutionary relationships between the subspecies of Musa by DNA barcodes

BACKGROUND

The banana (Musa sp., AAA) genome is constantly increasing due to high-frequency of somaclonal variations. Due to its large diversity, a conventional numerical and morphological based taxonomic identification of banana cultivars is laborious, difficult and often leads to subject of disagreements.

RESULTS

Hence, in the present study, we used universal DNA barcode ITS2 region to identify and to find the genetic relationship between the cultivars and varieties of banana. Herein, a total of 16 banana cultivars were PCR amplified using ITS2 primer pair. In addition, 321 sequences which were retrieved from GenBank, USA, were used in this study. The sequences were then aligned using Clustal W and genetic distances were computed using MEGA V5.1. The study showed significant divergence between the intra- and inter-specific genetic distances in ITS2 region. BLAST1 and Distance methods proved that ITS2 DNA barcode region successfully identified and distinguished the cultivar and varieties of banana.

CONCLUSION

Thus, from the results of the present study, it is clear that ITS2 is not only an efficient DNA barcode to identify the banana species but also a potential candidate for enumerating the phylogenetic relationships between the subspecies and cultivars. This is the first comprehensive study to categorically distinguish the economically important banana subspecies and varieties using DNA barcodes and to understand its evolutionary relationship.

Geographic population genetic structure and diversity of Sophora moorcroftiana based on genotyping-by-sequencing (GBS)

Sophora moorcroftiana is a perennial leguminous low shrub endemic to the Yarlung Zangbo River basin in Tibet with irreplaceable economic and ecological value. To determine the drivers of evolution in this species, 225 individuals belonging to 15 populations from different geographic locations were sampled, and population genetics was studied using high-throughput genotyping-by-sequencing (GBS). Based on genetic diversity analysis, phylogenetic analysis, principal component analysis, and structure analysis, 15 natural populations were clustered into the following five subgroups: subgroup I (Shigatse subgroup) was located in the upper reaches of the Yarlung Zangbo River with a relatively high level of population genetic variation (means for PIC, Shannon and PI were 0.173, 0.326 and 0.0000305, respectively), and gene flow within the subgroup was also high (mean value for Nm was 4.67). Subgroup II (including Pop 7 and Pop 8; means for PIC, Shannon and PI were 0.182, 0.345 and 0.0000321, respectively), located in the middle reaches of the Yarlung Zangbo River had relatively high levels of gene flow with the populations distributed in the upper and lower reaches. The Nm between subgroup II with subgroups I and III was 3.271 and 2.894, respectively. Considering all the genetic diversity indices Pop 8 had relatively high genetic diversity. Subgroup III (the remaining mixed subgroup of Lhasa and Shannan) was located in the middle reaches of the Yarlung Zangbo River and the means for PIC, Shannon and PI were 0.172, 0.324 and 0.0000303, respectively. Subgroup IV (Nyingchi subgroup), located in the lower reaches of the Yarlung Zangbo River basin, showed a further genetic distance from the other subgroups and the means for PIC, Shannon and PI were 0.147, 0.277 and 0.0000263, respectively. Subgroup V (Nyingchi Gongbu Jiangda subgroup), located in the upper reaches of the Niyang River, had the lowest level of genetic variation (means for PIC, Shannon and PI were 0.106, 0.198 and 0.0000187, respectively) and gene flow with other populations (mean value for Nm was 0.42). According to the comprehensive analysis, the S. moorcroftiana populations generally expanded from upstream to downstream and displayed a high level of genetic differentiation in the populations in the upper and lower reaches. There were high levels of gene exchange between the central populations with upstream and downstream populations, and wind-induced seed dispersal was an important factor in the formation of this gene exchange mode.

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.

Genetic Diversity, Pedigree Relationships, and A Haplotype-Based DNA Fingerprinting System of Red Bayberry Cultivars

High throughput sequencing was used to reveal the distribution of whole-genome variations in cultivated Morella rubra (Sieb. et Zucc.). A total of 3,151,123 SNPs, 371,757 small indels, and 15,904 SVs were detected in 52 accessions. Verification by Sanger sequencing demonstrated that the positive rate of the SNPs was approximately 97.3%. Search for more genetic variations was expanded to 141 red bayberry accessions, most of which were cultivars, by sequencing 19 selected genomic segments (SEG1-19). The results showed that each segment harbored, on average, 7.8 alleles (haplotypes), a haplotype diversity of 0.42, and a polymorphic information content (PIC) of 0.40. Seventy-two different genotypes were identified from the 141 accessions, and statistical analysis showed that the accessions with duplicated genotypes were either somatic mutants or simply synonyms. Core set selection results showed that a minimum of 34 genotypes could already have covered all the alleles on the segments. A DNA fingerprinting system was developed for red bayberry, which used the diversity information of only 8 DNA segments yet still achieved a very high efficiency without losing robustness. No large clade was robustly supported by hierarchical clustering, and well-supported small clusters mainly included close relatives. These results should lead to an improved understanding of the genetic diversity of red bayberry and be valuable for future molecular breeding and variety protection.

Microhaplotype identified and performed in genetic investigation using PCR-SSCP

The recently introduced concept of microhaplotype loci has attracted attention in forensics. Previous studies estimated the allele frequencies generally through obtaining genotypic data on the individual SNPs from a larger set of unrelated individuals then phasing microhaplotypes by statistical and computational techniques. Determining phase for a single new individual requires the larger set of individuals to have been genotyped previously. Rare microhaplotypes possessed only by the target individual or microhaplotypes private to a specific population not previously studied are unlikely to be accurately phased using data sets of SNPs. Thus, there is a demand for an approach that could directly determine a gain single individual's precise microhaplotype information. In the present study, we introduced potential approaches of single chain sequencing based Massively Parallel Sequencing Technology (MiSeq) and PCR based Single Strand Conformational Polymorphism (SSCP) technology which was simple, accurate, and cost-effective. The results indicated that microhaplotypes contain much more polymorphic information than divided SNPs per locus (average heterozygosity of microhaplotype 0.61 VS SNPs 0.41). When microhaplotype allele frequencies were compared among five Chinese ethnic populations, significantly different distributions were found between the Han and Uyghur populations. Further analysis of pairwise Fst values and analysis of molecular variance (AMOVA), showed significant population differentiation between the Uyghur and other populations.

High-Resolution DNA Melting Analysis in Plant Research

Genetic and genomic studies provide valuable insight into the inheritance, structure, organization, and function of genes. The knowledge gained from the analysis of plant genes is beneficial to all aspects of plant research, including crop improvement. New methods and tools are continually being developed to facilitate rapid and accurate mapping, sequencing, and analyzing of genes. Here, I review the recent progress in the application of high-resolution melting (HRM) analysis of DNA, a method that allows detecting polymorphism in double-stranded DNA by comparing profiles of melting curves. Use of HRM has expanded considerably in the past few years as the method was successfully applied for high-throughput genotyping, mapping genes, testing food products and seeds, and other areas of plant research.

GBS-SNP-CROP: a reference-optional pipeline for SNP discovery and plant germplasm characterization using variable length, paired-end genotyping-by-sequencing data

BACKGROUND

With its simple library preparation and robust approach to genome reduction, genotyping-by-sequencing (GBS) is a flexible and cost-effective strategy for SNP discovery and genotyping, provided an appropriate reference genome is available. For resource-limited curation, research, and breeding programs of underutilized plant genetic resources, however, even low-depth references may not be within reach, despite declining sequencing costs. Such programs would find value in an open-source bioinformatics pipeline that can maximize GBS data usage and perform high-density SNP genotyping in the absence of a reference.

RESULTS

The GBS SNP-Calling Reference Optional Pipeline (GBS-SNP-CROP) developed and presented here adopts a clustering strategy to build a population-tailored "Mock Reference" from the same GBS data used for downstream SNP calling and genotyping. Designed for libraries of paired-end (PE) reads, GBS-SNP-CROP maximizes data usage by eliminating unnecessary data culling due to imposed read-length uniformity requirements. Using 150 bp PE reads from a GBS library of 48 accessions of tetraploid kiwiberry (Actinidia arguta), GBS-SNP-CROP yielded on average three times as many SNPs as TASSEL-GBS analyses (32 and 64 bp tag lengths) and over 18 times as many as TASSEL-UNEAK, with fewer genotyping errors in all cases, as evidenced by comparing the genotypic characterizations of biological replicates. Using the published reference genome of a related diploid species (A. chinensis), the reference-based version of GBS-SNP-CROP behaved similarly to TASSEL-GBS in terms of the number of SNPs called but had an improved read depth distribution and fewer genotyping errors. Our results also indicate that the sets of SNPs detected by the different pipelines above are largely orthogonal to one another; thus GBS-SNP-CROP may be used to augment the results of alternative analyses, whether or not a reference is available.

CONCLUSIONS

By achieving high-density SNP genotyping in populations for which no reference genome is available, GBS-SNP-CROP is worth consideration by curators, researchers, and breeders of under-researched plant genetic resources. In cases where a reference is available, especially if from a related species or when the target population is particularly diverse, GBS-SNP-CROP may complement other reference-based pipelines by extracting more information per sequencing dollar spent. The current version of GBS-SNP-CROP is available at https://github.com/halelab/GBS-SNP-CROP.git.

Tracking crop varieties using genotyping-by-sequencing markers: a case study using cassava (Manihot esculenta Crantz)

Background

Accurate identification of crop cultivars is crucial in assessing the impact of crop improvement research outputs. Two commonly used identification approaches, elicitation of variety names from farmer interviews and morphological plant descriptors, have inherent uncertainty levels. Genotyping-by-sequencing (GBS) was used in a case study as an alternative method to track released varieties in farmers’ fields, using cassava, a clonally propagated root crop widely grown in the tropics, and often disseminated through extension services and informal seed systems. A total of 917 accessions collected from 495 farming households across Ghana were genotyped at 56,489 SNP loci along with a “reference library” of 64 accessions of released varieties and popular landraces.

Results

Accurate cultivar identification and ancestry estimation was accomplished through two complementary clustering methods: (i) distance-based hierarchical clustering; and (ii) model-based maximum likelihood admixture analysis. Subsequently, 30 % of the identified accessions from farmers’ fields were matched to specific released varieties represented in the reference library. ADMIXTURE analysis revealed that the optimum number of major varieties was 11 and matched the hierarchical clustering results. The majority of the accessions (69 %) belonged purely to one of the 11 groups, while the remaining accessions showed two or more ancestries. Further analysis using subsets of SNP markers reproduced results obtained from the full-set of markers, suggesting that GBS can be done at higher DNA multiplexing, thereby reducing the costs of variety fingerprinting. A large proportion of discrepancy between genetically unique cultivars as identified by markers and variety names as elicited from farmers were observed. Clustering results from ADMIXTURE analysis was validated using the assumption-free Discriminant Analysis of Principal Components (DAPC) method.

Conclusion

We show that genome-wide SNP markers from increasingly affordable GBS methods coupled with complementary cluster analysis is a powerful tool for fine-scale population structure analysis and variety identification. Moreover, the ancestry estimation provides a framework for quantifying the contribution of exotic germplasm or older improved varieties to the genetic background of contemporary improved cultivars.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0273-1) contains supplementary material, which is available to authorized users.

Identifying Litchi (Litchi chinensis Sonn.) Cultivars and Their Genetic Relationships Using Single Nucleotide Polymorphism (SNP) Markers

Litchi is an important fruit tree in tropical and subtropical areas of the world. However, there is widespread confusion regarding litchi cultivar nomenclature and detailed information of genetic relationships among litchi germplasm is unclear. In the present study, the potential of single nucleotide polymorphism (SNP) for the identification of 96 representative litchi accessions and their genetic relationships in China was evaluated using 155 SNPs that were evenly spaced across litchi genome. Ninety SNPs with minor allele frequencies above 0.05 and a good genotyping success rate were used for further analysis. A relatively high level of genetic variation was observed among litchi accessions, as quantified by the expected heterozygosity (He = 0.305). The SNP based multilocus matching identified two synonymous groups, 'Heiye' and 'Wuye', and 'Chengtuo' and 'Baitangli 1'. A subset of 14 SNPs was sufficient to distinguish all the non-redundant litchi genotypes, and these SNPs were proven to be highly stable by repeated analyses of a selected group of cultivars. Unweighted pair-group method of arithmetic averages (UPGMA) cluster analysis divided the litchi accessions analyzed into four main groups, which corresponded to the traits of extremely early-maturing, early-maturing, middle-maturing, and late-maturing, indicating that the fruit maturation period should be considered as the primary criterion for litchi taxonomy. Two subpopulations were detected among litchi accessions by STRUCTURE analysis, and accessions with extremely early- and late-maturing traits showed membership coefficients above 0.99 for Cluster 1 and Cluster 2, respectively. Accessions with early- and middle-maturing traits were identified as admixture forms with varying levels of membership shared between the two clusters, indicating their hybrid origin during litchi domestication. The results of this study will benefit litchi germplasm conservation programs and facilitate maximum genetic gains in litchi breeding programs.

De novo transcriptome assembly of pummelo and molecular marker development

Pummelo (Citrus grandis) is an important fruit crop worldwide because of its nutritional value. To accelerate the pummelo breeding program, it is essential to obtain extensive genetic information and develop relative molecular markers. Here, we obtained a 12-Gb transcriptome dataset of pummelo through a mixture of RNA from seven tissues using Illumina pair-end sequencing, assembled into 57,212 unigenes with an average length of 1010 bp. The annotation and classification results showed that a total of 39,584 unigenes had similar hits to the known proteins of four public databases, and 31,501 were classified into 55 Gene Ontology (GO) functional sub-categories. The search for putative molecular markers among 57,212 unigenes identified 10,276 simple sequence repeats (SSRs) and 64,720 single nucleotide polymorphisms (SNPs). High-quality primers of 1174 SSR loci were designed, of which 88.16% were localized to nine chromosomes of sweet orange. Of 100 SSR primers that were randomly selected for testing, 87 successfully amplified clear banding patterns. Of these primers, 29 with a mean PIC (polymorphic information content) value of 0.52 were effectively applied for phylogenetic analysis. Of the 20 SNP primers, 14 primers, including 54 potential SNPs, yielded target amplifications, and 46 loci were verified via Sanger sequencing. This new dataset will be a valuable resource for molecular biology studies of pummelo and provides reliable information regarding SNP and SSR marker development, thus expediting the breeding program of pummelo.

Developing single nucleotide polymorphism (SNP) markers from transcriptome sequences for identification of longan (Dimocarpus longan) germplasm

Longan (Dimocarpus longan Lour.) is an important tropical fruit tree crop. Accurate varietal identification is essential for germplasm management and breeding. Using longan transcriptome sequences from public databases, we developed single nucleotide polymorphism (SNP) markers; validated 60 SNPs in 50 longan germplasm accessions, including cultivated varieties and wild germplasm; and designated 25 SNP markers that unambiguously identified all tested longan varieties with high statistical rigor (P<0.0001). Multiple trees from the same clone were verified and off-type trees were identified. Diversity analysis revealed genetic relationships among analyzed accessions. Cultivated varieties differed significantly from wild populations (F st=0.300; P<0.001), demonstrating untapped genetic diversity for germplasm conservation and utilization. Within cultivated varieties, apparent differences between varieties from China and those from Thailand and Hawaii indicated geographic patterns of genetic differentiation. These SNP markers provide a powerful tool to manage longan genetic resources and breeding, with accurate and efficient genotype identification.