QTL Mapping of Resistance to Bacterial Wilt in Pepper Plants (Capsicum annuum) Using Genotyping-by-Sequencing (GBS)

Bacterial wilt (BW) disease, which is caused by Ralstonia solanacearum, is one globally prevalent plant disease leading to significant losses of crop production and yield with the involvement of a diverse variety of monocot and dicot host plants. In particular, the BW of the soil-borne disease seriously influences solanaceous crops, including peppers (sweet and chili peppers), paprika, tomatoes, potatoes, and eggplants. Recent studies have explored genetic regions that are associated with BW resistance for pepper crops. However, owing to the complexity of BW resistance, the identification of the genomic regions controlling BW resistance is poorly understood and still remains to be unraveled in the pepper cultivars. In this study, we performed the quantitative trait loci (QTL) analysis to identify genomic loci and alleles, which play a critical role in the resistance to BW in pepper plants. The disease symptoms and resistance levels for BW were assessed by inoculation with R. solanacearum. Genotyping-by-sequencing (GBS) was utilized in 94 F2 segregating populations originated from a cross between a resistant line, KC352, and a susceptible line, 14F6002-14. A total of 628,437 single-nucleotide polymorphism (SNP) was obtained, and a pepper genetic linkage map was constructed with putative 1550 SNP markers via the filtering criteria. The linkage map exhibited 16 linkage groups (LG) with a total linkage distance of 828.449 cM. Notably, QTL analysis with CIM (composite interval mapping) method uncovered pBWR-1 QTL underlying on chromosome 01 and explained 20.13 to 25.16% by R2 (proportion of explained phenotyphic variance by the QTL) values. These results will be valuable for developing SNP markers associated with BW-resistant QTLs as well as for developing elite BW-resistant cultivars in pepper breeding programs.

Genotyping-by-Sequencing Derived Genetic Linkage Map and Quantitative Trait Loci for Sugar Content in Onion (Allium cepa L.)

Onion (2n = 2x = 16) has been a nutritional, medicinal and economically valuable vegetable crop all over the world since ancient times. To accelerate the molecular breeding in onion, genetic linkage maps are prerequisite. However, construction of genetic linkage maps of onion remains relatively rudimentary due to a large genome (about 16.3 Gbp) as well as biennial life cycle, cross-pollinated nature, and high inbreeding depression. In this study, we constructed single nucleotide polymorphism (SNP)-based genetic linkage map of onion in an F₂ segregating population derived from a cross between the doubled haploid line '16P118' and inbred line 'Sweet Green' through genotyping by sequencing (GBS). A total of 207.3 Gbp of raw sequences were generated using an Illumina HiSeq X system, and 24,341 SNPs were identified with the criteria based on three minimum depths, lower than 30% missing rate, and more than 5% minor allele frequency. As a result, an onion genetic linkage map consisting of 216 GBS-based SNPs were constructed comprising eight linkage groups spanning a genetic length of 827.0 cM. Furthermore, we identified the quantitative trait loci (QTLs) for the sucrose, glucose, fructose, and total sugar content across the onion genome. We identified a total of four QTLs associated with sucrose (qSC4.1), glucose (qGC5.1), fructose (qFC5.1), and total sugar content (qTSC5.1) explaining the phenotypic variation (R²%) ranging from 6.07-11.47%. This map and QTL information will contribute to develop the molecular markers to breed the cultivars with high sugar content in onion.

Molecular genetic diversity and population structure analyses of rutabaga accessions from Nordic countries as revealed by single nucleotide polymorphism markers

Background

Rutabaga or swede (Brassica napus ssp. napobrassica (L.) Hanelt) varies in root and leaf shape and colour, flesh colour, foliage growth habits, maturity date, seed quality parameters, disease resistance and other traits. Despite these morphological differences, no in-depth molecular analyses of genetic diversity have been conducted in this crop. Understanding this diversity is important for conservation and broadening the use of this resource.

Results

This study investigated the genetic diversity within and among 124 rutabaga accessions from five Nordic countries (Norway, Sweden, Finland, Denmark and Iceland) using a 15 K single nucleotide polymorphism (SNP) Brassica array. After excluding markers that did not amplify genomic DNA, monomorphic and low coverage site markers, the accessions were analyzedwith 6861 SNP markers. Allelic frequency statistics, including polymorphism information content (PIC), minor allele frequency (MAF) and mean expected heterozygosity (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \overline{H} $$\end{document}H¯e) and population differentiation statistics such as Wright’s F-statistics (F_ST) and analysis of molecular variance (AMOVA) indicated that the rutabaga accessions from Norway, Sweden, Finland and Denmark were not genetically different from each other. In contrast, accessions from these countries were significantly different from the accessions from Iceland (P < 0.05). Bayesian analysis with the software STRUCTURE placed 66.9% of the rutabaga accessions into three to four clusters, while the remaining 33.1% constituted admixtures. Three multivariate analyses: principal coordinate analysis (PCoA), the unweighted pair group method with arithmetic mean (UPGMA) and neighbour-joining (NJ) clustering methods grouped the 124 accessions into four to six subgroups.

Conclusion

Overall, the correlation of the accessions with their geographic origin was very low, except for the accessions from Iceland. Thus, Icelandic rutabaga accessions can offer valuable germplasm for crop improvement.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07762-4.

Construction of a SNP Fingerprinting Database and Population Genetic Analysis of Cigar Tobacco Germplasm Resources in China

Cigar tobacco is an important economic crop that is widely grown around the world. In recent years, varietal identification has become a frequent problem in germplasm preservation collections, which causes considerable inconvenience and uncertainty in the cataloging and preservation of cigar germplasm resources, in the selection of parental lines for breeding, and in the promotion and use of high quality varieties. Therefore, the use of DNA fingerprints to achieve rapid and accurate identification of varieties can play an important role in germplasm identification and property rights disputes. In this study, we used genotyping-by-sequencing (GBS) on 113 cigar tobacco accessions to develop SNP markers. After filtering, 580,942 high-quality SNPs were obtained. We used the 580,942 SNPs to perform principal component analysis (PCA), population structure analysis, and neighbor joining (NJ) cluster analysis on the 113 cigar tobacco accessions. The results showed that the accessions were not completely classified based on their geographical origins, and the genetic backgrounds of these cigar resources are complex and diverse. We further selected from these high-quality SNPs to obtained 163 SNP sites, 133 of which were successfully converted into KASP markers. Finally, 47 core KASP markers and 24 candidate core markers were developed. Using the core markers, we performed variety identification and fingerprinting in 216 cigar germplasm accessions. The results of SNP fingerprinting, 2D barcoding, and genetic analysis of cigar tobacco germplasm in this study provide a scientific basis for screening and identifying high-quality cigar tobacco germplasm, mining important genes, and broadening the basis of cigar tobacco genetics and subsequent breeding work at the molecular level.

Assembly and comparison of two closely related Brassica napus genomes

As an increasing number of plant genome sequences become available, it is clear that gene content varies between individuals, and the challenge arises to predict the gene content of a species. However, genome comparison is often confounded by variation in assembly and annotation. Differentiating between true gene absence and variation in assembly or annotation is essential for the accurate identification of conserved and variable genes in a species. Here, we present the de novo assembly of the B. napus cultivar Tapidor and comparison with an improved assembly of the Brassica napus cultivar Darmor-bzh. Both cultivars were annotated using the same method to allow comparison of gene content. We identified genes unique to each cultivar and differentiate these from artefacts due to variation in the assembly and annotation. We demonstrate that using a common annotation pipeline can result in different gene predictions, even for closely related cultivars, and repeat regions which collapse during assembly impact whole genome comparison. After accounting for differences in assembly and annotation, we demonstrate that the genome of Darmor-bzh contains a greater number of genes than the genome of Tapidor. Our results are the first step towards comparison of the true differences between B. napus genomes and highlight the potential sources of error in future production of a B. napus pangenome.

A user guide to the Brassica 60K Illumina Infinium™ SNP genotyping array

The Brassica napus 60K Illumina Infinium™ SNP array has had huge international uptake in the rapeseed community due to the revolutionary speed of acquisition and ease of analysis of this high-throughput genotyping data, particularly when coupled with the newly available reference genome sequence. However, further utilization of this valuable resource can be optimized by better understanding the promises and pitfalls of SNP arrays. We outline how best to analyze Brassica SNP marker array data for diverse applications, including linkage and association mapping, genetic diversity and genomic introgression studies. We present data on which SNPs are locus-specific in winter, semi-winter and spring B. napus germplasm pools, rather than amplifying both an A-genome and a C-genome locus or multiple loci. Common issues that arise when analyzing array data will be discussed, particularly those unique to SNP markers and how to deal with these for practical applications in Brassica breeding applications.

SNP Discovery Using a Pangenome: Has the Single Reference Approach Become Obsolete?

Increasing evidence suggests that a single individual is insufficient to capture the genetic diversity within a species due to gene presence absence variation. In order to understand the extent to which genomic variation occurs in a species, the construction of its pangenome is necessary. The pangenome represents the complete set of genes of a species; it is composed of core genes, which are present in all individuals, and variable genes, which are present only in some individuals. Aside from variations at the gene level, single nucleotide polymorphisms (SNPs) are also an important form of genetic variation. The advent of next-generation sequencing (NGS) coupled with the heritability of SNPs make them ideal markers for genetic analysis of human, animal, and microbial data. SNPs have also been extensively used in crop genetics for association mapping, quantitative trait loci (QTL) analysis, analysis of genetic diversity, and phylogenetic analysis. This review focuses on the use of pangenomes for SNP discovery. It highlights the advantages of using a pangenome rather than a single reference for this purpose. This review also demonstrates how extra information not captured in a single reference alone can be used to provide additional support for linking genotypic data to phenotypic data.

Development of a Genetic Map for Onion (Allium cepa L.) Using Reference-Free Genotyping-by-Sequencing and SNP Assays

Single nucleotide polymorphisms (SNPs) play important roles as molecular markers in plant genomics and breeding studies. Although onion (Allium cepa L.) is an important crop globally, relatively few molecular marker resources have been reported due to its large genome and high heterozygosity. Genotyping-by-sequencing (GBS) offers a greater degree of complexity reduction followed by concurrent SNP discovery and genotyping for species with complex genomes. In this study, GBS was employed for SNP mining in onion, which currently lacks a reference genome. A segregating F₂ population, derived from a cross between 'NW-001' and 'NW-002,' as well as multiple parental lines were used for GBS analysis. A total of 56.15 Gbp of raw sequence data were generated and 1,851,428 SNPs were identified from the de novo assembled contigs. Stringent filtering resulted in 10,091 high-fidelity SNP markers. Robust SNPs that satisfied the segregation ratio criteria and with even distribution in the mapping population were used to construct an onion genetic map. The final map contained eight linkage groups and spanned a genetic length of 1,383 centiMorgans (cM), with an average marker interval of 8.08 cM. These robust SNPs were further analyzed using the high-throughput Fluidigm platform for marker validation. This is the first study in onion to develop genome-wide SNPs using GBS. The resulting SNP markers and developed linkage map will be valuable tools for genetic mapping of important agronomic traits and marker-assisted selection in onion breeding programs.

Oilseed rape: learning about ancient and recent polyploid evolution from a recent crop species

Oilseed rape (Brassica napus) is one of our youngest crop species, arising several times under cultivation in the last few thousand years and completely unknown in the wild. Oilseed rape originated from hybridisation events between progenitor diploid species B. rapa and B. oleracea, both important vegetable species. The diploid progenitors are also ancient polyploids, with remnants of two previous polyploidisation events evident in the triplicated genome structure. This history of polyploid evolution and human agricultural selection makes B. napus an excellent model with which to investigate processes of genomic evolution and selection in polyploid crops. The ease of de novo interspecific hybridisation, responsiveness to tissue culture, and the close relationship of oilseed rape to the model plant Arabidopsis thaliana, coupled with the recent availability of reference genome sequences and suites of molecular cytogenetic and high-throughput genotyping tools, allow detailed dissection of genetic, genomic and phenotypic interactions in this crop. In this review we discuss the past and present uses of B. napus as a model for polyploid speciation and evolution in crop species, along with current and developing analysis tools and resources. We further outline unanswered questions that may now be tractable to investigation.

High-resolution skim genotyping by sequencing reveals the distribution of crossovers and gene conversions in Cicer arietinum and Brassica napus

We characterise the distribution of crossover and non-crossover recombination in Brassica napus and Cicer arietinum using a low-coverage genotyping by sequencing pipeline SkimGBS. The growth of next-generation DNA sequencing technologies has led to a rapid increase in sequence-based genotyping for applications including diversity assessment, genome structure validation and gene-trait association. We have established a skim-based genotyping by sequencing method for crop plants and applied this approach to genotype-segregating populations of Brassica napus and Cicer arietinum. Comparison of progeny genotypes with those of the parental individuals allowed the identification of crossover and non-crossover (gene conversion) events. Our results identify the positions of recombination events with high resolution, permitting the mapping and frequency assessment of recombination in segregating populations.

A bi-filtering method for processing single nucleotide polymorphism array data improves the quality of genetic map and accuracy of quantitative trait locus mapping in doubled haploid populations of polyploid Brassica napus

Background

Single nucleotide polymorphism (SNP) markers have a wide range of applications in crop genetics and genomics. Due to their polyploidy nature, many important crops, such as wheat, cotton and rapeseed contain a large amount of repeat and homoeologous sequences in their genomes, which imposes a huge challenge in high-throughput genotyping with sequencing and/or array technologies. Allotetraploid Brassica napus (AACC, 2n = 4x = 38) comprises of two highly homoeologous sub-genomes derived from its progenitor species B. rapa (AA, 2n = 2x = 20) and B. oleracea (CC, 2n = 2x = 18), and is an ideal species to exploit methods for reducing the interference of extensive inter-homoeologue polymorphisms (mHemi-SNPs and Pseudo-simple SNPs) between closely related sub-genomes.

Results

Based on a recent B. napus 6K SNP array, we developed a bi-filtering procedure to identify unauthentic lines in a DH population, and mHemi-SNPs and Pseudo-simple SNPs in an array data matrix. The procedure utilized both monomorphic and polymorphic SNPs in the DH population and could effectively distinguish the mHemi-SNPs and Pseudo-simple SNPs that resulted from superposition of the signals from multiple SNPs. Compared with conventional procedure for array data processing, the bi-filtering method could minimize the pseudo linkage relationship caused by the mHemi-SNPs and Pseudo-simple SNPs, thus improving the quality of SNP genetic map. Furthermore, the improved genetic map could increase the accuracies of mapping of QTLs as demonstrated by the ability to eliminate non-real QTLs in the mapping population.

Conclusions

The bi-filtering analysis of the SNP array data represents a novel approach to effectively assigning the multi-loci SNP genotypes in polyploid B. napus and may find wide applications to SNP analyses in polyploid crops.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1559-4) contains supplementary material, which is available to authorized users.

Skim-based genotyping by sequencing

Genotyping by sequencing (GBS) is a relatively new method used to determine the differences in the genetic makeup of individuals. Its novelty stems from a combination of two already available methods: genotyping and next-generation sequencing. Depending on the individual study design GBS protocols can take multiple forms, however most share a sequence of core steps that have to be undertaken. These include: sequencing of the DNA from the individuals of interest (usually two parents of a mapping population and their progeny), mapping of the sequencing reads to the reference sequence, SNP calling and filtering, SNP genotyping and imputation, followed by haplotype identification and downstream analysis. GBS has a range of applications from general marker discovery, haplotype identification, and recombination characterization to quantitative trait locus (QTL) analysis, genome-wide association studies (GWAS), and genomic selection (GS). It has already been applied to a range of plant species including: rice, maize, artichoke, and Arabidopsis thaliana. It is a promising approach which is likely to provide new and important insights into plant biology.

Bioinformatics: identification of markers from next-generation sequence data

With the advent of sequencing technology, next-generation sequencing (NGS) technology has dramatically revolutionized plant genomics. NGS technology combined with new software tools enables the discovery, validation, and assessment of genetic markers on a large scale. Among different markers systems, simple sequence repeats (SSRs) and Single nucleotide polymorphisms (SNPs) are the markers of choice for genetics and plant breeding. SSR markers have been a choice for large-scale characterization of germplasm collections, construction of genetic maps, and QTL identification. Similarly, SNPs are the most abundant genetic variations with higher frequencies throughout the genome of plant species. This chapter discusses various tools available for genome assembly and widely focuses on SSR and SNP marker discovery.

Molecular marker applications in plants

Individuals within a population of a sexually reproducing species will have some degree of heritable genomic variation caused by mutations, insertion/deletions (INDELS), inversions, duplications, and translocations. Such variation can be detected and screened using molecular, or genetic, markers. By definition, molecular markers are genetic loci that can be easily tracked and quantified in a population and may be associated with a particular gene or trait of interest. This chapter will review the current major applications of molecular markers in plants.

Molecular marker databases

The detection and analysis of genetic variation plays an important role in plant breeding and this role is increasing with the continued development of genome sequencing technologies. Molecular genetic markers are important tools to characterize genetic variation and assist with genomic breeding. Processing and storing the growing abundance of molecular marker data being produced requires the development of specific bioinformatics tools and advanced databases. Molecular marker databases range from species specific through to organism wide and often host a variety of additional related genetic, genomic, or phenotypic information. In this chapter, we will present some of the features of plant molecular genetic marker databases, highlight the various types of marker resources, and predict the potential future direction of crop marker databases.

Challenges of genotyping polyploid species

Most plant species are known to be either ancient or recent polyploids, containing more than one genome as a result of past interspecific hybridization events (allopolyploidy) and/or genome doubling (autopolyploidy). Genotyping in polyploid species offers a set of unique challenges. Most molecular marker methodologies are made more complex by polyploidy, as multilocus alleles are generally produced when a single locus is targeted. Genotyping by sequencing is also more challenging in polyploids, with problematic assemblies of duplicated regions and difficulties in distinguishing between inter- and intragenomic polymorphisms. Strategies for identifying and overcoming the challenges of polyploidy in plant genotyping are proposed.

Advances in plant genotyping: where the future will take us

Genetic diversity between individuals can be tracked and monitored using a range of molecular markers. These markers can detect variation ranging in scale from a single base pair up to duplications and translocations of entire chromosomal regions. The genotyping of individuals allows the detection of this variation and it has been successfully applied in plant science for many years. The increasing amounts of sequence data able to be generated using next-generation sequencing (NGS) technologies have produced a vast expansion in the rate of discovery of polymorphisms, with single nucleotide polymorphisms (SNPs) predominating as the marker of choice. This increase in polymorphic marker resources through efficient discovery, coupled with the utility of SNPs, has enabled the shift to high-throughput genotyping assays and these methods are reviewed and discussed here, alongside the recent innovations allowing increased throughput.

A high-throughput SNP array in the amphidiploid species Brassica napus shows diversity in resistance genes

Single-nucleotide polymorphisms (SNPs)are molecular markers based on nucleotide variation and can be used for genotyping assays across populations and to track genomic inheritance. SNPs offer a comprehensive genotyping alternative to whole-genome sequencing for both agricultural and research purposes including molecular breeding and diagnostics, genome evolution and genetic diversity analyses, genetic mapping, and trait association studies. Here genomic SNPs were discovered between four cultivars of the important amphidiploid oilseed species Brassica napus and used to develop a B. napus Infinium™ array containing 5,306 SNPs randomly dispersed across the genome. Assay success was high, with >94 % of these producing a reproducible, polymorphic genotype in the 1,070 samples screened. Although the assay was designed to B. napus, successful SNP amplification was achieved in the B. napus progenitor species, Brassica rapa and Brassica oleracea, and to a lesser extent in the related species Brassica nigra. Phylogenetic analysis was consistent with the expected relationships between B. napus individuals. This study presents an efficient custom SNP assay development pipeline in the complex polyploid Brassica genome and demonstrates the utility of the array for high-throughput genotyping in a number of related Brassica species. It also demonstrates the utility of this assay in genotyping resistance genes on chromosome A7, which segregate amongst the 1,070 samples.

Comparative genomics of Brassicaceae crops

The family Brassicaceae is one of the major groups of the plant kingdom and comprises diverse species of great economic, agronomic and scientific importance, including the model plant Arabidopsis. The sequencing of the Arabidopsis genome has revolutionized our knowledge in the field of plant biology and provides a foundation in genomics and comparative biology. Genomic resources have been utilized in Brassica for diversity analyses, construction of genetic maps and identification of agronomic traits. In Brassicaceae, comparative sequence analysis across the species has been utilized to understand genome structure, evolution and the detection of conserved genomic segments. In this review, we focus on the progress made in genetic resource development, genome sequencing and comparative mapping in Brassica and related species. The utilization of genomic resources and next-generation sequencing approaches in improvement of Brassica crops is also discussed.

Accessing complex crop genomes with next-generation sequencing

Many important crop species have genomes originating from ancestral or recent polyploidisation events. Multiple homoeologous gene copies, chromosomal rearrangements and amplification of repetitive DNA within large and complex crop genomes can considerably complicate genome analysis and gene discovery by conventional, forward genetics approaches. On the other hand, ongoing technological advances in molecular genetics and genomics today offer unprecedented opportunities to analyse and access even more recalcitrant genomes. In this review, we describe next-generation sequencing and data analysis techniques that vastly improve our ability to dissect and mine genomes for causal genes underlying key traits and allelic variation of interest to breeders. We focus primarily on wheat and oilseed rape, two leading examples of major polyploid crop genomes whose size or complexity present different, significant challenges. In both cases, the latest DNA sequencing technologies, applied using quite different approaches, have enabled considerable progress towards unravelling the respective genomes. Our ability to discover the extent and distribution of genetic diversity in crop gene pools, and its relationship to yield and quality-related traits, is swiftly gathering momentum as DNA sequencing and the bioinformatic tools to deal with growing quantities of genomic data continue to develop. In the coming decade, genomic and transcriptomic sequencing, discovery and high-throughput screening of single nucleotide polymorphisms, presence-absence variations and other structural chromosomal variants in diverse germplasm collections will give detailed insight into the origins, domestication and available trait-relevant variation of polyploid crops, in the process facilitating novel approaches and possibilities for genomics-assisted breeding.