Using Next Generation Sequencing for Multiplexed Trait-Linked Markers in Wheat

Genetic architecture of adult-plant resistance to stripe rust in bread wheat (Triticum aestivum L.) association panel

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a severe disease in wheat worldwide, including Ethiopia, causing up to 100% wheat yield loss in the worst season. The use of resistant cultivars is considered to be the most effective and durable management technique for controlling the disease. Therefore, the present study targeted the genetic architecture of adult plant resistance to yellow rust in 178 wheat association panels. The panel was phenotyped for yellow rust adult-plant resistance at three locations. Phonological, yield, yield-related, and agro-morphological traits were recorded. The association panel was fingerprinted using the genotyping-by-sequencing (GBS) platform, and a total of 6,788 polymorphic single nucleotide polymorphisms (SNPs) were used for genome-wide association analysis to identify effective yellow rust resistance genes. The marker-trait association analysis was conducted using the Genome Association and Prediction Integrated Tool (GAPIT). The broad-sense heritability for the considered traits ranged from 74.52% to 88.64%, implying the presence of promising yellow rust resistance alleles in the association panel that could be deployed to improve wheat resistance to the disease. The overall linkage disequilibrium (LD) declined within an average physical distance of 31.44 Mbp at r2 = 0.2. Marker-trait association (MTA) analysis identified 148 loci significantly (p = 0.001) associated with yellow rust adult-plant resistance. Most of the detected resistance quantitative trait loci (QTLs) were located on the same chromosomes as previously reported QTLs for yellow rust resistance and mapped on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 3D, 4A, 4B, 4D, 5A, 5B, 6A, 6B, 7A, and 7D. However, 12 of the discovered MTAs were not previously documented in the wheat literature, suggesting that they could represent novel loci for stripe rust resistance. Zooming into the QTL regions in IWGSC RefSeq Annotation v1 identified crucial disease resistance-associated genes that are key in plants' defense mechanisms against pathogen infections. The detected QTLs will be helpful for marker-assisted breeding of wheat to increase resistance to stripe rust. Generally, the present study identified putative QTLs for field resistance to yellow rust and some important agronomic traits. Most of the discovered QTLs have been reported previously, indicating the potential to improve wheat resistance to yellow rust by deploying the QTLs discovered by marker-assisted selection.

Genotyping by Multiplexed Sequencing (GMS) Using SNP Markers

SNP-based genotyping has become the most effective approach to generate target-specific data for use in genetic studies. In this chapter, we will describe a high-throughput genotyping method that multiplexes hundreds to thousands of SNP markers in a two-step PCR protocol that can be customized to fit the specific needs of a study.

Identification of Secreted Protein Gene-Based SNP Markers Associated with Virulence Phenotypes of Puccinia striiformis f. sp. tritici, the Wheat Stripe Rust Pathogen

Stripe rust caused by Puccinia striiformis f. sp. tritici (Pst) is a destructive disease that occurs throughout the major wheat-growing regions of the world. This pathogen is highly variable due to the capacity of virulent races to undergo rapid changes in order to circumvent resistance in wheat cultivars and genotypes and to adapt to different environments. Intensive efforts have been made to study the genetics of wheat resistance to this disease; however, no known avirulence genes have been molecularly identified in Pst so far. To identify molecular markers for avirulence genes, a Pst panel of 157 selected isolates representing 126 races with diverse virulence spectra was genotyped using 209 secreted protein gene-based single nucleotide polymorphism (SP-SNP) markers via association analysis. Nineteen SP-SNP markers were identified for significant associations with 12 avirulence genes: AvYr1, AvYr6, AvYr7, AvYr9, AvYr10, AvYr24, AvYr27, AvYr32, AvYr43, AvYr44, AvYrSP, and AvYr76. Some SP-SNPs were associated with two or more avirulence genes. These results further confirmed that association analysis in combination with SP-SNP markers is a powerful tool for identifying markers for avirulence genes. This study provides genomic resources for further studies on the cloning of avirulence genes, understanding the mechanisms of host–pathogen interactions, and developing functional markers for tagging specific virulence genes and race groups.

Whole-exome sequencing of selected bread wheat recombinant inbred lines as a useful resource for allele mining and bulked segregant analysis

Although wheat (Triticum aestivum L.) is the main staple crop in the world and a major source of carbohydrates and proteins, functional genomics and allele mining are still big challenges. Given the advances in next-generation sequencing (NGS) technologies, the identification of causal variants associated with a target phenotype has become feasible. For these reasons, here, by combining sequence capture and target-enrichment methods with high-throughput NGS re-sequencing, we were able to scan at exome-wide level 46 randomly selected bread wheat individuals from a recombinant inbred line population and to identify and classify a large number of single nucleotide polymorphisms (SNPs). For technical validation of results, eight randomly selected SNPs were converted into Kompetitive Allele-Specific PCR (KASP) markers. This resource was established as an accessible and reusable molecular toolkit for allele data mining. The dataset we are making available could be exploited for novel studies on bread wheat genetics and as a foundation for starting breeding programs aimed at improving different key agronomic traits.

Molecular Fingerprinting and Hybridity Authentication in Cowpea Using Single Nucleotide Polymorphism Based Kompetitive Allele-Specific PCR Assay

Optimization of a breeding program for increased genetic gain requires quality assurance (QA) and quality control (QC) at key phases of the breeding process. One vital phase in a breeding program that requires QC and QA is the choice of parents and successful hybridizations to combine parental attributes and create variations. The objective of this study was to determine parental diversity and confirm hybridity of cowpea F₁ progenies using KASP (Kompetitive Allele-Specific PCR)-based single nucleotide polymorphism (SNP) markers. A total of 1,436 F₁ plants were derived from crossing 220 cowpea breeding lines and landraces to 2 elite sister lines IT99K-573-1-1 and IT99K-573-2-1 as male parents, constituting 225 cross combinations. The progenies and the parents were genotyped with 17 QC SNP markers via high-throughput KASP genotyping assay. The QC markers differentiated the parents with mean efficiency of 37.90% and a range of 3.4-82.8%, revealing unique fingerprints of the parents. Neighbor-Joining cladogram divided the 222 parents into 3 clusters. Genetic distances between parents ranged from 0 to 3.74 with a mean of 2.41. Principal component analysis (PCA) depicted a considerable overlap between parents and F₁ progenies with more scatters among parents than the F₁s. The differentiation among parents and F₁s was best contributed to by 82% of the markers. As expected, parents and F₁s showed a significant contrast in proportion of heterozygous individuals, with mean values of 0.02 and 0.32, respectively. KASP markers detected true hybridity with 100% success rate in 72% of the populations. Overall, 79% of the putative F₁ plants were true hybrids, 14% were selfed plants, and 7% were undetermined due to missing data and lack of marker polymorphism between parents. The study demonstrated an effective application of KASP-based SNP assay in fingerprinting, confirmation of hybridity, and early detection of false F₁ plants. The results further uncovered the need to deploy markers as a QC step in a breeding program.

Identification of Stripe Rust Resistance Loci in U.S. Spring Wheat Cultivars and Breeding Lines Using Genome-Wide Association Mapping and Yr Gene Markers

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), poses a major threat to wheat production worldwide, especially in the United States. To identify loci for effective stripe rust resistance in U.S. wheat, a genome-wide association study (GWAS) was conducted using a panel of 616 spring wheat cultivars and breeding lines. The accessions in this panel were phenotyped for stripe rust response in the greenhouse at seedling stage with five predominant and highly virulent races of Pst and in different field environments at adult-plant stage in 2017 and 2018. In total, 2,029 single-nucleotide polymorphism markers that cover the whole genome were generated with genotyping by multiplexed sequencing and used in GWAS. In addition, 23 markers of previously reported resistance genes or quantitative trait loci (QTLs) were used to genotype the population. This spring panel was grouped into three subpopulations based on principal component analysis. A total of 37 genes or QTLs including 10 potentially new QTLs for resistance to stripe rust were detected by GWAS and linked marker tests. The frequencies of the resistance genes or QTLs in various nurseries were determined, indicating different intensities of these genes or QTLs used in breeding programs of different regions. These resistance loci and the information on their markers, effectiveness, and distributions should be useful for improving stripe rust resistance in wheat cultivars.

Evolution in crop improvement approaches and future prospects of molecular markers to CRISPR/Cas9 system

The advent of genetic selection and genome modification method assure about a real novel reformation in biotechnology and genetic engineering. With the extensive capabilities of molecular markers of them being stable, cost-effective and easy to use, they ultimately become a potent tool for variety of applications such a gene targeting, selection, editing, functional genomics; mainly for the improvisation of commercially important crops. Three main benefits of molecular marker in the field of agriculture and crop improvement programmes first, reduction of the duration of breeding programmes, second, they allow creation of new genetic variation and genetic diversity of plants and third most promising benefit is help in production of engineered plant for disease resistance, or resistance from pathogen and herbicides. This review is anticipated to present an outline how the techniques have been evolved from the simple conventional applications of DNA based molecular markers to highly throughput CRISPR technology and geared the crop yield. Techniques like using Zinc Finger Nucleases (ZFNs), Transcription Activator-Like Effector Nucleases (TALENs) and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR/Cas9) systems have revolutionised in the field of genome editing. These have been promptly accepted in both the research and commercial industry. On the whole, the widespread use of molecular markers with their types, their appliance in plant breeding along with the advances in genetic selection and genome editing together being a novel strategy to boost crop yield has been reviewed.

Genotyping by multiplexed sequencing (GMS): A customizable platform for genomic selection

As genotyping technologies continue to evolve, so have their throughput and multiplexing capabilities. In this study, we demonstrate a new PCR-based genotyping technology that multiplexes thousands of single nucleotide polymorphism (SNP) markers with high-throughput capabilities in a simple protocol using a two-step PCR approach. The bioinformatic pipeline is user friendly and yields results that are intuitive to interpret. This method was tested on two recombinant inbred line (RIL) populations that had previous genotyping data from the Illumina Infinium assay for Triticum aestivum L. and the two data sets were found to be 100% in agreement. The genotyping by multiplexed sequencing (GMS) protocol multiplexes 1,656 wheat SNP markers, 207 syntenic barley SNP markers, and 49 known informative markers, which generate a possible 2,433 data points (including homoeoalleles and paralogs). This genotyping approach has the flexibility of being sequenced on either the Ion Torrent or Illumina next generation sequencing (NGS) platforms. Products are the result of direct sequencing and are therefore more reliable than scatter plot analysis which is the output of other genotyping methods such as the Illumina Infinium assay, komeptitive allele specific PCR and other like technologies.

Multifamily QTL analysis and comprehensive design of genotypes for high-quality soft wheat

Milling properties and flour color are essential selection criteria in soft wheat breeding. However, high phenotypic screening costs restrict selection to relatively few breeding lines in late generations. To achieve marker-based selection of these traits in early generations, we performed genetic dissection of quality traits using three doubled haploid populations that shared the high-quality soft wheat variety Kitahonami as the paternal parent. An amplicon sequencing approach allowed effective construction of well-saturated linkage maps of the populations. Marker-based heritability estimates revealed that target quality traits had relatively high values, indicating the possibility of selection in early generations. Taking advantage of Chinese Spring reference sequences, joint linkage maps of the three populations were generated. Based on the maps, multifamily quantitative trait locus (QTL) analysis revealed a total of 86 QTLs for ten traits investigated. In terms of target quality traits, 12 QTLs were detected for flour yield, and 12 were detected for flour redness (a* value). Among these QTLs, six for flour yield and nine for flour a* were segregating in more than two populations. Some relationships among traits were explained by QTL collocations on chromosomes, especially group 7 chromosomes. Ten different ideotypes with various combinations of favorable alleles for the flour yield and flour a* QTLs were generated. Phenotypes of derivatives from these ideotypes were predicted to design ideal genotypes for high-quality wheat. Simulations revealed the possibility of breeding varieties with better quality than Kitahonami.

Amand P, Le HQ, Su Z, Bai G. Multiplex restriction amplicon sequencing: a novel next-generation sequencing-based marker platform for high-throughput genotyping

To enable rapid selection of traits in marker-assisted breeding, markers must be technically simple, low-cost, high-throughput and randomly distributed in a genome. We developed such a technology, designated as Multiplex Restriction Amplicon Sequencing (MRASeq), which reduces genome complexity by polymerase chain reaction (PCR) amplification of amplicons flanked by restriction sites. The first PCR primers contain restriction site sequences at 3'-ends, preceded by 6-10 bases of specific or degenerate nucleotide sequences and then by a unique M13-tail sequence which serves as a binding site for a second PCR that adds sequencing primers and barcodes to allow sample multiplexing for sequencing. The sequences of restriction sites and adjacent nucleotides can be altered to suit different species. Physical mapping of MRASeq SNPs from a biparental population of allohexaploid wheat (Triticum aestivum L.) showed a random distribution of SNPs across the genome. MRASeq generated thousands of SNPs from a wheat biparental population and natural populations of wheat and barley (Hordeum vulgare L.). This novel, next-generation sequencing-based genotyping platform can be used for linkage mapping to screen quantitative trait loci (QTL), background selection in breeding and many other genetics and breeding applications of various species.

Imputation accuracy of wheat genotyping-by-sequencing (GBS) data using barley and wheat genome references

Genotyping-by-sequencing (GBS) provides high SNP coverage and has recently emerged as a popular technology for genetic and breeding applications in bread wheat (Triticum aestivum L.) and many other plant species. Although GBS can discover millions of SNPs, a high rate of missing data is a major concern for many applications. Accurate imputation of those missing data can significantly improve the utility of GBS data. This study compared imputation accuracies among four genome references including three wheat references (Chinese Spring survey sequence, W7984, and IWGSC RefSeq v1.0) and one barley reference genome by comparing imputed data derived from low-depth sequencing to actual data from high-depth sequencing. After imputation, the average number of imputed data points was the highest in the B genome (~48.99%). The D genome had the lowest imputed data points (~15.02%) but the highest imputation accuracy. Among the four reference genomes, IWGSC RefSeq v1.0 reference provided the most imputed data points, but the lowest imputation accuracy for the SNPs with < 10% minor allele frequency (MAF). The W7984 reference, however, provided the highest imputation accuracy for the SNPs with < 10% MAF.

Development and validation of diagnostic markers for Fhb1 region, a major QTL for Fusarium head blight resistance in wheat

Functional markers were developed based on the critical sequence deletion of TaHRC in the Fhb1 region and validated to be diagnostic in a worldwide wheat collection. Wheat Fusarium head blight (FHB) is a devastating disease in wheat and barley worldwide. Growing FHB-resistant cultivars is an effective strategy to minimize FHB damage in wheat production. Fhb1 is a quantitative trait locus for FHB resistance with the largest effect on disease severity identified to date. With this study, we developed diagnostic DNA markers for Fhb1 by comparing the genomic sequences in Fhb1 region between near-isogenic lines contrasting in Fhb1 alleles and phenotypic effects of the markers. Two markers were developed based on a deletion mutation in an gene encoding a putative histidine-rich calcium-binding protein (TaHRC) and validated in different types of populations. Haplotype or sequence analyses of the two markers in the three sets of diversity panels demonstrated that they are diagnostic for Fhb1, and superior to all previously used markers in selection accuracy. They also have the advantages of low cost, easy assay, and are suitable for breeding programs with either high- or low-throughput marker laboratories.

An efficient approach for the development of genome-specific markers in allohexaploid wheat (Triticum aestivum L.) and its application in the construction of high-density linkage maps of the D genome

In common wheat, the development of genotyping platforms has been hampered by the large size of the genome, its highly repetitive elements and its allohexaploid nature. However, recent advances in sequencing technology provide opportunities to resolve these difficulties. Using next-generation sequencing and gene-targeting sequence capture, 12,551 nucleotide polymorphisms were detected in the common wheat varieties 'Hatsumochi' and 'Kitahonami' and were assigned to chromosome arms using International Wheat Genome Sequencing Consortium survey sequences. Because the number of markers for D genome chromosomes in commercially available wheat single nucleotide polymorphism arrays is insufficient, we developed markers using a genome-specific amplicon sequencing strategy. Approximately 80% of the designed primers successfully amplified D genome-specific products, suggesting that by concentrating on a specific subgenome, we were able to design successful markers as efficiently as could be done in a diploid species. The newly developed markers were uniformly distributed across the D genome and greatly extended the total coverage. Polymorphisms were surveyed in six varieties, and 31,542 polymorphic sites and 5,986 potential marker sites were detected in the D genome. The marker development and genotyping strategies are cost effective, robust and flexible and may enhance multi-sample studies in the post-genomic era in wheat.

Mapping of Quantitative Trait Loci for Leaf Rust Resistance in the Wheat Population Ning7840 × Clark

Leaf rust, caused by Puccinia triticina, is an important fungal disease of wheat (Triticum aestivum L.) and causes significant yield losses worldwide. To determine quantitative trait loci (QTLs) responsible for leaf rust resistance, a recombinant inbred line (RIL) population developed from a cross of Ning7840 × Clark was evaluated for leaf rust severity, and was genotyped for single nucleotide polymorphisms (SNPs) using 9K Illumina chips, and with simple sequence repeat (SSR) markers. Two major QTLs on chromosome arms 7DS and 3BS, and two minor QTLs on chromosomes 5AS and 6AS showed a significant effect on leaf rust severity. The 7DS QTL from Ning7840 and the 3BS QTL from Clark explained, respectively, about 35% and 18% of the phenotypic variation for leaf rust resistance. The QTL on 7DS was confirmed to be Lr34. The QTL on 3BS, QLr.hwwg-3B.1, was associated with adult plant resistance and was provisionally identified as Lr74. QLr.hwwg-5AS and QLr.hwwg-6AS from Ning7840 and Clark, respectively, may correspond to previously described QTLs. Lr34, QLr.hwwg-3BS.1, and QLr.hwwg-6AS had an additive effect on leaf rust severity. RILs with all three favorable alleles showed the highest resistance to leaf rust and the RILs with none of them showed the lowest resistance.

Crop Breeding Chips and Genotyping Platforms: Progress, Challenges, and Perspectives

There is a rapidly rising trend in the development and application of molecular marker assays for gene mapping and discovery in field crops and trees. Thus far, more than 50 SNP arrays and 15 different types of genotyping-by-sequencing (GBS) platforms have been developed in over 25 crop species and perennial trees. However, much less effort has been made on developing ultra-high-throughput and cost-effective genotyping platforms for applied breeding programs. In this review, we discuss the scientific bottlenecks in existing SNP arrays and GBS technologies and the strategies to develop targeted platforms for crop molecular breeding. We propose that future practical breeding platforms should adopt automated genotyping technologies, either array or sequencing based, target functional polymorphisms underpinning economic traits, and provide desirable prediction accuracy for quantitative traits, with universal applications under wide genetic backgrounds in crops. The development of such platforms faces serious challenges at both the technological level due to cost ineffectiveness, and the knowledge level due to large genotype-phenotype gaps in crop plants. It is expected that such genotyping platforms will be achieved in the next ten years in major crops in consideration of (a) rapid development in gene discovery of important traits, (b) deepened understanding of quantitative traits through new analytical models and population designs, (c) integration of multi-layer -omics data leading to identification of genes and pathways responsible for important breeding traits, and (d) improvement in cost effectiveness of large-scale genotyping. Crop breeding chips and genotyping platforms will provide unprecedented opportunities to accelerate the development of cultivars with desired yield potential, quality, and enhanced adaptation to mitigate the effects of climate change.

Identification of Single Nucleotide Polymorphisms Associated with Brown Rust Resistance, α-Amylase Activity and Pre-harvest Sprouting in Rye (Secale cereale L.)

Rye is a crop with relatively high resistance to biotic and abiotic stresses. However, the resistance to brown rust (Puccinia recondita f. sp. secalis) and pre-harvest sprouting are still not satisfactory. High α-amylase activity is also among the main disadvantages of this species. Therefore, effective tools, e.g. molecular markers, allowing precise and environmentally independent selection of favourable alleles are desirable. In the present study, two kinds of association mapping-genome-wide association mapping (GWAM) based on sequences of DArTSeq markers and candidate gene association mapping (CGAM) based on sequences of ScBx genes-were chosen for development of molecular markers fulfilling these criteria. The analysed population consisted of 149 diverse inbred lines (DILs). Altogether, 67 and 11 single nucleotide polymorphisms (SNPs) identified in, respectively, GWAM and CGAM, were significantly associated with the investigated traits: 2 SNPs with resistance to brown rust, 71 SNPs with resistance to pre-harvest sprouting and 5 SNPs with α-amylase activity in the grain. Fifteen SNPs were stable across all environments. The highest number (13) of environmentally stable SNPs was associated with pre-harvest sprouting resistance. The test employing the Kompetitive Allele Specific PCR method proved the versatility of four markers identified in both GWAM and CGAM.

Resequencing of Capsicum annuum parental lines (YCM334 and Taean) for the genetic analysis of bacterial wilt resistance

BACKGROUND

Bacterial wilt (BW) is a widespread plant disease that affects a broad range of dicot and monocot hosts and is particularly harmful for solanaceous plants, such as pepper, tomato, and eggplant. The pathogen responsible for BW is the soil-borne bacterium, Ralstonia solanacearum, which can adapt to diverse temperature conditions and is found in climates ranging from tropical to temperate. Resistance to BW has been detected in some pepper plant lines; however, the genomic loci and alleles that mediate this are poorly studied in this species.

RESULTS

We resequenced the pepper cultivars YCM344 and Taean, which are parental recombinant inbred lines (RIL) that display differential resistance phenotypes against BW, with YCM344 being highly resistant to infection with this pathogen. We identified novel single nucleotide polymorphisms (SNPs) and insertions/deletions (Indels) that are only present in both parental lines, as compared to the reference genome and further determined variations that distinguish these two cultivars from one another. We then identified potentially informative SNPs that were found in genes related to those that have been previously associated with disease resistance, such as the R genes and stress response genes. Moreover, via comparative analysis, we identified SNPs located in genomic regions that have homology to known resistance genes in the tomato genomes.

CONCLUSIONS

From our SNP profiling in both parental lines, we could identify SNPs that are potentially responsible for BW resistance, and practically, these may be used as markers for assisted breeding schemes using these populations. We predict that our analyses will be valuable for both better understanding the YCM334/Taean-derived populations, as well as for enhancing our knowledge of critical SNPs present in the pepper genome.