Bridging the genotyping gap: using genotyping by sequencing (GBS) to add high-density SNP markers and new value to traditional bi-parental mapping and breeding populations

Tools for Genetic Studies in Experimental Populations of Polyploids

Polyploid organisms carry more than two copies of each chromosome, a condition rarely tolerated in animals but which occurs relatively frequently in the plant kingdom. One of the principal challenges faced by polyploid organisms is to evolve stable meiotic mechanisms to faithfully transmit genetic information to the next generation upon which the study of inheritance is based. In this review we look at the tools available to the research community to better understand polyploid inheritance, many of which have only recently been developed. Most of these tools are intended for experimental populations (rather than natural populations), facilitating genomics-assisted crop improvement and plant breeding. This is hardly surprising given that a large proportion of domesticated plant species are polyploid. We focus on three main areas: (1) polyploid genotyping; (2) genetic and physical mapping; and (3) quantitative trait analysis and genomic selection. We also briefly review some miscellaneous topics such as the mode of inheritance and the availability of polyploid simulation software. The current polyploid analytic toolbox includes software for assigning marker genotypes (and in particular, estimating the dosage of marker alleles in the heterozygous condition), establishing chromosome-scale linkage phase among marker alleles, constructing (short-range) haplotypes, generating linkage maps, performing genome-wide association studies (GWAS) and quantitative trait locus (QTL) analyses, and simulating polyploid populations. These tools can also help elucidate the mode of inheritance (disomic, polysomic or a mixture of both as in segmental allopolyploids) or reveal whether double reduction and multivalent chromosomal pairing occur. An increasing number of polyploids (or associated diploids) are being sequenced, leading to publicly available reference genome assemblies. Much work remains in order to keep pace with developments in genomic technologies. However, such technologies also offer the promise of understanding polyploid genomes at a level which hitherto has remained elusive.

Deciphering genetic factors that determine melon fruit-quality traits using RNA-Seq-based high-resolution QTL and eQTL mapping

Combined quantitative trait loci (QTL) and expression-QTL (eQTL) mapping analysis was performed to identify genetic factors affecting melon (Cucumis melo) fruit quality, by linking genotypic, metabolic and transcriptomic data from a melon recombinant inbred line (RIL) population. RNA sequencing (RNA-Seq) of fruit from 96 RILs yielded a highly saturated collection of > 58 000 single-nucleotide polymorphisms, identifying 6636 recombination events that separated the genome into 3663 genomic bins. Bin-based QTL analysis of 79 RILs and 129 fruit-quality traits affecting taste, aroma and color resulted in the mapping of 241 QTL. Thiol acyltransferase (CmThAT1) gene was identified within the QTL interval of its product, S-methyl-thioacetate, a key component of melon fruit aroma. Metabolic activity of CmThAT1-encoded protein was validated in bacteria and in vitro. QTL analysis of flesh color intensity identified a candidate white-flesh gene (CmPPR1), one of two major loci determining fruit flesh color in melon. CmPPR1 encodes a member of the pentatricopeptide protein family, involved in processing of RNA in plastids, where carotenoid and chlorophyll pigments accumulate. Network analysis of > 12 000 eQTL mapped for > 8000 differentially expressed fruit genes supported the role of CmPPR1 in determining the expression level of plastid targeted genes. We highlight the potential of RNA-Seq-based QTL analysis of small to moderate size, advanced RIL populations for precise marker-assisted breeding and gene discovery. We provide the following resources: a RIL population genotyped with a unique set of SNP markers, confined genomic segments that harbor QTL governing 129 traits and a saturated set of melon eQTLs.

Accounting for Errors in Low Coverage High-Throughput Sequencing Data When Constructing Genetic Maps Using Biparental Outcrossed Populations

Next-generation sequencing is an efficient method that allows for substantially more markers than previous technologies, providing opportunities for building high-density genetic linkage maps, which facilitate the development of nonmodel species' genomic assemblies and the investigation of their genes. However, constructing genetic maps using data generated via high-throughput sequencing technology (e.g., genotyping-by-sequencing) is complicated by the presence of sequencing errors and genotyping errors resulting from missing parental alleles due to low sequencing depth. If unaccounted for, these errors lead to inflated genetic maps. In addition, map construction in many species is performed using full-sibling family populations derived from the outcrossing of two individuals, where unknown parental phase and varying segregation types further complicate construction. We present a new methodology for modeling low coverage sequencing data in the construction of genetic linkage maps using full-sibling populations of diploid species, implemented in a package called GUSMap. Our model is based on the Lander-Green hidden Markov model but extended to account for errors present in sequencing data. We were able to obtain accurate estimates of the recombination fractions and overall map distance using GUSMap, while most existing mapping packages produced inflated genetic maps in the presence of errors. Our results demonstrate the feasibility of using low coverage sequencing data to produce genetic maps without requiring extensive filtering of potentially erroneous genotypes, provided that the associated errors are correctly accounted for in the model.

QTL Mapping of Fiber Quality and Yield-Related Traits in an Intra-Specific Upland Cotton Using Genotype by Sequencing (GBS)

Fiber quality and yield improvement are crucial for cotton domestication and breeding. With the transformation in spinning techniques and multiplicity needs, the development of cotton fiber quality and yield is of great importance. A genetic map of 5178 Single Nucleotide Polymorphism (SNP) markers were generated using 277 F2:3 population, from an intra-specific cross between two upland cotton accessions, CCRI35 a high fiber quality as female and Nan Dan Ba Di Da Hua (NH), with good yield properties as male parent. The map spanned 4768.098 cM with an average distance of 0.92 cM. A total of 110 Quantitative Traits Loci (QTLs) were identified for 11 traits, but only 30 QTLs were consistent in at least two environments. The highest percentage of phenotypic variance explained by a single QTL was 15.45%. Two major cluster regions were found, cluster 1 (chromosome17-D03) and cluster 2 (chromosome26-D12). Five candidate genes were identified in the two QTL cluster regions. Based on GO functional annotation, all the genes were highly correlated with fiber development, with functions such as protein kinase and phosphorylation. The five genes were associated with various fiber traits as follows: Gh_D03G0889 linked to qFM-D03_cb, Gh_D12G0093, Gh_D12G0410, Gh_D12G0435 associated with qFS-D12_cb and Gh_D12G0969 linked to qFY-D12_cb. Further structural annotation and fine mapping is needed to determine the specific role played by the five identified genes in fiber quality and yield related pathway.

Developing genome-wide SNPs and constructing an ultrahigh-density linkage map in oil palm

Oil palm (Elaeis guineensis Jacq.) is the leading oil-producing crops and the most important edible oil resource worldwide. DNA markers and genetic linkage maps are essential resources for marker-assisted selection to accelerate genetic improvement. We conducted RAD-seq on an Illumina NextSeq500 to discover genome-wide SNPs, and used the SNPs to construct a linkage map for an oil palm (Tenera) population derived from a cross between a Deli Dura and an AVROS Pisifera. The RAD-seq produced 1,076 million single-end reads across the breeding population containing 155 trees. Mining this dataset detected 510,251 loci. After filtering out loci with low accuracy and more than 20% missing data, 11,394 SNPs were retained. Using these SNPs, in combination with 188 anchor SNPs and 123 microsatellites, we constructed a linkage map containing 10,023 markers covering 16 chromosomes. The map length is 2,938.2 cM with an average marker space of 0.29 cM. The large number of SNPs will supply ample choices of DNA markers in analysing the genetic diversity, population structure and evolution of oil palm. This high-density linkage map will contribute to mapping quantitative trait loci (QTL) for important traits, thus accelerating oil palm genetic improvement.

Revolution in Genotyping Platforms for Crop Improvement

In the past decade, the application of high-throughput sequencing to crop genotyping has given rise to novel platforms capable of genotyping tens of thousands of genome-wide DNA markers. Coupled with the decreasing costs of sequencing, this rapid increase in markers allows accelerated and highly accurate genotyping of entire crop populations and diversity sets using single nucleotide polymorphisms (SNPs). These revolutionary advances accelerate crop improvement by facilitating a more precise connection of phenotype to genotype through association studies, linkage mapping and diversity analysis. The platforms driving the advances in genotyping are array technologies and genotyping by sequencing (GBS) methods, which include both low-coverage whole genome resequencing (skim sequencing) and reduced representation sequencing (RRS) approaches. Here, we outline and compare these genotyping platforms and provide a perspective on the promising future of crop genotyping. While SNP arrays provide high quality, simple handling, and unchallenging analysis, the lower cost of RRS and the greater data volume produced by skim sequencing suggest that use of GBS will become more prevalent in crop genomics as sequencing costs decrease and data analysis becomes more streamlined. Graphical Abstract.

Diversity in Grain Amaranths and Relatives Distinguished by Genotyping by Sequencing (GBS)

The genotyping by sequencing (GBS) method has become a molecular marker technology of choice for many crop plants because of its simultaneous discovery and evaluation of a large number of single nucleotide polymorphisms (SNPs) and utility for germplasm characterization. Genome representation and complexity reduction are the basis for GBS fingerprinting and can vary by species based on genome size and other sequence characteristics. Grain amaranths are a set of three species that were domesticated in the New World to be high protein, pseudo-cereal grain crops. The goal of this research was to employ the GBS technique for diversity evaluation in grain amaranth accessions and close relatives from six Amaranthus species and determine genetic differences and similarities between groupings. A total of 10,668 SNPs were discovered in 94 amaranth accessions with ApeKI complexity reduction and 10X genome coverage Illumina sequencing. The majority of the SNPs were species specific with 4,568 and 3,082 for the two grain amaranths originating in Central America Amaranthus cruentus and A. hypochondriacus and 3,284 found amongst both A. caudatus, originally domesticated in South America, and its close relative, A. quitensis. The distance matrix based on shared alleles provided information on the close relationships of the two cultivated Central American species with each other and of the wild and cultivated South American species with each other, as distinguished from the outgroup with two wild species, A. powellii and A. retroflexus. The GBS data also distinguished admixture between each pair of species and the geographical origins and seed colors of the accessions. The SNPs we discovered here can be used for marker development for future amaranth study.

Evolution of the Banana Genome (Musa acuminata) Is Impacted by Large Chromosomal Translocations

Most banana cultivars are triploid seedless parthenocarpic clones derived from hybridization between Musa acuminata subspecies and sometimes M. balbisiana. M. acuminata subspecies were suggested to differ by a few large chromosomal rearrangements based on chromosome pairing configurations in intersubspecies hybrids. We searched for large chromosomal rearrangements in a seedy M. acuminata ssp. malaccensis banana accession through mate-pair sequencing, BAC-FISH, targeted PCR and marker (DArTseq) segregation in its progeny. We identified a heterozygous reciprocal translocation involving two distal 3 and 10 Mb segments from chromosomes 01 and 04, respectively, and showed that it generated high segregation distortion, reduced recombination and linkage between chromosomes 01 and 04 in its progeny. The two chromosome structures were found to be mutually exclusive in gametes and the rearranged structure was preferentially transmitted to the progeny. The rearranged chromosome structure was frequently found in triploid cultivars but present only in wild malaccensis ssp. accessions, thus suggesting that this rearrangement occurred in M. acuminata ssp. malaccensis. We propose a mechanism for the spread of this rearrangement in Musa diversity and suggest that this rearrangement could have played a role in the emergence of triploid cultivars.

ALUMINUM RESISTANCE TRANSCRIPTION FACTOR 1 (ART1) contributes to natural variation in aluminum resistance in diverse genetic backgrounds of rice (O. sativa)

Transcription factors (TFs) regulate the expression of other genes to indirectly mediate stress resistance mechanisms. Therefore, when studying TF-mediated stress resistance, it is important to understand how TFs interact with genes in the genetic background. Here, we fine-mapped the aluminum (Al) resistance QTL Alt12.1 to a 44-kb region containing six genes. Among them is ART1, which encodes a C2H2-type zinc finger TF required for Al resistance in rice. The mapping parents, Al-resistant cv Azucena (tropical japonica) and Al-sensitive cv IR64 (indica), have extensive sequence polymorphism within the ART1 coding region, but similar ART1 expression levels. Using reciprocal near-isogenic lines (NILs) we examined how allele-swapping the Alt12.1 locus would affect plant responses to Al. Analysis of global transcriptional responses to Al stress in roots of the NILs alongside their recurrent parents demonstrated that the presence of the Alt12.1 from Al-resistant Azucena led to greater changes in gene expression in response to Al when compared to the Alt12.1 from IR64 in both genetic backgrounds. The presence of the ART1 allele from the opposite parent affected the expression of several genes not previously implicated in rice Al tolerance. We highlight examples where putatively functional variation in cis-regulatory regions of ART1-regulated genes interacts with ART1 to determine gene expression in response to Al. This ART1-promoter interaction may be associated with transgressive variation for Al resistance in the Azucena × IR64 population. These results illustrate how ART1 interacts with the genetic background to contribute to quantitative phenotypic variation in rice Al resistance.

Genotyping-by-sequencing enables linkage mapping in three octoploid cultivated strawberry families

Genotyping-by-sequencing (GBS) was used to survey genome-wide single-nucleotide polymorphisms (SNPs) in three biparental strawberry (Fragaria × ananassa) populations with the goal of evaluating this technique in a species with a complex octoploid genome. GBS sequence data were aligned to the F. vesca ‘Fvb’ reference genome in order to call SNPs. Numbers of polymorphic SNPs per population ranged from 1,163 to 3,190. Linkage maps consisting of 30–65 linkage groups were produced from the SNP sets derived from each parent. The linkage groups covered 99% of the Fvb reference genome, with three to seven linkage groups from a given parent aligned to any particular chromosome. A phylogenetic analysis performed using the POLiMAPS pipeline revealed linkage groups that were most similar to ancestral species F. vesca for each chromosome. Linkage groups that were most similar to a second ancestral species, F. iinumae, were only resolved for Fvb 4. The quantity of missing data and heterogeneity in genome coverage inherent in GBS complicated the analysis, but POLiMAPS resolved F. × ananassa chromosomal regions derived from diploid ancestor F. vesca.

Genome-wide association mapping for phenotypic plasticity in rice

Phenotypic plasticity of plants in response to environmental changes is important for adapting to changing climate. Less attention has been paid to exploring the advantages of phenotypic plasticity in resource-rich environments to enhance the productivity of agricultural crops. Here, we examined genetic variation for phenotypic plasticity in indica rice (Oryza sativa L.) across two diverse panels: (1) a Phenomics of Rice Adaptation and Yield (PRAY) population comprising 301 accessions; and (2) a Multi-parent Advanced Generation Inter-Cross (MAGIC) indica population comprising 151 accessions. Altered planting density was used as a proxy for elevated atmospheric CO₂ response. Low planting density significantly increased panicle weight per plant compared with normal density, and the magnitude of the increase ranged from 1.10 to 2.78 times among accessions for the PRAY population and from 1.05 to 2.45 times for the MAGIC population. Genome-wide-association studies validate three Environmental Responsiveness (ER) candidate alleles (qER1-3) that were associated with relative response of panicle weight to low density. Two of these alleles were tested in 13 genotypes to clarify their biomass responses during vegetative growth under elevated CO₂ in Japan. Our study provides evidence for polymorphisms that control rice phenotypic plasticity in environments that are rich in resources such as light and CO₂ .

Development of a high-density linkage map and mapping of the three-pistil gene (Pis1) in wheat using GBS markers

Background

The wheat mutant line three-pistil (TP) exhibits three pistils per floret. As TP normally has two or three seeds in each of the florets on the same spike, there is the possibility of increasing the number of grains per spike. Therefore, TP is a highly valuable mutant for breeding and for the study of floral development in wheat. To map the three-pistil gene (Pis1), genotyping-by-sequencing single-nucleotide polymorphism (GBS-SNP) data from an F₂ mapping population (CM28 × CM28TP) was used to construct a genetic map that is of significant value.

Results

In the present study, a high-density genetic map of wheat containing 2917 GBS-SNP markers was constructed. Twenty-one linkage groups were resolved, with a total length of 2371.40 cM. The individual chromosomes range from 2.64 cM to 454.55 cM with an average marker density of 0.81 cM. The Pis1 gene was mapped using this high-resolution map, and two flanking SNP markers tightly linked to the gene, M70 and M71, were identified. The Pis1 is 3.00 cM from M70 and 1.10 cM from M71. In bread wheat genome, M70 and M71 were found to delimit a physical distance of 3.40 Mb, which encompasses 127 protein-coding genes. To validate the GBS-generated genotypic data and to eliminate missing marker data in the Pis1 region, five Kompetitive Allele-Specific PCR (KASP) assays were designed from corresponding GBS sequences, which harbor SNPs that surround Pis1. Three KASP-SNP markers, KM70, KM71, and KM75, were remapped to the Pis1 gene region.

Conclusions

This work not only lays the foundation for the map-based cloning of Pis1 but can also serve as a valuable tool for studying marker-trait association of important traits and marker-assisted breeding in wheat.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3960-7) contains supplementary material, which is available to authorized users.

The buffering capacity of stems: genetic architecture of nonstructural carbohydrates in cultivated Asian rice, Oryza sativa

Harnessing stem carbohydrate dynamics in grasses offers an opportunity to help meet future demands for plant-based food, fiber and fuel production, but requires a greater understanding of the genetic controls that govern the synthesis, interconversion and transport of such energy reserves. We map out a blueprint of the genetic architecture of rice (Oryza sativa) stem nonstructural carbohydrates (NSC) at two critical developmental time-points using a subpopulation-specific genome-wide association approach on two diverse germplasm panels followed by quantitative trait loci (QTL) mapping in a biparental population. Overall, 26 QTL are identified; three are detected in multiple panels and are associated with starch-at-maturity, sucrose-at-maturity and NSC-at-heading. They tag OsHXK6 (rice hexokinase), ISA2 (rice isoamylase) and a tandem array of sugar transporters. This study provides the foundation for more in-depth molecular investigation to validate candidate genes underlying rice stem NSC and informs future comparative studies in other agronomically vital grass species.

Genetic Architecture of a Rice Nested Association Mapping Population

Describing the genetic diversity in the gene pool of crops will provide breeders with novel resources for varietal improvement. Nested Association Mapping (NAM) populations are uniquely suited for characterizing parental diversity through the shuffling and fixation of parental haplotypes. Here, we describe a set of 1879 rice NAM lines created through the selfing and single-seed descent of F1 hybrids derived from elite IR64 indica crossed with 10 diverse tropical japonica lines. Genotyping data indicated tropical japonica alleles were captured at every queried locus despite the presence of segregation distortion factors. Several distortion loci were mapped, both shared and unique, among the 10 populations. Using two-point and multi-point genetic map calculations, our datasets achieved the ∼1500 cM expected map size in rice. Finally, we highlighted the utility of the NAM lines for QTL mapping, including joint analysis across the 10 populations, by confirming known QTL locations for the trait days to heading.

Adapting Genotyping-by-Sequencing for Rice F2 Populations

Rapid and cost-effective genotyping of large mapping populations can be achieved by sequencing a reduced representation of the genome of every individual in a given population, and using that information to generate genetic markers. A customized genotyping-by-sequencing (GBS) pipeline was developed to genotype a rice F2 population from a cross of Oryza sativa ssp. japonica cv. Nipponbare and the African wild rice species O. longistaminata While most GBS pipelines aim to analyze mainly homozygous populations, we attempted to genotype a highly heterozygous F2 population. We show how species- and population-specific improvements of established protocols can drastically increase sample throughput and genotype quality. Using as few as 50,000 reads for some individuals (134,000 reads on average), we were able to generate up to 8154 informative SNP markers in 1081 F2 individuals. Additionally, the effects of enzyme choice, read coverage, and data postprocessing are evaluated. Using GBS-derived markers, we were able to assemble a genetic map of 1536 cM. To demonstrate the usefulness of our GBS pipeline, we determined quantitative trait loci (QTL) for the number of tillers. We were able to map four QTL to chromosomes 1, 3, 4, and 8, and partially confirm their effects using introgression lines. We provide an example of how to successfully use GBS with heterozygous F2 populations. By using the comparatively low-cost MiSeq platform, we show that the GBS method is flexible and cost-effective, even for smaller laboratories.

Genome-wide association analysis of agronomic traits in wheat under drought-stressed and non-stressed conditions

This study determined the population structure and genome-wide marker-trait association of agronomic traits of wheat for drought-tolerance breeding. Ninety-three diverse bread wheat genotypes were genotyped using the Diversity Arrays Technology sequencing (DArTseq) protocol. The number of days-to-heading (DTH), number of days-to-maturity (DTM), plant height (PHT), spike length (SPL), number of kernels per spike (KPS), thousand kernel weight (TKW) and grain yield (GYLD), assessed under drought-stressed and non-stressed conditions, were considered for the study. Population structure analysis and genome-wide association mapping were undertaken based on 16,383 silico DArTs loci with < 10% missing data. The population evaluated was grouped into nine distinct genetic structures. Inter-chromosomal linkage disequilibrium showed the existence of linkage decay as physical distance increased. A total of 62 significant (P < 0.001) marker-trait associations (MTAs) were detected explaining more than 20% of the phenotypic variation observed under both drought-stressed and non-stressed conditions. Significant (P < 0.001) MTA event(s) were observed for DTH, PHT, SPL, SPS, and KPS; under both stressed and non-stressed conditions, while additional significant (P < 0.05) associations were observed for TKW, DTM and GYLD under non-stressed condition. The MTAs reported in this population could be useful to initiate marker-assisted selection (MAS) and targeted trait introgression of wheat under drought-stressed and non-stressed conditions, and for fine mapping and cloning of the underlying genes and QTL.

Transcriptome-based SNP discovery by GBS and the construction of a genetic map for olive

Molecular markers located in the genic regions of plants are valuable tools for the identification of candidate genes of economically important traits and consequent use in marker-assisted selection (MAS). In the past, simple sequence repeat markers (SSRs) and single-nucleotide polymorphisms (SNPs) located in expressed sequence tags (ESTs) were developed by sequencing RNA derived from different plant tissues, which involves laborious RNA extraction, mRNA isolation, and cDNA synthesis. In order to develop SNP markers located in olive transcriptomes, we used the recently developed genotyping-by-sequencing (GBS) technique. An analysis was done for 125 olive DNA samples (123 DNA samples from a cross-pollinated F₁ mapping population, and two samples from parents). From 45 to 66% of Illumina reads from GBS analysis were aligned to the olive transcriptome. A total of 22,033 transcriptome-based SNP markers were identified, and 3384 of these were mapped in the olive genome. The genetic linkage map constructed in this study consists of 1 cleaved amplified polymorphic sequence (CAPS), 19 SSR, and 3384 transcriptome-based SNP markers. The map covers 3340.8 cM of the olive genome in 23 linkage groups, with the length of the linkage groups ranging from 55.6 to 248.7 cM. Average map distance between flanking markers was 0.98 cM. This genetic linkage map is a saturated genetic map and will be a useful tool for the localization of quantitative trait loci (QTLs) and gene(s) of interest and for the identification of candidate genes for economically important traits.

Genome-wide SNP identification, linkage map construction and QTL mapping for seed mineral concentrations and contents in pea (Pisum sativum L.)

BACKGROUND

Marker-assisted breeding is now routinely used in major crops to facilitate more efficient cultivar improvement. This has been significantly enabled by the use of next-generation sequencing technology to identify loci and markers associated with traits of interest. While rich in a range of nutritional components, such as protein, mineral nutrients, carbohydrates and several vitamins, pea (Pisum sativum L.), one of the oldest domesticated crops in the world, remains behind many other crops in the availability of genomic and genetic resources. To further improve mineral nutrient levels in pea seeds requires the development of genome-wide tools. The objectives of this research were to develop these tools by: identifying genome-wide single nucleotide polymorphisms (SNPs) using genotyping by sequencing (GBS); constructing a high-density linkage map and comparative maps with other legumes, and identifying quantitative trait loci (QTL) for levels of boron, calcium, iron, potassium, magnesium, manganese, molybdenum, phosphorous, sulfur, and zinc in the seed, as well as for seed weight.

RESULTS

In this study, 1609 high quality SNPs were found to be polymorphic between 'Kiflica' and 'Aragorn', two parents of an F6-derived recombinant inbred line (RIL) population. Mapping 1683 markers including 75 previously published markers and 1608 SNPs developed from the present study generated a linkage map of size 1310.1 cM. Comparative mapping with other legumes demonstrated that the highest level of synteny was observed between pea and the genome of Medicago truncatula. QTL analysis of the RIL population across two locations revealed at least one QTL for each of the mineral nutrient traits. In total, 46 seed mineral concentration QTLs, 37 seed mineral content QTLs, and 6 seed weight QTLs were discovered. The QTLs explained from 2.4% to 43.3% of the phenotypic variance.

CONCLUSION

The genome-wide SNPs and the genetic linkage map developed in this study permitted QTL identification for pea seed mineral nutrients that will serve as important resources to enable marker-assisted selection (MAS) for nutritional quality traits in pea breeding programs.

Genome-Wide Single-Nucleotide Polymorphisms in CMS and Restorer Lines Discovered by Genotyping Using Sequencing and Association with Marker-Combining Ability for 12 Yield-Related Traits in Oryza sativa L. subsp. Japonica

Heterosis or hybrid vigor is closely related with general combing ability (GCA) of parents and special combining ability (SCA) of combinations. The evaluation of GCA and SCA facilitate selection of parents and combinations in heterosis breeding. In order to improve combining ability (CA) by molecular marker assist selection, it is necessary to identify marker loci associated with the CA. To identify the single nucleotide polymorphisms (SNP) loci associated with CA in the parental genomes of japonica rice, genome-wide discovered SNP loci were tested for association with the CA of 18 parents for 12 yield-related traits. In this study, 81 hybrids were created and evaluated to calculate the CA of 18 parents. The parents were sequenced by genotyping by sequencing (GBS) method for identification of genome-wide SNPs. The analysis of GBS indicated that the successful mapping of 9.86 × 10⁶ short reads in the Nipponbare reference genome consists of 39,001 SNPs in parental genomes at 11,085 chromosomal positions. The discovered SNPs were non-randomly distributed within and among the 12 chromosomes of rice. Overall, 20.4% (8026) of the discovered SNPs were coding types, and 8.6% (3344) and 9.9% (3951) of the SNPs revealed synonymous and non-synonymous changes, which provide valuable knowledge about the underlying performance of the parents. Furthermore, the associations between SNPs and CA indicated that 362 SNP loci were significantly related to the CA of 12 parental traits. The identified SNP loci of CA in our study were distributed genome wide and caused a positive or negative effect on the CA of traits. For the yield-related traits, such as grain thickness, days to heading, panicle length, grain length and 1000-grain weight, a maximum number of positive SNP loci of CA were found in CMS A171 and in the restorers LC64 and LR27. On an individual basis, some of associated loci that resided on chromosomes 2, 5, 7, 9, and 11 recorded maximum positive values for the CA of traits. From our results, we suggest that heterosis in japonica rice would be improved by pyramiding the favorable SNP loci of CA and eliminating the unfavorable loci from parental genomes.

Genome-Wide Single Nucleotide Polymorphism Discovery and the Construction of a High-Density Genetic Map for Melon (Cucumis melo L.) Using Genotyping-by-Sequencing

Although genotyping-by-sequencing (GBS) enables the efficient and low-cost generation of large numbers of markers, the utility of resultant genotypes are limited, because they are enormously error-prone and contain high proportions of missing data. In this study, we generated single nucleotide polymorphism (SNP) markers for 109 recombinant inbred lines of melon (Cucumis melo L.) using the GBS approach and ordered them according to their physical position on the draft double haploid line DHL92 genome. Next, by investigating associations between these SNPs, we discovered that some segments on the physical map conflict with linkage relationships. Therefore, to filter out error-prone loci, 4,110 SNPs in which we have a high degree of confidence were selected as anchors to test independence with respect to unselected markers, and the resultant dataset was then analyzed using the Full-Sib Family Haplotype (FSFHap) algorithm in the software TASSEL 5.2. On the basis of this analysis, 22,933 loci that have an average rate of missing data of 0.281% were used to construct a genetic map, which spans 1,088.3 cM across 12 chromosomes and has a maximum spacing of 6.0 cM. Use of this high-quality linkage map enabled the identification of several quantitative trait loci (QTL) known to control traits in fruit and validated our approach. This study highlights the utility of GBS markers for the identification of trait-associated QTLs in melon and facilitates further investigation of genome structure.

Genome-wide association analysis for heat tolerance at flowering detected a large set of genes involved in adaptation to thermal and other stresses

Fertilization sensitivity to heat in rice is a major issue within climate change scenarios in the tropics. A panel of 167 indica landraces and improved varieties was phenotyped for spikelet sterility (SPKST) under 38°C during anthesis and for several secondary traits potentially affecting panicle micro-climate and thus the fertilization process. The panel was genotyped with an average density of one marker per 29 kb using genotyping by sequencing. Genome-wide association analyses (GWAS) were conducted using three methods based on single marker regression, haplotype regression and simultaneous fitting of all markers, respectively. Fourteen loci significantly associated with SPKST under at least two GWAS methods were detected. A large number of associations was also detected for the secondary traits. Analysis of co-localization of SPKST associated loci with QTLs detected in progenies of bi-parental crosses reported in the literature allowed to narrow -down the position of eight of those QTLs, including the most documented one, qHTSF4.1. Gene families underlying loci associated with SPKST corresponded to functions ranging from sensing abiotic stresses and regulating plant response, such as wall-associated kinases and heat shock proteins, to cell division and gametophyte development. Analysis of diversity at the vicinity of loci associated with SPKST within the rice three thousand genomes, revealed widespread distribution of the favourable alleles across O. sativa genetic groups. However, few accessions assembled the favourable alleles at all loci. Effective donors included the heat tolerant variety N22 and some Indian and Taiwanese varieties. These results provide a basis for breeding for heat tolerance during anthesis and for functional validation of major loci governing this trait.

Genotyping-by-sequencing approaches to characterize crop genomes: choosing the right tool for the right application

In the last decade, the revolution in sequencing technologies has deeply impacted crop genotyping practice. New methods allowing rapid, high-throughput genotyping of entire crop populations have proliferated and opened the door to wider use of molecular tools in plant breeding. These new genotyping-by-sequencing (GBS) methods include over a dozen reduced-representation sequencing (RRS) approaches and at least four whole-genome resequencing (WGR) approaches. The diversity of methods available, each often producing different types of data at different cost, can make selection of the best-suited method seem a daunting task. We review the most common genotyping methods used today and compare their suitability for linkage mapping, genomewide association studies (GWAS), marker-assisted and genomic selection and genome assembly and improvement in crops with various genome sizes and complexity. Furthermore, we give an outline of bioinformatics tools for analysis of genotyping data. WGR is well suited to genotyping biparental cross populations with complex, small- to moderate-sized genomes and provides the lowest cost per marker data point. RRS approaches differ in their suitability for various tasks, but demonstrate similar costs per marker data point. These approaches are generally better suited for de novo applications and more cost-effective when genotyping populations with large genomes or high heterozygosity. We expect that although RRS approaches will remain the most cost-effective for some time, WGR will become more widespread for crop genotyping as sequencing costs continue to decrease.

QTL mapping and candidate genes for resistance to Fusarium ear rot and fumonisin contamination in maize

BACKGROUND

Fusarium verticillioides is a common maize pathogen causing ear rot (FER) and contamination of the grains with the fumonisin B1 (FB1) mycotoxin. Resistance to FER and FB1 contamination are quantitative traits, affected by environmental conditions, and completely resistant maize genotypes to the pathogen are so far unknown. In order to uncover genomic regions associated to reduced FER and FB1 contamination and identify molecular markers for assisted selection, an F2:3 population of 188 progenies was developed crossing CO441 (resistant) and CO354 (susceptible) genotypes. FER severity and FB1 contamination content were evaluated over 2 years and sowing dates (early and late) in ears artificially inoculated with F. verticillioides by the use of either side-needle or toothpick inoculation techniques.

RESULTS

Weather conditions significantly changed in the two phenotyping seasons and FER and FB1 content distribution significantly differed in the F3 progenies according to the year and the sowing time. Significant positive correlations (P < 0.01) were detected between FER and FB1 contamination, ranging from 0.72 to 0.81. A low positive correlation was determined between FB1 contamination and silking time (DTS). A genetic map was generated for the cross, based on 41 microsatellite markers and 342 single nucleotide polymorphisms (SNPs) derived from Genotyping-by-Sequencing (GBS). QTL analyses revealed 15 QTLs for FER, 17 QTLs for FB1 contamination and nine QTLs for DTS. Eight QTLs located on linkage group (LG) 1, 2, 3, 6, 7 and 9 were in common between FER and FB1, making possible the selection of genotypes with both low disease severity and low fumonisin contamination. Moreover, five QTLs on LGs 1, 2, 4, 5 and 9 located close to previously reported QTLs for resistance to other mycotoxigenic fungi. Finally, 24 candidate genes for resistance to F. verticillioides are proposed combining previous transcriptomic data with QTL mapping.

CONCLUSIONS

This study identified a set of QTLs and candidate genes that could accelerate breeding for resistance of maize lines showing reduced disease severity and low mycotoxin contamination determined by F. verticillioides.

GBS-based single dosage markers for linkage and QTL mapping allow gene mining for yield-related traits in sugarcane

BACKGROUND

Sugarcane (Saccharum spp.) is predominantly an autopolyploid plant with a variable ploidy level, frequent aneuploidy and a large genome that hampers investigation of its organization. Genetic architecture studies are important for identifying genomic regions associated with traits of interest. However, due to the genetic complexity of sugarcane, the practical applications of genomic tools have been notably delayed in this crop, in contrast to other crops that have already advanced to marker-assisted selection (MAS) and genomic selection. High-throughput next-generation sequencing (NGS) technologies have opened new opportunities for discovering molecular markers, especially single nucleotide polymorphisms (SNPs) and insertion-deletion (indels), at the genome-wide level. The objectives of this study were to (i) establish a pipeline for identifying variants from genotyping-by-sequencing (GBS) data in sugarcane, (ii) construct an integrated genetic map with GBS-based markers plus target region amplification polymorphisms and microsatellites, (iii) detect QTLs related to yield component traits, and (iv) perform annotation of the sequences that originated the associated markers with mapped QTLs to search putative candidate genes.

RESULTS

We used four pseudo-references to align the GBS reads. Depending on the reference, from 3,433 to 15,906 high-quality markers were discovered, and half of them segregated as single-dose markers (SDMs) on average. In addition to 7,049 non-redundant SDMs from GBS, 629 gel-based markers were used in a subsequent linkage analysis. Of 7,678 SDMs, 993 were mapped. These markers were distributed throughout 223 linkage groups, which were clustered in 18 homo(eo)logous groups (HGs), with a cumulative map length of 3,682.04 cM and an average marker density of 3.70 cM. We performed QTL mapping of four traits and found seven QTLs. Our results suggest the presence of a stable QTL across locations. Furthermore, QTLs to soluble solid content (BRIX) and fiber content (FIB) traits had markers linked to putative candidate genes.

CONCLUSIONS

This study is the first to report the use of GBS for large-scale variant discovery and genotyping of a mapping population in sugarcane, providing several insights regarding the use of NGS data in a polyploid, non-model species. The use of GBS generated a large number of markers and still enabled ploidy and allelic dosage estimation. Moreover, we were able to identify seven QTLs, two of which had great potential for validation and future use for molecular breeding in sugarcane.

Genome-wide SNP discovery and QTL mapping for fruit quality traits in inbred backcross lines (IBLs) of solanum pimpinellifolium using genotyping by sequencing

Background

Solanum pimpinellifolium has high breeding potential for fruit quality traits and has been used as a donor in tomato breeding programs. Unlocking the genetic potential of S. pimpinellifolium requires high-throughput polymorphism identification protocols for QTL mapping and introgression of favourable alleles into cultivated tomato by both positive and background selection.

Results

In this study we identified SNP loci using a genotyping by sequencing (GBS) approach in an IBL mapping population derived from the cross between a high yielding fresh market tomato and S. pimpinellifolium (LA1589) as the recurrent and donor parents, respectively. A total of 120,983,088 reads were generated by the Illumina HiSeq next-generation sequencing platform. From these reads 448,539 sequence tags were generated. A majority of the sequence tags (84.4%) were uniquely aligned to the tomato genome. A total of 3.125 unique SNP loci were identified as a result of tag alignment to the genome assembly and were used in QTL analysis of 11 fruit quality traits. As a result, 37 QTLs were identified. S. pimpinellifolium contributed favourable alleles for 16 QTLs (43.2%), thus confirming the high breeding potential of this wild species.

Conclusions

The present work introduced a set of SNPs at sufficiently high density for QTL mapping in populations derived from S. pimpinellifolium (LA1589). Moreover, this study demonstrated the high efficiency of the GBS approach for SNP identification, genotyping and QTL mapping in an interspecific tomato population.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3406-7) contains supplementary material, which is available to authorized users.

High Density Linkage Map Construction and Mapping of Yield Trait QTLs in Maize (Zea mays) Using the Genotyping-by-Sequencing (GBS) Technology

Increasing grain yield is the ultimate goal for maize breeding. High resolution quantitative trait loci (QTL) mapping can help us understand the molecular basis of phenotypic variation of yield and thus facilitate marker assisted breeding. The aim of this study is to use genotyping-by-sequencing (GBS) for large-scale SNP discovery and simultaneous genotyping of all F₂ individuals from a cross between two varieties of maize that are in clear contrast in yield and related traits. A set of 199 F₂ progeny derived from the cross of varieties SG-5 and SG-7 were generated and genotyped by GBS. A total of 1,046,524,604 reads with an average of 5,258,918 reads per F₂ individual were generated. This number of reads represents an approximately 0.36-fold coverage of the maize reference genome Zea_mays.AGPv3.29 for each F₂ individual. A total of 68,882 raw SNPs were discovered in the F₂ population, which, after stringent filtering, led to a total of 29,927 high quality SNPs. Comparative analysis using these physically mapped marker loci revealed a higher degree of synteny with the reference genome. The SNP genotype data were utilized to construct an intra-specific genetic linkage map of maize consisting of 3,305 bins on 10 linkage groups spanning 2,236.66 cM at an average distance of 0.68 cM between consecutive markers. From this map, we identified 28 QTLs associated with yield traits (100-kernel weight, ear length, ear diameter, cob diameter, kernel row number, corn grains per row, ear weight, and grain weight per plant) using the composite interval mapping (CIM) method and 29 QTLs using the least absolute shrinkage selection operator (LASSO) method. QTLs identified by the CIM method account for 6.4% to 19.7% of the phenotypic variation. Small intervals of three QTLs (qCGR-1, qKW-2, and qGWP-4) contain several genes, including one gene (GRMZM2G139872) encoding the F-box protein, three genes (GRMZM2G180811, GRMZM5G828139, and GRMZM5G873194) encoding the WD40-repeat protein, and one gene (GRMZM2G019183) encoding the UDP-Glycosyltransferase. The work will not only help to understand the mechanisms that control yield traits of maize, but also provide a basis for marker-assisted selection and map-based cloning in further studies.

Genetic linkage analysis using DNA markers in sweetpotato

Sweetpotato is one of the most important food crop species in the world, with more than 104,000,000 tons produced each year, and the breeding of superior cultivars with agronomically important traits, such as improved disease resistance, yield, and nutrient richness, is necessary, especially in developing countries. However, as a result of the crop's complex genomic architecture, which results from its hexaploidy (2n = 6× = 90), high heterozygosity, huge genome, and outcrossing nature, the analysis of genetic linkage in sweetpotato has been challenging. In addition, the lack of whole genome sequences or gene annotations for cultivated hexaploids has interrupted the validation of mapped QTL regions and gene cloning. In spite of these technical difficulties, linkage map construction and QTL mapping analysis have been reported. This review summarizes the results of these linkage analyses, which used SSR, AFLP, and retrotransposon-based molecular markers, and describes future directions for the genetic analysis and marker-assisted breeding of this important but genetically complex crop species.

Dissection of Recombination Attributes for Multiple Maize Populations Using a Common SNP Assay

Recombination is a vital characteristic for quantitative trait loci mapping and breeding to enhance the yield potential of maize. However, recombination characteristics in globally used segregating populations have never been evaluated at similar genetic marker densities. This study aimed to divulge the characteristics of recombination events, recombinant chromosomal segments, and recombination frequency for four dissimilar populations. These populations were doubled haploid (DH), recombination inbred line (RIL), intermated B73xMo17 (IBM), and multi-parent advanced generation inter-cross (MAGIC), using the Illumina MaizeSNP50 BeadChip to provide markers. Our results revealed that the average number of recombination events was 16, 41, 72, and 86 per line in DH, RIL, IBM, and MAGIC populations, respectively. Accordingly, the average length of recombinant chromosomal segments was 84.8, 47.3, 29.2, and 20.4 Mb in DH, RIL, IBM, and MAGIC populations, respectively. Furtherly, the recombination frequency varied in different genomic regions and population types [DH (0-12.7 cM/Mb), RIL (0-15.5 cM/Mb), IBM (0-24.1 cM/Mb), MAGIC (0-42.3 cM/Mb)]. Utilizing different sub-sets of lines, the recombination bin number and size were analyzed in each population. Additionally, different sub-sets of markers and lines were employed to estimate the recombination bin number and size via formulas for relationship in these populations. The relationship between recombination events and recombination bin length was also examined. Our results contribute to determining the most suitable number of genetic markers, lines in each population, and population type for successful mapping and breeding.

Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency

BACKGROUND

Switchgrass, a warm-season perennial grass studied as a potential dedicated biofuel feedstock, is classified into two main taxa - lowland and upland ecotypes - that differ in morphology and habitat of adaptation. But there is limited information on their inherent molecular variations.

RESULTS

Transcriptome analysis by RNA-sequencing (RNA-Seq) was conducted for lowland and upland ecotypes to document their gene expression variations. Mapping of transcriptome to the reference genome (Panicum virgatum v1.1) revealed that the lowland and upland ecotypes differ substantially in sets of genes transcribed as well as levels of expression. Differential gene expression analysis exhibited that transcripts related to photosynthesis efficiency and development and photosystem reaction center subunits were upregulated in lowlands compared to upland genotype. On the other hand, catalase isozymes, helix-loop-helix, late embryogenesis abundant group I, photosulfokinases, and S-adenosyl methionine synthase gene transcripts were upregulated in the upland compared to the lowlands. At ≥100x coverage and ≥5% minor allele frequency, a total of 25,894 and 16,979 single nucleotide polymorphism (SNP) markers were discovered for VS16 (upland ecotype) and K5 (lowland ecotype) against the reference genome. The allele combination of the SNPs revealed that the transition mutations are more prevalent than the transversion mutations.

CONCLUSIONS

The gene ontology (GO) analysis of the transcriptome indicated lowland ecotype had significantly higher representation for cellular components associated with photosynthesis machinery controlling carbon fixation. In addition, using the transcriptome data, SNP markers were detected, which were distributed throughout the genome. The differentially expressed genes and SNP markers detected in this study would be useful resources for traits mapping and gene transfer across ecotypes in switchgrass breeding for increased biomass yield for biofuel conversion.

Genotype-by-sequencing facilitates genetic mapping of a stem rust resistance locus in Aegilops umbellulata, a wild relative of cultivated wheat

BACKGROUND

Wild relatives of wheat play a significant role in wheat improvement as a source of genetic diversity. Stem rust disease of wheat causes significant yield losses at the global level and stem rust pathogen race TTKSK (Ug99) is virulent to most previously deployed resistance genes. Therefore, the objective of this study was to identify loci conferring resistance to stem rust pathogen races including Ug99 in an Aegilops umbelluata bi-parental mapping population using genotype-by-sequencing (GBS) SNP markers.

RESULTS

A bi-parental F2:3 population derived from a cross made between stem rust resistant accession PI 298905 and stem rust susceptible accession PI 542369 was used for this study. F2 individuals were evaluated with stem rust race TTTTF followed by testing F2:3 families with races TTTTF and TTKSK. The segregation pattern of resistance to both stem rust races suggested the presence of one resistance gene. A genetic linkage map, comprised 1,933 SNP markers, was created for all seven chromosomes of Ae. umbellulata using GBS. A major stem rust resistance QTL that explained 80% and 52% of the phenotypic variations for TTTTF and TTKSK, respectively, was detected on chromosome 2U of Ae. umbellulata.

CONCLUSION

The novel resistance gene for stem rust identified in this study can be transferred to commercial wheat varieties assisted by the tightly linked markers identified here. These markers identified through our mapping approach can be a useful strategy to identify and track the resistance gene in marker-assisted breeding in wheat.

Molecular Dissection of Seedling Salinity Tolerance in Rice (Oryza sativa L.) Using a High-Density GBS-Based SNP Linkage Map

BACKGROUND

Salinity is one of the many abiotic stresses limiting rice production worldwide. Several studies were conducted to identify quantitative trait loci (QTLs) for traits associated to salinity tolerance. However, due to large confidence interval for the position of QTLs, utility of reported QTLs and the associated markers has been limited in rice breeding programs. The main objective of this study is to construct a high-density rice genetic map for identification QTLs and candidate genes for salinity tolerance at seedling stage.

RESULTS

We evaluated a population of 187 recombinant inbred lines (RILs) developed from a cross between Bengal and Pokkali for nine traits related to salinity tolerance. A total of 9303 SNP markers generated by genotyping-by-sequencing (GBS) were mapped to 2817 recombination points. The genetic map had a total map length of 1650 cM with an average resolution of 0.59 cM between markers. For nine traits, a total of 85 additive QTLs were identified, of which, 16 were large-effect QTLs and the rest were small-effect QTLs. The average interval size of QTL was about 132 kilo base pairs (Kb). Eleven of the 85 additive QTLs validated 14 reported QTLs for shoot potassium concentration, sodium-potassium ratio, salt injury score, plant height, and shoot dry weight. Epistatic QTL mapping identified several pairs of QTLs that significantly contributed to the variation of traits. The QTL for high shoot K⁺ concentration was mapped near the qSKC1 region. However, candidate genes within the QTL interval were a CC-NBS-LRR protein, three uncharacterized genes, and transposable elements. Additionally, many QTLs flanked small chromosomal intervals containing few candidate genes. Annotation of the genes located within QTL intervals indicated that ion transporters, osmotic regulators, transcription factors, and protein kinases may play essential role in various salt tolerance mechanisms.

CONCLUSION

The saturation of SNP markers in our linkage map increased the resolution of QTL mapping. Our study offers new insights on salinity tolerance and presents useful candidate genes that will help in marker-assisted gene pyramiding to develop salt tolerant rice varieties.

Genetic architecture of the maize kernel row number revealed by combining QTL mapping using a high-density genetic map and bulked segregant RNA sequencing

BACKGROUND

The maize kernel row number (KRN) is a key component that contributes to grain yield and has high broad-sense heritability (H ² ). Quantitative trait locus/loci (QTL) mapping using a high-density genetic map is a powerful approach to detecting loci that are responsible for traits of interest. Bulked segregant ribonucleic acid (RNA) sequencing (BSR-seq) is another rapid and cost-effective strategy to identify QTL. Combining QTL mapping using a high-density genetic map and BSR-seq may dissect comprehensively the genetic architecture underlying the maize KRN.

RESULTS

A panel of 300 F₂ individuals derived from inbred lines abe2 and B73 were genotyped using the specific-locus amplified fragment sequencing (SLAF-seq) method. A total of 4,579 high-quality polymorphic SLAF markers were obtained and used to construct a high-density genetic map with a total length of 2,123 centimorgan (cM) and an average distance between adjacent markers of 0.46 cM. Combining the genetic map and KRN of F₂ individuals, four QTL (qKRN1, qKRN2, qKRN5, and qKRN8-1) were identified on chromosomes 1, 2, 5, and 8, respectively. The physical intervals of these four QTL ranged from 4.36 Mb for qKRN8-1 to 7.11 Mb for qKRN1 with an average value of 6.08 Mb. Based on high-throughput sequencing of two RNA pools bulked from leaves of plants with extremely high and low KRNs, two QTL were detected on chromosome 8 in the 10-25 Mb (BSR_QTL1) and 60-150 Mb (BSR_QTL2) intervals. According to the physical positions of these QTL, qKRN8-1 was included by BSR_QTL2. In addition, qKRN8-1 was validated using QTL mapping with a recombinant inbred lines population that was derived from inbred lines abe2 and B73.

CONCLUSIONS

In this study, we proved that combining QTL mapping using a high-density genetic map and BSR-seq is a powerful and cost-effective approach to comprehensively revealing genetic architecture underlying traits of interest. The QTL for the KRN detected in this study, especially qKRN8-1, can be used for performing fine mapping experiments and marker-assisted selection in maize breeding.

Characterization of Brassica napus L. genotypes utilizing sequence-related amplified polymorphism and genotyping by sequencing in association with cluster analysis

Identifying parental combinations that exhibit high heterosis is a constant target for commercial Brassica napus L. hybrid development programs. Finding high heterotic parental combinations can require hundreds of test crosses and years of yield evaluation. Heterotic pool development could be used to divide breeding material into specific breeding pools and focus the number of parental combinations created. Here, we report the genotypic characterization of 79 B. napus genotypes by calculating genetic distance based on sequence-related amplified polymorphism (SRAP) and genotyping by sequencing (GBS) in association with a neighbour-joining clustering algorithm. Despite the different genotypic analyses, neighbour-joining cluster analysis based on genetic distance of SRAP and GBS produced similar clusters. Homology between SRAP and GBS clusters was approximately 77 % when manually comparing clusters and 68 % when comparing clusters using Compare2Trees. This research demonstrates that SRAP can have similar efficacy when compared to next-generation sequencing technology for heterotic pool classification. This information may provide an important breeding scaffold for the development of hybrid cultivars based upon genetic distance and cluster analysis.

Genotyping-by-sequencing provides the discriminating power to investigate the subspecies of Daucus carota (Apiaceae)

BACKGROUND

The majority of the subspecies of Daucus carota have not yet been discriminated clearly by various molecular or morphological methods and hence their phylogeny and classification remains unresolved. Recent studies using 94 nuclear orthologs and morphological characters, and studies employing other molecular approaches were unable to distinguish clearly many of the subspecies. Fertile intercrosses among traditionally recognized subspecies are well documented. We here explore the utility of single nucleotide polymorphisms (SNPs) generated by genotyping-by-sequencing (GBS) to serve as an effective molecular method to discriminate the subspecies of the D. carota complex.

RESULTS

We used GBS to obtain SNPs covering all nine Daucus carota chromosomes from 162 accessions of Daucus and two related genera. To study Daucus phylogeny, we scored a total of 10,814 or 38,920 SNPs with a maximum of 10 or 30 % missing data, respectively. To investigate the subspecies of D. carota, we employed two data sets including 150 accessions: (i) rate of missing data 10 % with a total of 18,565 SNPs, and (ii) rate of missing data 30 %, totaling 43,713 SNPs. Consistent with prior results, the topology of both data sets separated species with 2n = 18 chromosome from all other species. Our results place all cultivated carrots (D. carota subsp. sativus) in a single clade. The wild members of D. carota from central Asia were on a clade with eastern members of subsp. sativus. The other subspecies of D. carota were in four clades associated with geographic groups: (1) the Balkan Peninsula and the Middle East, (2) North America and Europe, (3) North Africa exclusive of Morocco, and (4) the Iberian Peninsula and Morocco. Daucus carota subsp. maximus was discriminated, but neither it, nor subsp. gummifer (defined in a broad sense) are monophyletic.

CONCLUSIONS

Our study suggests that (1) the morphotypes identified as D. carota subspecies gummifer (as currently broadly circumscribed), all confined to areas near the Atlantic Ocean and the western Mediterranean Sea, have separate origins from sympatric members of other subspecies of D. carota, (2) D. carota subsp. maximus, on two clades with some accessions of subsp. carota, can be distinguished from each other but only with poor morphological support, (3) D. carota subsp. capillifolius, well distinguished morphologically, is an apospecies relative to North African populations of D. carota subsp. carota, (4) the eastern cultivated carrots have origins closer to wild carrots from central Asia than to western cultivated carrots, and (5) large SNP data sets are suitable for species-level phylogenetic studies in Daucus.

Multiple Minor QTLs Are Responsible for Fusarium Head Blight Resistance in Chinese Wheat Landrace Haiyanzhong

Fusarium head blight (FHB), caused by Fusarium graminearum Schwabe, is a devastating disease in wheat (Triticum aestivum L.). Use of host resistance is one of the most effective strategies to minimize the disease damage. Haiyanzhong (HYZ) is a Chinese wheat landrace that shows a high level of resistance to FHB spread within a spike (type II resistance). To map the quantitative trait loci (QTLs) in HYZ and identify markers tightly linked to the QTLs for FHB resistance, a population of 172 recombinant inbred lines (RILs) from a cross between HYZ and Wheaton (FHB susceptible) was genotyped using simple sequence repeats (SSRs) and single-nucleotide polymorphisms (SNPs) derived from genotyping-by-sequencing (GBS), and evaluated for percentage of symptomatic spikelets (PSSs) per spike in three greenhouse experiments. Six QTLs for type II resistance were identified in HYZ, indicating that multiple minor QTLs together can provide a high level of FHB resistance in wheat. The QTL with the largest effect on FHB resistance was mapped on the chromosome arm 5AS, and the other five from HYZ were mapped on the chromosomes 6B, 7D, 3B, 4B and 4D. In addition, two QTLs from Wheaton were mapped on 2B. Critical SNPs linked to the QTLs on chromosomes 5A, 6B, and 2B were converted into KBioscience competitive allele-specific PCR (KASP) assays, which can be used for marker-assisted selection (MAS) to pyramid these QTLs in wheat.

Whole-genome characterization in pedigreed non-human primates using genotyping-by-sequencing (GBS) and imputation

BACKGROUND

Rhesus macaques are widely used in biomedical research, but the application of genomic information in this species to better understand human disease is still in its infancy. Whole-genome sequence (WGS) data in large pedigreed macaque colonies could provide substantial experimental power for genetic discovery, but the collection of WGS data in large cohorts remains a formidable expense. Here, we describe a cost-effective approach that selects the most informative macaques in a pedigree for 30X WGS, followed by low-cost genotyping-by-sequencing (GBS) at 30X on the remaining macaques in order to generate sparse genotype data at high accuracy. Dense variants from the selected macaques with WGS data are then imputed into macaques having only sparse GBS data, resulting in dense genome-wide genotypes throughout the pedigree.

RESULTS

We developed GBS for the macaque genome using a digestion with PstI, followed by sequencing of size-selected fragments at 30X coverage. From GBS sequence data collected on all individuals in a 16-member pedigree, we characterized high-confidence genotypes at 22,455 single nucleotide variant (SNV) sites that were suitable for guiding imputation of dense sequence data from WGS. To characterize dense markers for imputation, we performed WGS at 30X coverage on nine of the 16 individuals, yielding 10,193,425 high-confidence SNVs. To validate the use of GBS data for facilitating imputation, we initially focused on chromosome 19 as a test case, using an optimized panel of 833 sparse, evenly-spaced markers from GBS and 5,010 dense markers from WGS. Using the method of "Genotype Imputation Given Inheritance" (GIGI), we evaluated the effects on imputation accuracy of 3 different strategies for selecting individuals for WGS, including 1) using "GIGI-Pick" to select the most informative individuals, 2) using the most recent generation, or 3) using founders only.  We also evaluated the effects on imputation accuracy of using a range of from 1 to 9 WGS individuals for imputation. We found that the GIGI-Pick algorithm for selection of WGS individuals outperformed common heuristic approaches, and that genotype numbers and accuracy improved very little when using >5 WGS individuals for imputation. Informed by our findings, we used 4 macaques with WGS data to impute variants at up to 7,655,491 sites spanning all 20 autosomes in the 12 remaining macaques, based on their GBS genotypes at only 17,158 loci. Using a strict confidence threshold, we imputed an average of 3,680,238 variants per individual at >99 % accuracy, or an average 4,458,883 variants per individual at a more relaxed threshold, yielding >97 % accuracy.

CONCLUSIONS

We conclude that an optimal tradeoff between genotype accuracy, number of imputed genotypes, and overall cost exists at the ratio of one individual selected for WGS using the GIGI-Pick algorithm, per 3-5 relatives selected for GBS. This approach makes feasible the collection of accurate, dense genome-wide sequence data in large pedigreed macaque cohorts without the need for more expensive WGS data on all individuals.

Genome analysis and avirulence gene cloning using a high-density RADseq linkage map of the flax rust fungus, Melampsora lini

BACKGROUND

Rust fungi are an important group of plant pathogens that cause devastating losses in agricultural, silvicultural and natural ecosystems. Plants can be protected from rust disease by resistance genes encoding receptors that trigger a highly effective defence response upon recognition of specific pathogen avirulence proteins. Identifying avirulence genes is crucial for understanding how virulence evolves in the field.

RESULTS

To facilitate avirulence gene cloning in the flax rust fungus, Melampsora lini, we constructed a high-density genetic linkage map using single nucleotide polymorphisms detected in restriction site-associated DNA sequencing (RADseq) data. The map comprises 13,412 RADseq markers in 27 linkage groups that together span 5860 cM and contain 2756 recombination bins. The marker sequences were used to anchor 68.9 % of the M. lini genome assembly onto the genetic map. The map and anchored assembly were then used to: 1) show that M. lini has a high overall meiotic recombination rate, but recombination distribution is uneven and large coldspots exist; 2) show that substantial genome rearrangements have occurred in spontaneous loss-of-avirulence mutants; and 3) identify the AvrL2 and AvrM14 avirulence genes by map-based cloning. AvrM14 is a dual-specificity avirulence gene that encodes a predicted nudix hydrolase. AvrL2 is located in the region of the M. lini genome with the lowest recombination rate and encodes a small, highly-charged proline-rich protein.

CONCLUSIONS

The M. lini high-density linkage map has greatly advanced our understanding of virulence mechanisms in this pathogen by providing novel insights into genome variability and enabling identification of two new avirulence genes.

Exploring Genetic Diversity in Plants Using High-Throughput Sequencing Techniques

Food security has emerged as an urgent concern because of the rising world population. To meet the food demands of the near future, it is required to improve the productivity of various crops, not just of staple food crops. The genetic diversity among plant populations in a given species allows the plants to adapt to various environmental conditions. Such diversity could therefore yield valuable traits that could overcome the food-security challenges. To explore genetic diversity comprehensively and to rapidly identify useful genes and/or allele, advanced high-throughput sequencing techniques, also called next-generation sequencing (NGS) technologies, have been developed. These provide practical solutions to the challenges in crop genomics. Here, we review various sources of genetic diversity in plants, newly developed genetic diversity-mining tools synergized with NGS techniques, and related genetic approaches such as quantitative trait locus analysis and genome-wide association study.

Using Genotyping by Sequencing to Map Two Novel Anthracnose Resistance Loci in Sorghum bicolor

Colletotrichum sublineola is an aggressive fungal pathogen that causes anthracnose in sorghum [Sorghum bicolor (L.) Moench]. The obvious symptoms of anthracnose are leaf blight and stem rot. Sorghum, the fifth most widely grown cereal crop in the world, can be highly susceptible to the disease, most notably in hot and humid environments. In the southeastern United States the acreage of sorghum has been increasing steadily in recent years, spurred by growing interest in producing biofuels, bio-based products, and animal feed. Resistance to anthracnose is, therefore, of paramount importance for successful sorghum production in this region. To identify anthracnose resistance loci present in the highly resistant cultivar ‘Bk7’, a biparental mapping population of F_3:4 and F_4:5 sorghum lines was generated by crossing ‘Bk7’ with the susceptible inbred ‘Early Hegari-Sart’. Lines were phenotyped in three environments and in two different years following natural infection. The population was genotyped by sequencing. Following a stringent custom filtering protocol, totals of 5186 and 2759 informative SNP markers were identified in the two populations. Segregation data and association analysis identified resistance loci on chromosomes 7 and 9, with the resistance alleles derived from ‘Bk7’. Both loci contain multiple classes of defense-related genes based on sequence similarity and gene ontologies. Genetic analysis following an independent selection experiment of lines derived from a cross between ‘Bk7’ and sweet sorghum ‘Mer81-4’ narrowed the resistance locus on chromosome 9 substantially, validating this QTL. As observed in other species, sorghum appears to have regions of clustered resistance genes. Further characterization of these regions will facilitate the development of novel germplasm with resistance to anthracnose and other diseases.

An ultra-high density genetic linkage map of perennial ryegrass (Lolium perenne) using genotyping by sequencing (GBS) based on a reference shotgun genome assembly

BACKGROUND AND AIMS

High density genetic linkage maps that are extensively anchored to assembled genome sequences of the organism in question are extremely useful in gene discovery. To facilitate this process in perennial ryegrass (Lolium perenne L.), a high density single nucleotide polymorphism (SNP)- and presence/absence variant (PAV)-based genetic linkage map has been developed in an F2 mapping population that has been used as a reference population in numerous studies. To provide a reference sequence to which to align genotyping by sequencing (GBS) reads, a shotgun assembly of one of the grandparents of the population, a tenth-generation inbred line, was created using Illumina-based sequencing.

METHODS

The assembly was based on paired-end Illumina reads, scaffolded by mate pair and long jumping distance reads in the range of 3-40 kb, with >200-fold initial genome coverage. A total of 169 individuals from an F2 mapping population were used to construct PstI-based GBS libraries tagged with unique 4-9 nucleotide barcodes, resulting in 284 million reads, with approx. 1·6 million reads per individual. A bioinformatics pipeline was employed to identify both SNPs and PAVs. A core genetic map was generated using high confidence SNPs, to which lower confidence SNPs and PAVs were subsequently fitted in a straightforward binning approach.

KEY RESULTS

The assembly comprises 424 750 scaffolds, covering 1·11 Gbp of the 2·5 Gbp perennial ryegrass genome, with a scaffold N50 of 25 212 bp and a contig N50 of 3790 bp. It is available for download, and access to a genome browser has been provided. Comparison of the assembly with available transcript and gene model data sets for perennial ryegrass indicates that approx. 570 Mbp of the gene-rich portion of the genome has been captured. An ultra-high density genetic linkage map with 3092 SNPs and 7260 PAVs was developed, anchoring just over 200 Mb of the reference assembly.

CONCLUSIONS

The combined genetic map and assembly, combined with another recently released genome assembly, represent a significant resource for the perennial ryegrass genetics community.

The report of my death was an exaggeration: A review for researchers using microsatellites in the 21st century

Microsatellites, or simple sequence repeats (SSRs), have long played a major role in genetic studies due to their typically high polymorphism. They have diverse applications, including genome mapping, forensics, ascertaining parentage, population and conservation genetics, identification of the parentage of polyploids, and phylogeography. We compare SSRs and newer methods, such as genotyping by sequencing (GBS) and restriction site associated DNA sequencing (RAD-Seq), and offer recommendations for researchers considering which genetic markers to use. We also review the variety of techniques currently used for identifying microsatellite loci and developing primers, with a particular focus on those that make use of next-generation sequencing (NGS). Additionally, we review software for microsatellite development and report on an experiment to assess the utility of currently available software for SSR development. Finally, we discuss the future of microsatellites and make recommendations for researchers preparing to use microsatellites. We argue that microsatellites still have an important place in the genomic age as they remain effective and cost-efficient markers.

SNP-based analysis of genetic diversity reveals important alleles associated with seed size in rice

BACKGROUND

Single-nucleotide polymorphisms (SNPs) have become the genetic markers of choice in various genetic, ecological, and evolutionary studies. Genotyping-by-sequencing (GBS) is a next-generation-sequencing based method that takes advantage of reduced representation to enable high-throughput genotyping using a large number of SNP markers.

RESULTS

In the present study, the distribution of non-redundant SNPs in the parents of 12 rice recombination line populations was evaluated through GBS. A total of 45 Gigabites of nucleotide sequences conservatively provided satisfactory genotyping of rice SNPs. By assembling to the genomes of reference genomes of japonica Nipponbare, we detected 22,682 polymorphic SNPs that may be utilized for QTL/gene mapping with the Recombinant Inbred Lines (RIL) populations derived from these parental lines. Meanwhile, we identified polymorphic SNPs with large effects on protein-coding and miRNA genes. To validate the effect of the polymorphic SNPs, we further investigated a SNP (chr4:28,894,757) at the miRNA binding site in the 3'-UTR region of the locus Os4g48460, which is associated with rice seed size. Os4g48460 encodes a putative cytochrome P450, CYP704A3. Direct degradation of the 3'-UTR of the CYP704A3 gene by a miRNA (osa-miRf10422-akr) was validated by in planta mRNA degradation assay. We also showed that rice seeds of longer lengths may be produced by downregulating CYP704A3 via RNAi.

CONCLUSIONS

Our study has identified the genome-wide SNPs by GBS of the parental varieties of RIL populations and identified CYP704A3, a miRNA-regulated gene that is responsible for rice seed length.

Understanding and utilizing crop genome diversity via high-resolution genotyping

High-resolution genome analysis technologies provide an unprecedented level of insight into structural diversity across crop genomes. Low-cost discovery of sequence variation has become accessible for all crops since the development of next-generation DNA sequencing technologies, using diverse methods ranging from genome-scale resequencing or skim sequencing, reduced-representation genotyping-by-sequencing, transcriptome sequencing or sequence capture approaches. High-density, high-throughput genotyping arrays generated using the resulting sequence data are today available for the assessment of genomewide single nucleotide polymorphisms in all major crop species. Besides their application in genetic mapping or genomewide association studies for dissection of complex agronomic traits, high-density genotyping arrays are highly suitable for genomic selection strategies. They also enable description of crop diversity at an unprecedented chromosome-scale resolution. Application of population genetics parameters to genomewide diversity data sets enables dissection of linkage disequilibrium to characterize loci underlying selective sweeps. High-throughput genotyping platforms simultaneously open the way for targeted diversity enrichment, allowing rejuvenation of low-diversity chromosome regions in strongly selected breeding pools to potentially reverse the influence of linkage drag. Numerous recent examples are presented which demonstrate the power of next-generation genomics for high-resolution analysis of crop diversity on a subgenomic and chromosomal scale. Such studies give deep insight into the history of crop evolution and selection, while simultaneously identifying novel diversity to improve yield and heterosis.

SNP discovery in common bean by restriction-associated DNA (RAD) sequencing for genetic diversity and population structure analysis

Researchers have made great advances into the development and application of genomic approaches for common beans, creating opportunities to driving more real and applicable strategies for sustainable management of the genetic resource towards plant breeding. This work provides useful polymorphic single-nucleotide polymorphisms (SNPs) for high-throughput common bean genotyping developed by RAD (restriction site-associated DNA) sequencing. The RAD tags were generated from DNA pooled from 12 common bean genotypes, including breeding lines of different gene pools and market classes. The aligned sequences identified 23,748 putative RAD-SNPs, of which 3357 were adequate for genotyping; 1032 RAD-SNPs with the highest ADT (assay design tool) score are presented in this article. The RAD-SNPs were structurally annotated in different coding (47.00 %) and non-coding (53.00 %) sequence components of genes. A subset of 384 RAD-SNPs with broad genome distribution was used to genotype a diverse panel of 95 common bean germplasms and revealed a successful amplification rate of 96.6 %, showing 73 % of polymorphic SNPs within the Andean group and 83 % in the Mesoamerican group. A slightly increased He (0.161, n = 21) value was estimated for the Andean gene pool, compared to the Mesoamerican group (0.156, n = 74). For the linkage disequilibrium (LD) analysis, from a group of 580 SNPs (289 RAD-SNPs and 291 BARC-SNPs) genotyped for the same set of genotypes, 70.2 % were in LD, decreasing to 0.10 %in the Andean group and 0.77 % in the Mesoamerican group. Haplotype patterns spanning 310 Mb of the genome (60 %) were characterized in samples from different origins. However, the haplotype frameworks were under-represented for the Andean (7.85 %) and Mesoamerican (5.55 %) gene pools separately. In conclusion, RAD sequencing allowed the discovery of hundreds of useful SNPs for broad genetic analysis of common bean germplasm. From now, this approach provides an excellent panel of molecular tools for whole genome analysis, allowing integrating and better exploring the common bean breeding practices.

SNP Discovery by GBS in Olive and the Construction of a High-Density Genetic Linkage Map

Genetic linkage maps are valuable tools for genetic, genomic, and crop breeding studies. Several genetic linkage maps were constructed for the olive (Olea europaea L.) genome, mainly using amplified fragment length polymorphisms (AFLPs) and simple sequence repeat (SSR) markers. However, AFLPs and SSR markers were not enough to develop a high-density olive linkage map. Genotyping-by-sequencing (GBS), a recently developed single-nucleotide polymorphism (SNP) identification methodology based on next-generation sequencing (NGS) technologies, has been demonstrated to be useful for the identification of a high number of SNP markers and the construction of high-density genetic linkage maps. In the present study, we identified a total of 10,941 SNPs from a cross between the olive cultivars 'Gemlik' and 'Edincik Su' using GBS and de novo SNP discovery implemented in the computer program "Stacks." A high-density genetic linkage map for the olive genome was constructed using 121 cross-pollinated full-sib F1 progeny and 5643 markers (21 SSRs, 203 AFLPs, and 5736 SNPs). This linkage map was composed of 25 linkage groups, covering 3049 cM of the olive genome, and the mean distance between the flanking markers was 0.53 cM. To the best of our knowledge, this map is the most saturated genetic linkage map in olive to date. We demonstrated that GBS is a valuable tool for the identification of thousands of SNPs for the construction of a saturated genetic linkage map in olive. The high-density genetic map developed in this study is a useful tool for locating quantitative trait loci and other economically important traits in the olive genome.

A next-generation marker genotyping platform (AmpSeq) in heterozygous crops: a case study for marker-assisted selection in grapevine

Marker-assisted selection (MAS) is often employed in crop breeding programs to accelerate and enhance cultivar development, via selection during the juvenile phase and parental selection prior to crossing. Next-generation sequencing and its derivative technologies have been used for genome-wide molecular marker discovery. To bridge the gap between marker development and MAS implementation, this study developed a novel practical strategy with a semi-automated pipeline that incorporates trait-associated single nucleotide polymorphism marker discovery, low-cost genotyping through amplicon sequencing (AmpSeq) and decision making. The results document the development of a MAS package derived from genotyping-by-sequencing using three traits (flower sex, disease resistance and acylated anthocyanins) in grapevine breeding. The vast majority of sequence reads (⩾99%) were from the targeted regions. Across 380 individuals and up to 31 amplicons sequenced in each lane of MiSeq data, most amplicons (83 to 87%) had <10% missing data, and read depth had a median of 220-244×. Several strengths of the AmpSeq platform that make this approach of broad interest in diverse crop species include accuracy, flexibility, speed, high-throughput, low-cost and easily automated analysis.