Identification, characterization and interpretation of single-nucleotide sequence variation in allopolyploid crop species

Population Genetic Analysis in Persimmons (Diospyros kaki Thunb.) Based on Genome-Wide Single-Nucleotide Polymorphisms

This study investigated the genetic diversity and population structure of a persimmon (Diospyros kaki Thunb., 2n = 6x = 90) collection in South Korea by evaluating 9751 genome-wide single-nucleotide polymorphisms (SNPs) detected using genotyping-by-sequencing in 93 cultivars. The results of neighbor-joining clustering, principal component analysis, and STRUCTURE analysis based on SNPs indicated clear separation between cultivar groups (pollination-constant nonastringent (PCNA, 40 cultivars), pollination-constant astringent (PCA, 19), pollination-variant nonastringent (PVNA, 23), and the pollination-variant astringent type (PVA, 9)) based on the astringency types, while separation between PVA and PVNA-type cultivars was unclear. Population genetic diversity based on SNPs showed that the proportions of polymorphic SNPs within each group ranged from 99.01% (PVNA) to 94.08% (PVA), and the PVNA group exhibited the highest genetic diversity (He = 3.86 and uHe = 0.397). F (fixation index) values were low ranging from -0.024 (PVA) to 0.176 (PCA) with an average of 0.089, indicating a deficiency of heterozygosity. Analysis of molecular variance (AMOVA) and Fst among cultivar groups indicated that variation within individuals was higher than that among the groups. Pairwise Fst values among the groups ranged from 0.01566 (between PVA and PVNA) to 0.09416 (between PCA and PCNA), indicating a low level of cultivar type differentiation. These findings highlight the potential application of biallelic SNPs in population genetics studies of allopolyploids species and provide valuable insights that may have significant implications for breeding and cultivar identification in persimmon.

Smooth Descent: A ploidy-aware algorithm to improve linkage mapping in the presence of genotyping errors

Linkage mapping is an approach to order markers based on recombination events. Mapping algorithms cannot easily handle genotyping errors, which are common in high-throughput genotyping data. To solve this issue, strategies have been developed, aimed mostly at identifying and eliminating these errors. One such strategy is SMOOTH, an iterative algorithm to detect genotyping errors. Unlike other approaches, SMOOTH can also be used to impute the most probable alternative genotypes, but its application is limited to diploid species and to markers heterozygous in only one of the parents. In this study we adapted SMOOTH to expand its use to any marker type and to autopolyploids with the use of identity-by-descent probabilities, naming the updated algorithm Smooth Descent (SD). We applied SD to real and simulated data, showing that in the presence of genotyping errors this method produces better genetic maps in terms of marker order and map length. SD is particularly useful for error rates between 5% and 20% and when error rates are not homogeneous among markers or individuals. With a starting error rate of 10%, SD reduced it to ∼5% in diploids, ∼7% in tetraploids and ∼8.5% in hexaploids. Conversely, the correlation between true and estimated genetic maps increased by 0.03 in tetraploids and by 0.2 in hexaploids, while worsening slightly in diploids (∼0.0011). We also show that the combination of genotype curation and map re-estimation allowed us to obtain better genetic maps while correcting wrong genotypes. We have implemented this algorithm in the R package Smooth Descent.

A population-level statistic for assessing Mendelian behavior of genotyping-by-sequencing data from highly duplicated genomes

Background

Given the economic and environmental importance of allopolyploids and other species with highly duplicated genomes, there is a need for methods to distinguish paralogs, i.e. duplicate sequences within a genome, from Mendelian loci, i.e. single copy sequences that pair at meiosis. The ratio of observed to expected heterozygosity is an effective tool for filtering loci but requires genotyping to be performed first at a high computational cost, whereas counting the number of sequence tags detected per genotype is computationally quick but very ineffective in inbred or polyploid populations. Therefore, new methods are needed for filtering paralogs.

Results

We introduce a novel statistic, H_ind/H_E, that uses the probability that two reads sampled from a genotype will belong to different alleles, instead of observed heterozygosity. The expected value of H_ind/H_E is the same across all loci in a dataset, regardless of read depth or allele frequency. In contrast to methods based on observed heterozygosity, it can be estimated and used for filtering loci prior to genotype calling. In addition to filtering paralogs, it can be used to filter loci with null alleles or high overdispersion, and identify individuals with unexpected ploidy and hybrid status. We demonstrate that the statistic is useful at read depths as low as five to 10, well below the depth needed for accurate genotype calling in polyploid and outcrossing species.

Conclusions

Our methodology for estimating H_ind/H_E across loci and individuals, as well as determining reasonable thresholds for filtering loci, is implemented in polyRAD v1.6, available at https://github.com/lvclark/polyRAD. In large sequencing datasets, we anticipate that the ability to filter markers and identify problematic individuals prior to genotype calling will save researchers considerable computational time.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04635-9.

An enrichment method for mapping ambiguous reads to the reference genome for NGS analysis

Mapping short reads to a reference genome is an essential step in many next-generation sequencing (NGS) analyses. In plants with large genomes, a large fraction of the reads can align to multiple locations of the genome with equally good alignment scores. How to map these ambiguous reads to the genome is a challenging problem with big impacts on the downstream analysis. Traditionally, the default method is to assign an ambiguous read randomly to one of the many potential locations. In this study, we explore two alternative methods that are based on the hypothesis that the possibility of an ambiguous read being generated by a location is proportional to the total number of reads produced by that location: (1) the enrichment method that assigns an ambiguous read to the location that has produced the most reads among all the potential locations, (2) the probability method that assigns an ambiguous read to a location based on a probability proportional to the number of reads the location produces. We systematically compared the performance of the proposed methods with that of the default random method. Our results showed that the enrichment method produced better results than the default random method and the probability method in the discovery of single nucleotide polymorphisms (SNPs). Not only did it produce more SNP markers, but it also produced SNP markers with better quality, which was demonstrated using multiple mainstay genomic analyses, including genome-wide association studies (GWAS), minor allele distribution, population structure, and genomic prediction.

Rapid identification of homozygosity and site of wild relative introgressions in wheat through chromosome-specific KASP genotyping assays

For future food security, it is important that wheat, one of the most widely consumed crops in the world, can survive the threat of abiotic and biotic stresses. New genetic variation is currently being introduced into wheat through introgressions from its wild relatives. For trait discovery, it is necessary that each introgression is homozygous and hence stable. Breeding programmes rely on efficient genotyping platforms for marker-assisted selection (MAS). Recently, single nucleotide polymorphism (SNP)-based markers have been made available on high-throughput Axiom^® SNP genotyping arrays. However, these arrays are inflexible in their design and sample numbers, making their use unsuitable for long-term MAS. SNPs can potentially be converted into Kompetitive allele-specific PCR (KASP™) assays that are comparatively cost-effective and efficient for low-density genotyping of introgression lines. However, due to the polyploid nature of wheat, KASP assays for homoeologous SNPs can have difficulty in distinguishing between heterozygous and homozygous hybrid lines in a backcross population. To identify co-dominant SNPs, that can differentiate between heterozygotes and homozygotes, we PCR-amplified and sequenced genomic DNA from potential single-copy regions of the wheat genome and compared them to orthologous copies from different wild relatives. A panel of 620 chromosome-specific KASP assays have been developed that allow rapid detection of wild relative segments and provide information on their homozygosity and site of introgression in the wheat genome. A set of 90 chromosome-nonspecific assays was also produced that can be used for genotyping introgression lines. These multipurpose KASP assays represent a powerful tool for wheat breeders worldwide.

Understanding the Complexity of Cold Tolerance in White Clover using Temperature Gradient Locations and a GWAS Approach

White clover ( L.) is the most important grazing perennial forage legume in temperate climates. However, its limited capacity to survive and restore growth after low temperatures during winter constrains the productivity and wide adoption of the crop. Despite the importance of cold tolerance for white clover cultivar development, the genetic basis of this trait remains largely unknown. Hence, in this study, we performed the first genome-wide association study (GWAS) analyses in white clover to identify quantitative trait loci (QTL) for cold-tolerance-related traits. Seeds from 192 divergent genotypes from six populations in the Patagonia region of South America were collected and seed-derived plants were further clonally propagated. Clonal trials were established in three locations representing temperature gradient associated with elevation. Given the allotetraploid nature of the white clover genome, distinct genetic models (diploid and tetraploid) were tested. Only the tetraploid parameterization was able to detect the 53 loci associated with cold-tolerance traits. Out of the 53 single nucleotide polymorphism (SNP) trait associations, 17 controlled more than one trait or were stable across multiple sites. This work represents the first report of QTL for cold-tolerance-related traits, providing insights into its genetic basis and candidate genomic regions for further functional validation studies.

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.

A Novel Complementation Assay for Quick and Specific Screen of Genes Encoding Glycerol-3-Phosphate Acyltransferases

The initial step in glycerolipid biosynthesis, especially in diverse allopolyploid crop species, is poorly understood, mainly due to the lack of an effective and convenient method for functional characterization of genes encoding glycerol-3-phosphate acyltransferases (GPATs) catalyzing this reaction. Here we present a novel complementation assay for quick and specific characterization of GPAT-encoding genes. Its key design involves rational construction of yeast conditional lethal gat1Δgat2Δ double mutant bearing the heterologous Arabidopsis AtGPAT1 gene whose leaky expression under repressed conditions does not support any non-specific growth, thereby circumventing the false positive problem encountered with the system based on the gat1Δgat2Δ mutant harboring the native episomal GAT1 gene whose leaky expression appears to be sufficient for generating enough GPAT activities for the non-specific restoration of the mutant growth. A complementation assay developed based on this novel mutant enables quick phenotypic screen of GPAT sequences. A high degree of specificity of our assay was exemplified by its ability to differentiate effectively GPAT-encoding genes from those of other fatty acyltransferases and lipid-related sequences. Using this assay, we show that Arabidopsis AtGPAT1, AtGPAT5, and AtGPAT7 can complement the phosphatidate biosynthetic defect in the double mutants. Collectively, our assay provides a powerful tool for rapid screening, validation and optimization of GPAT sequences, aiding future engineering of the initial step of the triacylglycerol biosynthesis in oilseeds.

Development and Applications of a High Throughput Genotyping Tool for Polyploid Crops: Single Nucleotide Polymorphism (SNP) Array

Polypoid species play significant roles in agriculture and food production. Many crop species are polyploid, such as potato, wheat, strawberry, and sugarcane. Genotyping has been a daunting task for genetic studies of polyploid crops, which lags far behind the diploid crop species. Single nucleotide polymorphism (SNP) array is considered to be one of, high-throughput, relatively cost-efficient and automated genotyping approaches. However, there are significant challenges for SNP identification in complex, polyploid genomes, which has seriously slowed SNP discovery and array development in polyploid species. Ploidy is a significant factor impacting SNP qualities and validation rates of SNP markers in SNP arrays, which has been proven to be a very important tool for genetic studies and molecular breeding. In this review, we (1) discussed the pros and cons of SNP array in general for high throughput genotyping, (2) presented the challenges of and solutions to SNP calling in polyploid species, (3) summarized the SNP selection criteria and considerations of SNP array design for polyploid species, (4) illustrated SNP array applications in several different polyploid crop species, then (5) discussed challenges, available software, and their accuracy comparisons for genotype calling based on SNP array data in polyploids, and finally (6) provided a series of SNP array design and genotype calling recommendations. This review presents a complete overview of SNP array development and applications in polypoid crops, which will benefit the research in molecular breeding and genetics of crops with complex genomes.

Dominant Allele Phylogeny and Constitutive Subgenome Haplotype Inference in Bananas Using Mitochondrial and Nuclear Markers

Cultivated bananas (Musa spp.) have undergone domestication patterns involving crosses of wild progenitors followed by long periods of clonal propagation. Majority of cultivated bananas are polyploids with different constitutive subgenomes and knowledge on phylogenies to their progenitors at the species and subspecies levels is essential. Here, the mitochondrial (NAD1) and nuclear (CENH3) markers were used to phylogenetically position cultivated banana genotypes to diploid progenitors. The CENH3 nuclear marker was used to identify a minimum representative haplotype number in polyploids and diploid bananas based on single nucleotide polymorphisms. The mitochondrial marker NAD1 was observed to be ideal in differentiating bananas of different genomic constitutions based on size of amplicons as well as sequence. The genotypes phylogenetically segregated based on the dominant genome; AAB genotypes grouped with AA and AAA, and the ABB together with BB. Both markers differentiated banana sections, but could not differentiate subspecies within the A genomic group. On the basis of CENH3 marker, a total of 13 haplotypes (five in both diploid and triploid, three in diploids, and rest unique to triploids) were identified from the genotypes tested. The presence of haplotypes, which were common in diploids and triploids, stipulate possibility of a shared ancestry in the genotypes involved in this study. Furthermore, the presence of multiple haplotypes in some diploid bananas indicates their being heterozygous. The haplotypes identified in this study are of importance because they can be used to check the level of homozygozity in breeding lines as well as to track segregation in progenies.

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.

Diversity analysis of cotton (Gossypium hirsutum L.) germplasm using the CottonSNP63K Array

BACKGROUND

Cotton germplasm resources contain beneficial alleles that can be exploited to develop germplasm adapted to emerging environmental and climate conditions. Accessions and lines have traditionally been characterized based on phenotypes, but phenotypic profiles are limited by the cost, time, and space required to make visual observations and measurements. With advances in molecular genetic methods, genotypic profiles are increasingly able to identify differences among accessions due to the larger number of genetic markers that can be measured. A combination of both methods would greatly enhance our ability to characterize germplasm resources. Recent efforts have culminated in the identification of sufficient SNP markers to establish high-throughput genotyping systems, such as the CottonSNP63K array, which enables a researcher to efficiently analyze large numbers of SNP markers and obtain highly repeatable results. In the current investigation, we have utilized the SNP array for analyzing genetic diversity primarily among cotton cultivars, making comparisons to SSR-based phylogenetic analyses, and identifying loci associated with seed nutritional traits.

RESULTS

The SNP markers distinctly separated G. hirsutum from other Gossypium species and distinguished the wild from cultivated types of G. hirsutum. The markers also efficiently discerned differences among cultivars, which was the primary goal when designing the CottonSNP63K array. Population structure within the genus compared favorably with previous results obtained using SSR markers, and an association study identified loci linked to factors that affect cottonseed protein content.

CONCLUSIONS

Our results provide a large genome-wide variation data set for primarily cultivated cotton. Thousands of SNPs in representative cotton genotypes provide an opportunity to finely discriminate among cultivated cotton from around the world. The SNPs will be relevant as dense markers of genome variation for association mapping approaches aimed at correlating molecular polymorphisms with variation in phenotypic traits, as well as for molecular breeding approaches in cotton.

QTL meta-analysis of root traits in Brassica napus under contrasting phosphorus supply in two growth systems

A high-density SNP-based genetic linkage map was constructed and integrated with a previous map in the Tapidor x Ningyou7 (TNDH) Brassica napus population, giving a new map with a total of 2041 molecular markers and an average marker density which increased from 0.39 to 0.97 (0.82 SNP bin) per cM. Root and shoot traits were screened under low and 'normal' phosphate (Pi) supply using a 'pouch and wick' system, and had been screened previously in an agar based system. The P-efficient parent Ningyou7 had a shorter primary root length (PRL), greater lateral root density (LRD) and a greater shoot biomass than the P-inefficient parent Tapidor under both treatments and growth systems. Quantitative trait loci (QTL) analysis identified a total of 131 QTL, and QTL meta-analysis found four integrated QTL across the growth systems. Integration reduced the confidence interval by ~41%. QTL for root and shoot biomass were co-located on chromosome A3 and for lateral root emergence were co-located on chromosomes A4/C4 and C8/C9. There was a major QTL for LRD on chromosome C9 explaining ~18% of the phenotypic variation. QTL underlying an increased LRD may be a useful breeding target for P uptake efficiency in Brassica.

HaploSNP affinities and linkage map positions illuminate subgenome composition in the octoploid, cultivated strawberry (Fragaria×ananassa)

The cultivated strawberry, Fragaria×ananassa possesses a genetically complex allo-octoploid genome. Advances in genomics research in Fragaria, including the release of a genome sequence for F. vesca, have permitted the development of a high throughput whole genome genotyping array for strawberry, which promises to facilitate genetics and genomics research. In this investigation, we used the Axiom® IStraw90®)array for linkage map development, and produced a linkage map containing 8,407 SNP markers spanning 1,820cM. Whilst the linkage map provides good coverage of the genome of both parental genotypes, the map of 'Monterey' contained significantly fewer mapped markers than did that of 'Darselect'. The array contains a novel marker class known as haploSNPs, which exploit homoeologous sequence variants as probe destabilization sites to effectively reduce marker ploidy. We examined these sites as potential indicators of subgenomic identities by using comparisons to allele states in two ancestral diploids. On this basis, haploSNP loci could be inferred to be derived from F. vesca, F. iinumae, or from an unknown source. When the identity classifications of haploSNPs were considered in conjunction with their respective linkage map positions, it was possible to define two discrete subgenomes, while the remaining homoeologues of each chromosome could not be partitioned into two discrete subgenomic groupings. These findings suggested a novel hypothesis regarding octoploid strawberry subgenome structure and evolutionary origins.

Development and preliminary evaluation of a 90 K Axiom® SNP array for the allo-octoploid cultivated strawberry Fragaria × ananassa

BACKGROUND

A high-throughput genotyping platform is needed to enable marker-assisted breeding in the allo-octoploid cultivated strawberry Fragaria × ananassa. Short-read sequences from one diploid and 19 octoploid accessions were aligned to the diploid Fragaria vesca 'Hawaii 4' reference genome to identify single nucleotide polymorphisms (SNPs) and indels for incorporation into a 90 K Affymetrix® Axiom® array. We report the development and preliminary evaluation of this array.

RESULTS

About 36 million sequence variants were identified in a 19 member, octoploid germplasm panel. Strategies and filtering pipelines were developed to identify and incorporate markers of several types: di-allelic SNPs (66.6%), multi-allelic SNPs (1.8%), indels (10.1%), and ploidy-reducing "haploSNPs" (11.7%). The remaining SNPs included those discovered in the diploid progenitor F. iinumae (3.9%), and speculative "codon-based" SNPs (5.9%). In genotyping 306 octoploid accessions, SNPs were assigned to six classes with Affymetrix's "SNPolisher" R package. The highest quality classes, PolyHigh Resolution (PHR), No Minor Homozygote (NMH), and Off-Target Variant (OTV) comprised 25%, 38%, and 1% of array markers, respectively. These markers were suitable for genetic studies as demonstrated in the full-sib family 'Holiday' × 'Korona' with the generation of a genetic linkage map consisting of 6,594 PHR SNPs evenly distributed across 28 chromosomes with an average density of approximately one marker per 0.5 cM, thus exceeding our goal of one marker per cM.

CONCLUSIONS

The Affymetrix IStraw90 Axiom array is the first high-throughput genotyping platform for cultivated strawberry and is commercially available to the worldwide scientific community. The array's high success rate is likely driven by the presence of naturally occurring variation in ploidy level within the nominally octoploid genome, and by effectiveness of the employed array design and ploidy-reducing strategies. This array enables genetic analyses including generation of high-density linkage maps, identification of quantitative trait loci for economically important traits, and genome-wide association studies, thus providing a basis for marker-assisted breeding in this high value crop.

Development and preliminary evaluation of a 90 K Axiom® SNP array for the allo-octoploid cultivated strawberry Fragaria × ananassa

BACKGROUND

A high-throughput genotyping platform is needed to enable marker-assisted breeding in the allo-octoploid cultivated strawberry Fragaria × ananassa. Short-read sequences from one diploid and 19 octoploid accessions were aligned to the diploid Fragaria vesca 'Hawaii 4' reference genome to identify single nucleotide polymorphisms (SNPs) and indels for incorporation into a 90 K Affymetrix® Axiom® array. We report the development and preliminary evaluation of this array.

RESULTS

About 36 million sequence variants were identified in a 19 member, octoploid germplasm panel. Strategies and filtering pipelines were developed to identify and incorporate markers of several types: di-allelic SNPs (66.6%), multi-allelic SNPs (1.8%), indels (10.1%), and ploidy-reducing "haploSNPs" (11.7%). The remaining SNPs included those discovered in the diploid progenitor F. iinumae (3.9%), and speculative "codon-based" SNPs (5.9%). In genotyping 306 octoploid accessions, SNPs were assigned to six classes with Affymetrix's "SNPolisher" R package. The highest quality classes, PolyHigh Resolution (PHR), No Minor Homozygote (NMH), and Off-Target Variant (OTV) comprised 25%, 38%, and 1% of array markers, respectively. These markers were suitable for genetic studies as demonstrated in the full-sib family 'Holiday' × 'Korona' with the generation of a genetic linkage map consisting of 6,594 PHR SNPs evenly distributed across 28 chromosomes with an average density of approximately one marker per 0.5 cM, thus exceeding our goal of one marker per cM.

CONCLUSIONS

The Affymetrix IStraw90 Axiom array is the first high-throughput genotyping platform for cultivated strawberry and is commercially available to the worldwide scientific community. The array's high success rate is likely driven by the presence of naturally occurring variation in ploidy level within the nominally octoploid genome, and by effectiveness of the employed array design and ploidy-reducing strategies. This array enables genetic analyses including generation of high-density linkage maps, identification of quantitative trait loci for economically important traits, and genome-wide association studies, thus providing a basis for marker-assisted breeding in this high value crop.

Next-generation transcriptome sequencing, SNP discovery and validation in four market classes of peanut, Arachis hypogaea L

Single-nucleotide polymorphisms, which can be identified in the thousands or millions from comparisons of transcriptome or genome sequences, are ideally suited for making high-resolution genetic maps, investigating population evolutionary history, and discovering marker-trait linkages. Despite significant results from their use in human genetics, progress in identification and use in plants, and particularly polyploid plants, has lagged. As part of a long-term project to identify and use SNPs suitable for these purposes in cultivated peanut, which is tetraploid, we generated transcriptome sequences of four peanut cultivars, namely OLin, New Mexico Valencia C, Tamrun OL07 and Jupiter, which represent the four major market classes of peanut grown in the world, and which are important economically to the US southwest peanut growing region. CopyDNA libraries of each genotype were used to generate 2 × 54 paired-end reads using an Illumina GAIIx sequencer. Raw reads were mapped to a custom reference consisting of Tifrunner 454 sequences plus peanut ESTs in GenBank, compromising 43,108 contigs; 263,840 SNP and indel variants were identified among four genotypes compared to the reference. A subset of 6 variants was assayed across 24 genotypes representing four market types using KASP chemistry to assess the criteria for SNP selection. Results demonstrated that transcriptome sequencing can identify SNPs usable as selectable DNA-based markers in complex polyploid species such as peanut. Criteria for effective use of SNPs as markers are discussed in this context.

Identification and Evaluation of Single-Nucleotide Polymorphisms in Allotetraploid Peanut (Arachis hypogaea L.) Based on Amplicon Sequencing Combined with High Resolution Melting (HRM) Analysis

The cultivated peanut (Arachis hypogaea L.) is an allotetraploid (AABB) species derived from the A-genome (Arachis duranensis) and B-genome (Arachis ipaensis) progenitors. Presence of two versions of a DNA sequence based on the two progenitor genomes poses a serious technical and analytical problem during single nucleotide polymorphism (SNP) marker identification and analysis. In this context, we have analyzed 200 amplicons derived from expressed sequence tags (ESTs) and genome survey sequences (GSS) to identify SNPs in a panel of genotypes consisting of 12 cultivated peanut varieties and two diploid progenitors representing the ancestral genomes. A total of 18 EST-SNPs and 44 genomic-SNPs were identified in 12 peanut varieties by aligning the sequence of A. hypogaea with diploid progenitors. The average frequency of sequence polymorphism was higher for genomic-SNPs than the EST-SNPs with one genomic-SNP every 1011 bp as compared to one EST-SNP every 2557 bp. In order to estimate the potential and further applicability of these identified SNPs, 96 peanut varieties were genotyped using high resolution melting (HRM) method. Polymorphism information content (PIC) values for EST-SNPs ranged between 0.021 and 0.413 with a mean of 0.172 in the set of peanut varieties, while genomic-SNPs ranged between 0.080 and 0.478 with a mean of 0.249. Total 33 SNPs were used for polymorphism detection among the parents and 10 selected lines from mapping population Y13Zh (Zhenzhuhei × Yueyou13). Of the total 33 SNPs, nine SNPs showed polymorphism in the mapping population Y13Zh, and seven SNPs were successfully mapped into five linkage groups. Our results showed that SNPs can be identified in allotetraploid peanut with high accuracy through amplicon sequencing and HRM assay. The identified SNPs were very informative and can be used for different genetic and breeding applications in peanut.

Development and bin mapping of gene-associated interspecific SNPs for cotton (Gossypium hirsutum L.) introgression breeding efforts

BACKGROUND

Cotton (Gossypium spp.) is the largest producer of natural fibers for textile and is an important crop worldwide. Crop production is comprised primarily of G. hirsutum L., an allotetraploid. However, elite cultivars express very small amounts of variation due to the species monophyletic origin, domestication and further bottlenecks due to selection. Conversely, wild cotton species harbor extensive genetic diversity of prospective utility to improve many beneficial agronomic traits, fiber characteristics, and resistance to disease and drought. Introgression of traits from wild species can provide a natural way to incorporate advantageous traits through breeding to generate higher-producing cotton cultivars and more sustainable production systems. Interspecific introgression efforts by conventional methods are very time-consuming and costly, but can be expedited using marker-assisted selection.

RESULTS

Using transcriptome sequencing we have developed the first gene-associated single nucleotide polymorphism (SNP) markers for wild cotton species G. tomentosum, G. mustelinum, G. armourianum and G. longicalyx. Markers were also developed for a secondary cultivated species G. barbadense cv. 3-79. A total of 62,832 non-redundant SNP markers were developed from the five wild species which can be utilized for interspecific germplasm introgression into cultivated G. hirsutum and are directly associated with genes. Over 500 of the G. barbadense markers have been validated by whole-genome radiation hybrid mapping. Overall 1,060 SNPs from the five different species have been screened and shown to produce acceptable genotyping assays.

CONCLUSIONS

This large set of 62,832 SNPs relative to cultivated G. hirsutum will allow for the first high-density mapping of genes from five wild species that affect traits of interest, including beneficial agronomic and fiber characteristics. Upon mapping, the markers can be utilized for marker-assisted introgression of new germplasm into cultivated cotton and in subsequent breeding of agronomically adapted types, including cultivar development.

Development and bin mapping of gene-associated interspecific SNPs for cotton (Gossypium hirsutum L.) introgression breeding efforts

Background

Cotton (Gossypium spp.) is the largest producer of natural fibers for textile and is an important crop worldwide. Crop production is comprised primarily of G. hirsutum L., an allotetraploid. However, elite cultivars express very small amounts of variation due to the species monophyletic origin, domestication and further bottlenecks due to selection. Conversely, wild cotton species harbor extensive genetic diversity of prospective utility to improve many beneficial agronomic traits, fiber characteristics, and resistance to disease and drought. Introgression of traits from wild species can provide a natural way to incorporate advantageous traits through breeding to generate higher-producing cotton cultivars and more sustainable production systems. Interspecific introgression efforts by conventional methods are very time-consuming and costly, but can be expedited using marker-assisted selection.

Results

Using transcriptome sequencing we have developed the first gene-associated single nucleotide polymorphism (SNP) markers for wild cotton species G. tomentosum, G. mustelinum, G. armourianum and G. longicalyx. Markers were also developed for a secondary cultivated species G. barbadense cv. 3–79. A total of 62,832 non-redundant SNP markers were developed from the five wild species which can be utilized for interspecific germplasm introgression into cultivated G. hirsutum and are directly associated with genes. Over 500 of the G. barbadense markers have been validated by whole-genome radiation hybrid mapping. Overall 1,060 SNPs from the five different species have been screened and shown to produce acceptable genotyping assays.

Conclusions

This large set of 62,832 SNPs relative to cultivated G. hirsutum will allow for the first high-density mapping of genes from five wild species that affect traits of interest, including beneficial agronomic and fiber characteristics. Upon mapping, the markers can be utilized for marker-assisted introgression of new germplasm into cultivated cotton and in subsequent breeding of agronomically adapted types, including cultivar development.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-945) contains supplementary material, which is available to authorized users.

Application of next-generation sequencing technology to study genetic diversity and identify unique SNP markers in bread wheat from Kazakhstan

BACKGROUND

New SNP marker platforms offer the opportunity to investigate the relationships between wheat cultivars from different regions and assess the mechanism and processes that have led to adaptation to particular production environments. Wheat breeding has a long history in Kazakhstan and the aim of this study was to explore the relationship between key varieties from Kazakhstan and germplasm from breeding programs for other regions.

RESULTS

The study revealed 5,898 polymorphic markers amongst ten cultivars, of which 2,730 were mapped in the consensus genetic map. Mapped SNP markers were distributed almost equally across the A and B genomes, with between 279 and 484 markers assigned to each chromosome. Marker coverage was approximately 10-fold lower in the D genome. There were 863 SNP markers identified as unique to specific cultivars, and clusters of these markers (regions containing more than three closely mapped unique SNPs) showed specific patterns on the consensus genetic map for each cultivar. Significant intra-varietal genetic polymorphism was identified in three cultivars (Tzelinnaya 3C, Kazakhstanskaya rannespelaya and Kazakhstanskaya 15). Phylogenetic analysis based on inter-varietal polymorphism showed that the very old cultivar Erythrospermum 841 was the most genetically distinct from the other nine cultivars from Kazakhstan, falling in a clade together with the American cultivar Sonora and genotypes from Central and South Asia. The modern cultivar Kazakhstanskaya 19 also fell into a separate clade, together with the American cultivar Thatcher. The remaining eight cultivars shared a single sub-clade but were categorised into four clusters.

CONCLUSION

The accumulated data for SNP marker polymorphisms amongst bread wheat genotypes from Kazakhstan may be used for studying genetic diversity in bread wheat, with potential application for marker-assisted selection and the preparation of a set of genotype-specific markers.

Transcriptome and complexity-reduced, DNA-based identification of intraspecies single-nucleotide polymorphisms in the polyploid Gossypium hirsutum L

Varietal single nucleotide polymorphisms (SNPs) are the differences within one of the two subgenomes between different tetraploid cotton varieties and have not been practically used in cotton genetics and breeding because they are difficult to identify due to low genetic diversity and very high sequence identity between homeologous genes in cotton. We have used transcriptome and restriction site-associated DNA sequencing to identify varietal SNPs among 18 G. hirsutum varieties based on the rationale that varietal SNPs can be more confidently called when flanked by subgenome-specific SNPs. Using transcriptome data, we successfully identified 37,413 varietal SNPs and, of these, 22,121 did not have an additional varietal SNP within their 20-bp flanking regions so can be used in most SNP genotyping assays. From restriction site-associated DNA sequencing data, we identified an additional 3090 varietal SNPs between two of the varieties. Of the 1583 successful SNP assays achieved using different genotyping platforms, 1363 were verified. Many of the SNPs behaved as dominant markers because of coamplification from homeologous loci, but the number of SNPs acting as codominant markers increased when one or more subgenome-specific SNP(s) were incorporated in their assay primers, giving them greater utility for breeding applications. A G. hirsutum genetic map with 1244 SNP markers was constructed covering 5557.42 centiMorgan and used to map qualitative and quantitative traits. This collection of G. hirsutum varietal SNPs complements existing intra-specific SNPs and provides the cotton community with a valuable marker resource applicable to genetic analyses and breeding programs.

Genome-wide association study dissects the genetic architecture of seed weight and seed quality in rapeseed (Brassica napus L.)

Association mapping can quickly and efficiently dissect complex agronomic traits. Rapeseed is one of the most economically important polyploid oil crops, although its genome sequence is not yet published. In this study, a recently developed 60K Brassica Infinium(®) SNP array was used to analyse an association panel with 472 accessions. The single-nucleotide polymorphisms (SNPs) of the array were in silico mapped using 'pseudomolecules' representative of the genome of rapeseed to establish their hypothetical order and to perform association mapping of seed weight and seed quality. As a result, two significant associations on A8 and C3 of Brassica napus were detected for erucic acid content, and the peak SNPs were found to be only 233 and 128 kb away from the key genes BnaA.FAE1 and BnaC.FAE1. BnaA.FAE1 was also identified to be significantly associated with the oil content. Orthologues of Arabidopsis thaliana HAG1 were identified close to four clusters of SNPs associated with glucosinolate content on A9, C2, C7 and C9. For seed weight, we detected two association signals on A7 and A9, which were consistent with previous studies of quantitative trait loci mapping. The results indicate that our association mapping approach is suitable for fine mapping of the complex traits in rapeseed.

Intergenomic single nucleotide polymorphisms as a tool for bacterial artificial chromosome contig building of homoeologous Brassica napus regions

BACKGROUND

Homoeologous sequences pose a particular challenge if bacterial artificial chromosome (BAC) contigs shall be established for specific regions of an allopolyploid genome. Single nucleotide polymorphisms (SNPs) differentiating between homoeologous genomes (intergenomic SNPs) may represent a suitable screening tool for such purposes, since they do not only identify homoeologous sequences but also differentiate between them.

RESULTS

Sequence alignments between Brassica rapa (AA) and Brassica oleracea (CC) sequences mapping to corresponding regions on chromosomes A1 and C1, respectively were used to identify single nucleotide polymorphisms between the A and C genomes. A large fraction of these polymorphisms was also present in Brassica napus (AACC), an allopolyploid species that originated from hybridisation of A and C genome species. Intergenomic SNPs mapping throughout homoeologous chromosome segments spanning approximately one Mbp each were included in Illumina's GoldenGate® Genotyping Assay and used to screen multidimensional pools of a Brassica napus bacterial artificial chromosome library with tenfold genome coverage. Based on the results of 50 SNP assays, a BAC contig for the Brassica napus A subgenome was established that spanned the entire region of interest. The C subgenome region was represented in three BAC contigs.

CONCLUSIONS

This proof-of-concept study shows that sequence resources of diploid progenitor genomes can be used to deduce intergenomic SNPs suitable for multiplex polymerase chain reaction (PCR)-based screening of multidimensional BAC pools of a polyploid organism. Owing to their high abundance and ease of identification, intergenomic SNPs represent a versatile tool to establish BAC contigs for homoeologous regions of a polyploid genome.

Homoeologous duplicated regions are involved in quantitative resistance of Brassica napus to stem canker

BACKGROUND

Several major crop species are current or ancient polyploids. To better describe the genetic factors controlling traits of agronomic interest (QTL), it is necessary to understand the structural and functional organisation of these QTL regions in relation to genome duplication. We investigated quantitative resistance to the fungal disease stem canker in Brassica napus, a highly duplicated amphidiploid species, to assess the proportion of resistance QTL located at duplicated positions.

RESULTS

Genome-wide association analysis on a panel of 116 oilseed rape varieties genotyped with 3228 SNP indicated that 321 markers, corresponding to 64 genomic regions, are associated with resistance to stem canker. These genomic regions are relatively equally distributed on the A (53%) and C (47%) genomes of B. napus. Overall, 44% of these regions (28/64) are duplicated homoeologous regions. They are located in duplications of six (E, J, R, T, U and W) of the 24 ancestral blocks that constitute the B. napus genome. Overall, these six ancestral blocks have 34 duplicated copies in the B.napus genome. Almost all of the duplicated copies (82% of the 34 regions) harboured resistance associated markers for stem canker resistance, which suggests structural and functional conservation of genetic factors involved in this trait in B. napus.

CONCLUSIONS

Our study provides information on the involvement of duplicated loci in the control of stem canker resistance in B. napus. Further investigation of the similarity/divergence in sequence and gene content of these duplicated regions will provide insight into the conservation and allelic diversity of the underlying genes.

RNA-seq based SNPs for mapping in Brassica juncea (AABB): synteny analysis between the two constituent genomes A (from B. rapa) and B (from B. nigra) shows highly divergent gene block arrangement and unique block fragmentation patterns

BACKGROUND

Brassica juncea (AABB) is an allotetraploid species containing genomes of B. rapa (AA) and B. nigra (BB). It is a major oilseed crop in South Asia, and grown on approximately 6-7 million hectares of land in India during the winter season under dryland conditions. B. juncea has two well defined gene pools--Indian and east European. Hybrids between the two gene pools are heterotic for yield. A large number of qualitative and quantitative traits need to be introgressed from one gene pool into the other. This study explores the availability of SNPs in RNA-seq generated contigs, and their use for general mapping, fine mapping of selected regions, and comparative arrangement of gene blocks on B. juncea A and B genomes.

RESULTS

RNA isolated from two lines of B. juncea--Varuna (Indian type) and Heera (east European type)--was sequenced using Illumina paired end sequencing technology, and assembled using the Velvet de novo programme. A and B genome specific contigs were identified in two steps. First, by aligning contigs against the B. rapa protein database (available at BRAD), and second by comparing percentage identity at the nucleotide level with B. rapa CDS and B. nigra transcriptome. 135,693 SNPs were recorded in the assembled partial gene models of Varuna and Heera, 85,473 in the A genome and 50,236 in the B. Using KASpar technology, 999 markers were added to an earlier intron polymorphism marker based map of a B. juncea Varuna x Heera DH population. Many new gene blocks were identified in the B genome. A number of SNP markers covered single copy homoeologues of the A and B genomes, and these were used to identify homoeologous blocks between the two genomes. Comparison of the block architecture of A and B genomes revealed extensive differences in gene block associations and block fragmentation patterns.

CONCLUSIONS

Sufficient SNP markers are available for general and specific -region fine mapping of crosses between lines of two diverse B. juncea gene pools. Comparative gene block arrangement and block fragmentation patterns between A and B genomes support the hypothesis that the two genomes evolved from independent hexaploidy events.

Genomic DNA enrichment using sequence capture microarrays: a novel approach to discover sequence nucleotide polymorphisms (SNP) in Brassica napus L

Targeted genomic selection methodologies, or sequence capture, allow for DNA enrichment and large-scale resequencing and characterization of natural genetic variation in species with complex genomes, such as rapeseed canola (Brassica napus L., AACC, 2n=38). The main goal of this project was to combine sequence capture with next generation sequencing (NGS) to discover single nucleotide polymorphisms (SNPs) in specific areas of the B. napus genome historically associated (via quantitative trait loci –QTL– analysis) to traits of agronomical and nutritional importance. A 2.1 million feature sequence capture platform was designed to interrogate DNA sequence variation across 47 specific genomic regions, representing 51.2 Mb of the Brassica A and C genomes, in ten diverse rapeseed genotypes. All ten genotypes were sequenced using the 454 Life Sciences chemistry and to assess the effect of increased sequence depth, two genotypes were also sequenced using Illumina HiSeq chemistry. As a result, 589,367 potentially useful SNPs were identified. Analysis of sequence coverage indicated a four-fold increased representation of target regions, with 57% of the filtered SNPs falling within these regions. Sixty percent of discovered SNPs corresponded to transitions while 40% were transversions. Interestingly, fifty eight percent of the SNPs were found in genic regions while 42% were found in intergenic regions. Further, a high percentage of genic SNPs was found in exons (65% and 64% for the A and C genomes, respectively). Two different genotyping assays were used to validate the discovered SNPs. Validation rates ranged from 61.5% to 84% of tested SNPs, underpinning the effectiveness of this SNP discovery approach. Most importantly, the discovered SNPs were associated with agronomically important regions of the B. napus genome generating a novel data resource for research and breeding this crop species.

Identification of genome-wide single nucleotide polymorphisms in allopolyploid crop Brassica napus

Background

Single nucleotide polymorphisms (SNPs) are the most common type of genetic variation. Identification of large numbers of SNPs is helpful for genetic diversity analysis, map-based cloning, genome-wide association analyses and marker-assisted breeding. Recently, identifying genome-wide SNPs in allopolyploid Brassica napus (rapeseed, canola) by resequencing many accessions has become feasible, due to the availability of reference genomes of Brassica rapa (2n = AA) and Brassica oleracea (2n = CC), which are the progenitor species of B. napus (2n = AACC). Although many SNPs in B. napus have been released, the objective in the present study was to produce a larger, more informative set of SNPs for large-scale and efficient genotypic screening. Hence, short-read genome sequencing was conducted on ten elite B. napus accessions for SNP discovery. A subset of these SNPs was randomly selected for sequence validation and for genotyping efficiency testing using the Illumina GoldenGate assay.

Results

A total of 892,536 bi-allelic SNPs were discovered throughout the B. napus genome. A total of 36,458 putative amino acid variants were located in 13,552 protein-coding genes, which were predicted to have enriched binding and catalytic activity as a result. Using the GoldenGate genotyping platform, 94 of 96 SNPs sampled could effectively distinguish genotypes of 130 lines from two mapping populations, with an average call rate of 92%.

Conclusions

Despite the polyploid nature of B. napus, nearly 900,000 simple SNPs were identified by whole genome resequencing. These SNPs were predicted to be effective in high-throughput genotyping assays (51% polymorphic SNPs, 92% average call rate using the GoldenGate assay, leading to an estimated >450 000 useful SNPs). Hence, the development of a much larger genotyping array of informative SNPs is feasible. SNPs identified in this study to cause non-synonymous amino acid substitutions can also be utilized to directly identify causal genes in association studies.

Disentangling homeologous contigs in allo-tetraploid assembly: application to durum wheat

BACKGROUND

Using Next Generation Sequencing, SNP discovery is relatively easy on diploid species and still hampered in polyploid species by the confusion due to homeology. We develop HomeoSplitter; a fast and effective solution to split original contigs obtained by RNAseq into two homeologous sequences. It uses the differential expression of the two homeologous genes in the RNA. We verify that the new sequences are closer to the diploid progenitors of the allopolyploid species than the original contig. By remapping original reads on these new sequences, we also verify that the number of valuable detected SNPs has significantly increased.

RESULTS

HomeoSplitter is a fast and effective solution to disentangle homeologous sequences based on a maximum likelihood optimization. On a benchmark set of 2,505 clusters containing homologous sequences of urartu, speltoides and durum, HomeoSplitter was efficient to build sequences closer to the diploid references and increased the number of valuable SNPs from 188 out of 1,360 SNPs detected when mapping the reads on the de novo durum assembly to 762 out of 1,620 SNPs when mapping on HomeoSplitter contigs.

CONCLUSIONS

The HomeoSplitter program is freely available at http://bioweb.supagro.inra.fr/homeoSplitter/. This work provides a practical solution to the complex problem of disentangling homeologous transcripts in allo-tetraploids, which further allows an improved SNP detection.

Contribution of subgenomes to the transcriptome and their intertwined regulation in the allopolyploid Coffea arabica grown at contrasted temperatures

Polyploidy has occurred throughout the evolutionary history of plants and led to diversification and plant ecological adaptation. Functional plasticity of duplicate genes is believed to play a major role in the environmental adaptation of polyploids. In this context, we characterized genome-wide homoeologous gene expression in Coffea arabica, a recent allopolyploid combining two subgenomes that derive from two closely related diploid species, and investigated its variation in response to changing environment. The transcriptome of leaves of C. arabica cultivated at different growing temperatures suitable for one or the other parental species was examined using RNA-sequencing. The relative contribution of homoeologs to gene expression was estimated for 9959 and 10,628 genes in warm and cold conditions, respectively. Whatever the growing conditions, 65% of the genes showed equivalent levels of homoeologous gene expression. In 92% of the genes, relative homoeologous gene expression varied < 10% between growing temperatures. The subgenome contributions to the transcriptome appeared to be only marginally altered by the different conditions (involving intertwined regulations of homeologs) suggesting that C. arabica's ability to tolerate a broader range of growing temperatures than its diploid parents does not result from differential use of homoeologs.

SNiPloid: A Utility to Exploit High-Throughput SNP Data Derived from RNA-Seq in Allopolyploid Species

High-throughput sequencing is a common approach to discover SNP variants, especially in plant species. However, methods to analyze predicted SNPs are often optimized for diploid plant species whereas many crop species are allopolyploids and combine related but divergent subgenomes (homoeologous chromosome sets). We created a software tool, SNiPloid, that exploits and interprets putative SNPs in the context of allopolyploidy by comparing SNPs from an allopolyploid with those obtained in its modern-day diploid progenitors. SNiPloid can compare SNPs obtained from a sample to estimate the subgenome contribution to the transcriptome or SNPs obtained from two polyploid accessions to search for SNP divergence.

Screening of a Brassica napus bacterial artificial chromosome library using highly parallel single nucleotide polymorphism assays

Background

Efficient screening of bacterial artificial chromosome (BAC) libraries with polymerase chain reaction (PCR)-based markers is feasible provided that a multidimensional pooling strategy is implemented. Single nucleotide polymorphisms (SNPs) can be screened in multiplexed format, therefore this marker type lends itself particularly well for medium- to high-throughput applications. Combining the power of multiplex-PCR assays with a multidimensional pooling system may prove to be especially challenging in a polyploid genome. In polyploid genomes two classes of SNPs need to be distinguished, polymorphisms between accessions (intragenomic SNPs) and those differentiating between homoeologous genomes (intergenomic SNPs). We have assessed whether the highly parallel Illumina GoldenGate® Genotyping Assay is suitable for the screening of a BAC library of the polyploid Brassica napus genome.

Results

A multidimensional screening platform was developed for a Brassica napus BAC library which is composed of almost 83,000 clones. Intragenomic and intergenomic SNPs were included in Illumina’s GoldenGate® Genotyping Assay and both SNP classes were used successfully for screening of the multidimensional BAC pools of the Brassica napus library. An optimized scoring method is proposed which is especially valuable for SNP calling of intergenomic SNPs. Validation of the genotyping results by independent methods revealed a success of approximately 80% for the multiplex PCR-based screening regardless of whether intra- or intergenomic SNPs were evaluated.

Conclusions

Illumina’s GoldenGate® Genotyping Assay can be efficiently used for screening of multidimensional Brassica napus BAC pools. SNP calling was specifically tailored for the evaluation of BAC pool screening data. The developed scoring method can be implemented independently of plant reference samples. It is demonstrated that intergenomic SNPs represent a powerful tool for BAC library screening of a polyploid genome.

Sequence-based SNP genotyping in durum wheat

Marker development for marker-assisted selection in plant breeding is increasingly based on next-generation sequencing (NGS). However, marker development in crops with highly repetitive, complex genomes is still challenging. Here we applied sequence-based genotyping (SBG), which couples AFLP®-based complexity reduction to NGS, for de novo single nucleotide polymorphisms (SNP) marker discovery in and genotyping of a biparental durum wheat population. We identified 9983 putative SNPs in 6372 contigs between the two parents and used these SNPs for genotyping 91 recombinant inbred lines (RILs). Excluding redundant information from multiple SNPs per contig, 2606 (41%) markers were used for integration in a pre-existing framework map, resulting in the integration of 2365 markers over 2607 cM. Of the 2606 markers available for mapping, 91% were integrated in the pre-existing map, containing 708 SSRs, DArT markers, and SNPs from CRoPS technology, with a map-size increase of 492 cM (23%). These results demonstrate the high quality of the discovered SNP markers. With this methodology, it was possible to saturate the map at a final marker density of 0.8 cM/marker. Looking at the binned marker distribution (Figure 2), 63 of the 268 10-cM bins contained only SBG markers, showing that these markers are filling in gaps in the framework map. As to the markers that could not be used for mapping, the main reason was the low sequencing coverage used for genotyping. We conclude that SBG is a valuable tool for efficient, high-throughput and high-quality marker discovery and genotyping for complex genomes such as that of durum wheat.

RNA-seq based SNPs in some agronomically important oleiferous lines of Brassica rapa and their use for genome-wide linkage mapping and specific-region fine mapping

Background

Brassica rapa (AA) contains very diverse forms which include oleiferous types and many vegetable types. Genome sequence of B. rapa line Chiifu (ssp. pekinensis), a leafy vegetable type, was published in 2011. Using this knowledge, it is important to develop genomic resources for the oleiferous types of B. rapa. This will allow more involved molecular mapping, in-depth study of molecular mechanisms underlying important agronomic traits and introgression of traits from B. rapa to major oilseed crops - B. juncea (AABB) and B. napus (AACC). The study explores the availability of SNPs in RNA-seq generated contigs of three oleiferous lines of B. rapa - Candle (ssp. oleifera, turnip rape), YSPB-24 and Tetra (ssp. trilocularis, Yellow sarson) and their use in genome-wide linkage mapping and specific-region fine mapping using a RIL population between Chiifu and Tetra.

Results

RNA-seq was carried out on the RNA isolated from young inflorescences containing unopened floral buds, floral axis and small leaves, using Illumina paired-end sequencing technology. Sequence assembly was carried out using the Velvet de-novo programme and the assembled contigs were organised against Chiifu gene models, available in the BRAD-CDS database. RNA-seq confirmed the presence of more than 17,000 single-copy gene models described in the BRAD database. The assembled contigs and the BRAD gene models were analyzed for the presence of SSRs and SNPs. While the number of SSRs was limited, more than 0.2 million SNPs were observed between Chiifu and the three oleiferous lines. Assays for SNPs were designed using KASPar technology and tested on a F₇-RIL population derived from a Chiifu x Tetra cross. The design of the SNP assays were based on three considerations - the 50 bp flanking region of the SNPs should be strictly similar, the SNP should have a read-depth of ≥7 and no exon/intron junction should be present within the 101 bp target region. Using these criteria, a total of 640 markers (580 for genome-wide mapping and 60 for specific-region mapping) marking as many genes were tested for mapping. Out of 640 markers that were tested, 594 markers could be mapped unambiguously which included 542 markers for genome-wide mapping and 42 markers for fine mapping of the tet-o locus that is involved with the trait tetralocular ovary in the line Tetra.

Conclusion

A large number of SNPs and PSVs are present in the transcriptome of B. rapa lines for genome-wide linkage mapping and specific-region fine mapping. Criteria used for SNP identification delivered markers, more than 93% of which could be successfully mapped to the F₇–RIL population of Chiifu x Tetra cross.

Searching for novel sources of field resistance to Ug99 and Ethiopian stem rust races in durum wheat via association mapping

Puccinia graminis f. sp. tritici, the causative agent of stem rust in wheat, is a devastating disease of durum wheat. While more than 50 stem rust resistance (Sr) loci have been identified in wheat, only a few of them have remained effective against Ug99 (TTKSK race) and other durum-specific Ethiopian races. An association mapping (AM) approach based on 183 diverse durum wheat accessions was utilized to identify resistance loci for stem rust response in Ethiopia over four field-evaluation seasons and artificial inoculation with Ug99 and a mixture of durum-specific races. The panel was profiled with simple sequence repeat, Diversity Arrays Technology and sequence-tagged site markers (1,253 in total). The resistance turned out to be oligogenic, with twelve QTL-tagging markers that were significant (P < 0.05) across three or four seasons. R (2) values ranged from 1.1 to 11.3 %.Twenty-four additional single-marker/QTL regions were found to be significant over two seasons. The AM results confirmed the role of Sr13, previously described in bi-parental mapping studies, and the role of chromosome regions putatively harbouring Sr9, Sr14, Sr17 and Sr28. Three minor QTLs were coincident with those reported in hexaploid wheat and five overlapped with those recently reported in the Sebatel × Kristal durum mapping population. Thirteen single-marker/QTL regions were located in chromosome regions where no Sr genes/QTLs have been previously reported. The allelic variation identified in this study is readily available and can be exploited for marker-assisted selection, thus providing additional opportunities for a more durable stem rust resistance under field conditions.

Discovery and development of exome-based, co-dominant single nucleotide polymorphism markers in hexaploid wheat (Triticum aestivum L.)

Globally, wheat is the most widely grown crop and one of the three most important crops for human and livestock feed. However, the complex nature of the wheat genome has, until recently, resulted in a lack of single nucleotide polymorphism (SNP)-based molecular markers of practical use to wheat breeders. Recently, large numbers of SNP-based wheat markers have been made available via the use of next-generation sequencing combined with a variety of genotyping platforms. However, many of these markers and platforms have difficulty distinguishing between heterozygote and homozygote individuals and are therefore of limited use to wheat breeders carrying out commercial-scale breeding programmes. To identify exome-based co-dominant SNP-based assays, which are capable of distinguishing between heterozygotes and homozygotes, we have used targeted re-sequencing of the wheat exome to generate large amounts of genomic sequences from eight varieties. Using a bioinformatics approach, these sequences have been used to identify 95 266 putative single nucleotide polymorphisms, of which 10 251 were classified as being putatively co-dominant. Validation of a subset of these putative co-dominant markers confirmed that 96% were true polymorphisms and 65% were co-dominant SNP assays. The new co-dominant markers described here are capable of genotypic classification of a segregating locus in polyploid wheat and can be used on a variety of genotyping platforms; as such, they represent a powerful tool for wheat breeders. These markers and related information have been made publically available on an interactive web-based database to facilitate their use on genotyping programmes worldwide.

Characterization of expressed sequence tags from developing fibers of Gossypium barbadense and evaluation of insertion-deletion variation in tetraploid cultivated cotton species

Background

Cotton is the leading fiber crop worldwide. Gossypium barbadense is an important species of cotton because of its extra-long staple fibers with superior luster and silkiness. However, a systematic analysis and utilization of cDNA sequences from G. barbadense fiber development remains understudied.

Results

A total of 21,079 high quality sequences were generated from two non-normalized cDNA libraries prepared by using a mixture of G. barbadense Hai7124 fibers and ovules. After assembly processing, a set of 8,653 unigenes were obtained. Of those, 7,786 were matched to known proteins and 7,316 were assigned to functional categories. The molecular functions of these unigenes were mostly related to binding and catalytic activity, and carbohydrate, amino acid, and energy metabolisms were major contributors among the subsets of metabolism. Sequences comparison between G. barbadense and G. hirsutum revealed that 8,245 unigenes from G. barbadense were detected the similarity with those released publicly in G. hirsutum, however, the remaining 408 sequences had no hits against G. hirsutum unigenes database. Furthermore, 13,275 putative ESTs InDels loci involved in the orthologous and/or homoeologous differences between/within G. barbadense and G. hirsutum were discovered by in silico analyses, and 2,160 InDel markers were developed by ESTs with more than five insertions or deletions. By gel electrophoresis combined with sequencing verification, 71.11% candidate InDel loci were reconfirmed orthologous and/or homoeologous loci polymorphisms using G. hirsutum acc TM-1 and G. barbadense cv Hai7124. Blastx result showed among 2,160 InDel loci, 81 with significant function similarity with known genes associated with secondary wall synthesis process, indicating the important roles in fiber quality in tetraploid cultivated cotton species.

Conclusion

Sequence comparisons and InDel markers development will lay the groundwork for promoting the identification of genes related to superior agronomic traits, genetic differentiation and comparative genomic studies between G. hirsutum and G. barbadense.

High-density SNP-based genetic map development and linkage disequilibrium assessment in Brassica napus L

Background

High density genetic maps built with SNP markers that are polymorphic in various genetic backgrounds are very useful for studying the genetics of agronomical traits as well as genome organization and evolution. Simultaneous dense SNP genotyping of segregating populations and variety collections was applied to oilseed rape (Brassica napus L.) to obtain a high density genetic map for this species and to study the linkage disequilibrium pattern.

Results

We developed an integrated genetic map for oilseed rape by high throughput SNP genotyping of four segregating doubled haploid populations. A very high level of collinearity was observed between the four individual maps and a large number of markers (>59%) was common to more than two maps. The precise integrated map comprises 5764 SNP and 1603 PCR markers. With a total genetic length of 2250 cM, the integrated map contains a density of 3.27 markers (2.56 SNP) per cM. Genotyping of these mapped SNP markers in oilseed rape collections allowed polymorphism level and linkage disequilibrium (LD) to be studied across the different collections (winter vs spring, different seed quality types) and along the linkage groups. Overall, polymorphism level was higher and LD decayed faster in spring than in “00” winter oilseed rape types but this was shown to vary greatly along the linkage groups.

Conclusions

Our study provides a valuable resource for further genetic studies using linkage or association mapping, for marker assisted breeding and for Brassica napus sequence assembly and genome organization analyses.

Deep sequencing reveals differences in the transcriptional landscapes of fibers from two cultivated species of cotton

Cotton (Gossypium) fiber is the most prevalent natural product used in the textile industry. The two major cultivated species, G. hirsutum (Gh) and G. barbadense (Gb), are allotetraploids with contrasting fiber quality properties. To better understand the molecular basis for their fiber differences, EST pyrosequencing was used to document the fiber transcriptomes at two key development stages, 10 days post anthesis (dpa), representing the peak of fiber elongation, and 22 dpa, representing the transition to secondary cell wall synthesis. The 617,000 high quality reads (89% of the total 692,000 reads) from 4 libraries were assembled into 46,072 unigenes, comprising 38,297 contigs and 7,775 singletons. Functional annotation of the unigenes together with comparative digital gene expression (DGE) revealed a diverse set of functions and processes that were partly linked to specific fiber stages. Globally, 2,770 contigs (7%) showed differential expression (>2-fold) between 10 and 22 dpa (irrespective of genotype), with 70% more highly expressed at 10 dpa, while 2,248 (6%) were differentially expressed between the genotypes (irrespective of stage). The most significant genes with differential DGE at 10 dpa included expansins and lipid transfer proteins (higher in Gb), while at 22 dpa tubulins, cellulose, and sucrose synthases showed higher expression in Gb. DGE was compared with expression data of 10 dpa-old fibers from Affymetrix microarrays. Among 543 contigs showing differential expression on both platforms, 74% were consistent in being either over-expressed in Gh (242 genes) or in Gb (161 genes). Furthermore, the unigene set served to identify 339 new SSRs and close to 21,000 inter-genotypic SNPs. Subsets of 88 SSRs and 48 SNPs were validated through mapping and added 65 new loci to a RIL genetic map. The new set of fiber ESTs and the gene-based markers complement existing available resources useful in basic and applied research for crop improvement in cotton.

Molecular tools for exploring polyploid genomes in plants

Polyploidy is a very common phenomenon in the plant kingdom, where even diploid species are often described as paleopolyploids. The polyploid condition may bring about several advantages compared to the diploid state. Polyploids often show phenotypes that are not present in their diploid progenitors or exceed the range of the contributing species. Some of these traits may play a role in heterosis or could favor adaptation to new ecological niches. Advances in genomics and sequencing technology may create unprecedented opportunities for discovering and monitoring the molecular effects of polyploidization. Through this review, we provide an overview of technologies and strategies that may allow an in-depth analysis of polyploid genomes. After introducing some basic aspects on the origin and genetics of polyploids, we highlight the main tools available for genome and gene expression analysis and summarize major findings. In the last part of this review, the implications of next generation sequencing are briefly discussed. The accumulation of knowledge on polyploid formation, maintenance, and divergence at whole-genome and subgenome levels will not only help plant biologists to understand how plants have evolved and diversified, but also assist plant breeders in designing new strategies for crop improvement.

Single nucleotide polymorphism discovery from wheat next-generation sequence data

Single nucleotide polymorphisms (SNPs) are the most abundant type of molecular genetic marker and can be used for producing high-resolution genetic maps, marker-trait association studies and marker-assisted breeding. Large polyploid genomes such as wheat present a challenge for SNP discovery because of the potential presence of multiple homoeologs for each gene. AutoSNPdb has been successfully applied to identify SNPs from Sanger sequence data for several species, including barley, rice and Brassica, but the volume of data required to accurately call SNPs in the complex genome of wheat has prevented its application to this important crop. DNA sequencing technology has been revolutionized by the introduction of next-generation sequencing, and it is now possible to generate several million sequence reads in a timely and cost-effective manner. We have produced wheat transcriptome sequence data using 454 sequencing technology and applied this for SNP discovery using a modified autoSNPdb method, which integrates SNP and gene annotation information with a graphical viewer. A total of 4,694,141 sequence reads from three bread wheat varieties were assembled to identify a total of 38 928 candidate SNPs. Each SNP is within an assembly complete with annotation, enabling the selection of polymorphism within genes of interest.

Genome-wide SNP identification in multiple morphotypes of allohexaploid tall fescue (Festuca arundinacea Schreb)

BACKGROUND

Single nucleotide polymorphisms (SNPs) provide essential tools for the advancement of research in plant genomics, and the development of SNP resources for many species has been accelerated by the capabilities of second-generation sequencing technologies. The current study aimed to develop and use a novel bioinformatic pipeline to generate a comprehensive collection of SNP markers within the agriculturally important pasture grass tall fescue; an outbreeding allopolyploid species displaying three distinct morphotypes: Continental, Mediterranean and rhizomatous.

RESULTS

A bioinformatic pipeline was developed that successfully identified SNPs within genotypes from distinct tall fescue morphotypes, following the sequencing of 414 polymerase chain reaction (PCR) - generated amplicons using 454 GS FLX technology. Equivalent amplicon sets were derived from representative genotypes of each morphotype, including six Continental, five Mediterranean and one rhizomatous. A total of 8,584 and 2,292 SNPs were identified with high confidence within the Continental and Mediterranean morphotypes respectively. The success of the bioinformatic approach was demonstrated through validation (at a rate of 70%) of a subset of 141 SNPs using both SNaPshot™ and GoldenGate™ assay chemistries. Furthermore, the quantitative genotyping capability of the GoldenGate™ assay revealed that approximately 30% of the putative SNPs were accessible to co-dominant scoring, despite the hexaploid genome structure. The sub-genome-specific origin of each SNP validated from Continental tall fescue was predicted using a phylogenetic approach based on comparison with orthologous sequences from predicted progenitor species.

CONCLUSIONS

Using the appropriate bioinformatic approach, amplicon resequencing based on 454 GS FLX technology is an effective method for the identification of polymorphic SNPs within the genomes of Continental and Mediterranean tall fescue. The GoldenGate™ assay is capable of high-throughput co-dominant SNP allele detection, and minimises the problems associated with SNP genotyping in a polyploid by effectively reducing the complexity to a diploid system. This SNP collection may now be refined and used in applications such as cultivar identification, genetic linkage map construction, genome-wide association studies and genomic selection in tall fescue. The bioinformatic pipeline described here represents an effective general method for SNP discovery within outbreeding allopolyploid species.