Development and evaluation of single-nucleotide polymorphism markers in allotetraploid rapeseed (Brassica napus L.)

Insights on SNP types, detection methods and their utilization in Brassica species: Recent progress and future perspectives

The genus Brassica, family Brassicaceae (Cruciferae), comprises many important species of oil crops, vegetables and medicinal plants including B. rapa, B. oleracea, B. nigra, B. napus, B. juncea, B. carinata. Genomic researches in Brassica species is constrained by polyploidization, mainly due to its complicated genomic structure. However, rapid development of methods for detecting single nucleotide polymorphisms (SNP), such as next generation sequencing and SNP microarray, has accelerated release of reference Brassica species genomes as well as discovery of large numbers and genome-wide SNPs, thus intensifying forward genetics in this genus. In this review, we summarize biological characteristics, classification and various methods for detecting SNPs, focusing on high-throughput techniques. Moreover, we describe the pivotal roles of SNPs in genetic diversity, linkage map construction and QTL mapping, comparative genomics, linkage disequilibrium and genome-wide association studies. These insights are expected to deepen our understanding and guide further advancements in Brassica species research.

Comparison of statistical models for nested association mapping in rapeseed (Brassica napus L.) through computer simulations

BACKGROUND

Rapeseed (Brassica napus L.) is an important oilseed crop throughout the world, serving as source for edible oil and renewable energy. Development of nested association mapping (NAM) population and methods is of importance for quantitative trait locus (QTL) mapping in rapeseed. The objectives of the research were to compare the power of QTL detection 1- β(∗) (β(∗) is the empirical type II error rate) (i) of two mating designs, double haploid (DH-NAM) and backcross (BC-NAM), (ii) of different statistical models, and (iii) for different genetic situations.

RESULTS

The computer simulations were based on the empirical data of a single nucleotide polymorphism (SNP) set of 790 SNPs from 30 sequenced conserved genes of 51 accessions of world-wide diverse B. napus germplasm. The results showed that a joint composite interval mapping (JCIM) model had significantly higher power of QTL detection than a single marker model. The DH-NAM mating design showed a slightly higher power of QTL detection than the BC-NAM mating design. The JCIM model considering QTL effects nested within subpopulations showed higher power of QTL detection than the JCIM model considering QTL effects across subpopulations, when examing a scenario in which there were interaction effects by a few QTLs interacting with a few background markers as well as a scenario in which there were interaction effects by many QTLs (≥ 25) each with more than 10 background markers and the proportion of total variance explained by the interactions was higher than 75 %.

CONCLUSIONS

The results of our study support the optimal design as well as analysis of NAM populations, especially in rapeseed.

Allelic Variation of BnaC.TT2.a and Its Association with Seed Coat Color and Fatty Acids in Rapeseed (Brassica napus L.)

Efficient molecular markers for the selection of rapeseed genetic materials with high seed oil content and ideal fatty acid (FA) composition are preferred by rapeseed breeders. Recently, we reported the molecular mechanism of TRANSPARENT TESTA 2 (TT2) in inhibiting seed FA biosynthesis in Arabidopsis. However, evidence showing the association of rapeseed TT2 homologs and seed FA production are still insufficient. In this study, we collected 83 rapeseed (Brassica napus L.) landraces from different geographical backgrounds to conduct association mapping of BnaC.TT2.a in relation to seed coat color and FA biosynthesis. Population background was corrected by 84 pairs of SSR markers that were uniformly distributed among the linkage groups of the Tapidor-Ningyou-7 DH population. A single copy of BnaC.TT2.a for single nucleotide polymorphism (SNP) assay was cloned by a pair of previously reported specific primers. From the analysis of BnaC.TT2.a allelic variations using GLM+Q model, four SNPs on intron 1 of BnaC.TT2.a that were associated with seed FA were discovered. Moreover, an InDel at position 738 on exon 3 of BnaC.TT2.a indicated a change of protein function that was significantly associated with seed coat color, linoleic acid (C18:2), and total FA content. These findings revealed the role of BnaC.TT2.a in regulating the seed color formation and seed FA biosynthesis in rapeseed, thereby suggesting effective molecular markers for rapeseed breeding.

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

Background

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

Results

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

Conclusions

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

Electronic supplementary material

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

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

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

Applications and challenges of next-generation sequencing in Brassica species

Next-generation sequencing (NGS) produces numerous (often millions) short DNA sequence reads, typically varying between 25 and 400 bp in length, at a relatively low cost and in a short time. This revolutionary technology is being increasingly applied in whole-genome, transcriptome, epigenome and small RNA sequencing, molecular marker and gene discovery, comparative and evolutionary genomics, and association studies. The Brassica genus comprises some of the most agro-economically important crops, providing abundant vegetables, condiments, fodder, oil and medicinal products. Many Brassica species have undergone the process of polyploidization, which makes their genomes exceptionally complex and can create difficulties in genomics research. NGS injects new vigor into Brassica research, yet also faces specific challenges in the analysis of complex crop genomes and traits. In this article, we review the advantages and limitations of different NGS technologies and their applications and challenges, using Brassica as an advanced model system for agronomically important, polyploid crops. Specifically, we focus on the use of NGS for genome resequencing, transcriptome sequencing, development of single-nucleotide polymorphism markers, and identification of novel microRNAs and their targets. We present trends and advances in NGS technology in relation to Brassica crop improvement, with wide application for sophisticated genomics research into agronomically important polyploid crops.

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.

Identification of mitochondrial DNA sequence variation and development of single nucleotide polymorphic markers for CMS-D8 in cotton

Cytoplasmic male sterility (CMS), which is a maternally inherited trait and controlled by novel chimeric genes in the mitochondrial genome, plays a pivotal role in the production of hybrid seed. In cotton, no PCR-based marker has been developed to discriminate CMS-D8 (from Gossypium trilobum) from its normal Upland cotton (AD1, Gossypium hirsutum) cytoplasm. The objective of the current study was to develop PCR-based single nucleotide polymorphic (SNP) markers from mitochondrial genes for the CMS-D8 cytoplasm. DNA sequence variation in mitochondrial genes involved in the oxidative phosphorylation chain including ATP synthase subunit 1, 4, 6, 8 and 9, and cytochrome c oxidase 1, 2 and 3 subunits were identified by comparing CMS-D8, its isogenic maintainer and restorer lines on the same nuclear genetic background. An allelic specific PCR (AS-PCR) was utilized for SNP typing by incorporating artificial mismatched nucleotides into the third or fourth base from the 3' terminus in both the specific and nonspecific primers. The result indicated that the method modifying allele-specific primers was successful in obtaining eight SNP markers out of eight SNPs using eight primer pairs to discriminate two alleles between AD1 and CMS-D8 cytoplasms. Two of the SNPs for atp1 and cox1 could also be used in combination to discriminate between CMS-D8 and CMS-D2 cytoplasms. Additionally, a PCR-based marker from a nine nucleotide insertion-deletion (InDel) sequence (AATTGTTTT) at the 59-67 bp positions from the start codon of atp6, which is present in the CMS and restorer lines with the D8 cytoplasm but absent in the maintainer line with the AD1 cytoplasm, was also developed. A SNP marker for two nucleotide substitutions (AA in AD1 cytoplasm to CT in CMS-D8 cytoplasm) in the intron (1,506 bp) of cox2 gene was also developed. These PCR-based SNP markers should be useful in discriminating CMS-D8 and AD1 cytoplasms, or those with CMS-D2 cytoplasm as a rapid, simple, inexpensive, and reliable genotyping tool to assist hybrid cotton breeding.

Detection and genotyping of restriction fragment associated polymorphisms in polyploid crops with a pseudo-reference sequence: a case study in allotetraploid Brassica napus

Background

The presence of homoeologous sequences and absence of a reference genome sequence make discovery and genotyping of single nucleotide polymorphisms (SNPs) more challenging in polyploid crops.

Results

To address this challenge, we constructed reduced representation libraries (RRLs) for two Brassica napus inbred lines and their 91 doubled haploid (DH) progenies using a modified ddRADseq technique. A bioinformatics pipeline termed RFAPtools was developed to discover and genotype SNPs and presence/absence variations (PAVs). Using this pipeline, a pseudo-reference sequence (PRF) containing 180,991 sequence tags was constructed. By aligning sequence reads to the pseudo-reference sequence, allelic SNPs as well as PAVs were identified and genotyped with RFAPtools. Two parallel linkage maps, one SNP bin map containing 8,780 SNP loci and one PAV linkage map containing 12,423 dominant loci, were constructed. By aligning marker sequences to B. rapa sequence scaffolds, whose genome is available, we assigned 44 unassembled sequence scaffolds comprising 8.15 Mb onto the B. rapa chromosomes, and also identified 14 instances of misassembly and eight instances of mis-ordering sequence scaffolds.

Conclusions

These results indicate that the modified ddRADseq approach is a cost-effective and simple method to genotype tens of thousands SNPs and PAV markers in a polyploidy plant species. The results also demonstrated that RFAPtools developed in this study are powerful to mine allelic SNPs from homoeologous sequences in polyploids, therefore they are generally applicable in either diploid or polyploid species with or without a reference genome sequence.

Design of new genome- and gene-sourced primers and identification of QTL for seed oil content in a specially high-oil Brassica napus cultivar

Rapeseed (Brassica napus L.) is one of most important oilseed crops in the world. There are now various rapeseed cultivars in nature that differ in their seed oil content because they vary in oil-content alleles and there are high-oil alleles among the high-oil rapeseed cultivars. For these experiments, we generated doubled haploid (DH) lines derived from the cross between the specially high-oil cultivar zy036 whose seed oil content is approximately 50% and the specially low-oil cultivar 51070 whose seed oil content is approximately 36%. First, to address the deficiency in polymorphic markers, we designed 5944 pairs of newly developed genome-sourced primers and 443 pairs of newly developed primers related to oil-content genes to complement the 2244 pairs of publicly available primers. Second, we constructed a new DH genetic linkage map using 527 molecular markers, consisting of 181 publicly available markers, 298 newly developed genome-sourced markers and 48 newly developed markers related to oil-content genes. The map contained 19 linkage groups, covering a total length of 2,265.54 cM with an average distance between markers of 4.30 cM. Third, we identified quantitative trait loci (QTL) for seed oil content using field data collected at three sites over 3 years, and found a total of 12 QTL. Of the 12 QTL associated with seed oil content identified, 9 were high-oil QTL which derived from the specially high-oil cultivar zy036. Two high-oil QTL on chromosomes A2 and C9 co-localized in two out of three trials. By QTL mapping for seed oil content, we found four candidate genes for seed oil content related to four gene markers: GSNP39, GSSR161, GIFLP106 and GIFLP046. This information will be useful for cloning functional genes correlated with seed oil content in the future.

High-throughput polymorphism detection and genotyping in Brassica napus using next-generation RAD sequencing

Background

The complex genome of rapeseed (Brassica napus) is not well understood despite the economic importance of the species. Good knowledge of sequence variation is needed for genetics approaches and breeding purposes. We used a diversity set of B. napus representing eight different germplasm types to sequence genome-wide distributed restriction-site associated DNA (RAD) fragments for polymorphism detection and genotyping.

Results

More than 113,000 RAD clusters with more than 20,000 single nucleotide polymorphisms (SNPs) and 125 insertions/deletions were detected and characterized. About one third of the RAD clusters and polymorphisms mapped to the Brassica rapa reference sequence. An even distribution of RAD clusters and polymorphisms was observed across the B. rapa chromosomes, which suggests that there might be an equal distribution over the Brassica oleracea chromosomes, too. The representation of Gene Ontology (GO) terms for unigenes with RAD clusters and polymorphisms revealed no signature of selection with respect to the distribution of polymorphisms within genes belonging to a specific GO category.

Conclusions

Considering the decreasing costs for next-generation sequencing, the results of our study suggest that RAD sequencing is not only a simple and cost-effective method for high-density polymorphism detection but also an alternative to SNP genotyping from transcriptome sequencing or SNP arrays, even for species with complex genomes such as B. napus.

Discovery of pod shatter-resistant associated SNPs by deep sequencing of a representative library followed by bulk segregant analysis in rapeseed

Background

Single nucleotide polymorphisms (SNPs) are an important class of genetic marker for target gene mapping. As of yet, there is no rapid and effective method to identify SNPs linked with agronomic traits in rapeseed and other crop species.

Methodology/Principal Findings

We demonstrate a novel method for identifying SNP markers in rapeseed by deep sequencing a representative library and performing bulk segregant analysis. With this method, SNPs associated with rapeseed pod shatter-resistance were discovered. Firstly, a reduced representation of the rapeseed genome was used. Genomic fragments ranging from 450–550 bp were prepared from the susceptible bulk (ten F2 plants with the silique shattering resistance index, SSRI <0.10) and the resistance bulk (ten F2 plants with SSRI >0.90), and also Solexa sequencing-produced 90 bp reads. Approximately 50 million of these sequence reads were assembled into contigs to a depth of 20-fold coverage. Secondly, 60,396 ‘simple SNPs’ were identified, and the statistical significance was evaluated using Fisher's exact test. There were 70 associated SNPs whose –log₁₀p value over 16 were selected to be further analyzed. The distribution of these SNPs appeared a tight cluster, which consisted of 14 associated SNPs within a 396 kb region on chromosome A09. Our evidence indicates that this region contains a major quantitative trait locus (QTL). Finally, two associated SNPs from this region were mapped on a major QTL region.

Conclusions/Significance

70 associated SNPs were discovered and a major QTL for rapeseed pod shatter-resistance was found on chromosome A09 using our novel method. The associated SNP markers were used for mapping of the QTL, and may be useful for improving pod shatter-resistance in rapeseed through marker-assisted selection and map-based cloning. This approach will accelerate the discovery of major QTLs and the cloning of functional genes for important agronomic traits in rapeseed and other crop species.

A candidate gene-based association study of tocopherol content and composition in rapeseed (Brassica napus)

Rapeseed (Brassica napus L.) is the most important oil crop of temperate climates. Rapeseed oil contains tocopherols, also known as vitamin E, which is an indispensable nutrient for humans and animals due to its antioxidant and radical scavenging abilities. Moreover, tocopherols are also important for the oxidative stability of vegetable oils. Therefore, seed oil with increased tocopherol content or altered tocopherol composition is a target for breeding. We investigated the role of nucleotide variations within candidate genes from the tocopherol biosynthesis pathway. Field trials were carried out with 229 accessions from a worldwide B. napus collection which was divided into two panels of 96 and 133 accessions. Seed tocopherol content and composition were measured by HPLC. High heritabilities were found for both traits, ranging from 0.62 to 0.94. We identified polymorphisms by sequencing selected regions of the tocopherol genes from the 96 accession panel. Subsequently, we determined the population structure (Q) and relative kinship (K) as detected by genotyping with genome-wide distributed SSR markers. Association studies were performed using two models, the structure-based GLM + Q and the PK-mixed model. Between 26 and 12 polymorphisms within two genes (BnaX.VTE3.a, BnaA.PDS1.c) were significantly associated with tocopherol traits. The SNPs explained up to 16.93% of the genetic variance for tocopherol composition and up to 10.48% for total tocopherol content. Based on the sequence information we designed CAPS markers for genotyping the 133 accessions from the second panel. Significant associations with various tocopherol traits confirmed the results from the first experiment. We demonstrate that the polymorphisms within the tocopherol genes clearly impact tocopherol content and composition in B. napus seeds. We suggest that these nucleotide variations may be used as selectable markers for breeding rapeseed with enhanced tocopherol quality.

SNP discovery by amplicon sequencing and multiplex SNP genotyping in the allopolyploid species Brassica napus

Oilseed rape (Brassica napus) is an allotetraploid species consisting of two genomes, derived from B. rapa (A genome) and B. oleracea (C genome). The presence of these two genomes makes single nucleotide polymorphism (SNP) marker identification and SNP analysis more challenging than in diploid species, as for a given locus usually two versions of a DNA sequence (based on the two ancestral genomes) have to be analyzed simultaneously during SNP identification and analysis. One hundred amplicons derived from expressed sequence tag (ESTs) were analyzed to identify SNPs in a panel of oilseed rape varieties and within two sister species representing the ancestral genomes. A total of 604 SNPs were identified, averaging one SNP in every 42 bp. It was possible to clearly discriminate SNPs that are polymorphic between different plant varieties from SNPs differentiating the two ancestral genomes. To validate the identified SNPs for their use in genetic analysis, we have developed Illumina GoldenGate assays for some of the identified SNPs. Through the analysis of a number of oilseed rape varieties and mapping populations with GoldenGate assays, we were able to identify a number of different segregation patterns in allotetraploid oilseed rape. The majority of the identified SNP markers can be readily used for genetic mapping, showing that amplicon sequencing and Illumina GoldenGate assays can be used to reliably identify SNP markers in tetraploid oilseed rape and to convert them into successful SNP assays that can be used for genetic analysis.

Mapping of quantitative trait loci and development of allele-specific markers for seed weight in Brassica napus

Seed weight is an important component of grain yield in oilseed rape (Brassica napus L.), but the genetic basis for the important quantitative trait is still not clear. In order to identify the genes for seed weight in oilseed rape, QTL mapping for thousand seed weight (TSW) was conducted with a doubled haploid (DH) population and an F(2) population. A complete linkage map of the DH population was constructed using 297 simple sequence repeat (SSR) markers. Among nine TSW QTLs detected, two major QTLs, TSWA7a and TSWA7b, were stably identified across years and collectively explained 27.6-37.9% of the trait variation in the DH population. No significant epistatic interactions for TSW detected in the DH population indicate that the seed weight variation may be primarily attributed to additive effects. The stability and significance of TSWA7a and TSWA7b were further validated in the F(2) population with different genetic backgrounds. By cloning BnMINI3a and BnTTG2a, two B. napus homologous genes to Arabidopsis thaliana, allele-specific markers were developed for TSWA5b and TSWA5c, two TSW QTLs on A5, respectively. The importance of the major and minor QTLs identified was further demonstrated by analysis of the allelic effects on TSW in the DH population.