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Keywords:

  • Brassica napus;
  • genomics;
  • next-generation sequencing;
  • SNP discovery;
  • breeding

Abstract

  1. Top of page
  2. Abstract
  3. Brassica Genome Sequencing
  4. Global Transcriptome Analysis
  5. SNPs, The Molecular Marker Jewel of the Genomics Era
  6. NGS-Based SNP Discovery in Brassica napus
  7. Surveying DNA Sequence Variation in Brassica napus Using Sequence-Capture Technologies
  8. Data Analysis and SNP Selection
  9. Genetic Diversity and Genome-Wide Association Studies
  10. A Public, High-Density Brassica napus SNP Array
  11. Towards ‘Predictive Breeding’
  12. Summary/Outlook
  13. Acknowledgements
  14. References

With 2 figures and 1 table

Abstract

High-throughput genomics technologies today offer unprecedented possibilities for gene discovery, complex trait analysis by genome-wide association studies, global gene expression analyses, genomic selection and predictive breeding strategies. Dissection of the complex Brassica napus genome using mapping-by-sequencing techniques provides a powerful bridge between genetic maps and genome sequences. The completed sequence of the Brassica rapa A genome and the expected forthcoming publication of the C genome (Brassica oleracea) will greatly accelerate the release of public reference sequences for B. napus (genome AC). Dramatically falling DNA costs for targeted or genomic resequencing and the availability of a new, high-density B. napus single-nucleotide polymorphism (SNP) array open the way for considerably more efficient mining and exploitation of genetic variation within the primary and secondary gene pools of B. napus. In this review, we outline some of the most significant recent advances in high-throughput genomics of Brassica crops and their potential impact on germplasm development and breeding of oilseed rape and canola in the coming years and decades.

Molecular genetics has become one of the world’s most important biotechnologies during the past decade. Ultra-dense array technologies and next-generation sequencing (NGS) platforms (see LaFrombiose 2009, Metzker 2010, Kaur et al. 2011, Glenn 2011 for recent reviews) have revolutionized this field in just a few years, driven by unprecedented recent advances in nanotechnology, optical imaging and computing. Present and future genomics technologies are set to have long-term and far-reaching consequences in many facets of society, ranging from medicinal genetics and environmental diagnostics through to food technology, agriculture and even crop breeding. Illumination of the genome sequences and species-wide genetic diversity of major crop plants will help greatly to elucidate the genetic background of complex traits and broaden gene pools as a basis for more successful breeding. In addition, the availability of sequence information will help researchers to pinpoint the areas of the genome that are most affected by the environment, for example by targeting epigenetic or environmentally sensitive quantitative trait loci (QTL) like those investigated by Long et al. (2011) and Zhu et al. (2012), respectively, in oilseed rape. This potentially opens the way to design seeds that will better withstand fluctuating climatic conditions or abiotic stress.

Oilseed rape (Brassica napus L.), known in North America and Australia as canola (from Canadian Oil; Thomas 1984), is a close relative of the model crucifer Arabidopsis thaliana and of numerous important cruciferous vegetable, oilseed and forage species. Today one of the world’s primary oilseed crops, B. napus has been subject to considerable improvement by breeders since the recent spontaneous origin of this modern allopolyploid species around the middle of the last millennium (Iniguez Luy and Federico 2011). The breeding history of modern double-low (00) varieties with low seed erucic acid and glucosinolate contents involved considerable genetic bottlenecks, however (see Friedt and Snowdon 2010), meaning that current breeding pools are decidedly narrow especially in Europe, North America and Australia, three of the major growing areas (Diers and Osborn 1994, Becker et al. 1995, Hasan et al. 2006, Chen et al. 2008, Bus et al. 2011). As a particularly dramatic case in point, Cowling (2007) estimated the effective population size among Australian varieties during the first three decades of canola breeding in Australia at merely Ne = 11. This presents breeders a difficult challenge of increasing genetic diversity to cope with climatic changes or reduced inputs, while at the same time needing to maintain and improve present yield and quality standards.

In China, the world’s largest producer of oilseed rape, a substantial increase in genetic diversity of available B. napus gene pools via marker-assisted genome introgressions from related species was used to raise hybrid vigour and intersubgenomic heterosis (Xiao et al. 2010, Zou et al. 2010, Chen et al. 2011, Mei et al. 2011). In the face of increased demand for vegetable oils and biofuel under changing environmental conditions and emerging production constraints, identification and implementation of novel germplasm in breeding programs is an ongoing goal for improvement of abiotic and biotic stress tolerance, nutrient efficiency, seed and meal quality, seed yield and heterosis. Falk (2010) demonstrated the high value of implementing new genetic diversity into a narrow breeding programme by classical breeding methods.

This process can potentially be optimized and streamlined with the help of genome-wide markers to help breeders re-expand genetic variation in the species without compromising previous selections for domestication, adaptation (particularly flowering time) or seed quality (Cowling et al. 2009, 2011). The integration of new diversity by conventional breeding necessarily involves generation and detailed phenotyping of large populations in which only few individuals can be expected to carry all positive allelic combinations for the large number of loci contributing to all desired traits. On the other hand, experience from animal breeding has demonstrated that it is potentially feasible to replace expensive and time-consuming phenotyping in breeding populations through implementation of statistical models to calculate genomic estimated breeding values (GEBVs). The GEBV can forthwith be used to predict the expected performance of a non-phenotyped individual (Meuwissen et al. 2001). As genotyping and sequencing costs continue to fall, there is little doubt that genomic selection, which has meanwhile begun to revolutionize animal breeding (Hayes et al. 2009, Bagnato and Rosati 2012), will also play an ever-increasing role in plant breeding (Jannink et al. 2010). An important consideration in applying genomic selection to plant breeding is the need to effectively capture and interpret information on genotype by environment (G × E) interactions into selection models. Using data from canola breeding trials, Beeck et al. (2010) and Cullis et al. (2010) demonstrated significant improvements in prediction of total, additive and non-additive genetic values for oil content and grain yield through consideration of pedigree information and G × E interaction, respectively. Pedigree selection in multilocation trials was found in those studies to greatly improve the efficiency of selection for total genetic value and estimated breeding value in the presence of the strong G × E interactions expected for expression of yield and oil content, for example. These authors suggest methods for fitting factor-analytical mixed models with pedigree information as a basis for the application of genomic selection in oilseed rape and canola breeding. A further prerequisite for the implementation of genomic selection in oilseed rape breeding is an availability of sufficient genome-wide single-nucleotide polymorphism (SNP) markers, along with high-throughput platforms for cost-effective SNP screening in breeding populations.

Brassica Genome Sequencing

  1. Top of page
  2. Abstract
  3. Brassica Genome Sequencing
  4. Global Transcriptome Analysis
  5. SNPs, The Molecular Marker Jewel of the Genomics Era
  6. NGS-Based SNP Discovery in Brassica napus
  7. Surveying DNA Sequence Variation in Brassica napus Using Sequence-Capture Technologies
  8. Data Analysis and SNP Selection
  9. Genetic Diversity and Genome-Wide Association Studies
  10. A Public, High-Density Brassica napus SNP Array
  11. Towards ‘Predictive Breeding’
  12. Summary/Outlook
  13. Acknowledgements
  14. References

The A genome sequence of Brassica rapa, recently published in Nature Genetics by the multinational B. rapa Genome Sequencing Project Consortium (The Brassica rapa Genome Sequencing Project Consortium 2011), represents a huge milestone towards understanding and harnessing genetic variation within Brassica gene pools for more targeted breeding. Among other things, the B. rapa sequence, together with a high-density SNP map published by Bancroft et al. (2011), enabled a microlinear alignment of full-length Brassica chromosomes to the genome of the model crucifer A. thaliana. On the one hand, this confirmed the segmental structure of Brassica genomes that was shown by previous comparative mapping studies, in particular the seminal work of Parkin et al. (2005) and the integrated B. napus comparative map published by Wang et al. (2011). On the other hand, a closer look at the microsyntenic relationships between Brassica genomic sequences and A. thaliana chromosomes has also revealed a high complexity of micro-scale genome rearrangements (Town et al. 2006, The Brassica rapa Genome Sequencing Project Consortium 2011). Early, optimistic expectations of the extent to which conserved synteny to the A. thaliana genome might aid in functional gene mapping and QTL cloning in B. napus (e.g. Snowdon and Friedt 2004) have thus been proven somewhat naïve in hindsight.

The B. rapa genome sequencing project was initiated in 2003 to sequence the smaller, less complex genome of the two diploid progenitor genomes of B. napus. The development of the first massively parallel NGS technologies a few years later (Shendure et al. 2005, Margulies et al. 2005; see Mardis 2008 for an early review) greatly accelerated the completion of the B. rapa sequence. Combining long, robust and physically anchored Sanger sequence reads with high-depth NGS data enabled more accurate assembly of the draft reference genome released in August 2011. A proprietary whole-genome sequence for the amphidiploid B. napus was reported already in press releases by Bayer Crop Science in 2009 (http://tinyurl.com/28cbe6v); however, at the time of writing, no public B. napus genome sequence is yet available. This is set to change in the very near future, however, with completion of the A genome expected to help consortia with members in China, Australia, North America and Europe to complete robust assemblies for the C genome of Brassica oleracea and for different B. napus genotypes within the next year.

In their first description of multiplex polymerase colony (‘polony’) sequencing, Shendure et al. (2005) described a cost-per-base reduction of one-ninth compared to conventional Sanger sequencing. In just the past few years, the constant logarithmic decay seen in the cost of conventional Sanger sequencing prior to the commercialization of NGS platforms has been eclipsed by an exponential reduction in per-base sequencing prices (Fig. 1). Today it is theoretically possible to resequence multiple B. napus genomes in a single sequencing run for only a few thousand dollars per genome. As sequencing costs continue to drop during the next couple of years, we can expect a comprehensive atlas of B. napus chromosome structure variation and DNA sequence diversity to emerge. This will provide new insight into the complex polyploid nature of the B. napus genome, the origins and distinguishing features of the modern crop forms and the extent of useful variation for breeding purposes. Furthermore, comprehensive species-wide genomic sequence data represent the ultimate resource for development of robust and effective molecular markers.

image

Figure 1.  Development of DNA sequencing prices during the past two decades. Approximate costs of sequencing per DNA base are given on the Y-axis in a logarithmic scale. Figure adapted and updated from the US National Human Genome Research Institute, http://www.genome.gov/sequencingcosts

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Table 1 gives an outline of current and planned B. napus genome sequencing activities; up-to-date information can be obtained from the brassica.info website: http://www.brassica.info/resource/sequencing.php. For example, the public–private CanSeq consortium (see http://canseq.ca/) is generating a draft B. napus sequence for the canola line DH12075, using B. rapa and B. oleracea as reference sequences. This B. napus assembly will be used as a template for resequencing of a further 16 B. napus accessions. A similar approach is being used by an international consortium led by Chinese researchers, who are beginning with assemblies from B. rapa and B. oleracea to generate a reference B. napus sequence from the Chinese oilseed rape cultivar ‘Zhongshuang 11’. In France, a DH line from the winter oilseed rape variety ‘Darmor Bzh’ is also being used to generate a B. napus reference assembly. Integration of data from these projects is expected to result in release of a public B. napus reference genome sequence by mid 2012. Resequencing of the well-characterized mapping parents ‘Tapidor’ and ‘Ningyou’ is in progress in China, while a newly established public–private consortium in Germany intends to resequence the genomes of 51 genetically diverse B. napus founder lines of nested-association populations (R. Snowdon, personal communication). These were selected to broadly represent gene sequence diversity in a geographically and genetically diverse set of over 500 B. napus accessions, including Asian and Eastern European origins along with swede and vegetable types and a considerable collection of resynthesized B. napus accessions from different A and C genome donors. The intention is to broadly cover genetic diversity present both within and beyond the present oilseed rape and canola breeding pools.

Table 1.   Examples of completed, ongoing and planned Brassica napus genome sequencing and resequencing projects (for updates see http://www.brassica.info/resource/sequencing.php)
AccessionTypeSequencing aimPlatformConsortium/CountryContact
DH12075Spring canolaB. napus reference assemblyIllumina, 454CANSEQIsobel Parkin. Agriculture and Agri-Food Canada
Darmor DHWinter oilseed rapeB. napus reference assemblyIllumina, 454, SangerFranceBoulos Chaloub. INRA, Évry, France
Zhongshuang 11Spring oilseed rapeB. napus reference assemblyIllumina, 454ChinaShengyi Liu, CAAS, Wuhan, China
Tapidor DHWinter oilseed rapeB. napus reference assemblyIllumina, 454China, UKJinling Meng, Huazhong Agric. Univ., Wuhan, China
Ningyou 7Chinese oilseed rapeB. napus reference assemblyIllumina, 454China, UKJinling Meng, Huazhong Agric. Univ., Wuhan, China
51 linesDiverse B. napus, nested-association mapping founder linesWhole-genome resequencingIlluminaGermanyRod Snowdon, Justus Liebig University, Giessen, Germany
123 linesDiverse B. napusLeaf transcriptomesIlluminaUKIan Bancroft, John Innes Centre, Norwich, UK
517Species-wide B. napus diversity collectionRestriction-associated DNA (RAD)IlluminaASSYST/GermanyBenjamin Stich, Max Planck Institute for Breeding Research, Cologne, Germany
Express 617, V8 plus 94 ExV8-DH linesWinter oilseed rape mapping populationRADIlluminaGermany, ChinaRod Snowdon, Justus Liebig University, Giessen, Germany
500 linesDiverse winter-type B. napusSequence capture of 40+ flowering regulatory genesIlluminaGermanyRod Snowdon, Justus Liebig University, Giessen, Germany
10 inbred lines6 winter and 4 springSequence capture of meta-quantitative trait loci regions454, IlluminaChile, CanadaFederico Iniguez-Luy, Agri aquaculture Nutritional Genomic Center (CGNA), Chile

Global Transcriptome Analysis

  1. Top of page
  2. Abstract
  3. Brassica Genome Sequencing
  4. Global Transcriptome Analysis
  5. SNPs, The Molecular Marker Jewel of the Genomics Era
  6. NGS-Based SNP Discovery in Brassica napus
  7. Surveying DNA Sequence Variation in Brassica napus Using Sequence-Capture Technologies
  8. Data Analysis and SNP Selection
  9. Genetic Diversity and Genome-Wide Association Studies
  10. A Public, High-Density Brassica napus SNP Array
  11. Towards ‘Predictive Breeding’
  12. Summary/Outlook
  13. Acknowledgements
  14. References

The more that is known about DNA sequence variation, the more we have begun to realize that not only sequence polymorphisms but particularly also differences in gene regulation play an enormously important role in complex trait expression. Complex networks have been suggested to regulate phenomena including heterosis, yield and seed quality in B. napus (Basunanda et al. 2010, Shi et al. 2009, 2011, Feng et al. 2011). Global gene expression profiling offers the opportunity for detailed insight into gene expression networks involved in trait variation and can help to pinpoint regulatory genes underlying such variation. In recent years, different microarray platforms for Brassica species have been developed, providing commercially available tools for high-throughput transcriptome analysis. Trick et al. (2009a) used over 800 000 Brassica expressed sequence tags (ESTs) to develop a 2 × 104k probe 60mer oligonucleotide expression microarray on the Agilent Technologies® platform. Using this array, Hammond et al. (2011) mapped regulatory loci controlling gene networks in B. rapa associated with phosphorous use efficiency, for example. An alternative microarray format (4 × 44k probes) on the same platform has been used for example by Schiebold et al. (2010) for quantitative gene expression analyses of laser-microdissected B. napus seed tissues, enabling a first view into compartmentalization of gene expression associated with metabolite biosynthesis in oilseed rape embryos. A high-density Affymetrix GeneChip®Brassica exon array was developed by Love et al. (2010) for whole-transcript gene expression profiling. Although array-based techniques are presently still somewhat cheaper than whole-transcriptome profiling using RNA sequencing methods, digital gene expression (DGE) methods can already be employed as a cost-effective alternative for global transcriptome profiling with large sample numbers. The LongSAGE method used by Obermeier et al. (2009) for transcriptome-wide gene expression profiling during B. napus seed development is well suited to sequencing platforms that output extremely high numbers of genotype-barcoded short reads for quantification of expression. DGE-based global transcriptome analyses are also suitable and cost-effective methods for expression QTL (eQTL) and gene expression network analysis in segregating DH populations.

Bancroft et al. (2011) estimated transcript abundance in RNAseq data in B. napus by counting reads per kbp per million aligned reads along the lengths of chromosomes, demonstrating that even relatively low-coverage mRNA sequencing is able to provide semi-quantitative data on relative expression levels of Brassica unigenes. Using advanced sample multiplexing techniques on ultrahigh-throughput DNA sequencers, it is today feasible to obtain accurate quantification of expression even for low-abundance transcripts. Furthermore, NGS-based transcriptome analyses can overcome limitations of microarray techniques in distinguishing between expression of homologous and paralogous gene copies (Parkin et al. 2010). These represent potentially convincing advantages over current array-based expression profiling methods.

SNPs, The Molecular Marker Jewel of the Genomics Era

  1. Top of page
  2. Abstract
  3. Brassica Genome Sequencing
  4. Global Transcriptome Analysis
  5. SNPs, The Molecular Marker Jewel of the Genomics Era
  6. NGS-Based SNP Discovery in Brassica napus
  7. Surveying DNA Sequence Variation in Brassica napus Using Sequence-Capture Technologies
  8. Data Analysis and SNP Selection
  9. Genetic Diversity and Genome-Wide Association Studies
  10. A Public, High-Density Brassica napus SNP Array
  11. Towards ‘Predictive Breeding’
  12. Summary/Outlook
  13. Acknowledgements
  14. References

Single nucleotide polymorphism markers have become the marker of choice for high-throughput genetic analysis in human, animal and plant genetics and have revolutionized the field of medical diagnosis (International HapMap Consortium, 2007). They are extremely helpful at defining the individual (e.g. varieties or parental lines in crops) by establishing a haplotype map (Rafalski 2002, McCarthy et al. 2008). SNPs are extremely prolific and their implicit simplicity makes them extremely useful as genetic markers. SNP markers can be mapped to specific chromosomal regions in segregating populations or in turn be used in associative mapping studies of non-bi-parental populations (International HapMap Consortium, 2007, Ganal et al. 2009, Kaur et al. 2011).

In crop species, the use of SNPs is still relatively limited compared to their application in human genetics and animal breeding, but even in crops interest is growing rapidly (Ganal et al. 2009, Deschamps and Campbell 2010, Kaur et al. 2011). To be broadly useful, SNP discovery must be performed in genetically diverse germplasm or on a population basis, which can be costly (Yu and Buckler 2006, Das et al. 2008). However, NGS opens broad new avenues for the discovery of SNPs in crop plants including Brassica crops.

NGS-Based SNP Discovery in Brassica napus

  1. Top of page
  2. Abstract
  3. Brassica Genome Sequencing
  4. Global Transcriptome Analysis
  5. SNPs, The Molecular Marker Jewel of the Genomics Era
  6. NGS-Based SNP Discovery in Brassica napus
  7. Surveying DNA Sequence Variation in Brassica napus Using Sequence-Capture Technologies
  8. Data Analysis and SNP Selection
  9. Genetic Diversity and Genome-Wide Association Studies
  10. A Public, High-Density Brassica napus SNP Array
  11. Towards ‘Predictive Breeding’
  12. Summary/Outlook
  13. Acknowledgements
  14. References

Increased competition in commercial breeding and demand for constantly improving new varieties has driven crop breeders to seek cheaper and more efficient tools to tag regions of crop genomes that are associated with agronomical and nutritional traits (Collard and Mackill 2008). The most powerful approaches to achieve this aim involve use of high-throughput SNP screening, creating a demand for SNP discovery in all major crops and many minor crops as well. The power of NGS technologies for SNP discovery has been demonstrated in numerous crop species with more or less complex genomes, including B. napus.

While resequencing on a whole-genome scale has only recently become financially feasible, reduced-representation approaches including long-read sequencing of anchored ESTs (Parkin et al. 2010), whole-transcriptome profiling (Trick et al. 2009b, Bancroft et al. 2011), 454 amplicon sequencing (Gholami et al. 2012) or array-based sequence capture have all been demonstrated as highly effective strategies for mid- to large-scale SNP discovery in genetically diverse B. napus accessions. Whole-genome and reduced-representation resequencing projects (e.g. Table 1; see also http://www.brassica.info/resource/sequencing.php) will not only enable identification of genome-wide SNPs on a species-wide level, but will also allow the comprehensive description of gene presence–absence polymorphisms and structural chromosome rearrangements resulting from ancient and recent polyploidy in B. napus and its progenitor species.

Trick et al. (2009b) described the use of the Solexa sequencing platform to sequence 20 million ESTs from each of two oilseed rape cultivars (‘Tapidor’ and ‘Ningyou’). From these, they identified 23 330–41 593 putative SNPs between these two lines, although some 80% of these were hemi-SNPs between homologous or paralogous loci. Computational tools were developed to assess potential polymorphisms from the NGS-generated sequences using a set reference sequence comprising approximately 94 000 unigenes from different Brassica species. In a different study, Durstewitz et al. (2010) combined Sanger sequencing of candidate gene amplicons with the Illumina GoldenGate genotyping assay in order to discover SNP markers across a diverse set of B. napus germplasm and the parental A and C genomes of B. rapa and B. oleracea, respectively. A high proportion of the identified SNPs (more than 75%) were informative and could be used in breeding programmes. Although this study was limited in the number of SNP markers identified, it highlighted the tremendous potential that exists for this type of molecular marker in Brassica molecular breeding.

Simultaneous discovery and mapping of genome-wide sequence polymorphisms in non-genic regions is also possible using reduced-representation sequencing of libraries generated from restriction-associated DNA (RAD) as described by Baird et al. (2008), for example. By targeting only a small, user-definable proportion of the genome (e.g. 1–5%) and utilizing high-level multiplexing, it is feasible to identify large quantities of locus-specific SNP and indel polymorphisms in relatively large populations in a single sequencing experiment. Different groups are using the RAD technology to identify genome-wide SNPs in B. napus diversity collections for association analyses or in segregating populations for ‘mapping-by-sequencing’ (see Table 1).

Surveying DNA Sequence Variation in Brassica napus Using Sequence-Capture Technologies

  1. Top of page
  2. Abstract
  3. Brassica Genome Sequencing
  4. Global Transcriptome Analysis
  5. SNPs, The Molecular Marker Jewel of the Genomics Era
  6. NGS-Based SNP Discovery in Brassica napus
  7. Surveying DNA Sequence Variation in Brassica napus Using Sequence-Capture Technologies
  8. Data Analysis and SNP Selection
  9. Genetic Diversity and Genome-Wide Association Studies
  10. A Public, High-Density Brassica napus SNP Array
  11. Towards ‘Predictive Breeding’
  12. Summary/Outlook
  13. Acknowledgements
  14. References

The rich history of QTL mapping for various agronomical and nutritional traits in oilseed rape B. napus (e.g. Mayerhofer et al. 2005, Parkin et al. 2005, Udall et al. 2005, 2006, Quijada et al. 2006, Radoev et al. 2008, Iniguez-Luy et al. 2009, Kramer et al. 2009, Basunanda et al. 2010) makes it tempting to investigate sequence variation (SNPs, indels and presence–absence variation) in specific QTL-targeted genomic regions. In particular, meta-QTL for key complex traits including yield are highly interesting target regions for investigation of useful DNA sequence variation. Hybridization-based sequence-capture technologies were established for targeted resequencing of genomic loci in humans (Albert et al. 2007, Hodges et al. 2007, Okou et al. 2007), but more recently have been applied successfully for reduced-representation resequencing in maize (Fu et al. 2010) and for SNP discovery in B. napus (J.-P. Pichon and colleagues, conference presentation: http://www.intl-pag.org/18/abstracts/W92_PAGXVIII_643.html). A great advantage of sequence-capture techniques in polyploid crops like B. napus is that homologous loci can be captured by the same capture oligonucleotides and resolved later based on interlocus polymorphisms. This means that locus-specific assays are not necessary, even for multilocus targets which can be very difficult to assay with conventional sequencing methods. The NimbleGen sequence-capture microarray technology (Roche NimbleGen, Madison, WI, USA), which can capture target regions >500 kbp, is being used to target the B. napus meta-QTL regions shown in Fig. 2 related to yield and other complex traits (M.L. Federico, F. Iniguez Luy, I. Parkin and A. Sharpe, personal communication). In another example, the SureSelect target enrichment technology from Agilent Technologies (Santa Clara, CA, USA), which can target smaller regions down to 200 kbp, is being used to survey sequence variation in homologous copies of a large set of regulatory genes involved in development and flowering. The identified sequence variants will be compared to phenotypic variation for relevant traits including seedling vigour, abiotic stress tolerance/avoidance and yield (R. Snowdon and S. Schießl, personal communication).

image

Figure 2.  Genetic map integration and localization of meta-quantitative trait loci (QTL) for traits of agronomical and nutritional interest in Brassica napus. Map integration was conducted according to common molecular markers and parental lines used in three different mapping studies (Parkin et al. 2005, Udall et al. 2006, Iniguez-Luy et al. 2009). QTL location was inferred from relative map position as described by Parkin et al. (2005), Udall et al. (2006), Mayerhofer et al. (2005), Radoev et al. (2008), Kramer et al. (2009) and Basunanda et al. (2010). By sequence capture of chromosome regions corresponding to important meta-QTL for yield and quality-related traits in genetically diverse germplasm, it is possible to capture relevant allelic variation for targeted enrichment of the depleted B. napus gene pool

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Data Analysis and SNP Selection

  1. Top of page
  2. Abstract
  3. Brassica Genome Sequencing
  4. Global Transcriptome Analysis
  5. SNPs, The Molecular Marker Jewel of the Genomics Era
  6. NGS-Based SNP Discovery in Brassica napus
  7. Surveying DNA Sequence Variation in Brassica napus Using Sequence-Capture Technologies
  8. Data Analysis and SNP Selection
  9. Genetic Diversity and Genome-Wide Association Studies
  10. A Public, High-Density Brassica napus SNP Array
  11. Towards ‘Predictive Breeding’
  12. Summary/Outlook
  13. Acknowledgements
  14. References

In the face of high-throughput genomics technologies, an emerging challenge for crop researchers is to harness suitable computational and bioinformatic tools to deal with increasing complexities and quantities of genomic data. Particular attention is required to decipher and make meaningful use of duplicated DNA sequences and SNP variants among the homoeologous Brassica genomes. A key to discovery of SNP markers from NGS data resides in the accurate alignment of the interrogated genotype data with a suitable reference genome. In the case of B. napus, alignment to genomic reference sequences for both the A and C genomes is vital to efficiently discriminate between orthologous and paralogous loci and their corresponding haplo- and hemi-SNPs.

In the complex polyploid B. napus genome, such alignments will inevitably uncover multiple copies of any given sequence; hence, the stringency used to map sequence reads from different genotypes becomes crucial for the identification and elimination of potential homologous and paralogous SNPs. However, stringent mapping of NGS reads from each interrogated genotype against A and C genome references generally allows an average of 80% of the NGS reads to map to the correct diploid reference genome. This allows generation of a framework data set that can be further manipulated to filter potential non-informative markers (e.g. hemi-SNPs). By selection of SNPs with high-quality scores that show high allele frequencies in genetically diverse populations and possess unique flanking sequences (taking into account introns and non-transcribed sequences), it is possible to obtain a robust set of markers from which large numbers of spatially distributed, high-quality SNPs can be selected for downstream analyses with dedicated assays or arrays. Putative informative, locus-specific haplo-SNPs can be further classified by their genomic context (distribution of interrogated region, coding vs. non-coding regions, transition vs. transversion SNPs, etc.).

Genetic Diversity and Genome-Wide Association Studies

  1. Top of page
  2. Abstract
  3. Brassica Genome Sequencing
  4. Global Transcriptome Analysis
  5. SNPs, The Molecular Marker Jewel of the Genomics Era
  6. NGS-Based SNP Discovery in Brassica napus
  7. Surveying DNA Sequence Variation in Brassica napus Using Sequence-Capture Technologies
  8. Data Analysis and SNP Selection
  9. Genetic Diversity and Genome-Wide Association Studies
  10. A Public, High-Density Brassica napus SNP Array
  11. Towards ‘Predictive Breeding’
  12. Summary/Outlook
  13. Acknowledgements
  14. References

A major challenge facing plant breeders in coming years will be to link rapidly expanding quantities of genomic data to relevant phenotypic data, particularly for the complex traits that are of most interest to breeders. Improving abiotic stress tolerance, nutrient efficiency, heterosis, oil content and seed yield in the face of changing environments and emerging production constraints remain challenging goals in this respect. In the space of just a few years, genotyping costs have been rapidly overtaken by phenotyping costs as the most important bottleneck in efforts to understand and breed for complex traits. Overcoming this ‘phenotyping bottleneck’ requires innovative new approaches to analyse and dissect complex traits and associate their components with the underlying genetic mechanisms.

A first step towards achieving this goal is defining and generating suitable plant populations that adequately represent the phenotypic and genetic diversity present in the species, then using these to associate detailed phenotype data with patterns of genetic diversity. Recently, a large, public B. napus diversity set (see Bus et al. 2011) has been established within the international ERANET Plant Genomics consortium ASSYST (see http://www.erapg.org/everyone/16790/18613/19533/19534). To our knowledge, the ASSYST diversity set is one of the most extensive public B. napus diversity collections to date, incorporating fixed or founder lines from other previous collections including the European RESGEN B. napus core collection (Lühs et al. 2003), the United Kingdom B. napus Diversity Fixed Foundation Set (http://www.brassica.info/resource/plants/diversity_sets.php), and a diverse set of modern, double-low quality European winter oilseed rape inbred lines described by Ecke et al. (2010). The ASSYST diversity set has been genotyped with genome-wide simple-sequence repeat (SSR) markers to evaluate genetic diversity and linkage disequilibrium (Bus et al. 2011) and the accessions are currently being screened with a B. napus 6000-SNP array (I. Parkin and A. Sharpe, Saskatoon, Canada, personal communication). By making the population and SNP data publicly available, a highly valuable resource should be established for multitrait genome-wide association studies (GWAS) in B. napus. The ASSYST population has so far been grown in field trials at multiple years and locations in Europe, China and Chile, as well as under controlled conditions, and the data are being used for GWAS of developmental characters, flowering time, seed quality, root development and other agronomical traits.

Power to detect small phenotypic effects contributed by rare alleles is generally low in conventional GWAS approaches. To overcome this, Yu et al. (2008) proposed the concept of nested-association mapping (NAM) populations and used these techniques to generate a NAM population for maize (McMullen et al. 2009). Similar immortal NAM populations for B. napus, comprising half-sibling populations from founder lines with maximal genetic diversity, will represent a highly valuable resource for breeders over coming decades. Genotyping using highly dense SNP arrays and haplotype reconstruction based on genomic sequences of parental lines will provide a basis for high-power detection and identification of genic and non-genic sequence variants associated with complex traits. Different public–private consortia in Germany, France and Canada have recognized the benefit of such materials and are beginning with efforts to develop suitable populations for NAM approaches. When related to yield-relevant traits for assignment of GEBVs to genome-wide SNP markers, such populations should form the basis for genomic selection approaches (Heffner et al. 2009, Jannink et al. 2010) in oilseed rape and canola.

A Public, High-Density Brassica napus SNP Array

  1. Top of page
  2. Abstract
  3. Brassica Genome Sequencing
  4. Global Transcriptome Analysis
  5. SNPs, The Molecular Marker Jewel of the Genomics Era
  6. NGS-Based SNP Discovery in Brassica napus
  7. Surveying DNA Sequence Variation in Brassica napus Using Sequence-Capture Technologies
  8. Data Analysis and SNP Selection
  9. Genetic Diversity and Genome-Wide Association Studies
  10. A Public, High-Density Brassica napus SNP Array
  11. Towards ‘Predictive Breeding’
  12. Summary/Outlook
  13. Acknowledgements
  14. References

In 2011, an international Brassica SNP consortium was established in collaboration with the company Illumina Inc. (San Diego, CA, USA) to generate a public, high-density Brassica Infinium SNP array for high-throughput germplasm screening. The consortium array, containing between 50 000 and 54 000 SNPs designed to function well in Brassica A or C genome species, is scheduled for availability in the second quarter of 2012. The SNP content was derived from DNA sequence contributions by academic and commercial partners from Australia, China, Europe, North and South America. This array will be useful not only for GWAS but also for breeders as a tool for comprehensive genome-wide screens of elite germplasm and breeding pools. Valuable phenotype knowledge provided by decades of pedigree and performance information provides breeders with historical insight into breeding values. In combination with genome-wide SNP data, this will open exciting new opportunities for genomic selection and pool development. A frequently asked questions (FAQ) document outlining the B. napus SNP consortium and with further details on the consortium array can be obtained from Illumina or from the authors of this article.

Towards ‘Predictive Breeding’

  1. Top of page
  2. Abstract
  3. Brassica Genome Sequencing
  4. Global Transcriptome Analysis
  5. SNPs, The Molecular Marker Jewel of the Genomics Era
  6. NGS-Based SNP Discovery in Brassica napus
  7. Surveying DNA Sequence Variation in Brassica napus Using Sequence-Capture Technologies
  8. Data Analysis and SNP Selection
  9. Genetic Diversity and Genome-Wide Association Studies
  10. A Public, High-Density Brassica napus SNP Array
  11. Towards ‘Predictive Breeding’
  12. Summary/Outlook
  13. Acknowledgements
  14. References

Access to Brassica genome sequences, genome-wide SNPs and new genotyping technologies will almost certainly lead to new methods and tools for breeding of major crops, including oilseed rape and canola (Tester and Langridge 2010). One potentially achievable aim is to use detailed genomic and transcriptomic information for a particular individual to predict how it (or its offspring) will perform under a variety of different agronomical and environmental scenarios. The continuous advent of newer and more effective DNA sequencing and global gene expression profiling technologies (Schadt et al. 2010) is making it feasible to study large numbers of genes and their regulatory interactions for a wide variety of individuals simultaneously. An ability to relate global gene expression and sequence profiles to phenotypic variation will bring breeders closer to the challenge of facing environmental changes more readily and effectively. By implementing genomic information, we should become increasingly able to target favourable alleles that have relatively small effects on quantitative traits. Such alleles are seldom identified in conventional breeding. Statistical models that identify favourable cross-combinations associated with improved performance can be derived from metabolite profiles, gene expression profiles and/or genome-wide SNP markers. Such models are the key to future implementation of genomic selection strategies (Jannink et al. 2010) or to better predict hybrid performance (Riedelsheimer et al. 2012).

Summary/Outlook

  1. Top of page
  2. Abstract
  3. Brassica Genome Sequencing
  4. Global Transcriptome Analysis
  5. SNPs, The Molecular Marker Jewel of the Genomics Era
  6. NGS-Based SNP Discovery in Brassica napus
  7. Surveying DNA Sequence Variation in Brassica napus Using Sequence-Capture Technologies
  8. Data Analysis and SNP Selection
  9. Genetic Diversity and Genome-Wide Association Studies
  10. A Public, High-Density Brassica napus SNP Array
  11. Towards ‘Predictive Breeding’
  12. Summary/Outlook
  13. Acknowledgements
  14. References

Genomic data from B. napus and other Brassica species is providing breeders with powerful new tools to characterize genetic diversity and assist the introduction of useful variation into narrow elite populations. High-density genome-wide SNP arrays provide a means to potentially more efficiently identify, through the use of genomic selection, cross-combinations and/or progenies with the desired quality characteristics and high yield potential. As the cost of SNP discovery and high-throughput genotyping continues to drop, there is an ever-growing gap between genotype and phenotyping data availability, however. This raises an urgent need for concerted efforts to develop and characterize immortal populations containing genetically diverse germplasm of interest for breeding. More detailed phenotyping of such materials for complex traits in multiple environments will be a key to better understanding and utilizing such diversity for breeding of tomorrow’s oilseed rape and canola varieties, with the necessary adaptability to produce high and stable yields in fluctuating environments.

References

  1. Top of page
  2. Abstract
  3. Brassica Genome Sequencing
  4. Global Transcriptome Analysis
  5. SNPs, The Molecular Marker Jewel of the Genomics Era
  6. NGS-Based SNP Discovery in Brassica napus
  7. Surveying DNA Sequence Variation in Brassica napus Using Sequence-Capture Technologies
  8. Data Analysis and SNP Selection
  9. Genetic Diversity and Genome-Wide Association Studies
  10. A Public, High-Density Brassica napus SNP Array
  11. Towards ‘Predictive Breeding’
  12. Summary/Outlook
  13. Acknowledgements
  14. References
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