**11. Molecular dissection of qualitative and quantitative resistance loci**

Molecular markers have been applied to identify loci associated with resistance to *L. macu‐ lans*, which relies on the availability of sequence variation among parental genotypes of mapping populations and diversity panels. Several genotyping methods based upon DNA hybridisation such as Restriction Fragment Length Polymorphism (RFLP) and Diversity Arrays Technology (DArT); PCR-based techniques such as Randomly Amplified Polymorphic DNA (RAPD), Simple Sequence Repeats (SSR) and Amplified Fragment Length Polymor‐ phism (AFLP); Sequence-related amplified polymorphism (SRAP); and sequence-based analysis such as Single Nucleotide Polymorphism (SNP); Restriction site-associated DNA, (RAD) and Genotyping by Sequencing (GBS) have been developed for molecular analyses [81, 127 - 136]. RFLP, RAPD, SSR, SRAP and AFLP markers have all been used to map loci for resistance to *L. maculans* (Table 1). New marker technologies such as DArT, 60K SNP Infinium array, RAD and GBS are currently being developed and applied for mapping of blackleg resistance loci. These high-throughput approaches are expected to complement or replace lowthroughput marker assays that were used previously to facilitate genetic and physical mapbased cloning of resistance genes.

Loci for resistance to *L. maculans* have been mapped using linkage/QTL mapping and associ‐ ation mapping approaches [32, 74, 82, 86, 137] using structured (F2, doubled-haploid (DH) and backcross) and unstructured (diversity sets/breeding lines) populations (Table 1). Bulked Segregant Analysis approach, used for the first time [138], is particularly useful when a limited number of traits are to be mapped and resources (money and time) required for extensive genotyping are limited [81]. Whole-genome analysis has been used to locate both qualitative and quantitative loci associated with resistance to *L. maculans* [32, 86]. Generally, it requires the framework linkage map of all 19 chromosomes (linkage groups) for linkage (QTL) analysis.

#### **11.1. Qualitative resistance**

The majority of genes for resistance to *L. maculans* have been genetically mapped with molecular markers (Table 1) on chromosomes A1, A2, A6, A7, A10, B3, B4 and B8 in *Brassica species: B. rapa, B. napus, B juncea* and *B. nigra* [31, 32, 45, 68-70, 99]. None of the race-specific genes have been mapped on the C genome yet. Previous linkage mapping studies revealed that at least five resistance genes (*Rlm1, Rlm3, Rlm4, Rlm7* and *Rlm9)* are localised in a cluster within a 35 cM genomic region on chromosome A7 [32, 45, 64-68, 74, 82]. This genomic region showed extensive inter- and intra-genomic duplications, as well as intra-chromosomal tandem duplications [140]. Whether some of these *R-*genes are allelic remains unknown. For example, it was concluded that at least four resistance genes *Rlm3*, *Rlm4*, *Rlm7*, and *Rlm9* could corre‐ spond to a cluster of tightly linked genes, to a unique gene with different alleles, or to a combination of these two hypotheses. However, *Rlm1* has been shown to be linked with *Rlm3* but is not allelic [74].

A major gene named *LmFr1* controlling adult plant resistance to blackleg was tagged in the DH population from French cultivar Cresor (resistant to *L. maculans*) and Westar (susceptible to *L. maculans*) with RFLP markers [64]. Similar study [65] mapped loci for blackleg resistance in a DH population from Major/Stellar and found that genetic control of resistance vary with inoculation techniques. A major gene designated as *LEM1* was mapped to linkage group 6 based on qualitative/quantitative scores of the interaction phenotype on inoculated cotyledons with a single ascospore-derived PG2 isolate, PHW1245. However, four other putative QTL for resistance were also identified on linkage groups LG8, LG17 and pair 4. This study further showed that none of the QTL that were associated with resistance at the seedling and stem stage had a significant effect in conferring resistance in the field. This may be attributed due to use of different pathogen population (PHW 1245 in cotyledon and stem experiments and natural *L. maculans* population in field experiment). The *Rpg3Dun* gene was mapped in an F2 population from Westar/Dunkeld and identified a suite of SCAR markers that showed cosegregation with resistance to *L. maculans* [81]. Recently, the whole genome average interval mapping approach was applied to localise both qualitative and quantitative trait loci control‐ ling blackleg resistance [32] in a DH population derived from the Australian *B. napus* vernal‐ isation responsive cultivars, Skipton and Ag-Spectrum. Marker regression analyses revealed that at least fourteen genomic regions were associated with blackleg resistance, explaining 19.5% to 88.9% of genotypic variation. A major qualitative locus, designated *RlmSkipton (Rlm4),* was mapped on chromosome A7, within 0.8 cM of the SSR marker BRMS075 (Table 1).

Genomic regions of chromosome A10 harbours *Rlm2*, which has been shown to be the most common *R*-gene in winter *B. napus* varieties, such as Samourai, Eurol, Bristol, Symbol, Andol, Kintol, Akamar, Colvert, Synergy, and Tapidor, [41]. Chromosome A10 also harbours *LepR2*, *LepR3* and *BLMR2* genes derived from *B. rapa* subsp. *sylvestris* sources [31, 69, 70]. *LepR1* and *LepR2* were mapped on chromosomes A2 and A10, respectively with RFLP markers [31]. Genetic analysis revealed that both genes confer resistance independently and therefore are additive. *LepR1* was a dominant nuclear gene while *LepR2* was an incompletely dominant gene. This study further showed that *LepR1* generally conferred a higher level of resistance than *LepR2*. Both genes exhibited race-specific interactions with pathogen isolates.

The blackleg resistance gene *Rlm6* has been identified on B genome chromosome 8 [47]. *Rlm6* has been successfully introgressed to *B. napus* (AACC) from *B. juncea* (AABB) [47, 141] and provides excellent resistance to *L. maculans* isolates [58], though this gene has not yet been deployed in commercial cultivars [47, 58].

#### **11.2. Quantitative resistance**

sustainable canola production, especially in areas where *L. maculans* populations are highly

**11. Molecular dissection of qualitative and quantitative resistance loci**

Molecular markers have been applied to identify loci associated with resistance to *L. macu‐ lans*, which relies on the availability of sequence variation among parental genotypes of mapping populations and diversity panels. Several genotyping methods based upon DNA hybridisation such as Restriction Fragment Length Polymorphism (RFLP) and Diversity Arrays Technology (DArT); PCR-based techniques such as Randomly Amplified Polymorphic DNA (RAPD), Simple Sequence Repeats (SSR) and Amplified Fragment Length Polymor‐ phism (AFLP); Sequence-related amplified polymorphism (SRAP); and sequence-based analysis such as Single Nucleotide Polymorphism (SNP); Restriction site-associated DNA, (RAD) and Genotyping by Sequencing (GBS) have been developed for molecular analyses [81, 127 - 136]. RFLP, RAPD, SSR, SRAP and AFLP markers have all been used to map loci for resistance to *L. maculans* (Table 1). New marker technologies such as DArT, 60K SNP Infinium array, RAD and GBS are currently being developed and applied for mapping of blackleg resistance loci. These high-throughput approaches are expected to complement or replace lowthroughput marker assays that were used previously to facilitate genetic and physical map-

Loci for resistance to *L. maculans* have been mapped using linkage/QTL mapping and associ‐ ation mapping approaches [32, 74, 82, 86, 137] using structured (F2, doubled-haploid (DH) and backcross) and unstructured (diversity sets/breeding lines) populations (Table 1). Bulked Segregant Analysis approach, used for the first time [138], is particularly useful when a limited number of traits are to be mapped and resources (money and time) required for extensive genotyping are limited [81]. Whole-genome analysis has been used to locate both qualitative and quantitative loci associated with resistance to *L. maculans* [32, 86]. Generally, it requires the framework linkage map of all 19 chromosomes (linkage groups) for linkage (QTL) analysis.

The majority of genes for resistance to *L. maculans* have been genetically mapped with molecular markers (Table 1) on chromosomes A1, A2, A6, A7, A10, B3, B4 and B8 in *Brassica species: B. rapa, B. napus, B juncea* and *B. nigra* [31, 32, 45, 68-70, 99]. None of the race-specific genes have been mapped on the C genome yet. Previous linkage mapping studies revealed that at least five resistance genes (*Rlm1, Rlm3, Rlm4, Rlm7* and *Rlm9)* are localised in a cluster within a 35 cM genomic region on chromosome A7 [32, 45, 64-68, 74, 82]. This genomic region showed extensive inter- and intra-genomic duplications, as well as intra-chromosomal tandem duplications [140]. Whether some of these *R-*genes are allelic remains unknown. For example, it was concluded that at least four resistance genes *Rlm3*, *Rlm4*, *Rlm7*, and *Rlm9* could corre‐ spond to a cluster of tightly linked genes, to a unique gene with different alleles, or to a

diverse and rapidly evolving.

98 Plant Breeding from Laboratories to Fields

based cloning of resistance genes.

**11.1. Qualitative resistance**

The genetic basis of quantitative resistance has been investigated only in limited *B. napus* cultivars such as in Darmor; a derivative of Jet Neuf [119, 137, 142]. However, a number of DH populations have recently been utilised for identification of loci for quantitative resistance under field conditions [32, 86, 143], and are currently being validated (Raman *et al*., unpub‐ lished, Larkan *et al*., unpublished). Thirteen quantitative trait loci (QTL) on 10 linkage groups associated with quantitative field resistance to *L. maculans* were identified in a DH population from Darmor-*bzh*/Yudal [87]. Their detection was dependent upon phenotypic method used; seven QTL for mean disease index and six QTL for per cent survival (percentage of lost plants due to canker) and were also dependant on growing environment (year of evaluation). However, only four of the QTL were stable across experiments. These QTL accounted from 23% to 57% of the genotypic variation (Table 2). The unexplained variation was described due to non-detected additive QTL, G x E interaction and incomplete map coverage. This study further showed that resistance to *L. maculans* is influenced with growth habit. For example, one QTL, located close to a dwarf gene (*bzh*), was detected with a very strong effect, masking the detection of other QTL. This study further showed that these dwarfing genes also affect other traits such as earliness, and glucoinsolate content.

In order to validate the stability of QTL for field resistance to *L. maculans*, QTL were mapped and characterised in F2:3 population from Darmor (resistant)/Samourai (susceptible) revealing only four QTL on LG3, LG11 and DY5 and DS6 that were consistent in Darmor/Yudal and Darmor/Samourai populations [143]. This study found that the genetic background and inoculum pressure are the major factors of the QTL instability and therefore suggested that QTL mapping must be carried out separately for each population. The genomic regions carrying the most consistent resistance QTL in Darmor do not correspond to the two regions on N7 (A7) and N10 (A10) identified as carrying race specific resistance genes to *L. maculans* [74]. The position of *Rlm2* on N10 (A10) corresponds to a QTL identified for adult plant resistance in the Darmor/Samourai DH population [88]. The cultivar Samourai carries both the resistance allele at this QTL and *Rlm2*. Since it has been reported that no French isolates of *L. maculans* carry *AvrLm2* [34], two hypotheses were proposed to explain this co-location; either the *Rlm2* gene has a residual effect at the adult plant stage, similar to that suggested in other pathosystems, or genes linked to *Rlm2* are responsible for part of variation for resistance at this QTL [99].

QTL for blackleg resistance were identified in four mapping populations derived from the crosses Caiman/Westar10, Camberra/Westar10, AVSapphire/Westar10 and Rainbow/AVSapphire [86]. Multiple QTLs were identified accounting for 13–33% of phenotypic variance. A recent study [32] identified seven significant QTL associated with blackleg resistance, scored on the basis of internal disease score, on chromosomes A2, A9, A10, C1, C2, C3 and C6 in a DH population derived from Skipton/Ag-Spectrum. The genotypic variation explained by the individual QTL ranged from 5% to 24.5%. Both parents contributed the alleles for blackleg resistance. This study showed poor correlation between canker lesion scores over the two years (2009, 2010). Some of the genomic regions for blackleg resistance may be the same as reported previously that have been identified using both classical QTL and association mapping approaches [31, 69, 87, 137, 144, 145]. The conservation of QTL between Australian and French studies is interesting and suggests the non-specificity of these QTL, irrespective of the environment, genetic background and G x E interactions [32]. However, it is possible that some of the original donor gene sources in French and Australian parental lines used for mapping resistance genes may be the same.

The majority of mapping populations used to map blackleg resistance genes in *B. napus* so far have been comparatively small (Table 1). The development of a high density map utilising larger populations, comprising several hundred to thousands lines, will allow for the precise mapping of resistance loci. Stability of QTL resistance needs to be tested in different environ‐ ments. Although QTL mapping studies provide comprehensive information on the nature of inheritance, location, magnitude and allelic effects of QTL, much of the information tends to be 'population' specific. In biparental (structured) populations, generally two alleles at each locus are sampled and therefore trait-marker association may not be highly relevant to diverse genetic backgrounds. The validation of trait-marker association is necessary before their use for routine marker-assisted breeding (MAS). Association mapping can be utilised for investi‐ gating linkage disequilibrium close to loci of interest in a diverse germplasm [145-149] and therefore offers an alternative to linkage and QTL mapping. This approach has been applied in determining and confirming the markers located within the QTL associated with resistance to *L. maculans* previously identified in Darmor and established their usefulness in MAS [137]. A diverse set of an oilseed rape collection, comprised of 128 lines showing a large spectrum of responses to infection by *L. maculans*, was characterised using 72 SSR and other markers. At least 61 marker alleles were found to be associated with resistance to stem canker. Some of these markers were associated with previously identified QTL, which confirms their useful‐ ness in MAS. Markers located in regions not harbouring previously identified QTL were also associated with resistance, suggesting that new QTL or allelic variants are present in the collection [137]. Genome-wide association based on 1513 markers enabled identification and validation of genomic loci associated with blackleg resistance. This study detected significant marker - race-specific blackleg resistance associations (P<0.01) at the seedling and adult plant stages. Loci for resistance were located on chromosomes A1, A2, A3, A5, A6, A7, A10, C1, and C2. Both studies suggested that association mapping is an efficient approach for identifying novel loci/alleles associated with blackleg resistance in diverse germplasm [137, 142]. Superior molecular marker allele(s) associated with resistance to *L. maculans* may be captured by canola breeding programs. Molecular markers associated with seedling and stem canker resistance will help identify accessions carrying desirable alleles and facilitate QTL introgression to develop elite germplasm having new gene/allele combinations for blackleg resistance [32].

#### **12. Host** *R***-gene cloning and candidate gene analysis**

associated with quantitative field resistance to *L. maculans* were identified in a DH population from Darmor-*bzh*/Yudal [87]. Their detection was dependent upon phenotypic method used; seven QTL for mean disease index and six QTL for per cent survival (percentage of lost plants due to canker) and were also dependant on growing environment (year of evaluation). However, only four of the QTL were stable across experiments. These QTL accounted from 23% to 57% of the genotypic variation (Table 2). The unexplained variation was described due to non-detected additive QTL, G x E interaction and incomplete map coverage. This study further showed that resistance to *L. maculans* is influenced with growth habit. For example, one QTL, located close to a dwarf gene (*bzh*), was detected with a very strong effect, masking the detection of other QTL. This study further showed that these dwarfing genes also affect

In order to validate the stability of QTL for field resistance to *L. maculans*, QTL were mapped and characterised in F2:3 population from Darmor (resistant)/Samourai (susceptible) revealing only four QTL on LG3, LG11 and DY5 and DS6 that were consistent in Darmor/Yudal and Darmor/Samourai populations [143]. This study found that the genetic background and inoculum pressure are the major factors of the QTL instability and therefore suggested that QTL mapping must be carried out separately for each population. The genomic regions carrying the most consistent resistance QTL in Darmor do not correspond to the two regions on N7 (A7) and N10 (A10) identified as carrying race specific resistance genes to *L. maculans* [74]. The position of *Rlm2* on N10 (A10) corresponds to a QTL identified for adult plant resistance in the Darmor/Samourai DH population [88]. The cultivar Samourai carries both the resistance allele at this QTL and *Rlm2*. Since it has been reported that no French isolates of *L. maculans* carry *AvrLm2* [34], two hypotheses were proposed to explain this co-location; either the *Rlm2* gene has a residual effect at the adult plant stage, similar to that suggested in other pathosystems, or genes linked to *Rlm2* are responsible for part of variation for resistance at

QTL for blackleg resistance were identified in four mapping populations derived from the crosses Caiman/Westar10, Camberra/Westar10, AVSapphire/Westar10 and Rainbow/AVSapphire [86]. Multiple QTLs were identified accounting for 13–33% of phenotypic variance. A recent study [32] identified seven significant QTL associated with blackleg resistance, scored on the basis of internal disease score, on chromosomes A2, A9, A10, C1, C2, C3 and C6 in a DH population derived from Skipton/Ag-Spectrum. The genotypic variation explained by the individual QTL ranged from 5% to 24.5%. Both parents contributed the alleles for blackleg resistance. This study showed poor correlation between canker lesion scores over the two years (2009, 2010). Some of the genomic regions for blackleg resistance may be the same as reported previously that have been identified using both classical QTL and association mapping approaches [31, 69, 87, 137, 144, 145]. The conservation of QTL between Australian and French studies is interesting and suggests the non-specificity of these QTL, irrespective of the environment, genetic background and G x E interactions [32]. However, it is possible that some of the original donor gene sources in French and Australian parental lines used for mapping

other traits such as earliness, and glucoinsolate content.

100 Plant Breeding from Laboratories to Fields

this QTL [99].

resistance genes may be the same.

At least 20 *R*-genes and several allele variants and haplotypes of cloned *R*-genes have been identified in plants [151-158]. Molecular analyses revealed that these genes belong to large multiple gene families, which encode nucleotide binding site- leucine–rich repeats (NBS-LRRs), serine-threonine-kinases, leucine zipper and protein kinase domains, and toll/inter‐ leukin-1 receptor domains [159-164]. These genes are often clustered in many plant species including crops such as rice, maize and soybean and transduce the hypersensitive response to defend against pathogen attack [164-167]. At least 30 CC-NBS-LRR and TIR-NBS-LRR nonredundant genes have been identified in *B. rapa* [167]. Two major gene clusters for resistance to *L. maculans* exist on chromosomes A7 [74] and A10 [31, 69, 70], along with other genes dispersed on different chromosomes. It is possible that some of these *R*-genes may represent to multiple copies of the same functional gene. A recent study has shown that at least eight functional copies of *FLOWERING TIME LOCUS C* (*FLC*) exist within *B. napus* [6] which may modulate flowering time and other functions in different cultivars [168].

In *B. napus*, only few studies aimed at characterizing the genes underlying the resistance to *L. maculans* have been attempted. The recent cloning of the first functional *B. napus* resistance gene *LepR3* revealed a receptor-like protein responsible for conferring resistance to *AvrLm1 L. maculans* isolates [79]. Resistance genes effective against *L. maculans* have also been cloned in *A. thaliana* [169-171], which encode Toll interleukin-1 receptor-nucleotide binding (TIR-NB) or TIR-NB-LRR class proteins. Based on the synteny between *B. napus* and *A. thaliana*, it was deduced that several *B. napus* resistance genes are localised in a region of A7 (N7) that corresponds to the chromosome segment on *Arabidopsis* chromosome 1 which harbours *RLM1*Col [139, 167]. However, a recent report detailing the gene responses to *L. maculans* infections suggests very different responses in *B. napus* and *A. thaliana* [172]. Both salicylic acid and ethylene signaling was triggered in *B. napus*, possibly due to the hemibiotrophic nature of the infection. This stands in contrast to the JA signaling observed in *A. thaliana*, suggesting *L. maculans* is acting as a necrotroph during infection of susceptible *A. thaliana* lines. Since many *R*-genes are conserved and share sequence similarity, degenerated primers based on conserved motifs of *R*-genes have also been used to localise potential resistance gene loci in Brassica species such as *B. oleracea* (on chromosomes C1 (O1), C4 (O4), C8 (O8) and C9 (O9) and *B. napus* on linkage groups LG1a, LG1b, LG2, LG5, LG8, LG12, LG13, LG14, LG15 and LG18 [173, 174]. However their association with loci controlling resistance to *L. maculans* have not yet been established/validated.

In order to clone genes controlling blackleg resistance in *B. napus* population, high resolution mapping of *LmR1* and *ClmR1* loci was performed using 2500 backcross lines from two crosses between PSA12 and Shiralee, and PSA12 and Cresor, respectively [140], and reported that both resistance loci are located in a highly duplicated genomic region on chromosome A7. This region contained several genes encoding protein kinases or LRR domains. It is reported that the SCAR marker (BN204) that showed cosegregation with *RpgDun* locus for resistance to *L. maculans* is derived from a region showing 92% amino acid identity with the defense-related gene serine threonine 20 (ste-20) protein kinase of *Arabidopsis thaliana* [81]. A proteomic approach has also been utilised to understand gene expression in response to *L. maculans* infection [176]. However, candidacy of any of these genes has not yet been reported.

Recently an alternative approach for identifying candidate *R*-genes has been employed based on genomics [177]. Next-generation massively parallel sequencing platforms such as the Roche 454 genome sequencer FLX instrument, the Illumina Genome Analyser (HiSeq), and the ABI SOLiD System have revolutionized genome sequencing by providing high throughput and cost-effective high coverage sequencing [179-182] and has enabled much quicker identification of candidate genes [178]. Molecular markers associated with *RlmSkipton* (*Rlm4*) locus in the DH population from Skipton/Ag-Spectrum were aligned with the complete genome sequence *B. rapa* as reported in [32]. Eighteen candidate genes, designated as *BLR1-18* with disease resistance characteristics, several of which were clustered around a region syntenic to *Rlm4.*

Among candidates, *BLR2* and *BLR11* were the promising candidates for *Rlm4*-mediated resistance [178]. High resolution mapping and gene sequencing of different sources of *L. maculans* resistance will allow for a better understanding of the structural organisation and function of *R*-genes. Recently, the reference genome of *B. rapa* has been published [182] and genomes of *B. oleracea*, *B. nigra* and *B. napus* are expected to be published in coming years. Resequencing of whole genomes of known blackleg-resistant genotypes will allow identification of genetic variation between individuals, which can provide molecular genetic markers and insights into gene function [183]. Sequencing of different *R*-genes and understanding their function will also enable us to manipulate resistance to *L. maculans*, as genes with different specificities can be created.

dispersed on different chromosomes. It is possible that some of these *R*-genes may represent to multiple copies of the same functional gene. A recent study has shown that at least eight functional copies of *FLOWERING TIME LOCUS C* (*FLC*) exist within *B. napus* [6] which may

In *B. napus*, only few studies aimed at characterizing the genes underlying the resistance to *L. maculans* have been attempted. The recent cloning of the first functional *B. napus* resistance gene *LepR3* revealed a receptor-like protein responsible for conferring resistance to *AvrLm1 L. maculans* isolates [79]. Resistance genes effective against *L. maculans* have also been cloned in *A. thaliana* [169-171], which encode Toll interleukin-1 receptor-nucleotide binding (TIR-NB) or TIR-NB-LRR class proteins. Based on the synteny between *B. napus* and *A. thaliana*, it was deduced that several *B. napus* resistance genes are localised in a region of A7 (N7) that corresponds to the chromosome segment on *Arabidopsis* chromosome 1 which harbours *RLM1*Col [139, 167]. However, a recent report detailing the gene responses to *L. maculans* infections suggests very different responses in *B. napus* and *A. thaliana* [172]. Both salicylic acid and ethylene signaling was triggered in *B. napus*, possibly due to the hemibiotrophic nature of the infection. This stands in contrast to the JA signaling observed in *A. thaliana*, suggesting *L. maculans* is acting as a necrotroph during infection of susceptible *A. thaliana* lines. Since many *R*-genes are conserved and share sequence similarity, degenerated primers based on conserved motifs of *R*-genes have also been used to localise potential resistance gene loci in Brassica species such as *B. oleracea* (on chromosomes C1 (O1), C4 (O4), C8 (O8) and C9 (O9) and *B. napus* on linkage groups LG1a, LG1b, LG2, LG5, LG8, LG12, LG13, LG14, LG15 and LG18 [173, 174]. However their association with loci controlling resistance to *L. maculans* have not yet been

In order to clone genes controlling blackleg resistance in *B. napus* population, high resolution mapping of *LmR1* and *ClmR1* loci was performed using 2500 backcross lines from two crosses between PSA12 and Shiralee, and PSA12 and Cresor, respectively [140], and reported that both resistance loci are located in a highly duplicated genomic region on chromosome A7. This region contained several genes encoding protein kinases or LRR domains. It is reported that the SCAR marker (BN204) that showed cosegregation with *RpgDun* locus for resistance to *L. maculans* is derived from a region showing 92% amino acid identity with the defense-related gene serine threonine 20 (ste-20) protein kinase of *Arabidopsis thaliana* [81]. A proteomic approach has also been utilised to understand gene expression in response to *L. maculans*

infection [176]. However, candidacy of any of these genes has not yet been reported.

Recently an alternative approach for identifying candidate *R*-genes has been employed based on genomics [177]. Next-generation massively parallel sequencing platforms such as the Roche 454 genome sequencer FLX instrument, the Illumina Genome Analyser (HiSeq), and the ABI SOLiD System have revolutionized genome sequencing by providing high throughput and cost-effective high coverage sequencing [179-182] and has enabled much quicker identification of candidate genes [178]. Molecular markers associated with *RlmSkipton* (*Rlm4*) locus in the DH population from Skipton/Ag-Spectrum were aligned with the complete genome sequence *B. rapa* as reported in [32]. Eighteen candidate genes, designated as *BLR1-18* with disease resistance characteristics, several of which were clustered around a region syntenic to *Rlm4.*

modulate flowering time and other functions in different cultivars [168].

established/validated.

102 Plant Breeding from Laboratories to Fields
