Multienvironment QTL analysis delineates a major locus associated with homoeologous exchanges for water-use efficiency and seed yield in canola.

Canola varieties exhibit variation in drought avoidance and drought escape traits, reflecting adaptation to water-deficit environments. Our understanding of underlying genes and their interaction across environments in improving crop productivity is limited. A doubled haploid population was analysed to identify quantitative trait loci (QTL) associated with water-use efficiency (WUE) related traits. High WUE in the vegetative phase was associated with low seed yield. Based on the resequenced parental genome data, we developed sequence-capture-based markers and validated their linkage with carbon isotope discrimination (Δ13 C) in an F2 population. RNA sequencing was performed to determine the expression of candidate genes underlying Δ13 C QTL. QTL contributing to main and QTL × environment interaction effects for Δ13 C and yield were identified. One multiple-trait QTL for Δ13 C, days to flower, plant height, and seed yield was identified on chromosome A09. Interestingly, this QTL region overlapped with a homoeologous exchange (HE) event, suggesting its association with the multiple traits. Transcriptome analysis revealed 121 significantly differentially expressed genes underlying Δ13 C QTL on A09 and C09, including in HE regions. Sorting out the negative relationship between vegetative WUE and seed yield is a priority. Genetic and genomic resources and knowledge so developed could improve canola WUE and yield.

Modelling of gene loss propensity in the pangenomes of three Brassica species suggests different mechanisms between polyploids and diploids.

Plant genomes demonstrate significant presence/absence variation (PAV) within a species; however, the factors that lead to this variation have not been studied systematically in Brassica across diploids and polyploids. Here, we developed pangenomes of polyploid Brassica napus and its two diploid progenitor genomes B. rapa and B. oleracea to infer how PAV may differ between diploids and polyploids. Modelling of gene loss suggests that loss propensity is primarily associated with transposable elements in the diploids while in B. napus, gene loss propensity is associated with homoeologous recombination. We use these results to gain insights into the different causes of gene loss, both in diploids and following polyploidization, and pave the way for the application of machine learning methods to understanding the underlying biological and physical causes of gene presence/absence.

A copia-like retrotransposon insertion in the upstream region of the SHATTERPROOF1 gene, BnSHP1.A9, is associated with quantitative variation in pod shattering resistance in oilseed rape.

Seed loss resulting from pod shattering is a major constraint in production of oilseed rape (Brassica napus L.). However, the molecular mechanisms underlying pod shatter resistance are not well understood. Here, we show that the pod shatter resistance at quantitative trait locus qSRI.A9.1 is controlled by one of the B. napus SHATTERPROOF1 homologs, BnSHP1.A9, in a doubled haploid population generated from parents designated R1 and R2 as well as in a diverse panel of oilseed rape. The R1 maternal parental line of the doubled haploid population carried the allele for shattering at qSRI.A9.1, while the R2 parental line carried the allele for shattering resistance. Quantitative RT-PCR showed that BnSHP1.A9 was expressed specifically in flower buds, flowers, and developing siliques in R1, while it was not expressed in any tissue of R2. Transgenic plants constitutively expressing either of the BnSHP1.A9 alleles from the R1 and R2 parental lines showed that both alleles are responsible for pod shattering, via a mechanism that promotes lignification of the enb layer. These findings indicated that the allelic differences in the BnSHP1.A9 gene per se are not the causal factor for quantitative variation in shattering resistance at qSRI.A9.1. Instead, a highly methylated copia-like long terminal repeat retrotransposon insertion (4803 bp) in the promotor region of the R2 allele of BnSHP1.A9 repressed the expression of BnSHP1.A9, and thus contributed to pod shatter resistance. Finally, we showed a copia-like retrotransposon-based marker, BnSHP1.A9R2, can be used for marker-assisted breeding targeting the pod shatter resistance trait in oilseed rape.

GWAS hints at pleiotropic roles for FLOWERING LOCUS T in flowering time and yield-related traits in canola.

BACKGROUND: Transition to flowering at the right time is critical for local adaptation and to maximize grain yield in crops. Canola is an important oilseed crop with extensive variation in flowering time among varieties. However, our understanding of underlying genes and their role in canola productivity is limited. RESULTS: We report our analyses of a diverse GWAS panel (300-368 accessions) of canola and identify SNPs that are significantly associated with variation in flowering time and response to photoperiod across multiple locations. We show that several of these associations map in the vicinity of FLOWERING LOCUS T (FT) paralogs and its known transcriptional regulators. Complementary QTL and eQTL mapping studies, conducted in an Australian doubled haploid population, also detected consistent genomic regions close to the FT paralogs associated with flowering time and yield-related traits. FT sequences vary between accessions. Expression levels of FT in plants grown in field (or under controlled environment cabinets) correlated with flowering time. We show that markers linked to the FT paralogs display association with variation in multiple traits including flowering time, plant emergence, shoot biomass and grain yield. CONCLUSIONS: Our findings suggest that FT paralogs not only control flowering time but also modulate yield-related productivity traits in canola.

Co-linearity and divergence of the A subgenome of Brassica juncea compared with other Brassica species carrying different A subgenomes.

BACKGROUND: There are three basic Brassica genomes (A, B, and C) and three parallel sets of subgenomes distinguished in the diploid Brassica (i.e.: B. rapa, A(r)A(r); B. nigra, B(ni)B(ni); B. oleracea, C(o)C(o)) and the derived allotetraploid species (i.e.: B. juncea, A(j)A(j)B(j)B(j); B. napus, A(n)A(n)C(n)C(n); B. carinata, B(c)B(c)C(c)C(c)). To understand subgenome differentiation in B. juncea in comparison to other A genome-carrying Brassica species (B. rapa and B. napus), we constructed a dense genetic linkage map of B. juncea, and conducted population genetic analysis on diverse lines of the three A-genome carrying Brassica species using a genotyping-by-sequencing approach (DArT-seq). RESULTS: A dense genetic linkage map of B. juncea was constructed using an F2 population derived from Sichuan Yellow/Purple Mustard. The map included 3329 DArT-seq markers on 18 linkage groups and covered 1579 cM with an average density of two markers per cM. Based on this map and the alignment of the marker sequences with the physical genome of Arabidopsis thaliana, we observed strong co-linearity of the ancestral blocks among the different A subgenomes but also considerable block variation. Comparative analyses at the level of genome sequences of B. rapa and B. napus, and marker sequence anchored on the genetic map of B. juncea, revealed a total of 30 potential inversion events across large segments and 20 potential translocation events among the three A subgenomes. Population genetic analysis on 26 accessions of the three A genome-carrying Brassica species showed that the highest genetic distance were estimated when comparing A(j)-A(n) than between A(n)-A(r) and A(j)-A(r) subgenome pairs. CONCLUSIONS: The development of the dense genetic linkage map of B. juncea with informative DArT-seq marker sequences and availability of the reference sequences of the A(r), and A(n)C(n) genomes allowed us to compare the A subgenome structure of B. juncea (A(j)) . Our results suggest that strong co-linearity exists among the three A Brassica genomes (A(r), A(n) and A(j)) but with apparent subgenomic variation. Population genetic analysis on three A-genome carrying Brassica species support the idea that B. juncea has distinct genomic diversity, and/or evolved from a different A genome progenitor of B. napus.

Multi-environment QTL studies suggest a role for cysteine-rich protein kinase genes in quantitative resistance to blackleg disease in Brassica napus.

BACKGROUND: Resistance to the blackleg disease of Brassica napus (canola/oilseed rape), caused by the hemibiotrophic fungal pathogen Leptosphaeria maculans, is determined by both race-specific resistance (R) genes and quantitative resistance loci (QTL), or adult-plant resistance (APR). While the introgression of R genes into breeding material is relatively simple, QTL are often detected sporadically, making them harder to capture in breeding programs. For the effective deployment of APR in crop varieties, resistance QTL need to have a reliable influence on phenotype in multiple environments and be well defined genetically to enable marker-assisted selection (MAS). RESULTS: Doubled-haploid populations produced from the susceptible B. napus variety Topas and APR varieties AG-Castle and AV-Sapphire were analysed for resistance to blackleg in two locations over 3 and 4 years, respectively. Three stable QTL were detected in each population, with two loci appearing to be common to both APR varieties. Physical delineation of three QTL regions was sufficient to identify candidate defense-related genes, including a cluster of cysteine-rich receptor-like kinases contained within a 49 gene QTL interval on chromosome A01. Individual L. maculans isolates were used to define the physical intervals for the race-specific R genes Rlm3 and Rlm4 and to identify QTL common to both field studies and the cotyledon resistance response. CONCLUSION: Through multi-environment QTL analysis we have identified and delineated four significant and stable QTL suitable for MAS of quantitative blackleg resistance in B. napus, and identified candidate genes which potentially play a role in quantitative defense responses to L. maculans.

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.

SNP markers-based map construction and genome-wide linkage analysis in Brassica napus.

An Illumina Infinium array comprising 5306 single nucleotide polymorphism (SNP) markers was used to genotype 175 individuals of a doubled haploid population derived from a cross between Skipton and Ag-Spectrum, two Australian cultivars of rapeseed (Brassica napus L.). A genetic linkage map based on 613 SNP and 228 non-SNP (DArT, SSR, SRAP and candidate gene markers) covering 2514.8 cM was constructed and further utilized to identify loci associated with flowering time and resistance to blackleg, a disease caused by the fungus Leptosphaeria maculans. Comparison between genetic map positions of SNP markers and the sequenced Brassica rapa (A) and Brassica oleracea (C) genome scaffolds showed several genomic rearrangements in the B. napus genome. A major locus controlling resistance to L. maculans was identified at both seedling and adult plant stages on chromosome A07. QTL analyses revealed that up to 40.2% of genetic variation for flowering time was accounted for by loci having quantitative effects. Comparative mapping showed Arabidopsis and Brassica flowering genes such as Phytochrome A/D, Flowering Locus C and agamous-Like MADS box gene AGL1 map within marker intervals associated with flowering time in a DH population from Skipton/Ag-Spectrum. Genomic regions associated with flowering time and resistance to L. maculans had several SNP markers mapped within 10 cM. Our results suggest that SNP markers will be suitable for various applications such as trait introgression, comparative mapping and high-resolution mapping of loci in B. napus.

Constructing a dense genetic linkage map and mapping QTL for the traits of flower development in Brassica carinata.

KEY MESSAGE: An integrated dense genetic linkage map was constructed in a B. carinata population and used for comparative genome analysis and QTL identification for flowering time. An integrated dense linkage map of Brassica carinata (BBCC) was constructed in a doubled haploid population based on DArT-Seq(TM) markers. A total of 4,031 markers corresponding to 1,366 unique loci were mapped including 639 bins, covering a genetic distance of 2,048 cM. We identified 136 blocks and islands conserved in Brassicaceae, which showed a feature of hexaploidisation representing the suggested ancestral crucifer karyotype. The B and C genome of B. carinata shared 85 % of commonly conserved blocks with the B genome of B. nigra/B. juncea and 80 % of commonly conserved blocks with the C genome of B. napus, and shown frequent structural rearrangements such as insertions and inversions. Up to 24 quantitative trait loci (QTL) for flowering and budding time were identified in the DH population. Of these QTL, one consistent QTL (qFT.B4-2) for flowering time was identified in all of the environments in the J block of the B4 linkage group, where a group of genes for flowering time were aligned in A. thaliana. Another major QTL for flowering time under a winter-cropped environment was detected in the E block of C6, where the BnFT-C6 gene was previously localised in B. napus. This high-density map would be useful not only to reveal the genetic variation in the species with QTL analysis and genome sequencing, but also for other applications such as marker-assisted selection and genomic selection, for the African mustard improvement.

Identification of QTLs associated with resistance to Phomopsis pod blight (Diaporthe toxica) in Lupinus albus.

Phomopsis blight in Lupinus albus is caused by a fungal pathogen, Diaporthe toxica. It can invade all plant parts, leading to plant material becoming toxic to grazing animals, and potentially resulting in lupinosis. Identifying sources of resistance and breeding for resistance remains the best strategy for controlling Phomopsis and reducing lupinosis risks. However, loci associated with resistance to Phomopsis blight have not yet been identified. In this study, quantitative trait locus (QTL) analysis identified genomic regions associated with resistance to Phomopsis pod blight (PPB) using a linkage map of L. albus constructed previously from an F8 recombinant inbred line population derived from a cross between Kiev-Mutant (susceptible to PPB) and P27174 (resistant to PPB). Phenotyping was undertaken using a detached pod assay. In total, we identified eight QTLs for resistance to PPB on linkage group (LG) 3, LG6, LG10, LG12, LG17 and LG27 from different phenotyping environments. However, at least one QTL, QTL-5 on LG10 was consistently detected in both phenotyping environments and accounted for up to 28.2% of the total phenotypic variance. The results of this study showed that the QTL-2 on LG3 interacts epistatically with QTL-5 and QTL-6, which map on LG10 and LG12, respectively.

A consensus map of rapeseed (Brassica napus L.) based on diversity array technology markers: applications in genetic dissection of qualitative and quantitative traits.

BACKGROUND: Dense consensus genetic maps based on high-throughput genotyping platforms are valuable for making genetic gains in Brassica napus through quantitative trait locus identification, efficient predictive molecular breeding, and map-based gene cloning. This report describes the construction of the first B. napus consensus map consisting of a 1,359 anchored array based genotyping platform; Diversity Arrays Technology (DArT), and non-DArT markers from six populations originating from Australia, Canada, China and Europe. We aligned the B. napus DArT sequences with genomic scaffolds from Brassica rapa and Brassica oleracea, and identified DArT loci that showed linkage with qualitative and quantitative loci associated with agronomic traits. RESULTS: The integrated consensus map covered a total of 1,987.2 cM and represented all 19 chromosomes of the A and C genomes, with an average map density of one marker per 1.46 cM, corresponding to approximately 0.88 Mbp of the haploid genome. Through in silico physical mapping 2,457 out of 3,072 (80%) DArT clones were assigned to the genomic scaffolds of B. rapa (A genome) and B. oleracea (C genome). These were used to orientate the genetic consensus map with the chromosomal sequences. The DArT markers showed linkage with previously identified non-DArT markers associated with qualitative and quantitative trait loci for plant architecture, phenological components, seed and oil quality attributes, boron efficiency, sucrose transport, male sterility, and race-specific resistance to blackleg disease. CONCLUSIONS: The DArT markers provide increased marker density across the B. napus genome. Most of the DArT markers represented on the current array were sequenced and aligned with the B. rapa and B. oleracea genomes, providing insight into the Brassica A and C genomes. This information can be utilised for comparative genomics and genomic evolution studies. In summary, this consensus map can be used to (i) integrate new generation markers such as SNP arrays and next generation sequencing data; (ii) anchor physical maps to facilitate assembly of B. napus genome sequences; and (iii) identify candidate genes underlying natural genetic variation for traits of interest.

Identifying genetic diversity of avirulence genes in Leptosphaeria maculans using whole genome sequencing.

Next generation sequencing technology allows rapid re-sequencing of individuals, as well as the discovery of single nucleotide polymorphisms (SNPs), for genomic diversity and evolutionary analyses. By sequencing two isolates of the fungal plant pathogen Leptosphaeria maculans, the causal agent of blackleg disease in Brassica crops, we have generated a resource of over 76 million sequence reads aligned to the reference genome. We identified over 21,000 SNPs with an overall SNP frequency of one SNP every 2,065 bp. Sequence validation of a selection of these SNPs in additional isolates collected throughout Australia indicates a high degree of polymorphism in the Australian population. In preliminary phylogenetic analysis, isolates from Western Australia clustered together and those collected from Brassica juncea stubble were identical. These SNPs provide a novel marker resource to study the genetic diversity of this pathogen. We demonstrate that re-sequencing provides a method of validating previously characterised SNPs and analysing differences in important genes, such as the disease related avirulence genes of L. maculans. Understanding the genetic characteristics of this devastating pathogen is vital in developing long-term solutions to managing blackleg disease in Brassica crops.

Genetic and physical mapping of flowering time loci in canola (Brassica napus L.).

We identified quantitative trait loci (QTL) underlying variation for flowering time in a doubled haploid (DH) population of vernalisation-responsive canola (Brassica napus L.) cultivars Skipton and Ag-Spectrum and aligned them with physical map positions of predicted flowering genes from the Brassica rapa genome. Significant genetic variation in flowering time and response to vernalisation were observed among the DH lines from Skipton/Ag-Spectrum. A molecular linkage map was generated comprising 674 simple sequence repeat, sequence-related amplified polymorphism, sequence characterised amplified region, Diversity Array Technology, and candidate gene based markers loci. QTL analysis indicated that flowering time is a complex trait and is controlled by at least 20 loci, localised on ten different chromosomes. These loci each accounted for between 2.4 and 28.6% of the total genotypic variation for first flowering and response to vernalisation. However, identification of consistent QTL was found to be dependant upon growing environments. We compared the locations of QTL with the physical positions of predicted flowering time genes located on the sequenced genome of B. rapa. Some QTL associated with flowering time on A02, A03, A07, and C06 may represent homologues of known flowering time genes in Arabidopsis; VERNALISATION INSENSITIVE 3, APETALA1, CAULIFLOWER, FLOWERING LOCUS C, FLOWERING LOCUS T, CURLY LEAF, SHORT VEGETATIVE PHASE, GA3 OXIDASE, and LEAFY. Identification of the chromosomal location and effect of the genes influencing flowering time may hasten the development of canola varieties having an optimal time for flowering in target environments such as for low rainfall areas, via marker-assisted selection.

Construction of integrated linkage map of a recombinant inbred line population of white lupin (Lupinus albus L.).

We report the development of a Diversity Arrays Technology (DArT) marker panel and its utilisation in the development of an integrated genetic linkage map of white lupin (Lupinus albus L.) using an F8 recombinant inbred line population derived from Kiev Mutant/P27174. One hundred and thirty-six DArT markers were merged into the first genetic linkage map composed of 220 amplified fragment length polymorphisms (AFLPs) and 105 genic markers. The integrated map consists of 38 linkage groups of 441 markers and spans a total length of 2,169 cM, with an average interval size of 4.6 cM. The DArT markers exhibited good genome coverage and were associated with previously identified genic and AFLP markers linked with quantitative trait loci for anthracnose resistance, flowering time and alkaloid content. The improved genetic linkage map of white lupin will aid in the identification of markers for traits of interest and future syntenic studies.

Data-driven approaches to improve water-use efficiency and drought resistance in crop plants.

With the increasing population, there lies a pressing demand for food, feed and fibre, while the changing climatic conditions pose severe challenges for agricultural production worldwide. Water is the lifeline for crop production; thus, enhancing crop water-use efficiency (WUE) and improving drought resistance in crop varieties are crucial for overcoming these challenges. Genetically-driven improvements in yield, WUE and drought tolerance traits can buffer the worst effects of climate change on crop production in dry areas. While traditional crop breeding approaches have delivered impressive results in increasing yield, the methods remain time-consuming and are often limited by the existing allelic variation present in the germplasm. Significant advances in breeding and high-throughput omics technologies in parallel with smart agriculture practices have created avenues to dramatically speed up the process of trait improvement by leveraging the vast volumes of genomic and phenotypic data. For example, individual genome and pan-genome assemblies, along with transcriptomic, metabolomic and proteomic data from germplasm collections, characterised at phenotypic levels, could be utilised to identify marker-trait associations and superior haplotypes for crop genetic improvement. In addition, these omics approaches enable the identification of genes involved in pathways leading to the expression of a trait, thereby providing an understanding of the genetic, physiological and biochemical basis of trait variation. These data-driven gene discoveries and validation approaches are essential for crop improvement pipelines, including genomic breeding, speed breeding and gene editing. Herein, we provide an overview of prospects presented using big data-driven approaches (including artificial intelligence and machine learning) to harness new genetic gains for breeding programs and develop drought-tolerant crop varieties with favourable WUE and high-yield potential traits.

Quantitative Trait Loci for Genotype and Genotype by Environment Interaction Effects for Seed Yield Plasticity to Terminal Water-Deficit Conditions in Canola (Brassica napus L.).

Canola plants suffer severe crop yield and oil content reductions when exposed to water-deficit conditions, especially during the reproductive stages of plant development. There is a pressing need to develop canola cultivars that can perform better under increased water-deficit conditions with changing weather patterns. In this study, we analysed genetic determinants for the main effects of quantitative trait loci (QTL), (Q), and the interaction effects of QTL and Environment (QE) underlying seed yield and related traits utilising 223 doubled haploid (DH) lines of canola in well-watered and water-deficit conditions under a rainout shelter. Moderate water-deficit at the pre-flowering stage reduced the seed yield to 40.8%. Multi-environmental QTL analysis revealed 23 genomic regions associated with days to flower (DTF), plant height (PH) and seed yield (SY) under well-watered and water-deficit conditions. Three seed yield QTL for main effects were identified on chromosomes A09, C03, and C09, while two were related to QE interactions on A02 and C09. Two QTL regions were co-localised to similar genomic regions for flowering time and seed yield (A09) and the second for plant height and chlorophyll content. The A09 QTL was co-located with a previously mapped QTL for carbon isotope discrimination (Δ13C) that showed a positive relationship with seed yield in the same population. Opposite allelic effects for plasticity in seed yield were identified due to QE interactions in response to water stress on chromosomes A02 and C09. Our results showed that QTL's allelic effects for DTF, PH, and SY and their correlation with Δ13C are stable across environments (field conditions, previous study) and contrasting water regimes (this study). The QTL and DH lines that showed high yield under well-watered and water-deficit conditions could be used to manipulate water-use efficiency for breeding improved canola cultivars.

Novel quantitative trait loci from an interspecific Brassica rapa derivative improve pod shatter resistance in Brassica napus.

Pod shatter is a trait of agricultural relevance that ensures plants dehisce seeds in their native environment and has been subjected to domestication and selection for non-shattering types in several broadacre crops. However, pod shattering causes a significant yield reduction in canola (Brassica napus L.) crops. An interspecific breeding line BC95042 derived from a B. rapa/B. napus cross showed improved pod shatter resistance (up to 12-fold than a shatter-prone B. napus variety). To uncover the genetic basis and improve pod shatter resistance in new varieties, we analysed F2 and F2:3 derived populations from the cross between BC95042 and an advanced breeding line, BC95041, and genotyped with 15,498 DArTseq markers. Through genome scan, interval and inclusive composite interval mapping analyses, we identified seven quantitative trait loci (QTLs) associated with pod rupture energy, a measure for pod shatter resistance or pod strength, and they locate on A02, A03, A05, A09 and C01 chromosomes. Both parental lines contributed alleles for pod shatter resistance. We identified five pairs of significant epistatic QTLs for additive x additive, additive dominance and dominance x dominance interactions between A01/C01, A03/A07, A07/C03, A03/C03, and C01/C02 chromosomes for rupture energy. QTL effects on A03/A07 and A01/C01 were in the repulsion phase. Comparative mapping identified several candidate genes (AG, ABI3, ARF3, BP1, CEL6, FIL, FUL, GA2OX2, IND, LATE, LEUNIG, MAGL15, RPL, QRT2, RGA, SPT and TCP10) underlying main QTL and epistatic QTL interactions for pod shatter resistance. Three QTLs detected on A02, A03, and A09 were near the FUL (FRUITFULL) homologues BnaA03g39820D and BnaA09g05500D. Focusing on the FUL, we investigated putative motifs, sequence variants and the evolutionary rate of its homologues in 373 resequenced B. napus accessions of interest. BnaA09g05500D is subjected to purifying selection as it had a low Ka/Ks ratio compared to other FUL homologues in B. napus. This study provides a valuable resource for genetic improvement for yield through an understanding of the genetic mechanism controlling pod shatter resistance in Brassica species.

A Tourist-like MITE insertion in the upstream region of the BnFLC.A10 gene is associated with vernalization requirement in rapeseed (Brassica napus L.).

BACKGROUND: Rapeseed (Brassica napus L.) has spring and winter genotypes adapted to different growing seasons. Winter genotypes do not flower before the onset of winter, thus leading to a longer vegetative growth period that promotes the accumulation and allocation of more resources to seed production. The development of winter genotypes enabled the rapeseed to spread rapidly from southern to northern Europe and other temperate regions of the world. The molecular basis underlying the evolutionary transition from spring- to winter- type rapeseed is not known, however, and needs to be elucidated. RESULTS: We fine-mapped the spring environment specific quantitative trait locus (QTL) for flowering time, qFT10-4,in a doubled haploid (DH) mapping population of rapeseed derived from a cross between Tapidor (winter-type) and Ningyou7 (semi-winter) and delimited the qFT10-4 to an 80-kb region on chromosome A10 of B. napus. The BnFLC.A10 gene, an ortholog of FLOWERING LOCUS C (FLC) in Arabidopsis, was cloned from the QTL. We identified 12 polymorphic sites between BnFLC.A10 parental alleles of the TN-DH population in the upstream region and in intron 1. Expression of both BnFLC.A10 alleles decreased during vernalization, but decreased more slowly in the winter parent Tapidor. Haplotyping and association analysis showed that one of the polymorphic sites upstream of BnFLC.A10 is strongly associated with the vernalization requirement of rapeseed (r2 = 0.93, χ2 = 0.50). This polymorphic site is derived from a Tourist-like miniature inverted-repeat transposable element (MITE) insertion/deletion in the upstream region of BnFLC.A10. The MITE sequence was not present in the BnFLC.A10 gene in spring-type rapeseed, nor in ancestral 'A' genome species B. rapa genotypes. Our results suggest that the insertion may have occurred in winter rapeseed after B. napus speciation. CONCLUSIONS: Our findings strongly suggest that (i) BnFLC.A10 is the gene underlying qFT10-4, the QTL for phenotypic diversity of flowering time in the TN-DH population, (ii) the allelic diversity caused by MITE insertion/deletion upstream of BnFLC.A10 is one of the major causes of differentiation of winter and spring genotypes in rapeseed and (iii) winter rapeseed has evolved from spring genotypes through selection pressure at the BnFLC.A10 locus, enabling expanded cultivation of rapeseed along the route of Brassica domestication.

Identification and characterization of candidate Rlm4 blackleg resistance genes in Brassica napus using next-generation sequencing.

A thorough understanding of the relationships between plants and pathogens is essential if we are to continue to meet the agricultural needs of the world's growing population. The identification of genes underlying important quantitative trait loci is extremely challenging in complex genomes such as Brassica napus (canola, oilseed rape or rapeseed). However, recent advances in next-generation sequencing (NGS) enable much quicker identification of candidate genes for traits of interest. Here, we demonstrate this with the identification of candidate disease resistance genes from B. napus for its most devastating fungal pathogen, Leptosphaeria maculans (blackleg fungus). These two species are locked in an evolutionary arms race whereby a gene-for-gene interaction confers either resistance or susceptibility in the plant depending on the genotype of the plant and pathogen. Preliminary analysis of the complete genome sequence of Brassica rapa, the diploid progenitor of B. napus, identified numerous candidate genes with disease resistance characteristics, several of which were clustered around a region syntenic with a major locus (Rlm4) for blackleg resistance on A7 of B. napus. Molecular analyses of the candidate genes using B. napus NGS data are presented, and the difficulties associated with identifying functional gene copies within the highly duplicated Brassica genome are discussed.

Molecular mapping of qualitative and quantitative loci for resistance to Leptosphaeria maculans causing blackleg disease in canola (Brassica napus L.).

Blackleg, caused by Leptosphaeria maculans, is one of the most important diseases of oilseed and vegetable crucifiers worldwide. The present study describes (1) the construction of a genetic linkage map, comprising 255 markers, based upon simple sequence repeats (SSR), sequence-related amplified polymorphism, sequence tagged sites, and EST-SSRs and (2) the localization of qualitative (race-specific) and quantitative (race non-specific) trait loci controlling blackleg resistance in a doubled-haploid population derived from the Australian canola (Brassica napus L.) cultivars Skipton and Ag-Spectrum using the whole-genome average interval mapping approach. Marker regression analyses revealed that at least 14 genomic regions with LOD ≥ 2.0 were associated with qualitative and quantitative blackleg resistance, explaining 4.6-88.9 % of genotypic variation. A major qualitative locus, designated RlmSkipton (Rlm4), was mapped on chromosome A7, within 0.8 cM of the SSR marker Xbrms075. Alignment of the molecular markers underlying this QTL region with the genome sequence data of B. rapa L. suggests that RlmSkipton is located approximately 80 kb from the Xbrms075 locus. Molecular marker-RlmSkipton linkage was further validated in an F(2) population from Skipton/Ag-Spectrum. Our results show that SSR markers linked to consistent genomic regions are suitable for enrichment of favourable alleles for blackleg resistance in canola breeding programs.