Christian Obermeier

Genetic analysis of phenylpropanoid metabolites associated with resistance against Verticillium longisporum in Brassica napus

Verticillium longisporum is a major threat to production of oilseed rape (Brassica napus) in Europe. The aim of the study was to develop new markers and obtain insights into putative mechanisms and pathways involved in the resistance reaction. A genetic approach was used to identify quantitative trait loci (QTL) for V. longisporum resistance and metabolic traits potentially influencing resistance in a B. napus mapping population. Resistance to V. longisporum was mapped in a doubled haploid (DH) population from a cross between the partially resistant winter oilseed rape variety Express 617 and a resistant resynthesized B. napus line, R53. One major resistance QTL contributed by R53 was identified on chromosome C5, while a further, minor QTL contributed by Express 617 was detected on chromosome C1. Markers flanking the QTL also significantly correlated with V. longisporum resistance in four further DH populations derived from crosses between elite oilseed rape cultivars and other resynthesized B. napus lines originating from genetically and geographically diverse brassica A and C genome donors. The tightly-linked markers developed enable the combination of favorable alleles for novel resistance loci from resynthesized B. napus materials with existing resistance loci from commercial breeding lines. HPLC analysis of hypocotyls from infected DH lines revealed that concentrations of a number of phenylpropanoids were correlated with V. longisporum resistance. QTL for some of these phenylpropanoids were also found to co-localize with the QTL for V. longisporum resistance. Genes from the phenylpropanoid pathway are suggested as candidates for V. longisporum resistance.

Gene expression profiling via LongSAGE in a non-model plant species: a case study in seeds of Brassica napus

BackgroundSerial analysis of gene expression (LongSAGE) was applied for gene expression profiling in seeds of oilseed rape (Brassica napus ssp. napus). The usefulness of this technique for detailed expression profiling in a non-model organism was demonstrated for the highly complex, neither fully sequenced nor annotated genome of B. napus by applying a tag-to-gene matching strategy based on Brassica ESTs and the annotated proteome of the closely related model crucifer A. thaliana.ResultsTranscripts from 3,094 genes were detected at two time-points of seed development, 23 days and 35 days after pollination (DAP). Differential expression showed a shift from gene expression involved in diverse developmental processes including cell proliferation and seed coat formation at 23 DAP to more focussed metabolic processes including storage protein accumulation and lipid deposition at 35 DAP. The most abundant transcripts at 23 DAP were coding for diverse protease inhibitor proteins and proteases, including cysteine proteases involved in seed coat formation and a number of lipid transfer proteins involved in embryo pattern formation. At 35 DAP, transcripts encoding napin, cruciferin and oleosin storage proteins were most abundant. Over both time-points, 18.6% of the detected genes were matched by Brassica ESTs identified by LongSAGE tags in antisense orientation. This suggests a strong involvement of antisense transcript expression in regulatory processes during B. napu s seed development.ConclusionThis study underlines the potential of transcript tagging approaches for gene expression profiling in Brassica crop species via EST matching to annotated A. thaliana genes. Limits of tag detection for low-abundance transcripts can today be overcome by ultra-high throughput sequencing approaches, so that tag-based gene expression profiling may soon become the method of choice for global expression profiling in non-model species.

Mapping of homoeologous chromosome exchanges influencing quantitative trait variation in Brassica napus

Summary Genomic rearrangements arising during polyploidization are an important source of genetic and phenotypic variation in the recent allopolyploid crop Brassica napus. Exchanges among homoeologous chromosomes, due to interhomoeologue pairing, and deletions without compensating homoeologous duplications are observed in both natural B. napus and synthetic B. napus. Rearrangements of large or small chromosome segments induce gene copy number variation (CNV) and can potentially cause phenotypic changes. Unfortunately, complex genome restructuring is difficult to deal with in linkage mapping studies. Here, we demonstrate how high‐density genetic mapping with codominant, physically anchored SNP markers can detect segmental homoeologous exchanges (HE) as well as deletions and accurately link these to QTL. We validated rearrangements detected in genetic mapping data by whole‐genome resequencing of parental lines along with cytogenetic analysis using fluorescence in situ hybridization with bacterial artificial chromosome probes (BAC‐FISH) coupled with PCR using primers specific to the rearranged region. Using a well‐known QTL region influencing seed quality traits as an example, we confirmed that HE underlies the trait variation in a DH population involving a synthetic B. napus trait donor, and succeeded in narrowing the QTL to a small defined interval that enables delineation of key candidate genes.

Disruption of Germination and Seedling Development in Brassica napus by Mutations Causing Severe Seed Hormonal Imbalance.

The Brassica napus (oilseed rape) accession 1012-98 shows a disturbed germination phenotype that was thought to be associated with its lack of testa pigmentation and thin seed coat. Here, we demonstrate that the disturbed germination and seedling development are actually due to independent mutations that disrupt the balance of hormone metabolites and their regulators in the seeds. High-throughput UPLC-MS/MS hormone profiling of seeds and seedlings before and after germination revealed that 1012-98 has a severely disturbed hormone balance with extremely atypical, excessive quantities of auxin and ABA metabolites. The resulting hypersensitivity to abscisic acid (ABA) and a corresponding increase in dormancy often results in death of the embryo after imbibition or high frequencies of disturbed, often lethal developmental phenotypes, resembling Arabidopsis mutants for the auxin regulatory factor gene ARF10 or the auxin-overproducing transgenic line iaaM-OX. Molecular cloning of Brassica ARF10 orthologs revealed four loci in normal B. napus, two derived from the Brassica A genome and two from the C genome. On the other hand, the phenotypic mutant 1012-98 exhibited amplification of C-genome BnaC.ARF10 copy number along with a chimeric allele originating from recombination between homeologous A and C genome loci which lead to minor increase of Bna.ARF10 transcription on the critical timepoint for seed germination, the indirect regulator of ABI3, the germinative inhibitor. Bna.GH3.5 expression was upregulated to conjugate free auxin to IAA-asp between 2 and 6 DAS. Functional amino acid changes were also found in important DNA binding domains of one BnaC.ARF10 locus, suggesting that regulatory changes in Bna.ARF10 are collectively responsible for the observed phenotpyes in 1012-98. To our knowledge, this study is the first to report disruption of germination and seedling development in Brassica napus caused by the crosstalk of auxin-ABA and the corresponding regulators Bna.ARF10 and Bna.GH3.5.

Finding invisible quantitative trait loci with missing data

Summary Evolutionary processes during plant polyploidization and speciation have led to extensive presence–absence variation (PAV) in crop genomes, and there is increasing evidence that PAV associates with important traits. Today, high‐resolution genetic analysis in major crops frequently implements simple, cost‐effective, high‐throughput genotyping from single nucleotide polymorphism (SNP) hybridization arrays; however, these are normally not designed to distinguish PAV from failed SNP calls caused by hybridization artefacts. Here, we describe a strategy to recover valuable information from single nucleotide absence polymorphisms (SNaPs) by population‐based quality filtering of SNP hybridization data to distinguish patterns associated with genuine deletions from those caused by technical failures. We reveal that including SNaPs in genetic analyses elucidate segregation of small to large‐scale structural variants in nested association mapping populations of oilseed rape (Brassica napus), a recent polyploid crop with widespread structural variation. Including SNaP markers in genomewide association studies identified numerous quantitative trait loci, invisible using SNP markers alone, for resistance to two major fungal diseases of oilseed rape, Sclerotinia stem rot and blackleg disease. Our results indicate that PAV has a strong influence on quantitative disease resistance in B. napus and that SNaP analysis using cost‐effective SNP array data can provide extensive added value from ‘missing data’. This strategy might also be applicable for improving the precision of genetic mapping in many important crop species.

Multiplexed Digital Gene Expression Analysis for Genetical Genomics in Large Plant Populations

Digital gene expression (DGE) analysis is a cost-effective method for large-scale quantitative transcriptome analysis using second generation sequencing. Here we describe how adaptation of DGE with barcode indexing in large segregating plant populations of over 100 genotypes can be applied for successful expression QTL (eQTL) and gene expression network analysis to develop transcript-based markers for breeding.

Applied oilseed rape marker technology and genomics

Oilseed rape (OSR) (Brassica napus L.) is the world’s second oilseed crop. Breeding of OSR and sustained growth over the last three decades has been largely driven by biotechnology applications including doubled haploid (DH) and molecular marker technologies and has been resulting in the transition from line (OP) to hybrid varieties in the market. This review is discussing the role of interspecific hybridization in combination with the development of molecular marker technology, marker-assisted selection and genomics approaches for broadening the narrow genetic diversity of elite B. napus breeding material to address specific OSR breeding goals, i.e. oil yield, seed quality and disease resistance. New high-throughput technologies for B. napus genotyping, whole-genome analyses and comparative mapping approaches have been recently established and are nowadays enabling the screening of large collections of germplasm for identification of novel alleles from diverse sources. These technologies are opening up the door to speed up the genetic dissection of complex traits and increase the efficiency of knowledge-based breeding of OSR in the near future.

Genetic insights into underground responses to Fusarium graminearum infection in wheat

The ongoing global intensification of wheat production will likely be accompanied by a rising pressure of Fusarium diseases. While utmost attention was given to Fusarium head blight (FHB) belowground plant infections of the pathogen have largely been ignored. The current knowledge about the impact of soil borne Fusarium infection on plant performance and the underlying genetic mechanisms for resistance remain very limited. Here, we present the first large-scale investigation of Fusarium root rot (FRR) resistance using a diverse panel of 215 international wheat lines. We obtained data for a total of 21 resistance-related traits, including large-scale Real-time PCR experiments to quantify fungal spread. Association mapping and subsequent haplotype analyses discovered a number of highly conserved genomic regions associated with resistance, and revealed a significant effect of allele stacking on the stembase discoloration. Resistance alleles were accumulated in European winter wheat germplasm, implying indirect prior selection for improved FRR resistance in elite breeding programs. Our results give first insights into the genetic basis of FRR resistance in wheat and demonstrate how molecular parameters can successfully be explored in genomic prediction. Ongoing work will help to further improve our understanding of the complex interactions of genetic factors influencing FRR resistance.