Fiona Fraser

Associative transcriptomics of traits in the polyploid crop species Brassica napus

Association genetics can quickly and efficiently delineate regions of the genome that control traits and provide markers to accelerate breeding by marker-assisted selection. But most crops are polyploid, making it difficult to identify the required markers and to assemble a genome sequence to order those markers. To circumvent this difficulty, we developed associative transcriptomics, which uses transcriptome sequencing to identify and score molecular markers representing variation in both gene sequences and gene expression, and correlate this with trait variation. Applying the method in the recently formed tetraploid crop Brassica napus, we identified genomic deletions that underlie two quantitative trait loci for glucosinolate content of seeds. The deleted regions contained orthologs of the transcription factor HAG1 (At5g61420), which controls aliphatic glucosinolate biosynthesis in Arabidopsis thaliana. This approach facilitates the application of association genetics in a broad range of crops, even those with complex genomes.

Dissecting the genome of the polyploid crop oilseed rape by transcriptome sequencing

Polyploidy complicates genomics-based breeding of many crops, including wheat, potato, cotton, oat and sugarcane. To address this challenge, we sequenced leaf transcriptomes across a mapping population of the polyploid crop oilseed rape (Brassica napus) and representative ancestors of the parents of the population. Analysis of sequence variation and transcript abundance enabled us to construct twin single nucleotide polymorphism linkage maps of B. napus, comprising 23,037 markers. We used these to align the B. napus genome with that of a related species, Arabidopsis thaliana, and to genome sequence assemblies of its progenitor species, Brassica rapa and Brassica oleracea. We also developed methods to detect genome rearrangements and track inheritance of genomic segments, including the outcome of an interspecific cross. By revealing the genetic consequences of breeding, cost-effective, high-resolution dissection of crop genomes by transcriptome sequencing will increase the efficiency of predictive breeding even in the absence of a complete genome sequence.

A newly-developed community microarray resource for transcriptome profiling in Brassica species enables the confirmation of Brassica-specific expressed sequences

BackgroundThe Brassica species include an important group of crops and provide opportunities for studying the evolutionary consequences of polyploidy. They are related to Arabidopsis thaliana, for which the first complete plant genome sequence was obtained and their genomes show extensive, although imperfect, conserved synteny with that of A. thaliana. A large number of EST sequences, derived from a range of different Brassica species, are available in the public database, but no public microarray resource has so far been developed for these species.ResultsWe assembled unigenes using ~800,000 EST sequences, mainly from three species: B. napus, B. rapa and B. oleracea. The assembly was conducted with the aim of co-assembling ESTs of orthologous genes (including homoeologous pairs of genes in B. napus from each of the A and C genomes), but resolving assemblies of paralogous, or paleo-homoeologous, genes (i.e. the genes related by the ancestral genome triplication observed in diploid Brassica species). 90,864 unique sequence assemblies were developed. These were incorporated into the BAC sequence annotation for the Brassica rapa Genome Sequencing Project, enabling the identification of cognate genomic sequences for a proportion of them. A 60-mer oligo microarray comprising 94,558 probes was developed using the unigene sequences. Gene expression was analysed in reciprocal resynthesised B. napus lines and the B. oleracea and B. rapa lines used to produce them. The analysis showed that significant expression could consistently be detected in leaf tissue for 35,386 unigenes. Expression was detected across all four genotypes for 27,355 unigenes, genome-specific expression patterns were observed for 7,851 unigenes and 180 unigenes displayed other classes of expression pattern. Principal component analysis (PCA) clearly resolved the individual microarray datasets for B. rapa, B. oleracea and resynthesised B. napus. Quantitative differences in expression were observed between the resynthesised B. napus lines for 98 unigenes, most of which could be classified into non-additive expression patterns, including 17 that showed cytoplasm-specific patterns. We further characterized the unigenes for which A genome-specific expression was observed and cognate genomic sequences could be identified. Ten of these unigenes were found to be Brassica-specific sequences, including two that originate from complex loci comprising gene clusters.ConclusionWe succeeded in developing a Brassica community microarray resource. Although expression can be measured for the majority of unigenes across species, there were numerous probes that reported in a genome-specific manner. We anticipate that some proportion of these will represent species-specific transcripts and the remainder will be the consequence of variation of sequences within the regions represented by the array probes. Our studies demonstrated that the datasets obtained from the arrays can be used for typical analyses, including PCA and the analysis of differential expression. We have also demonstrated that Brassica-specific transcripts identified in silico in the sequence assembly of public EST database accessions are indeed reported by the array. These would not be detectable using arrays designed using A. thaliana sequences.

Use of mRNA-seq to discriminate contributions to the transcriptome from the constituent genomes of the polyploid crop species Brassica napus

BackgroundPolyploidy often results in considerable changes in gene expression, both immediately and over evolutionary time. New phenotypes often arise with polyploid formation and may contribute to the fitness of polyploids in nature or their selection for use in agriculture. Oilseed rape (Brassica napus) is widely used to study the process of polyploidy both in artificially resynthesised and natural forms. mRNA-Seq, a recently developed approach to transcriptome profiling using deep-sequencing technologies is an alternative to microarrays for the study of gene expression in a polyploid.ResultsIllumina mRNA-Seq is comparable to microarray analysis for transcript quantification but has increased sensitivity and, very importantly, the potential to distinguish between homoeologous genes in polyploids. Using a novel curing process, we adapted a reference sequence that was a consensus derived from ESTs from both Brassica A and C genomes to one containing separate A and C genome versions for each of the 94,558 original unigenes. We aligned reads from B. napus to this cured reference, finding 38% more reads mapping from resynthesised lines and 28% more reads mapping from natural lines. Where the A and C versions differed at single nucleotide positions, termed inter-homoeologue polymorphisms (IHPs), we were able to apportion expression in the polyploid between the A and C genome homoeologues. 43,761 unigenes contained at least one IHP, with a mean frequency of 10.5 per kb unigene sequence. 6,350 of the unigenes with IHPs were differentially expressed between homoeologous gene pairs in resynthesised B. napus. 3,212 unigenes showed a similar pattern of differential expression across a range of natural B. napus crop varieties and, of these, 995 were in common with resynthesised B. napus. Functional classification showed over-representation in gene ontology categories not associated with dosage-sensitivity.ConclusionmRNA-Seq is the method of choice for measuring transcript abundance in polyploids due to its ability to measure the contributions of homoeologues to gene expression. The identification of large numbers of differentially expressed genes in both a newly resynthesised polyploid and natural B. napus confirms that there are both immediate and long-term alterations in the expression of homoeologous gene pairs following polyploidy.

Complexity of genome evolution by segmental rearrangement in Brassica rapa revealed by sequence-level analysis

BackgroundThe Brassica species, related to Arabidopsis thaliana, include an important group of crops and represent an excellent system for studying the evolutionary consequences of polyploidy. Previous studies have led to a proposed structure for an ancestral karyotype and models for the evolution of the B. rapa genome by triplication and segmental rearrangement, but these have not been validated at the sequence level.ResultsWe developed computational tools to analyse the public collection of B. rapa BAC end sequence, in order to identify candidates for representing collinearity discontinuities between the genomes of B. rapa and A. thaliana. For each putative discontinuity, one of the BACs was sequenced and analysed for collinearity with the genome of A. thaliana. Additional BAC clones were identified and sequenced as part of ongoing efforts to sequence four chromosomes of B. rapa. Strikingly few of the 19 inter-chromosomal rearrangements corresponded to the set of collinearity discontinuities anticipated on the basis of previous studies. Our analyses revealed numerous instances of newly detected collinearity blocks. For B. rapa linkage group A8, we were able to develop a model for the derivation of the chromosome from the ancestral karyotype. We were also able to identify a rearrangement event in the ancestor of B. rapa that was not shared with the ancestor of A. thaliana, and is represented in triplicate in the B. rapa genome. In addition to inter-chromosomal rearrangements, we identified and analysed 32 BACs containing the end points of segmental inversion events.ConclusionOur results show that previous studies of segmental collinearity between the A. thaliana, Brassica and ancestral karyotype genomes, although very useful, represent over-simplifications of their true relationships. The presence of numerous cryptic collinear genome segments and the frequent occurrence of segmental inversions mean that inference of the positions of genes in B. rapa based on the locations of orthologues in A. thaliana can be misleading. Our results will be of relevance to a wide range of plants that have polyploid genomes, many of which are being considered according to a paradigm of comprising conserved synteny blocks with respect to sequenced, related genomes.

Molecular markers for tolerance of European ash (Fraxinus excelsior) to dieback disease identified using Associative Transcriptomics.

Tree disease epidemics are a global problem, impacting food security, biodiversity and national economies. The potential for conservation and breeding in trees is hampered by complex genomes and long lifecycles, with most species lacking genomic resources. The European Ash tree Fraxinus excelsior is being devastated by the fungal pathogen Hymenoscyphus fraxineus, which causes ash dieback disease. Taking this system as an example and utilizing Associative Transcriptomics for the first time in a plant pathology study, we discovered gene sequence and gene expression variants across a genetic diversity panel scored for disease symptoms and identified markers strongly associated with canopy damage in infected trees. Using these markers we predicted phenotypes in a test panel of unrelated trees, successfully identifying individuals with a low level of susceptibility to the disease. Co-expression analysis suggested that pre-priming of defence responses may underlie reduced susceptibility to ash dieback.

Associative Transcriptomics Study Dissects the Genetic Architecture of Seed Glucosinolate Content in Brassica napus

Breeding new varieties with low seed glucosinolate (GS) concentrations has long been a prime target in Brassica napus. In this study, a novel association mapping methodology termed ‘associative transcriptomics’ (AT) was applied to a panel of 101 B. napus lines to define genetic regions and also candidate genes controlling total seed GS contents. Over 100,000 informative single-nucleotide polymorphisms (SNPs) and gene expression markers (GEMs) were developed for AT analysis, which led to the identification of 10 SNP and 7 GEM association peaks. Within these peaks, 26 genes were inferred to be involved in GS biosynthesis. A weighted gene co-expression network analysis provided additional 40 candidate genes. The transcript abundance in leaves of two candidate genes, BnaA.GTR2a located on chromosome A2 and BnaC.HAG3b on C9, was correlated with seed GS content, explaining 18.8 and 16.8% of phenotypic variation, respectively. Resequencing of genomic regions revealed six new SNPs in BnaA.GTR2a and four insertions or deletions in BnaC.HAG3b. These deletion polymorphisms were then successfully converted into polymerase chain reaction–based diagnostic markers that can, due to high linkage disequilibrium observed in these regions of the genome, be used for marker-assisted breeding for low seed GS lines.

Sequence-level comparative analysis of the Brassica napus genome around two stearoyl-ACP desaturase loci.

We conducted a sequence-level comparative analyses, at the scale of complete bacterial artificial chromosome (BAC) clones, between the genome of the most economically important Brassica species, Brassica napus (oilseed rape), and those of Brassica rapa, the genome of which is currently being sequenced, and Arabidopsis thaliana. We constructed a new B. napus BAC library and identified and sequenced clones that contain homoeologous regions of the genome including stearoyl-ACP desaturase-encoding genes. We sequenced the orthologous region of the genome of B. rapa and conducted comparative analyses between the Brassica sequences and those of the orthologous region of the genome of A. thaliana. The proportion of genes conserved (approximately 56%) is lower than has been reported previously between A. thaliana and Brassica (approximately 66%). The gene models for sets of conserved genes were used to determine the extent of nucleotide conservation of coding regions. This was found to be 84.2 +/- 3.9% and 85.8 +/- 3.7% between the B. napus A and C genomes, respectively, and that of A. thaliana, which is consistent with previous results for other Brassica species, and 97.5 +/- 3.1% between the B. napus A genome and B. rapa, and 93.1 +/- 4.9% between the B. napus C genome and B. rapa. The divergence of the B. napus genes from the A genome and the B. rapa genes was greater than anticipated and indicates that the A genome ancestor of the B. napus cultivar studied was relatively distantly related to the cultivar of B. rapa selected for genome sequencing.

An association transcriptomics approach to the prediction of hybrid performance

Many animal and plant species exhibit increased growth rates, reach larger sizes and, in the cases of crops and farm animals, produce higher yields when bred as hybrids between genetically differing strains, a phenomenon known as hybrid vigour or heterosis. Despite the importance of heterosis, and its extensive genetic analysis, little understanding exists of its molecular basis. We aimed to determine whether characteristics of the leaf transcriptome, as an indicator of the innate functional genetic architecture of a plant line, could be used as markers to predict heterosis and the performance of hybrids, a methodology we term Association Transcriptomics. Relationships between transcript abundance of specific genes and the values of heterosis and heterosis-dependent traits were identified and mathematical models were constructed that relate gene expression characteristics in inbred lines of Arabidopsis thaliana and maize with vegetative biomass and grain yield, respectively, in corresponding hybrids. These models were used to predict, using gene expression data, the performance of additional hybrids. The success of the application in a monocot crop of a methodology developed in a dicot model species indicates that transcriptional markers may have widespread applicability in hybrid breeding.

Defining and quantifying the resilience of responses to disturbance: a conceptual and modelling approach from soil science

There are several conceptual definitions of resilience pertaining to environmental systems and, even if resilience is clearly defined in a particular context, it is challenging to quantify. We identify four characteristics of the response of a system function to disturbance that relate to “resilience”: (1) degree of return of the function to a reference level; (2) time taken to reach a new quasi-stable state; (3) rate (i.e. gradient) at which the function reaches the new state; (4) cumulative magnitude of the function (i.e. area under the curve) before a new state is reached. We develop metrics to quantify these characteristics based on an analogy with a mechanical spring and damper system. Using the example of the response of a soil function (respiration) to disturbance, we demonstrate that these metrics effectively discriminate key features of the dynamic response. Although any one of these characteristics could define resilience, each may lead to different insights and conclusions. The salient properties of a resilient response must thus be identified for different contexts. Because the temporal resolution of data affects the accurate determination of these metrics, we recommend that at least twelve measurements are made over the temporal range for which the response is expected.