Genetic Mapping of Genotype-by-Ploidy Effects in Arabidopsis thaliana

Plants can express different phenotypic responses following polyploidization, but ploidy-dependent phenotypic variation has so far not been assigned to specific genetic factors. To map such effects, segregating populations at different ploidy levels are required. The availability of an efficient haploid inducer line in Arabidopsis thaliana allows for the rapid development of large populations of segregating haploid offspring. Because Arabidopsis haploids can be self-fertilised to give rise to homozygous doubled haploids, the same genotypes can be phenotyped at both the haploid and diploid ploidy level. Here, we compared the phenotypes of recombinant haploid and diploid offspring derived from a cross between two late flowering accessions to map genotype × ploidy (G × P) interactions. Ploidy-specific quantitative trait loci (QTLs) were detected at both ploidy levels. This implies that mapping power will increase when phenotypic measurements of monoploids are included in QTL analyses. A multi-trait analysis further revealed pleiotropic effects for a number of the ploidy-specific QTLs as well as opposite effects at different ploidy levels for general QTLs. Taken together, we provide evidence of genetic variation between different Arabidopsis accessions being causal for dissimilarities in phenotypic responses to altered ploidy levels, revealing a G × P effect. Additionally, by investigating a population derived from late flowering accessions, we revealed a major vernalisation-specific QTL for variation in flowering time, countering the historical bias of research in early flowering accessions.

Drought response in Arabidopsis displays synergistic coordination between stems and leaves

The synergy between drought-responsive traits across different organs is crucial in the whole-plant mechanism influencing drought resilience. These organ interactions, however, are poorly understood, limiting our understanding of drought response strategies at the whole-plant level. Therefore, we need more integrative studies, especially on herbaceous species that represent many important food crops but remain underexplored in their drought response. We investigated inflorescence stems and rosette leaves of six Arabidopsis thaliana genotypes with contrasting drought tolerance, and combined anatomical observations with hydraulic measurements and gene expression studies to assess differences in drought response. The soc1ful double mutant was the most drought-tolerant genotype based on its synergistic combination of low stomatal conductance, largest stomatal safety margin, more stable leaf water potential during non-watering, reduced transcript levels of drought stress marker genes, and reduced loss of chlorophyll content in leaves, in combination with stems showing the highest embolism resistance, most pronounced lignification, and thickest intervessel pit membranes. In contrast, the most sensitive Cvi ecotype shows the opposite extreme of the same set of traits. The remaining four genotypes show variations in this drought syndrome. Our results reveal that anatomical, ecophysiological, and molecular adaptations across organs are intertwined, and multiple (differentially combined) strategies can be applied to acquire a certain level of drought tolerance.

Genotypic and tissue-specific variation of Populus nigra transcriptome profiles in response to drought

Climate change is one of the most important challenges for mankind in the far and near future. In this regard, sustainable production of woody crops on marginal land with low water availability is a major challenge to tackle. This dataset is part of an experiment, in which we exposed three genetically differentiated genotypes of Populus nigra originating from contrasting natural habitats to gradually increasing moderate drought. RNA sequencing was performed on fine roots, developing xylem and leaves of those three genotypes under control and moderate drought conditions in order to get a comprehensive dataset on the transcriptional changes at the whole plant level under water limiting conditions. This dataset has already provided insight in the transcriptional control of saccharification potential of the three Populus genotypes under drought conditions and we suggest that our data will be valuable for further in-depth analysis regarding candidate gene identification or, on a bigger scale, for meta-transcriptome analysis.

Measurement(s)	transcriptome
Technology Type(s)	illumina sequencing
Factor Type(s)	treatment
Sample Characteristic - Organism	Populus nigra
Sample Characteristic - Environment	greenhouse experiment

Intervessel pit membrane thickness best explains variation in embolism resistance amongst stems of Arabidopsis thaliana accessions

BACKGROUND AND AIMS

The ability to avoid drought-induced embolisms in the xylem is one of the essential traits for plants to survive periods of water shortage. Over the past three decades, hydraulic studies have been focusing on trees, which limits our ability to understand how herbs tolerate drought. Here we investigate the embolism resistance in inflorescence stems of four Arabidopsis thaliana accessions that differ in growth form and drought response. We assess functional traits underlying the variation in embolism resistance amongst the accessions studied using detailed anatomical observations.

METHODS

Vulnerability to xylem embolism was evaluated via vulnerability curves using the centrifuge technique and linked with detailed anatomical observations in stems using light microscopy and transmission electron microscopy.

KEY RESULTS

The data show significant differences in stem P50, varying 2-fold from -1.58 MPa in the Cape Verde Island accession to -3.07 MPa in the woody soc1 ful double mutant. Out of all the anatomical traits measured, intervessel pit membrane thickness (TPM) best explains the differences in P50, as well as P12 and P88. The association between embolism resistance and TPM can be functionally explained by the air-seeding hypothesis. There is no evidence that the correlation between increased woodiness and increased embolism resistance is directly related to functional aspects. However, we found that increased woodiness is strongly linked to other lignification characters, explaining why mechanical stem reinforcement is indirectly related to increased embolism resistance.

CONCLUSIONS

The woodier or more lignified accessions are more resistant to embolism than the herbaceous accessions, confirming the link between increased stem lignification and increased embolism resistance, as also observed in other lineages. Intervessel pit membrane thickness and, to a lesser extent, theoretical vessel implosion resistance and vessel wall thickness are the missing functional links between stem lignification and embolism resistance.

Meiotic crossover reduction by virus-induced gene silencing enables the efficient generation of chromosome substitution lines and reverse breeding in Arabidopsis thaliana

Plant breeding applications exploiting meiotic mutant phenotypes (like the increase or decrease of crossover (CO) recombination) have been proposed over the last years. As recessive meiotic mutations in breeding lines may affect fertility or have other pleiotropic effects, transient silencing techniques may be preferred. Reverse breeding is a breeding technique that would benefit from the transient downregulation of CO formation. The technique is essentially the opposite of plant hybridization: a method to extract parental lines from a hybrid. The method can also be used to efficiently generate chromosome substitution lines (CSLs). For successful reverse breeding, the two homologous chromosome sets of a heterozygous plant must be divided over two haploid complements, which can be achieved by the suppression of meiotic CO recombination and the subsequent production of doubled haploid plants. Here we show the feasibility of transiently reducing CO formation using virus-induced gene silencing (VIGS) by targeting the meiotic gene MSH5 in a wild-type heterozygote of Arabidopsis thaliana. The application of VIGS (rather than using lengthy stable transformation) generates transgene-free offspring with the desired genetic composition: we obtained parental lines from a wild-type heterozygous F₁ in two generations. In addition, we obtained 20 (of the 32 possible) CSLs in one experiment. Our results demonstrate that meiosis can be modulated at will in A. thaliana to generate CSLs and parental lines rapidly for hybrid breeding. Furthermore, we illustrate how the modification of meiosis using VIGS can open routes to develop efficient plant breeding strategies.

The Role of Transcriptional Regulation in Hybrid Vigor

The genetic basis of hybrid vigor in plants remains largely unsolved but strong evidence suggests that variation in transcriptional regulation can explain many aspects of this phenomenon. Natural variation in transcriptional regulation is highly abundant in virtually all species and thus a potential source of heterotic variability. Allele Specific Expression (ASE), which is tightly linked to parent of origin effects and modulated by complex interactions in cis and in trans, is generally considered to play a key role in explaining the differences between hybrids and parental lines. Here we discuss the recent developments in elucidating the role of transcriptional variation in a number of aspects of hybrid vigor, thereby bridging old paradigms and hypotheses with contemporary research in various species.

Reciprocal cybrids reveal how organellar genomes affect plant phenotypes

Assessment of the impact of variation in chloroplast and mitochondrial DNA (collectively termed the plasmotype) on plant phenotypes is challenging due to the difficulty in separating their effect from nuclear-derived variation (the nucleotype). Haploid-inducer lines can be used as efficient plasmotype donors to generate new plasmotype-nucleotype combinations (cybrids)¹. We generated a panel comprising all possible cybrids of seven Arabidopsis thaliana accessions and extensively phenotyped these lines for 1,859 phenotypes under both stable and fluctuating conditions. We show that natural variation in the plasmotype results in both additive and epistatic effects across all phenotypic categories. Plasmotypes that induce more additive phenotypic changes also cause more epistatic effects, suggesting a possible common basis for both additive and epistatic effects. On average, epistatic interactions explained twice as much of the variance in phenotypes as additive plasmotype effects. The impact of plasmotypic variation was also more pronounced under fluctuating and stressful environmental conditions. Thus, the phenotypic impact of variation in plasmotypes is the outcome of multi-level nucleotype-plasmotype-environment interactions and, as such, the plasmotype is likely to serve as a reservoir of variation that is predominantly exposed under certain conditions. The production of cybrids using haploid inducers is a rapid and precise method for assessment of the phenotypic effects of natural variation in organellar genomes. It will facilitate efficient screening of unique nucleotype-plasmotype combinations to both improve our understanding of natural variation in these combinations and identify favourable combinations to enhance plant performance.

Sustainable bioenergy for climate mitigation: developing drought-tolerant trees and grasses

BACKGROUND AND AIMS

Bioenergy crops are central to climate mitigation strategies that utilize biogenic carbon, such as BECCS (bioenergy with carbon capture and storage), alongside the use of biomass for heat, power, liquid fuels and, in the future, biorefining to chemicals. Several promising lignocellulosic crops are emerging that have no food role - fast-growing trees and grasses - but are well suited as bioenergy feedstocks, including Populus, Salix, Arundo, Miscanthus, Panicum and Sorghum.

SCOPE

These promising crops remain largely undomesticated and, until recently, have had limited germplasm resources. In order to avoid competition with food crops for land and nature conservation, it is likely that future bioenergy crops will be grown on marginal land that is not needed for food production and is of poor quality and subject to drought stress. Thus, here we define an ideotype for drought tolerance that will enable biomass production to be maintained in the face of moderate drought stress. This includes traits that can readily be measured in wide populations of several hundred unique genotypes for genome-wide association studies, alongside traits that are informative but can only easily be assessed in limited numbers or training populations that may be more suitable for genomic selection. Phenotyping, not genotyping, is now the major bottleneck for progress, since in all lignocellulosic crops studied extensive use has been made of next-generation sequencing such that several thousand markers are now available and populations are emerging that will enable rapid progress for drought-tolerance breeding. The emergence of novel technologies for targeted genotyping by sequencing are particularly welcome. Genome editing has already been demonstrated for Populus and offers significant potential for rapid deployment of drought-tolerant crops through manipulation of ABA receptors, as demonstrated in Arabidopsis, with other gene targets yet to be tested.

CONCLUSIONS

Bioenergy is predicted to be the fastest-developing renewable energy over the coming decade and significant investment over the past decade has been made in developing genomic resources and in collecting wild germplasm from within the natural ranges of several tree and grass crops. Harnessing these resources for climate-resilient crops for the future remains a challenge but one that is likely to be successful.

A genetical metabolomics approach for bioprospecting plant biosynthetic gene clusters

OBJECTIVE

Plants produce a plethora of specialized metabolites to defend themselves against pathogens and insects, to attract pollinators and to communicate with other organisms. Many of these are also applied in the clinic and in agriculture. Genes encoding the enzymes that drive the biosynthesis of these metabolites are sometimes physically grouped on the chromosome, in regions called biosynthetic gene clusters (BGCs). Several algorithms have been developed to identify plant BGCs, but a large percentage of predicted gene clusters upon further inspection do not show coexpression or do not encode a single functional biosynthetic pathway. Hence, further prioritization is needed.

RESULTS

Here, we introduce a strategy to systematically evaluate potential functions of predicted BGCs by superimposing their locations on metabolite quantitative trait loci (mQTLs). We show the feasibility of such an approach by integrating automated BGC prediction with mQTL datasets originating from a recombinant inbred line (RIL) population of Oryza sativa and a genome-wide association study (GWAS) of Arabidopsis thaliana. In these data, we identified several links for which the enzyme content of the BGCs matches well with the chemical features observed in the metabolite structure, suggesting that this method can effectively guide bioprospecting of plant BGCs.

A cheminformatics approach to characterize metabolomes in stable-isotope-labeled organisms

We report a computational approach (implemented in MS-DIAL 3.0; http://prime.psc.riken.jp/) for metabolite structure characterization using fully ¹³C-labeled and non-labeled plants and LC-MS/MS. Our approach facilitates carbon number determination and metabolite classification for unknown molecules. Applying our method to 31 tissues from 12 plant species, we assigned 1,092 structures and 344 formulae to 3,604 carbon-determined metabolite ions, 69 of which were found to represent structures currently not listed in metabolome databases.

Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency

In recent years developments in plant phenomic approaches and facilities have gradually caught up with genomic approaches. An opportunity lies ahead to dissect complex, quantitative traits when both genotype and phenotype can be assessed at a high level of detail. This is especially true for the study of natural variation in photosynthetic efficiency, for which forward genetics studies have yielded only a little progress in our understanding of the genetic layout of the trait. High-throughput phenotyping, primarily from chlorophyll fluorescence imaging, should help to dissect the genetics of photosynthesis at the different levels of both plant physiology and development. Specific emphasis should be directed towards understanding the acclimation of the photosynthetic machinery in fluctuating environments, which may be crucial for the identification of genetic variation for relevant traits in food crops. Facilities should preferably be designed to accommodate phenotyping of photosynthesis-related traits in such environments. The use of forward genetics to study the genetic architecture of photosynthesis is likely to lead to the discovery of novel traits and/or genes that may be targeted in breeding or bio-engineering approaches to improve crop photosynthetic efficiency. In the near future, big data approaches will play a pivotal role in data processing and streamlining the phenotype-to-gene identification pipeline.

Epigenetic mapping of the Arabidopsis metabolome reveals mediators of the epigenotype-phenotype map

Identifying the sources of natural variation underlying metabolic differences between plants will enable a better understanding of plant metabolism and provide insights into the regulatory networks that govern plant growth and morphology. So far, however, the contribution of epigenetic variation to metabolic diversity has been largely ignored. In the present study, we utilized a panel of Arabidopsis thaliana epigenetic recombinant inbred lines (epiRILs) to assess the impact of epigenetic variation on the metabolic composition. Thirty epigenetic QTL (QTL^epi) were detected, which partly overlap with QTL^epi linked to growth and morphology. In an effort to identify causal candidate genes in the QTL^epi regions and their putative trans-targets, we performed in silico small RNA and qPCR analyses. Differentially expressed genes were further studied by phenotypic and metabolic analyses of knockout mutants. Three genes were detected that recapitulated the detected QTL^epi effects, providing evidence for epigenetic regulation in cis and in trans. These results indicate that epigenetic mechanisms impact metabolic diversity, possibly via small RNAs, and thus aid in further disentangling the complex epigenotype-phenotype map.

Assessment of heterosis in two Arabidopsis thaliana common-reference mapping populations

Hybrid vigour, or heterosis, has been of tremendous importance in agriculture for the improvement of both crops and livestock. Notwithstanding large efforts to study the phenomenon of heterosis in the last decades, the identification of common molecular mechanisms underlying hybrid vigour remain rare. Here, we conducted a systematic survey of the degree of heterosis in Arabidopsis thaliana hybrids. For this purpose, two overlapping Arabidopsis hybrid populations were generated by crossing a large collection of naturally occurring accessions to two common reference lines. In these Arabidopsis hybrid populations the range of heterosis for several developmental and yield related traits was examined, and the relationship between them was studied. The traits under study were projected leaf area at 17 days after sowing, flowering time, height of the main inflorescence, number of side branches from the main stem or from the rosette base, total seed yield, seed weight, seed size and the estimated number of seeds per plant. Predominantly positive heterosis was observed for leaf area and height of the main inflorescence, whereas mainly negative heterosis was observed for rosette branching. For the other traits both positive and negative heterosis was observed in roughly equal amounts. For flowering time and seed size only low levels of heterosis were detected. In general the observed heterosis levels were highly trait specific. Furthermore, no correlation was observed between heterosis levels and the genetic distance between the parental lines. Since all selected lines were a part of the Arabidopsis genome wide association (GWA) mapping panel, a genetic mapping approach was applied to identify possible regions harbouring genetic factors causal for heterosis, with separate calculations for additive and dominance effects. Our study showed that the genetic mechanisms underlying heterosis were highly trait specific in our hybrid populations and greatly depended on the genetic background, confirming the elusive character of heterosis.

Genes and gene clusters related to genotype and drought-induced variation in saccharification potential, lignin content and wood anatomical traits in Populus nigra

Wood is a renewable resource that can be employed for the production of second generation biofuels by enzymatic saccharification and subsequent fermentation. Knowledge on how the saccharification potential is affected by genotype-related variation of wood traits and drought is scarce. Here, we used three Populus nigra L. genotypes from habitats differing in water availability to (i) investigate the relationships between wood anatomy, lignin content and saccharification and (ii) identify genes and co-expressed gene clusters related to genotype and drought-induced variation in wood traits and saccharification potential. The three poplar genotypes differed in wood anatomy, lignin content and saccharification potential. Drought resulted in reduced cambial activity, decreased vessel and fiber lumina, and increased the saccharification potential. The saccharification potential was unrelated to lignin content as well as to most wood anatomical traits. RNA sequencing of the developing xylem revealed that 1.5% of the analyzed genes were differentially expressed in response to drought, while 67% differed among the genotypes. Weighted gene correlation network analysis identified modules of co-expressed genes correlated with saccharification potential. These modules were enriched in gene ontology terms related to cell wall polysaccharide biosynthesis and modification and vesicle transport, but not to lignin biosynthesis. Among the most strongly saccharification-correlated genes, those with regulatory functions, especially kinases, were prominent. We further identified transcription factors whose transcript abundances differed among genotypes, and which were co-regulated with genes for biosynthesis and modifications of hemicelluloses and pectin. Overall, our study suggests that the regulation of pectin and hemicellulose metabolism is a promising target for improving wood quality of second generation bioenergy crops. The causal relationship of the identified genes and pathways with saccharification potential needs to be validated in further experiments.

Parental DNA Methylation States Are Associated with Heterosis in Epigenetic Hybrids

Despite the importance and wide exploitation of heterosis in commercial crop breeding, the molecular mechanisms behind this phenomenon are not completely understood. Recent studies have implicated changes in DNA methylation and small RNAs in hybrid performance; however, it remains unclear whether epigenetic changes are a cause or a consequence of heterosis. Here, we analyze a large panel of over 500 Arabidopsis (Arabidopsis thaliana) epigenetic hybrid plants (epiHybrids), which we derived from near-isogenic but epigenetically divergent parents. This proof-of-principle experimental system allowed us to quantify the contribution of parental methylation differences to heterosis. We measured traits such as leaf area, growth rate, flowering time, main stem branching, rosette branching, and final plant height and observed several strong positive and negative heterotic phenotypes among the epiHybrids. Using an epigenetic quantitative trait locus mapping approach, we were able to identify specific differentially methylated regions in the parental genomes that are associated with hybrid performance. Sequencing of methylomes, transcriptomes, and genomes of selected parent-epiHybrid combinations further showed that these parental differentially methylated regions most likely mediate the remodeling of methylation and transcriptional states at specific loci in the hybrids. Taken together, our data suggest that locus-specific epigenetic divergence between the parental lines can directly or indirectly trigger heterosis in Arabidopsis hybrids independent of genetic changes. These results add to a growing body of evidence that points to epigenetic factors as one of the key determinants of hybrid performance.

QTLepi Mapping in Arabidopsis thaliana

While DNA sequence variation is known to be a major driver of phenotypic divergence, epigenetic variation has long been disregarded. One reason for that was the lack of suitable tools. The creation of epigenetically divergent but otherwise largely isogenic Arabidopsis populations has now alleviated some of these constraints. Epigenetic recombinant inbred line (epiRIL) populations allow for examining the effects of epigenetic variation on phenotypes. In addition, epiRILs enabled the development of epigenetic quantitative trait locus (QTL^epi) mapping, an approach to identify causal epigenetic factors. Here, we describe the successive steps of QTL^epi mapping in a broad sense, from the creation of epigenetically divergent populations to the identification of causal genes underlying particular phenotypes in Arabidopsis.

Genetic Components of Root Architecture Remodeling in Response to Salt Stress

Salinity of the soil is highly detrimental to plant growth. Plants respond by a redistribution of root mass between main and lateral roots, yet the genetic machinery underlying this process is still largely unknown. Here, we describe the natural variation among 347 Arabidopsis thaliana accessions in root system architecture (RSA) and identify the traits with highest natural variation in their response to salt. Salt-induced changes in RSA were associated with 100 genetic loci using genome-wide association studies. Two candidate loci associated with lateral root development were validated and further investigated. Changes in CYP79B2 expression in salt stress positively correlated with lateral root development in accessions, and cyp79b2 cyp79b3 double mutants developed fewer and shorter lateral roots under salt stress, but not in control conditions. By contrast, high HKT1 expression in the root repressed lateral root development, which could be partially rescued by addition of potassium. The collected data and multivariate analysis of multiple RSA traits, available through the Salt_NV_Root App, capture root responses to salinity. Together, our results provide a better understanding of effective RSA remodeling responses, and the genetic components involved, for plant performance in stress conditions.

Genome-Wide Association Mapping Reveals That Specific and Pleiotropic Regulatory Mechanisms Fine-Tune Central Metabolism and Growth in Arabidopsis

Central metabolism is a coordinated network that is regulated at multiple levels by resource availability and by environmental and developmental cues. Its genetic architecture has been investigated by mapping metabolite quantitative trait loci (QTL). A more direct approach is to identify enzyme activity QTL, which distinguishes between cis-QTL in structural genes encoding enzymes and regulatory trans-QTL. Using genome-wide association studies, we mapped QTL for 24 enzyme activities, nine metabolites, three structural components, and biomass in Arabidopsis thaliana We detected strong cis-QTL for five enzyme activities. A cis-QTL for UDP-glucose pyrophosphorylase activity in the UGP1 promoter is maintained through balancing selection. Variation in acid invertase activity reflects multiple evolutionary events in the promoter and coding region of VAC-INVcis-QTL were also detected for ADP-glucose pyrophosphorylase, fumarase, and phosphoglucose isomerase activity. We detected many trans-QTL, including transcription factors, E3 ligases, protein targeting components, and protein kinases, and validated some by knockout analysis. trans-QTL are more frequent but tend to have smaller individual effects than cis-QTL. We detected many colocalized QTL, including a multitrait QTL on chromosome 4 that affects six enzyme activities, three metabolites, protein, and biomass. These traits are coordinately modified by different ACCELERATED CELL DEATH6 alleles, revealing a trade-off between metabolism and defense against biotic stress.

Natural variation in life history strategy of Arabidopsis thaliana determines stress responses to drought and insects of different feeding guilds

Plants are sessile organisms and, consequently, are exposed to a plethora of stresses in their local habitat. As a result, different populations of a species are subject to different selection pressures leading to adaptation to local conditions and intraspecific divergence. The annual brassicaceous plant Arabidopsis thaliana is an attractive model for ecologists and evolutionary biologists due to the availability of a large collection of resequenced natural accessions. Accessions of A. thaliana display one of two different life cycle strategies: summer and winter annuals. We exposed a collection of 308 European Arabidopsis accessions, that have been genotyped for 250K SNPs, to a range of stresses: one abiotic stress (drought), four biotic stresses (Pieris rapae caterpillars, Plutella xylostella caterpillars, Frankliniella occidentalis thrips and Myzus persicae aphids) and two combined stresses (drought plus P. rapae and Botrytis cinerea fungus plus P. rapae). We identified heritable genetic variation for responses to the different stresses, estimated by narrow-sense heritability. We found that accessions displaying different life cycle strategies differ in their response to stresses. Winter annuals are more resistant to drought, aphids and thrips and summer annuals are more resistant to P. rapae and P. xylostella caterpillars. Summer annuals are also more resistant to the combined stresses of drought plus P. rapae and infection by the fungus Botryris cinerea plus herbivory by P. rapae. Adaptation to drought displayed a longitudinal gradient. Finally, trade-offs were recorded between the response to drought and responses to herbivory by caterpillars of the specialist herbivore P. rapae.

AraQTL - workbench and archive for systems genetics in Arabidopsis thaliana

Genetical genomics studies uncover genome-wide genetic interactions between genes and their transcriptional regulators. High-throughput measurement of gene expression in recombinant inbred line populations has enabled investigation of the genetic architecture of variation in gene expression. This has the potential to enrich our understanding of the molecular mechanisms affected by and underlying natural variation. Moreover, it contributes to the systems biology of natural variation, as a substantial number of experiments have resulted in a valuable amount of interconnectable phenotypic, molecular and genotypic data. A number of genetical genomics studies have been published for Arabidopsis thaliana, uncovering many expression quantitative trait loci (eQTLs). However, these complex data are not easily accessible to the plant research community, leaving most of the valuable genetic interactions unexplored as cross-analysis of these studies is a major effort. We address this problem with AraQTL (http://www.bioinformatics.nl/Ara QTL/), an easily accessible workbench and database for comparative analysis and meta-analysis of all published Arabidopsis eQTL datasets. AraQTL provides a workbench for comparing, re-using and extending upon the results of these experiments. For example, one can easily screen a physical region for specific local eQTLs that could harbour candidate genes for phenotypic QTLs, or detect gene-by-environment interactions by comparing eQTLs under different conditions.

Genetic architecture of plant stress resistance: multi-trait genome-wide association mapping

Plants are exposed to combinations of various biotic and abiotic stresses, but stress responses are usually investigated for single stresses only. Here, we investigated the genetic architecture underlying plant responses to 11 single stresses and several of their combinations by phenotyping 350 Arabidopsis thaliana accessions. A set of 214 000 single nucleotide polymorphisms (SNPs) was screened for marker-trait associations in genome-wide association (GWA) analyses using tailored multi-trait mixed models. Stress responses that share phytohormonal signaling pathways also share genetic architecture underlying these responses. After removing the effects of general robustness, for the 30 most significant SNPs, average quantitative trait locus (QTL) effect sizes were larger for dual stresses than for single stresses. Plants appear to deploy broad-spectrum defensive mechanisms influencing multiple traits in response to combined stresses. Association analyses identified QTLs with contrasting and with similar responses to biotic vs abiotic stresses, and below-ground vs above-ground stresses. Our approach allowed for an unprecedented comprehensive genetic analysis of how plants deal with a wide spectrum of stress conditions.

De novo assembly, functional annotation, and analysis of the giant reed (Arundo donax L.) leaf transcriptome provide tools for the development of a biofuel feedstock

BACKGROUND

Arundo donax has attracted renewed interest as a potential candidate energy crop for use in biomass-to-liquid fuel conversion processes and biorefineries. This is due to its high productivity, adaptability to marginal land conditions, and suitability for biofuel and biomaterial production. Despite its importance, the genomic resources currently available for supporting the improvement of this species are still limited.

RESULTS

We used RNA sequencing (RNA-Seq) to de novo assemble and characterize the A. donax leaf transcriptome. The sequencing generated 1249 million clean reads that were assembled using single-k-mer and multi-k-mer approaches into 62,596 unique sequences (unitranscripts) with an N50 of 1134 bp. TransDecoder and Trinotate software suites were used to obtain putative coding sequences and annotate them by mapping to UniProtKB/Swiss-Prot and UniRef90 databases, searching for known transcripts, proteins, protein domains, and signal peptides. Furthermore, the unitranscripts were annotated by mapping them to the NCBI non-redundant, GO and KEGG pathway databases using Blast2GO. The transcriptome was also characterized by BLAST searches to investigate homologous transcripts of key genes involved in important metabolic pathways, such as lignin, cellulose, purine, and thiamine biosynthesis and carbon fixation. Moreover, a set of homologous transcripts of key genes involved in stomatal development and of genes coding for stress-associated proteins (SAPs) were identified. Additionally, 8364 simple sequence repeat (SSR) markers were identified and surveyed. SSRs appeared more abundant in non-coding regions (63.18%) than in coding regions (36.82%). This SSR dataset represents the first marker catalogue of A. donax. 53 SSRs (PolySSRs) were then predicted to be polymorphic between ecotype-specific assemblies, suggesting genetic variability in the studied ecotypes.

CONCLUSIONS

This study provides the first publicly available leaf transcriptome for the A. donax bioenergy crop. The functional annotation and characterization of the transcriptome will be highly useful for providing insight into the molecular mechanisms underlying its extreme adaptability. The identification of homologous transcripts involved in key metabolic pathways offers a platform for directing future efforts in genetic improvement of this species. Finally, the identified SSRs will facilitate the harnessing of untapped genetic diversity. This transcriptome should be of value to ongoing functional genomics and genetic studies in this crop of paramount economic importance.

Genome-Wide Association Mapping and Genomic Prediction Elucidate the Genetic Architecture of Morphological Traits in Arabidopsis

Quantitative traits in plants are controlled by a large number of genes and their interaction with the environment. To disentangle the genetic architecture of such traits, natural variation within species can be explored by studying genotype-phenotype relationships. Genome-wide association studies that link phenotypes to thousands of single nucleotide polymorphism markers are nowadays common practice for such analyses. In many cases, however, the identified individual loci cannot fully explain the heritability estimates, suggesting missing heritability. We analyzed 349 Arabidopsis accessions and found extensive variation and high heritabilities for different morphological traits. The number of significant genome-wide associations was, however, very low. The application of genomic prediction models that take into account the effects of all individual loci may greatly enhance the elucidation of the genetic architecture of quantitative traits in plants. Here, genomic prediction models revealed different genetic architectures for the morphological traits. Integrating genomic prediction and association mapping enabled the assignment of many plausible candidate genes explaining the observed variation. These genes were analyzed for functional and sequence diversity, and good indications that natural allelic variation in many of these genes contributes to phenotypic variation were obtained. For ACS11, an ethylene biosynthesis gene, haplotype differences explaining variation in the ratio of petiole and leaf length could be identified.

Effects of Multi-Generational Stress Exposure and Offspring Environment on the Expression and Persistence of Transgenerational Effects in Arabidopsis thaliana

Plant phenotypes can be affected by environments experienced by their parents. Parental environmental effects are reported for the first offspring generation and some studies showed persisting environmental effects in second and further offspring generations. However, the expression of these transgenerational effects proved context-dependent and their reproducibility can be low. Here we study the context-dependency of transgenerational effects by evaluating parental and transgenerational effects under a range of parental induction and offspring evaluation conditions. We systematically evaluated two factors that can influence the expression of transgenerational effects: single- versus multiple-generation exposure and offspring environment. For this purpose, we exposed a single homozygous Arabidopsis thaliana Col-0 line to salt stress for up to three generations and evaluated offspring performance under control and salt conditions in a climate chamber and in a natural environment. Parental as well as transgenerational effects were observed in almost all traits and all environments and traced back as far as great-grandparental environments. The length of exposure exerted strong effects; multiple-generation exposure often reduced the expression of the parental effect compared to single-generation exposure. Furthermore, the expression of transgenerational effects strongly depended on offspring environment for rosette diameter and flowering time, with opposite effects observed in field and greenhouse evaluation environments. Our results provide important new insights into the occurrence of transgenerational effects and contribute to a better understanding of the context-dependency of these effects.

Improved batch correction in untargeted MS-based metabolomics

INTRODUCTION

Batch effects in large untargeted metabolomics experiments are almost unavoidable, especially when sensitive detection techniques like mass spectrometry (MS) are employed. In order to obtain peak intensities that are comparable across all batches, corrections need to be performed. Since non-detects, i.e., signals with an intensity too low to be detected with certainty, are common in metabolomics studies, the batch correction methods need to take these into account.

OBJECTIVES

This paper aims to compare several batch correction methods, and investigates the effect of different strategies for handling non-detects.

METHODS

Batch correction methods usually consist of regression models, possibly also accounting for trends within batches. To fit these models quality control samples (QCs), injected at regular intervals, can be used. Also study samples can be used, provided that the injection order is properly randomized. Normalization methods, not using information on batch labels or injection order, can correct for batch effects as well. Introducing two easy-to-use quality criteria, we assess the merits of these batch correction strategies using three large LC-MS and GC-MS data sets of samples from Arabidopsis thaliana.

RESULTS

The three data sets have very different characteristics, leading to clearly distinct behaviour of the batch correction strategies studied. Explicit inclusion of information on batch and injection order in general leads to very good corrections; when enough QCs are available, also general normalization approaches perform well. Several approaches are shown to be able to handle non-detects-replacing them with very small numbers such as zero seems the worst of the approaches considered.

CONCLUSION

The use of quality control samples for batch correction leads to good results when enough QCs are available. If an experiment is properly set up, batch correction using the study samples usually leads to a similar high-quality correction, but has the advantage that more metabolites are corrected. The strategy for handling non-detects is important: choosing small values like zero can lead to suboptimal batch corrections.

Genome-wide association mapping of time-dependent growth responses to moderate drought stress in Arabidopsis

Large areas of arable land are often confronted with irregular rainfall resulting in limited water availability for part(s) of the growing seasons, which demands research for drought tolerance of plants. Natural variation was observed for biomass accumulation upon controlled moderate drought stress in 324 natural accessions of Arabidopsis. Improved performance under drought stress was correlated with early flowering and lack of vernalization requirement, indicating overlap in the regulatory networks of flowering time and drought response or correlated responses of these traits to natural selection. In addition, plant size was negatively correlated with relative water content (RWC) independent of the absolute water content (WC), indicating a prominent role for soluble compounds. Growth in control and drought conditions was determined over time and was modelled by an exponential function. Genome-wide association (GWA) mapping of temporal plant size data and of model parameters resulted in the detection of six time-dependent quantitative trait loci (QTLs) strongly associated with drought. Most QTLs would not have been identified if plant size was determined at a single time point. Analysis of earlier reported gene expression changes upon drought enabled us to identify for each QTL the most likely candidates.

Biomass traits and candidate genes for bioenergy revealed through association genetics in coppiced European Populus nigra (L.)

BACKGROUND

Second generation (2G) bioenergy from lignocellulosic feedstocks has the potential to develop as a sustainable source of renewable energy; however, significant hurdles still remain for large-scale commercialisation. Populus is considered as a promising 2G feedstock and understanding the genetic basis of biomass yield and feedstock quality are a research priority in this model tree species.

RESULTS

We report the first coppiced biomass study for 714 members of a wide population of European black poplar (Populus nigra L.), a native European tree, selected from 20 river populations ranging in latitude and longitude between 40.5 and 52.1°N and 1.0 and 16.4°E, respectively. When grown at a single site in southern UK, significant Site of Origin (SO) effects were seen for 14 of the 15 directly measured or derived traits including biomass yield, leaf area and stomatal index. There was significant correlation (p < 0.001) between biomass yield traits over 3 years of harvest which identified leaf size and cell production as strong predictors of biomass yield. A 12 K Illumina genotyping array (constructed from 10,331 SNPs in 14 QTL regions and 4648 genes) highlighted significant population genetic structure with pairwise FST showing strong differentiation (p < 0.001) between the Spanish and Italian subpopulations. Robust associations reaching genome-wide significance are reported for main stem height and cell number per leaf; two traits tightly linked to biomass yield. These genotyping and phenotypic data were also used to show the presence of significant isolation by distance (IBD) and isolation by adaption (IBA) within this population.

CONCLUSIONS

The three associations identified reaching genome-wide significance at p < 0.05 include a transcription factor; a putative stress response gene and a gene of unknown function. None of them have been previously linked to bioenergy yield; were shown to be differentially expressed in a panel of three selected genotypes from the collection and represent exciting, novel candidates for further study in a bioenergy tree native to Europe and Euro-Asia. A further 26 markers (22 genes) were found to reach putative significance and are also of interest for biomass yield, leaf area, epidermal cell expansion and stomatal patterning. This research on European P. nigra provides an important foundation for the development of commercial native trees for bioenergy and for advanced, molecular breeding in these species.

Novel Genes Affecting the Interaction between the Cabbage Whitefly and Arabidopsis Uncovered by Genome-Wide Association Mapping

Plants have evolved a variety of ways to defend themselves against biotic attackers. This has resulted in the presence of substantial variation in defense mechanisms among plants, even within a species. Genome-wide association (GWA) mapping is a useful tool to study the genetic architecture of traits, but has so far only had limited exploitation in studies of plant defense. Here, we study the genetic architecture of defense against the phloem-feeding insect cabbage whitefly (Aleyrodes proletella) in Arabidopsis thaliana. We determined whitefly performance, i.e. the survival and reproduction of whitefly females, on 360 worldwide selected natural accessions and subsequently performed GWA mapping using 214,051 SNPs. Substantial variation for whitefly adult survival and oviposition rate (number of eggs laid per female per day) was observed between the accessions. We identified 39 candidate SNPs for either whitefly adult survival or oviposition rate, all with relatively small effects, underpinning the complex architecture of defense traits. Among the corresponding candidate genes, i.e. genes in linkage disequilibrium (LD) with candidate SNPs, none have previously been identified as a gene playing a role in the interaction between plants and phloem-feeding insects. Whitefly performance on knock-out mutants of a number of candidate genes was significantly affected, validating the potential of GWA mapping for novel gene discovery in plant-insect interactions. Our results show that GWA analysis is a very useful tool to gain insight into the genetic architecture of plant defense against herbivorous insects, i.e. we identified and validated several genes affecting whitefly performance that have not previously been related to plant defense against herbivorous insects.

GWA Mapping of Anthocyanin Accumulation Reveals Balancing Selection of MYB90 in Arabidopsis thaliana

Induction of anthocyanin accumulation by osmotic stress was assessed in 360 accessions of Arabidopsis thaliana. A wide range of natural variation, with phenotypes ranging from green to completely red/purple rosettes, was observed. A genome wide association (GWA) mapping approach revealed that sequence diversity in a small 15 kb region on chromosome 1 explained 40% of the variation observed. Sequence and expression analyses of alleles of the candidate gene MYB90 identified a causal polymorphism at amino acid (AA) position 210 of this transcription factor of the anthocyanin biosynthesis pathway. This amino acid discriminates the two most frequent alleles of MYB90. Both alleles are present in a substantial part of the population, suggesting balancing selection between these two alleles. Analysis of the geographical origin of the studied accessions suggests that the macro climate is not the driving force behind positive or negative selection for anthocyanin accumulation. An important role for local climatic conditions is, therefore, suggested. This study emphasizes that GWA mapping is a powerful approach to identify alleles that are under balancing selection pressure in nature.

Genome-wide association mapping of growth dynamics detects time-specific and general quantitative trait loci

Growth is a complex trait determined by the interplay between many genes, some of which play a role at a specific moment during development whereas others play a more general role. To identify the genetic basis of growth, natural variation in Arabidopsis rosette growth was followed in 324 accessions by a combination of top-view imaging, high-throughput image analysis, modelling of growth dynamics, and end-point fresh weight determination. Genome-wide association (GWA) mapping of the temporal growth data resulted in the detection of time-specific quantitative trait loci (QTLs), whereas mapping of model parameters resulted in another set of QTLs related to the whole growth curve. The positive correlation between projected leaf area (PLA) at different time points during the course of the experiment suggested the existence of general growth factors with a function in multiple developmental stages or with prolonged downstream effects. Many QTLs could not be identified when growth was evaluated only at a single time point. Eleven candidate genes were identified, which were annotated to be involved in the determination of cell number and size, seed germination, embryo development, developmental phase transition, or senescence. For eight of these, a mutant or overexpression phenotype related to growth has been reported, supporting the identification of true positives. In addition, the detection of QTLs without obvious candidate genes implies the annotation of novel functions for underlying genes.

Genome-Wide Association Mapping of Fertility Reduction upon Heat Stress Reveals Developmental Stage-Specific QTLs in Arabidopsis thaliana

For crops that are grown for their fruits or seeds, elevated temperatures that occur during flowering and seed or fruit set have a stronger effect on yield than high temperatures during the vegetative stage. Even short-term exposure to heat can have a large impact on yield. In this study, we used Arabidopsis thaliana to study the effect of short-term heat exposure on flower and seed development. The impact of a single hot day (35°C) was determined in more than 250 natural accessions by measuring the lengths of the siliques along the main inflorescence. Two sensitive developmental stages were identified, one before anthesis, during male and female meiosis, and one after anthesis, during fertilization and early embryo development. In addition, we observed a correlation between flowering time and heat tolerance. Genome-wide association mapping revealed four quantitative trait loci (QTLs) strongly associated with the heat response. These QTLs were developmental stage specific, as different QTLs were detected before and after anthesis. For a number of QTLs, T-DNA insertion knockout lines could validate assigned candidate genes. Our findings show that the regulation of complex traits can be highly dependent on the developmental timing.

Epigenetic basis of morphological variation and phenotypic plasticity in Arabidopsis thaliana

Epigenetics is receiving growing attention in the plant science community. Epigenetic modifications are thought to play a particularly important role in fluctuating environments. It is hypothesized that epigenetics contributes to plant phenotypic plasticity because epigenetic modifications, in contrast to DNA sequence variation, are more likely to be reversible. The population of decrease in DNA methylation 1-2 (ddm1-2)-derived epigenetic recombinant inbred lines (epiRILs) in Arabidopsis thaliana is well suited for studying this hypothesis, as DNA methylation differences are maximized and DNA sequence variation is minimized. Here, we report on the extensive heritable epigenetic variation in plant growth and morphology in neutral and saline conditions detected among the epiRILs. Plant performance, in terms of branching and leaf area, was both reduced and enhanced by different quantitative trait loci (QTLs) in the ddm1-2 inherited epigenotypes. The variation in plasticity associated significantly with certain genomic regions in which the ddm1-2 inherited epigenotypes caused an increased sensitivity to environmental changes, probably due to impaired genetic regulation in the epiRILs. Many of the QTLs for morphology and plasticity overlapped, suggesting major pleiotropic effects. These findings indicate that epigenetics contributes substantially to variation in plant growth, morphology, and plasticity, especially under stress conditions.

Epigenetic variation contributes to environmental adaptation of Arabidopsis thaliana

Epigenetic variation is frequently observed in plants and direct relationships between differences in DNA methylation and phenotypic responses to changing environments have often been described. The identification of contributing genetic loci, however, was until recently hampered by the lack of suitable genome wide mapping resources that specifically segregate for epigenetic marks. The development of epi-RIL populations in the model species Arabidopsis thaliana has alleviated this obstacle, enabling the accurate genetic analysis of epigenetic variation. Comprehensive morphological phenotyping of a ddm1 derived epi-RIL population in different environments and subsequent epi-QTL mapping revealed a high number of epi-QTLs and pleiotropic effects of several DMRs on numerous traits. For a number of these epi-QTLs epistatic interactions could be observed, further adding to the complexity of epigenetic regulation. Moreover, linkage to epigenetic marks indicated a specific role for DNA-methylation variation, rather than TE transposition, in plastic responses to changing environments. These findings provide supportive evidence for a role of epigenetic regulation in evolutionary and adaptive processes.

Genetic resources for quantitative trait analysis: novelty and efficiency in design from an Arabidopsis perspective

The use of genetic resources for the analysis of quantitative traits finds its roots in crop breeding but has seen a rejuvenation in Arabidopsis thaliana thanks to specific tools and genomic approaches. Although widely used in numerous crop and natural species, many approaches were first developed in this reference plant. We will discuss the scientific background and historical use of mapping populations in Arabidopsis and highlight the technological innovations that drove the development of novel strategies. We will especially lay emphasis on the methodologies used to generate the diverse population types and designate possible applications. Finally we highlight some of the most recent developments in generating genetic mapping resources and suggest specific usage for these novel tools and concepts.

Hybrid recreation by reverse breeding in Arabidopsis thaliana

Hybrid crop varieties are traditionally produced by selecting and crossing parental lines to evaluate hybrid performance. Reverse breeding allows doing the opposite: selecting uncharacterized heterozygotes and generating parental lines from them. With these, the selected heterozygotes can be recreated as F1 hybrids, greatly increasing the number of hybrids that can be screened in breeding programs. Key to reverse breeding is the suppression of meiotic crossovers in a hybrid plant to ensure the transmission of nonrecombinant chromosomes to haploid gametes. These gametes are subsequently regenerated as doubled-haploid (DH) offspring. Each DH carries combinations of its parental chromosomes, and complementing pairs can be crossed to reconstitute the initial hybrid. Achiasmatic meiosis and haploid generation result in uncommon phenotypes among offspring owing to chromosome number variation. We describe how these features can be dealt with during a reverse-breeding experiment, which can be completed in six generations (∼1 year).

Exploiting natural variation in Arabidopsis

Natural variation for many traits is present within the species Arabidopsis thaliana. This chapter describes the use of natural variation to elucidate genes underlying the regulation of quantitative traits. It deals with the development and use of mapping populations, the detection and handling of genetic markers, the phenotyping of quantitative traits, and, finally, QTL analyses. The focus of the chapter is on the use and development of recombinant inbred lines, but other types of segregating populations, including genome-wide association mapping in natural populations, are also discussed.

Predictive modelling of complex agronomic and biological systems

Biological systems are tremendously complex in their functioning and regulation. Studying the multifaceted behaviour and describing the performance of such complexity has challenged the scientific community for years. The reduction of real-world intricacy into simple descriptive models has therefore convinced many researchers of the usefulness of introducing mathematics into biological sciences. Predictive modelling takes such an approach another step further in that it takes advantage of existing knowledge to project the performance of a system in alternating scenarios. The ever growing amounts of available data generated by assessing biological systems at increasingly higher detail provide unique opportunities for future modelling and experiment design. Here we aim to provide an overview of the progress made in modelling over time and the currently prevalent approaches for iterative modelling cycles in modern biology. We will further argue for the importance of versatility in modelling approaches, including parameter estimation, model reduction and network reconstruction. Finally, we will discuss the difficulties in overcoming the mathematical interpretation of in vivo complexity and address some of the future challenges lying ahead.

Genetic analysis of metabolome-phenotype interactions: from model to crop species

The past decade has seen increased interest from the scientific community, and particularly plant biologists, in integrating metabolic approaches into research aimed at unraveling phenotypic diversity and its underlying genetic variation. Advances in plant metabolomics have enabled large-scale analyses that have identified qualitative and quantitative variation in the metabolic content of various species, and this variation has been linked to genetic factors through genetic-mapping approaches, providing a glimpse of the genetic architecture of the plant metabolome. Parallel analyses of morphological phenotypes and physiological performance characteristics have further enhanced our understanding of the complex molecular mechanisms regulating these quantitative traits. This review aims to illustrate the advantages of including assessments of phenotypic and metabolic diversity in investigations of the genetic basis of complex traits, and the value of this approach in studying agriculturally important crops. We highlight the ground-breaking work on model species and discuss recent achievements in important crop species.

Multi-dimensional regulation of metabolic networks shaping plant development and performance

The metabolome is an integral part of a plant's life cycle and determines for a large part its external phenotype. It is the final, internal product of chemical interactions, obtained through developmental, genetic, and environmental inputs, and as such, it defines the state of a plant in terms of development and performance. Understanding its regulation will provide knowledge and new insights into the biochemical pathways and genetic interactions that shape the plant and its surroundings. In this review, we will focus on four dimensions that contribute to the huge diversity of metabolomes and we will illustrate how this diversity shapes the plant in terms of development and performance: (i) temporal regulation: the metabolome is extremely dynamic and temporal changes in the environment can have an immense impact on its composition; (ii) spatial regulation: metabolites can be very specific, in both quantitative and qualitative terms, to specialized organs, tissues, and cell types; (iii) environmental regulation: the metabolic profile of plants is highly dependent on environmental signals, such as light, temperature, and nutrients, and very susceptible to biotic and abiotic stresses; and (iv) genetic regulation: the biosynthesis, structure, and accumulation of metabolites have a genetic origin, and there is quantitative and qualitative variation for metabolomes within a species. We will address the contribution of these dimensions to the wide diversity of metabolomes and highlight how the multi-dimensional regulation of metabolism defines the plant's phenotype.

Reverse breeding in Arabidopsis thaliana generates homozygous parental lines from a heterozygous plant

Traditionally, hybrid seeds are produced by crossing selected inbred lines. Here we provide a proof of concept for reverse breeding, a new approach that simplifies meiosis such that homozygous parental lines can be generated from a vigorous hybrid individual. We silenced DMC1, which encodes the meiotic recombination protein DISRUPTED MEIOTIC cDNA1, in hybrids of A. thaliana, so that non-recombined parental chromosomes segregate during meiosis. We then converted the resulting gametes into adult haploid plants, and subsequently into homozygous diploids, so that each contained half the genome of the original hybrid. From 36 homozygous lines, we selected 3 (out of 6) complementing parental pairs that allowed us to recreate the original hybrid by intercrossing. In addition, this approach resulted in a complete set of chromosome-substitution lines. Our method allows the selection of a single choice offspring from a segregating population and preservation of its heterozygous genotype by generating homozygous founder lines.

Genetic analysis of morphological traits in a new, versatile, rapid-cycling Brassica rapa recombinant inbred line population

A recombinant inbred line (RIL) population was produced based on a wide cross between the rapid-cycling and self-compatible genotypes L58, a Caixin vegetable type, and R-o-18, a yellow sarson oil type. A linkage map based on 160 F7 lines was constructed using 100 Single nucleotide polymorphisms (SNPs), 130 AFLP®, 27 InDel, and 13 publicly available SSR markers. The map covers a total length of 1150 centiMorgan (cM) with an average resolution of 4.3 cM/marker. To demonstrate the versatility of this new population, 17 traits, related to plant architecture and seed characteristics, were subjected to quantitative trait loci (QTL) analysis. A total of 47 QTLs were detected, each explaining between 6 and 54% of the total phenotypic variance for the concerned trait. The genetic analysis shows that this population is a useful new tool for analyzing genetic variation for interesting traits in B. rapa, and for further exploitation of the recent availability of the B. rapa whole genome sequence for gene cloning and gene function analysis.

Advances in genetical genomics of plants

Natural variation provides a valuable resource to study the genetic regulation of quantitative traits. In quantitative trait locus (QTL) analyses this variation, captured in segregating mapping populations, is used to identify the genomic regions affecting these traits. The identification of the causal genes underlying QTLs is a major challenge for which the detection of gene expression differences is of major importance. By combining genetics with large scale expression profiling (i.e. genetical genomics), resulting in expression QTLs (eQTLs), great progress can be made in connecting phenotypic variation to genotypic diversity. In this review we discuss examples from human, mouse, Drosophila, yeast and plant research to illustrate the advances in genetical genomics, with a focus on understanding the regulatory mechanisms underlying natural variation. With their tolerance to inbreeding, short generation time and ease to generate large families, plants are ideal subjects to test new concepts in genetics. The comprehensive resources which are available for Arabidopsis make it a favorite model plant but genetical genomics also found its way to important crop species like rice, barley and wheat. We discuss eQTL profiling with respect to cis and trans regulation and show how combined studies with other ‘omics’ technologies, such as metabolomics and proteomics may further augment current information on transcriptional, translational and metabolomic signaling pathways and enable reconstruction of detailed regulatory networks. The fast developments in the ‘omics’ area will offer great potential for genetical genomics to elucidate the genotype-phenotype relationships for both fundamental and applied research.

Redefining plant systems biology: from cell to ecosystem

Molecular biologists typically restrict systems biology to cellular levels. By contrast, ecologists define biological systems as communities of interacting individuals at different trophic levels that process energy, nutrient and information flows. Modern plant breeding needs to increase agricultural productivity while decreasing the ecological footprint. This requires a holistic systems biology approach that couples different aggregation levels while considering the variables that affect these biological systems from cell to community. The challenge is to generate accurate experimental data that can be used together with modelling concepts and techniques that allow experimentally verifying in silico predictions. The coupling of aggregation levels in plant sciences, termed Integral Quantification of Biological Organization (IQ(BiO)), might enhance our abilities to generate new desired plant phenotypes.

Metabolomics: the chemistry between ecology and genetics

Metabolomics is a fast developing field of comprehensive untargeted chemical analyses. It has many applications and can in principle be used on any organism without prior knowledge of the metabolome or genome. The amount of functional information that is acquired with metabolomics largely depends on whether a metabolome database has been developed for the focal species. Metabolomics is a level downstream from transcriptomics and proteomics and has been widely advertised as a functional genomics and systems biology tool. Indeed, it has been successfully applied to link phenotypes to genotypes in the model plant Arabidopsis thaliana. Metabolomics is also increasingly being used in ecology (ecological metabolomics) and environmental sciences (environmental metabolomics). In ecology, the technique has led to novel insights into the mechanisms of plant resistance to herbivores. Some of the most commonly used analytical metabolomic platforms are briefly discussed in this review, as well as their limitations. We will mainly focus on the application of metabolomics in plant ecology and genetics.

What has natural variation taught us about plant development, physiology, and adaptation?

Nearly 100 genes and functional polymorphisms underlying natural variation in plant development and physiology have been identified. In crop plants, these include genes involved in domestication traits, such as those related to plant architecture, fruit and seed structure and morphology, as well as yield and quality traits improved by subsequent crop breeding. In wild plants, comparable traits have been dissected mainly in Arabidopsis thaliana. In this review, we discuss the major contributions of the analysis of natural variation to our understanding of plant development and physiology, focusing in particular on the timing of germination and flowering, plant growth and morphology, primary metabolism, and mineral accumulation. Overall, functional polymorphisms appear in all types of genes and gene regions, and they may have multiple mutational causes. However, understanding this diversity in relation to adaptation and environmental variation is a challenge for which tools are now available.

Starch as a major integrator in the regulation of plant growth

Rising demand for food and bioenergy makes it imperative to breed for increased crop yield. Vegetative plant growth could be driven by resource acquisition or developmental programs. Metabolite profiling in 94 Arabidopsis accessions revealed that biomass correlates negatively with many metabolites, especially starch. Starch accumulates in the light and is degraded at night to provide a sustained supply of carbon for growth. Multivariate analysis revealed that starch is an integrator of the overall metabolic response. We hypothesized that this reflects variation in a regulatory network that balances growth with the carbon supply. Transcript profiling in 21 accessions revealed coordinated changes of transcripts of more than 70 carbon-regulated genes and identified 2 genes (myo-inositol-1-phosphate synthase, a Kelch-domain protein) whose transcripts correlate with biomass. The impact of allelic variation at these 2 loci was shown by association mapping, identifying them as candidate lead genes with the potential to increase biomass production.

Genetical metabolomics: closing in on phenotypes

One of the long-standing goals in plant biology has been to link genotypic variation to natural variation in plant development and adaptive traits. From recent studies it has become clear that a complex interacting network is underlying phenotypic diversity. A major role in this regulatory mechanism is assigned to the metabolism since plants are extremely rich and variable in metabolic content profiles. Technological advances in detecting and quantifying biochemical content as well as novel experimental approaches have accelerated data generation and increased our understanding of regulatory mechanisms in plant biology. It is now clear that modern plant sciences can benefit enormously from integrated multidisciplinary approaches.

The role of natural variation in dissecting genetic regulation of primary metabolism

Primary carbohydrate metabolism plays an essential role in the growth and development of plants. Despite the fact that most of the intermediary steps in the metabolic pathways involved are known, knowledge about the genetic regulation of this complex biochemical network is limited. We have recently shown that exploring natural variation is an efficient approach to reveal genetic regulation at various stages along the path from genotype to phenotype. In this study genetic analyses were performed at the levels of gene expression, activity of a subset of enzymes involved in carbohydrate metabolism and abundance of the metabolites involved in the reactions catalyzed by these enzymes. Although a strong correlation was observed between the different entities analyzed, specific regulation of individual components could also be observed at different levels. These results show that the genetic regulation of plant carbohydrate metabolism is highly complex which advocates the application of multi-disciplinary approaches to disentangle the various interacting regulatory modes.

Integrative analyses of genetic variation in enzyme activities of primary carbohydrate metabolism reveal distinct modes of regulation in Arabidopsis thaliana

Multiparallel QTL analysis of 15 Arabidopsis primary carbohydrate metabolism enzymes reveals that traits affecting primary metabolism are often correlated.

Background

Plant primary carbohydrate metabolism is complex and flexible, and is regulated at many levels. Changes of transcript levels do not always lead to changes in enzyme activities, and these do not always affect metabolite levels and fluxes. To analyze interactions between these three levels of function, we have performed parallel genetic analyses of 15 enzyme activities involved in primary carbohydrate metabolism, transcript levels for their encoding structural genes, and a set of relevant metabolites. Quantitative analyses of each trait were performed in the Arabidopsis thaliana Ler × Cvi recombinant inbred line (RIL) population and subjected to correlation and quantitative trait locus (QTL) analysis.

Results

Traits affecting primary metabolism were often correlated, possibly due to developmental control affecting multiple genes, enzymes, or metabolites. Moreover, the activity QTLs of several enzymes co-localized with the expression QTLs (eQTLs) of their structural genes, or with metabolite accumulation QTLs of their substrates or products. In addition, many trait-specific QTLs were identified, revealing that there is also specific regulation of individual metabolic traits. Regulation of enzyme activities often occurred through multiple loci, involving both cis- and trans-acting transcriptional or post-transcriptional control of structural genes, as well as independently of the structural genes.

Conclusion

Future studies of the regulatory processes in primary carbohydrate metabolism will benefit from an integrative genetic analysis of gene transcription, enzyme activity, and metabolite content. The multiparallel QTL analyses of the various interconnected transducers of biological information flow, described here for the first time, can assist in determining the causes and consequences of genetic regulation at different levels of complex biological systems.

Quantitative genetics in the age of omics

The use of natural variation in the genetic dissection of quantitative traits has a long-standing tradition. Recent advances in high-throughput technologies for the quantification of biological molecules have shifted the focus in quantitative genetics from single traits to comprehensive large-scale analyses. So-called omic technologies now enable geneticists to take a look in the black box that translates genetic information into biological function. These processes include transcriptional and (post) translational regulation as well as metabolic signaling pathways. The progress made in analytical and statistical techniques now allows the construction of regulatory networks that integrate the different levels of the biological information flow from gene-to-function.