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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 P 50, 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 (T PM) best explains the differences in P 50, as well as P 12 and P 88. The association between embolism resistance and T PM 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. [ABSTRACT FROM AUTHOR]

Summary: 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Summary: 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. Significance Statement: The fields of genomics and phenomics in plant science have gone through a major revolution that has led to the technological and methodological maturation of both fields of study in the past decade. Expansion of high‐throughput phenotyping technology will soon allow the scaling up of forward genetics approaches in order to adequately study the genetic architecture of traits that may accelerate the much needed improvement of photosynthesis in crop plants. [ABSTRACT FROM AUTHOR]

Giant reed (Arundo donax L.) is a perennial rhizomatous grass, which has attracted great attention as a potential lignocellulosic feedstock for bioethanol production due to high biomass yield in marginal land areas, high polysaccharide content and low inhibitor levels in microbial fermentations. However, little is known about the trait variation that is available across a broad ecotypic panel of A. donax nor the traits that contribute most significantly to yield and growth in drought prone environments. A collection of 82 ecotypes of A. donax sampled across the Mediterranean basin was planted in a common garden experimental field in Savigliano, Italy. We analysed the collection using 367 clumps representing replicate plantings of 82 ecotypes for variation in 21 traits important for biomass accumulation and to identify the particular set of ecotypes with the most promising potential for biomass production. We measured morpho‐physiological, phenological and biomass traits and analysed causal relationships between traits and productivity characteristics assessed at leaf and canopy levels. The results identified differences among the 82 ecotypes for all studied traits: those showing the highest level of variability included stomatal resistance, stem density (StN), stem dry mass (StDM) and total biomass production (TotDM). Multiple regression analysis revealed that leaf area index, StDM, StN, number of nodes per stem, stem height and diameter were the most significant predictors of TotDM and the most important early selection criteria for bioenergy production from A. donax. These traits were used in a hierarchical cluster analysis to identify groups of similar ecotypes, and a selection was made of promising ecotypes for multiyear and multisite testing for biomass production. Heritability estimates were significant for all traits. The potential of this ecotype collection as a resource for studies of germplasm diversity and for the analysis of traits underpinning high productivity of A. donax is highlighted. A broad Euro‐Mediterranean panel of 82 ecotypes of giant reed (Arundo donax L.) were phenotyped in a common garden experimental field in Italy. Twenty one morpho‐physiological, phenological and biomass traits were measured and causal relationships were analysed between traits and productivity characteristics at leaf and canopy levels. Multiple regression analysis revealed that leaf area index, stem dry mass, stem density, number of nodes per stem, stem height, and diameter were the most significant predictors of total biomass production and the most important early selection criteria for bioenergy production from A. donax. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Arundo donax has attracted renewed interest as a potential candidate energy crop for use in biomassto- 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. [ABSTRACT FROM AUTHOR]

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 Ara QTL ( QTL/), an easily accessible workbench and database for comparative analysis and meta-analysis of all published Arabidopsis eQTL datasets. Ara QTL 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. [ABSTRACT FROM AUTHOR]

• 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 thalianaaccessions. 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

A complex phenotype such as seed germination is the result of several genetic and environmental cues and requires the concerted action of many genes. The use of well-structured recombinant inbred lines in combination with "omics" analysis can help to disentangle the genetic basis of such quantitative traits. This so-called genetical genomics approach can effectively capture both genetic and epistatic interactions. However, to understand how the environment interacts with genomic-encoded information, a better understanding of the perception and processing of environmental signals is needed. In a classical genetical genomics setup, this requires replication of the whole experiment in different environmental conditions. A novel generalized setup overcomes this limitation and includes environmental perturbation within a single experimental design. We developed a dedicated quantitative trait loci mapping procedure to implement this approach and used existing phenotypical data to demonstrate its power. In addition, we studied the genetic regulation of primary metabolism in dry and imbibed Arabidopsis (Arabidopsis thahana) seeds. In the metabolome, many changes were observed that were under both environmental and genetic controls and their interaction. This concept offers unique reduction of experimental load with minimal compromise of statistical power and is of great potential in the field of systems genetics, which requires a broad understanding of both plasticity and dynamic regulation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The article discusses the relationship between primary metabolism and potato tuber quality. It states that an analysis of the statistical associations between the metabolic and classical phenotypic traits is needed for identifying the putative indicators that may affect a metabolic network. Gas chromatography-time of flight-mass spectrometry which involves primary metabolite content of potato tubers was used.

In Arabidopsis, a variety of mapping populations have been used for the detection of quantitative trait loci (QTLs) responsible for natural variation. In this study, we present an overview of the advantages and disadvantages of the different types of populations used. To do this, we compare the results of both experimental and natural populations for the commonly analysed trait flowering time. It is expected that genome wide association (GWA) mapping will be an increasingly important tool for QTL mapping because of the high allelic richness and mapping resolution in natural populations. In Arabidopsis, GWA mapping becomes ever more facilitated by the increasing availability of re-sequenced genomes of many accessions. However, specifically designed mapping populations such as recombinant inbred lines and near isogenic lines will remain important. The high QTL detection power of such experimental populations can identify spurious GWA associations, and their unique genomic structure is superior for investigating the role of low-frequency alleles. Future QTL studies will therefore benefit from a combined approach of GWA and classical linkage analysis. [ABSTRACT FROM AUTHOR]

Gene expression differences between individuals within a species can be largely explained by differences in genetic background. The effect of genetic variants (alleles) of genes on expression can be studied in a multifactorial way by the application of genetical genomics or expression quantitative trait locus mapping. In this paper, we present a strategy to construct regulatory networks by the application of genetical genomics in combination with transcript profiling of mutants that are disrupted in single genes. We describe the network identification downstream of the receptor-like kinase ERECTA in Arabidopsis (Arabidopsis thaliana). Extending genetical genomics on the Landsberg erecta/Cape Verde Islands (Ler/Cvi) recombinant inbred population with expression profiling of monogenic mutants enabled the identification of regulatory networks in the so far elusive ERECTA signal transduction cascade. We provide evidence that ERECTA is the causal gene for the major hotspot for transcript regulation in the Arabidopsis Ler/Cvi recombinant inbred population. We further propose additional genetic variation between Ler and Cvi in loci of the signaling pathway downstream of ERECTA and suggest candidate genes underlying these loci. Integration of publicly available microarray expression data of other monogenic mutants allowed us to link ERECTA to a downstream mitogen-activated protein kinase signaling cascade. Our study shows that microarray data of monogenic mutants can be effectively used in combination with genetical genomics data to enhance the identification of genetic regulatory networks. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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-1phosphate 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. [ABSTRACT FROM AUTHOR]

In Arabidopsis recombinant inbred line (RIL) populations are widely used for quantitative trait locus (QTL) analyses. However, mapping analyses with this type of population can be limited because of the masking effects of major QTL and epistatic interactions of multiple QTL. An alternative type of immortal experimental population commonly used in plant species are sets of introgression lines. Here we introduce the development of a genomewide coverage near-isogenic line (NIL) population of Arabidopsis thaliana, by introgressing genomic regions from the Cape Verde Islands (Cvi) accession into the Landsberg erecta (Ler) genetic background. We have empirically compared the QTL mapping power of this new population with an already existing RIL population derived from the same parents. For that, we analyzed and mapped QTL affecting six developmental traits with different heritability. Overall, in the NIL population smaller-effect QTL than in the RIL population could be detected although the localization resolution was lower. Furthermore, we estimated the effect of population size and of the number of replicates on the detection power of QTL affecting the developmental traits. In general, population size is more important than the number of replicates to increase the mapping power of RILs, whereas for NILs several replicates are absolutely required. These analyses are expected to facilitate experimental design for QTL mapping using these two common types of segregating populations. [ABSTRACT FROM AUTHOR]

Variation for metabolite composition and content is often observed in plants. However, it is poorly understood to what extent this variation has a genetic basis. Here, we describe the genetic analysis of natural variation in the metabolite composition in Arabidopsis thaliana. Instead of focusing on specific metabolites, we have applied empirical untargeted metabolomics using liquid chromatography–time of flight mass spectrometry (LC-QTOF MS). This uncovered many qualitative and quantitative differences in metabolite accumulation between A. thaliana accessions. Only 13.4% of the mass peaks were detected in all 14 accessions analyzed. Quantitative trait locus (QTL) analysis of more than 2,000 mass peaks, detected in a recombinant inbred line (RIL) population derived from the two most divergent accessions, enabled the identification of QTLs for about 75% of the mass signals. More than one-third of the signals were not detected in either parent, indicating the large potential for modification of metabolic composition through classical breeding. [ABSTRACT FROM AUTHOR]

Water limitation is one of the most important factors limiting crop productivity world-wide and has likely been an important selective regime influencing the evolution of plant physiology. Understanding the genetic and physiological basis of drought adaptation is therefore important for improving crops as well as for understanding the evolution of wild species. Here, results are presented from quantitative trait loci (QTL) mapping of flowering time (a drought escape mechanism) and carbon stable isotope ratio ( δ13C) (a drought-avoidance mechanism) in Arabidopsis thaliana. Whole-genome scans were performed using multiple-QTL models for both additive and epistatic QTL effects. We mapped five QTL affecting flowering time and five QTL affecting δ13C, but two genomic regions contained QTL with effects on both traits, suggesting a potential pleiotropic relationship. In addition, we observed QTL–QTL interaction for both traits. Two δ13C QTL were captured in near-isogenic lines to further characterize their physiological basis. These experiments revealed allelic effects on δ13C through the upstream trait of stomatal conductance with subsequent consequences for whole plant transpiration efficiency and water loss. Our findings document considerable natural genetic variation in whole-plant, drought resistance physiology of Arabidopsis and highlight the value of quantitative genetic approaches for exploring functional relationships regulating physiology. [ABSTRACT FROM AUTHOR]

We profiled 162 lines of Arabidopsis for variation in transcript, protein and metabolite abundance using mRNA microarrays, two-dimensional polyacrylamide gel electrophoresis, gas chromatography time-of-flight mass spectrometry, liquid chromatography quadrupole time-of-flight mass spectrometry, and proton nuclear magnetic resonance. We added all publicly available phenotypic data from the same lines and mapped quantitative trait loci (QTL) for 40,580 molecular and 139 phenotypic traits. We found six QTL hot spots with major, system-wide effects, suggesting there are six breakpoints in a system otherwise buffered against many of the 500,000 SNPs. [ABSTRACT FROM AUTHOR]