Currently, genetic variation is probably the most important basic resource for plant biology. In addition to the variation artificially generated by mutants in model plants, naturally occurring genetic variation is extensively found for most species, including Arabidopsis. In many cases, natural variation present among accessions is multigenic, which has historically hampered its analysis. However, the exploitation of this resource down to the molecular level has now become feasible, especially in model species like Arabidopsis, where several genes accounting for natural variation have already been identified. Dissecting this variation requires first a quantitative trait locus (QTL) analysis, which in Arabidopsis has proven very effective by using recombinant inbred lines (RILs). Second, identifying the particular gene and the nucleotide polymorphism underlying QTL is the major challenge, and is now feasible by combining high-throughput genetics and functional genomic strategies. The analysis of Arabidopsis natural genetic variation is providing unique knowledge from functional, ecological, and evolutionary perspectives. This is illustrated by reviewing current research in two different biological fields: flowering time and plant growth. The analysis of Arabidopsis natural variation for flowering time revealed the identity of several genes, some of which correspond to genes with previously unknown function. In addition, for many other traits such as those related to primary metabolism and plant growth, Arabidopsis QTL analyses are detecting loci with small effects that are not easily amenable by mutant approaches, and which might provide new insights into the networks of gene regulation.
SummaryUsing a highly synchronous in vitro tuberization system, in combination with an amplified restriction fragment polymorphism (AFLpt)-derived technique for RNA fingerprinting (cDNA-AFLPt), transcriptional changes at and around the time point of potato tuberization have been analyzed. The targeted expression analysis of a specific transcript coding for the major potato storage protein, patatin and a second transcript, coding for ADP-glucose pyrophosphorylase, a key gene in the starch biosynthetic pathway is described. This paper confirms that kinetics of expression revealed by cDNA-AFLP analysis are comparable to those found in Northern analysis. Furthermore, this paper reports the isolation and analysis of two tuberspecific transcript-derived fragments (TDFs) coding for the lipoxygenase enzyme, which are differentially induced around the time point of tuber formation. Analysis of the two Iox TDFs demonstrates that it is possible to dissect the expression modalities of individual transcripts, not independently detectable by Northern analysis. Finally, it is shown that using cDNA-AFLP, rapid and simple verification of band identity may be achieved. The results indicate that cDNA-AFLP is a broadly applicable technology for identifying developmentally regulated genes.
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.Metabolites are critical in biology, and plants are especially rich in diverse biochemical compounds. It has been estimated that over 100,000 metabolites can be found in plants, and each species may contain its own chemotypic expression pattern 1 . Moreover, substantial quantitative and qualitative variation in metabolite composition is often observed within plant species 2 .Although knowledge on the regulation of metabolite formation is increasing, for thousands of metabolites, their function in the plant, their biosynthetic pathway and the regulation thereof is still unknown. QTL analysis of natural variation, which can affect metabolites 3 , in segregating populations can identify loci explaining the observed variation 4 . In recent years, a few studies have focused on identifying QTLs regulating a specific group of known metabolites using detection methods directed toward specific metabolite groups 5-9 . However, recent advances in mass spectrometry-based metabolomics and data processing techniques should now allow large-scale QTL analyses of untargeted metabolic profiles, which may uncover previously unknown regulatory functions of loci in metabolic pathways. Using dedicated alignment software, it is now possible to perform an unbiased comparison of large numbers of metabolite-derived masses detectable in large numbers of samples arising from inherently large sets of genotypes (which are required for accurate mapping of QTLs) in an RIL population 10,11 . QTL mapping will result in the localization of loci, and ultimately genes, causal for the observed variation and will allow the discovery of coregulated compounds. In this way, genomewide genetic correlative metabolic analysis now becomes feasible, as we demonstrate here. RESULTS Metabolite variation is abundant and genetically controlledTo assess the natural variation in metabolite content present in A. thaliana, we performed HPLC-QTOF MS-based untargeted metabolic fingerprinting of acidified aqueous methanol extracts fr...
Accessions of a plant species can show considerable genetic differences that are analyzed effectively by using recombinant inbred line (RIL) populations. Here we describe the results of genomewide expression variation analysis in an RIL population of Arabidopsis thaliana. For many genes, variation in expression could be explained by expression quantitative trait loci (eQTLs). The nature and consequences of this variation are discussed based on additional genetic parameters, such as heritability and transgression and by examining the genomic position of eQTLs versus gene position, polymorphism frequency, and gene ontology. Furthermore, we developed an approach for genetic regulatory network construction by combining eQTL mapping and regulator candidate gene selection. The power of our method was shown in a case study of genes associated with flowering time, a well studied regulatory network in Arabidopsis. Results that revealed clusters of coregulated genes and their most likely regulators were in agreement with published data, and unknown relationships could be predicted.natural variation
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.
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