Understanding the Evolution of Defense Metabolites in <i>Arabidopsis thaliana</i> Using Genome-wide Association Mapping

Chan, Eva; Rowe, Heather C.; Kliebenstein, Daniel J.

doi:10.1534/genetics.109.108522

Cited by 195 publications

(259 citation statements)

References 116 publications

(170 reference statements)

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“…FDR) and the confounding effect of population structure may explain this difference. This has been observed in a study of glucosinolate metabolites in Arabidopsis (Chan et al, 2010) and a study of leaf metabolic profiles in maize (Riedelsheimer et al, 2012). In the latter study, when comparing a linkage mapping experiment and a GWA scan, increased genetic variation was reported, suggesting that the genetic variability is greater in the GWAS, as it relies on a larger genetic pool (from several up to hundreds of individuals), whereas a linkage experiment relies on a much narrower genetic pool (i.e.…”

Section: Gwa For Metabolic Traitssupporting

confidence: 60%

Genome-Wide Association in Tomato Reveals 44 Candidate Loci for Fruit Metabolic Traits

Sauvage

Segura

Bauchet³

et al. 2014

Plant Physiology

202

217

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Genome-wide association studies have been successful in identifying genes involved in polygenic traits and are valuable for crop improvement. Tomato (Solanum lycopersicum) is a major crop and is highly appreciated worldwide for its health value. We used a core collection of 163 tomato accessions composed of S. lycopersicum, S. lycopersicum var cerasiforme, and Solanum pimpinellifolium to map loci controlling variation in fruit metabolites. Fruits were phenotyped for a broad range of metabolites, including amino acids, sugars, and ascorbate. In parallel, the accessions were genotyped with 5,995 single-nucleotide polymorphism markers spread over the whole genome. Genome-wide association analysis was conducted on a large set of metabolic traits that were stable over 2 years using a multilocus mixed model as a general method for mapping complex traits in structured populations and applied to tomato. We detected a total of 44 loci that were significantly associated with a total of 19 traits, including sucrose, ascorbate, malate, and citrate levels. These results not only provide a list of candidate loci to be functionally validated but also a powerful analytical approach for finding genetic variants that can be directly used for crop improvement and deciphering the genetic architecture of complex traits.

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Section: Gwa For Metabolic Traitssupporting

confidence: 60%

Genome-Wide Association in Tomato Reveals 44 Candidate Loci for Fruit Metabolic Traits

Sauvage

Segura

Bauchet³

et al. 2014

Plant Physiology

202

217

View full text Add to dashboard Cite

show abstract

“…and unknown physiological processes. Similar results were found for primary metabolic networks suggesting that this level of connectedness between a metabolic pathway and the plants physiological network is true across most pathways [38]. Thus, while the number of genes to consider is daunting, a solution may be to consider the physiological processes linked to a metabolic pathway as the basis of engineering rather than treating the genes as independent units.…”

Section: Introductionsupporting

confidence: 64%

“…Or alternatively do they show some form of epistasis that complicates modeling and prediction. Comparing epistasis versus additive interactions is largely impossible in GWA studies do to the non-random structure of the populations and instead requires more randomly structured population like recombinant inbred lines [38,42,43]. Analysis of secondary metabolite pathways using RILs has shown a high level of epistatic interactions amongst causal genes [29 ,44,45].…”

Section: Quantitative Trait Locus Mapping To Reverse Engineer the Shamentioning

confidence: 99%

Synthetic biology of metabolism: using natural variation to reverse engineer systems

Kliebenstein

2014

Current Opinion in Plant Biology

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A goal of metabolic engineering is to take a plant and introduce new or modify existing pathways in a directed and predictable fashion. However, existing data does not provide the necessary level of information to allow for predictive models to be generated. One avenue to reverse engineer the necessary information is to study the genetic control of natural variation in plant primary and secondary metabolism. These studies are showing that any engineering model will have to incorporate information about 1000s of genes in both the nuclear and organellar genome to optimize the function of the introduced pathway. Further, these genes may interact in an unpredictable fashion complicating any engineering approach as it moves from the one or two gene manipulation to higher order stacking efforts. Finally, metabolic engineering may be influenced by a previously unrecognized potential for a plant to measure the metabolites within it. In combination, these observations from natural variation provide a beginning to help improve current efforts at metabolic engineering. Introduction A significant goal of synthetic biology or biological engineering is to take an existant organism and alter it in a directed and predictive fashion to introduce a new phenotype that had not previously existed in that organism. Some of these efforts start with introducing a new metabolic pathway into an organism to provide a better source of a commercially important chemical or to make new chemicals entirely [1][2][3]. Other efforts are focused at taking agronomically important traits such as defensive chemicals, nitrogen fixation or perennial growth from one species and transferring these traits into other species that do not contain them [4 ,5,6]. However these efforts while exciting frequently run into great difficulty and for this review article, I will focus on one the potential of using information from natural variation studies to facilitate these efforts for metabolic engineering.To predictively engineer a new metabolic pathway into a plant with optimal efficiency requires a base level of knowledge that likely does not exist to any full level. To generate full predictive ability we would need much deeper understanding of the following questions. First, how many genes within the plant need to be manipulated to facilitate the integration of the new pathway into the organisms metabolic and regulatory network. How do these genes interact, are they solely additive or is there evidence of more complex epistasis that complicates predictive capacity? Finally, are these genes solely in the nuclear genome or is there causal variation also in the organellar genomes? Most efforts to answer these questions focus largely on forward or single-gene reverse genetics approaches which are highly time consuming and difficult to scale up to the necessary level.An alternative approach to understanding a system is to use the concept of reverse engineering [7,8]. The goal of reverse engineering is to take a functioning system, say an existing metabolic pathway, ...

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“…Gene discovery strategies exploiting natural variation in quantitative traits, including metabolite levels, have been extensively used in combination with genetic approaches (6)(7)(8)(9)(10)(11)(12). Analytical approaches applied in this research field are frequently focused on the quantification of individual or small families of compounds.…”

mentioning

confidence: 99%

Navigating natural variation in herbivory-induced secondary metabolism in coyote tobacco populations using MS/MS structural analysis

Baldwin

Gaquerel

2015

Proc. Natl. Acad. Sci. U.S.A.

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Natural variation can be extremely useful in unraveling the determinants of phenotypic trait evolution but has rarely been analyzed with unbiased metabolic profiling to understand how its effects are organized at the level of biochemical pathways. Native populations of Nicotiana attenuata, a wild tobacco species, have been shown to be highly genetically diverse for traits important for their interactions with insects. To resolve the chemodiversity existing in these populations, we developed a metabolomics and computational pipeline to annotate leaf metabolic responses to Manduca sexta herbivory. We selected seeds from 43 accessions of different populations from the southwestern United Statesincluding the well-characterized Utah 30th generation inbred accession-and grew 183 plants in the glasshouse for standardized herbivory elicitation. Metabolic profiles were generated from elicited leaves of each plant using a high-throughput ultra HPLC (UHPLC)-quadrupole TOFMS (qTOFMS) method, processed to systematically infer covariation patterns among biochemically related metabolites, as well as unknown ones, and finally assembled to map natural variation. Navigating this map revealed metabolic branch-specific variations that surprisingly only partly overlapped with jasmonate accumulation polymorphisms and deviated from canonical jasmonate signaling. Fragmentation analysis via indiscriminant tandem mass spectrometry (idMS/MS) was conducted with 10 accessions that spanned a large proportion of the variance found in the complete accession dataset, and compound spectra were computationally assembled into spectral similarity networks. The biological information captured by this networking approach facilitates the mining of the mass spectral data of unknowns with high natural variation, as demonstrated by the annotation of a strongly herbivory-inducible phenolic derivative, and can guide pathway analysis.plant-insect interactions | metabolomics | mass spectrometry | natural variation E lucidating the structure of metabolites underlying complex traits and the factors that maintain their variation in natural populations are important challenges in plant ecological studies (1). Many studies have notably shown that stress-responsive pathways that produce secondary metabolites are sporadically found across different plant taxa with extensive diversification (2). This important diversification suggests that particular metabolic systems have been recruited through natural selection when the set of compounds that they produce address specific ecological needs. Interactions with insects are important selection pressures that have sculpted plant metabolism, and many plant metabolites protect against herbivore attack and physical damage (3-5). The timely production of particular secondary metabolites in response to insect attack benefits plants by decreasing the costs of constitutive metabolite production. Trade-offs between defense metabolite productions and the intrinsic growth-related functions of central metabolic pathways likely prov...

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Understanding the Evolution of Defense Metabolites in Arabidopsis thaliana Using Genome-wide Association Mapping

Cited by 195 publications

References 116 publications

Genome-Wide Association in Tomato Reveals 44 Candidate Loci for Fruit Metabolic Traits

Genome-Wide Association in Tomato Reveals 44 Candidate Loci for Fruit Metabolic Traits

Synthetic biology of metabolism: using natural variation to reverse engineer systems

Navigating natural variation in herbivory-induced secondary metabolism in coyote tobacco populations using MS/MS structural analysis

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