Abstract:MS performed the experiments, wrote the manuscript, and processed and analyzed data, AY wrote the manuscript and carried out metabolic analysis, CB carried out genotyping experiments, YC analyzed data, VS analyzed data, SH carried out genotyping and metabolic analysis, EK performed GLS measurements, CK peformed initial gtr1/2 experiment, AL verified analytical methods and assisted with statistical aid, H N-E provided gtr1/2 mutants and initial analysis, DK provided all the GLS mutants and GLS related measureme… Show more
“…Moreover, increasing the annotation rate by computational sciences in combination with ion mobility, spectral library, stable isotope labeling, and ultra-high-resolution MS will enhance the discovery in metabolite-based genome-wide association study (mGWAS) 296,297 and illuminate the diversity of metabolites in the plant kingdom. Although the advances in genomics enable one to discover the gene clusters and to decode the plant revolution from the viewpoint of metabolisms, the information of metabolomics is essential not only to validate the gene functions but also to offer new opportunities for genome mining that meets with novel metabolites.…”
Plants and their associated microbial communities are known to produce millions of metabolites, a majority of which are still not characterized and will be illuminated by the advance of metabolomics and the informatics techniques.
“…Moreover, increasing the annotation rate by computational sciences in combination with ion mobility, spectral library, stable isotope labeling, and ultra-high-resolution MS will enhance the discovery in metabolite-based genome-wide association study (mGWAS) 296,297 and illuminate the diversity of metabolites in the plant kingdom. Although the advances in genomics enable one to discover the gene clusters and to decode the plant revolution from the viewpoint of metabolisms, the information of metabolomics is essential not only to validate the gene functions but also to offer new opportunities for genome mining that meets with novel metabolites.…”
Plants and their associated microbial communities are known to produce millions of metabolites, a majority of which are still not characterized and will be illuminated by the advance of metabolomics and the informatics techniques.
“…This approach could be called the proximate strategy, which has been frequently used for finding candidate genes in GWAS or QTL studies ( Monclus et al 2012 ; Geng et al 2015 ; Su et al 2017 ; Vanous et al 2018 ). Alternatively, LD analysis can be used to search candidate genes with procedures as described by ( Slaten et al 2020 ). As a comparison, we also tried this method to find candidate genes that are in LD with the significant SNP.…”
With the advances in high-throughput sequencing technologies, it is not difficult to extract tens of thousands of single nucleotide polymorphisms (SNPs) across many individuals in a fast and cheap way, making it possible to perform genome-wide association studies (GWAS) of quantitative traits in outbred forest trees. It is very valuable to apply traditional breeding experiments in GWAS for identifying genome variants associated to ecologically and economically important traits in Populus. Here, we reported a GWAS of tree height measured at multiple time points from a randomized complete block design (RCBD), which was established with clones from an F1 hybrid population of Populus deltoides and Populus simonii. A total of 22,670 SNPs across 172 clones in the RCBD were obtained with restriction site-associated DNA sequencing (RADseq) technology. The multivariate mixed linear model was applied by incorporating the pedigree relationship matrix of individuals to test the association of each SNP to the tree heights over 8 time points. Consequently, 41 SNPs were identified significantly associated to the tree height under the p-value threshold determined by Bonferroni correction at the significant level of 0.01. These SNPs were distributed on all but 2 chromosomes (Chr02 and Chr18) and explained the phenotypic variance ranged from 0.26% to 2.64%, amounting to 63.68% in total. Comparison with previous mapping studies for poplar height as well as the candidate genes of these detected SNPs were also investigated. We therefore demonstrated that the application of multivariate linear mixed model to the longitudinal phenotypic data from the traditional breeding experimental design facilitated to identify far more genome-wide variants for tree height in poplar. The significant SNPs identified in this study would enhance understanding of molecular mechanism for growth traits and would accelerate marker-assisted breeding programs in Populus.
“…Interestingly, nitrogen and GSLs are bidirectionally coordinated with GSLs influencing nitrogen signaling and/or responses. A metabolic genome-wide association study measuring natural variation in amino acid content within Arabidopsis seeds found that two key GSL biosynthetic loci were causally associated with the level of free glutamine in the seed (Slaten et al, 2020). One possible explanation for this GSL to nitrogen connection comes from the observation that specific GSLs can function as growth and development regulators through interactions with different mechanisms including the TOR complex that integrates nitrogen availability into complex signaling networks (Katz et al, 2020; Katz et al, 2015; Malinovsky et al, 2017; Salehin et al, 2019).…”
Nitrogen is an essential element required for plant growth and productivity. Understanding the mechanisms and natural genetic variation underlying nitrogen use in plants will facilitate engineering plant nitrogen use to maximize crop productivity while minimizing environmental costs. To understand the scope of natural variation that may influence nitrogen use, we grew 1135 Arabidopsis thaliana natural genotypes on two nitrogen sources, nitrate and ammonium, and measured both developmental and defense metabolite traits. By using different environments and focused on multiple traits, we identified a wide array of different nitrogen responses. These responses are associated with a large number of genes, most of them not previously associated with nitrogen responses. Only a small portion of these genes appear to be shared between environments or traits while most of the detected genes are predominantly specific to a developmental or defense trait under a specific nitrogen source. Finally, by using a large population we were able to identify unique nitrogen responses, like preferring ammonium or nitrate, that appear to be generated by combinations of loci rather than a few large effect loci. This suggests that it may be possible to obtain novel phenotypes in complex nitrogen responses by manipulating sets of genes with small effects rather than solely focusing on large effect single gene manipulations.
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