Genomic Analysis of QTLs and Genes Altering Natural Variation in Stochastic Noise

Quantitative genetic analysis has long been used to study how natural variation of genotype can influence an organism's phenotype. While most studies have focused on genetic determinants of phenotypic average, it is rapidly becoming understood that stochastic noise is genetically determined. However, it is not known how many traits display genetic control of stochastic noise nor how broadly these stochastic loci are distributed within the genome. Understanding these questions is critical to our understanding of quantitative traits and how they relate to the underlying causal loci, especially since stochastic noise may be directly influenced by underlying changes in the wiring of regulatory networks. We identified QTLs controlling natural variation in stochastic noise of glucosinolates, plant defense metabolites, as well as QTLs for stochastic noise of related transcripts. These loci included stochastic noise QTLs unique for either transcript or metabolite variation. Validation of these loci showed that genetic polymorphism within the regulatory network alters stochastic noise independent of effects on corresponding average levels. We examined this phenomenon more globally, using transcriptomic datasets, and found that the Arabidopsis transcriptome exhibits significant, heritable differences in stochastic noise. Further analysis allowed us to identify QTLs that control genomic stochastic noise. Some genomic QTL were in common with those altering average transcript abundance, while others were unique to stochastic noise. Using a single isogenic population, we confirmed that natural variation at ELF3 alters stochastic noise in the circadian clock and metabolism. Since polymorphisms controlling stochastic noise in genomic phenotypes exist within wild germplasm for naturally selected phenotypes, this suggests that analysis of Arabidopsis evolution should account for genetic control of stochastic variance and average phenotypes. It remains to be determined if natural genetic variation controlling stochasticity is equally distributed across the genomes of other multi-cellular eukaryotes

Genetic Networks Controlling Structural Outcome of Glucosinolate Activation across Development

Most phenotypic variation present in natural populations is under polygenic control, largely determined by genetic variation at quantitative trait loci (QTLs). These genetic loci frequently interact with the environment, development, and each other, yet the importance of these interactions on the underlying genetic architecture of quantitative traits is not well characterized. To better study how epistasis and development may influence quantitative traits, we studied genetic variation in Arabidopsis glucosinolate activation using the moderately sized Bayreuth×Shahdara recombinant inbred population, in terms of number of lines. We identified QTLs for glucosinolate activation at three different developmental stages. Numerous QTLs showed developmental dependency, as well as a large epistatic network, centered on the previously cloned large-effect glucosinolate activation QTL, ESP. Analysis of Heterogeneous Inbred Families validated seven loci and all of the QTL×DPG (days post-germination) interactions tested, but was complicated by the extensive epistasis. A comparison of transcript accumulation data within 211 of these RILs showed an extensive overlap of gene expression QTLs for structural specifiers and their homologs with the identified glucosinolate activation loci. Finally, we were able to show that two of the QTLs are the result of whole-genome duplications of a glucosinolate activation gene cluster. These data reveal complex age-dependent regulation of structural outcomes and suggest that transcriptional regulation is associated with a significant portion of the underlying ontogenic variation and epistatic interactions in glucosinolate activation

The Complex Genetic Architecture of the Metabolome

Discovering links between the genotype of an organism and its metabolite levels can increase our understanding of metabolism, its controls, and the indirect effects of metabolism on other quantitative traits. Recent technological advances in both DNA sequencing and metabolite profiling allow the use of broad-spectrum, untargeted metabolite profiling to generate phenotypic data for genome-wide association studies that investigate quantitative genetic control of metabolism within species. We conducted a genome-wide association study of natural variation in plant metabolism using the results of untargeted metabolite analyses performed on a collection of wild Arabidopsis thaliana accessions. Testing 327 metabolites against >200,000 single nucleotide polymorphisms identified numerous genotype–metabolite associations distributed non-randomly within the genome. These clusters of genotype–metabolite associations (hotspots) included regions of the A. thaliana genome previously identified as subject to recent strong positive selection (selective sweeps) and regions showing trans-linkage to these putative sweeps, suggesting that these selective forces have impacted genome-wide control of A. thaliana metabolism. Comparing the metabolic variation detected within this collection of wild accessions to a laboratory-derived population of recombinant inbred lines (derived from two of the accessions used in this study) showed that the higher level of genetic variation present within the wild accessions did not correspond to higher variance in metabolic phenotypes, suggesting that evolutionary constraints limit metabolic variation. While a major goal of genome-wide association studies is to develop catalogues of intraspecific variation, the results of multiple independent experiments performed for this study showed that the genotype–metabolite associations identified are sensitive to environmental fluctuations. Thus, studies of intraspecific variation conducted via genome-wide association will require analyses of genotype by environment interaction. Interestingly, the network structure of metabolite linkages was also sensitive to environmental differences, suggesting that key aspects of network architecture are malleable

Anatomical and Physiological Plasticity in Leymus chinensis (Poaceae) along Large-Scale Longitudinal Gradient in Northeast China

Although it has been widely accepted that global changes will pose the most important constrains to plant survival and distribution, our knowledge of the adaptive mechanism for plant with large-scale environmental changes (e.g. drought and high temperature) remains limited.An experiment was conducted to examine anatomical and physiological plasticity in Leymus chinensis along a large-scale geographical gradient from 115° to 124°E in northeast China. Ten sites selected for plant sampling at the gradient have approximately theoretical radiation, but differ in precipitation and elevation. The significantly increasing in leaf thickness, leaf mass per area, vessel and vascular diameters, and decreasing in stoma density and stoma index exhibited more obvious xerophil-liked traits for the species from the moist meadow grassland sites in contrast to that from the dry steppe and desert sites. Significant increase in proline and soluble sugar accumulation, K(+)/Na(+) for the species with the increasing of stresses along the gradient showed that osmotic adjustment was enhanced.Obvious xerophytic anatomical traits and stronger osmotic adjustment in stress conditions suggested that the plants have much more anatomical and physiological flexibilities than those in non-stress habitats along the large-scale gradient

Genome-wide expression quantitative trait loci (eQTL) analysis in maize

<p>Abstract</p> <p>Background</p> <p>Expression QTL analyses have shed light on transcriptional regulation in numerous species of plants, animals, and yeasts. These microarray-based analyses identify regulators of gene expression as either cis-acting factors that regulate proximal genes, or trans-acting factors that function through a variety of mechanisms to affect transcript abundance of unlinked genes.</p> <p>Results</p> <p>A hydroponics-based genetical genomics study in roots of a <it>Zea mays </it>IBM2 Syn10 double haploid population identified tens of thousands of cis-acting and trans-acting eQTL. Cases of false-positive eQTL, which results from the lack of complete genomic sequences from both parental genomes, were described. A candidate gene for a trans-acting regulatory factor was identified through positional cloning. The unexpected regulatory function of a class I glutamine amidotransferase controls the expression of an ABA 8'-hydroxylase pseudogene.</p> <p>Conclusions</p> <p>Identification of a candidate gene underlying a trans-eQTL demonstrated the feasibility of eQTL cloning in maize and could help to understand the mechanism of gene expression regulation. Lack of complete genome sequences from both parents could cause the identification of false-positive cis- and trans-acting eQTL.</p

Quantitative and Qualitative Stem Rust Resistance Factors in Barley Are Associated with Transcriptional Suppression of Defense Regulons

Stem rust (Puccinia graminis f. sp. tritici; Pgt) is a devastating fungal disease of wheat and barley. Pgt race TTKSK (isolate Ug99) is a serious threat to these Triticeae grain crops because resistance is rare. In barley, the complex Rpg-TTKSK locus on chromosome 5H is presently the only known source of qualitative resistance to this aggressive Pgt race. Segregation for resistance observed on seedlings of the Q21861 × SM89010 (QSM) doubled-haploid (DH) population was found to be predominantly qualitative, with little of the remaining variance explained by loci other than Rpg-TTKSK. In contrast, analysis of adult QSM DH plants infected by field inoculum of Pgt race TTKSK in Njoro, Kenya, revealed several additional quantitative trait loci that contribute to resistance. To molecularly characterize these loci, Barley1 GeneChips were used to measure the expression of 22,792 genes in the QSM population after inoculation with Pgt race TTKSK or mock-inoculation. Comparison of expression Quantitative Trait Loci (eQTL) between treatments revealed an inoculation-dependent expression polymorphism implicating Actin depolymerizing factor3 (within the Rpg-TTKSK locus) as a candidate susceptibility gene. In parallel, we identified a chromosome 2H trans-eQTL hotspot that co-segregates with an enhancer of Rpg-TTKSK-mediated, adult plant resistance discovered through the Njoro field trials. Our genome-wide eQTL studies demonstrate that transcript accumulation of 25% of barley genes is altered following challenge by Pgt race TTKSK, but that few of these genes are regulated by the qualitative Rpg-TTKSK on chromosome 5H. It is instead the chromosome 2H trans-eQTL hotspot that orchestrates the largest inoculation-specific responses, where enhanced resistance is associated with transcriptional suppression of hundreds of genes scattered throughout the genome. Hence, the present study associates the early suppression of genes expressed in this host–pathogen interaction with enhancement of R-gene mediated resistance

An eQTL Analysis of Partial Resistance to Puccinia hordei in Barley

Background - Genetic resistance to barley leaf rust caused by Puccinia hordei involves both R genes and quantitative trait loci. The R genes provide higher but less durable resistance than the quantitative trait loci. Consequently, exploring quantitative or partial resistance has become a favorable alternative for controlling disease. Four quantitative trait loci for partial resistance to leaf rust have been identified in the doubled haploid Steptoe (St)/Morex (Mx) mapping population. Further investigations are required to study the molecular mechanisms underpinning partial resistance and ultimately identify the causal genes.Methodology/Principal Findings - We explored partial resistance to barley leaf rust using a genetical genomics approach. We recorded RNA transcript abundance corresponding to each probe on a 15K Agilent custom barley microarray in seedlings from St and Mx and 144 doubled haploid lines of the St/Mx population. A total of 1154 and 1037 genes were, respectively, identified as being P. hordei-responsive among the St and Mx and differentially expressed between P. hordei-infected St and Mx. Normalized ratios from 72 distant-pair hybridisations were used to map the genetic determinants of variation in transcript abundance by expression quantitative trait locus (eQTL) mapping generating 15685 eQTL from 9557 genes. Correlation analysis identified 128 genes that were correlated with resistance, of which 89 had eQTL co-locating with the phenotypic quantitative trait loci (pQTL). Transcript abundance in the parents and conservation of synteny with rice allowed us to prioritise six genes as candidates for Rphq11, the pQTL of largest effect, and highlight one, a phospholipid hydroperoxide glutathione peroxidase (HvPHGPx) for detailed analysis.Conclusions/Significance - The eQTL approach yielded information that led to the identification of strong candidate genes underlying pQTL for resistance to leaf rust in barley and on the general pathogen response pathway. The dataset will facilitate a systems appraisal of this host-pathogen interaction and, potentially, for other traits measured in this populatio

Suppression of Jasmonic Acid-Dependent Defense in Cotton Plant by the Mealybug Phenacoccus solenopsis

The solenopsis mealybug, Phenacoccus solenopsis, has been recently recognized as an aggressively invasive pest in China, and is now becoming a serious threat to the cotton industry in the country. Thus, it is necessary to investigate the molecular mechanisms employed by cotton for defending against P. solenopsis before the pest populations reach epidemic levels. Here, we examined the effects of exogenous jasmonic acid (JA), salicylic acid (SA), and herbivory treatments on feeding behavior and on development of female P. solenopsis. Further, we compared the volatile emissions of cotton plants upon JA, SA, and herbivory treatments, as well as the time-related changes in gossypol production and defense-related genes. Female adult P. solenopsis were repelled by leaves from JA-treated plant, but were not repelled by leaves from SA-treated plants. In contrast, females were attracted by leaves from plants pre-infested by P. solenopsis. The diverse feeding responses by P. solenopsis were due to the difference in volatile emission of plants from different treatments. Furthermore, we show that JA-treated plants slowed P. solenopsis development, but plants pre-infested by P. solenopsis accelerated its development. We also show that P. solenopsis feeding inhibited the JA-regulated gossypol production, and prevented the induction of JA-related genes. We conclude that P. solenopsis is able to prevent the activation of JA-dependent defenses associated with basal resistance to mealybugs

The LSD1-Interacting Protein GILP Is a LITAF Domain Protein That Negatively Regulates Hypersensitive Cell Death in Arabidopsis

Hypersensitive cell death, a form of avirulent pathogen-induced programmed cell death (PCD), is one of the most efficient plant innate immunity. However, its regulatory mechanism is poorly understood. AtLSD1 is an important negative regulator of PCD and only two proteins, AtbZIP10 and AtMC1, have been reported to interact with AtLSD1.To identify a novel regulator of hypersensitive cell death, we investigate the possible role of plant LITAF domain protein GILP in hypersensitive cell death. Subcellular localization analysis showed that AtGILP is localized in the plasma membrane and its plasma membrane localization is dependent on its LITAF domain. Yeast two-hybrid and pull-down assays demonstrated that AtGILP interacts with AtLSD1. Pull-down assays showed that both the N-terminal and the C-terminal domains of AtGILP are sufficient for interactions with AtLSD1 and that the N-terminal domain of AtLSD1 is involved in the interaction with AtGILP. Real-time PCR analysis showed that AtGILP expression is up-regulated by the avirulent pathogen Pseudomonas syringae pv. tomato DC3000 avrRpt2 (Pst avrRpt2) and fumonisin B1 (FB1) that trigger PCD. Compared with wild-type plants, transgenic plants overexpressing AtGILP exhibited significantly less cell death when inoculated with Pst avrRpt2, indicating that AtGILP negatively regulates hypersensitive cell death.These results suggest that the LITAF domain protein AtGILP localizes in the plasma membrane, interacts with AtLSD1, and is involved in negatively regulating PCD. We propose that AtGILP functions as a membrane anchor, bringing other regulators of PCD, such as AtLSD1, to the plasma membrane. Human LITAF domain protein may be involved in the regulation of PCD, suggesting the evolutionarily conserved function of LITAF domain proteins in the regulation of PCD

Network Analysis Identifies ELF3 as a QTL for the Shade Avoidance Response in Arabidopsis

Quantitative Trait Loci (QTL) analyses in immortal populations are a powerful method for exploring the genetic mechanisms that control interactions of organisms with their environment. However, QTL analyses frequently do not culminate in the identification of a causal gene due to the large chromosomal regions often underlying QTLs. A reasonable approach to inform the process of causal gene identification is to incorporate additional genome-wide information, which is becoming increasingly accessible. In this work, we perform QTL analysis of the shade avoidance response in the Bayreuth-0 (Bay-0, CS954) x Shahdara (Sha, CS929) recombinant inbred line population of Arabidopsis. We take advantage of the complex pleiotropic nature of this trait to perform network analysis using co-expression, eQTL and functional classification from publicly available datasets to help us find good candidate genes for our strongest QTL, SAR2. This novel network analysis detected EARLY FLOWERING 3 (ELF3; AT2G25930) as the most likely candidate gene affecting the shade avoidance response in our population. Further genetic and transgenic experiments confirmed ELF3 as the causative gene for SAR2. The Bay-0 and Sha alleles of ELF3 differentially regulate developmental time and circadian clock period length in Arabidopsis, and the extent of this regulation is dependent on the light environment. This is the first time that ELF3 has been implicated in the shade avoidance response and that different natural alleles of this gene are shown to have phenotypic effects. In summary, we show that development of networks to inform candidate gene identification for QTLs is a promising technique that can significantly accelerate the process of QTL cloning