Quantitative variation in responses to root spatial constraint within <i>Arabidopsis thaliana</i>

Among the myriad of environmental stimuli that plants utilize to regulate growth and development to optimize fitness are signals obtained from various sources in the rhizosphere that give an indication of the nutrient status and volume of media available. These signals include chemical signals from other plants, nutrient signals, and thigmotropic interactions that reveal the presence of obstacles to growth. Little is known about the genetics underlying the response of plants to physical constraints present within the rhizosphere. In this study, we show that there is natural variation among Arabidopsis thaliana accessions in their growth response to physical rhizosphere constraints and competition. We mapped growth quantitative trait loci that regulate a positive response of foliar growth to short physical constraints surrounding the root. This is a highly polygenic trait and, using quantitative validation studies, we showed that natural variation in EARLY FLOWERING3 (ELF3) controls the link between root constraint and altered shoot growth. This provides an entry point to study how root and shoot growth are integrated to respond to environmental stimuli

Transcriptional networks governing plant metabolism

AbstractEfficiently obtaining and utilizing energy and elements is critical for an organism to maximize its fitness. Optimizing these processes requires precise regulation and coordination of an organism’s metabolic networks in response to diverse environmental conditions and developmental stages. Metabolic regulation is often considered to largely occur by allosteric feedback where the metabolites directly influence the enzymes function. Recent work is showing that there is also an extensive role for transcriptional control of the enzyme encoding genes to construct the metabolic network in response to developmental and environmental stimuli. Within this review, we go through the extensive evidence of how transcription can coordinate the necessary metabolic shifts required to coordinate a plants metabolism with its development and environment. Additionally, we discuss evidence that the metabolites not only feed-back regulate the enzymes but also the upstream transcriptional processes, possibly to stabilize the system

Genetic variation in the nuclear and organellar genomes modulates stochastic variation in the metabolome, growth, and defense

Recent studies are starting to show that genetic control over stochastic variation is a key evolutionary solution of single celled organisms in the face of unpredictable environments. This has been expanded to show that genetic variation can alter stochastic variation in transcriptional processes within multi-cellular eukaryotes. However, little is known about how genetic diversity can control stochastic variation within more non-cell autonomous phenotypes. Using an Arabidopsis reciprocal RIL population, we showed that there is significant genetic diversity influencing stochastic variation in the plant metabolome, defense chemistry, and growth. This genetic diversity included loci specific for the stochastic variation of each phenotypic class that did not affect the other phenotypic classes or the average phenotype. This suggests that the organism's networks are established so that noise can exist in one phenotypic level like metabolism and not permeate up or down to different phenotypic levels. Further, the genomic variation within the plastid and mitochondria also had significant effects on the stochastic variation of all phenotypic classes. The genetic influence over stochastic variation within the metabolome was highly metabolite specific, with neighboring metabolites in the same metabolic pathway frequently showing different levels of noise. As expected from bet-hedging theory, there was more genetic diversity and a wider range of stochastic variation for defense chemistry than found for primary metabolism. Thus, it is possible to begin dissecting the stochastic variation of whole organismal phenotypes in multi-cellular organisms. Further, there are loci that modulate stochastic variation at different phenotypic levels. Finding the identity of these genes will be key to developing complete models linking genotype to phenotype

Isolate dependency of <em>Brassica rapa</em> resistance QTLs to <em>Botrytis cinerea</em>

Generalist necrotrophic pathogens including Botrytis cinerea cause significant yield and financial losses on Brassica crops. However, there is little knowledge about the mechanisms underlying the complex interactions encoded by both host and pathogen genomes in this interaction. This potentially includes multiple layers of plant defense and pathogen virulence mechanisms that could complicate in breeding broad spectrum resistance within Brassica species. Glucosinolates (GSLs) are a diverse group of defense metabolites that play a key role in interaction between Brassica and biotic attackers. In this study, we utilized a collection of diverse B. cinerea isolates to investigate resistance within the Brassica rapa R500 × IMB211 recombinant inbred line population. We tested variation on lesion development and glucosinolate accumulation in parental lines and all population lines. We then mapped quantitative trait loci (QTL) for both resistances to B. cinerea and defense metabolites in this population. Phenotypic analysis and QTL mapping demonstrate that the genetic basis of resistance to B. cinerea in B. rapa is isolate specific and polygenic with transgressive segregation that both parents contribute resistance alleles. QTLs controlling defensive GSLs are highly dependent on pathogen infection. An overlap of two QTLs identified between resistance to B. cinerea and defense metabolites also showed isolate specific effects. This work suggests that directly searching for resistance loci may not be the best approach at improving resistance in B. rapa to necrotrophic pathogen

The conserved transcription factors, MYB115 and MYB118, control expression of the newly evolved benzoyloxy glucosinolate pathway in <i>Arabidopsis thaliana</i>

The evolution of plant metabolic diversity is largely driven by gene duplication and ensuing sub-functionalization and/or neo-functionalization to generate new enzymatic activities. However, it is not clear whether the transcription factors (TFs) regulating these new enzyme encoding genes were required to co-evolve with these genes in a similar fashion or if these new genes can be captured by existing conserved TFs to provide the appropriate expression pattern. In this study, we found two conserved TFs, MYB115, and MYB118, co-expressed with the key enzyme encoding genes in the newly evolved benzoyloxy glucosinolate (GLS) pathway. These TFs interacted with the promoters of the GLS biosynthetic genes and negatively influenced their expression. Similarly, the GLS profiles of these two TFs knockouts showed that they influenced the aliphatic GLS accumulation within seed, leaf and flower, while they mainly expressed in seeds. Further studies indicated that they are functionally redundant and epistatically interact to control the transcription of GLS genes. Complementation study confirmed their roles in regulating the aliphatic GLS biosynthesis. These results suggest that the newly evolved enzyme encoding genes for novel metabolites can be regulated by conserved TFs, which helps to improve our model for newly evolved genes regulation

An integrative genetic study of rice metabolism, growth and stochastic variation reveals potential C/N partitioning loci

Studying the genetic basis of variation in plant metabolism has been greatly facilitated by genomic and metabolic profiling advances. In this study, we use metabolomics and growth measurements to map QTL in rice, a major staple crop. Previous rice metabolism studies have largely focused on identifying genes controlling major effect loci. To complement these studies, we conducted a replicated metabolomics analysis on a japonica (Lemont) by indica (Teqing) rice recombinant inbred line population and focused on the genetic variation for primary metabolism. Using independent replicated studies, we show that in contrast to other rice studies, the heritability of primary metabolism is similar to Arabidopsis. The vast majority of metabolic QTLs had small to moderate effects with significant polygenic epistasis. Two metabolomics QTL hotspots had opposing effects on carbon and nitrogen rich metabolites suggesting that they may influence carbon and nitrogen partitioning, with one locus co-localizing with SUSIBA2 (WRKY78). Comparing QTLs for metabolomic and a variety of growth related traits identified few overlaps. Interestingly, the rice population displayed fewer loci controlling stochastic variation for metabolism than was found in Arabidopsis. Thus, it is possible that domestication has differentially impacted stochastic metabolite variation more than average metabolite variation

Whole genome resequencing of Botrytis cinerea isolates identifies high levels of standing diversity

How standing genetic variation within a pathogen contributes to diversity in host/pathogen interactions is poorly understood, partly because most studied pathogens are host-specific, clonally reproducing organisms which complicates genetic analysis. In contrast, Botrytis cinerea is a sexually reproducing, true haploid ascomycete that can infect a wide range of diverse plant hosts. While previous work had shown significant genomic variation between two isolates, we proceeded to assess the level and frequency of standing variation in a population of B. cinerea. To begin measuring standing genetic variation in B. cinerea, we re-sequenced the genomes of 13 different isolates and aligned them to the previously sequenced T4 reference genome. In addition one of these isolates was resequenced from four independently repeated cultures. A high level of genetic diversity was found within the 13 isolates. Within this variation, we could identify clusters of genes with major effect polymorphisms, i.e., polymorphisms that lead to a predicted functional knockout, that surrounded genes involved in controlling vegetative incompatibility. The genotype at these loci was able to partially predict the interaction of these isolates in vegetative fusion assays showing that these loci control vegetative incompatibility. This suggests that the vegetative incompatibility loci within B. cinerea are associated with regions of increased genetic diversity. The genome re-sequencing of four clones from the one isolate (Grape) that had been independently propagated over 10 years showed no detectable spontaneous mutation. This suggests that B. cinerea does not display an elevated spontaneous mutation rate. Future work will allow us to test if, and how, this diversity may be contributing to the pathogen's broad host range