Variation in gene expression, in addition to sequence polymorphisms, is known to influence developmental, physiological, and metabolic traits in plants. Genetic mapping populations have facilitated identification of expression quantitative trait loci (eQTL), the genetic determinants of variation in gene expression patterns. We used an introgression population developed from the wild desert-adapted Solanum pennellii and domesticated tomato (Solanum lycopersicum) to identify the genetic basis of transcript level variation. We established the effect of each introgression on the transcriptome and identified approximately 7,200 eQTL regulating the steady-state transcript levels of 5,300 genes. Barnes-Hut t-distributed stochastic neighbor embedding clustering identified 42 modules revealing novel associations between transcript level patterns and biological processes. The results showed a complex genetic architecture of global transcript abundance pattern in tomato. Several genetic hot spots regulating a large number of transcript level patterns relating to diverse biological processes such as plant defense and photosynthesis were identified. Important eQTL regulating transcript level patterns were related to leaf number and complexity as well as hypocotyl length. Genes associated with leaf development showed an inverse correlation with photosynthetic gene expression, but eQTL regulating genes associated with leaf development and photosynthesis were dispersed across the genome. This comprehensive eQTL analysis details the influence of these loci on plant phenotypes and will be a valuable community resource for investigations on the genetic effects of eQTL on phenotypic traits in tomato.
Quantitative Trait Locus (QTL) mapping is a powerful technique for dissecting the genetic basis of traits and species differences. Established tomato mapping populations between domesticated tomato (Solanum lycopersicum) and its more distant interfertile relatives typically follow a near isogenic line (NIL) design, such as the Solanum pennellii Introgression Line (IL) population, with a single wild introgression per line in an otherwise domesticated genetic background. Here we report on a new advanced backcross QTL mapping resource for tomato, derived from a cross between the M82 tomato cultivar and S. pennelli This so-called Backcrossed Inbred Line (BIL) population is comprised of a mix of BC2 and BC3 lines, with domesticated tomato as the recurrent parent. The BIL population is complementary to the existing S. pennellii IL population, with which it shares parents. Using the BILs we mapped traits for leaf complexity, leaflet shape, and flowering time. We demonstrate the utility of the BILs for fine-mapping QTL, particularly QTL initially mapped in the ILs, by fine-mapping several QTL to single or few candidate genes. Moreover, we confirm the value of a backcrossed population with multiple introgressions per line, such as the BILs, for epistatic QTL mapping. Our work was further enabled by the development of our own statistical inference and visualization tools, namely a heterogeneous Hidden Markov Model for genotyping the lines, and by using state of the art sparse regression techniques for QTL mapping.
The shade avoidance response (SAR) in crops can be detrimental to yield, as precious carbon resources are redirected to stem or petiole elongation at the expense of biomass production. While breeding efforts have inadvertently attenuated this response in staple crops through correlated selection for yield at high density, it has not been eliminated. The extensive work done in Arabidopsis has provided a detailed understanding of the SAR and can be used as a framework for understanding the SAR in crop species. Recent crop SAR works point to auxin as a key factor in regulating the SAR in several crop species. These works also clearly demonstrate that one model for crop SAR will not fit all, and thus we need to move forward with studying the genetic players of the SAR in several model crop species. In this review, we provide the current knowledge of the SAR as reported at the physiological and molecular levels.
Floral attraction traits can significantly affect pollinator visitation patterns, but adaptive evolution of these traits may be constrained by correlations with other traits. In some cases, molecular pathways contributing to floral attraction are well characterized, offering the opportunity to explore loci potentially underlying variation among individuals. Here, we quantify the range of variation in floral UV patterning (i.e. UV 'bulls-eye nectar guides) among crop and wild accessions of Brassica rapa. We then use experimental crosses to examine the genetic architecture, candidate loci and biochemical underpinnings of this patterning as well as phenotypic manipulations to test the ecological impact. We find qualitative variation in UV patterning between wild (commonly lacking UV patterns) and crop (commonly exhibiting UV patterns) accessions. Similar to the majority of crops, recombinant inbred lines (RILs) derived from an oilseed crop × WI fast-plant® cross exhibit UV patterns, the size of which varies extensively among genotypes. In RILs, we further observe strong statistical-genetic and QTL correlations within petal morphological traits and within measurements of petal UV patterning; however, correlations between morphology and UV patterning are weak or nonsignificant, suggesting that UV patterning is regulated and may evolve independently of overall petal size. HPLC analyses reveal a high concentration of sinapoyl glucose in UV-absorbing petal regions, which, in concert with physical locations of UV-trait QTLs, suggest a regulatory and structural gene as candidates underlying observed quantitative variation. Finally, insects prefer flowers with UV bulls-eye patterns over those that lack patterns, validating the importance of UV patterning in pollen-limited populations of B. rapa.
The circadian clock is a critical regulator of plant physiology and development, controlling key agricultural traits in crop plants. In addition, natural variation in circadian rhythms is important for local adaptation. However, quantitative modulation of circadian rhythms due to artificial selection has not yet been reported. Here we show that the circadian clock of cultivated tomato (Solanum lycopersicum) has slowed during domestication. Allelic variation of the tomato homolog of the Arabidopsis gene EID1 is responsible for a phase delay. Notably, the genomic region harboring EID1 shows signatures of a selective sweep. We find that the EID1 allele in cultivated tomatoes enhances plant performance specifically under long day photoperiods, suggesting that humans selected slower circadian rhythms to adapt the cultivated species to the long summer days it encountered as it was moved away from the equator.
Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants. This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud registration and plant feature measurement). This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance.
Plant biology is rapidly entering an era where we have the ability to conduct intricate studies that investigate how a plant interacts with the entirety of its environment. This requires complex, large studies to measure how plant genotypes simultaneously interact with a diverse array of environmental stimuli. Successful interpretation of the results from these studies requires us to transition away from the traditional standard of conducting an array of pairwise t tests toward more general linear modeling structures, such as those provided by the extendable ANOVA framework. In this Perspective, we present arguments for making this transition and illustrate how it will help to avoid incorrect conclusions in factorial interaction studies (genotype × genotype, genotype × treatment, and treatment × treatment, or higher levels of interaction) that are becoming more prevalent in this new era of plant biology.
Improved predictions of fitness and yield may be obtained by characterizing the genetic controls and environmental dependencies of organismal ontogeny. Elucidating the shape of growth curves may reveal novel genetic controls that single-time-point (STP) analyses do not because, in theory, infinite numbers of growth curves can result in the same final measurement. We measured leaf lengths and widths in Brassica rapa recombinant inbred lines (RILs) throughout ontogeny. We modeled leaf growth and allometry as function valued traits (FVT), and examined genetic correlations between these traits and aspects of phenology, physiology, circadian rhythms and fitness. We used RNA-seq to construct a SNP linkage map and mapped trait quantitative trait loci (QTL). We found genetic trade-offs between leaf size and growth rate FVT and uncovered differences in genotypic and QTL correlations involving FVT vs STPs. We identified leaf shape (allometry) as a genetic module independent of length and width and identified selection on FVT parameters of development. Leaf shape is associated with venation features that affect desiccation resistance. The genetic independence of leaf shape from other leaf traits may therefore enable crop optimization in leaf shape without negative effects on traits such as size, growth rate, duration or gas exchange.
Shade from neighboring plants limits light for photosynthesis; as a consequence, plants have a variety of strategies to avoid canopy shade and compete with their neighbors for light. Collectively the response to foliar shade is called the shade avoidance syndrome (SAS). The SAS includes elongation of a variety of organs, acceleration of flowering time, and additional physiological responses, which are seen throughout the plant life cycle. However, current mechanistic knowledge is mainly limited to shade-induced elongation of seedlings. Here we use phenotypic profiling of seedling, leaf, and flowering time traits to untangle complex SAS networks. We used over-representation analysis (ORA) of shade-responsive genes, combined with previous annotation, to logically select 59 known and candidate novel mutants for phenotyping. Our analysis reveals shared and separate pathways for each shade avoidance response. In particular, auxin pathway components were required for shade avoidance responses in hypocotyl, petiole, and flowering time, whereas jasmonic acid pathway components were only required for petiole and flowering time responses. Our phenotypic profiling allowed discovery of seventeen novel shade avoidance mutants. Our results demonstrate that logical selection of mutants increased success of phenotypic profiling to dissect complex traits and discover novel components.
Plants sense the foliar shade of competitors and alter their developmental programs through the shade-avoidance response. Internode and petiole elongation, and changes in overall leaf area and leaf mass per area, are the stereotypical architectural responses to foliar shade in the shoot. However, changes in leaf shape and complexity in response to shade remain incompletely, and qualitatively, described. Using a meta-analysis of more than 18,000 previously published leaflet outlines, we demonstrate that shade avoidance alters leaf shape in domesticated tomato (Solanum lycopersicum) and wild relatives. The effects of shade avoidance on leaf shape are subtle with respect to individual traits but are combinatorially strong. We then seek to describe the developmental origins of shade-induced changes in leaf shape by swapping plants between light treatments. Leaf size is light responsive late into development, but patterning events, such as stomatal index, are irrevocably specified earlier. Observing that shade induces increases in shoot apical meristem size, we then describe gene expression changes in early leaf primordia and the meristem using laser microdissection. We find that in leaf primordia, shade avoidance is not mediated through canonical pathways described in mature organs but rather through the expression of KNOTTED1-LIKE HOMEOBOX and other indeterminacy genes, altering known developmental pathways responsible for patterning leaf shape. We also demonstrate that shade-induced changes in leaf primordium gene expression largely do not overlap with those found in successively initiated leaf primordia, providing evidence against classic hypotheses that shaded leaf morphology results from the prolonged production of juvenile leaf types.
Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow the spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes.
Solanum pennellii is a wild tomato species endemic to Andean regions in South America, where it has evolved to thrive in arid habitats. Because of its extreme stress tolerance and unusual morphology, it is an important donor of germplasm for the cultivated tomato Solanum lycopersicum. Introgression lines (ILs) in which large genomic regions of S. lycopersicum are replaced with the corresponding segments from S. pennellii can show remarkably superior agronomic performance. Here we describe a high-quality genome assembly of the parents of the IL population. By anchoring the S. pennellii genome to the genetic map, we define candidate genes for stress tolerance and provide evidence that transposable elements had a role in the evolution of these traits. Our work paves a path toward further tomato improvement and for deciphering the mechanisms underlying the myriad other agronomic traits that can be improved with S. pennellii germplasm.
Leaf shape is mutable, changing in ways modulated by both development and environment within genotypes. A complete model of leaf phenotype would incorporate the changes in leaf shape during juvenile-to-adult phase transitions and the ontogeny of each leaf. Here, we provide a morphometric description of >33,000 leaflets from a set of tomato (Solanum spp) introgression lines grown under controlled environment conditions. We first compare the shape of these leaves, arising during vegetative development, with >11,000 previously published leaflets from a field setting and >11,000 leaflets from wild tomato relatives. We then quantify the changes in shape, across ontogeny, for successive leaves in the heteroblastic series. Using principal component analysis, we then separate genetic effects modulating (1) the overall shape of all leaves versus (2) the shape of specific leaves in the series, finding the former more heritable than the latter and comparing quantitative trait loci regulating each. Our results demonstrate that phenotype is highly contextual and that unbiased assessments of phenotype, for quantitative genetic or other purposes, would ideally sample the many developmental and environmental factors that modulate it.
The mapping and functional analysis of quantitative traits in Brassica rapa can be greatly improved with the availability of physically positioned, gene-based genetic markers and accurate genome annotation. In this study, deep transcriptome RNA sequencing (RNA-Seq) of Brassica rapa was undertaken with two objectives: SNP detection and improved transcriptome annotation. We performed SNP detection on two varieties that are parents of a mapping population to aid in development of a marker system for this population and subsequent development of high-resolution genetic map. An improved Brassica rapa transcriptome was constructed to detect novel transcripts and to improve the current genome annotation. This is useful for accurate mRNA abundance and detection of expression QTL (eQTLs) in mapping populations. Deep RNA-Seq of two Brassica rapa genotypes-R500 (var. trilocularis, Yellow Sarson) and IMB211 (a rapid cycling variety)-using eight different tissues (root, internode, leaf, petiole, apical meristem, floral meristem, silique, and seedling) grown across three different environments (growth chamber, greenhouse and field) and under two different treatments (simulated sun and simulated shade) generated 2.3 billion high-quality Illumina reads. A total of 330,995 SNPs were identified in transcribed regions between the two genotypes with an average frequency of one SNP in every 200 bases. The deep RNA-Seq reassembled Brassica rapa transcriptome identified 44,239 protein-coding genes. Compared with current gene models of B. rapa, we detected 3537 novel transcripts, 23,754 gene models had structural modifications, and 3655 annotated proteins changed. Gaps in the current genome assembly of B. rapa are highlighted by our identification of 780 unmapped transcripts. All the SNPs, annotations, and predicted transcripts can be viewed at http://phytonetworks.ucdavis.edu/.
Despite a long-standing interest in the genetic basis of morphological diversity, the molecular mechanisms that give rise to developmental variation are incompletely understood. Here, we use comparative transcriptomics coupled with the construction of gene coexpression networks to predict a gene regulatory network (GRN) for leaf development in tomato and two related wild species with strikingly different leaf morphologies. The core network in the leaf developmental GRN contains regulators of leaf morphology that function in global cell proliferation with peripheral gene network modules (GNMs). The BLADE-ON-PETIOLE (BOP) transcription factor in one GNM controls the core network by altering effective concentration of the KNOTTED-like HOMEOBOX gene product. Comparative network analysis and experimental perturbations of BOP levels suggest that variation in BOP expression could explain the diversity in leaf complexity among these species through dynamic rewiring of interactions in the GRN. The peripheral location of the BOP-containing GNM in the leaf developmental GRN and the phenotypic mimics of evolutionary diversity caused by alteration in BOP levels identify a key role for this GNM in canalizing the leaf morphospace by modifying the maturation schedule of leaves to create morphological diversity.
Female control of nonrandom mating has never been genetically established, despite being linked to inbreeding depression and sexual selection. In order to map the loci that control female-mediated nonrandom mating, we constructed a new advanced intercross recombinant inbred line (RIL) population derived from a cross between Arabidopsis (Arabidopsis thaliana) accessions Vancouver (Van-0) and Columbia (Col-0) and mapped quantitative trait loci (QTLs) responsible for nonrandom mating and seed yield traits. We genotyped a population of 490 RILs. A subset of these lines was used to construct an expanded map of 1,061.4 centimorgans with an average interval of 6.7±5.3 centimorgans between markers. QTLs were then mapped for female- and male-mediated nonrandom mating and seed yield traits. To map the genetic loci responsible for female-mediated nonrandom mating and seed yield, we performed mixed pollinations with genetically marked Col-0 pollen and Van-0 pollen on RIL pistils. To map the loci responsible for male-mediated nonrandom mating and seed yield, we performed mixed pollinations with genetically marked Col-0 and RIL pollen on Van-0 pistils. Composite interval mapping of these data identified four QTLs that control female-mediated nonrandom mating and five QTLs that control female-mediated seed yield. We also identified four QTLs that control male-mediated nonrandom mating and three QTLs that control male-mediated seed yield. Epistasis analysis indicates that several of these loci interact. To our knowledge, the results of these experiments represent the first time female-mediated nonrandom mating has been genetically defined.
Terroir, the unique interaction between genotype, environment, and culture, is highly refined in domesticated grape (Vitis vinifera). Toward cultivating terroir, the science of ampelography tried to distinguish thousands of grape cultivars without the aid of genetics. This led to sophisticated phenotypic analyses of natural variation in grape leaves, which within a palmate-lobed framework exhibit diverse patterns of blade outgrowth, hirsuteness, and venation patterning. Here, we provide a morphometric analysis of more than 1,200 grape accessions. Elliptical Fourier descriptors provide a global analysis of leaf outlines and lobe positioning, while a Procrustes analysis quantitatively describes venation patterning. Correlation with previous ampelography suggests an important genetic component, which we confirm with estimates of heritability. We further use RNA-Seq of mutant varieties and perform a genome-wide association study to explore the genetic basis of leaf shape. Meta-analysis reveals a relationship between leaf morphology and hirsuteness, traits known to correlate with climate in the fossil record and extant species. Together, our data demonstrate a genetic basis for the intricate diversity present in grape leaves. We discuss the possibility of using grape leaves as a breeding target to preserve terroir in the face of anticipated climate change, a major problem facing viticulture.
Although applied over extremely short timescales, artificial selection has dramatically altered the form, physiology, and life history of cultivated plants. We have used RNAseq to define both gene sequence and expression divergence between cultivated tomato and five related wild species. Based on sequence differences, we detect footprints of positive selection in over 50 genes. We also document thousands of shifts in gene-expression level, many of which resulted from changes in selection pressure. These rapidly evolving genes are commonly associated with environmental response and stress tolerance. The importance of environmental inputs during evolution of gene expression is further highlighted by large-scale alteration of the light response coexpression network between wild and cultivated accessions. Human manipulation of the genome has heavily impacted the tomato transcriptome through directed admixture and by indirectly favoring nonsynonymous over synonymous substitutions. Taken together, our results shed light on the pervasive effects artificial and natural selection have had on the transcriptomes of tomato and its wild relatives.
Introgression lines (ILs), in which genetic material from wild tomato species is introgressed into a domesticated background, have been used extensively in tomato (Solanum lycopersicum) improvement. Here, we genotype an IL population derived from the wild desert tomato Solanum pennellii at ultrahigh density, providing the exact gene content harbored by each line. To take advantage of this information, we determine IL phenotypes for a suite of vegetative traits, ranging from leaf complexity, shape, and size to cellular traits, such as stomatal density and epidermal cell phenotypes. Elliptical Fourier descriptors on leaflet outlines provide a global analysis of highly heritable, intricate aspects of leaf morphology. We also demonstrate constraints between leaflet size and leaf complexity, pavement cell size, and stomatal density and show independent segregation of traits previously assumed to be genetically coregulated. Meta-analysis of previously measured traits in the ILs shows an unexpected relationship between leaf morphology and fruit sugar levels, which RNA-Seq data suggest may be attributable to genetically coregulated changes in fruit morphology or the impact of leaf shape on photosynthesis. Together, our results both improve upon the utility of an important genetic resource and attest to a complex, genetic basis for differences in leaf morphology between natural populations.
Developmental differences between species commonly result from changes in the tissue-specific expression of genes. Clustering algorithms are a powerful means to detect coexpression across tissues in single species but are not often applied to multidimensional data sets, such as gene expression across tissues in multiple species. As next-generation sequencing approaches enable interspecific analyses, methods to visualize and explore such data sets will be required. Here, we analyze a data set comprising gene expression profiles across six different tissue types in domesticated tomato (Solanum lycopersicum) and a wild relative (Solanum pennellii). We find that self-organizing maps are a useful means to analyze interspecies data, as orthologs can be assigned to independent levels of a "super self-organizing map." We compare various clustering approaches using a principal component analysis in which the expression of orthologous pairs is indicated by two points. We leverage the expression profile differences between orthologs to look at tissue-specific changes in gene expression between species. Clustering based on expression differences between species (rather than absolute expression profiles) yields groups of genes with large tissue-by-species interactions. The changes in expression profiles of genes we observe reflect differences in developmental architecture, such as changes in meristematic activity between S. lycopersicum and S. pennellii. Together, our results offer a suite of data-exploration methods that will be important to visualize and make biological sense of next-generation sequencing experiments designed explicitly to discover tissue-by-species interactions in gene expression data.
While the Arabidopsis (Arabidopsis thaliana) root has been elegantly characterized with respect to specification of cell identity, its development is missing a number of cellular features present in other species. We have characterized the root development of a wild and a domesticated tomato species, Solanum pennellii and Solanum lycopersicum 'M82.' We found extensive differences between these species for root morphology and cellular development including root length, a novel gravity set point angle, differences in cortical cell layer patterning, stem cell niche structure, and radial cell division. Using an introgression line population between these two species, we identified numerous loci that regulate these distinct aspects of development. Specifically we comprehensively identified loci that regulate (1) root length by distinct mechanisms including regulation of cell production within the meristem and the balance between cell division and expansion, (2) the gravity set point angle, and (3) radial cell division or expansion either in specific cell types or generally across multiple cell types. Our findings provide a novel perspective on the regulation of root growth and development between species. These loci have exciting implications with respect to regulation of drought resistance or salinity tolerance and regulation of root development in a family that has undergone domestication.
The RXopJ4 resistance locus from the wild accession Solanum pennellii (Sp) LA716 confers resistance to bacterial spot disease of tomato (S. lycopersicum, Sl) caused by Xanthomonas perforans (Xp). RXopJ4 resistance depends on recognition of the pathogen type III effector protein XopJ4. We used a collection of Sp introgression lines (ILs) to narrow the RXopJ4 locus to a 4.2-Mb segment on the long arm of chromosome 6, encompassed by the ILs 6-2 and 6-2-2. We then adapted or developed a collection of 14 molecular markers to map on a segregating F(2) population from a cross between the susceptible parent Sl FL8000 and the resistant parent RXopJ4 8000 OC(7). In the F(2) population, a 190-kb segment between the markers J350 and J352 cosegregated with resistance. This fine mapping will enable both the identification of candidate genes and the detection of resistant plants using cosegregating markers. The RXopJ4 resistance gene(s), in combination with other recently characterized genes and a quantitative trait locus (QTL) for bacterial spot disease resistance, will likely be an effective tool for the development of durable resistance in cultivated tomato.
High throughput phenotyping (phenomics) is a powerful tool for linking genes to their functions (see review and recent examples). Leaves are the primary photosynthetic organ, and their size and shape vary developmentally and environmentally within a plant. For these reasons studies on leaf morphology require measurement of multiple parameters from numerous leaves, which is best done by semi-automated phenomics tools. Canopy shade is an important environmental cue that affects plant architecture and life history; the suite of responses is collectively called the shade avoidance syndrome (SAS). Among SAS responses, shade induced leaf petiole elongation and changes in blade area are particularly useful as indices. To date, leaf shape programs (e.g. SHAPE, LAMINA, LeafAnalyzer, LEAFPROCESSOR) can measure leaf outlines and categorize leaf shapes, but can not output petiole length. Lack of large-scale measurement systems of leaf petioles has inhibited phenomics approaches to SAS research. In this paper, we describe a newly developed ImageJ plugin, called LeafJ, which can rapidly measure petiole length and leaf blade parameters of the model plant Arabidopsis thaliana. For the occasional leaf that required manual correction of the petiole/leaf blade boundary we used a touch-screen tablet. Further, leaf cell shape and leaf cell numbers are important determinants of leaf size. Separate from LeafJ we also present a protocol for using a touch-screen tablet for measuring cell shape, area, and size. Our leaf trait measurement system is not limited to shade-avoidance research and will accelerate leaf phenotyping of many mutants and screening plants by leaf phenotyping.
Quantitative trait loci (QTL) mapping is a powerful tool for investigating the genetic basis of natural variation. QTL can be mapped using a number of different population designs, but recombinant inbred lines (RILs) are among the most effective. Unfortunately, homozygous RIL populations are time consuming to construct, typically requiring at least six generations of selfing starting from a heterozygous F(1). Haploid plants produced from an F(1) combine the two parental genomes and have only one allele at every locus. Converting these sterile haploids into fertile diploids (termed "doubled haploids," DHs) produces immortal homozygous lines in only two steps. Here we describe a unique technique for rapidly creating recombinant doubled haploid populations in Arabidopsis thaliana: centromere-mediated genome elimination. We generated a population of 238 doubled haploid lines that combine two parental genomes and genotyped them by reduced representation Illumina sequencing. The recombination rate and parental allele frequencies in our population are similar to those found in existing RIL sets. We phenotyped this population for traits related to flowering time and for petiole length and successfully mapped QTL controlling each trait. Our work demonstrates that doubled haploid populations offer a rapid, easy alternative to RILs for Arabidopsis genetic analysis.
Leaves between species vary in their size, serration, complexity, and shape. However, phylogeny is not the only predictor of leaf morphology. The shape of a leaf is the result of intricate developmental processes, including heteroblastic progression (changes in leaf size and shape at different nodes) and the developmental stage of an organ. The leaflets that arise from complex leaves are additionally modified by their positioning along the proximal-distal axis of a leaf and whether they fall on the left or right side of leaves. Even further, leaves are environmentally responsive, and their final shape is influenced by environmental inputs. Here, we comprehensively describe differences in leaflet shape between wild tomato (Solanum section Lycopersicon) species using a principal component analysis on elliptical Fourier descriptors arising from >11,000 sampled leaflets. We leverage differences in developmental rate to approximate a developmental series, which allows us to resolve the confounding differences in intrinsic leaflet form and developmental stage along positions of the heteroblastic leaf series and proximal-distal axis of leaves. We find that the resulting developmental trajectory of organs at different positions along these axes are useful for describing the changes in leaflet shape that occur during the shade avoidance response in tomato. We argue that it is the developmental trajectory, the changes in shape that occur over developmental time in organs reiterated at multiple positions, that is the relevant phenotype for discerning differences between populations and species, and to understand the underlying developmental processes that change during evolution.
The laminae of leaves optimize photosynthetic rates by serving as a platform for both light capture and gas exchange, while minimizing water losses associated with thermoregulation and transpiration. Many have speculated that plants maximize photosynthetic output and minimize associated costs through leaf size, complexity, and shape, but a unifying theory linking the plethora of observed leaf forms with the environment remains elusive. Additionally, the leaf itself is a plastic structure, responsive to its surroundings, further complicating the relationship. Despite extensive knowledge of the genetic mechanisms underlying angiosperm leaf development, little is known about how phenotypic plasticity and selective pressures converge to create the diversity of leaf shapes and sizes across lineages. Here, we use wild tomato accessions, collected from locales with diverse levels of foliar shade, temperature, and precipitation, as a model to assay the extent of shade avoidance in leaf traits and the degree to which these leaf traits correlate with environmental factors. We find that leaf size is correlated with measures of foliar shade across the wild tomato species sampled and that leaf size and serration correlate in a species-dependent fashion with temperature and precipitation. We use far-red induced changes in leaf length as a proxy measure of the shade avoidance response, and find that shade avoidance in leaves negatively correlates with the level of foliar shade recorded at the point of origin of an accession. The direction and magnitude of these correlations varies across the leaf series, suggesting that heterochronic and/or ontogenic programs are a mechanism by which selective pressures can alter leaf size and form. This study highlights the value of wild tomato accessions for studies of both morphological and light-regulated development of compound leaves, and promises to be useful in the future identification of genes regulating potentially adaptive plastic leaf traits.
Shade avoidance is an ecologically and molecularly well-understood set of plant developmental responses that occur when the ratio of red to far-red light (R:FR) is reduced as a result of foliar shade. Here, a genome-wide association study (GWAS) in Arabidopsis thaliana was used to identify variants underlying one of these responses: increased hypocotyl elongation. Four hypocotyl phenotypes were included in the study, including height in high R:FR conditions (simulated sun), height in low R:FR conditions (simulated shade), and two different indices of the response of height to low R:FR. GWAS results showed that variation in these traits is controlled by many loci of small to moderate effect. A known PHYC variant contributing to hypocotyl height variation was identified and lists of significantly associated genes were enriched in a priori candidates, suggesting that this GWAS was capable of generating meaningful results. Using metadata such as expression data, GO terms, and other annotation, we were also able to identify variants in candidate de novo genes. Patterns of significance among our four phenotypes allowed us to categorize associations into three groups: those that affected hypocotyl height without influencing shade avoidance, those that affected shade avoidance in a height-dependent fashion, and those that exerted specific control over shade avoidance. This grouping allowed for the development of explicit hypotheses about the genetics underlying shade avoidance variation. Additionally, the response to shade did not exhibit any marked geographic distribution, suggesting that variation in low R:FR-induced hypocotyl elongation may represent a response to local conditions.
With the introduction of cost effective, rapid, and superior quality next generation sequencing techniques, gene expression analysis has become viable for labs conducting small projects as well as large-scale gene expression analysis experiments. However, the available protocols for construction of RNA-sequencing (RNA-Seq) libraries are expensive and/or difficult to scale for high-throughput applications. Also, most protocols require isolated total RNA as a starting point. We provide a cost-effective RNA-Seq library synthesis protocol that is fast, starts with tissue, and is high-throughput from tissue to synthesized library. We have also designed and report a set of 96 unique barcodes for library adapters that are amenable to high-throughput sequencing by a large combination of multiplexing strategies. Our developed protocol has more power to detect differentially expressed genes when compared to the standard Illumina protocol, probably owing to less technical variation amongst replicates. We also address the problem of gene-length biases affecting differential gene expression calls and demonstrate that such biases can be efficiently minimized during mRNA isolation for library preparation.
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.
A B-box zinc finger protein, B-BOX32 (BBX32), was identified as playing a role in determining hypocotyl length during a large-scale functional genomics study in Arabidopsis (Arabidopsis thaliana). Further analysis revealed that seedlings overexpressing BBX32 display elongated hypocotyls in red, far-red, and blue light, along with reduced cotyledon expansion in red light. Through comparative analysis of mutant and overexpression line phenotypes, including global expression profiling and growth curve studies, we demonstrate that BBX32 acts antagonistically to ELONGATED HYPOCOTYL5 (HY5). We further show that BBX32 interacts with SALT TOLERANCE HOMOLOG2/BBX21, another B-box protein previously shown to interact with HY5. Based on these data, we propose that BBX32 functions downstream of multiple photoreceptors as a modulator of light responses. As such, BBX32 potentially has a native role in mediating gene repression to maintain dark adaptation.
Circadian clocks are endogenous timekeeping mechanisms that allow organisms to anticipate rhythmic, daily environmental changes. Temporal coordination of transcription results in a set of gene expression patterns with peak levels occurring at precise times of the day. An intriguing question is how a single clock can generate different oscillatory rhythms, and it has been proposed that hormone signaling might act in plants as a relay mechanism to modulate the amplitude and the phase of output rhythms. Here we show that the circadian clock gates gibberellin (GA) signaling through transcriptional regulation of the GA receptors, resulting in higher stability of DELLA proteins during daytime and higher GA sensitivity at night. Oscillation of GA signaling appears to be particularly critical for rhythmic growth, given that constitutive expression of the GA receptor expands the daily growth period in seedlings, and complete loss of DELLA function causes continuous, arrhythmic hypocotyl growth. Moreover, transcriptomic analysis of a pentuple della KO mutant indicates that the GA pathway mediates the rhythmic expression of many clock-regulated genes related to biotic and abiotic stress responses and cell wall modification. Thus, gating of GA sensitivity by the circadian clock represents an additional layer of regulation that might provide extra robustness to the diurnal growth rhythm and constitute a regulatory module that coordinates the circadian clock with additional endogenous and environmental signals.
Light regulates multiple aspects of growth and development in plants. Transcriptomic changes govern the expression of signaling molecules with the perception of light. Also, the 26S proteasome regulates the accumulation of positive and negative regulators for optimal growth of Arabidopsis (Arabidopsis thaliana) in the dark, light, or light/dark cycles. BBX22, whose induction is both light regulated and HY5 dependent, is a positive regulator of deetiolation in Arabidopsis. We found that during skotomorphogenesis, the expression of BBX22 needs to be tightly regulated at both transcriptional and posttranslational levels. During photomorphogenesis, the expression of BBX22 transiently accumulates to execute its roles as a positive regulator. BBX22 protein accumulates to a higher level under short-day conditions and functions to inhibit hypocotyl elongation. The proteasome-dependent degradation of BBX22 protein is tightly controlled even in plants overexpressing BBX22. An analysis of BBX22 degradation kinetics shows that the protein has a short half-life under both dark and light conditions. COP1 mediates the degradation of BBX22 in the dark. Although dispensable in the dark, HY5 contributes to the degradation of BBX22 in the light. The constitutive photomorphogenic development of the cop1 mutant is enhanced in cop1BBX22ox plants, which show a short hypocotyl, high anthocyanin accumulation, and expression of light-responsive genes. Exaggerated light responsiveness is also observed in cop1BBX22ox seedlings grown under short-day conditions. Therefore, the proper accumulation of BBX22 is crucial for plants to maintain optimal growth when grown in the dark as well as to respond to seasonal changes in daylength.
Plants exhibit daily rhythms in their growth, providing an ideal system for the study of interactions between environmental stimuli such as light and internal regulators such as the circadian clock. We previously found that two basic loop-helix-loop transcription factors, PHYTOCHROME-INTERACTING FACTOR4 (PIF4) and PIF5, integrate light and circadian clock signaling to generate rhythmic plant growth in Arabidopsis (Arabidopsis thaliana). Here, we use expression profiling and real-time growth assays to identify growth regulatory networks downstream of PIF4 and PIF5. Genome-wide analysis of light-, clock-, or growth-correlated genes showed significant overlap between the transcriptomes of clock-, light-, and growth-related pathways. Overrepresentation analysis of growth-correlated genes predicted that the auxin and gibberellic acid (GA) hormone pathways both contribute to diurnal growth control. Indeed, lesions of GA biosynthesis genes retarded rhythmic growth. Surprisingly, GA-responsive genes are not enriched among genes regulated by PIF4 and PIF5, whereas auxin pathway and response genes are. Consistent with this finding, the auxin response is more severely affected than the GA response in pif4 pif5 double mutants and in PIF5-overexpressing lines. We conclude that at least two downstream modules participate in diurnal rhythmic hypocotyl growth: PIF4 and/or PIF5 modulation of auxin-related pathways and PIF-independent regulation of the GA pathway.
Modern systems biology permits the study of complex networks, such as circadian clocks, and the use of complex methodologies, such as quantitative genetics. However, it is difficult to combine these approaches due to factorial expansion in experiments when networks are examined using complex methods. We developed a genomic quantitative genetic approach to overcome this problem, allowing us to examine the function(s) of the plant circadian clock in different populations derived from natural accessions. Using existing microarray data, we defined 24 circadian time phase groups (i.e., groups of genes with peak phases of expression at particular times of day). These groups were used to examine natural variation in circadian clock function using existing single time point microarray experiments from a recombinant inbred line population. We identified naturally variable loci that altered circadian clock outputs and linked these circadian quantitative trait loci to preexisting metabolomics quantitative trait loci, thereby identifying possible links between clock function and metabolism. Using single-gene isogenic lines, we found that circadian clock output was altered by natural variation in Arabidopsis thaliana secondary metabolism. Specifically, genetic manipulation of a secondary metabolic enzyme led to altered free-running rhythms. This represents a unique and valuable approach to the study of complex networks using quantitative genetics.
Phytochromes are red and far-red light photoreceptors that regulate various aspects of plant development. One of the less-understood roles of phytochromes is the inhibition of hypocotyl negative gravitropism, which refers to the loss of hypocotyl gravitropism and resulting random growth direction in red or far-red light. This light response allows seedlings to curve toward blue light after emergence from the soil and enhances seedling establishment in the presence of mulch. Phytochromes inhibit hypocotyl negative gravitropism by inhibiting four phytochrome-interacting factors (PIF1, PIF3, PIF4, PIF5), as shown by hypocotyl agravitropism of dark-grown pif1 pif3 pif4 pif5 quadruple mutants. We show that phytochromes inhibit negative gravitropism by converting starch-filled gravity-sensing endodermal amyloplasts to other plastids with chloroplastic or etioplastic features in red or far-red light, whereas PIFs promote negative gravitropism by inhibiting the conversion of endodermal amyloplasts to etioplasts in the dark. By analyzing transgenic plants expressing PIF1 with an endodermis-specific SCARECROW promoter, we further show that endodermal PIF1 is sufficient to inhibit the conversion of endodermal amyloplasts to etioplasts and hypocotyl negative gravitropism of the pif quadruple mutant in the dark. Although the functions of phytochromes in gravitropism and chloroplast development are normally considered distinct, our results indicate that these two functions are closely related.
As photoautotrophs, plants can use both the form and amount of fixed carbon as a measure of the light environment. In this study, we used a variety of approaches to elucidate the role of exogenous sucrose in modifying seedling growth dynamics. In addition to its known effects on germination, high-resolution temporal analysis revealed that sucrose could extend the number of days plants exhibited rapid hypocotyl elongation, leading to dramatic increases in ultimate seedling height. In addition, sucrose changed the timing of daily growth maxima, demonstrating that diel growth dynamics are more plastic than previously suspected. Sucrose-dependent growth promotion required function of multiple phytochrome-interacting factors (PIFs), and overexpression of PIF5 led to growth dynamics similar to plants exposed to sucrose. Consistent with this result, sucrose was found to increase levels of PIF5 protein. PIFs have well-established roles as integrators of response to light levels, time of day and phytohormone signaling. Our findings strongly suggest that carbon availability can modify the known photomorphogenetic signaling network.
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.
Association studies utilize the action of recombination over numerous generations to identify loci that underlie quantitative traits. We use a candidate-gene association approach, segregation analyses and analyses of local linkage disequilibrium (LD) to evaluate the potentially causal effects of molecular variation at PIF4 (PHYTOCROME INTERACTING FACTOR 4) on ecologically important traits in Arabidopsis thaliana. A preliminary analysis of sequence diversity in 14 natural genotypes revealed one intermediate-frequency replacement polymorphism at PIF4. A sample of 161 natural accessions was genotyped at PIF4 and screened for average length of early internodes, inflorescence length, days to flowering and flowering interval (days between bolting and flowering) under high- and low-density environments to test for genotype-phenotype associations. PIF4 was associated with early internode lengths, while the PIF4x treatment interaction was associated with flowering interval in the panel of 161 accessions. Further, in a set of recombinant inbred lines that segregate for the PIF4 polymorphism, nucleotide substitutions at PIF4 co-segregated with early internode lengths, days to flowering and fruit set, suggesting that cryptic population structure in the association-mapping panel and attendant LD with a physically distant locus do not account for the observed association. Finally, in a panel of pseudochromosomes from 20 re-sequenced genotypes, LD appeared to decay rapidly in the immediate vicinity of PIF4, suggesting that flanking loci contribute little to the observed association. In sum, the results suggest that PIF4 causally affects early internode lengths on the primary inflorescence, potentially via effects on reproductive timing and that these traits in turn affect fitness.
Genetic correlations are expected to be high among functionally related traits and lower between groups of traits with distinct functions (e.g., reproductive vs. resource-acquisition traits). Here, we explore the quantitative-genetic and QTL architecture of floral organ sizes, vegetative traits, and life history in a set of Brassica rapa recombinant inbred lines within and across field and greenhouse environments. Floral organ lengths were strongly positively correlated within both environments, and analysis of standardized G-matrices indicates that the structure of genetic correlations is ∼80% conserved across environments. Consistent with these correlations, we detected a total of 19 and 21 additive-effect floral QTL in the field and the greenhouse, respectively, and individual QTL typically affected multiple organ types. Interestingly, QTL×QTL epistasis also appeared to contribute to observed genetic correlations; i.e., interactions between two QTL had similar effects on filament length and two estimates of petal size. Although floral and nonfloral traits are hypothesized to be genetically decoupled, correlations between floral organ size and both vegetative and life-history traits were highly significant in the greenhouse; G-matrices of floral and vegetative traits as well as floral and life-history traits differed across environments. Correspondingly, many QTL (45% of those mapped in the greenhouse) showed environmental interactions, including approximately even numbers of floral and nonfloral QTL. Most instances of QTL×QTL epistasis for floral traits were environment dependent.
The control of flowering time in plants is critical for plant fitness and for agriculture. The genetic pathways governing this developmental transition are reasonably well understood in Arabidopsis, although substantial new gains are still being made in this system. Much new work is focusing on how the genetic networks governing flowering function in other species.
Flowering time, a critical adaptive trait, is modulated by several environmental cues. These external signals converge on a small set of genes that in turn mediate the flowering response. Mutant analysis and subsequent molecular studies have revealed that one of these integrator genes, FLOWERING LOCUS T (FT), responds to photoperiod and temperature cues, two environmental parameters that greatly influence flowering time. As the central player in the transition to flowering, the protein coding sequence of FT and its function are highly conserved across species. Using QTL mapping with a new advanced intercross-recombinant inbred line (AI-RIL) population, we show that a QTL tightly linked to FT contributes to natural variation in the flowering response to the combined effects of photoperiod and ambient temperature. Using heterogeneous inbred families (HIF) and introgression lines, we fine map the QTL to a 6.7 kb fragment in the FT promoter. We confirm by quantitative complementation that FT has differential activity in the two parental strains. Further support for FT underlying the QTL comes from a new approach, quantitative knockdown with artificial microRNAs (amiRNAs). Consistent with the causal sequence polymorphism being in the promoter, we find that the QTL affects FT expression. Taken together, these results indicate that allelic variation at pathway integrator genes such as FT can underlie phenotypic variability and that this may be achieved through cis-regulatory changes.
BACKGROUND: Even when phenotypic differences are large between natural or domesticated strains, the underlying genetic basis is often complex, and causal genomic regions need to be identified by quantitative trait locus (QTL) mapping. Unfortunately, QTL positions typically have large confidence intervals, which can, for example, lead to one QTL being masked by another, when two closely linked loci are detected as a single QTL. One strategy to increase the power of precisely localizing small effect QTL, is the use of an intercross approach before inbreeding to produce Advanced Intercross RILs (AI-RILs).
METHODOLOGY/PRINCIPAL FINDINGS: We present two new AI-RIL populations of Arabidopsis thaliana genotyped with an average intermarker distance of 600 kb. The advanced intercrossing design led to expansion of the genetic map in the two populations, which contain recombination events corresponding to 50 kb/cM in an F(2) population. We used the AI-RILs to map QTL for light response and flowering time, and to identify segregation distortion in one of the AI-RIL populations due to a negative epistatic interaction between two genomic regions.
CONCLUSIONS/SIGNIFICANCE: The two new AI-RIL populations, EstC and KendC, derived from crosses of Columbia (Col) to Estland (Est-1) and Kendallville (Kend-L) provide an excellent resource for high precision QTL mapping. Moreover, because they have been genotyped with over 100 common markers, they are also excellent material for comparative QTL mapping.
BACKGROUND: Tomato species are of significant agricultural and ecological interest, with cultivated tomato being among the most common vegetable crops grown. Wild tomato species are native to diverse habitats in South America and show great morphological and ecological diversity that has proven useful in breeding programs. However, relatively little is known about nucleotide diversity between tomato species. Until recently limited sequence information was available for tomato, preventing genome-wide evolutionary analyses. Now, an extensive collection of tomato expressed sequence tags (ESTs) is available at the SOL Genomics Network (SGN). This database holds sequences from several species, annotated with quality values, assembled into unigenes, and tested for homology against other genomes. Despite the importance of polymorphism detection for breeding and natural variation studies, such analyses in tomato have mostly been restricted to cultivated accessions. Importantly, previous polymorphisms surveys mostly ignored the linked meta-information, limiting functional and evolutionary analyses. The current data in SGN is thus an under-exploited resource. Here we describe a cross-species analysis taking full-advantage of available information.
RESULTS: We mined 20,000 interspecific polymorphisms between Solanum lycopersicum and S. habrochaites or S. pennellii and 28,800 intraspecific polymorphisms within S. lycopersicum. Using the available meta-information we classified genes into functional categories and obtained estimations of single nucleotide polymorphisms (SNP) quality, position in the gene, and effect on the encoded proteins, allowing us to perform evolutionary analyses. Finally, we developed a set of more than 10,000 between-species molecular markers optimized by sequence quality and predicted intron position. Experimental validation of 491 of these molecular markers resulted in confirmation of 413 polymorphisms.
CONCLUSION: We present a new analysis of the extensive tomato EST sequences available that represents the most comprehensive survey of sequence diversity across Solanum species to date. These SNPs, plus thousands of molecular makers designed to detect the polymorphisms are available to the community via a website. Evolutionary analyses on these polymorphism uncovered sets of genes potentially important for the evolution and domestication of tomato; interestingly these sets were enriched for genes involved in response to the environment.
Plants have a sophisticated system for sensing and responding to their light environment. The light responses of populations and species native to different habitats show adaptive variation; understanding the mechanisms underlying photomorphogenic variation is therefore of significant interest. In Arabidopsis thaliana, phytochrome B (PHYB) is the dominant photoreceptor for red light and plays a major role in white light. Because PHYB has been proposed as a candidate gene for several quantitative trait loci (QTLs) affecting light response, we have investigated sequence and functional variation in Arabidopsis PHYB. We examined PHYB sequences in 33 A. thaliana individuals and in the close relative Arabidopsis lyrata. From 14 nonsynonymous polymorphisms, we chose 5 for further study based on previous QTL studies. In a larger collection of A. thaliana accessions, one of these five polymorphisms, I143L, was associated with variation in red light response. We used transgenic analysis to test this association and confirmed experimentally that natural PHYB polymorphisms cause differential plant responses to light. Furthermore, our results show that allelic variation of PHYB activity is due to amino acid rather than regulatory changes. Together with earlier studies linking variation in light sensitivity to photoreceptor genes, our work suggests that photoreceptors may be a common target of natural selection.
BACKGROUND: As nonmotile organisms, plants must rapidly adapt to ever-changing environmental conditions, including those caused by daily light/dark cycles. One important mechanism for anticipating and preparing for such predictable changes is the circadian clock. Nearly all organisms have circadian oscillators that, when they are in phase with the Earth's rotation, provide a competitive advantage. In order to understand how circadian clocks benefit plants, it is necessary to identify the pathways and processes that are clock controlled.
RESULTS: We have integrated information from multiple circadian microarray experiments performed on Arabidopsis thaliana in order to better estimate the fraction of the plant transcriptome that is circadian regulated. Analyzing the promoters of clock-controlled genes, we identified circadian clock regulatory elements correlated with phase-specific transcript accumulation. We have also identified several physiological pathways enriched for clock-regulated changes in transcript abundance, suggesting they may be modulated by the circadian clock.
CONCLUSION: Our analysis suggests that transcript abundance of roughly one-third of expressed A. thaliana genes is circadian regulated. We found four promoter elements, enriched in the promoters of genes with four discrete phases, which may contribute to the time-of-day specific changes in the transcript abundance of these genes. Clock-regulated genes are over-represented among all of the classical plant hormone and multiple stress response pathways, suggesting that all of these pathways are influenced by the circadian clock. Further exploration of the links between the clock and these pathways will lead to a better understanding of how the circadian clock affects plant growth and leads to improved fitness.
Most organisms use circadian oscillators to coordinate physiological and developmental processes such as growth with predictable daily environmental changes like sunrise and sunset. The importance of such coordination is highlighted by studies showing that circadian dysfunction causes reduced fitness in bacteria and plants, as well as sleep and psychological disorders in humans. Plant cell growth requires energy and water-factors that oscillate owing to diurnal environmental changes. Indeed, two important factors controlling stem growth are the internal circadian oscillator and external light levels. However, most circadian studies have been performed in constant conditions, precluding mechanistic study of interactions between the clock and diurnal variation in the environment. Studies of stem elongation in diurnal conditions have revealed complex growth patterns, but no mechanism has been described. Here we show that the growth phase of Arabidopsis seedlings in diurnal light conditions is shifted 8-12 h relative to plants in continuous light, and we describe a mechanism underlying this environmental response. We find that the clock regulates transcript levels of two basic helix-loop-helix genes, phytochrome-interacting factor 4 (PIF4) and PIF5, whereas light regulates their protein abundance. These genes function as positive growth regulators; the coincidence of high transcript levels (by the clock) and protein accumulation (in the dark) allows them to promote plant growth at the end of the night. Thus, these two genes integrate clock and light signalling, and their coordinated regulation explains the observed diurnal growth rhythms. This interaction may serve as a paradigm for understanding how endogenous and environmental signals cooperate to control other processes.
In some ecological settings, an individual's fitness depends on both its own phenotype (individual-level selection) as well as the phenotype of the individuals with which it interacts (group-level selection). Using contextual analysis to measure multilevel selection in experimental stands of Arabidopsis thaliana, we detected significant linear selection that reversed across individual versus group levels for two composite phenotypic traits, "size" and "elongation." In both cases, selection at the individual level acted to increase values of these traits, presumably due to their positive effect on resource acquisition. Group selection favored decreased values of the same traits. Nonlinear selection was weak but significant in several cases, including stabilizing selection on developmental rate; individuals with very rapid development likely had lower than average fitness due to their reduced resource level at reproduction, while very delayed reproduction may have resulted in lower fitness if prolonged competition for resources reduced overall environmental quality and fitness of all individuals in a group. Under this scenario, stabilizing selection on individual traits is evidence of selection at the group level. Significant density-dependent selection suggests that a threshold density must be reached before group selection acts. Below this threshold, selection at the individual level affects phenotypic evolution more strongly than group selection. A second experiment measured multilevel selection in progeny stands of the original experimental plants. Multilevel selection again acted antagonistically on a composite trait that included size and elongation as well as on an architectural trait, branch production. The magnitude of individual versus group selection was relatively similar in the progeny generation, and the observed balance of individual versus group selection across densities is generally consistent with the hypotheses that multilevel selection can contribute to phenotypic evolution and to important demographic phenomena, including soft selection and the "law of constant yield."
Loss-of-function, dominant-negative, and change-of-function genetic approaches were used to investigate the role played by the Arabidopsis mitogen-activated protein (MAP) kinase MPK6 throughout development. Plants homozygous for T-DNA null alleles of MPK6 displayed reduced male fertility and abnormal anther development. In addition, a portion of the seed produced by mpk6 plants was found to contain embryos that had burst out of their seed coats. To address potential functional redundancy, a dominant-negative version of MPK6 was constructed by changing the TEY activation loop motif to the amino acid sequence AEF. Plants expressing MPK6AEF via the MPK6 native promoter were found to produce excessive stomata, consistent with the recently described role of MPK6 in stomatal patterning. A novel floral phenotype characterized by abnormal sepal development was also observed in MPK6AEF lines. The gene expression pattern of the MPK6 native promoter was determined using a YFP-MPK6 fusion construct, and expression was observed throughout most plant tissues, consistent with a role for MPK6 in multiple developmental processes. The YFP-MPK6 construct was found to rescue the fertility phenotype of mpk6 null alleles, indicating that the fusion protein retains its biological activity. It was also observed, however, that plants expressing YFP-MPK6 displayed reduced apical dominance and a shortening of inflorescence internodes. These results suggest that the YFP tag modifies the activity of MPK6 in a manner that affects inflorescence development but not anther development. Taken together, the present results indicate that MPK6 is involved in the regulation of multiple aspects of plant development.
Light has an important role in modulating seedling growth and flowering time. We show that allelic variation at the PHYTOCHROME C (PHYC) photoreceptor locus affects both traits in natural populations of A. thaliana. Two functionally distinct PHYC haplotype groups are distributed in a latitudinal cline dependent on FRIGIDA, a locus that together with FLOWERING LOCUS C explains a large portion of the variation in A. thaliana flowering time. In a genome-wide scan for association of 65 loci with latitude, there was an excess of significant P values, indicative of population structure. Nevertheless, PHYC was the most strongly associated locus across 163 strains, suggesting that PHYC alleles are under diversifying selection in A. thaliana. Our work, together with previous findings, suggests that photoreceptor genes are major agents of natural variation in plant flowering and growth response.
Life occurs in an ever-changing environment. Some of the most striking and predictable changes are the daily rhythms of light and temperature. To cope with these rhythmic changes, plants use an endogenous circadian clock to adjust their growth and physiology to anticipate daily environmental changes. Most studies of circadian functions in plants have been performed under continuous conditions. However, in the natural environment, diurnal outputs result from complex interactions of endogenous circadian rhythms and external cues. Accumulated studies using the hypocotyl as a model for plant growth have shown that both light signalling and circadian clock mutants have growth defects, suggesting strong interactions between hypocotyl elongation, light signalling and the circadian clock. Here, we review evidence suggesting that light, plant hormones and the circadian clock all interact to control diurnal patterns of plant growth.
Members of the kinesin superfamily are microtubule-based motor proteins that transport molecules/organelles along microtubules. We have identified similar internal motor kinesins, Kinesin-13A, from the cotton Gossypium hirsutum and Arabidopsis thaliana. Their motor domains share high degree of similarity with those of internal motor kinesins of animals and protists in the MCAK/Kinesin13 subfamily. However, no significant sequence similarities were detected in sequences outside the motor domain. In Arabidopsis plants carrying the T-DNA knockout kinesin-13a-1 and kinesin-13a-2 mutations at the Kinesin-13A locus, >70% leaf trichomes had four branches, whereas wild-type trichomes had three. Immunofluorescent results showed that AtKinesin-13A and GhKinesin-13A localized to entire Golgi stacks. In both wild-type and kinesin-13a mutant cells, the Golgi stacks were frequently associated with microtubules and with actin microfilaments. Aggregation/clustering of Golgi stacks was often observed in the kinesin-13a mutant trichomes and other epidermal cells. This suggested that the distribution of the Golgi apparatus in cell cortex might require microtubules and Kinesin-13A, and the organization of Golgi stacks could play a regulatory role in trichome morphogenesis. Our results also indicate that plant kinesins in the MCAK/Kinesin-13 subfamily have evolved to take on different tasks than their animal counterparts.
Individuals and strains within most species exhibit heritable, and sometimes dramatic, differences in their growth and morphology. Advances in marker genotyping and statistical methods have increased the precision and sensitivity with which the quantitative trait loci (QTL) that are responsible for these differences can be mapped. This has resulted in both a more refined picture of the genetic architecture of many growth traits and the cloning of several of the genes that underlie plant QTL.
The genomics tools available for studying Arabidopsis thaliana are a great resource for researchers trying to characterize and understand the genetic basis of natural variation. Abundant polymorphic markers aid quantitative trait locus (QTL) mapping, the fully sequenced genome provides rapid identification of candidate loci, and extensive knockout collections allow those candidate loci to be tested. Combining QTL mapping of classic phenotypic traits with biochemical or expression analysis is providing mechanistic insight into the traits of interest. Conversely, natural variation studies are now being done on genomic traits such as methylation or chiasma frequency.