Association mapping of local climate-sensitive quantitative trait loci in Arabidopsis thaliana

Bioinformatics Approach in Plant Genomic Research

The advance in genomics technology leads to the dramatic change in plant biology research. Plant biologists now easily access to enormous genomic data to deeply study plant high-density genetic variation at molecular level. Therefore, fully understanding and well manipulating bioinformatics tools to manage and analyze these data are essential in current plant genome research. Many plant genome databases have been established and continued expanding recently. Meanwhile, analytical methods based on bioinformatics are also well developed in many aspects of plant genomic research including comparative genomic analysis, phylogenomics and evolutionary analysis, and genome-wide association study. However, constantly upgrading in computational infrastructures, such as high capacity data storage and high performing analysis software, is the real challenge for plant genome research. This review paper focuses on challenges and opportunities which knowledge and skills in bioinformatics can bring to plant scientists in present plant genomics era as well as future aspects in critical need for effective tools to facilitate the translation of knowledge from new sequencing data to enhancement of plant productivity.

The Arabidopsis thaliana mobilome and its impact at the species level

Transposable elements (TEs) are powerful motors of genome evolution yet a comprehensive assessment of recent transposition activity at the species level is lacking for most organisms. Here, using genome sequencing data for 211 Arabidopsis thaliana accessions taken from across the globe, we identify thousands of recent transposition events involving half of the 326 TE families annotated in this plant species. We further show that the composition and activity of the 'mobilome' vary extensively between accessions in relation to climate and genetic factors. Moreover, TEs insert equally throughout the genome and are rapidly purged by natural selection from gene-rich regions because they frequently affect genes, in multiple ways. Remarkably, loci controlling adaptive responses to the environment are the most frequent transposition targets observed. These findings demonstrate the pervasive, species-wide impact that a rich mobilome can have and the importance of transposition as a recurrent generator of large-effect alleles.

AtWRKY22 promotes susceptibility to aphids and modulates salicylic acid and jasmonic acid signalling

Aphids induce many transcriptional perturbations in their host plants, but the signalling cascades responsible and the effects on plant resistance are largely unknown. Through a genome-wide association (GWA) mapping study in Arabidopsis thaliana, we identified WRKY22 as a candidate gene associated with feeding behaviour of the green peach aphid, Myzus persicae The transcription factor WRKY22 is known to be involved in pathogen-triggered immunity, and WRKY22 gene expression has been shown to be induced by aphids. Assessment of aphid population development and feeding behaviour on knockout mutants and overexpression lines showed that WRKY22 increases susceptibility to M. persicae via a mesophyll-located mechanism. mRNA sequencing analysis of aphid-infested wrky22 knockout plants revealed the up-regulation of genes involved in salicylic acid (SA) signalling and down-regulation of genes involved in plant growth and cell-wall loosening. In addition, mechanostimulation of knockout plants by clip cages up-regulated jasmonic acid (JA)-responsive genes, resulting in substantial negative JA-SA crosstalk. Based on this and previous studies, WRKY22 is considered to modulate the interplay between the SA and JA pathways in response to a wide range of biotic and abiotic stimuli. Its induction by aphids and its role in suppressing SA and JA signalling make WRKY22 a potential target for aphids to manipulate host plant defences.

Natural genetic variation in Arabidopsis for responsiveness to plant growth-promoting rhizobacteria

The plant growth-promoting rhizobacterium (PGPR) Pseudomonas simiae WCS417r stimulates lateral root formation and increases shoot growth in Arabidopsis thaliana (Arabidopsis). These plant growth-stimulating effects are partly caused by volatile organic compounds (VOCs) produced by the bacterium. Here, we performed a genome-wide association (GWA) study on natural genetic variation in Arabidopsis for the ability to profit from rhizobacteria-mediated plant growth-promotion. To this end, 302 Arabidopsis accessions were tested for root architecture characteristics and shoot fresh weight in response to exposure to WCS417r. Although virtually all Arabidopsis accessions tested responded positively to WCS417r, there was a large variation between accessions in the increase in shoot fresh weight, the extra number of lateral roots formed, and the effect on primary root length. Correlation analyses revealed that the bacterially-mediated increase in shoot fresh weight is related to alterations in root architecture. GWA mapping for WCS417r-stimulated changes in root and shoot growth characteristics revealed 10 genetic loci highly associated with the responsiveness of Arabidopsis to the plant growth-promoting activity of WCS417r. Several of the underlying candidate genes have been implicated in important plant growth-related processes. These results demonstrate that plants possess natural genetic variation for the capacity to profit from the plant growth-promoting function of a beneficial rhizobacterium in their rhizosphere. This knowledge is a promising starting point for sustainable breeding strategies for future crops that are better able to maximize profitable functions from their root microbiome.

Fluctuating, warm temperatures decrease the effect of a key floral repressor on flowering time in Arabidopsis thaliana

The genetic basis of growth and development is often studied in constant laboratory environments; however, the environmental conditions that organisms experience in nature are often much more dynamic. We examined how daily temperature fluctuations, average temperature, day length and vernalization influence the flowering time of 59 genotypes of Arabidopsis thaliana with allelic perturbations known to affect flowering time. For a subset of genotypes, we also assessed treatment effects on morphology and growth. We identified 17 genotypes, many of which have high levels of the floral repressor FLOWERING LOCUS C (FLC), that bolted dramatically earlier in fluctuating - as opposed to constant - warm temperatures (mean = 22°C). This acceleration was not caused by transient VERNALIZATION INSENSITIVE 3-mediated vernalization, differential growth rates or exposure to high temperatures, and was not apparent when the average temperature was cool (mean = 12°C). Further, in constant temperatures, contrary to physiological expectations, these genotypes flowered more rapidly in cool than in warm environments. Fluctuating temperatures often reversed these responses, restoring faster bolting in warm conditions. Independently of bolting time, warm fluctuating temperature profiles also caused morphological changes associated with shade avoidance or 'high-temperature' phenotypes. Our results suggest that previous studies have overestimated the effect of the floral repressor FLC on flowering time by using constant temperature laboratory conditions.

Genome-Wide Association Mapping and Genomic Prediction Elucidate the Genetic Architecture of Morphological Traits in Arabidopsis

Quantitative traits in plants are controlled by a large number of genes and their interaction with the environment. To disentangle the genetic architecture of such traits, natural variation within species can be explored by studying genotype-phenotype relationships. Genome-wide association studies that link phenotypes to thousands of single nucleotide polymorphism markers are nowadays common practice for such analyses. In many cases, however, the identified individual loci cannot fully explain the heritability estimates, suggesting missing heritability. We analyzed 349 Arabidopsis accessions and found extensive variation and high heritabilities for different morphological traits. The number of significant genome-wide associations was, however, very low. The application of genomic prediction models that take into account the effects of all individual loci may greatly enhance the elucidation of the genetic architecture of quantitative traits in plants. Here, genomic prediction models revealed different genetic architectures for the morphological traits. Integrating genomic prediction and association mapping enabled the assignment of many plausible candidate genes explaining the observed variation. These genes were analyzed for functional and sequence diversity, and good indications that natural allelic variation in many of these genes contributes to phenotypic variation were obtained. For ACS11, an ethylene biosynthesis gene, haplotype differences explaining variation in the ratio of petiole and leaf length could be identified.

A Comparative Study of Ethylene Emanation upon Nitrogen Deficiency in Natural Accessions of Arabidopsis thaliana

An original approach to develop sustainable agriculture with less nitrogen fertilizer inputs is to tackle the cross-talk between nitrogen nutrition and plant growth regulators. In particular the gaseous hormone, ethylene, is a prime target for that purpose. The variation of ethylene production in natural accessions of the model species Arabidopsis thaliana was explored in response to the nitrate supply. Ethylene was measured with a laser-based photoacoustic detector. First, experimental conditions were established with Columbia-0 (Col-0) accession, which was grown in vitro on horizontal plates across a range of five nitrate concentrations (0.5, 1, 2.5, 5, or 10 mM). The concentrations of 1 and 10 mM nitrate were retained for further characterization. Along with a decrease of total dry biomass and higher biomass allocation to the roots, the ethylene production was 50% more important at 1 mM than at 10 mM nitrate. The total transcript levels of 1-AMINOCYCLOPROPANE-1-CARBOXYLIC ACID SYNTHASES (ACS) in roots and those of ACC OXIDASES (ACO) in shoots increased by 100% between the same treatments. This was mainly due to higher transcript levels of ACS6 and of ACO2 and ACO4 respectively. The assumption was that during nitrogen deficiency, the greater biomass allocation in favor of the roots was controlled by ethylene being released in the shoots after conversion of ACC originating from the roots. Second, biomass and ethylene productions were measured in 20 additional accessions. Across all accessions, the total dry biomass and ethylene production were correlated negatively at 1 mM but positively at 10 mM nitrate. Furthermore, polymorphism was surveyed in ACC and ethylene biosynthesis genes and gene products among accessions. Very few substitutions modifying the amino acids properties in conserved motifs of the enzymes were found in the accessions. Natural variation of ethylene production could be further explored to improve Nitrogen Use Efficiency (NUE), in particular by manipulating features like the biomass production and the timing of senescence upon nitrogen limitation.

A genome-wide association study of a global rice panel reveals resistance in Oryza sativa to root-knot nematodes

The root-knot nematode Meloidogyne graminicola is one of the most serious nematode pests worldwide and represents a major constraint on rice production. While variation in the susceptibility of Asian rice (Oryza sativa) exists, so far no strong and reliable resistance has been reported. Quantitative trait loci for partial resistance have been reported but no underlying genes have been tagged or cloned. Here, 332 accessions of the Rice Diversity Panel 1 were assessed for gall formation, revealing large variation across all subpopulations of rice and higher susceptibility in temperate japonica accessions. Accessions Khao Pahk Maw and LD 24 appeared to be resistant, which was confirmed in large pot experiments where no galls were observed. Detailed observations on these two accessions revealed no nematodes inside the roots 2 days after inoculation and very few females after 17 days (5 in Khao Pahk Maw and <1 in LD 24, in comparison with >100 in the susceptible controls). These two cultivars appear ideal donors for breeding root-knot nematode resistance. A genome-wide association study revealed 11 quantitative trait loci, two of which are close to epistatic loci detected in the Bala x Azucena population. The discussion highlights a small number of candidate genes worth exploring further, in particular many genes with lectin domains and genes on chromosome 11 with homology to the Hordeum Mla locus.

Genome-wide association mapping revealed a diverse genetic basis of seed dormancy across subpopulations in rice (Oryza sativa L.)

BACKGROUND

Seed dormancy is an adaptive trait employed by flowering plants to avoid harsh environmental conditions for the continuity of their next generations. In cereal crops, moderate seed dormancy could help prevent pre-harvest sprouting and improve grain yield and quality. We performed a genome wide association study (GWAS) for dormancy, based on seed germination percentage (GP) in freshly harvested seeds (FHS) and after-ripened seeds (ARS) in 350 worldwide accessions that were characterized with strong population structure of indica, japonica and Aus subpopulations.

RESULTS

The germination tests revealed that Aus and indica rice had stronger seed dormancy than japonica rice in FHS. Association analysis revealed 16 loci significantly associated with GP in FHS and 38 in ARS. Three out of the 38 loci detected in ARS were also detected in FHS and 13 of the ARS loci were detected near previously mapped dormancy QTL. In FHS, three of the association loci were located within 100 kb around previously cloned GA/IAA inactivation genes such as GA2ox3, EUI1 and GH3-2 and one near dormancy gene, Sdr4. In ARS, an association signal was detected near ABA signaling gene ABI5. No association peaks were commonly detected among the sub-populations in FHS and only one association peak was detected in both indica and japonica populations in ARS. Sdr4 and GA2OX3 haplotype analysis showed that Aus and indica II (IndII) varieties had stronger dormancy alleles whereas indica I (IndI) and japonica had weak or non-dormancy alleles.

CONCLUSION

The association study and haplotype analysis together, indicate an involvement of independent genes and alleles contributing towards regulation and natural variation of seed dormancy among the rice sub-populations.

Improved batch correction in untargeted MS-based metabolomics

INTRODUCTION

Batch effects in large untargeted metabolomics experiments are almost unavoidable, especially when sensitive detection techniques like mass spectrometry (MS) are employed. In order to obtain peak intensities that are comparable across all batches, corrections need to be performed. Since non-detects, i.e., signals with an intensity too low to be detected with certainty, are common in metabolomics studies, the batch correction methods need to take these into account.

OBJECTIVES

This paper aims to compare several batch correction methods, and investigates the effect of different strategies for handling non-detects.

METHODS

Batch correction methods usually consist of regression models, possibly also accounting for trends within batches. To fit these models quality control samples (QCs), injected at regular intervals, can be used. Also study samples can be used, provided that the injection order is properly randomized. Normalization methods, not using information on batch labels or injection order, can correct for batch effects as well. Introducing two easy-to-use quality criteria, we assess the merits of these batch correction strategies using three large LC-MS and GC-MS data sets of samples from Arabidopsis thaliana.

RESULTS

The three data sets have very different characteristics, leading to clearly distinct behaviour of the batch correction strategies studied. Explicit inclusion of information on batch and injection order in general leads to very good corrections; when enough QCs are available, also general normalization approaches perform well. Several approaches are shown to be able to handle non-detects-replacing them with very small numbers such as zero seems the worst of the approaches considered.

CONCLUSION

The use of quality control samples for batch correction leads to good results when enough QCs are available. If an experiment is properly set up, batch correction using the study samples usually leads to a similar high-quality correction, but has the advantage that more metabolites are corrected. The strategy for handling non-detects is important: choosing small values like zero can lead to suboptimal batch corrections.

Genome Wide Association Mapping for the Tolerance to the Polyamine Oxidase Inhibitor Guazatine in Arabidopsis thaliana

Guazatine is a potent inhibitor of polyamine oxidase (PAO) activity. In agriculture, guazatine is used as non-systemic contact fungicide efficient in the protection of cereals and citrus fruits against disease. The composition of guazatine is complex, mainly constituted by a mixture of synthetic guanidated polyamines (polyaminoguanidines). Here, we have studied the effects from exposure to guazatine in the weed Arabidopsis thaliana. We report that micromolar concentrations of guazatine are sufficient to inhibit growth of Arabidopsis seedlings and induce chlorosis, whereas germination is barely affected. We observed the occurrence of quantitative variation in the response to guazatine between 107 randomly chosen Arabidopsis accessions. This enabled us to undertake genome-wide association (GWA) mapping that identified a locus on chromosome one associated with guazatine tolerance. CHLOROPHYLLASE 1 (CLH1) within this locus was studied as candidate gene, together with its paralog (CLH2). The analysis of independent clh1-2, clh1-3, clh2-3, clh2-2, and double clh1-2 clh2-3 mutant alleles indicated that CLH1 and/or CLH2 loss-of-function or expression down-regulation promote guazatine tolerance in Arabidopsis. We report a natural mechanism by which Arabidopsis populations can overcome toxicity by the fungicide guazatine.

Divergence of the diapause transcriptome in apple maggot flies: winter regulation and post-winter transcriptional repression

Duration of dormancy regulates seasonal timing in many organisms and may be modulated by day length and temperature. Though photoperiodic modulation has been well studied, temperature modulation of dormancy has received less attention. Here, we leverage genetic variation in diapause in the apple maggot fly, Rhagoletis pomonella, to test whether gene expression during winter or following spring warming regulates diapause duration. We used RNAseq to compare transcript abundance during and after simulated winter between an apple-infesting population and a hawthorn-infesting population where the apple population ends pupal diapause earlier than the hawthorn-infesting population. Marked differences in transcription between the two populations during winter suggests that the ‘early’ apple population is developmentally advanced compared to the ‘late’ hawthorn population prior to spring warming, with transcripts participating in growth and developmental processes relatively up-regulated in apple pupae during the winter cold period. Thus, regulatory differences during winter ultimately drive phenological differences that manifest themselves in the following summer. Expression and polymorphism analysis identify candidate genes in the Wnt and insulin signaling pathways that contribute to population differences in seasonality. Both populations remained in diapause and displayed a pattern of up- and then down-regulation (or vice versa) of growth-related transcripts following warming, consistent with transcriptional repression. The ability to repress growth stimulated by permissive temperatures is likely critical to avoid mismatched phenology and excessive metabolic demand. Compared to diapause studies in other insects, our results suggest some overlap in candidate genes/pathways, though the timing and direction of changes in transcription are likely species-specific.

Genome-wide association mapping of time-dependent growth responses to moderate drought stress in Arabidopsis

Large areas of arable land are often confronted with irregular rainfall resulting in limited water availability for part(s) of the growing seasons, which demands research for drought tolerance of plants. Natural variation was observed for biomass accumulation upon controlled moderate drought stress in 324 natural accessions of Arabidopsis. Improved performance under drought stress was correlated with early flowering and lack of vernalization requirement, indicating overlap in the regulatory networks of flowering time and drought response or correlated responses of these traits to natural selection. In addition, plant size was negatively correlated with relative water content (RWC) independent of the absolute water content (WC), indicating a prominent role for soluble compounds. Growth in control and drought conditions was determined over time and was modelled by an exponential function. Genome-wide association (GWA) mapping of temporal plant size data and of model parameters resulted in the detection of six time-dependent quantitative trait loci (QTLs) strongly associated with drought. Most QTLs would not have been identified if plant size was determined at a single time point. Analysis of earlier reported gene expression changes upon drought enabled us to identify for each QTL the most likely candidates.

Natural Genetic Variation of Seed Micronutrients of Arabidopsis thaliana Grown in Zinc-Deficient and Zinc-Amended Soil

The quality of edible seeds for human and animal nutrition is crucially dependent on high zinc (Zn) and iron (Fe) seed concentrations. The micronutrient bioavailability is strongly reduced by seed phytate that forms complexes with seed cations. Superior genotypes with increased seed Zn concentrations had been identified, but low micronutrient seed levels often prevail when the plants are grown in Zn-deficient soils, which are globally widespread and correlate with human Zn-deficiency. Here, seed Zn concentrations of Arabidopsis accessions grown in Zn-deficient and Zn-amended conditions were measured together with seed Fe and manganese (Mn), in a panel of 108 accessions. By applying genome-wide association, de novo candidate genes potentially involved in the seed micronutrient accumulation were identified. However, a candidate inositol 1,3,4-trisphosphate 5/6-kinase 3 gene (ITPK3), located close to a significant nucleotide polymorphism associated with relative Zn seed concentrations, was dispensable for seed micronutrients accumulation in Col-0. Loss of this gene in itpk3-1 did neither affect phytate seed levels, nor seed Zn, Fe, and Mn. It is concluded that large natural variance of micronutrient seed levels is identified in the population and several accessions maintain high seed Zn despite growth in Zn-deficient conditions.

Novel Genes Affecting the Interaction between the Cabbage Whitefly and Arabidopsis Uncovered by Genome-Wide Association Mapping

Plants have evolved a variety of ways to defend themselves against biotic attackers. This has resulted in the presence of substantial variation in defense mechanisms among plants, even within a species. Genome-wide association (GWA) mapping is a useful tool to study the genetic architecture of traits, but has so far only had limited exploitation in studies of plant defense. Here, we study the genetic architecture of defense against the phloem-feeding insect cabbage whitefly (Aleyrodes proletella) in Arabidopsis thaliana. We determined whitefly performance, i.e. the survival and reproduction of whitefly females, on 360 worldwide selected natural accessions and subsequently performed GWA mapping using 214,051 SNPs. Substantial variation for whitefly adult survival and oviposition rate (number of eggs laid per female per day) was observed between the accessions. We identified 39 candidate SNPs for either whitefly adult survival or oviposition rate, all with relatively small effects, underpinning the complex architecture of defense traits. Among the corresponding candidate genes, i.e. genes in linkage disequilibrium (LD) with candidate SNPs, none have previously been identified as a gene playing a role in the interaction between plants and phloem-feeding insects. Whitefly performance on knock-out mutants of a number of candidate genes was significantly affected, validating the potential of GWA mapping for novel gene discovery in plant-insect interactions. Our results show that GWA analysis is a very useful tool to gain insight into the genetic architecture of plant defense against herbivorous insects, i.e. we identified and validated several genes affecting whitefly performance that have not previously been related to plant defense against herbivorous insects.

GWA Mapping of Anthocyanin Accumulation Reveals Balancing Selection of MYB90 in Arabidopsis thaliana

Induction of anthocyanin accumulation by osmotic stress was assessed in 360 accessions of Arabidopsis thaliana. A wide range of natural variation, with phenotypes ranging from green to completely red/purple rosettes, was observed. A genome wide association (GWA) mapping approach revealed that sequence diversity in a small 15 kb region on chromosome 1 explained 40% of the variation observed. Sequence and expression analyses of alleles of the candidate gene MYB90 identified a causal polymorphism at amino acid (AA) position 210 of this transcription factor of the anthocyanin biosynthesis pathway. This amino acid discriminates the two most frequent alleles of MYB90. Both alleles are present in a substantial part of the population, suggesting balancing selection between these two alleles. Analysis of the geographical origin of the studied accessions suggests that the macro climate is not the driving force behind positive or negative selection for anthocyanin accumulation. An important role for local climatic conditions is, therefore, suggested. This study emphasizes that GWA mapping is a powerful approach to identify alleles that are under balancing selection pressure in nature.

Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits

Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation.

Finding genes involved in adaptation to the environment has long been of interest to evolutionary biologists and ecologists. Most commonly, researchers look for loci whose differences in allelic state correlate with differences in a particular trait or environmental variable such as temperature. The implicit assumption behind such methods is that natural selection by the environment will shape variation in adaptive traits through associated changes in allele frequencies. This means that both environmental and phenotypic variation are relevant for detecting adaptive genes, although we have incomplete knowledge of how the two types of variation relate to adaptation. Here we present a method that aims to identify adaptive genes by combining phenotypic and environmental data. We first predict trait variation from a set of environmental variables as a way to extract the most biologically relevant information from the environment and then look for genes associated with both the predicted and observed trait. Using simulations and published data from the model plant Arabidopsis thaliana, we show that this approach may find adaptive genes more effectively compared to existing methods. We also demonstrate that predicted traits can be used to identify relevant loci in individuals for which no phenotypic data is available.

Modulation of Ambient Temperature-Dependent Flowering in Arabidopsis thaliana by Natural Variation of FLOWERING LOCUS M

Plants integrate seasonal cues such as temperature and day length to optimally adjust their flowering time to the environment. Compared to the control of flowering before and after winter by the vernalization and day length pathways, mechanisms that delay or promote flowering during a transient cool or warm period, especially during spring, are less well understood. Due to global warming, understanding this ambient temperature pathway has gained increasing importance. In Arabidopsis thaliana, FLOWERING LOCUS M (FLM) is a critical flowering regulator of the ambient temperature pathway. FLM is alternatively spliced in a temperature-dependent manner and the two predominant splice variants, FLM-ß and FLM-δ, can repress and activate flowering in the genetic background of the A. thaliana reference accession Columbia-0. The relevance of this regulatory mechanism for the environmental adaptation across the entire range of the species is, however, unknown. Here, we identify insertion polymorphisms in the first intron of FLM as causative for accelerated flowering in many natural A. thaliana accessions, especially in cool (15°C) temperatures. We present evidence for a potential adaptive role of this structural variation and link it specifically to changes in the abundance of FLM-ß. Our results may allow predicting flowering in response to ambient temperatures in the Brassicaceae.

Which plant trait explains the variations in relative growth rate and its response to elevated carbon dioxide concentration among Arabidopsis thaliana ecotypes derived from a variety of habitats?

Elevated atmospheric carbon dioxide (CO2) concentration ([CO2]) enhances plant growth, but this enhancement varies considerably. It is still uncertain which plant traits are quantitatively related to the variation in plant growth. To identify the traits responsible, we developed a growth analysis model that included primary parameters associated with morphology, nitrogen (N) use, and leaf and root activities. We analysed the vegetative growth of 44 ecotypes of Arabidopsis thaliana L. grown at ambient and elevated [CO2] (800 μmol mol(-1)). The 44 ecotypes were selected such that they were derived from various altitudes and latitudes. Relative growth rate (RGR; growth rate per unit plant mass) and its response to [CO2] varied by 1.5- and 1.7-fold among ecotypes, respectively. The variation in RGR at both [CO2]s was mainly explained by the variation in leaf N productivity (LNP; growth rate per leaf N),which was strongly related to photosynthetic N use efficiency (PNUE). The variation in the response of RGR to [CO2] was also explained by the variation in the response of LNP to [CO2]. Genomic analyses indicated that there was no phylogenetic constraint on inter-ecotype variation in the CO2 response of RGR or LNP. We conclude that the significant variation in plant growth and its response to [CO2] among ecotypes reflects the variation in N use for photosynthesis among ecotypes, and that the response of PNUE to CO2 is an important target for predicting and/or breeding plants that have high growth rates at elevated [CO2].

Population Genomics for Understanding Adaptation in Wild Plant Species

Darwin's theory of evolution by natural selection is the foundation of modern biology. However, it has proven remarkably difficult to demonstrate at the genetic, genomic, and population level exactly how wild species adapt to their natural environments. We discuss how one can use large sets of multiple genome sequences from wild populations to understand adaptation, with an emphasis on the small herbaceous plant Arabidopsis thaliana. We present motivation for such studies; summarize progress in describing whole-genome, species-wide sequence variation; and then discuss what insights have emerged from these resources, either based on sequence information alone or in combination with phenotypic data. We conclude with thoughts on opportunities with other plant species and the impact of expected progress in sequencing technology and genome engineering for studying adaptation in nature.

"Missing" G x E Variation Controls Flowering Time in Arabidopsis thaliana

Understanding how genetic variation interacts with the environment is essential for understanding adaptation. In particular, the life cycle of plants is tightly coordinated with local environmental signals through complex interactions with the genetic variation (G x E). The mechanistic basis for G x E is almost completely unknown. We collected flowering time data for 173 natural inbred lines of Arabidopsis thaliana from Sweden under two growth temperatures (10°C and 16°C), and observed massive G x E variation. To identify the genetic polymorphisms underlying this variation, we conducted genome-wide scans using both SNPs and local variance components. The SNP-based scan identified several variants that had common effects in both environments, but found no trace of G x E effects, whereas the scan using local variance components found both. Furthermore, the G x E effects appears to be concentrated in a small fraction of the genome (0.5%). Our conclusion is that G x E effects in this study are mostly due to large numbers of allele or haplotypes at a small number of loci, many of which correspond to previously identified flowering time genes.

Diverse regulatory factors associate with flowering time and yield responses in winter-type Brassica napus

BACKGROUND

Flowering time, plant height and seed yield are strongly influenced by climatic and day-length adaptation in crop plants. To investigate these traits under highly diverse field conditions in the important oilseed crop Brassica napus, we performed a genome-wide association study using data from diverse agroecological environments spanning three continents.

METHODS

A total of 158 European winter-type B.napus inbred lines were genotyped with 21,623 unique, single-locus single-nucleotide polymorphism (SNP) markers using the Brassica 60 K-SNP Illumina® Infinium consortium array. Phenotypic associations were calculated in the panel over the years 2010-2012 for flowering time, plant height and seed yield in 5 highly diverse locations in Germany, China and Chile, adding up to 11 diverse environments in total.

RESULTS

We identified 101 genome regions associating with the onset of flowering, 69 with plant height, 36 with seed yield and 68 cross-trait regions with potential adaptive value. Within these regions, B.napus orthologs for a number of candidate adaptation genes were detected, including central circadian clock components like CIRCADIAN CLOCK- ASSOCIATED 1 (Bna.CCA1) and the important flowering-time regulators FLOWERING LOCUS T (Bna.FT) and FRUITFUL (Bna.FUL).

DISCUSSION

Gene ontology (GO) enrichment analysis of candidate regions suggested that selection of genes involved in post-transcriptional and epigenetic regulation of flowering time may play a potential role in adaptation of B. napus to highly divergent environments. The classical flowering time regulators Bna.FLC and Bna.CO were not found among the candidate regions, although both show functional variation. Allelic effects were additive for plant height and yield, but not for flowering time. The scarcity of positive minor alleles for yield in this breeding pool points to a lack of diversity for adaptation that could restrict yield gain in the face of environmental change.

CONCLUSIONS

Our study provides a valuable framework to further improve the adaptability and yield stability of this recent allopolyploid crop under changing environments. The results suggest that flowering time regulation within an adapted B. napus breeding pool is driven by a high number of small modulating processes rather than major transcription factors like Bna.CO. In contrast, yield regulation appears highly parallel, therefore yield could be increased by pyramiding positively associated haplotypes.

Genome-wide association mapping of growth dynamics detects time-specific and general quantitative trait loci

Growth is a complex trait determined by the interplay between many genes, some of which play a role at a specific moment during development whereas others play a more general role. To identify the genetic basis of growth, natural variation in Arabidopsis rosette growth was followed in 324 accessions by a combination of top-view imaging, high-throughput image analysis, modelling of growth dynamics, and end-point fresh weight determination. Genome-wide association (GWA) mapping of the temporal growth data resulted in the detection of time-specific quantitative trait loci (QTLs), whereas mapping of model parameters resulted in another set of QTLs related to the whole growth curve. The positive correlation between projected leaf area (PLA) at different time points during the course of the experiment suggested the existence of general growth factors with a function in multiple developmental stages or with prolonged downstream effects. Many QTLs could not be identified when growth was evaluated only at a single time point. Eleven candidate genes were identified, which were annotated to be involved in the determination of cell number and size, seed germination, embryo development, developmental phase transition, or senescence. For eight of these, a mutant or overexpression phenotype related to growth has been reported, supporting the identification of true positives. In addition, the detection of QTLs without obvious candidate genes implies the annotation of novel functions for underlying genes.

Genomic variation across landscapes: insights and applications

The distribution of genomic variation across landscapes can provide insights into the complex interactions between the environment and the genome that influence the distribution of species, and mediate phenotypic adaptation to local conditions. High throughput sequencing technologies now offer unprecedented power to explore these interactions, allowing powerful inferences about historical processes of colonization, gene flow and divergence, as well as the identification of loci that mediate local adaptation. These 'landscape genomic' approaches have been validated in model species and are now being applied to nonmodel organisms, including foundation species that have substantial effects on ecosystem processes. Here we review the growing field of landscape genomics from a very broad perspective. In particular, we describe the inferential power that is gained by taking a genome-wide view of genetic variation, strategies for study design to best capture adaptive variation, and how to apply this information to practical challenges, such as restoration.

Heterochrony underpins natural variation in Cardamine hirsuta leaf form

A key problem in biology is whether the same processes underlie morphological variation between and within species. Here, by using plant leaves as an example, we show that the causes of diversity at these two evolutionary scales can be divergent. Some species like the model plant Arabidopsis thaliana have simple leaves, whereas others like the A. thaliana relative Cardamine hirsuta bear complex leaves comprising leaflets. Previous work has shown that these interspecific differences result mostly from variation in local tissue growth and patterning. Now, by cloning and characterizing a quantitative trait locus (QTL) for C. hirsuta leaf shape, we find that a different process, age-dependent progression of leaf form, underlies variation in this trait within species. This QTL effect is caused by cis-regulatory variation in the floral repressor ChFLC, such that genotypes with low-expressing ChFLC alleles show both early flowering and accelerated age-dependent changes in leaf form, including faster leaflet production. We provide evidence that this mechanism coordinates leaf development with reproductive timing and may help to optimize resource allocation to the next generation.

Arabidopsis thaliana natural variation reveals connections between UV radiation stress and plant pathogen-like defense responses

UV radiation is a ubiquitous component of solar radiation that affects plant growth and development. Here we studied growth related traits of 345 Arabidopsis thaliana accessions in response to UV radiation stress. We analyzed the genetic basis of this natural variation by genome-wide association studies, which suggested a specific candidate genomic region. RNA-sequencing of three sensitive and three resistant accessions combined with mutant analysis revealed five large effect genes. Mutations in PHE ammonia lyase 1 (PAL1) and putative kinase At1g76360 rendered Arabidopsis hypersensitive to UV stress, while loss of function from putative methyltransferase At4g22530, novel plant snare 12 (NPSN12) and defense gene activated disease resistance 2 (ADR2) conferred higher UV stress resistance. Three sensitive accessions showed strong ADR2 transcriptional activation, accumulation of salicylic acid (SA) and dwarf growth upon UV stress, while these phenotypes were much less affected in resistant plants. The phenotype of sensitive accessions resembles autoimmune reactions due to overexpression of defense related genes, and suggests that natural variation in response to UV radiation stress is driven by pathogen-like responses in Arabidopsis.

Flowering Locus C's Lessons: Conserved Chromatin Switches Underpinning Developmental Timing and Adaptation

Analysis of how seasonal cues influence the timing of the floral transition has revealed many important principles for how epigenetic regulation can integrate a variety of environmental cues with developmental signals. The study of the pathways that necessitate overwintering in plants and their ability to respond to prolonged cold (the vernalization requirement and response pathways) has elaborated different chromatin regulatory pathways and the involvement of noncoding RNAs. The major target of these vernalization pathways in Arabidopsis (Arabidopsis thaliana) is Flowering Locus C (FLC). A relatively simple picture of FLC regulation is emerging of a few core complexes and mechanisms that antagonize each other's actions. This balance provides a fine degree of control that has nevertheless permitted evolution of a wide range of natural variation in vernalization in Arabidopsis. Similar simple routes of adaptation may underlie life history variation between species.

Genome-Wide Association Mapping of Fertility Reduction upon Heat Stress Reveals Developmental Stage-Specific QTLs in Arabidopsis thaliana

For crops that are grown for their fruits or seeds, elevated temperatures that occur during flowering and seed or fruit set have a stronger effect on yield than high temperatures during the vegetative stage. Even short-term exposure to heat can have a large impact on yield. In this study, we used Arabidopsis thaliana to study the effect of short-term heat exposure on flower and seed development. The impact of a single hot day (35°C) was determined in more than 250 natural accessions by measuring the lengths of the siliques along the main inflorescence. Two sensitive developmental stages were identified, one before anthesis, during male and female meiosis, and one after anthesis, during fertilization and early embryo development. In addition, we observed a correlation between flowering time and heat tolerance. Genome-wide association mapping revealed four quantitative trait loci (QTLs) strongly associated with the heat response. These QTLs were developmental stage specific, as different QTLs were detected before and after anthesis. For a number of QTLs, T-DNA insertion knockout lines could validate assigned candidate genes. Our findings show that the regulation of complex traits can be highly dependent on the developmental timing.

Large-scale adaptive differentiation in the alpine perennial herb Arabis alpina

Information about the incidence and magnitude of local adaptation can help to predict the response of natural populations to a changing environment, and should be of particular interest in arctic and alpine environments where the effects of climate change are expected to be severe. To quantify adaptive differentiation in the arctic-alpine perennial herb Arabis alpina, we conducted reciprocal transplant experiments for 3 yr between Spanish and Scandinavian populations. At the sites of one Spanish and one Scandinavian population, we planted seedlings representing two Spanish and four Scandinavian populations, and recorded survival, flowering propensity and fecundity. The experiment was replicated in two subsequent years. The results demonstrate strong adaptive differentiation between A. alpina populations from the two regions. At the field site in Spain, survival and fruit production of Spanish populations were higher than those of Scandinavian populations, while the opposite was true at the site in Scandinavia, and these differences were consistent across years. By comparison, fitness varied little among populations from the same region. The results suggest that the magnitude and geographical scale of local adaptation need to be considered in predictions of the effects of global change on the dynamics of arctic and alpine plant populations.

Loci and candidate gene identification for resistance to Sclerotinia sclerotiorum in soybean (Glycine max L. Merr.) via association and linkage maps

Soybean white mold (SWM), caused by Sclerotinia sclerotiorum ((Lib.) W. Phillips), is currently considered to be the second most important cause of soybean yield loss due to disease. Research is needed to identify SWM-resistant germplasm and gain a better understanding of the genetic and molecular basis of SWM resistance in soybean. Stem pigmentation after treatment with oxaloacetic acid is an effective indicator of resistance to SWM. A total of 128 recombinant inbred lines (RILs) derived from a cross of 'Maple Arrow' (partial resistant to SWM) and 'Hefeng 25' (susceptible) and 330 diverse soybean cultivars were screened for the soluble pigment concentration of their stems, which were treated with oxalic acid. Four quantitative trait loci (QTLs) underlying soluble pigment concentration were detected by linkage mapping of the RILs. Three hundred and thirty soybean cultivars were sequenced using the whole-genome encompassing approach and 25 179 single-nucleotide polymorphisms (SNPs) were detected for the fine mapping of SWM resistance genes by genome-wide association studies. Three out of five SNP markers representing a linkage disequilibrium (LD) block and a single locus on chromosome 13 (Gm13) were significantly associated with the soluble pigment content of stems. Three more SNPs that represented three minor QTLs for the soluble pigment content of stems were identified on another three chromosomes by association mapping. A major locus with the largest effect on Gm13 was found both by linkage and association mapping. Four potential candidate genes involved in disease response or the anthocyanin biosynthesis pathway were identified at the locus near the significant SNPs (<60 kbp). The beneficial allele and candidate genes should be useful in soybean breeding for improving resistance to SWM.

Natural genetic variation for acclimation of photosynthetic light use efficiency to growth irradiance in Arabidopsis

Plants are known to be able to acclimate their photosynthesis to the level of irradiance. Here, we present the analysis of natural genetic variation for photosynthetic light use efficiency (ΦPSII) in response to five light environments among 12 genetically diverse Arabidopsis (Arabidopsis thaliana) accessions. We measured the acclimation of ΦPSII to constant growth irradiances of four different levels (100, 200, 400, and 600 µmol m(-2) s(-1)) by imaging chlorophyll fluorescence after 24 d of growth and compared these results with acclimation of ΦPSII to a step-wise change in irradiance where the growth irradiance was increased from 100 to 600 µmol m(-2) s(-1) after 24 d of growth. Genotypic variation for ΦPSII is shown by calculating heritability for the short-term ΦPSII response to different irradiance levels as well as for the relation of ΦPSII measured at light saturation (a measure of photosynthetic capacity) to growth irradiance level and for the kinetics of the response to a step-wise increase in irradiance from 100 to 600 µmol m(-2) s(-1). A genome-wide association study for ΦPSII measured 1 h after a step-wise increase in irradiance identified several new candidate genes controlling this trait. In conclusion, the different photosynthetic responses to a changing light environment displayed by different Arabidopsis accessions are due to genetic differences, and we have identified candidate genes for the photosynthetic response to an irradiance change. The genetic variation for photosynthetic acclimation to irradiance found in this study will allow future identification and analysis of the causal genes for the regulation of ΦPSII in plants.

Quantitative trait loci and candidate genes underlying genotype by environment interaction in the response of Arabidopsis thaliana to drought

Drought stress was imposed on two sets of Arabidopsis thaliana genotypes grown in sand under short-day conditions and analysed for several shoot and root growth traits. The response to drought was assessed for quantitative trait locus (QTL) mapping in a genetically diverse set of Arabidopsis accessions using genome-wide association (GWA) mapping, and conventional linkage analysis of a recombinant inbred line (RIL) population. Results showed significant genotype by environment interaction (G×E) for all traits in response to different watering regimes. For the RIL population, the observed G×E was reflected in 17 QTL by environment interactions (Q×E), while 17 additional QTLs were mapped not showing Q×E. GWA mapping identified 58 single nucleotide polymorphism (SNPs) associated with loci displaying Q×E and an additional 16 SNPs associated with loci not showing Q×E. Many candidate genes potentially underlying these loci were suggested. The genes for RPS3C and YLS7 were found to contain conserved amino acid differences when comparing Arabidopsis accessions with strongly contrasting drought response phenotypes, further supporting their candidacy. One of these candidate genes co-located with a QTL mapped in the RIL population.

From phenotypes to causal sequences: using genome wide association studies to dissect the sequence basis for variation of plant development

Tremendous natural variation of growth and development exists within species. Uncovering the molecular mechanisms that tune growth and development promises to shed light on a broad set of biological issues including genotype to phenotype relations, regulatory mechanisms of biological processes and evolutionary questions. Recent progress in sequencing and data processing capabilities has enabled Genome Wide Association Studies (GWASs) to identify DNA sequence polymorphisms that underlie the variation of biological traits. In the last years, GWASs have proven powerful in revealing the complex genetic bases of many phenotypes in various plant species. Here we highlight successful recent GWASs that uncovered mechanistic and sequence bases of trait variation related to plant growth and development and discuss important considerations for conducting successful GWASs.

Quantitative Trait Locus Analysis of Seed Germination and Seedling Vigor in Brassica rapa Reveals QTL Hotspots and Epistatic Interactions

The genetic basis of seed germination and seedling vigor is largely unknown in Brassica species. We performed a study to evaluate the genetic basis of these important traits in a B. rapa doubled haploid population from a cross of a yellow-seeded oil-type yellow sarson and a black-seeded vegetable-type pak choi. We identified 26 QTL regions across all 10 linkage groups for traits related to seed weight, seed germination and seedling vigor under non-stress and salt stress conditions illustrating the polygenic nature of these traits. QTLs for multiple traits co-localized and we identified eight hotspots for quantitative trait loci (QTL) of seed weight, seed germination, and root and shoot lengths. A QTL hotspot for seed germination on A02 mapped at the B. rapa Flowering Locus C (BrFLC2). Another hotspot on A05 with salt stress specific QTLs co-located with the B. rapa Fatty acid desaturase 2 (BrFAD2) locus. Epistatic interactions were observed between QTL hotspots for seed germination on A02 and A10 and with a salt tolerance QTL on A05. These results contribute to the understanding of the genetics of seed quality and seeding vigor in B. rapa and can offer tools for Brassica breeding.

Is 'peak N' key to understanding the timing of flowering in annual plants?

Flowering time in annual plants has large fitness consequences and has been the focus of theoretical and empirical study. Previous theory has concluded that flowering time has evolved over evolutionary time to maximize fitness over a particular season length. We introduce a new model where flowering is cued by a growth-rate rule (peak nitrogen (N)). Flowering is therefore sensitive to physiological parameters and to current environmental conditions, including N availability and the presence of competitors. The model predicts that, when overall conditions are suitable for flowering, plants should never flower after 'peak N', the point during development when the whole-plant N uptake rate reaches its maximum. Our model further predicts correlations between flowering time and vegetative growth rates, and that the response to increased N depends heavily on how this extra N is made available. We compare our predictions to observations in the literature. We suggest that annual plants may have evolved to use growth-rate rules as part of the cue for flowering, allowing them to smoothly and optimally adjust their flowering time to a wide range of local conditions. If so, there are widespread implications for the study of the molecular biology behind flowering pathways.

Modeling the influence of genetic and environmental variation on the expression of plant life cycles across landscapes

Organisms develop through multiple life stages that differ in environmental tolerances. The seasonal timing, or phenology, of life-stage transitions determines the environmental conditions to which each life stage is exposed and the length of time required to complete a generation. Both environmental and genetic factors contribute to phenological variation, yet predicting their combined effect on life cycles across a geographic range remains a challenge. We linked submodels of the plasticity of individual life stages to create an integrated model that predicts life-cycle phenology in complex environments. We parameterized the model for Arabidopsis thaliana and simulated life cycles in four locations. We compared multiple "genotypes" by varying two parameters associated with natural genetic variation in phenology: seed dormancy and floral repression. The model predicted variation in life cycles across locations that qualitatively matches observed natural phenology. Seed dormancy had larger effects on life-cycle length than floral repression, and results suggest that a genetic cline in dormancy maintains a life-cycle length of 1 year across the geographic range of this species. By integrating across life stages, this approach demonstrates how genetic variation in one transition can influence subsequent transitions and the geographic distribution of life cycles more generally.

Marker-based estimation of heritability in immortal populations

Heritability is a central parameter in quantitative genetics, from both an evolutionary and a breeding perspective. For plant traits heritability is traditionally estimated by comparing within- and between-genotype variability. This approach estimates broad-sense heritability and does not account for different genetic relatedness. With the availability of high-density markers there is growing interest in marker-based estimates of narrow-sense heritability, using mixed models in which genetic relatedness is estimated from genetic markers. Such estimates have received much attention in human genetics but are rarely reported for plant traits. A major obstacle is that current methodology and software assume a single phenotypic value per genotype, hence requiring genotypic means. An alternative that we propose here is to use mixed models at the individual plant or plot level. Using statistical arguments, simulations, and real data we investigate the feasibility of both approaches and how these affect genomic prediction with the best linear unbiased predictor and genome-wide association studies. Heritability estimates obtained from genotypic means had very large standard errors and were sometimes biologically unrealistic. Mixed models at the individual plant or plot level produced more realistic estimates, and for simulated traits standard errors were up to 13 times smaller. Genomic prediction was also improved by using these mixed models, with up to a 49% increase in accuracy. For genome-wide association studies on simulated traits, the use of individual plant data gave almost no increase in power. The new methodology is applicable to any complex trait where multiple replicates of individual genotypes can be scored. This includes important agronomic crops, as well as bacteria and fungi.

Association mapping for five agronomic traits in the common bean (Phaseolus vulgaris L.)

BACKGROUND

The common bean is the most important grain legume and a major source of protein in many developing countries. We analysed the following traits: pod fibre (PF), seeds per pod (SPP), plant type (PT), growth habit (GH), and days to flowering (DF) for a set of diverse common bean accessions and determined whether such traits were associated with amplified fragment length polymorphism (AFLP), simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers.

RESULTS

In this study, 66 common bean genotypes were used and genotyped with 233 AFLP, 105 SNP and 80 SSR markers. The association analysis between markers and five traits was performed using a General Linear Model (GLM) in Trait Analysis by aSSociation, Evolution and Linkage (TASSEL). The population structure was determined using the STRUCTURE software, and seven groups (K = 7) were identified among genotypes. The associations for such traits were identified and quantified; 62 markers were associated with the five traits.

CONCLUSION

This study demonstrated that association mapping using a reasonable number of markers, distributed across the genome and with the appropriate number of individuals harboured to detect DNA markers linked to the traits of PF, SPP, PT, GH and DF in common bean.

Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice

Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1. Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits.

Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice

Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1. Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits.

Exploiting natural variation of secondary metabolism identifies a gene controlling the glycosylation diversity of dihydroxybenzoic acids in Arabidopsis thaliana

Plant secondary metabolism is an active research area because of the unique and important roles the specialized metabolites have in the interaction of plants with their biotic and abiotic environment, the diversity and complexity of the compounds and their importance to human medicine. Thousands of natural accessions of Arabidopsis thaliana characterized with increasing genomic precision are available, providing new opportunities to explore the biochemical and genetic mechanisms affecting variation in secondary metabolism within this model species. In this study, we focused on four aromatic metabolites that were differentially accumulated among 96 Arabidopsis natural accessions as revealed by leaf metabolic profiling. Using UV, mass spectrometry, and NMR data, we identified these four compounds as different dihydroxybenzoic acid (DHBA) glycosides, namely 2,5-dihydroxybenzoic acid (gentisic acid) 5-O-β-D-glucoside, 2,3-dihydroxybenzoic acid 3-O-β-D-glucoside, 2,5-dihydroxybenzoic acid 5-O-β-D-xyloside, and 2,3-dihydroxybenzoic acid 3-O-β-D-xyloside. Quantitative trait locus (QTL) mapping using recombinant inbred lines generated from C24 and Col-0 revealed a major-effect QTL controlling the relative proportion of xylosides vs. glucosides. Association mapping identified markers linked to a gene encoding a UDP glycosyltransferase gene. Analysis of Transfer DNA (T-DNA) knockout lines verified that this gene is required for DHBA xylosylation in planta and recombinant protein was able to xylosylate DHBA in vitro. This study demonstrates that exploiting natural variation of secondary metabolism is a powerful approach for gene function discovery.

Population genomic variation reveals roles of history, adaptation and ploidy in switchgrass

Geographic patterns of genetic variation are shaped by multiple evolutionary processes, including genetic drift, migration and natural selection. Switchgrass (Panicum virgatum L.) has strong genetic and adaptive differentiation despite life history characteristics that promote high levels of gene flow and can homogenize intraspecific differences, such as wind-pollination and self-incompatibility. To better understand how historical and contemporary factors shape variation in switchgrass, we use genotyping-by-sequencing to characterize switchgrass from across its range at 98 042 SNPs. Population structuring reflects biogeographic and ploidy differences within and between switchgrass ecotypes and indicates that biogeographic history, ploidy incompatibilities and differential adaptation each have important roles in shaping ecotypic differentiation in switchgrass. At one extreme, we determine that two Panicum taxa are not separate species but are actually conspecific, ecologically divergent types of switchgrass adapted to the extreme conditions of coastal sand dune habitats. Conversely, we identify natural hybrids among lowland and upland ecotypes and visualize their genome-wide patterns of admixture. Furthermore, we determine that genetic differentiation between primarily tetraploid and octoploid lineages is not caused solely by ploidy differences. Rather, genetic diversity in primarily octoploid lineages is consistent with a history of admixture. This suggests that polyploidy in switchgrass is promoted by admixture of diverged lineages, which may be important for maintaining genetic differentiation between switchgrass ecotypes where they are sympatric. These results provide new insights into the mechanisms shaping variation in widespread species and provide a foundation for dissecting the genetic basis of adaptation in switchgrass.

Multiple FLC haplotypes defined by independent cis-regulatory variation underpin life history diversity in Arabidopsis thaliana

A key question in evolutionary biology is how molecular variation relates to phenotypic diversity. Arabidopsis FLOWERING LOCUS C (FLC) plays a key role in controlling vernalization—the acceleration of flowering by prolonged cold. Li et al. identify five functionally distinct FLC haplotypes, defined by noncoding sequence variation, which vary in FLC expression level and silencing. Allelic heterogeneity at this single locus accounts for a large proportion of variation in Arabidopsis vernalization. This study advances our understanding of adaptation and provides a new paradigm for analysis of complex traits.

Relating molecular variation to phenotypic diversity is a central goal in evolutionary biology. In Arabidopsis thaliana, FLOWERING LOCUS C (FLC) is a major determinant of variation in vernalization—the acceleration of flowering by prolonged cold. Here, through analysis of 1307 A. thaliana accessions, we identify five predominant FLC haplotypes defined by noncoding sequence variation. Genetic and transgenic experiments show that they are functionally distinct, varying in FLC expression level and rate of epigenetic silencing. Allelic heterogeneity at this single locus accounts for a large proportion of natural variation in vernalization that contributes to adaptation of A. thaliana.

Efficient DNA fingerprinting based on the targeted sequencing of active retrotransposon insertion sites using a bench-top high-throughput sequencing platform

In many crop species, DNA fingerprinting is required for the precise identification of cultivars to protect the rights of breeders. Many families of retrotransposons have multiple copies throughout the eukaryotic genome and their integrated copies are inherited genetically. Thus, their insertion polymorphisms among cultivars are useful for DNA fingerprinting. In this study, we conducted a DNA fingerprinting based on the insertion polymorphisms of active retrotransposon families (Rtsp-1 and LIb) in sweet potato. Using 38 cultivars, we identified 2,024 insertion sites in the two families with an Illumina MiSeq sequencing platform. Of these insertion sites, 91.4% appeared to be polymorphic among the cultivars and 376 cultivar-specific insertion sites were identified, which were converted directly into cultivar-specific sequence-characterized amplified region (SCAR) markers. A phylogenetic tree was constructed using these insertion sites, which corresponded well with known pedigree information, thereby indicating their suitability for genetic diversity studies. Thus, the genome-wide comparative analysis of active retrotransposon insertion sites using the bench-top MiSeq sequencing platform is highly effective for DNA fingerprinting without any requirement for whole genome sequence information. This approach may facilitate the development of practical polymerase chain reaction-based cultivar diagnostic system and could also be applied to the determination of genetic relationships.

Association mapping of germination traits in Arabidopsis thaliana under light and nutrient treatments: searching for G×E effects

In the natural world, genotype expression is influenced by an organism’s environment. Identifying and understanding the genes underlying phenotypes in different environments is important for making advances in fields ranging from evolution to medicine to agriculture. With the availability of genome-wide genetic-marker datasets, it is possible to look for genes that interact with the environment. Using the model organism, Arabidopsis thaliana, we looked for genes underlying phenotypes as well as genotype-by-environment interactions in four germination traits under two light and two nutrient conditions. We then performed genome-wide association tests to identify candidate genes underlying the observed phenotypes and genotype-by-environment interactions. Of the four germination traits examined, only two showed significant genotype-by-environment interactions. While genome-wide association analyses did not identify any markers or genes explicitly linked to genotype-by-environment interactions, we did identify a total of 55 markers and 71 genes associated with germination differences. Of the 71 genes, four—ZIGA4, PS1, TOR, and TT12—appear to be strong candidates for further study of germination variation under different environments.

Lagging adaptation to warming climate in Arabidopsis thaliana

If climate change outpaces the rate of adaptive evolution within a site, populations previously well adapted to local conditions may decline or disappear, and banked seeds from those populations will be unsuitable for restoring them. However, if such adaptational lag has occurred, immigrants from historically warmer climates will outperform natives and may provide genetic potential for evolutionary rescue. We tested for lagging adaptation to warming climate using banked seeds of the annual weed Arabidopsis thaliana in common garden experiments in four sites across the species' native European range: Valencia, Spain; Norwich, United Kingdom; Halle, Germany; and Oulu, Finland. Genotypes originating from geographic regions near the planting site had high relative fitness in each site, direct evidence for broad-scale geographic adaptation in this model species. However, genotypes originating in sites historically warmer than the planting site had higher average relative fitness than local genotypes in every site, especially at the northern range limit in Finland. This result suggests that local adaptive optima have shifted rapidly with recent warming across the species' native range. Climatic optima also differed among seasonal germination cohorts within the Norwich site, suggesting that populations occurring where summer germination is common may have greater evolutionary potential to persist under future warming. If adaptational lag has occurred over just a few decades in banked seeds of an annual species, it may be an important consideration for managing longer-lived species, as well as for attempts to conserve threatened populations through ex situ preservation.

Climate relicts and their associated communities as natural ecology and evolution laboratories

Climate relicts, marginal populations that have become isolated via climate-driven range shifts, preserve ecological and evolutionary histories that can span millennia. Studies point to climate relicts as 'natural laboratories' for investigating how long-term environmental change impacts species and populations. However, we propose that such research should be expanded to reveal how climate change affects 'interacting' species in ways that reshape community composition and evolution. Biotic interactions and their community and ecosystem effects are often genetically based and driven by associations with foundation species. We discuss evolution in climate relicts within the context of the emerging fields of community and ecosystem genetics, exploring the idea that foundation relicts are also natural community and ecosystem laboratories and windows to future landscapes.

Genotype×environment interaction QTL mapping in plants: lessons from Arabidopsis

Plant growth and development are influenced by the genetic composition of the plant (G), the environment (E), and the interaction between them (G×E). To produce suitable genotypes for multiple environments, G×E should be accounted for and assessed in plant-breeding programs. Here, we review the genetic basis of G×E and its consequence for quantitative trait loci (QTL) mapping in biparental and genome-wide association (GWA) mapping populations. We also consider the implications of G×E for understanding plant fitness trade-offs and evolutionary ecology.