Expression quantitative trait locus mapping across water availability environments reveals contrasting associations with genomic features in Arabidopsis

The quantitative genetics of gene expression in Mimulus guttatus

Gene expression can be influenced by genetic variants that are closely linked to the expressed gene (cis eQTLs) and variants in other parts of the genome (trans eQTLs). We created a multiparental mapping population by sampling genotypes from a single natural population of Mimulus guttatus and scored gene expression in the leaves of 1,588 plants. We find that nearly every measured gene exhibits cis regulatory variation (91% have FDR < 0.05). cis eQTLs are usually allelic series with three or more functionally distinct alleles. The cis locus explains about two thirds of the standing genetic variance (on average) but varies among genes and tends to be greatest when there is high indel variation in the upstream regulatory region and high nucleotide diversity in the coding sequence. Despite mapping over 10,000 trans eQTL / affected gene pairs, most of the genetic variance generated by trans acting loci remains unexplained. This implies a large reservoir of trans acting genes with subtle or diffuse effects. Mapped trans eQTLs show lower allelic diversity but much higher genetic dominance than cis eQTLs. Several analyses also indicate that trans eQTLs make a substantial contribution to the genetic correlations in expression among different genes. They may thus be essential determinants of "gene expression modules," which has important implications for the evolution of gene expression and how it is studied by geneticists.

Genome-wide mapping of regulatory variants for temperature- and salinity-adaptive genes reveals genetic basis of genotype-by-environment interaction in Crassostrea ariakensis

Regulatory variants in gene expression serve as bridges linking genetic variation and phenotypic plasticity. Environmental conditions typically influence the effects of regulatory variants on phenotypic plasticity; however, such genotype-by-environment interactions (G × E) are poorly understood. This study aimed to investigate the genetic basis of G × E in estuarine oyster (Crassostrea ariakensis), which is an important model animal for studying environmental adaption owing to its high plasticity and large intraspecific divergence. Genome-wide mapping of expression quantitative trait loci (eQTLs) for 23 environmental adaptive genes was performed for 256 estuarine oysters. We identified 1194 eQTL single nucleotide polymorphisms (eSNPs), including 433 cis-eSNPs in four genes and 722 trans-eSNPs in eight genes. The expression variation explanation of cis-eSNPs (9.95%) was significantly higher than that of trans-eSNPs (9.15%). We specifically showed cis- and trans-eSNPs with high linkage disequilibrium (LD) for Traf7, Slc6a5, Ggt, and Dap3. For example, we identified a cis-regulatory LD block containing 68 cis-eSNP and a trans-regulatory LD block, including 20 trans-eSNPs in Traf7. A high proportion (85%) of 40 vital eSNPs exhibited significant G × E effects. We identified crossing and nonparallel interactions of G × E, with the tag cis-eSNPs of Baat and Slc6a5 as representatives. Our results indicated that cis-eQTLs are highly conserved. This study provides insights into the understanding of adaptive evolutionary mechanisms and phenotypic response prediction to variable environments, as well as the genetic improvement for superior adaptive traits for genetic resource conservation and aquaculture.

Combined genome-wide association studies and expression quantitative trait locus analysis uncovers a genetic regulatory network of floral organ number in a tree peony (Paeonia suffruticosa Andrews) breeding population

Great progress has been made in our understanding of floral organ identity determination and its regulatory network in many species; however, the quantitative genetic basis of floral organ number variation is far less well understood for species-specific traits from the perspective of population variation. Here, using a tree peony (Paeonia suffruticosa Andrews, Paeoniaceae) cultivar population as a model, the phenotypic polymorphism and genetic variation based on genome-wide association studies (GWAS) and expression quantitative trait locus (eQTL) analysis were analyzed. Based on 24 phenotypic traits of 271 representative cultivars, the transcript profiles of 119 cultivars were obtained, which indicated abundant genetic variation in tree peony. In total, 86 GWAS-related cis-eQTLs and 3188 trans-eQTL gene pairs were found to be associated with the numbers of petals, stamens, and carpels. In addition, 19 floral organ number-related hub genes with 121 cis-eQTLs were obtained by weighted gene co-expression network analysis, among which five hub genes belonging to the ABCE genes of the MADS-box family and their spatial-temporal co-expression and regulatory network were constructed. These results not only help our understanding of the genetic basis of floral organ number variation during domestication, but also pave the way to studying the quantitative genetics and evolution of flower organ number and their regulatory network within populations.

Environmental response in gene expression and DNA methylation reveals factors influencing the adaptive potential of Arabidopsis lyrata

Understanding what factors influence plastic and genetic variation is valuable for predicting how organisms respond to changes in the selective environment. Here, using gene expression and DNA methylation as molecular phenotypes, we study environmentally induced variation among Arabidopsis lyrata plants grown at lowland and alpine field sites. Our results show that gene expression is highly plastic, as many more genes are differentially expressed between the field sites than between populations. These environmentally responsive genes evolve under strong selective constraint – the strength of purifying selection on the coding sequence is high, while the rate of adaptive evolution is low. We find, however, that positive selection on cis-regulatory variants has likely contributed to the maintenance of genetically variable environmental responses, but such variants segregate only between distantly related populations. In contrast to gene expression, DNA methylation at genic regions is largely insensitive to the environment, and plastic methylation changes are not associated with differential gene expression. Besides genes, we detect environmental effects at transposable elements (TEs): TEs at the high-altitude field site have higher expression and methylation levels, suggestive of a broad-scale TE activation. Compared to the lowland population, plants native to the alpine environment harbor an excess of recent TE insertions, and we observe that specific TE families are enriched within environmentally responsive genes. Our findings provide insight into selective forces shaping plastic and genetic variation. We also highlight how plastic responses at TEs can rapidly create novel heritable variation in stressful conditions.

Natural variation in growth and leaf ion homeostasis in response to salinity stress in Panicum hallii

Soil salinity can negatively impact plants growth, development and fitness. Natural plant populations restricted to coastal environments may evolve in response to saline habitats and therefore provide insights into the process of salinity adaptation. We investigated the growth and physiological responses of coastal and inland populations of Panicum hallii to experimental salinity treatments. Coastal genotypes demonstrated less growth reduction and superior ion homeostasis compared to the inland genotypes in response to saline conditions, supporting a hypothesis of local adaptation. We identified several QTL associated with the plasticity of belowground biomass, leaf sodium and potassium content, and their ratio which underscores the genetic variation present in this species for salinity responses. Genome-wide transcriptome analysis in leaf and root tissue revealed tissue specific overexpression of genes including several cation transporters in the coastal genotype. These transporters mediate sodium ion compartmentalization and potassium ion retention and thus suggests that maintenance of ionic homeostasis of the coastal genotypes might be due to the regulation of these ion transporters. These findings contribute to our understanding of the genetics and molecular mechanisms of salinity adaptation in natural populations, and widens the scope for genetic manipulation of these candidate genes to design plants more resilient to climate change.

A Pleiotropic Flowering Time QTL Exhibits Gene-by-Environment Interaction for Fitness in a Perennial Grass

Appropriate flowering time is a crucial adaptation impacting fitness in natural plant populations. Although the genetic basis of flowering variation has been extensively studied, its mechanisms in nonmodel organisms and its adaptive value in the field are still poorly understood. Here, we report new insights into the genetic basis of flowering time and its effect on fitness in Panicum hallii, a native perennial grass. Genetic mapping in populations derived from inland and coastal ecotypes identified flowering time quantitative trait loci (QTL) and many exhibited extensive QTL-by-environment interactions. Patterns of segregation within recombinant hybrids provide strong support for directional selection driving ecotypic divergence in flowering time. A major QTL on chromosome 5 (q-FT5) was detected in all experiments. Fine-mapping and expression studies identified a gene with orthology to a rice FLOWERING LOCUS T-like 9 (PhFTL9) as the candidate underlying q-FT5. We used a reciprocal transplant experiment to test for local adaptation and the specific impact of q-FT5 on performance. We did not observe local adaptation in terms of fitness tradeoffs when contrasting ecotypes in home versus away habitats. However, we observed that the coastal allele of q-FT5 conferred a fitness advantage only in its local habitat but not at the inland site. Sequence analyses identified an excess of low-frequency polymorphisms at the PhFTL9 promoter in the inland lineage, suggesting a role for either selection or population expansion on promoter evolution. Together, our findings demonstrate the genetic basis of flowering variation in a perennial grass and provide evidence for conditional neutrality underlying flowering time divergence.

Genetics as a key to improving crop photosynthesis

Since the basic biochemical mechanisms of photosynthesis are remarkably conserved among plant species, genetic modification approaches have so far been the main route to improve the photosynthetic performance of crops. Yet, phenotypic variation observed in wild species and between varieties of crop species implies there is standing natural genetic variation for photosynthesis, offering a largely unexplored resource to use for breeding crops with improved photosynthesis and higher yields. The reason this has not yet been explored is that the variation probably involves thousands of genes, each contributing only a little to photosynthesis, making them hard to identify without proper phenotyping and genetic tools. This is changing, though, and increasingly studies report on quantitative trait loci for photosynthetic phenotypes. So far, hardly any of these quantitative trait loci have been used in marker assisted breeding or genomic selection approaches to improve crop photosynthesis and yield, and hardly ever have the underlying causal genes been identified. We propose to take the genetics of photosynthesis to a higher level, and identify the genes and alleles nature has used for millions of years to tune photosynthesis to be in line with local environmental conditions. We will need to determine the physiological function of the genes and alleles, and design novel strategies to use this knowledge to improve crop photosynthesis through conventional plant breeding, based on readily available crop plant germplasm. In this work, we present and discuss the genetic methods needed to reveal natural genetic variation, and elaborate on how to apply this to improve crop photosynthesis.

Exploitation of Drought Tolerance-Related Genes for Crop Improvement

Drought has become a major threat to food security, because it affects crop growth and development. Drought tolerance is an important quantitative trait, which is regulated by hundreds of genes in crop plants. In recent decades, scientists have made considerable progress to uncover the genetic and molecular mechanisms of drought tolerance, especially in model plants. This review summarizes the evaluation criteria for drought tolerance, methods for gene mining, characterization of genes related to drought tolerance, and explores the approaches to enhance crop drought tolerance. Collectively, this review illustrates the application prospect of these genes in improving the drought tolerance breeding of crop plants.

Detecting drought regulators using stochastic inference in Bayesian networks

Drought is a natural hazard that affects crops by inducing water stress. Water stress, induced by drought accounts for more loss in crop yield than all the other causes combined. With the increasing frequency and intensity of droughts worldwide, it is essential to develop drought-resistant crops to ensure food security. In this paper, we model multiple drought signaling pathways in Arabidopsis using Bayesian networks to identify potential regulators of drought-responsive reporter genes. Genetically intervening at these regulators can help develop drought-resistant crops. We create the Bayesian network model from the biological literature and determine its parameters from publicly available data. We conduct inference on this model using a stochastic simulation technique known as likelihood weighting to determine the best regulators of drought-responsive reporter genes. Our analysis reveals that activating MYC2 or inhibiting ATAF1 are the best single node intervention strategies to regulate the drought-responsive reporter genes. Additionally, we observe simultaneously activating MYC2 and inhibiting ATAF1 is a better strategy. The Bayesian network model indicated that MYC2 and ATAF1 are possible regulators of the drought response. Validation experiments showed that ATAF1 negatively regulated the drought response. Thus intervening at ATAF1 has the potential to create drought-resistant crops.

Fine-scale empirical data on niche divergence and homeolog expression patterns in an allopolyploid and its diploid progenitor species

Polyploidization is pervasive in plants, but little is known about the niche divergence of wild allopolyploids (species that harbor polyploid genomes originating from different diploid species) relative to their diploid progenitor species and the gene expression patterns that may underlie such ecological divergence. We conducted a fine-scale empirical study on habitat and gene expression of an allopolyploid and its diploid progenitors. We quantified soil properties and light availability of habitats of an allotetraploid Cardamine flexuosa and its diploid progenitors Cardamine amara and Cardamine hirsuta in two seasons. We analyzed expression patterns of genes and homeologs (homeologous gene copies in allopolyploids) using RNA sequencing. We detected niche divergence between the allopolyploid and its diploid progenitors along water availability gradient at a fine scale: the diploids in opposite extremes and the allopolyploid in a broader range between diploids, with limited overlap with diploids at both ends. Most of the genes whose homeolog expression ratio changed among habitats in C. flexuosa varied spatially and temporally. These findings provide empirical evidence for niche divergence between an allopolyploid and its diploid progenitor species at a fine scale and suggest that divergent expression patterns of homeologs in an allopolyploid may underlie its persistence in diverse habitats.

A framework for understanding gene expression plasticity and its influence on stress tolerance

Phenotypic plasticity can serve as a stepping stone towards adaptation. Recently, studies have shown that gene expression contributes to emergent stress responses such as thermal tolerance, with tolerant and susceptible populations showing distinct transcriptional profiles. However, given the dynamic nature of gene expression, interpreting transcriptomic results in a way that elucidates the functional connection between gene expression and the observed stress response is challenging. Here, we present a conceptual framework to guide interpretation of gene expression reaction norms in the context of stress tolerance. We consider the evolutionary and adaptive potential of gene expression reaction norms and discuss the influence of sampling timing, transcriptomic resilience, as well as complexities related to life history when interpreting gene expression dynamics and how these patterns relate to host tolerance. We highlight corals as a case study to demonstrate the value of this framework for non-model systems. As species face rapidly changing environmental conditions, modulating gene expression can serve as a mechanistic link from genetic and cellular processes to the physiological responses that allow organisms to thrive under novel conditions. Interpreting how or whether a species can employ gene expression plasticity to ensure short-term survival will be critical for understanding the global impacts of climate change across diverse taxa.

Network Analysis Prioritizes DEWAX and ICE1 as the Candidate Genes for Major eQTL Hotspots in Seed Germination of Arabidopsis thaliana

Seed germination is characterized by a constant change of gene expression across different time points. These changes are related to specific processes, which eventually determine the onset of seed germination. To get a better understanding on the regulation of gene expression during seed germination, we performed a quantitative trait locus mapping of gene expression (eQTL) at four important seed germination stages (primary dormant, after-ripened, six-hour after imbibition, and radicle protrusion stage) using Arabidopsis thaliana Bay x Sha recombinant inbred lines (RILs). The mapping displayed the distinctness of the eQTL landscape for each stage. We found several eQTL hotspots across stages associated with the regulation of expression of a large number of genes. Interestingly, an eQTL hotspot on chromosome five collocates with hotspots for phenotypic and metabolic QTL in the same population. Finally, we constructed a gene co-expression network to prioritize the regulatory genes for two major eQTL hotspots. The network analysis prioritizes transcription factors DEWAX and ICE1 as the most likely regulatory genes for the hotspot. Together, we have revealed that the genetic regulation of gene expression is dynamic along the course of seed germination.

Combined GWAS and eQTL analysis uncovers a genetic regulatory network orchestrating the initiation of secondary cell wall development in cotton

The cotton fibre serves as a valuable experimental system to study cell wall synthesis in plants, but our understanding of the genetic regulation of this process during fibre development remains limited. We performed a genome-wide association study (GWAS) and identified 28 genetic loci associated with fibre quality in allotetraploid cotton. To investigate the regulatory roles of these loci, we sequenced fibre transcriptomes of 251 cotton accessions and identified 15 330 expression quantitative trait loci (eQTL). Analysis of local eQTL and GWAS data prioritised 13 likely causal genes for differential fibre quality in a transcriptome-wide association study (TWAS). Characterisation of distal eQTL revealed unequal genetic regulation patterns between two subgenomes, highlighted by an eQTL hotspot (Hot216) that established a genome-wide genetic network regulating the expression of 962 genes. The primary regulatory role of Hot216, and specifically the gene encoding a KIP-related protein, was found to be the transcriptional regulation of genes responsible for cell wall synthesis, which contributes to fibre length by modulating the developmental transition from rapid cell elongation to secondary cell wall synthesis. This study uncovered the genetic regulation of fibre-cell development and revealed the molecular basis of the temporal modulation of secondary cell wall synthesis during plant cell elongation.

The Evolutionary Forces Shaping Cis- and Trans-Regulation of Gene Expression within a Population of Outcrossing Plants

Understanding the persistence of genetic variation within populations has long been a goal of evolutionary biology. One promising route toward achieving this goal is using population genetic approaches to describe how selection acts on the loci associated with trait variation. Gene expression provides a model trait for addressing the challenge of the maintenance of variation because it can be measured genome-wide without information about how gene expression affects traits. Previous work has shown that loci affecting the expression of nearby genes (local or cis-eQTLs) are under negative selection, but we lack a clear understanding of the selective forces acting on variants that affect the expression of genes in trans. Here, we identify loci that affect gene expression in trans using genomic and transcriptomic data from one population of the obligately outcrossing plant, Capsella grandiflora. The allele frequencies of trans-eQTLs are consistent with stronger negative selection acting on trans-eQTLs than cis-eQTLs, and stronger negative selection acting on trans-eQTLs associated with the expression of multiple genes. However, despite this general pattern, we still observe the presence of a trans-eQTL at intermediate frequency that affects the expression of a large number of genes in the same coexpression module. Overall, our work highlights the different selective pressures shaping variation in cis- and trans-regulation.

Genome-wide expression quantitative trait locus analysis in a recombinant inbred line population for trait dissection in peanut

The transcriptome connects genome to the gene function and ultimate phenome in biology. So far, transcriptomic approach was not used in peanut for performing trait mapping in bi-parental populations. In this research, we sequenced the whole transcriptome in immature seeds in a peanut recombinant inbred line (RIL) population and explored thoroughly the landscape of transcriptomic variations and its genetic basis. The comprehensive analysis identified total 49 691 genes in RIL population, of which 92 genes followed a paramutation-like expression pattern. Expression quantitative trait locus (eQTL) analysis identified 1207 local eQTLs and 15 837 distant eQTLs contributing to the whole-genome transcriptomic variation in peanut. There were 94 eQTL hot spot regions detected across the genome with the dominance of distant eQTL. By integrating transcriptomic profile and annotation analyses, we unveiled a putative candidate gene and developed a linked marker InDel02 underlying a major QTL responsible for purple testa colour in peanut. Our result provided a first understanding of genetic basis of whole-genome transcriptomic variation in peanut and illustrates the potential of the transcriptome-aid approach in dissecting important traits in non-model plants.

Discovery of early life stress interacting and sex-specific quantitative trait loci impacting cocaine responsiveness

BACKGROUND AND PURPOSE

Addiction vulnerability involves complex gene X environment interactions leading to a pathological response to drugs. Identification of the genes involved in these interactions is an important step in understanding the underlying neurobiology and rarely have such analyses examined sex-specific influences. To dissect this interaction, we examined the impact of prenatal stress (PNS) on cocaine responsiveness in male and female mice of the BXD recombinant inbred panel.

EXPERIMENTAL APPROACH

BXD strains were subjected to timed mating and assigned to PNS or control groups. PNS dams were subjected to restraint stress (1-hr restraint, three times daily) starting between embryonic day (E) 11 and 14 and continued until parturition. Adult male and female, control and PNS offspring were tested for locomotor response to initial and repeated cocaine injections (sensitization) as well as cocaine-induced conditioned place preference (CPP).

KEY RESULTS

Strain, PNS, and sex interacted to modulate initial and sensitized cocaine-induced locomotion, as well as CPP. Moreover, a quantitative trait locus (QTL) interacting with PNS regulating initial locomotor response to cocaine (chromosome X, 37.91 to 50.95 Mb) was identified. Also PNS-independent, female-specific QTLs regulating CPP (chromosome 11, 65.50 to 81.31 Mb) and sensitized cocaine-induced locomotion (chromosome 16, 95.79 to 98.32 Mb) were identified. Publicly available mRNA expression data were utilized to identify cis-eQTL and transcript covariation with the behavioural phenotype to prioritize candidate genes; including Aifm1.

CONCLUSIONS AND IMPLICATIONS

These QTL encompass genes that may moderate genetic susceptibility to PNS and interact with sex to determine adult responsiveness to cocaine and addiction vulnerability.

LINKED ARTICLES

This article is part of a themed section on The Importance of Sex Differences in Pharmacology Research. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v176.21/issuetoc.

Allele-specific expression and genetic determinants of transcriptomic variations in response to mild water deficit in tomato

Characterizing the natural diversity of gene expression across environments is an important step in understanding how genotype-by-environment interactions shape phenotypes. Here, we analyzed the impact of water deficit onto gene expression levels in tomato at the genome-wide scale. We sequenced the transcriptome of growing leaves and fruit pericarps at cell expansion stage in a cherry and a large fruited accession and their F₁ hybrid grown under two watering regimes. Gene expression levels were steadily affected by the genotype and the watering regime. Whereas phenotypes showed mostly additive inheritance, ~80% of the genes displayed non-additive inheritance. By comparing allele-specific expression (ASE) in the F₁ hybrid to the allelic expression in both parental lines, respectively, 3005 genes in leaf and 2857 genes in fruit deviated from 1:1 ratio independently of the watering regime. Among these genes, ~55% were controlled by cis factors, ~25% by trans factors and ~20% by a combination of both types of factors. A total of 328 genes in leaf and 113 in fruit exhibited significant ASE-by-watering regime interaction, among which ~80% presented trans-by-watering regime interaction, suggesting a response to water deficit mediated through a majority of trans-acting loci in tomato. We cross-validated the expression levels of 274 transcripts in fruit and leaves of 124 recombinant inbred lines (RILs) and identified 163 expression quantitative trait loci (eQTLs) mostly confirming the divergences identified by ASE. Combining phenotypic and expression data, we observed a complex network of variation between genes encoding enzymes involved in the sugar metabolism.

Components of Water Use Efficiency Have Unique Genetic Signatures in the Model C4 Grass Setaria

Plant growth and water use are interrelated processes influenced by genetically controlled morphological and biochemical characteristics. Improving plant water use efficiency (WUE) to sustain growth in different environments is an important breeding objective that can improve crop yields and enhance agricultural sustainability. However, genetic improvement of WUE using traditional methods has proven difficult due to the low throughput and environmental heterogeneity of field settings. To overcome these limitations, this study utilizes a high-throughput phenotyping platform to quantify plant size and water use of an interspecific Setaria italica × Setaria viridis recombinant inbred line population at daily intervals in both well-watered and water-limited conditions. Our findings indicate that measurements of plant size and water use are correlated strongly in this system; therefore, a linear modeling approach was used to partition this relationship into predicted values of plant size given water use and deviations from this relationship at the genotype level. The resulting traits describing plant size, water use, and WUE all were heritable and responsive to soil water availability, allowing for a genetic dissection of the components of plant WUE under different watering treatments. Linkage mapping identified major loci underlying two different pleiotropic components of WUE. This study indicates that alleles controlling WUE derived from both wild and domesticated accessions can be utilized to predictably modulate trait values given a specified precipitation regime in the model C4 genus Setaria.

Integrated QTL and eQTL Mapping Provides Insights and Candidate Genes for Fatty Acid Composition, Flowering Time, and Growth Traits in a F2 Population of a Novel Synthetic Allopolyploid Brassica napus

Brassica napus (B. napus, AACC), is an economically important allotetraploid crop species that resulted from hybridization between two diploid species, Brassica rapa (AA) and Brassica olereacea (CC). We have created one new synthetic B. napus genotype Da-Ae (AACC) and one introgression line Da-Ol-1 (AACC), which were used to generate an F₂ mapping population. Plants in this F₂ mapping population varied in fatty acid content, flowering time, and growth-related traits. Using quantitative trait locus (QTL) mapping, we aimed to determine if Da-Ae and Da-Ol-1 provided novel genetic variation beyond what has already been found in B. napus. Making use of the genotyping information generated from RNA-seq data of these two lines and their F₂ mapping population of 166 plants, we constructed a genetic map consisting of 2,021 single nucleotide polymorphism markers that spans 2,929 cM across 19 linkage groups. Besides the known major QTL identified, our high resolution genetic map facilitated the identification of several new QTL contributing to the different fatty acid levels, flowering time, and growth-related trait values. These new QTL probably represent novel genetic variation that existed in our new synthetic B. napus strain. By conducting genome-wide expression variation analysis in our F₂ mapping population, genetic regions that potentially regulate many genes across the genome were revealed. A FLOWERING LOCUS C gene homolog, which was identified as a candidate regulating flowering time and multiple growth-related traits, was found underlying one of these regions. Integrated QTL and expression QTL analyses also helped us identified candidate causative genes associated with various biological traits through expression level change and/or possible protein function modification.

Construction of a High-Density Genetic Map from RNA-Seq Data for an Arabidopsis Bay-0 × Shahdara RIL Population

High-density genetic maps are essential for high resolution mapping of quantitative traits. Here, we present a new genetic map for an Arabidopsis Bayreuth × Shahdara recombinant inbred line (RIL) population, built on RNA-seq data. RNA-seq analysis on 160 RILs of this population identified 30,049 single-nucleotide polymorphisms (SNPs) covering the whole genome. Based on a 100-kbp window SNP binning method, 1059 bin-markers were identified, physically anchored on the genome. The total length of the RNA-seq genetic map spans 471.70 centimorgans (cM) with an average marker distance of 0.45 cM and a maximum marker distance of 4.81 cM. This high resolution genotyping revealed new recombination breakpoints in the population. To highlight the advantages of such high-density map, we compared it to two publicly available genetic maps for the same population, comprising 69 PCR-based markers and 497 gene expression markers derived from microarray data, respectively. In this study, we show that SNP markers can effectively be derived from RNA-seq data. The new RNA-seq map closes many existing gaps in marker coverage, saturating the previously available genetic maps. Quantitative trait locus (QTL) analysis for published phenotypes using the available genetic maps showed increased QTL mapping resolution and reduced QTL confidence interval using the RNA-seq map. The new high-density map is a valuable resource that facilitates the identification of candidate genes and map-based cloning approaches.

In situ conservation-harnessing natural and human-derived evolutionary forces to ensure future crop adaptation

Ensuring the availability of the broadest possible germplasm base for agriculture in the face of increasingly uncertain and variable patterns of biotic and abiotic change is fundamental for the world's future food supply. While ex situ conservation plays a major role in the conservation and availability of crop germplasm, it may be insufficient to ensure this. In situ conservation aims to maintain target species and the collective genotypes they represent under evolution. A major rationale for this view is based on the likelihood that continued exposure to changing selective forces will generate and favor new genetic variation and an increased likelihood that rare alleles that may be of value to future agriculture are maintained. However, the evidence that underpins this key rationale remains fragmented and has not been examined systematically, thereby decreasing the perceived value and support for in situ conservation for agriculture and food systems and limiting the conservation options available. This study reviews evidence regarding the likelihood and rate of evolutionary change in both biotic and abiotic traits for crops and their wild relatives, placing these processes in a realistic context in which smallholder farming operates and crop wild relatives continue to exist. It identifies areas of research that would contribute to a deeper understanding of these processes as the basis for making them more useful for future crop adaptation.

Time-course expression QTL-atlas of the global transcriptional response of wheat to Fusarium graminearum

Fusarium head blight is a devastating disease of small grain cereals such as bread wheat (Triticum aestivum). The pathogen switches from a biotrophic to a nectrotrophic lifestyle in course of disease development forcing its host to adapt its defence strategies. Using a genetical genomics approach, we illustrate genome-wide reconfigurations of genetic control over transcript abundances between two decisive time points after inoculation with the causative pathogen Fusarium graminearum. Whole transcriptome measurements have been recorded for 163 lines of a wheat doubled haploid population segregating for several resistance genes yielding 15 552 at 30 h and 15 888 eQTL at 50 h after inoculation. The genetic map saturated with transcript abundance-derived markers identified of a novel QTL on chromosome 6A, besides the previously reported QTL Fhb1 and Qfhs.ifa-5A. We find a highly different distribution of eQTL between time points with about 40% of eQTL being unique for the respective assessed time points. But also for more than 20% of genes governed by eQTL at either time point, genetic control changes in time. These changes are reflected in the dynamic compositions of three major regulatory hotspots on chromosomes 2B, 4A and 5A. In particular, control of defence-related biological mechanisms concentrated in the hotspot at 4A shift to hotspot 2B as the disease progresses. Hotspots do not colocalize with phenotypic QTL, and within their intervals no higher than expected number of eQTL was detected. Thus, resistance conferred by either QTL is mediated by few or single genes.

Stress-Related Gene Expression Reflects Morphophysiological Responses to Water Deficit

Acclimation to water deficit (WD) enables plants to maintain growth under unfavorable environmental conditions, although the mechanisms are not completely understood. In this study, the natural variation of long-term acclimation to moderate and severe soil WD was investigated in 18 Arabidopsis (Arabidopsis thaliana) accessions using PHENOPSIS, an automated phenotyping platform. Soil water content was adjusted at an early stage of plant development and maintained at a constant level until reproductive age was achieved. The accessions were selected based on the expression levels of ANNEXIN1, a drought-related marker. Severe WD conditions had a greater effect on most of the measured morphophysiological traits than moderate WD conditions. Multivariate analyses indicated that trait responses associated with plant size and water management drove most of the variation. Accessions with similar responses at these two levels were grouped in clusters that displayed different response strategies to WD The expression levels of selected stress-response genes revealed large natural variation under WD conditions. Responses of morphophysiological traits, such as projected rosette area, transpiration rate, and rosette water content, were correlated with changes in the expression of stress-related genes, such as NINE-CIS-EPOXYCAROTENOID DIOXYGENASE3 and N-MYC DOWNREGULATED-LIKE1 (NDL1), in response to WD Interestingly, the morphophysiological acclimation response to WD also was reflected in the gene expression levels (most notably those of NDL1, CHALCONE SYNTHASE, and MYB DOMAIN PROTEIN44) in plants cultivated under well-watered conditions. Our results may lead to the development of biomarkers and predictors of plant morphophysiological responses based on gene expression patterns.

Topological features of a gene co-expression network predict patterns of natural diversity in environmental response

Molecular interactions affect the evolution of complex traits. For instance, adaptation may be constrained by pleiotropic or epistatic effects, both of which can be reflected in the structure of molecular interaction networks. To date, empirical studies investigating the role of molecular interactions in phenotypic evolution have been idiosyncratic, offering no clear patterns. Here, we investigated the network topology of genes putatively involved in local adaptation to two abiotic stressors-drought and cold-in Arabidopsis thaliana Our findings suggest that the gene-interaction topologies for both cold and drought stress response are non-random, with genes that show genetic variation in drought expression response (eGxE) being significantly more peripheral and cold response genes being significantly more central than genes which do not show GxE. We suggest that the observed topologies reflect different constraints on the genetic pathways involved in environmental response. The approach presented here may inform predictive models linking genetic variation in molecular signalling networks with phenotypic variation, specifically traits involved in environmental response.

Genetic dissection of seed oil and protein content and identification of networks associated with oil content in Brassica napus

High-density linkage maps can improve the precision of QTL localization. A high-density SNP-based linkage map containing 3207 markers covering 3072.7 cM of the Brassica napus genome was constructed in the KenC-8 × N53-2 (KNDH) population. A total of 67 and 38 QTLs for seed oil and protein content were identified with an average confidence interval of 5.26 and 4.38 cM, which could explain up to 22.24% and 27.48% of the phenotypic variation, respectively. Thirty-eight associated genomic regions from BSA overlapped with and/or narrowed the SOC-QTLs, further confirming the QTL mapping results based on the high-density linkage map. Potential candidates related to acyl-lipid and seed storage underlying SOC and SPC, respectively, were identified and analyzed, among which six were checked and showed expression differences between the two parents during different embryonic developmental periods. A large primary carbohydrate pathway based on potential candidates underlying SOC- and SPC-QTLs, and interaction networks based on potential candidates underlying SOC-QTLs, was constructed to dissect the complex mechanism based on metabolic and gene regulatory features, respectively. Accurate QTL mapping and potential candidates identified based on high-density linkage map and BSA analyses provide new insights into the complex genetic mechanism of oil and protein accumulation in the seeds of rapeseed.

Gene co-expression network connectivity is an important determinant of selective constraint

While several studies have investigated general properties of the genetic architecture of natural variation in gene expression, few of these have considered natural, outbreeding populations. In parallel, systems biology has established that a general feature of biological networks is that they are scale-free, rendering them buffered against random mutations. To date, few studies have attempted to examine the relationship between the selective processes acting to maintain natural variation of gene expression and the associated co-expression network structure. Here we utilised RNA-Sequencing to assay gene expression in winter buds undergoing bud flush in a natural population of Populus tremula, an outbreeding forest tree species. We performed expression Quantitative Trait Locus (eQTL) mapping and identified 164,290 significant eQTLs associating 6,241 unique genes (eGenes) with 147,419 unique SNPs (eSNPs). We found approximately four times as many local as distant eQTLs, with local eQTLs having significantly higher effect sizes. eQTLs were primarily located in regulatory regions of genes (UTRs or flanking regions), regardless of whether they were local or distant. We used the gene expression data to infer a co-expression network and investigated the relationship between network topology, the genetic architecture of gene expression and signatures of selection. Within the co-expression network, eGenes were underrepresented in network module cores (hubs) and overrepresented in the periphery of the network, with a negative correlation between eQTL effect size and network connectivity. We additionally found that module core genes have experienced stronger selective constraint on coding and non-coding sequence, with connectivity associated with signatures of selection. Our integrated genetics and genomics results suggest that purifying selection is the primary mechanism underlying the genetic architecture of natural variation in gene expression assayed in flushing leaf buds of P. tremula and that connectivity within the co-expression network is linked to the strength of purifying selection.

AraQTL - workbench and archive for systems genetics in Arabidopsis thaliana

Genetical genomics studies uncover genome-wide genetic interactions between genes and their transcriptional regulators. High-throughput measurement of gene expression in recombinant inbred line populations has enabled investigation of the genetic architecture of variation in gene expression. This has the potential to enrich our understanding of the molecular mechanisms affected by and underlying natural variation. Moreover, it contributes to the systems biology of natural variation, as a substantial number of experiments have resulted in a valuable amount of interconnectable phenotypic, molecular and genotypic data. A number of genetical genomics studies have been published for Arabidopsis thaliana, uncovering many expression quantitative trait loci (eQTLs). However, these complex data are not easily accessible to the plant research community, leaving most of the valuable genetic interactions unexplored as cross-analysis of these studies is a major effort. We address this problem with AraQTL (http://www.bioinformatics.nl/Ara QTL/), an easily accessible workbench and database for comparative analysis and meta-analysis of all published Arabidopsis eQTL datasets. AraQTL provides a workbench for comparing, re-using and extending upon the results of these experiments. For example, one can easily screen a physical region for specific local eQTLs that could harbour candidate genes for phenotypic QTLs, or detect gene-by-environment interactions by comparing eQTLs under different conditions.

Different contributions of local- and distant-regulatory changes to transcriptome divergence between stickleback ecotypes

Differential gene expression can play an important role in phenotypic evolution and divergent adaptation. Although differential gene expression can be caused by both local- and distant-regulatory changes, we know little about their relative contribution to transcriptome evolution in natural populations. Here, we conducted expression quantitative trait loci (eQTL) analysis to investigate the genetic architecture underlying transcriptome divergence between marine and stream ecotypes of threespine sticklebacks (Gasterosteus aculeatus). We identified both local and distant eQTLs, some of which constitute hotspots, regions with a disproportionate number of significant eQTLs relative to the genomic background. The majority of local eQTLs including those in the hotspots caused expression changes consistent with the direction of transcriptomic divergence between ecotypes. Genome scan analysis showed that many local eQTLs overlapped with genomic regions of high differentiation. In contrast, nearly half of the distant eQTLs including those in the hotspots caused opposite expression changes, and few overlapped with regions of high differentiation, indicating that distant eQTLs may act as a constraint of transcriptome evolution. Finally, a comparison between two salinity conditions revealed that nearly half of eQTL hotspots were environment specific, suggesting that analysis of genetic architecture in multiple conditions is essential for predicting response to selection.

eQTLs Regulating Transcript Variations Associated with Rapid Internode Elongation in Deepwater Rice

To avoid low oxygen, oxygen deficiency or oxygen deprivation, deepwater rice cultivated in flood planes can develop elongated internodes in response to submergence. Knowledge of the gene regulatory networks underlying rapid internode elongation is important for an understanding of the evolution and adaptation of major crops in response to flooding. To elucidate the genetic and molecular basis controlling their deepwater response we used microarrays and performed expression quantitative trait loci (eQTL) and phenotypic QTL (phQTL) analyses of internode samples of 85 recombinant inbred line (RIL) populations of non-deepwater (Taichung 65)- and deepwater rice (Bhadua). After evaluating the phenotypic response of the RILs exposed to submergence, confirming the genotypes of the populations, and generating 188 genetic markers, we identified 10,047 significant eQTLs comprised of 2,902 cis-eQTLs and 7,145 trans-eQTLs and three significant eQTL hotspots on chromosomes 1, 4, and 12 that affect the expression of many genes. The hotspots on chromosomes 1 and 4 located at different position from phQTLs detected in this study and other previous studies. We then regarded the eQTL hotspots as key regulatory points to infer causal regulatory networks of deepwater response including rapid internode elongation. Our results suggest that the downstream regulation of the eQTL hotspots on chromosomes 1 and 4 is independent, and that the target genes are partially regulated by SNORKEL1 and SNORKEL2 genes (SK1/2), key ethylene response factors. Subsequent bioinformatic analyses, including gene ontology-based annotation and functional enrichment analysis and promoter enrichment analysis, contribute to enhance our understanding of SK1/2-dependent and independent pathways. One remarkable observation is that the functional categories related to photosynthesis and light signaling are significantly over-represented in the candidate target genes of SK1/2. The combined results of these investigations together with genetical genomics approaches using structured populations with a deepwater response are also discussed in the context of current molecular models concerning the rapid internode elongation in deepwater rice. This study provides new insights into the underlying genetic architecture of gene expression regulating the response to flooding in deepwater rice and will be an important community resource for analyses on the genetic basis of deepwater responses.

Metabolomic analysis of tomato seed germination

INTRODUCTION

Seed germination is inherently related to seed metabolism, which changes throughout its maturation, desiccation and germination processes. The metabolite content of a seed and its ability to germinate are determined by underlying genetic architecture and environmental effects during development.

OBJECTIVE

This study aimed to assess an integrative approach to explore genetics modulating seed metabolism in different developmental stages and the link between seed metabolic- and germination traits.

METHODS

We have utilized gas chromatography-time-of-flight/mass spectrometry (GC-TOF/MS) metabolite profiling to characterize tomato seeds during dry and imbibed stages. We describe, for the first time in tomato, the use of a so-called generalized genetical genomics (GGG) model to study the interaction between genetics, environment and seed metabolism using 100 tomato recombinant inbred lines (RILs) derived from a cross between Solanum lycopersicum and Solanum pimpinellifolium.

RESULTS

QTLs were found for over two-thirds of the metabolites within several QTL hotspots. The transition from dry to 6 h imbibed seeds was associated with programmed metabolic switches. Significant correlations varied among individual metabolites and the obtained clusters were significantly enriched for metabolites involved in specific biochemical pathways.

CONCLUSIONS

Extensive genetic variation in metabolite abundance was uncovered. Numerous identified genetic regions that coordinate groups of metabolites were detected and these will contain plausible candidate genes. The combined analysis of germination phenotypes and metabolite profiles provides a strong indication for the hypothesis that metabolic composition is related to germination phenotypes and thus to seed performance.

Natural gene expression variation studies in yeast

The rise of sequence information across different yeast species and strains is driving an increasing number of studies in the emerging field of genomics to associate polymorphic variants, mRNA abundance and phenotypic differences between individuals. Here, we gathered evidence from recent studies covering several layers that define the genotype-phenotype gap, such as mRNA abundance, allele-specific expression and translation efficiency to demonstrate how genetic variants co-evolve and define an individual's genome. Moreover, we exposed several antecedents where inter- and intra-specific studies led to opposite conclusions, probably owing to genetic divergence. Future studies in this area will benefit from the access to a massive array of well-annotated genomes and new sequencing technologies, which will allow the fine breakdown of the complex layers that delineate the genotype-phenotype map. Copyright © 2016 John Wiley & Sons, Ltd.

Quantitative trait loci associated with natural diversity in water-use efficiency and response to soil drying in Brachypodium distachyon

All plants must optimize their growth with finite resources. Water use efficiency (WUE) measures the relationship between biomass acquisition and transpired water. In the present study, we performed two experiments to understand the genetic basis of WUE and other parameters of plant-water interaction under control and water-limited conditions. Our study used two inbred natural accessions of Brachypodium distachyon, a model grass species with close phylogenetic affinity to temperate forage and cereal crops. First, we identify the soil water content which causes a reduction in leaf relative water content and an increase in WUE. Second, we present results from a large phenotyping experiment utilizing a recombinant inbred line mapping population derived from these same two natural accessions. We identify QTLs associated with environmentally-insensitive genetic variation in WUE, including a pair of epistatically interacting loci. We also identify QTLs associated with constitutive differences in biomass and a QTL describing an environmentally-sensitive difference in leaf carbon content. Finally, we present a new linkage map for this mapping population based on new SNP markers as well as updated genomic positions for previously described markers. Our studies provide an initial characterization of plant-water relations in B. distachyon and identify candidate genomic regions involved in WUE.

Leaf Growth Response to Mild Drought: Natural Variation in Arabidopsis Sheds Light on Trait Architecture

Plant growth and crop yield are negatively affected by a reduction in water availability. However, a clear understanding of how growth is regulated under nonlethal drought conditions is lacking. Recent advances in genomics, phenomics, and transcriptomics allow in-depth analysis of natural variation. In this study, we conducted a detailed screening of leaf growth responses to mild drought in a worldwide collection of Arabidopsis thaliana accessions. The genetic architecture of the growth responses upon mild drought was investigated by subjecting the different leaf growth phenotypes to genome-wide association mapping and by characterizing the transcriptome of young developing leaves. Although no major effect locus was found to be associated with growth in mild drought, the transcriptome analysis delivered further insight into the natural variation of transcriptional responses to mild drought in a specific tissue. Coexpression analysis indicated the presence of gene clusters that co-vary over different genetic backgrounds, among others a cluster of genes with important regulatory functions in the growth response to osmotic stress. It was found that the occurrence of a mild drought stress response in leaves can be inferred with high accuracy across accessions based on the expression profile of 283 genes. A genome-wide association study on the expression data revealed that trans regulation seems to be more important than cis regulation in the transcriptional response to environmental perturbations.

Transcriptome responses to temperature, water availability and photoperiod are conserved among mature trees of two divergent Douglas-fir provenances from a coastal and an interior habitat

BACKGROUND

Local adaptation and phenotypic plasticity are important components of plant responses to variations in environmental conditions. While local adaptation has been widely studied in trees, little is known about plasticity of gene expression in adult trees in response to ever changing environmental conditions in natural habitats. Here we investigate plasticity of gene expression in needle tissue between two Douglas-fir provenances represented by 25 adult trees using deep RNA sequencing (RNA-Seq).

RESULTS

Using linear mixed models we investigated the effect of temperature, soil water availability and photoperiod on the abundance of 59189 detected transcripts. Expression of more than 80 % of all identified transcripts revealed a response to variations in environmental conditions in the field. GO term overrepresentation analysis revealed gene expression responses to temperature, soil water availability and photoperiod that are highly conserved among many plant taxa. However, expression differences between the two Douglas-fir provenances were rather small compared to the expression differences observed between individual trees. Although the effect of environment on global transcript expression was high, the observed genotype by environment (GxE) interaction of gene expression was surprisingly low, since only 21 of all detected transcripts showed a GxE interaction.

CONCLUSIONS

The majority of the transcriptome responses in plant leaf tissue is driven by variations in environmental conditions. The small variation between individuals and populations suggests strong conservation of this response within Douglas-fir. Therefore we conclude that plastic transcriptome responses to variations in environmental conditions are only weakly affected by local adaptation in Douglas-fir.

Genotypes, Networks, Phenotypes: Moving Toward Plant Systems Genetics

One of the central goals in biology is to understand how and how much of the phenotype of an organism is encoded in its genome. Although many genes that are crucial for organismal processes have been identified, much less is known about the genetic bases underlying quantitative phenotypic differences in natural populations. We discuss the fundamental gap between the large body of knowledge generated over the past decades by experimental genetics in the laboratory and what is needed to understand the genotype-to-phenotype problem on a broader scale. We argue that systems genetics, a combination of systems biology and the study of natural variation using quantitative genetics, will help to address this problem. We present major advances in these two mostly disconnected areas that have increased our understanding of the developmental processes of flowering time control and root growth. We conclude by illustrating and discussing the efforts that have been made toward systems genetics specifically in plants.

Envirotyping for deciphering environmental impacts on crop plants

Global climate change imposes increasing impacts on our environments and crop production. To decipher environmental impacts on crop plants, the concept "envirotyping" is proposed, as a third "typing" technology, complementing with genotyping and phenotyping. Environmental factors can be collected through multiple environmental trials, geographic and soil information systems, measurement of soil and canopy properties, and evaluation of companion organisms. Envirotyping contributes to crop modeling and phenotype prediction through its functional components, including genotype-by-environment interaction (GEI), genes responsive to environmental signals, biotic and abiotic stresses, and integrative phenotyping. Envirotyping, driven by information and support systems, has a wide range of applications, including environmental characterization, GEI analysis, phenotype prediction, near-iso-environment construction, agronomic genomics, precision agriculture and breeding, and development of a four-dimensional profile of crop science involving genotype (G), phenotype (P), envirotype (E) and time (T) (developmental stage). In the future, envirotyping needs to zoom into specific experimental plots and individual plants, along with the development of high-throughput and precision envirotyping platforms, to integrate genotypic, phenotypic and envirotypic information for establishing a high-efficient precision breeding and sustainable crop production system based on deciphered environmental impacts.

Transcriptome sequencing reveals the roles of transcription factors in modulating genotype by nitrogen interaction in maize

Global transcriptome analysis in maize revealed differential nitrogen response between genotypes and implicate a crucial role of transcription factors in driving genotype by nitrogen interactions at gene expression level. Developing nitrogen-efficient cultivars are essential for sustainable and productive agriculture. Nitrogen use efficiency of plants is highly dependent on the interaction of environmental and genetic variation and results in adaptive phenotypes. This study used transcriptome sequencing to perform a comprehensive genotype by nitrogen (G × N) interaction analysis for two elite Chinese maize inbreds grown at normal and low nitrogen levels in field conditions. We demonstrated that the two maize inbreds showed contrasting agronomic and transcriptomic responses to changes in nitrogen availability. A total of 96 genes with a significant G × N interaction were detected. After characterizing the expression patterns of G × N interaction genes, we found that the G × N interaction genes tended to show condition-specific differential expression. The functional annotations of G × N interaction genes revealed that many different kinds of genes were involved in G × N interactions, but a significant enrichment for transcription factors was detected, particularly the AP2/EREBP and WRKY family, suggesting that transcription factors might play important roles in driving G × N interaction at gene expression level for nitrogen response in maize. Taken together, these results not only provide novel insights into the mechanism of nitrogen response in maize and set important basis for further characterization but also have important implications for other genotype by stress interaction.

Exploiting Differential Gene Expression and Epistasis to Discover Candidate Genes for Drought-Associated QTLs in Arabidopsis thaliana

Soil water availability represents one of the most important selective agents for plants in nature and the single greatest abiotic determinant of agricultural productivity, yet the genetic bases of drought acclimation responses remain poorly understood. Here, we developed a systems-genetic approach to characterize quantitative trait loci (QTLs), physiological traits and genes that affect responses to soil moisture deficit in the TSUxKAS mapping population of Arabidopsis thaliana. To determine the effects of candidate genes underlying QTLs, we analyzed gene expression as a covariate within the QTL model in an effort to mechanistically link markers, RNA expression, and the phenotype. This strategy produced ranked lists of candidate genes for several drought-associated traits, including water use efficiency, growth, abscisic acid concentration (ABA), and proline concentration. As a proof of concept, we recovered known causal loci for several QTLs. For other traits, including ABA, we identified novel loci not previously associated with drought. Furthermore, we documented natural variation at two key steps in proline metabolism and demonstrated that the mitochondrial genome differentially affects genomic QTLs to influence proline accumulation. These findings demonstrate that linking genome, transcriptome, and phenotype data holds great promise to extend the utility of genetic mapping, even when QTL effects are modest or complex.

Transcriptomic changes due to water deficit define a general soybean response and accession-specific pathways for drought avoidance

BACKGROUND

Among abiotic stresses, drought is the most common reducer of crop yields. The slow-wilting soybean genotype PI 416937 is somewhat robust to water deficit and has been used previously to map the trait in a bi-parental population. Since drought stress response is a complex biological process, whole genome transcriptome analysis was performed to obtain a deeper understanding of the drought response in soybean.

RESULTS

Contrasting data from PI 416937 and the cultivar 'Benning', we developed a classification system to identify genes that were either responding to water-deficit in both genotypes or that had a genotype x environment (GxE) response. In spite of very different wilting phenotypes, 90% of classifiable genes had either constant expression in both genotypes (33%) or very similar response profiles (E genes, 57%). By further classifying E genes based on expression profiles, we were able to discern the functional specificity of transcriptional responses at particular stages of water-deficit, noting both the well-known reduction in photosynthesis genes as well as the less understood up-regulation of the protein transport pathway. Two percent of classifiable genes had a well-defined GxE response, many of which are located within slow-wilting QTLs. We consider these strong candidates for possible causal genes underlying PI 416937's unique drought avoidance strategy.

CONCLUSIONS

There is a general and functionally significant transcriptional response to water deficit that involves not only known pathways, such as down-regulation of photosynthesis, but also up-regulation of protein transport and chromatin remodeling. Genes that show a genotypic difference are more likely to show an environmental response than genes that are constant between genotypes. In this study, at least five genes that clearly exhibited a genotype x environment response fell within known QTL and are very good candidates for further research into slow-wilting.

Extensive cis-regulatory variation robust to environmental perturbation in Arabidopsis

cis- and trans-acting factors affect gene expression and responses to environmental conditions. However, for most plant systems, we lack a comprehensive map of these factors and their interaction with environmental variation. Here, we examined allele-specific expression (ASE) in an F1 hybrid to study how alleles from two Arabidopsis thaliana accessions affect gene expression. To investigate the effect of the environment, we used drought stress and developed a variance component model to estimate the combined genetic contributions of cis- and trans-regulatory polymorphisms, environmental factors, and their interactions. We quantified ASE for 11,003 genes, identifying 3318 genes with consistent ASE in control and stress conditions, demonstrating that cis-acting genetic effects are essentially robust to changes in the environment. Moreover, we found 1618 genes with genotype x environment (GxE) interactions, mostly cis x E interactions with magnitude changes in ASE. We found fewer trans x E interactions, but these effects were relatively less robust across conditions, showing more changes in the direction of the effect between environments; this confirms that trans-regulation plays an important role in the response to environmental conditions. Our data provide a detailed map of cis- and trans-regulation and GxE interactions in A. thaliana, laying the ground for mechanistic investigations and studies in other plants and environments.

Natural variation in abiotic stress responsive gene expression and local adaptation to climate in Arabidopsis thaliana

Gene expression varies widely in natural populations, yet the proximate and ultimate causes of this variation are poorly known. Understanding how variation in gene expression affects abiotic stress tolerance, fitness, and adaptation is central to the field of evolutionary genetics. We tested the hypothesis that genes with natural genetic variation in their expression responses to abiotic stress are likely to be involved in local adaptation to climate in Arabidopsis thaliana. Specifically, we compared genes with consistent expression responses to environmental stress (expression stress responsive, "eSR") to genes with genetically variable responses to abiotic stress (expression genotype-by-environment interaction, "eGEI"). We found that on average genes that exhibited eGEI in response to drought or cold had greater polymorphism in promoter regions and stronger associations with climate than those of eSR genes or genomic controls. We also found that transcription factor binding sites known to respond to environmental stressors, especially abscisic acid responsive elements, showed significantly higher polymorphism in drought eGEI genes in comparison to eSR genes. By contrast, eSR genes tended to exhibit relatively greater pairwise haplotype sharing, lower promoter diversity, and fewer nonsynonymous polymorphisms, suggesting purifying selection or selective sweeps. Our results indicate that cis-regulatory evolution and genetic variation in stress responsive gene expression may be important mechanisms of local adaptation to climatic selective gradients.

Genetic architecture of naturally occurring quantitative traits in plants: an updated synthesis

Deciphering the genetic and molecular bases of quantitative variation is a long-standing challenge in plant biology because it is essential for understanding evolution and for accelerating plant breeding. Recent multi-trait analyses at different phenotypic levels are uncovering the pleiotropy and the genetic regulation underlying high-level complex traits. Thus, the number of known causal loci, genes and nucleotide polymorphisms is expanding. Current plant causal catalogs contain ∼400 genes and natural polymorphisms revealing several dysfunctional allelic series that involve multiple mutations. In addition, repeated evolution of quantitative traits mediated by large effect alleles is found across plant phylogeny. Finally, systematic analyses of genetic and environmental interactions are beginning to elucidate the molecular mechanisms of relevant interactions.