A cell wall-associated gene network shapes leaf boundary domains.

Boundary domains delimit and organize organ growth throughout plant development almost relentlessly, building plant architecture and morphogenesis. Boundary domains display reduced growth and orchestrate development of adjacent tissues in a non-cell-autonomous manner. How these two functions are achieved remains elusive despite the identification of several boundary-specific genes. Here, we show using morphometrics at the organ and cellular levels that leaf boundary domain development requires SPINDLY (SPY), an O-fucosyltransferase, to act as cell growth repressor. Furthermore, we show that SPY acts redundantly with the CUP-SHAPED COTYLEDON transcription factors (CUC2 and CUC3), which are major determinants of boundaries development. Accordingly, at the molecular level CUC2 and SPY repress a common set of genes involved in cell wall loosening, providing a molecular framework for the growth repression associated with boundary domains. Atomic force microscopy confirmed that young leaf boundary domain cells have stiffer cell walls than marginal outgrowth. This differential cell wall stiffness was reduced in spy mutant plants. Taken together, our data reveal a concealed CUC2 cell wall-associated gene network linking tissue patterning with cell growth and mechanics.

A Case of Gene Fragmentation in Plant Mitochondria Fixed by the Selection of a Compensatory Restorer of Fertility-Like PPR Gene.

The high mutational load of mitochondrial genomes combined with their uniparental inheritance and high polyploidy favors the maintenance of deleterious mutations within populations. How cells compose and adapt to the accumulation of disadvantageous mitochondrial alleles remains unclear. Most harmful changes are likely corrected by purifying selection, however, the intimate collaboration between mitochondria- and nuclear-encoded gene products offers theoretical potential for compensatory adaptive changes. In plants, cytoplasmic male sterilities are known examples of nucleo-mitochondrial coadaptation situations in which nuclear-encoded restorer of fertility (Rf) genes evolve to counteract the effect of mitochondria-encoded cytoplasmic male sterility (CMS) genes and restore fertility. Most cloned Rfs belong to a small monophyletic group, comprising 26 pentatricopeptide repeat genes in Arabidopsis, called Rf-like (RFL). In this analysis, we explored the functional diversity of RFL genes in Arabidopsis and found that the RFL8 gene is not related to CMS suppression but essential for plant embryo development. In vitro-rescued rfl8 plantlets are deficient in the production of the mitochondrial heme-lyase complex. A complete ensemble of molecular and genetic analyses allowed us to demonstrate that the RFL8 gene has been selected to permit the translation of the mitochondrial ccmFN2 gene encoding a heme-lyase complex subunit which derives from the split of the ccmFN gene, specifically in Brassicaceae plants. This study represents thus a clear case of nuclear compensation to a lineage-specific mitochondrial genomic rearrangement in plants and demonstrates that RFL genes can be selected in response to other mitochondrial deviancies than CMS suppression.

Omics Data Reveal Putative Regulators of Einkorn Grain Protein Composition under Sulfur Deficiency.

Understanding the molecular mechanisms controlling the accumulation of grain storage proteins in response to nitrogen (N) and sulfur (S) nutrition is essential to improve cereal grain nutritional and functional properties. Here, we studied the grain transcriptome and metabolome responses to postanthesis N and S supply for the diploid wheat einkorn (Triticum monococcum). During grain filling, 848 transcripts and 24 metabolites were differentially accumulated in response to N and S availability. The accumulation of total free amino acids per grain and the expression levels of 241 genes showed significant modifications during most of the grain filling period and were upregulated in response to S deficiency. Among them, 24 transcripts strongly responded to S deficiency and were identified in coexpression network analyses as potential coordinators of the grain response to N and S supply. Sulfate transporters and genes involved in sulfate and Met metabolism were upregulated, suggesting regulation of the pool of free amino acids and of the grain N-to-S ratio. Several genes highlighted in this study might limit the impact of S deficiency on the accumulation of grain storage proteins.

Landscape of the Noncoding Transcriptome Response of Two Arabidopsis Ecotypes to Phosphate Starvation.

Root architecture varies widely between species; it even varies between ecotypes of the same species, despite strong conservation of the coding portion of their genomes. By contrast, noncoding RNAs evolve rapidly between ecotypes and may control their differential responses to the environment, since several long noncoding RNAs (lncRNAs) are known to quantitatively regulate gene expression. Roots from ecotypes Columbia and Landsberg erecta of Arabidopsis (Arabidopsis thaliana) respond differently to phosphate starvation. Here, we compared transcriptomes (mRNAs, lncRNAs, and small RNAs) of root tips from these two ecotypes during early phosphate starvation. We identified thousands of lncRNAs that were largely conserved at the DNA level in these ecotypes. In contrast to coding genes, many lncRNAs were specifically transcribed in one ecotype and/or differentially expressed between ecotypes independent of phosphate availability. We further characterized these ecotype-related lncRNAs and studied their link with small interfering RNAs. Our analysis identified 675 lncRNAs differentially expressed between the two ecotypes, including antisense RNAs targeting key regulators of root-growth responses. Misregulation of several lincRNAs showed that at least two ecotype-related lncRNAs regulate primary root growth in ecotype Columbia. RNA-sequencing analysis following deregulation of lncRNA NPC48 revealed a potential link with root growth and transport functions. This exploration of the noncoding transcriptome identified ecotype-specific lncRNA-mediated regulation in root apexes. The noncoding genome may harbor further mechanisms involved in ecotype adaptation of roots to different soil environments.

Systemic control of nodule formation by plant nitrogen demand requires autoregulation-dependent and independent mechanisms.

In legumes interacting with rhizobia, the formation of symbiotic organs involved in the acquisition of atmospheric nitrogen gas (N2) is dependent on the plant nitrogen (N) demand. We used Medicago truncatula plants cultivated in split-root systems to discriminate between responses to local and systemic N signaling. We evidenced a strong control of nodule formation by systemic N signaling but obtained no clear evidence of a local control by mineral nitrogen. Systemic signaling of the plant N demand controls numerous transcripts involved in root transcriptome reprogramming associated with early rhizobia interaction and nodule formation. SUPER NUMERIC NODULES (SUNN) has an important role in this control, but we found that major systemic N signaling responses remained active in the sunn mutant. Genes involved in the activation of nitrogen fixation are regulated by systemic N signaling in the mutant, explaining why its hypernodulation phenotype is not associated with higher nitrogen fixation of the whole plant. We show that the control of transcriptome reprogramming of nodule formation by systemic N signaling requires other pathway(s) that parallel the SUNN/CLE (CLAVATA3/EMBRYO SURROUNDING REGION-LIKE PEPTIDES) pathway.

Involvement of SUT1 and SUT2 Sugar Transporters in the Impairment of Sugar Transport and Changes in Phloem Exudate Contents in Phytoplasma-Infected Plants.

Phytoplasmas inhabit phloem sieve elements and cause abnormal growth and altered sugar partitioning. However, how they interact with phloem functions is not clearly known. The phloem responses were investigated in tomatoes infected by "Candidatus Phytoplasma solani" at the beginning of the symptomatic stage, the first symptoms appearing in the newly emerged leaf at the stem apex. Antisense lines impaired in the phloem sucrose transporters SUT1 and SUT2 were included. In symptomatic sink leaves, leaf curling was associated with higher starch accumulation and the expression of defense genes. The analysis of leaf midribs of symptomatic leaves indicated that transcript levels for genes acting in the glycolysis and peroxisome metabolism differed from these in noninfected plants. The phytoplasma also multiplied in the three lower source leaves, even if it was not associated with the symptoms. In these leaves, the rate of phloem sucrose exudation was lower for infected plants. Metabolite profiling of phloem sap-enriched exudates revealed that glycolate and aspartate levels were affected by the infection. Their levels were also affected in the noninfected SUT1- and SUT2-antisense lines. The findings suggest the role of sugar transporters in the responses to infection and describe the consequences of impaired sugar transport on the primary metabolism.

In situ transcriptomic and metabolomic study of the loss of photosynthesis in the leaves of mixotrophic plants exploiting fungi.

Mycoheterotrophic plants have lost photosynthesis and obtain carbon through mycorrhizal fungi colonizing their roots. They are likely to have evolved from mixotrophic ancestors, which rely on both photosynthesis and fungal carbon for their development. Whereas our understanding of the ecological and genomic changes associated with the evolutionary shift to mycoheterotrophy is deepening, little information is known about the specific metabolic and physiological features driving this evolution. We investigated this issue in naturally occurring achlorophyllous variants of temperate mixotrophic orchids. We carried out an integrated transcriptomic and metabolomic analysis of the response to achlorophylly in the leaves of three mixotrophic species sampled in natura. Achlorophyllous leaves showed major impairment of their photosynthetic and mineral nutrition functions, strong accumulation of free amino acids, overexpression of enzymes and transporters related to sugars, amino acids and fatty acid catabolism, as well as induction of some autophagy-related and biotic stress genes. Such changes were reminiscent of these reported for variegated leaves and appeared to be symptomatic of a carbon starvation response. Rather than decisive metabolic innovations, we suggest that the evolution towards mycoheterotrophy in orchids is more likely to be reliant on the versatility of plant metabolism and an ability to exploit fungal organic resources, especially amino acids, to replace missing photosynthates.

Gene expression predictions and networks in natural populations supports the omnigenic theory.

BACKGROUND: Recent literature on the differential role of genes within networks distinguishes core from peripheral genes. If previous works have shown contrasting features between them, whether such categorization matters for phenotype prediction remains to be studied. RESULTS: We measured 17 phenotypic traits for 241 cloned genotypes from a Populus nigra collection, covering growth, phenology, chemical and physical properties. We also sequenced RNA for each genotype and built co-expression networks to define core and peripheral genes. We found that cores were more differentiated between populations than peripherals while being less variable, suggesting that they have been constrained through potentially divergent selection. We also showed that while cores were overrepresented in a subset of genes statistically selected for their capacity to predict the phenotypes (by Boruta algorithm), they did not systematically predict better than peripherals or even random genes. CONCLUSION: Our work is the first attempt to assess the importance of co-expression network connectivity in phenotype prediction. While highly connected core genes appear to be important, they do not bear enough information to systematically predict better quantitative traits than other gene sets.

Synthetic data sets for the identification of key ingredients for RNA-seq differential analysis.

Numerous statistical pipelines are now available for the differential analysis of gene expression measured with RNA-sequencing technology. Most of them are based on similar statistical frameworks after normalization, differing primarily in the choice of data distribution, mean and variance estimation strategy and data filtering. We propose an evaluation of the impact of these choices when few biological replicates are available through the use of synthetic data sets. This framework is based on real data sets and allows the exploration of various scenarios differing in the proportion of non-differentially expressed genes. Hence, it provides an evaluation of the key ingredients of the differential analysis, free of the biases associated with the simulation of data using parametric models. Our results show the relevance of a proper modeling of the mean by using linear or generalized linear modeling. Once the mean is properly modeled, the impact of the other parameters on the performance of the test is much less important. Finally, we propose to use the simple visualization of the raw P-value histogram as a practical evaluation criterion of the performance of differential analysis methods on real data sets.

Responses of mature symbiotic nodules to the whole-plant systemic nitrogen signaling.

In symbiotic root nodules of legumes, terminally differentiated rhizobia fix atmospheric N2 producing an NH4+ influx that is assimilated by the plant. The plant, in return, provides photosynthates that fuel the symbiotic nitrogen acquisition. Mechanisms responsible for the adjustment of the symbiotic capacity to the plant N demand remain poorly understood. We have investigated the role of systemic signaling of whole-plant N demand on the mature N2-fixing nodules of the model symbiotic association Medicago truncatula/Sinorhizobium using split-root systems. The whole-plant N-satiety signaling rapidly triggers reductions of both N2 fixation and allocation of sugars to the nodule. These responses are associated with the induction of nodule senescence and the activation of plant defenses against microbes, as well as variations in sugars transport and nodule metabolism. The whole-plant N-deficit responses mirror these changes: a rapid increase of sucrose allocation in response to N-deficit is associated with a stimulation of nodule functioning and development resulting in nodule expansion in the long term. Physiological, transcriptomic, and metabolomic data together provide evidence for strong integration of symbiotic nodules into whole-plant nitrogen demand by systemic signaling and suggest roles for sugar allocation and hormones in the signaling mechanisms.

Sampling uncertainty versus method uncertainty: A general framework with applications to omics biomarker selection.

Uncertainty is a crucial issue in statistics which can be considered from different points of view. One type of uncertainty, typically referred to as sampling uncertainty, arises through the variability of results obtained when the same analysis strategy is applied to different samples. Another type of uncertainty arises through the variability of results obtained when using the same sample but different analysis strategies addressing the same research question. We denote this latter type of uncertainty as method uncertainty. It results from all the choices to be made for an analysis, for example, decisions related to data preparation, method choice, or model selection. In medical sciences, a large part of omics research is focused on the identification of molecular biomarkers, which can either be performed through ranking or by selection from among a large number of candidates. In this paper, we introduce a general resampling-based framework to quantify and compare sampling and method uncertainty. For illustration, we apply this framework to different scenarios related to the selection and ranking of omics biomarkers in the context of acute myeloid leukemia: variable selection in multivariable regression using different types of omics markers, the ranking of biomarkers according to their predictive performance, and the identification of differentially expressed genes from RNA-seq data. For all three scenarios, our findings suggest highly unstable results when the same analysis strategy is applied to two independent samples, indicating high sampling uncertainty and a comparatively smaller, but non-negligible method uncertainty, which strongly depends on the methods being compared.

Cytonuclear interactions affect adaptive traits of the annual plant Arabidopsis thaliana in the field.

Although the contribution of cytonuclear interactions to plant fitness variation is relatively well documented at the interspecific level, the prevalence of cytonuclear interactions at the intraspecific level remains poorly investigated. In this study, we set up a field experiment to explore the range of effects that cytonuclear interactions have on fitness-related traits in Arabidopsis thaliana To do so, we created a unique series of 56 cytolines resulting from cytoplasmic substitutions among eight natural accessions reflecting within-species genetic diversity. An assessment of these cytolines and their parental lines scored for 28 adaptive whole-organism phenotypes showed that a large proportion of phenotypic traits (23 of 28) were affected by cytonuclear interactions. The effects of these interactions varied from slight but frequent across cytolines to strong in some specific parental pairs. Two parental pairs accounted for half of the significant pairwise interactions. In one parental pair, Ct-1/Sha, we observed symmetrical phenotypic responses between the two nuclear backgrounds when combined with specific cytoplasms, suggesting nuclear differentiation at loci involved in cytonuclear epistasis. In contrast, asymmetrical phenotypic responses were observed in another parental pair, Cvi-0/Sha. In the Cvi-0 nuclear background, fecundity and phenology-related traits were strongly affected by the Sha cytoplasm, leading to a modified reproductive strategy without penalizing total seed production. These results indicate that natural variation in cytoplasmic and nuclear genomes interact to shape integrative traits that contribute to adaptation, thereby suggesting that cytonuclear interactions can play a major role in the evolutionary dynamics ofA. thaliana.

Transcriptome reprogramming due to the introduction of a barley telosome into bread wheat affects more barley genes than wheat.

Despite a long history, the production of useful alien introgression lines in wheat remains difficult mainly due to linkage drag and incomplete genetic compensation. In addition, little is known about the molecular mechanisms underlying the impact of foreign chromatin on plant phenotype. Here, a comparison of the transcriptomes of barley, wheat and a wheat-barley 7HL addition line allowed the transcriptional impact both on 7HL genes of a non-native genetic background and on the wheat gene complement as a result of the presence of 7HL to be assessed. Some 42% (389/923) of the 7HL genes assayed were differentially transcribed, which was the case for only 3% (960/35 301) of the wheat gene complement. The absence of any transcript in the addition line of a suite of chromosome 7A genes implied the presence of a 36 Mbp deletion at the distal end of the 7AL arm; this deletion was found to be in common across the full set of Chinese Spring/Betzes barley addition lines. The remaining differentially transcribed wheat genes were distributed across the whole genome. The up-regulated barley genes were mostly located in the proximal part of the 7HL arm, while the down-regulated ones were concentrated in the distal part; as a result, genes encoding basal cellular functions tended to be transcribed, while those encoding specific functions were suppressed. An insight has been gained into gene transcription in an alien introgression line, thereby providing a basis for understanding the interactions between wheat and exotic genes in introgression materials.

Nitrogen Limitation Alters the Response of Specific Genes to Biotic Stress.

In their natural environment, plants are generally confronted with multiple co-occurring stresses. However, the interaction between stresses is not well known and transcriptomic data in response to combined stresses remain scarce. This study aims at characterizing the interaction between transcriptomic responses to biotic stress and nitrogen (N) limitation. Plants were grown in low or full N, infected or not with Erwinia amylovora (Ea) and plant gene expression was analyzed through microarray and qRT-PCR. Most Ea-responsive genes had the same profile (induced/repressed) in response to Ea in low and full N. In response to stress combination, one third of modulated transcripts responded in a manner that could not be deduced from their response to each individual stress. Many defense-related genes showed a prioritization of their response to biotic stress over their response to N limitation, which was also observed using Pseudomonas syringae as a second pathosystem. Our results indicate an interaction between transcriptomic responses to N and biotic stress. A small fraction of transcripts was prioritized between antagonistic responses, reflecting a preservation of the plant defense program under N limitation. Furthermore, this interaction also led to a complex and specific response in terms of metabolism and cellular homeostasis-associated genes.

GEM2Net: from gene expression modeling to -omics networks, a new CATdb module to investigate Arabidopsis thaliana genes involved in stress response.

CATdb (http://urgv.evry.inra.fr/CATdb) is a database providing a public access to a large collection of transcriptomic data, mainly for Arabidopsis but also for other plants. This resource has the rare advantage to contain several thousands of microarray experiments obtained with the same technical protocol and analyzed by the same statistical pipelines. In this paper, we present GEM2Net, a new module of CATdb that takes advantage of this homogeneous dataset to mine co-expression units and decipher Arabidopsis gene functions. GEM2Net explores 387 stress conditions organized into 18 biotic and abiotic stress categories. For each one, a model-based clustering is applied on expression differences to identify clusters of co-expressed genes. To characterize functions associated with these clusters, various resources are analyzed and integrated: Gene Ontology, subcellular localization of proteins, Hormone Families, Transcription Factor Families and a refined stress-related gene list associated to publications. Exploiting protein-protein interactions and transcription factors-targets interactions enables to display gene networks. GEM2Net presents the analysis of the 18 stress categories, in which 17,264 genes are involved and organized within 681 co-expression clusters. The meta-data analyses were stored and organized to compose a dynamic Web resource.

The RNA helicases AtMTR4 and HEN2 target specific subsets of nuclear transcripts for degradation by the nuclear exosome in Arabidopsis thaliana.

The RNA exosome is the major 3'-5' RNA degradation machine of eukaryotic cells and participates in processing, surveillance and turnover of both nuclear and cytoplasmic RNA. In both yeast and human, all nuclear functions of the exosome require the RNA helicase MTR4. We show that the Arabidopsis core exosome can associate with two related RNA helicases, AtMTR4 and HEN2. Reciprocal co-immunoprecipitation shows that each of the RNA helicases co-purifies with the exosome core complex and with distinct sets of specific proteins. While AtMTR4 is a predominantly nucleolar protein, HEN2 is located in the nucleoplasm and appears to be excluded from nucleoli. We have previously shown that the major role of AtMTR4 is the degradation of rRNA precursors and rRNA maturation by-products. Here, we demonstrate that HEN2 is involved in the degradation of a large number of polyadenylated nuclear exosome substrates such as snoRNA and miRNA precursors, incompletely spliced mRNAs, and spurious transcripts produced from pseudogenes and intergenic regions. Only a weak accumulation of these exosome substrate targets is observed in mtr4 mutants, suggesting that MTR4 can contribute, but plays rather a minor role for the degradation of non-ribosomal RNAs and cryptic transcripts in Arabidopsis. Consistently, transgene post-transcriptional gene silencing (PTGS) is marginally affected in mtr4 mutants, but increased in hen2 mutants, suggesting that it is mostly the nucleoplasmic exosome that degrades aberrant transgene RNAs to limit their entry in the PTGS pathway. Interestingly, HEN2 is conserved throughout green algae, mosses and land plants but absent from metazoans and other eukaryotic lineages. Our data indicate that, in contrast to human and yeast, plants have two functionally specialized RNA helicases that assist the exosome in the degradation of specific nucleolar and nucleoplasmic RNA populations, respectively.

Co-expression analysis of high-throughput transcriptome sequencing data with Poisson mixture models.

MOTIVATION: In recent years, gene expression studies have increasingly made use of high-throughput sequencing technology. In turn, research concerning the appropriate statistical methods for the analysis of digital gene expression (DGE) has flourished, primarily in the context of normalization and differential analysis. RESULTS: In this work, we focus on the question of clustering DGE profiles as a means to discover groups of co-expressed genes. We propose a Poisson mixture model using a rigorous framework for parameter estimation as well as the choice of the appropriate number of clusters. We illustrate co-expression analyses using our approach on two real RNA-seq datasets. A set of simulation studies also compares the performance of the proposed model with that of several related approaches developed to cluster RNA-seq or serial analysis of gene expression data. AVAILABILITY AND AND IMPLEMENTATION: The proposed method is implemented in the open-source R package HTSCluster, available on CRAN. CONTACT: andrea.rau@jouy.inra.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Integrative epigenomic mapping defines four main chromatin states in Arabidopsis.

Post-translational modification of histones and DNA methylation are important components of chromatin-level control of genome activity in eukaryotes. However, principles governing the combinatorial association of chromatin marks along the genome remain poorly understood. Here, we have generated epigenomic maps for eight histone modifications (H3K4me2 and 3, H3K27me1 and 2, H3K36me3, H3K56ac, H4K20me1 and H2Bub) in the model plant Arabidopsis and we have combined these maps with others, produced under identical conditions, for H3K9me2, H3K9me3, H3K27me3 and DNA methylation. Integrative analysis indicates that these 12 chromatin marks, which collectively cover ∼90% of the genome, are present at any given position in a very limited number of combinations. Moreover, we show that the distribution of the 12 marks along the genomic sequence defines four main chromatin states, which preferentially index active genes, repressed genes, silent repeat elements and intergenic regions. Given the compact nature of the Arabidopsis genome, these four indexing states typically translate into short chromatin domains interspersed with each other. This first combinatorial view of the Arabidopsis epigenome points to simple principles of organization as in metazoans and provides a framework for further studies of chromatin-based regulatory mechanisms in plants.

Mutations in the Arabidopsis homolog of LST8/GßL, a partner of the target of Rapamycin kinase, impair plant growth, flowering, and metabolic adaptation to long days.

The conserved Target of Rapamycin (TOR) kinase forms high molecular mass complexes and is a major regulator of cellular adaptations to environmental cues. The Lethal with Sec Thirteen 8/G protein ß subunit-like (LST8/GßL) protein is a member of the TOR complexes, and two putative LST8 genes are present in Arabidopsis thaliana, of which only one (LST8-1) is significantly expressed. The Arabidopsis LST8-1 protein is able to complement yeast lst8 mutations and interacts with the TOR kinase. Mutations in the LST8-1 gene resulted in reduced vegetative growth and apical dominance with abnormal development of flowers. Mutant plants were also highly sensitive to long days and accumulated, like TOR RNA interference lines, higher amounts of starch and amino acids, including proline and glutamine, while showing reduced concentrations of inositol and raffinose. Accordingly, transcriptomic and enzymatic analyses revealed a higher expression of genes involved in nitrate assimilation when lst8-1 mutants were shifted to long days. The transcriptome of lst8-1 mutants in long days was found to share similarities with that of a myo-inositol 1 phosphate synthase mutant that is also sensitive to the extension of the light period. It thus appears that the LST8-1 protein has an important role in regulating amino acid accumulation and the synthesis of myo-inositol and raffinose during plant adaptation to long days.