Pervasive G × E interactions shape adaptive trajectories and the exploration of the phenotypic space in artificial selection experiments.

Quantitative genetics models have shown that long-term selection responses depend on initial variance and mutational influx. Understanding limits of selection requires quantifying the role of mutational variance. However, correlative responses to selection on nonfocal traits can perturb the selection response on the focal trait; and generations are often confounded with selection environments so that genotype by environment (G×E) interactions are ignored. The Saclay divergent selection experiments (DSEs) on maize flowering time were used to track the fate of individual mutations combining genotyping data and phenotyping data from yearly measurements (DSEYM) and common garden experiments (DSECG) with four objectives: (1) to quantify the relative contribution of standing and mutational variance to the selection response, (2) to estimate genotypic mutation effects, (3) to study the impact of G×E interactions in the selection response, and (4) to analyze how trait correlations modulate the exploration of the phenotypic space. We validated experimentally the expected enrichment of fixed beneficial mutations with an average effect of +0.278 and +0.299 days to flowering, depending on the genetic background. Fixation of unfavorable mutations reached up to 25% of incoming mutations, a genetic load possibly due to antagonistic pleiotropy, whereby mutations fixed in the selection environment (DSEYM) turned to be unfavorable in the evaluation environment (DSECG). Global patterns of trait correlations were conserved across genetic backgrounds but exhibited temporal patterns. Traits weakly or uncorrelated with flowering time triggered stochastic exploration of the phenotypic space, owing to microenvironment-specific fixation of standing variants and pleiotropic mutational input.

A successive time-to-event model of phyllochron dynamics for hypothesis testing: application to the analysis of genetic and environmental effects in maize.

BACKGROUND: The time between the appearance of successive leaves, or phyllochron, characterizes the vegetative development of annual plants. Hypothesis testing models, which allow the comparison of phyllochrons between genetic groups and/or environmental conditions, are usually based on regression of thermal time on the number of leaves; most of the time a constant leaf appearance rate is assumed. However regression models ignore auto-correlation of the leaf number process and may lead to biased testing procedures. Moreover, the hypothesis of constant leaf appearance rate may be too restrictive. METHODS: We propose a stochastic process model in which emergence of new leaves is considered to result from successive time-to-events. This model provides a flexible and more accurate modeling as well as unbiased testing procedures. It was applied to an original maize dataset collected in the field over three years on plants originating from two divergent selection experiments for flowering time in two maize inbred lines. RESULTS AND CONCLUSION: We showed that the main differences in phyllochron were not observed between selection populations but rather between ancestral lines, years of experimentation and leaf ranks. Our results highlight a strong departure from the assumption of a constant leaf appearance rate over a season which could be related to climate variations, even if the impact of individual climate variables could not be clearly determined.

Natural variation at FLM splicing has pleiotropic effects modulating ecological strategies in Arabidopsis thaliana.

Investigating the evolution of complex phenotypes and the underlying molecular bases of their variation is critical to understand how organisms adapt to their environment. Applying classical quantitative genetics on a segregating population derived from a Can-0xCol-0 cross, we identify the MADS-box transcription factor FLOWERING LOCUS M (FLM) as a player of the phenotypic variation in plant growth and color. We show that allelic variation at FLM modulates plant growth strategy along the leaf economics spectrum, a trade-off between resource acquisition and resource conservation, observable across thousands of plant species. Functional differences at FLM rely on a single intronic substitution, disturbing transcript splicing and leading to the accumulation of non-functional FLM transcripts. Associations between this substitution and phenotypic and climatic data across Arabidopsis natural populations, show how noncoding genetic variation at a single gene might be adaptive through pleiotropic effects.

BiPOm: a rule-based ontology to represent and infer molecule knowledge from a biological process-centered viewpoint.

BACKGROUND: Managing and organizing biological knowledge remains a major challenge, due to the complexity of living systems. Recently, systemic representations have been promising in tackling such a challenge at the whole-cell scale. In such representations, the cell is considered as a system composed of interlocked subsystems. The need is now to define a relevant formalization of the systemic description of cellular processes. RESULTS: We introduce BiPOm (Biological interlocked Process Ontology for metabolism) an ontology to represent metabolic processes as interlocked subsystems using a limited number of classes and properties. We explicitly formalized the relations between the enzyme, its activity, the substrates and the products of the reaction, as well as the active state of all involved molecules. We further showed that the information of molecules such as molecular types or molecular properties can be deduced by automatic reasoning using logical rules. The information necessary to populate BiPOm can be extracted from existing databases or existing bio-ontologies. CONCLUSION: BiPOm provides a formal rule-based knowledge representation to relate all cellular components together by considering the cellular system as a whole. It relies on a paradigm shift where the anchorage of knowledge is rerouted from the molecule to the biological process. AVAILABILITY: BiPOm can be downloaded at https://github.com/SysBioInra/SysOnto.

The complex genetic architecture of shoot growth natural variation in Arabidopsis thaliana.

One of the main outcomes of quantitative genetics approaches to natural variation is to reveal the genetic architecture underlying the phenotypic space. Complex genetic architectures are described as including numerous loci (or alleles) with small-effect and/or low-frequency in the populations, interactions with the genetic background, environment or age. Linkage or association mapping strategies will be more or less sensitive to this complexity, so that we still have an unclear picture of its extent. By combining high-throughput phenotyping under two environmental conditions with classical QTL mapping approaches in multiple Arabidopsis thaliana segregating populations as well as advanced near isogenic lines construction and survey, we have attempted to improve our understanding of quantitative phenotypic variation. Integrative traits such as those related to vegetative growth used in this work (highlighting either cumulative growth, growth rate or morphology) all showed complex and dynamic genetic architecture with respect to the segregating population and condition. The more resolutive our mapping approach, the more complexity we uncover, with several instances of QTLs visible in near isogenic lines but not detected with the initial QTL mapping, indicating that our phenotyping accuracy was less limiting than the mapping resolution with respect to the underlying genetic architecture. In an ultimate approach to resolve this complexity, we intensified our phenotyping effort to target specifically a 3Mb-region known to segregate for a major quantitative trait gene, using a series of selected lines recombined every 100kb. We discovered that at least 3 other independent QTLs had remained hidden in this region, some with trait- or condition-specific effects, or opposite allelic effects. If we were to extrapolate the figures obtained on this specific region in this particular cross to the genome- and species-scale, we would predict hundreds of causative loci of detectable phenotypic effect controlling these growth-related phenotypes.

The Evolution of Calcium-Based Signalling in Plants.

The calcium-based intracellular signalling system is used ubiquitously to couple extracellular stimuli to their characteristic intracellular responses. It is becoming clear from genomic and physiological investigations that while the basic elements in the toolkit are common between plants and animals, evolution has acted in such a way that, in plants, some components have diversified with respect to their animal counterparts, while others have either been lost or have never evolved in the plant lineages. In comparison with animals, in plants there appears to have been a loss of diversity in calcium-influx mechanisms at the plasma membrane. However, the evolution of the calcium-storing vacuole may provide plants with additional possibilities for regulating calcium influx into the cytosol. Among the proteins that are involved in sensing and responding to increases in calcium, plants possess specific decoder proteins that are absent from the animal lineage. In seeking to understand the selection pressures that shaped the plant calcium-signalling toolkit, we consider the evolution of fast electrical signalling. We also note that, in contrast to animals, plants apparently do not make extensive use of cyclic-nucleotide-based signalling. It is possible that reliance on a single intracellular second-messenger-based system, coupled with the requirement to adapt to changing environmental conditions, has helped to define the diversity of components found in the extant plant calcium-signalling toolkit.

Evolution of the Calcium-Based Intracellular Signaling System.

To progress our understanding of molecular evolution from a collection of well-studied genes toward the level of the cell, we must consider whole systems. Here, we reveal the evolution of an important intracellular signaling system. The calcium-signaling toolkit is made up of different multidomain proteins that have undergone duplication, recombination, sequence divergence, and selection. The picture of evolution, considering the repertoire of proteins in the toolkit of both extant organisms and ancestors, is radically different from that of other systems. In eukaryotes, the repertoire increased in both abundance and diversity at a far greater rate than general genomic expansion. We describe how calcium-based intracellular signaling evolution differs not only in rate but in nature, and how this correlates with the disparity of plants and animals.

Involvement of two-component signalling systems in the regulation of stomatal aperture by light in Arabidopsis thaliana.

Two-component signalling (TCS) systems play important roles in cytokinin and ethylene signalling in Arabidopsis thaliana. Although the involvement of histidine kinases (AHKs) in drought stress responses has been described, their role and that of histidine phosphotransferases (AHPs) in guard cell signalling remain to be fully elucidated. Here, we investigated the roles of TCS genes, the histidine phosphotransferase AHP2 and the histidine kinases AHK2 and AHK3, previously reported to play roles in cytokinin and abscisic acid (ABA) signalling. We show that AHP2 is present in the nucleus and the cytoplasm, and is involved in light-induced opening. We also present evidence that there is some redistribution of AHP2 from the nucleus to the cytoplasm on addition of ABA. In addition, we provide data to support a role for the cytokinin receptors AHK2 and AHK3 in light-induced stomatal opening and, by inference, in controlling the stomatal sensitivity to ABA. Our results provide new insights into the operation of TCS in plants, cross-talk in stomatal signalling and, in particular, the process of light-induced stomatal opening.

Mapping the twin-arginine protein translocation network of Bacillus subtilis.

Bacteria employ twin-arginine translocation (Tat) pathways for the transport of folded proteins to extracytoplasmic destinations. In recent years, most studies on bacterial Tat pathways addressed the membrane-bound TatA(B)C subunits of the Tat translocase, and the specific interactions between this translocase and its substrate proteins. In contrast, relatively few studies investigated possible coactors in the TatA(B)C-dependent protein translocation process. The present studies were aimed at identifying interaction partners of the Tat pathway of Bacillus subtilis, which is a paradigm for studies on protein secretion by Gram-positive bacteria. Specifically, 36 interaction partners of the TatA and TatC subunits were identified by rigorous application of the yeast two-hybrid (Y2H) approach. Our Y2H analyses revealed that the three TatA isoforms of B. subtilis can form homo- and heterodimers. Subsequently, the secretion of the Tat substrates YwbN and PhoD was tested in mutant strains lacking genes for the TatAC interaction partners identified in our genome-wide Y2H screens. Our results show that the cell wall-bound protease WprA is important for YwbN secretion, and that the HemAT and CsbC proteins are required for PhoD secretion under phosphate starvation conditions. Taken together, our findings imply that the Bacillus Tat pathway is embedded in an intricate protein-protein interaction network.

Condition-dependent transcriptome reveals high-level regulatory architecture in Bacillus subtilis.

Bacteria adapt to environmental stimuli by adjusting their transcriptomes in a complex manner, the full potential of which has yet to be established for any individual bacterial species. Here, we report the transcriptomes of Bacillus subtilis exposed to a wide range of environmental and nutritional conditions that the organism might encounter in nature. We comprehensively mapped transcription units (TUs) and grouped 2935 promoters into regulons controlled by various RNA polymerase sigma factors, accounting for ~66% of the observed variance in transcriptional activity. This global classification of promoters and detailed description of TUs revealed that a large proportion of the detected antisense RNAs arose from potentially spurious transcription initiation by alternative sigma factors and from imperfect control of transcription termination.

An expanded protein-protein interaction network in Bacillus subtilis reveals a group of hubs: Exploration by an integrative approach.

We have generated a protein-protein interaction network in Bacillus subtilis focused on several essential cellular processes such as cell division, cell responses to various stresses, the bacterial cytoskeleton, DNA replication and chromosome maintenance by careful application of the yeast two-hybrid approach. This network, composed of 793 interactions linking 287 proteins with an average connectivity of five interactions per protein, represents a valuable resource for future functional analyses. A striking feature of the network is a group of highly connected hubs (GoH) linking many different cellular processes. Most of the proteins of the GoH have unknown functions and are associated to the membrane. By the integration of available knowledge, in particular of transcriptome data sets, the GoH was decomposed into subgroups of party hubs corresponding to protein complexes or regulatory pathways expressed under different conditions. At a global level, the GoH might function as a very robust group of date hubs having partially redundant functions to integrate information from the different cellular pathways. Our analyses also provide a rational way to study the highly redundant functions of the GoH by a genetic approach.