Corrigendum: Proximal hyperspectral imaging detects diurnal and drought-induced changes in maize physiology

[This corrects the article DOI: 10.3389/fpls.2021.640914.].

Monitoring of drought stress and transpiration rate using proximal thermal and hyperspectral imaging in an indoor automated plant phenotyping platform

BACKGROUND

Thermography is a popular tool to assess plant water-use behavior, as plant temperature is influenced by transpiration rate, and is commonly used in field experiments to detect plant water deficit. Its application in indoor automated phenotyping platforms is still limited and mainly focuses on differences in plant temperature between genotypes or treatments, instead of estimating stomatal conductance or transpiration rate. In this study, the transferability of commonly used thermography analysis protocols from the field to greenhouse phenotyping platforms was evaluated. In addition, the added value of combining thermal infrared (TIR) with hyperspectral imaging to monitor drought effects on plant transpiration rate (E) was evaluated.

RESULTS

The sensitivity of commonly used TIR indices to detect drought-induced and genotypic differences in water status was investigated in eight maize inbred lines in the automated phenotyping platform PHENOVISION. Indices that normalized plant temperature for vapor pressure deficit and/or air temperature at the time of imaging were most sensitive to drought and could detect genotypic differences in the plants' water-use behavior. However, these indices were not strongly correlated to stomatal conductance and E. The canopy temperature depression index, the crop water stress index and the simplified stomatal conductance index were more suitable to monitor these traits, and were consequently used to develop empirical E prediction models by combining them with hyperspectral indices and/or environmental variables. Different modeling strategies were evaluated, including single index-based, machine learning and mechanistic models. Model comparison showed that combining multiple TIR indices in a random forest model can improve E prediction accuracy, and that the contribution of the hyperspectral data is limited when multiple indices are used. However, the empirical models trained on one genotype were not transferable to all eight inbred lines.

CONCLUSION

Overall, this study demonstrates that existing TIR indices can be used to monitor drought stress and develop E prediction models in an indoor setup, as long as the indices normalize plant temperature for ambient air temperature or relative humidity.

Interspecies co-expression analysis of lateral root development using inducible systems in rice, Medicago, and Arabidopsis

Lateral roots are crucial for plant growth and development, making them an important target for research aiming to improve crop yields and food security. However, their endogenous ontogeny and, as it were, stochastic appearance challenge their study. Lateral Root Inducible Systems (LRIS) can be used to overcome these challenges by inducing lateral roots massively and synchronously. The combination of LRISs with transcriptomic approaches significantly advanced our insights in the molecular control of lateral root formation, in particular for Arabidopsis. Despite this success, LRISs have been underutilized for other plant species or for lateral root developmental stages later than the initiation. In this study, we developed and/or adapted LRISs in rice, Medicago, and Arabidopsis to perform RNA-sequencing during time courses that cover different developmental stages of lateral root formation and primordium development. As such, our study provides three extensive datasets of gene expression profiles during lateral root development in three different plant species. The three LRISs are highly effective but timing and spatial distribution of lateral root induction vary among the species. Detailed characterization of the stages in time and space in the respective species enabled an interspecies co-expression analysis to identify conserved players involved in lateral root development, as illustrated for the AUX/IAA and LBD gene families. Overall, our results provide a valuable resource to identify potentially conserved regulatory mechanisms in lateral root development, and as such will contribute to a better understanding of the complex regulatory network underlying lateral root development.

Predicting yield of individual field-grown rapeseed plants from rosette-stage leaf gene expression

In the plant sciences, results of laboratory studies often do not translate well to the field. To help close this lab-field gap, we developed a strategy for studying the wiring of plant traits directly in the field, based on molecular profiling and phenotyping of individual plants. Here, we use this single-plant omics strategy on winter-type Brassica napus (rapeseed). We investigate to what extent early and late phenotypes of field-grown rapeseed plants can be predicted from their autumnal leaf gene expression, and find that autumnal leaf gene expression not only has substantial predictive power for autumnal leaf phenotypes but also for final yield phenotypes in spring. Many of the top predictor genes are linked to developmental processes known to occur in autumn in winter-type B. napus accessions, such as the juvenile-to-adult and vegetative-to-reproductive phase transitions, indicating that the yield potential of winter-type B. napus is influenced by autumnal development. Our results show that single-plant omics can be used to identify genes and processes influencing crop yield in the field.

SMAP design: a multiplex PCR amplicon and gRNA design tool to screen for natural and CRISPR-induced genetic variation

Multiplex amplicon sequencing is a versatile method to identify genetic variation in natural or mutagenized populations through eco-tilling or multiplex CRISPR screens. Such genotyping screens require reliable and specific primer designs, combined with simultaneous gRNA design for CRISPR screens. Unfortunately, current tools are unable to combine multiplex gRNA and primer design in a high-throughput and easy-to-use manner with high design flexibility. Here, we report the development of a bioinformatics tool called SMAP design to overcome these limitations. We tested SMAP design on several plant and non-plant genomes and obtained designs for more than 80-90% of the target genes, depending on the genome and gene family. We validated the designs with Illumina multiplex amplicon sequencing and Sanger sequencing in Arabidopsis, soybean, and maize. We also used SMAP design to perform eco-tilling by tilling PCR amplicons across nine candidate genes putatively associated with haploid induction in Cichorium intybus. We screened 60 accessions of chicory and witloof and identified thirteen knockout haplotypes and their carriers. SMAP design is an easy-to-use command-line tool that generates highly specific gRNA and/or primer designs for any number of loci for CRISPR or natural variation screens and is compatible with other SMAP modules for seamless downstream analysis.

Spatial Regression Models for Field Trials: A Comparative Study and New Ideas

Naturally occurring variability within a study region harbors valuable information on relationships between biological variables. Yet, spatial patterns within these study areas, e.g., in field trials, violate the assumption of independence of observations, setting particular challenges in terms of hypothesis testing, parameter estimation, feature selection, and model evaluation. We evaluate a number of spatial regression methods in a simulation study, including more realistic spatial effects than employed so far. Based on our results, we recommend generalized least squares (GLS) estimation for experimental as well as for observational setups and demonstrate how it can be incorporated into popular regression models for high-dimensional data such as regularized least squares. This new method is available in the BioConductor R-package pengls. Inclusion of a spatial error structure improves parameter estimation and predictive model performance in low-dimensional settings and also improves feature selection in high-dimensional settings by reducing "red-shift": the preferential selection of features with spatial structure. In addition, we argue that the absence of spatial autocorrelation (SAC) in the model residuals should not be taken as a sign of a good fit, since it may result from overfitting the spatial trend. Finally, we confirm our findings in a case study on the prediction of winter wheat yield based on multispectral measurements.

ksrates: positioning whole-genome duplications relative to speciation events in KS distributions

SUMMARY

We present ksrates, a user-friendly command-line tool to position ancient whole-genome duplication events with respect to speciation events in a phylogeny by comparing paralog and ortholog KS distributions derived from genomic or transcriptomic sequences, while adjusting for substitution rate differences among the lineages involved.

AVAILABILITY AND IMPLEMENTATION

ksrates is implemented in Python 3 and as a Nextflow pipeline. The source code, Singularity and Docker containers, documentation and tutorial are available via https://github.com/VIB-PSB/ksrates.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Drought affects the rate and duration of organ growth but not inter-organ growth coordination

Drought at flowering and grain filling greatly reduces maize (Zea mays) yield. Climate change is causing earlier and longer-lasting periods of drought, which affect the growth of multiple maize organs throughout development. To study how long periods of water deficit impact the dynamic nature of growth, and to determine how these relate to reproductive drought, we employed a high-throughput phenotyping platform featuring precise irrigation, imaging systems, and image-based biomass estimations. Prolonged drought resulted in a reduction of growth rate of individual organs-though an extension of growth duration partially compensated for this-culminating in lower biomass and delayed flowering. However, long periods of drought did not affect the highly organized succession of maximal growth rates of the distinct organs, i.e. leaves, stems, and ears. Two drought treatments negatively affected distinct seed yield components: Prolonged drought mainly reduced the number of spikelets, and drought during the reproductive period increased the anthesis-silking interval. The identification of these divergent biomass and yield components, which were affected by the shift in duration and intensity of drought, will facilitate trait-specific breeding toward future climate-resilient crops.

Proximal Hyperspectral Imaging Detects Diurnal and Drought-Induced Changes in Maize Physiology

Hyperspectral imaging is a promising tool for non-destructive phenotyping of plant physiological traits, which has been transferred from remote to proximal sensing applications, and from manual laboratory setups to automated plant phenotyping platforms. Due to the higher resolution in proximal sensing, illumination variation and plant geometry result in increased non-biological variation in plant spectra that may mask subtle biological differences. Here, a better understanding of spectral measurements for proximal sensing and their application to study drought, developmental and diurnal responses was acquired in a drought case study of maize grown in a greenhouse phenotyping platform with a hyperspectral imaging setup. The use of brightness classification to reduce the illumination-induced non-biological variation is demonstrated, and allowed the detection of diurnal, developmental and early drought-induced changes in maize reflectance and physiology. Diurnal changes in transpiration rate and vapor pressure deficit were significantly correlated with red and red-edge reflectance. Drought-induced changes in effective quantum yield and water potential were accurately predicted using partial least squares regression and the newly developed Water Potential Index 2, respectively. The prediction accuracy of hyperspectral indices and partial least squares regression were similar, as long as a strong relationship between the physiological trait and reflectance was present. This demonstrates that current hyperspectral processing approaches can be used in automated plant phenotyping platforms to monitor physiological traits with a high temporal resolution.

Using single-plant-omics in the field to link maize genes to functions and phenotypes

Most of our current knowledge on plant molecular biology is based on experiments in controlled laboratory environments. However, translating this knowledge from the laboratory to the field is often not straightforward, in part because field growth conditions are very different from laboratory conditions. Here, we test a new experimental design to unravel the molecular wiring of plants and study gene-phenotype relationships directly in the field. We molecularly profiled a set of individual maize plants of the same inbred background grown in the same field and used the resulting data to predict the phenotypes of individual plants and the function of maize genes. We show that the field transcriptomes of individual plants contain as much information on maize gene function as traditional laboratory-generated transcriptomes of pooled plant samples subject to controlled perturbations. Moreover, we show that field-generated transcriptome and metabolome data can be used to quantitatively predict individual plant phenotypes. Our results show that profiling individual plants in the field is a promising experimental design that could help narrow the lab-field gap.

Vascular transcription factors guide plant epidermal responses to limiting phosphate conditions

Optimal plant growth is hampered by deficiency of the essential macronutrient phosphate in most soils. Plant roots can, however, increase their root hair density to efficiently forage the soil for this immobile nutrient. By generating and exploiting a high-resolution single-cell gene expression atlas of Arabidopsis roots, we show an enrichment of TARGET OF MONOPTEROS 5/LONESOME HIGHWAY (TMO5/LHW) target gene responses in root hair cells. The TMO5/LHW heterodimer triggers biosynthesis of mobile cytokinin in vascular cells and increases root hair density during low-phosphate conditions by modifying both the length and cell fate of epidermal cells. Moreover, root hair responses in phosphate-deprived conditions are TMO5- and cytokinin-dependent. Cytokinin signaling links root hair responses in the epidermis to perception of phosphate depletion in vascular cells.

Interspecific hybridization facilitates niche adaptation in beer yeast

Hybridization between species often leads to non-viable or infertile offspring, yet examples of evolutionarily successful interspecific hybrids have been reported in all kingdoms of life. However, many questions on the ecological circumstances and evolutionary aftermath of interspecific hybridization remain unanswered. In this study, we sequenced and phenotyped a large set of interspecific yeast hybrids isolated from brewing environments to uncover the influence of interspecific hybridization in yeast adaptation and domestication. Our analyses demonstrate that several hybrids between Saccharomyces species originated and diversified in industrial environments by combining key traits of each parental species. Furthermore, posthybridization evolution within each hybrid lineage reflects subspecialization and adaptation to specific beer styles, a process that was accompanied by extensive chimerization between subgenomes. Our results reveal how interspecific hybridization provides an important evolutionary route that allows swift adaptation to novel environments.

Endoreplication as a potential driver of cell wall modifications

Endoreplication represents a variant of the mitotic cell cycle during which cells replicate their DNA without mitosis and/or cytokinesis, resulting in an increase in the cells' ploidy level. This process is especially prominent in higher plants, where it has been correlated with cell differentiation, metabolic output and rapid cell growth. However, different reports argue against a ploidy-dependent contribution to cell growth. Here, we review accumulating data suggesting that endocycle onset might exert an effect on cell growth through transcriptional control of cell wall-modifying genes to drive cell wall changes required to accommodate turgor-driven rapid cell expansion, consistent with the idea that vacuolar expansion rather than a ploidy-driven increase in cellular volume represents the major force driving cell growth.

A Spatiotemporal DNA Endoploidy Map of the Arabidopsis Root Reveals Roles for the Endocycle in Root Development and Stress Adaptation

Somatic polyploidy caused by endoreplication is observed in arthropods, molluscs, and vertebrates but is especially prominent in higher plants, where it has been postulated to be essential for cell growth and fate maintenance. However, a comprehensive understanding of the physiological significance of plant endopolyploidy has remained elusive. Here, we modeled and experimentally verified a high-resolution DNA endoploidy map of the developing Arabidopsis thaliana root, revealing a remarkable spatiotemporal control of DNA endoploidy levels across tissues. Fitting of a simplified model to publicly available data sets profiling root gene expression under various environmental stress conditions suggested that this root endoploidy patterning may be stress-responsive. Furthermore, cellular and transcriptomic analyses revealed that inhibition of endoreplication onset alters the nuclear-to-cellular volume ratio and the expression of cell wall-modifying genes, in correlation with the appearance of cell structural changes. Our data indicate that endopolyploidy might serve to coordinate cell expansion with structural stability and that spatiotemporal endoreplication pattern changes may buffer for stress conditions, which may explain the widespread occurrence of the endocycle in plant species growing in extreme or variable environments.

Fern genomes elucidate land plant evolution and cyanobacterial symbioses

Ferns are the closest sister group to all seed plants, yet little is known about their genomes other than that they are generally colossal. Here, we report on the genomes of Azolla filiculoides and Salvinia cucullata (Salviniales) and present evidence for episodic whole-genome duplication in ferns-one at the base of 'core leptosporangiates' and one specific to Azolla. One fern-specific gene that we identified, recently shown to confer high insect resistance, seems to have been derived from bacteria through horizontal gene transfer. Azolla coexists in a unique symbiosis with N2-fixing cyanobacteria, and we demonstrate a clear pattern of cospeciation between the two partners. Furthermore, the Azolla genome lacks genes that are common to arbuscular mycorrhizal and root nodule symbioses, and we identify several putative transporter genes specific to Azolla-cyanobacterial symbiosis. These genomic resources will help in exploring the biotechnological potential of Azolla and address fundamental questions in the evolution of plant life.

The Apicomplexa-specific glucosamine-6-phosphate N-acetyltransferase gene family encodes a key enzyme for glycoconjugate synthesis with potential as therapeutic target

Apicomplexa form a phylum of obligate parasitic protozoa of great clinical and veterinary importance. These parasites synthesize glycoconjugates for their survival and infectivity, but the enzymatic steps required to generate the glycosylation precursors are not completely characterized. In particular, glucosamine-phosphate N-acetyltransferase (GNA1) activity, needed to produce the essential UDP-N-acetylglucosamine (UDP-GlcNAc) donor, has not been identified in any Apicomplexa. We scanned the genomes of Plasmodium falciparum and representatives from six additional main lineages of the phylum for proteins containing the Gcn5-related N-acetyltransferase (GNAT) domain. One family of GNAT-domain containing proteins, composed by a P. falciparum sequence and its six apicomplexan orthologs, rescued the growth of a yeast temperature-sensitive GNA1 mutant. Heterologous expression and in vitro assays confirmed the GNA1 enzymatic activity in all lineages. Sequence, phylogenetic and synteny analyses suggest an independent origin of the Apicomplexa-specific GNA1 family, parallel to the evolution of a different GNA1 family in other eukaryotes. The inability to disrupt an otherwise modifiable gene target suggests that the enzyme is essential for P. falciparum growth. The relevance of UDP-GlcNAc for parasite viability, together with the independent evolution and unique sequence features of Apicomplexa GNA1, highlights the potential of this enzyme as a selective therapeutic target against apicomplexans.

The reduction in maize leaf growth under mild drought affects the transition between cell division and cell expansion and cannot be restored by elevated gibberellic acid levels

Growth is characterized by the interplay between cell division and cell expansion, two processes that occur separated along the growth zone at the maize leaf. To gain further insight into the transition between cell division and cell expansion, conditions were investigated in which the position of this transition zone was positively or negatively affected. High levels of gibberellic acid (GA) in plants overexpressing the GA biosynthesis gene GA20-OXIDASE (GA20OX-1^OE ) shifted the transition zone more distally, whereas mild drought, which is associated with lowered GA biosynthesis, resulted in a more basal positioning. However, the increased levels of GA in the GA20OX-1^OE line were insufficient to convey tolerance to the mild drought treatment, indicating that another mechanism in addition to lowered GA levels is restricting growth during drought. Transcriptome analysis with high spatial resolution indicated that mild drought specifically induces a reprogramming of transcriptional regulation in the division zone. 'Leaf Growth Viewer' was developed as an online searchable tool containing the high-resolution data.

Reciprocally Retained Genes in the Angiosperm Lineage Show the Hallmarks of Dosage Balance Sensitivity

In several organisms, particular functional categories of genes, such as regulatory and complex-forming genes, are preferentially retained after whole-genome multiplications but rarely duplicate through small-scale duplication, a pattern referred to as reciprocal retention. This peculiar duplication behavior is hypothesized to stem from constraints on the dosage balance between the genes concerned and their interaction context. However, the evidence for a relationship between reciprocal retention and dosage balance sensitivity remains fragmentary. Here, we identified which gene families are most strongly reciprocally retained in the angiosperm lineage and studied their functional and evolutionary characteristics. Reciprocally retained gene families exhibit stronger sequence divergence constraints and lower rates of functional and expression divergence than other gene families, suggesting that dosage balance sensitivity is a general characteristic of reciprocally retained genes. Gene families functioning in regulatory and signaling processes are much more strongly represented at the top of the reciprocal retention ranking than those functioning in multiprotein complexes, suggesting that regulatory imbalances may lead to stronger fitness effects than classical stoichiometric protein complex imbalances. Finally, reciprocally retained duplicates are often subject to dosage balance constraints for prolonged evolutionary times, which may have repercussions for the ease with which genome multiplications can engender evolutionary innovation.

Evolutionary Context Improves Regulatory Network Predictions

A novel algorithm harnesses phylogenetic information and facilitates a better understanding of the evolutionary divergence of gene regulation between species.

The Origin of Floral Organ Identity Quartets

The origin of flowers has puzzled plant biologists ever since Darwin referred to their sudden appearance in the fossil record as an abominable mystery. Flowers are considered to be an assembly of protective, attractive, and reproductive male and female leaf-like organs. Their origin cannot be understood by a morphological comparison to gymnosperms, their closest relatives, which develop separate male or female cones. Despite these morphological differences, gymnosperms and angiosperms possess a similar genetic toolbox consisting of phylogenetically related MADS domain proteins. Using ancestral MADS domain protein reconstruction, we trace the evolution of organ identity quartets along the stem lineage of crown angiosperms. We provide evidence that current floral quartets specifying male organ identity, which consist of four types of subunits, evolved from ancestral complexes of two types of subunits through gene duplication and integration of SEPALLATA proteins just before the origin of flowering plants. Our results suggest that protein interaction changes underlying this compositional shift were the result of a gradual and reversible evolutionary trajectory. Modeling shows that such compositional changes may have facilitated the evolution of the perfect, bisexual flower.

Domestication and Divergence of Saccharomyces cerevisiae Beer Yeasts

Whereas domestication of livestock, pets, and crops is well documented, it is still unclear to what extent microbes associated with the production of food have also undergone human selection and where the plethora of industrial strains originates from. Here, we present the genomes and phenomes of 157 industrial Saccharomyces cerevisiae yeasts. Our analyses reveal that today’s industrial yeasts can be divided into five sublineages that are genetically and phenotypically separated from wild strains and originate from only a few ancestors through complex patterns of domestication and local divergence. Large-scale phenotyping and genome analysis further show strong industry-specific selection for stress tolerance, sugar utilization, and flavor production, while the sexual cycle and other phenotypes related to survival in nature show decay, particularly in beer yeasts. Together, these results shed light on the origins, evolutionary history, and phenotypic diversity of industrial yeasts and provide a resource for further selection of superior strains.

PaperClip

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We sequenced and phenotyped 157 S. cerevisiae yeasts

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Present-day industrial yeasts originate from only a few domesticated ancestors

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Beer yeasts show strong genetic and phenotypic hallmarks of domestication

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Domestication of industrial yeasts predates microbe discovery

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.

Combined Large-Scale Phenotyping and Transcriptomics in Maize Reveals a Robust Growth Regulatory Network

Leaves are vital organs for biomass and seed production because of their role in the generation of metabolic energy and organic compounds. A better understanding of the molecular networks underlying leaf development is crucial to sustain global requirements for food and renewable energy. Here, we combined transcriptome profiling of proliferative leaf tissue with in-depth phenotyping of the fourth leaf at later stages of development in 197 recombinant inbred lines of two different maize (Zea mays) populations. Previously, correlation analysis in a classical biparental mapping population identified 1,740 genes correlated with at least one of 14 traits. Here, we extended these results with data from a multiparent advanced generation intercross population. As expected, the phenotypic variability was found to be larger in the latter population than in the biparental population, although general conclusions on the correlations among the traits are comparable. Data integration from the two diverse populations allowed us to identify a set of 226 genes that are robustly associated with diverse leaf traits. This set of genes is enriched for transcriptional regulators and genes involved in protein synthesis and cell wall metabolism. In order to investigate the molecular network context of the candidate gene set, we integrated our data with publicly available functional genomics data and identified a growth regulatory network of 185 genes. Our results illustrate the power of combining in-depth phenotyping with transcriptomics in mapping populations to dissect the genetic control of complex traits and present a set of candidate genes for use in biomass improvement.

Gene Duplicability of Core Genes Is Highly Consistent across All Angiosperms

Gene duplication is an important mechanism for adding to genomic novelty. Hence, which genes undergo duplication and are preserved following duplication is an important question. It has been observed that gene duplicability, or the ability of genes to be retained following duplication, is a nonrandom process, with certain genes being more amenable to survive duplication events than others. Primarily, gene essentiality and the type of duplication (small-scale versus large-scale) have been shown in different species to influence the (long-term) survival of novel genes. However, an overarching view of "gene duplicability" is lacking, mainly due to the fact that previous studies usually focused on individual species and did not account for the influence of genomic context and the time of duplication. Here, we present a large-scale study in which we investigated duplicate retention for 9178 gene families shared between 37 flowering plant species, referred to as angiosperm core gene families. For most gene families, we observe a strikingly consistent pattern of gene duplicability across species, with gene families being either primarily single-copy or multicopy in all species. An intermediate class contains gene families that are often retained in duplicate for periods extending to tens of millions of years after whole-genome duplication, but ultimately appear to be largely restored to singleton status, suggesting that these genes may be dosage balance sensitive. The distinction between single-copy and multicopy gene families is reflected in their functional annotation, with single-copy genes being mainly involved in the maintenance of genome stability and organelle function and multicopy genes in signaling, transport, and metabolism. The intermediate class was overrepresented in regulatory genes, further suggesting that these represent putative dosage-balance-sensitive genes.

A Conserved Core of Programmed Cell Death Indicator Genes Discriminates Developmentally and Environmentally Induced Programmed Cell Death in Plants

A plethora of diverse programmed cell death (PCD) processes has been described in living organisms. In animals and plants, different forms of PCD play crucial roles in development, immunity, and responses to the environment. While the molecular control of some animal PCD forms such as apoptosis is known in great detail, we still know comparatively little about the regulation of the diverse types of plant PCD. In part, this deficiency in molecular understanding is caused by the lack of reliable reporters to detect PCD processes. Here, we addressed this issue by using a combination of bioinformatics approaches to identify commonly regulated genes during diverse plant PCD processes in Arabidopsis (Arabidopsis thaliana). Our results indicate that the transcriptional signatures of developmentally controlled cell death are largely distinct from the ones associated with environmentally induced cell death. Moreover, different cases of developmental PCD share a set of cell death-associated genes. Most of these genes are evolutionary conserved within the green plant lineage, arguing for an evolutionary conserved core machinery of developmental PCD. Based on this information, we established an array of specific promoter-reporter lines for developmental PCD in Arabidopsis. These PCD indicators represent a powerful resource that can be used in addition to established morphological and biochemical methods to detect and analyze PCD processes in vivo and in planta.

Correlation analysis of the transcriptome of growing leaves with mature leaf parameters in a maize RIL population

BACKGROUND

To sustain the global requirements for food and renewable resources, unraveling the molecular networks underlying plant growth is becoming pivotal. Although several approaches to identify genes and networks involved in final organ size have been proven successful, our understanding remains fragmentary.

RESULTS

Here, we assessed variation in 103 lines of the Zea mays B73xH99 RIL population for a set of final leaf size and whole shoot traits at the seedling stage, complemented with measurements capturing growth dynamics, and cellular measurements. Most traits correlated well with the size of the division zone, implying that the molecular basis of final leaf size is already defined in dividing cells of growing leaves. Therefore, we searched for association between the transcriptional variation in dividing cells of the growing leaf and final leaf size and seedling biomass, allowing us to identify genes and processes correlated with the specific traits. A number of these genes have a known function in leaf development. Additionally, we illustrated that two independent mechanisms contribute to final leaf size, maximal growth rate and the duration of growth.

CONCLUSIONS

Untangling complex traits such as leaf size by applying in-depth phenotyping allows us to define the relative contributions of the components and their mutual associations, facilitating dissection of the biological processes and regulatory networks underneath.

Tangled up in two: a burst of genome duplications at the end of the Cretaceous and the consequences for plant evolution

Genome sequencing has demonstrated that besides frequent small-scale duplications, large-scale duplication events such as whole genome duplications (WGDs) are found on many branches of the evolutionary tree of life. Especially in the plant lineage, there is evidence for recurrent WGDs, and the ancestor of all angiosperms was in fact most likely a polyploid species. The number of WGDs found in sequenced plant genomes allows us to investigate questions about the roles of WGDs that were hitherto impossible to address. An intriguing observation is that many plant WGDs seem associated with periods of increased environmental stress and/or fluctuations, a trend that is evident for both present-day polyploids and palaeopolyploids formed around the Cretaceous–Palaeogene (K–Pg) extinction at 66 Ma. Here, we revisit the WGDs in plants that mark the K–Pg boundary, and discuss some specific examples of biological innovations and/or diversifications that may be linked to these WGDs. We review evidence for the processes that could have contributed to increased polyploid establishment at the K–Pg boundary, and discuss the implications on subsequent plant evolution in the Cenozoic.

Analysis of 41 plant genomes supports a wave of successful genome duplications in association with the Cretaceous-Paleogene boundary

Ancient whole-genome duplications (WGDs), also referred to as paleopolyploidizations, have been reported in most evolutionary lineages. Their attributed role remains a major topic of discussion, ranging from an evolutionary dead end to a road toward evolutionary success, with evidence supporting both fates. Previously, based on dating WGDs in a limited number of plant species, we found a clustering of angiosperm paleopolyploidizations around the Cretaceous-Paleogene (K-Pg) extinction event about 66 million years ago. Here we revisit this finding, which has proven controversial, by combining genome sequence information for many more plant lineages and using more sophisticated analyses. We include 38 full genome sequences and three transcriptome assemblies in a Bayesian evolutionary analysis framework that incorporates uncorrelated relaxed clock methods and fossil uncertainty. In accordance with earlier findings, we demonstrate a strongly nonrandom pattern of genome duplications over time with many WGDs clustering around the K-Pg boundary. We interpret these results in the context of recent studies on invasive polyploid plant species, and suggest that polyploid establishment is promoted during times of environmental stress. We argue that considering the evolutionary potential of polyploids in light of the environmental and ecological conditions present around the time of polyploidization could mitigate the stark contrast in the proposed evolutionary fates of polyploids.

Modeling the evolution of molecular systems from a mechanistic perspective

Systems biology-inspired genotype-phenotype mapping models are increasingly being used to study the evolutionary properties of molecular biological systems, in particular the general emergent properties of evolving systems, such as modularity, robustness, and evolvability. However, the level of abstraction at which many of these models operate might not be sufficient to capture all relevant intricacies of biological evolution in sufficient detail. Here, we argue that in particular gene and genome duplications, both evolutionary mechanisms of potentially major importance for the evolution of molecular systems and of special relevance to plant evolution, are not adequately accounted for in most GPM modeling frameworks, and that more fine-grained mechanistic models may significantly advance understanding of how gen(om)e duplication impacts molecular systems evolution.

Predicting gene function from uncontrolled expression variation among individual wild-type Arabidopsis plants

Gene expression profiling studies are usually performed on pooled samples grown under tightly controlled experimental conditions to suppress variability among individuals and increase experimental reproducibility. In addition, to mask unwanted residual effects, the samples are often subjected to relatively harsh treatments that are unrealistic in a natural context. Here, we show that expression variations among individual wild-type Arabidopsis thaliana plants grown under the same macroscopic growth conditions contain as much information on the underlying gene network structure as expression profiles of pooled plant samples under controlled experimental perturbations. We advocate the use of subtle uncontrolled variations in gene expression between individuals to uncover functional links between genes and unravel regulatory influences. As a case study, we use this approach to identify ILL6 as a new regulatory component of the jasmonate response pathway.

Reconstruction of ancestral metabolic enzymes reveals molecular mechanisms underlying evolutionary innovation through gene duplication

Resurrection of ancient fungal maltase enzymes uncovers the molecular details of how repeated gene duplications allow the evolution of protein variants with different functions.

Gene duplications are believed to facilitate evolutionary innovation. However, the mechanisms shaping the fate of duplicated genes remain heavily debated because the molecular processes and evolutionary forces involved are difficult to reconstruct. Here, we study a large family of fungal glucosidase genes that underwent several duplication events. We reconstruct all key ancestral enzymes and show that the very first preduplication enzyme was primarily active on maltose-like substrates, with trace activity for isomaltose-like sugars. Structural analysis and activity measurements on resurrected and present-day enzymes suggest that both activities cannot be fully optimized in a single enzyme. However, gene duplications repeatedly spawned daughter genes in which mutations optimized either isomaltase or maltase activity. Interestingly, similar shifts in enzyme activity were reached multiple times via different evolutionary routes. Together, our results provide a detailed picture of the molecular mechanisms that drove divergence of these duplicated enzymes and show that whereas the classic models of dosage, sub-, and neofunctionalization are helpful to conceptualize the implications of gene duplication, the three mechanisms co-occur and intertwine.

Darwin's theory of evolution is one of gradual change, yet evolution sometimes takes remarkable leaps. Such evolutionary innovations are often linked to gene duplication through one of three basic scenarios: an extra copy can increase protein levels, different ancestral subfunctions can be split over the copies and evolve distinct regulation, or one of the duplicates can develop a novel function. Although there are numerous examples for all these trajectories, the underlying molecular mechanisms remain obscure, mostly because the preduplication genes and proteins no longer exist. Here, we study a family of fungal metabolic enzymes that hydrolyze disaccharides, and that all originated from the same ancestral gene through repeated duplications. By resurrecting the ancient genes and proteins using high-confidence predictions from many fungal genome sequences available, we show that the very first preduplication enzyme was promiscuous, preferring maltose-like substrates but also showing trace activity towards isomaltose-like sugars. After duplication, specific mutations near the active site of one copy optimized the minor activity at the expense of the major ancestral activity, while the other copy further specialized in maltose and lost the minor activity. Together, our results reveal how the three basic trajectories for gene duplicates cannot be separated easily, but instead intertwine into a complex evolutionary path that leads to innovation.

Expansive evolution of the trehalose-6-phosphate phosphatase gene family in Arabidopsis

Trehalose is a nonreducing sugar used as a reserve carbohydrate and stress protectant in a variety of organisms. While higher plants typically do not accumulate high levels of trehalose, they encode large families of putative trehalose biosynthesis genes. Trehalose biosynthesis in plants involves a two-step reaction in which trehalose-6-phosphate (T6P) is synthesized from UDP-glucose and glucose-6-phosphate (catalyzed by T6P synthase [TPS]), and subsequently dephosphorylated to produce the disaccharide trehalose (catalyzed by T6P phosphatase [TPP]). In Arabidopsis (Arabidopsis thaliana), 11 genes encode proteins with both TPS- and TPP-like domains but only one of these (AtTPS1) appears to be an active (TPS) enzyme. In addition, plants contain a large family of smaller proteins with a conserved TPP domain. Here, we present an in-depth analysis of the 10 TPP genes and gene products in Arabidopsis (TPPA-TPPJ). Collinearity analysis revealed that all of these genes originate from whole-genome duplication events. Heterologous expression in yeast (Saccharomyces cerevisiae) showed that all encode active TPP enzymes with an essential role for some conserved residues in the catalytic domain. These results suggest that the TPP genes function in the regulation of T6P levels, with T6P emerging as a novel key regulator of growth and development in higher plants. Extensive gene expression analyses using a complete set of promoter-β-glucuronidase/green fluorescent protein reporter lines further uncovered cell- and tissue-specific expression patterns, conferring spatiotemporal control of trehalose metabolism. Consistently, phenotypic characterization of knockdown and overexpression lines of a single TPP, AtTPPG, points to unique properties of individual TPPs in Arabidopsis, and underlines the intimate connection between trehalose metabolism and abscisic acid signaling.

Inference of genome duplications from age distributions revisited

Whole-genome duplications (WGDs), thought to facilitate evolutionary innovations and adaptations, have been uncovered in many phylogenetic lineages. WGDs are frequently inferred from duplicate age distributions, where they manifest themselves as peaks against a small-scale duplication background. However, the interpretation of duplicate age distributions is complicated by the use of K(S), the number of synonymous substitutions per synonymous site, as a proxy for the age of paralogs. Two particular concerns are the stochastic nature of synonymous substitutions leading to increasing uncertainty in K(S) with increasing age since duplication and K(S) saturation caused by the inability of evolutionary models to fully correct for the occurrence of multiple substitutions at the same site. K(S) stochasticity is expected to erode the signal of older WGDs, whereas K(S) saturation may lead to artificial peaks in the distribution. Here, we investigate the consequences of these effects on K(S)-based age distributions and WGD inference by simulating the evolution of duplicated sequences according to predefined real age distributions and re-estimating the corresponding K(S) distributions. We show that, although K(S) estimates can be used for WGD inference far beyond the commonly accepted K(S) threshold of 1, K(S) saturation effects can cause artificial peaks at higher ages. Moreover, K(S) stochasticity and saturation may lead to confounded peaks encompassing multiple WGD events and/or saturation artifacts. We argue that K(S) effects need to be properly accounted for when inferring WGDs from age distributions and that the failure to do so could lead to false inferences.

Gamma paleohexaploidy in the stem lineage of core eudicots: significance for MADS-box gene and species diversification

Comparative genome biology has unveiled the polyploid origin of all angiosperms and the role of recurrent polyploidization in the amplification of gene families and the structuring of genomes. Which species share certain ancient polyploidy events, and which do not, is ill defined because of the limited number of sequenced genomes and transcriptomes and their uneven phylogenetic distribution. Previously, it has been suggested that most, but probably not all, of the eudicots have shared an ancient hexaploidy event, referred to as the gamma triplication. In this study, detailed phylogenies of subfamilies of MADS-box genes suggest that the gamma triplication has occurred before the divergence of Gunnerales but after the divergence of Buxales and Trochodendrales. Large-scale phylogenetic and K(S)-based approaches on the inflorescence transcriptomes of Gunnera manicata (Gunnerales) and Pachysandra terminalis (Buxales) provide further support for this placement, enabling us to position the gamma triplication in the stem lineage of the core eudicots. This triplication likely initiated the functional diversification of key regulators of reproductive development in the core eudicots, comprising 75% of flowering plants. Although it is possible that the gamma event triggered early core eudicot diversification, our dating estimates suggest that the event occurred early in the stem lineage, well before the rapid speciation of the earliest core eudicot lineages. The evolutionary significance of this paleopolyploidy event may thus rather lie in establishing a species lineage that was resilient to extinction, but with the genomic potential for later diversification. We consider that the traits generated from this potential characterize extant core eudicots both chemically and morphologically.

Targeted interactomics reveals a complex core cell cycle machinery in Arabidopsis thaliana

A protein interactome focused towards cell proliferation was mapped comprising 857 interactions among 393 proteins, leading to many new insights in plant cell cycle regulation.

A comprehensive view on heterodimeric cyclin-dependent kinase (CDK)/cyclin complexes in plants is obtained, in relation with their regulators.

Over 100 new candidate cell cycle proteins were predicted.

The basic underlying mechanisms that govern the cell cycle are conserved among all eukaryotes. Peculiar for plants, however, is that their genome contains a collection of cell cycle regulatory genes that is intriguingly large (Vandepoele et al, 2002; Menges et al, 2005) compared to other eukaryotes. Arabidopsis thaliana (Arabidopsis) encodes 71 genes in five regulatory classes versus only 15 in yeast and 23 in human.

Despite the discovery of numerous cell cycle genes, little is known about the protein complex machinery that steers plant cell division. Therefore, we applied tandem affinity purification (TAP) approach coupled with mass spectrometry (MS) on Arabidopsis cell suspension cultures to isolate and analyze protein complexes involved in the cell cycle. This approach allowed us to successfully map a first draft of the basic cell cycle complex machinery of Arabidopsis, providing many new insights into plant cell division.

To map the interactome, we relied on a streamlined platform comprising generic Gateway-based vectors with high cloning flexibility, the fast generation of transgenic suspension cultures, TAP adapted for plant cells, and matrix-assisted laser desorption ionization (MALDI) tandem-MS for the identification of purified proteins (Van Leene et al, 2007, 2008Van Leene et al, 2007, 2008). Complexes for 102 cell cycle proteins were analyzed using this approach, leading to a non-redundant data set of 857 interactions among 393 proteins (Figure 1A). Two subspaces were identified in this data set, domain I1, containing interactions confirmed in at least two independent experimental repeats or in the reciprocal purification experiment, and domain I2 consisting of uniquely observed interactions.

Several observations underlined the quality of both domains. All tested reverse purifications found the original interaction, and 150 known or predicted interactions were confirmed, meaning that also a huge stack of new interactions was revealed. An in-depth computational analysis revealed enrichment for many cell cycle-related features among the proteins of the network (Figure 1B), and many protein pairs were coregulated at the transcriptional level (Figure 1C). Through integration of known cell cycle-related features, more than 100 new candidate cell cycle proteins were predicted (Figure 1D). Besides common qualities of both interactome domains, their real significance appeared through mutual differences exposing two subspaces in the cell cycle interactome: a central regulatory network of stable complexes that are repeatedly isolated and represent core regulatory units, and a peripheral network comprising transient interactions identified less frequently, which are involved in other aspects of the process, such as crosstalk between core complexes or connections with other pathways. To evaluate the biological relevance of the cell cycle interactome in plants, we validated interactions from both domains by a transient split-luciferase assay in Arabidopsis plants (Marion et al, 2008), further sustaining the hypothesis-generating power of the data set to understand plant growth.

With respect to insights into the cell cycle physiology, the interactome was subdivided according to the functional classes of the baits and core protein complexes were extracted, covering cyclin-dependent kinase (CDK)/cyclin core complexes together with their positive and negative regulation networks, DNA replication complexes, the anaphase-promoting complex, and spindle checkpoint complexes. The data imply that mitotic A- and B-type cyclins exclusively form heterodimeric complexes with the plant-specific B-type CDKs and not with CDKA;1, whereas D-type cyclins seem to associate with CDKA;1. Besides the extraction of complexes previously shown in other organisms, our data also suggested many new functional links; for example, the link coupling cell division with the regulation of transcript splicing. The association of negative regulators of CDK/cyclin complexes with transcription factors suggests that their role in reallocation is not solely targeted to CDK/cyclin complexes. New members of the Siamese-related inhibitory proteins were identified, and for the first time potential inhibitors of plant-specific mitotic B-type CDKs have been found in plants. New evidence that the E2F–DP–RBR network is not only active at G1-to-S, but also at the G2-to-M transition is provided and many complexes involved in DNA replication or repair were isolated. For the first time, a plant APC has been isolated biochemically, identifying three potential new plant-specific APC interactors, and finally, complexes involved in the spindle checkpoint were isolated mapping many new but specific interactions.

Finally, to get a general view on the complex machinery, modules of interacting cyclins and core cell cycle regulators were ranked along the cell cycle phases according to the transcript expression peak of the cyclins, showing an assorted set of CDK–cyclin complexes with high regulatory differentiation (Figure 4). Even within the same subfamily (e.g. cyclin A3, B1, B2, D3, and D4), cyclins differ not only in their functional time frame but also in the type and number of CDKs, inhibitors, and scaffolding proteins they bind, further indicating their functional diversification. According to our interaction data, at least 92 different variants of CDK–cyclin complexes are found in Arabidopsis.

In conclusion, these results reflect how several rounds of gene duplication (Sterck et al, 2007) led to the evolution of a large set of cyclin paralogs and a myriad of regulators, resulting in a significant jump in the complexity of the cell cycle machinery that could accommodate unique plant-specific features such as an indeterminate mode of postembryonic development. Through their extensive regulation and connection with a myriad of up- and downstream pathways, the core cell cycle complexes might offer the plant a flexible toolkit to fine-tune cell proliferation in response to an ever-changing environment.

Cell proliferation is the main driving force for plant growth. Although genome sequence analysis revealed a high number of cell cycle genes in plants, little is known about the molecular complexes steering cell division. In a targeted proteomics approach, we mapped the core complex machinery at the heart of the Arabidopsis thaliana cell cycle control. Besides a central regulatory network of core complexes, we distinguished a peripheral network that links the core machinery to up- and downstream pathways. Over 100 new candidate cell cycle proteins were predicted and an in-depth biological interpretation demonstrated the hypothesis-generating power of the interaction data. The data set provided a comprehensive view on heterodimeric cyclin-dependent kinase (CDK)–cyclin complexes in plants. For the first time, inhibitory proteins of plant-specific B-type CDKs were discovered and the anaphase-promoting complex was characterized and extended. Important conclusions were that mitotic A- and B-type cyclins form complexes with the plant-specific B-type CDKs and not with CDKA;1, and that D-type cyclins and S-phase-specific A-type cyclins seem to be associated exclusively with CDKA;1. Furthermore, we could show that plants have evolved a combinatorial toolkit consisting of at least 92 different CDK–cyclin complex variants, which strongly underscores the functional diversification among the large family of cyclins and reflects the pivotal role of cell cycle regulation in the developmental plasticity of plants.

PiNGO: a Cytoscape plugin to find candidate genes in biological networks

PiNGO is a tool to screen biological networks for candidate genes, i.e. genes predicted to be involved in a biological process of interest. The user can narrow the search to genes with particular known functions or exclude genes belonging to particular functional classes. PiNGO provides support for a wide range of organisms and Gene Ontology classification schemes, and it can easily be customized for other organisms and functional classifications. PiNGO is implemented as a plugin for Cytoscape, a popular network visualization platform.

AVAILABILITY

PiNGO is distributed as an open-source Java package under the GNU General Public License (http://www.gnu.org/), and can be downloaded via the Cytoscape plugin manager. A detailed user guide and tutorial are available on the PiNGO website (http://www.psb.ugent.be/esb/PiNGO.

Extracting expression modules from perturbational gene expression compendia

Background

Compendia of gene expression profiles under chemical and genetic perturbations constitute an invaluable resource from a systems biology perspective. However, the perturbational nature of such data imposes specific challenges on the computational methods used to analyze them. In particular, traditional clustering algorithms have difficulties in handling one of the prominent features of perturbational compendia, namely partial coexpression relationships between genes. Biclustering methods on the other hand are specifically designed to capture such partial coexpression patterns, but they show a variety of other drawbacks. For instance, some biclustering methods are less suited to identify overlapping biclusters, while others generate highly redundant biclusters. Also, none of the existing biclustering tools takes advantage of the staple of perturbational expression data analysis: the identification of differentially expressed genes.

Results

We introduce a novel method, called ENIGMA, that addresses some of these issues. ENIGMA leverages differential expression analysis results to extract expression modules from perturbational gene expression data. The core parameters of the ENIGMA clustering procedure are automatically optimized to reduce the redundancy between modules. In contrast to the biclusters produced by most other methods, ENIGMA modules may show internal substructure, i.e. subsets of genes with distinct but significantly related expression patterns. The grouping of these (often functionally) related patterns in one module greatly aids in the biological interpretation of the data. We show that ENIGMA outperforms other methods on artificial datasets, using a quality criterion that, unlike other criteria, can be used for algorithms that generate overlapping clusters and that can be modified to take redundancy between clusters into account. Finally, we apply ENIGMA to the Rosetta compendium of expression profiles for Saccharomyces cerevisiae and we analyze one pheromone response-related module in more detail, demonstrating the potential of ENIGMA to generate detailed predictions.

Conclusion

It is increasingly recognized that perturbational expression compendia are essential to identify the gene networks underlying cellular function, and efforts to build these for different organisms are currently underway. We show that ENIGMA constitutes a valuable addition to the repertoire of methods to analyze such data.

Validating module network learning algorithms using simulated data

Background

In recent years, several authors have used probabilistic graphical models to learn expression modules and their regulatory programs from gene expression data. Despite the demonstrated success of such algorithms in uncovering biologically relevant regulatory relations, further developments in the area are hampered by a lack of tools to compare the performance of alternative module network learning strategies. Here, we demonstrate the use of the synthetic data generator SynTReN for the purpose of testing and comparing module network learning algorithms. We introduce a software package for learning module networks, called LeMoNe, which incorporates a novel strategy for learning regulatory programs. Novelties include the use of a bottom-up Bayesian hierarchical clustering to construct the regulatory programs, and the use of a conditional entropy measure to assign regulators to the regulation program nodes. Using SynTReN data, we test the performance of LeMoNe in a completely controlled situation and assess the effect of the methodological changes we made with respect to an existing software package, namely Genomica. Additionally, we assess the effect of various parameters, such as the size of the data set and the amount of noise, on the inference performance.

Results

Overall, application of Genomica and LeMoNe to simulated data sets gave comparable results. However, LeMoNe offers some advantages, one of them being that the learning process is considerably faster for larger data sets. Additionally, we show that the location of the regulators in the LeMoNe regulation programs and their conditional entropy may be used to prioritize regulators for functional validation, and that the combination of the bottom-up clustering strategy with the conditional entropy-based assignment of regulators improves the handling of missing or hidden regulators.

Conclusion

We show that data simulators such as SynTReN are very well suited for the purpose of developing, testing and improving module network algorithms. We used SynTReN data to develop and test an alternative module network learning strategy, which is incorporated in the software package LeMoNe, and we provide evidence that this alternative strategy has several advantages with respect to existing methods.

The Arabidopsis thaliana homolog of yeast BRE1 has a function in cell cycle regulation during early leaf and root growth

Chromatin modification and transcriptional activation are novel roles for E3 ubiquitin ligase proteins that have been mainly associated with ubiquitin-dependent proteolysis. We identified HISTONE MONOUBIQUITINATION1 (HUB1) (and its homolog HUB2) in Arabidopsis thaliana as RING E3 ligase proteins with a function in organ growth. We show that HUB1 is a functional homolog of the human and yeast BRE1 proteins because it monoubiquitinated histone H2B in an in vitro assay. Hub knockdown mutants had pale leaf coloration, modified leaf shape, reduced rosette biomass, and inhibited primary root growth. One of the alleles had been designated previously as ang4-1. Kinematic analysis of leaf and root growth together with flow cytometry revealed defects in cell cycle activities. The hub1-1 (ang4-1) mutation increased cell cycle duration in young leaves and caused an early entry into the endocycles. Transcript profiling of shoot apical tissues of hub1-1 (ang4-1) indicated that key regulators of the G2-to-M transition were misexpressed. Based on the mutant characterization, we postulate that HUB1 mediates gene activation and cell cycle regulation probably through chromatin modifications.

The gain and loss of genes during 600 million years of vertebrate evolution

Phylogenetic analysis of gene gain and loss during vertebrate evolution provides evidence for the importance of early gene or genome duplication events in evolution of complex vertebrates.

Background

Gene duplication is assumed to have played a crucial role in the evolution of vertebrate organisms. Apart from a continuous mode of duplication, two or three whole genome duplication events have been proposed during the evolution of vertebrates, one or two at the dawn of vertebrate evolution, and an additional one in the fish lineage, not shared with land vertebrates. Here, we have studied gene gain and loss in seven different vertebrate genomes, spanning an evolutionary period of about 600 million years.

Results

We show that: first, the majority of duplicated genes in extant vertebrate genomes are ancient and were created at times that coincide with proposed whole genome duplication events; second, there exist significant differences in gene retention for different functional categories of genes between fishes and land vertebrates; third, there seems to be a considerable bias in gene retention of regulatory genes towards the mode of gene duplication (whole genome duplication events compared to smaller-scale events), which is in accordance with the so-called gene balance hypothesis; and fourth, that ancient duplicates that have survived for many hundreds of millions of years can still be lost.

Conclusion

Based on phylogenetic analyses, we show that both the mode of duplication and the functional class the duplicated genes belong to have been of major importance for the evolution of the vertebrates. In particular, we provide evidence that massive gene duplication (probably as a consequence of entire genome duplications) at the dawn of vertebrate evolution might have been particularly important for the evolution of complex vertebrates.

Nonrandom divergence of gene expression following gene and genome duplications in the flowering plant Arabidopsis thaliana

Analysis of expression data of duplicated genes in Arabidopsis thaliana shows that the mode of duplication, the time since duplication and the function of the duplicated genes play a role in the divergence of their expression.

Background

Genome analyses have revealed that gene duplication in plants is rampant. Furthermore, many of the duplicated genes seem to have been created through ancient genome-wide duplication events. Recently, we have shown that gene loss is strikingly different for large- and small-scale duplication events and highly biased towards the functional class to which a gene belongs. Here, we study the expression divergence of genes that were created during large- and small-scale gene duplication events by means of microarray data and investigate both the influence of the origin (mode of duplication) and the function of the duplicated genes on expression divergence.

Results

Duplicates that have been created by large-scale duplication events and that can still be found in duplicated segments have expression patterns that are more correlated than those that were created by small-scale duplications or those that no longer lie in duplicated segments. Moreover, the former tend to have highly redundant or overlapping expression patterns and are mostly expressed in the same tissues, while the latter show asymmetric divergence. In addition, a strong bias in divergence of gene expression was observed towards gene function and the biological process genes are involved in.

Conclusion

By using microarray expression data for Arabidopsis thaliana, we show that the mode of duplication, the function of the genes involved, and the time since duplication play important roles in the divergence of gene expression and, therefore, in the functional divergence of genes after duplication.

Genome duplication and the origin of angiosperms

Despite intensive research, little is known about the origin of the angiosperms and their rise to ecological dominance during the Early Cretaceous. Based on whole-genome analyses of Arabidopsis thaliana, there is compelling evidence that angiosperms underwent two whole-genome duplication events early during their evolutionary history. Recent studies have shown that these events were crucial for the creation of many important developmental and regulatory genes found in extant angiosperm genomes. Here, we argue that these ancient polyploidy events might have also had an important role in the origin and diversification of the angiosperms.

BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks

The Biological Networks Gene Ontology tool (BiNGO) is an open-source Java tool to determine which Gene Ontology (GO) terms are significantly overrepresented in a set of genes. BiNGO can be used either on a list of genes, pasted as text, or interactively on subgraphs of biological networks visualized in Cytoscape. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy, and takes advantage of Cytoscape's versatile visualization environment to produce an intuitive and customizable visual representation of the results.

Modeling gene and genome duplications in eukaryotes

Recent analysis of complete eukaryotic genome sequences has revealed that gene duplication has been rampant. Moreover, next to a continuous mode of gene duplication, in many eukaryotic organisms the complete genome has been duplicated in their evolutionary past. Such large-scale gene duplication events have been associated with important evolutionary transitions or major leaps in development and adaptive radiations of species. Here, we present an evolutionary model that simulates the duplication dynamics of genes, considering genome-wide duplication events and a continuous mode of gene duplication. Modeling the evolution of the different functional categories of genes assesses the importance of different duplication events for gene families involved in specific functions or processes. By applying our model to the Arabidopsis genome, for which there is compelling evidence for three whole-genome duplications, we show that gene loss is strikingly different for large-scale and small-scale duplication events and highly biased toward certain functional classes. We provide evidence that some categories of genes were almost exclusively expanded through large-scale gene duplication events. In particular, we show that the three whole-genome duplications in Arabidopsis have been directly responsible for >90% of the increase in transcription factors, signal transducers, and developmental genes in the last 350 million years. Our evolutionary model is widely applicable and can be used to evaluate different assumptions regarding small- or large-scale gene duplication events in eukaryotic genomes.