FamNet: A Framework to Identify Multiplied Modules Driving Pathway Expansion in Plants

Coordinated regulation of the entry and exit steps of aromatic amino acid biosynthesis supports the dual lignin pathway in grasses

Vascular plants direct large amounts of carbon to produce the aromatic amino acid phenylalanine to support the production of lignin and other phenylpropanoids. Uniquely, grasses, which include many major crops, can synthesize lignin and phenylpropanoids from both phenylalanine and tyrosine. However, how grasses regulate aromatic amino acid biosynthesis to feed this dual lignin pathway is unknown. Here we show, by stable-isotope labeling, that grasses produce tyrosine >10-times faster than Arabidopsis without compromising phenylalanine biosynthesis. Detailed in vitro enzyme characterization and combinatorial in planta expression uncovered that coordinated expression of specific enzyme isoforms at the entry and exit steps of the aromatic amino acid pathway enables grasses to maintain high production of both tyrosine and phenylalanine, the precursors of the dual lignin pathway. These findings highlight the complex regulation of plant aromatic amino acid biosynthesis and provide novel genetic tools to engineer the interface of primary and specialized metabolism in plants.

Emerging Roles of Receptor-like Protein Kinases in Plant Response to Abiotic Stresses

The productivity of plants is hindered by unfavorable conditions. To perceive stress signals and to transduce these signals to intracellular responses, plants rely on membrane-bound receptor-like kinases (RLKs). These play a pivotal role in signaling events governing growth, reproduction, hormone perception, and defense responses against biotic stresses; however, their involvement in abiotic stress responses is poorly documented. Plant RLKs harbor an N-terminal extracellular domain, a transmembrane domain, and a C-terminal intracellular kinase domain. The ectodomains of these RLKs are quite diverse, aiding their responses to various stimuli. We summarize here the sub-classes of RLKs based on their domain structure and discuss the available information on their specific role in abiotic stress adaptation. Furthermore, the current state of knowledge on RLKs and their significance in abiotic stress responses is highlighted in this review, shedding light on their role in influencing plant-environment interactions and opening up possibilities for novel approaches to engineer stress-tolerant crop varieties.

Toward kingdom-wide analyses of gene expression

Gene expression data for Archaeplastida are accumulating exponentially, with more than 300 000 RNA-sequencing (RNA-seq) experiments available for hundreds of species. The gene expression data stem from thousands of experiments that capture gene expression in various organs, tissues, cell types, (a)biotic perturbations, and genotypes. Advances in software tools make it possible to process all these data in a matter of weeks on modern office computers, giving us the possibility to study gene expression in a kingdom-wide manner for the first time. We discuss how the expression data can be accessed and processed and outline analyses that take advantage of cross-species analyses, allowing us to generate powerful and robust hypotheses about gene function and evolution.

Analyzing lignin biosynthesis pathways in rattan using improved co-expression networks of NACs and MYBs

BACKGROUND

The rattan is a valuable plant resource with multiple applications in tropical forests. Calamus simplicifolius and Daemonorops jenkinsiana are the two most representative rattan species, supplying over 95% of the raw materials for the rattan industry. Hence, the wood properties of both rattans have always attracted researchers' attention.

RESULTS

We re-annotated the genomes, obtained 81 RNA-Seq datasets, and developed an improved pipeline to increase the reliability of co-expression networks of both rattans. Based on the data and pipeline, co-expression relationships were detected in 11 NACs, 49 MYBs, and 86 lignin biosynthesis genes in C. simplicifolius and four NACs, 59 MYBs, and 76 lignin biosynthesis genes in D. jenkinsiana, respectively. Among these co-expression pairs, several genes had a close relationship to the development of wood properties. Additionally, we detected the enzyme gene on the lignin biosynthesis pathway was regulated by either NAC or MYB, while LACCASES was regulated by both NAC and MYB. For D. jenkinsiana, the lignin biosynthesis regulatory network was characterized by positive regulation, and MYB possible negatively regulate non-expressed lignin biosynthesis genes in stem tissues. For C. simplicifolius, NAC may positively regulate highly expressed genes and negatively regulate non-expressed lignin biosynthesis genes in stem tissues. Furthermore, we established core regulatory networks of NAC and MYB for both rattans.

CONCLUSIONS

This work improved the accuracy of rattan gene annotation by integrating an efficient co-expression network analysis pipeline, enhancing gene coverage and accuracy of the constructed network, and facilitating an understanding of co-expression relationships among NAC, MYB, and lignin biosynthesis genes in rattan and other plants.

PERKing up our understanding of the proline-rich extensin-like receptor kinases, a forgotten plant receptor kinase family

Proline-rich extensin-like receptor kinases (PERKs) are an important class of receptor-like kinases (RLKs) containing an extracellular proline-rich domain. While they are thought to be putative sensors of the cell wall integrity, there are very few reports on their biological functions in the plant, as compared with other RLKs. Several studies support a role for PERKs in plant growth and development, but their effect on the cell wall composition to regulate cell expansion is still lacking. Gene expression data suggest that they may intervene in response to environmental changes, in agreement with their subcellular localization. And there is growing evidence for PERKs as novel sensors of environmental stresses such as insects and viruses. However, little is known about their precise role in plant immunity and in the extracellular network of RLKs, as no PERK-interacting RLK or any coreceptor has been identified as yet. Similarly, their signaling activities and downstream signaling components are just beginning to be deciphered, including Ca²⁺ fluxes, reactive oxygen species accumulation and phosphorylation events. Here we outline emerging roles for PERKs as novel sensors of environmental stresses, and we discuss how to better understand this overlooked class of receptor kinases via several avenues of research.

Exploiting plant transcriptomic databases: Resources, tools, and approaches

There are now more than 300 000 RNA sequencing samples available, stemming from thousands of experiments capturing gene expression in organs, tissues, developmental stages, and experimental treatments for hundreds of plant species. The expression data have great value, as they can be re-analyzed by others to ask and answer questions that go beyond the aims of the study that generated the data. Because gene expression provides essential clues to where and when a gene is active, the data provide powerful tools for predicting gene function, and comparative analyses allow us to study plant evolution from a new perspective. This review describes how we can gain new knowledge from gene expression profiles, expression specificities, co-expression networks, differential gene expression, and experiment correlation. We also introduce and demonstrate databases that provide user-friendly access to these tools.

Universal gene co-expression network reveals receptor-like protein genes involved in broad-spectrum resistance in pepper (Capsicum annuum L.)

Receptor-like proteins (RLPs) on plant cells have been implicated in immune responses and developmental processes. Although hundreds of RLP genes have been identified in plants, only a few RLPs have been functionally characterized in a limited number of plant species. Here, we identified RLPs in the pepper (Capsicum annuum) genome and performed comparative transcriptomics coupled with the analysis of conserved gene co-expression networks (GCNs) to reveal the role of core RLP regulators in pepper-pathogen interactions. A total of 102 RNA-seq datasets of pepper plants infected with four pathogens were used to construct CaRLP-targeted GCNs (CaRLP-GCNs). Resistance-responsive CaRLP-GCNs were merged to construct a universal GCN. Fourteen hub CaRLPs, tightly connected with defense-related gene clusters, were identified in eight modules. Based on the CaRLP-GCNs, we evaluated whether hub CaRLPs in the universal GCN are involved in the biotic stress response. Of the nine hub CaRLPs tested by virus-induced gene silencing, three genes (CaRLP264, CaRLP277, and CaRLP351) showed defense suppression with less hypersensitive response-like cell death in race-specific and non-host resistance response to viruses and bacteria, respectively, and consistently enhanced susceptibility to Ralstonia solanacearum and/or Phytophthora capsici. These data suggest that key CaRLPs are involved in the defense response to multiple biotic stresses and can be used to engineer a plant with broad-spectrum resistance. Together, our data show that generating a universal GCN using comprehensive transcriptome datasets can provide important clues to uncover genes involved in various biological processes.

Cross-Kingdom Comparative Transcriptomics Reveals Conserved Genetic Modules in Response to Cadmium Stress

It is known that organisms have developed various mechanisms to cope with cadmium (Cd) stress, while we still lack a system-level understanding of the functional isomorphy among them. In the present study, a cross-kingdom comparison was conducted among Escherichia coli, Saccharomyces cerevisiae, and Chlamydomonas reinhardtii, through toxicological tests, comparative transcriptomics, as well as conventional functional genomics. An equivalent level of Cd stress was determined via inhibition tests. Through transcriptome comparison, the three organisms exhibited differential gene expression under the same Cd stress relative to the corresponding no-treatment control. Results from functional enrichment analysis of differentially expressed genes (DEGs) showed that four metabolic pathways responsible for combating Cd stress were commonly regulated in the three organisms, including antioxidant reactions, sulfur metabolism, cell wall remodeling, and metal transport. In vivo expression patterns of 43 DEGs from the four pathways were further examined using quantitative PCR and resulted in a relatively comparable dynamic of gene expression patterns with transcriptome sequencing (RNA-seq). Cross-kingdom comparison of typical Cd stress-responding proteins resulted in the detection of 12 groups of homologous proteins in the three species. A class of potential metal transporters were subjected to cross-transformation to test their functional complementation. An ABC transporter gene in E. coli, possibly homologous to the yeast ycf1, was heterologously expressed in S. cerevisiae, resulting in enhanced Cd tolerance. Overall, our findings indicated that conserved genetic modules against Cd toxicity were commonly regulated among distantly related microbial species, which will be helpful for utilizing them in modifying microbial traits for bioremediation.

IMPORTANCE Research is establishing a systems biology view of biological response to Cd stress. It is meaningful to explore whether there is regulatory isomorphy among distantly related organisms. A transcriptomic comparison was done among model microbes, leading to the identification of a conserved cellular model pinpointing the generic strategies utilized by microbes for combating Cd stress. A novel E. coli transporter gene substantially increased yeast’s Cd tolerance. Knowledge on systems understanding of the cellular response to metals provides the basis for developing bioengineering remediation technology.

PERK13 modulates phosphate deficiency-induced root hair elongation in Arabidopsis

Phosphate starvation (-Pi)-induced root hair is crucial for enhancing plants' Pi absorption. Proline-rich extensin-like receptor kinase 13 (PERK13) is transcriptionally induced by -Pi and co-expressed with genes associated with root hair growth. However, how PERK13 participates in -Pi-induced root hair growth remains unclear. Here, we found that PERK13 was transcriptionally responsive to Pi, nitrogen, and iron deficiencies. Loss of PERK13 function (perk13) enhanced root hair growth under Pi/nitrogen limitation. Similar phenotype was also observed in transgenic lines overexpressing PERK13 (PERK13ox). Under -Pi, both perk13 and PERK13ox showed prolonged root hair elongation and increased reactive oxygen species (ROS). Deletion analysis showed, in PERK13ox, the extracellular domain was indispensable for PERK13 in -Pi-induced root hair growth. Different transcription profiles were observed under -Pi between perk13 and PERK13ox with the jasmonate zim-domain genes being repressed in perk13 and genes involved in cell wall remodeling being increased in PERK13ox. Taken together, we demonstrated that PERK13 participates in -Pi-induced root hair growth probably via regulating root hair elongation and the generation of ROS. Our study also suggested PERK13 probably being a vital hub coupling the environmental cues and root hair growth, and might play dual roles in -Pi-induced root hair growth via different processes.

A G protein-coupled receptor-like module regulates cellulose synthase secretion from the endomembrane system in Arabidopsis

Cellulose is produced at the plasma membrane of plant cells by cellulose synthase (CESA) complexes (CSCs). CSCs are assembled in the endomembrane system and then trafficked to the plasma membrane. Because CESAs are only active in the plasma membrane, control of CSC secretion regulates cellulose synthesis. We identified members of a family of seven transmembrane domain-containing proteins (7TMs) that are important for cellulose production during cell wall integrity stress. 7TMs are often associated with guanine nucleotide-binding (G) protein signaling and we found that mutants affecting the Gβγ dimer phenocopied the 7tm mutants. Unexpectedly, the 7TMs localized to the Golgi/trans-Golgi network where they interacted with G protein components. Here, the 7TMs and Gβγ regulated CESA trafficking but did not affect general protein secretion. Our results outline how a G protein-coupled module regulates CESA trafficking and reveal that defects in this process lead to exacerbated responses to cell wall integrity stress.

Reference gene identification for gene expression analysis in rice under different metal stress

Real-time quantitative polymerase chain reaction (RT-qPCR) is the most common approach to quantify changes in gene expression. Appropriate internal reference genes are essential for normalization of data of RT-qPCR. In the present study, we identified suitable reference genes for analysis of gene expression in rice seedlings subjected to different heavy metal stresses such as deficiencies of iron and zinc and toxicities of cobalt, cadmium and nickel. First, from publically available RNA-Seq data we identified 10 candidate genes having stable expression. We also included commonly used house-keeping gene OsUBQ5 (Ubiquitin 5) in our analysis. Expression stability of all the 11 genes was determined by two independent tools, NormFinder and geNorm. Our results show that selected candidate reference genes have higher stability in their expression compared to that of OsUBQ5. Genes with locus ID LOC_Os03g16690, encoding an oxysterol-binding protein (OsOBP) and LOC_Os01g56580, encoding Casein Kinase_1a.3 (OsCK1a.3) were identified to be the most stably expressed reference genes under most of the conditions tested. Finally, the study reveals that it is better to use a specific reference gene for a specific heavy metal stress condition rather than using a common reference gene for multiple heavy metal stress conditions. The reference genes identified here would be very useful for gene expression studies under heavy metal stresses in rice.

Using Gene Expression to Study Specialized Metabolism-A Practical Guide

Plants produce a vast array of chemical compounds that we use as medicines and flavors, but these compounds' biosynthetic pathways are still poorly understood. This paucity precludes us from modifying, improving, and mass-producing these specialized metabolites in suitable bioreactors. Many of the specialized metabolites are expressed in a narrow range of organs, tissues, and cell types, suggesting a tight regulation of the responsible biosynthetic pathways. Fortunately, with unprecedented ease of generating gene expression data and with >200,000 publicly available RNA sequencing samples, we are now able to study the expression of genes from hundreds of plant species. This review demonstrates how gene expression can elucidate the biosynthetic pathways by mining organ-specific genes, gene expression clusters, and applying various types of co-expression analyses. To empower biologists to perform these analyses, we showcase these analyses using recently published, user-friendly tools. Finally, we analyze the performance of co-expression networks and show that they are a valuable addition to elucidating multiple the biosynthetic pathways of specialized metabolism.

Fungi.guru: Comparative genomic and transcriptomic resource for the fungi kingdom

The fungi kingdom is composed of eukaryotic heterotrophs, which are responsible for balancing the ecosystem and play a major role as decomposers. They also produce a vast diversity of secondary metabolites, which have antibiotic or pharmacological properties. However, our lack of knowledge of gene function in fungi precludes us from tailoring them to our needs and tapping into their metabolic diversity. To help remedy this, we gathered genomic and gene expression data of 19 most widely-researched fungi to build an online tool, fungi.guru, which contains tools for cross-species identification of conserved pathways, functional gene modules, and gene families. We exemplify how our tool can elucidate the molecular function, biological process and cellular component of genes involved in various biological processes, by identifying a secondary metabolite pathway producing gliotoxin in Aspergillus fumigatus, the catabolic pathway of cellulose in Coprinopsis cinerea and the conserved DNA replication pathway in Fusarium graminearum and Pyricularia oryzae. The tool is available at www.fungi.guru.

LSTrAP-Crowd: prediction of novel components of bacterial ribosomes with crowd-sourced analysis of RNA sequencing data

BACKGROUND

Bacterial resistance to antibiotics is a growing health problem that is projected to cause more deaths than cancer by 2050. Consequently, novel antibiotics are urgently needed. Since more than half of the available antibiotics target the structurally conserved bacterial ribosomes, factors involved in protein synthesis are thus prime targets for the development of novel antibiotics. However, experimental identification of these potential antibiotic target proteins can be labor-intensive and challenging, as these proteins are likely to be poorly characterized and specific to few bacteria. Here, we use a bioinformatics approach to identify novel components of protein synthesis.

RESULTS

In order to identify these novel proteins, we established a Large-Scale Transcriptomic Analysis Pipeline in Crowd (LSTrAP-Crowd), where 285 individuals processed 26 terabytes of RNA-sequencing data of the 17 most notorious bacterial pathogens. In total, the crowd processed 26,269 RNA-seq experiments and used the data to construct gene co-expression networks, which were used to identify more than a hundred uncharacterized genes that were transcriptionally associated with protein synthesis. We provide the identity of these genes together with the processed gene expression data.

CONCLUSIONS

We identified genes related to protein synthesis in common bacterial pathogens and thus provide a resource of potential antibiotic development targets for experimental validation. The data can be used to explore additional vulnerabilities of bacteria, while our approach demonstrates how the processing of gene expression data can be easily crowd-sourced.

Characterization of In Vivo Function(s) of Members of the Plant Mitochondrial Carrier Family

Although structurally related, mitochondrial carrier family (MCF) proteins catalyze the specific transport of a range of diverse substrates including nucleotides, amino acids, dicarboxylates, tricarboxylates, cofactors, vitamins, phosphate and H⁺. Despite their name, they do not, however, always localize to the mitochondria, with plasma membrane, peroxisomal, chloroplast and thylakoid and endoplasmic reticulum localizations also being reported. The existence of plastid-specific MCF proteins is suggestive that the evolution of these proteins occurred after the separation of the green lineage. That said, plant-specific MCF proteins are not all plastid-localized, with members also situated at the endoplasmic reticulum and plasma membrane. While by no means yet comprehensive, the in vivo function of a wide range of these transporters is carried out here, and we discuss the employment of genetic variants of the MCF as a means to provide insight into their in vivo function complementary to that obtained from studies following their reconstitution into liposomes.

Genomics of Evolutionary Novelty in Hybrids and Polyploids

It has long been recognized that hybridization and polyploidy are prominent processes in plant evolution. Although classically recognized as significant in speciation and adaptation, recognition of the importance of interspecific gene flow has dramatically increased during the genomics era, concomitant with an unending flood of empirical examples, with or without genome doubling. Interspecific gene flow is thus increasingly thought to lead to evolutionary innovation and diversification, via adaptive introgression, homoploid hybrid speciation and allopolyploid speciation. Less well understood, however, are the suite of genetic and genomic mechanisms set in motion by the merger of differentiated genomes, and the temporal scale over which recombinational complexity mediated by gene flow might be expressed and exposed to natural selection. We focus on these issues here, considering the types of molecular genetic and genomic processes that might be set in motion by the saltational event of genome merger between two diverged species, either with or without genome doubling, and how these various processes can contribute to novel phenotypes. Genetic mechanisms include the infusion of new alleles and the genesis of novel structural variation including translocations and inversions, homoeologous exchanges, transposable element mobilization and novel insertional effects, presence-absence variation and copy number variation. Polyploidy generates massive transcriptomic and regulatory alteration, presumably set in motion by disrupted stoichiometries of regulatory factors, small RNAs and other genome interactions that cascade from single-gene expression change up through entire networks of transformed regulatory modules. We highlight both these novel combinatorial possibilities and the range of temporal scales over which such complexity might be generated, and thus exposed to natural selection and drift.

Metabolic Roles of Plant Mitochondrial Carriers

Mitochondrial carriers (MC) are a large family (MCF) of inner membrane transporters displaying diverse, yet often redundant, substrate specificities, as well as differing spatio-temporal patterns of expression; there are even increasing examples of non-mitochondrial subcellular localization. The number of these six trans-membrane domain proteins in sequenced plant genomes ranges from 39 to 141, rendering the size of plant families larger than that found in Saccharomyces cerevisiae and comparable with Homo sapiens. Indeed, comparison of plant MCs with those from these better characterized species has been highly informative. Here, we review the most recent comprehensive studies of plant MCFs, incorporating the torrent of genomic data emanating from next-generation sequencing techniques. As such we present a more current prediction of the substrate specificities of these carriers as well as review the continuing quest to biochemically characterize this feature of the carriers. Taken together, these data provide an important resource to guide direct genetic studies aimed at addressing the relevance of these vital carrier proteins.

Exploiting Natural Variation in Tomato to Define Pathway Structure and Metabolic Regulation of Fruit Polyphenolics in the Lycopersicum Complex

While the structures of plant primary metabolic pathways are generally well defined and highly conserved across species, those defining specialized metabolism are less well characterized and more highly variable across species. In this study, we investigated polyphenolic metabolism in the lycopersicum complex by characterizing the underlying biosynthetic and decorative reactions that constitute the metabolic network of polyphenols across eight different species of tomato. For this purpose, GC-MS- and LC-MS-based metabolomics of different tissues of Solanum lycopersicum and wild tomato species were carried out, in concert with the evaluation of cross-hybridized microarray data for MapMan-based transcriptomic analysis, and publicly available RNA-sequencing data for annotation of biosynthetic genes. The combined data were used to compile species-specific metabolic networks of polyphenolic metabolism, allowing the establishment of an entire pan-species biosynthetic framework as well as annotation of the functions of decoration enzymes involved in the formation of metabolic diversity of the flavonoid pathway. The combined results are discussed in the context of the current understanding of tomato flavonol biosynthesis as well as a global view of metabolic shifts during fruit ripening. Our results provide an example as to how large-scale biology approaches can be used for the definition and refinement of large specialized metabolism pathways.

Computational approaches to unravel the pathways and evolution of specialized metabolism

Specialized metabolites serve as a chemical arsenal that protects plants from abiotic stress, pathogens, and herbivores, and they are an essential component of our nutrition and medicine. Despite their importance, we are still at the beginning of unravelling biosynthetic pathways that produce these compounds, which is needed to produce more resilient and nutritious crops, expand our inventory of useful biomolecules, and give valuable insights into plant evolution. This review focuses on the evolution of specialized metabolism in the plant kingdom and the state-of-the-art approaches used to identify the biosynthetic pathways of these useful compounds.

Cross-Species Comparison of Fruit-Metabolomics to Elucidate Metabolic Regulation of Fruit Polyphenolics Among Solanaceous Crops

Many solanaceous crops are an important part of the human daily diet. Fruit polyphenolics are plant specialized metabolites that are recognized for their human health benefits and their defensive role against plant abiotic and biotic stressors. Flavonoids and chlorogenates are the major polyphenolic compounds found in solanaceous fruits that vary in quantity, physiological function, and structural diversity among and within plant species. Despite their biological significance, the elucidation of metabolic shifts of polyphenols during fruit ripening in different fruit tissues, has not yet been well-characterized in solanaceous crops, especially at a cross-species and cross-cultivar level. Here, we performed a cross-species comparison of fruit-metabolomics to elucidate the metabolic regulation of fruit polyphenolics from three representative crops of Solanaceae (tomato, eggplant, and pepper), and a cross-cultivar comparison among different pepper cultivars (Capsicum annuum cv.) using liquid chromatography-mass spectrometry (LC-MS). We observed a metabolic trade-off between hydroxycinnamates and flavonoids in pungent pepper and anthocyanin-type pepper cultivars and identified metabolic signatures of fruit polyphenolics in each species from each different tissue-type and fruit ripening stage. Our results provide additional information for metabolomics-assisted crop improvement of solanaceous fruits towards their improved nutritive properties and enhanced stress tolerance.

LSTrAP-Cloud: A User-Friendly Cloud Computing Pipeline to Infer Coexpression Networks

As genomes become more and more available, gene function prediction presents itself as one of the major hurdles in our quest to extract meaningful information on the biological processes genes participate in. In order to facilitate gene function prediction, we show how our user-friendly pipeline, the Large-Scale Transcriptomic Analysis Pipeline in Cloud (LSTrAP-Cloud), can be useful in helping biologists make a shortlist of genes involved in a biological process that they might be interested in, by using a single gene of interest as bait. The LSTrAP-Cloud is based on Google Colaboratory, and provides user-friendly tools that process quality-control RNA sequencing data streamed from the European Nucleotide Archive. The LSTRAP-Cloud outputs a gene coexpression network that can be used to identify functionally related genes for any organism with a sequenced genome and publicly available RNA sequencing data. Here, we used the biosynthesis pathway of Nicotiana tabacum as a case study to demonstrate how enzymes, transporters, and transcription factors involved in the synthesis, transport, and regulation of nicotine can be identified using our pipeline.

Expression Atlas of Selaginella moellendorffii Provides Insights into the Evolution of Vasculature, Secondary Metabolism, and Roots

Selaginella moellendorffii is a representative of the lycophyte lineage that is studied to understand the evolution of land plant traits such as the vasculature, leaves, stems, roots, and secondary metabolism. However, only a few studies have investigated the expression and transcriptional coordination of Selaginella genes, precluding us from understanding the evolution of the transcriptional programs behind these traits. We present a gene expression atlas comprising all major organs, tissue types, and the diurnal gene expression profiles for S. moellendorffii We show that the transcriptional gene module responsible for the biosynthesis of lignocellulose evolved in the ancestor of vascular plants and pinpoint the duplication and subfunctionalization events that generated multiple gene modules involved in the biosynthesis of various cell wall types. We demonstrate how secondary metabolism is transcriptionally coordinated and integrated with other cellular pathways. Finally, we identify root-specific genes and show that the evolution of roots did not coincide with an increased appearance of gene families, suggesting that the development of new organs does not coincide with increased fixation of new gene functions. Our updated database at conekt.plant.tools represents a valuable resource for studying the evolution of genes, gene families, transcriptomes, and functional gene modules in the Archaeplastida kingdom.

The evolution of metabolism: How to test evolutionary hypotheses at the genomic level

The origin of primordial metabolism and its expansion to form the metabolic networks extant today represent excellent systems to study the impact of natural selection and the potential adaptive role of novel compounds. Here we present the current hypotheses made on the origin of life and ancestral metabolism and present the theories and mechanisms by which the large chemical diversity of plants might have emerged along evolution. In particular, we provide a survey of statistical methods that can be used to detect signatures of selection at the gene and population level, and discuss potential and limits of these methods for investigating patterns of molecular adaptation in plant metabolism.

Gene expression analysis of Cyanophora paradoxa reveals conserved abiotic stress responses between basal algae and flowering plants

The glaucophyte Cyanophora paradoxa represents the most basal member of the kingdom Archaeplastida, but the function and expression of most of its genes are unknown. This information is needed to uncover how functional gene modules, that is groups of genes performing a given function, evolved in the plant kingdom. We have generated a gene expression atlas capturing responses of Cyanophora to various abiotic stresses. The data were included in the CoNekT-Plants database, enabling comparative transcriptomic analyses across two algae and six land plants. We demonstrate how the database can be used to study gene expression, co-expression networks and gene function in Cyanophora, and how conserved transcriptional programs can be identified. We identified gene modules involved in phycobilisome biosynthesis, response to high light and cell division. While we observed no correlation between the number of differentially expressed genes and the impact on growth of Cyanophora, we found that the response to stress involves a conserved, kingdom-wide transcriptional reprogramming, which is activated upon most stresses in algae and land plants. The Cyanophora stress gene expression atlas and the tools found in the https://conekt.plant.tools/ database thus provide a useful resource to reveal functionally related genes and stress responses in the plant kingdom.

Diurnal.plant.tools: Comparative Transcriptomic and Co-expression Analyses of Diurnal Gene Expression of the Archaeplastida Kingdom

Almost all organisms coordinate some aspects of their biology through the diurnal cycle. Photosynthetic organisms, and plants especially, have established complex programs that coordinate physiological, metabolic and developmental processes with the changing light. The diurnal regulation of the underlying transcriptional processes is observed when groups of functionally related genes (gene modules) are expressed at a specific time of the day. However, studying the diurnal regulation of these gene modules in the plant kingdom was hampered by the large amount of data required for the analyses. To meet this need, we used gene expression data from 17 diurnal studies spanning the whole Archaeplastida kingdom (Plantae kingdom in the broad sense) to make an online diurnal database. We have equipped the database with tools that allow user-friendly cross-species comparisons of gene expression profiles, entire co-expression networks, co-expressed clusters (involved in specific biological processes), time-specific gene expression and others. We exemplify how these tools can be used by studying three important biological questions: (i) the evolution of cell division, (ii) the diurnal control of gene modules in algae and (iii) the conservation of diurnally controlled modules across species. The database is freely available at http://diurnal.plant.tools.

Inferring biosynthetic and gene regulatory networks from Artemisia annua RNA sequencing data on a credit card-sized ARM computer

Prediction of gene function and gene regulatory networks is one of the most active topics in bioinformatics. The accumulation of publicly available gene expression data for hundreds of plant species, together with advances in bioinformatical methods and affordable computing, sets ingenuity as one of the major bottlenecks in understanding gene function and regulation. Here, we show how a credit card-sized computer retailing for <50 USD can be used to rapidly predict gene function and infer regulatory networks from RNA sequencing data. To achieve this, we constructed a bioinformatical pipeline that downloads and allows quality-control of RNA sequencing data; and generates a gene co-expression network that can reveal enzymes and transcription factors participating and controlling a given biosynthetic pathway. We exemplify this by first identifying genes and transcription factors involved in the biosynthesis of secondary cell wall in the plant Artemisia annua, the main natural source of the anti-malarial drug artemisinin. Networks were then used to dissect the artemisinin biosynthesis pathway, which suggest potential transcription factors regulating artemisinin biosynthesis. We provide the source code of our pipeline (https://github.com/mutwil/LSTrAP-Lite) and envision that the ubiquity of affordable computing, availability of biological data and increased bioinformatical training of biologists will transform the field of bioinformatics. This article is part of a Special Issue entitled: Transcriptional Profiles and Regulatory Gene Networks edited by Dr. Dr. Federico Manuel Giorgi and Dr. Shaun Mahony.

Co-expression networks for plant biology: why and how

Co-expression network analysis is one of the most powerful approaches for interpretation of large transcriptomic datasets. It enables characterization of modules of co-expressed genes that may share biological functional linkages. Such networks provide an initial way to explore functional associations from gene expression profiling and can be applied to various aspects of plant biology. This review presents the applications of co-expression network analysis in plant biology and addresses optimized strategies from the recent literature for performing co-expression analysis on plant biological systems. Additionally, we describe the combined interpretation of co-expression analysis with other genomic data to enhance the generation of biologically relevant information.

CoNekT: an open-source framework for comparative genomic and transcriptomic network analyses

The recent accumulation of gene expression data in the form of RNA sequencing creates unprecedented opportunities to study gene regulation and function. Furthermore, comparative analysis of the expression data from multiple species can elucidate which functional gene modules are conserved across species, allowing the study of the evolution of these modules. However, performing such comparative analyses on raw data is not feasible for many biologists. Here, we present CoNekT (Co-expression Network Toolkit), an open source web server, that contains user-friendly tools and interactive visualizations for comparative analyses of gene expression data and co-expression networks. These tools allow analysis and cross-species comparison of (i) gene expression profiles; (ii) co-expression networks; (iii) co-expressed clusters involved in specific biological processes; (iv) tissue-specific gene expression; and (v) expression profiles of gene families. To demonstrate these features, we constructed CoNekT-Plants for green alga, seed plants and flowering plants (Picea abies, Chlamydomonas reinhardtii, Vitis vinifera, Arabidopsis thaliana, Oryza sativa, Zea mays and Solanum lycopersicum) and thus provide a web-tool with the broadest available collection of plant phyla. CoNekT-Plants is freely available from http://conekt.plant.tools, while the CoNekT source code and documentation can be found at https://github.molgen.mpg.de/proost/CoNekT/.

PhytoNet: comparative co-expression network analyses across phytoplankton and land plants

Phytoplankton consists of autotrophic, photosynthesizing microorganisms that are a crucial component of freshwater and ocean ecosystems. However, despite being the major primary producers of organic compounds, accounting for half of the photosynthetic activity worldwide and serving as the entry point to the food chain, functions of most of the genes of the model phytoplankton organisms remain unknown. To remedy this, we have gathered publicly available expression data for one chlorophyte, one rhodophyte, one haptophyte, two heterokonts and four cyanobacteria and integrated it into our PlaNet (Plant Networks) database, which now allows mining gene expression profiles and identification of co-expressed genes of 19 species. We exemplify how the co-expressed gene networks can be used to reveal functionally related genes and how the comparative features of PhytoNet allow detection of conserved transcriptional programs between cyanobacteria, green algae, and land plants. Additionally, we illustrate how the database allows detection of duplicated transcriptional programs within an organism, as exemplified by two putative DNA repair programs within Chlamydomonas reinhardtii. PhytoNet is available from www.gene2function.de.

Comparing time series transcriptome data between plants using a network module finding algorithm

BACKGROUND

Comparative transcriptome analysis is the comparison of expression patterns between homologous genes in different species. Since most molecular mechanistic studies in plants have been performed in model species, including Arabidopsis and rice, comparative transcriptome analysis is particularly important for functional annotation of genes in diverse plant species. Many biological processes, such as embryo development, are highly conserved between different plant species. The challenge is to establish one-to-one mapping of the developmental stages between two species.

RESULTS

In this manuscript, we solve this problem by converting the gene expression patterns into co-expression networks and then apply network module finding algorithms to the cross-species co-expression network. We describe how such analyses are carried out using bash scripts for preliminary data processing followed by using the R programming language for module finding with a simulated annealing method. We also provide instructions on how to visualize the resulting co-expression networks across species.

CONCLUSIONS

We provide a comprehensive pipeline from installing software and downloading raw transcriptome data to predicting homologous genes and finding orthologous co-expression networks. From the example provided, we demonstrate the application of our method to reveal functional conservation and divergence of genes in two plant species.

Kingdom-wide comparison reveals the evolution of diurnal gene expression in Archaeplastida

Plants have adapted to the diurnal light-dark cycle by establishing elaborate transcriptional programs that coordinate many metabolic, physiological, and developmental responses to the external environment. These transcriptional programs have been studied in only a few species, and their function and conservation across algae and plants is currently unknown. We performed a comparative transcriptome analysis of the diurnal cycle of nine members of Archaeplastida, and we observed that, despite large phylogenetic distances and dramatic differences in morphology and lifestyle, diurnal transcriptional programs of these organisms are similar. Expression of genes related to cell division and the majority of biological pathways depends on the time of day in unicellular algae but we did not observe such patterns at the tissue level in multicellular land plants. Hence, our study provides evidence for the universality of diurnal gene expression and elucidates its evolutionary history among different photosynthetic eukaryotes.

Characterization of Cellulose Synthase A (CESA) Gene Family in Eudicots

Cellulose synthase A (CESA) is a key enzyme involved in the complex process of plant cell wall biosynthesis, and it remains a productive subject for research. We employed systems biology approaches to explore structural diversity of eudicot CESAs by exon-intron organization, mode of duplication, synteny, and splice site analyses. Using a combined phylogenetics and comparative genomics approach coupled with co-expression networks we reconciled the evolution of cellulose synthase gene family in eudicots and found that the basic forms of CESA proteins are retained in angiosperms. Duplications have played an important role in expansion of CESA gene family members in eudicots. Co-expression networks showed that primary and secondary cell wall modules are duplicated in eudicots. We also identified 230 simple sequence repeat markers in 103 eudicot CESAs. The 13 identified conserved motifs in eudicots will provide a basis for gene identification and functional characterization in other plants. Furthermore, we characterized (in silico) eudicot CESAs against senescence and found that expression levels of CESAs decreased during leaf senescence.

A pathway for every product? Tools to discover and design plant metabolism

The vast diversity of plant natural products is a powerful indication of the biosynthetic capacity of plant metabolism. Synthetic biology seeks to capitalize on this ability by understanding and reconfiguring the biosynthetic pathways that generate this diversity to produce novel products with improved efficiency. Here we review the algorithms and databases that presently support the design and manipulation of metabolic pathways in plants, starting from metabolic models of native biosynthetic pathways, progressing to novel combinations of known reactions, and finally proposing new reactions that may be carried out by existing enzymes. We show how these tools are useful for proposing new pathways as well as identifying side reactions that may affect engineering goals.

Carbon Supply and the Regulation of Cell Wall Synthesis

All plant cells are surrounded by a cell wall that determines the directionality of cell growth and protects the cell against its environment. Plant cell walls are comprised primarily of polysaccharides and represent the largest sink for photosynthetically fixed carbon, both for individual plants and in the terrestrial biosphere as a whole. Cell wall synthesis is a highly sophisticated process, involving multiple enzymes and metabolic intermediates, intracellular trafficking of proteins and cell wall precursors, assembly of cell wall polymers into the extracellular matrix, remodeling of polymers and their interactions, and recycling of cell wall sugars. In this review we discuss how newly fixed carbon, in the form of UDP-glucose and other nucleotide sugars, contributes to the synthesis of cell wall polysaccharides, and how cell wall synthesis is influenced by the carbon status of the plant, with a focus on the model species Arabidopsis (Arabidopsis thaliana).

Coordinated Functional Divergence of Genes after Genome Duplication in Arabidopsis thaliana

Gene and genome duplications have been rampant during the evolution of flowering plants. Unlike small-scale gene duplications, whole-genome duplications (WGDs) copy entire pathways or networks, and as such create the unique situation in which such duplicated pathways or networks could evolve novel functionality through the coordinated sub- or neofunctionalization of its constituent genes. Here, we describe a remarkable case of coordinated gene expression divergence following WGDs in Arabidopsis thaliana We identified a set of 92 homoeologous gene pairs that all show a similar pattern of tissue-specific gene expression divergence following WGD, with one homoeolog showing predominant expression in aerial tissues and the other homoeolog showing biased expression in tip-growth tissues. We provide evidence that this pattern of gene expression divergence seems to involve genes with a role in cell polarity and that likely function in the maintenance of cell wall integrity. Following WGD, many of these duplicated genes evolved separate functions through subfunctionalization in growth/development and stress response. Uncoupling these processes through genome duplications likely provided important adaptations with respect to growth and morphogenesis and defense against biotic and abiotic stress.

Two Complementary Mechanisms Underpin Cell Wall Patterning during Xylem Vessel Development

The evolution of the plant vasculature was essential for the emergence of terrestrial life. Xylem vessels are solute-transporting elements in the vasculature that possess secondary wall thickenings deposited in intricate patterns. Evenly dispersed microtubule (MT) bands support the formation of these wall thickenings, but how the MTs direct cell wall synthesis during this process remains largely unknown. Cellulose is the major secondary wall constituent and is synthesized by plasma membrane-localized cellulose synthases (CesAs) whose catalytic activity propels them through the membrane. We show that the protein CELLULOSE SYNTHASE INTERACTING1 (CSI1)/POM2 is necessary to align the secondary wall CesAs and MTs during the initial phase of xylem vessel development in Arabidopsis thaliana and rice (Oryza sativa). Surprisingly, these MT-driven patterns successively become imprinted and sufficient to sustain the continued progression of wall thickening in the absence of MTs and CSI1/POM2 function. Hence, two complementary principles underpin wall patterning during xylem vessel development.

Expression atlas and comparative coexpression network analyses reveal important genes involved in the formation of lignified cell wall in Brachypodium distachyon

While Brachypodium distachyon (Brachypodium) is an emerging model for grasses, no expression atlas or gene coexpression network is available. Such tools are of high importance to provide insights into the function of Brachypodium genes. We present a detailed Brachypodium expression atlas, capturing gene expression in its major organs at different developmental stages. The data were integrated into a large-scale coexpression database ( www.gene2function.de), enabling identification of duplicated pathways and conserved processes across 10 plant species, thus allowing genome-wide inference of gene function. We highlight the importance of the atlas and the platform through the identification of duplicated cell wall modules, and show that a lignin biosynthesis module is conserved across angiosperms. We identified and functionally characterised a putative ferulate 5-hydroxylase gene through overexpression of it in Brachypodium, which resulted in an increase in lignin syringyl units and reduced lignin content of mature stems, and led to improved saccharification of the stem biomass. Our Brachypodium expression atlas thus provides a powerful resource to reveal functionally related genes, which may advance our understanding of important biological processes in grasses.

Current understanding of the pathways of flavonoid biosynthesis in model and crop plants

Flavonoids are a signature class of secondary metabolites formed from a relatively simple collection of scaffolds. They are extensively decorated by chemical reactions including glycosylation, methylation, and acylation. They are present in a wide variety of fruits and vegetables and as such in Western populations it is estimated that 20-50 mg of flavonoids are consumed daily per person. In planta they have demonstrated to contribute to both flower color and UV protection. Their consumption has been suggested to presenta wide range of health benefits. Recent technical advances allowing affordable whole genome sequencing, as well as a better inventory of species-by-species chemical diversity, have greatly advanced our understanding as to how flavonoid biosynthesis pathways vary across species. In parallel, reverse genetics combined with detailed molecular phenotyping is currently allowing us to elucidate the functional importance of individual genes and metabolites and by this means to provide further mechanistic insight into their biological roles. Here we provide an inventory of current knowledge of pathways of flavonoid biosynthesis in both the model plant Arabidopsis thaliana and a range of crop species, including tomato, maize, rice, and bean.

Phylogenomic analysis of gene co-expression networks reveals the evolution of functional modules

Molecular evolutionary studies correlate genomic and phylogenetic information with the emergence of new traits of organisms. These traits are, however, the consequence of dynamic gene networks composed of functional modules, which might not be captured by genomic analyses. Here, we established a method that combines large-scale genomic and phylogenetic data with gene co-expression networks to extensively study the evolutionary make-up of modules in the moss Physcomitrella patens, and in the angiosperms Arabidopsis thaliana and Oryza sativa (rice). We first show that younger genes are less annotated than older genes. By mapping genomic data onto the co-expression networks, we found that genes from the same evolutionary period tend to be connected, whereas old and young genes tend to be disconnected. Consequently, the analysis revealed modules that emerged at a specific time in plant evolution. To uncover the evolutionary relationships of the modules that are conserved across the plant kingdom, we added phylogenetic information that revealed duplication and speciation events on the module level. This combined analysis revealed an independent duplication of cell wall modules in bryophytes and angiosperms, suggesting a parallel evolution of cell wall pathways in land plants. We provide an online tool allowing plant researchers to perform these analyses at http://www.gene2function.de.

Beyond Genomics: Studying Evolution with Gene Coexpression Networks

Understanding how genomes change as organisms become more complex is a central question in evolution. Molecular evolutionary studies typically correlate the appearance of genes and gene families with the emergence of biological pathways and morphological features. While such approaches are of great importance to understand how organisms evolve, they are also limited, as functionally related genes work together in contexts of dynamic gene networks. Since functionally related genes are often transcriptionally coregulated, gene coexpression networks present a resource to study the evolution of biological pathways. In this opinion article, we discuss recent developments in this field and how coexpression analyses can be merged with existing genomic approaches to transfer functional knowledge between species to study the appearance or extension of pathways.

BRASSINOSTEROID INSENSITIVE2 negatively regulates cellulose synthesis in Arabidopsis by phosphorylating cellulose synthase 1

The deposition of cellulose is a defining aspect of plant growth and development, but regulation of this process is poorly understood. Here, we demonstrate that the protein kinase BRASSINOSTEROID INSENSITIVE2 (BIN2), a key negative regulator of brassinosteroid (BR) signaling, can phosphorylate Arabidopsis cellulose synthase A1 (CESA1), a subunit of the primary cell wall cellulose synthase complex, and thereby negatively regulate cellulose biosynthesis. Accordingly, point mutations of the BIN2-mediated CESA1 phosphorylation site abolished BIN2-dependent regulation of cellulose synthase activity. Hence, we have uncovered a mechanism for how BR signaling can modulate cellulose synthesis in plants.

PlaNet: Comparative Co-Expression Network Analyses for Plants

Functional relations between genes can be represented as networks. These networks have been successfully used to infer gene function and to mediate transfer of functional knowledge between species. Transcriptionally coordinated or co-expressed genes tend to be functionally related, which combined with availability of transcriptomic data for multiple plant species make the co-expression networks a useful resource for the plant community. In this chapter, we describe PlaNet ( www.gene2function.de ), a database that includes comparative analyses for co-expression networks of 11 plant species. We exemplify how the tools included in PlaNet can be used to predict gene function, transfer knowledge, and discover conserved and multiplied gene modules.

Golgi-localized STELLO proteins regulate the assembly and trafficking of cellulose synthase complexes in Arabidopsis

As the most abundant biopolymer on Earth, cellulose is a key structural component of the plant cell wall. Cellulose is produced at the plasma membrane by cellulose synthase (CesA) complexes (CSCs), which are assembled in the endomembrane system and trafficked to the plasma membrane. While several proteins that affect CesA activity have been identified, components that regulate CSC assembly and trafficking remain unknown. Here we show that STELLO1 and 2 are Golgi-localized proteins that can interact with CesAs and control cellulose quantity. In the absence of STELLO function, the spatial distribution within the Golgi, secretion and activity of the CSCs are impaired indicating a central role of the STELLO proteins in CSC assembly. Point mutations in the predicted catalytic domains of the STELLO proteins indicate that they are glycosyltransferases facing the Golgi lumen. Hence, we have uncovered proteins that regulate CSC assembly in the plant Golgi apparatus.

A Meta-Analysis Based Method for Prioritizing Candidate Genes Involved in a Pre-specific Function

The identification of genes associated with a given biological function in plants remains a challenge, although network-based gene prioritization algorithms have been developed for Arabidopsis thaliana and many non-model plant species. Nevertheless, these network-based gene prioritization algorithms have encountered several problems; one in particular is that of unsatisfactory prediction accuracy due to limited network coverage, varying link quality, and/or uncertain network connectivity. Thus, a model that integrates complementary biological data may be expected to increase the prediction accuracy of gene prioritization. Toward this goal, we developed a novel gene prioritization method named RafSee, to rank candidate genes using a random forest algorithm that integrates sequence, evolutionary, and epigenetic features of plants. Subsequently, we proposed an integrative approach named RAP (Rank Aggregation-based data fusion for gene Prioritization), in which an order statistics-based meta-analysis was used to aggregate the rank of the network-based gene prioritization method and RafSee, for accurately prioritizing candidate genes involved in a pre-specific biological function. Finally, we showcased the utility of RAP by prioritizing 380 flowering-time genes in Arabidopsis. The "leave-one-out" cross-validation experiment showed that RafSee could work as a complement to a current state-of-art network-based gene prioritization system (AraNet v2). Moreover, RAP ranked 53.68% (204/380) flowering-time genes higher than AraNet v2, resulting in an 39.46% improvement in term of the first quartile rank. Further evaluations also showed that RAP was effective in prioritizing genes-related to different abiotic stresses. To enhance the usability of RAP for Arabidopsis and non-model plant species, an R package implementing the method is freely available at http://bioinfo.nwafu.edu.cn/software.