Editorial for Special Issue "Functional Genomics and Comparative Genomics Analysis in Plants, 3rd Edition".

Functional Plant Genomics

The first complete plant genome sequence to be determined was that of the model plant Arabidopsis thaliana , which was published in 2000. This was followed by the first drafts of the rice genome sequence in 2002. Since the publication of these landmark genomes, the development of high throughput sequencing technologies has reduced the time and cost of obtaining genome sequences to a fraction of that required a decade ago. This has enabled the sequencing of many plant genomes and thus a vast amount of genome sequence information is available to the researcher. The goal of functional genomics is to determine how these genome sequences generate plant phenotypes. The focus of most functional genomics research is to determine the function of all the genes involved in a particular process. To achieve this, functional genomics uses techniques and analyses that can survey the entire complement of genes in a genome. This chapter discusses the most commonly used functional genomics methods. Key Concepts: Advances in sequencing technologies are making entire genome sequences relatively easy to obtain. The goal of plant functional genomics is to understand how the genome generates the phenotype of the plant. Comparison to other gene sequences can often identify a likely function for a gene. Array and sequencing based methods can be used to show where and when all the genes in an organism are expressed. Gene function can be determined by knocking out or reducing gene function and can be achieved by insertion, chemical mutagenesis or RNAi. High throughput methods using recombination‐based cloning enable many tests of gene function to be applied on a genome‐wide scale.

Comparative genomics and functional genomics are two basic branches of plant genomics [...].

PLAZA is a platform for comparative, evolutionary, and functional plant genomics. It makes a broad set of genomes, data types and analysis tools available to researchers through a user-friendly website, an API, and bulk downloads. In this latest release of the PLAZA platform, we are integrating a record number of 134 high-quality plant genomes, split up over two instances: PLAZA Dicots 5.0 and PLAZA Monocots 5.0. This number of genomes corresponds with a massive expansion in the number of available species when compared to PLAZA 4.0, which offered access to 71 species, a 89% overall increase. The PLAZA 5.0 release contains information for 5 882 730 genes, and offers pre-computed gene families and phylogenetic trees for 5 274 684 protein-coding genes. This latest release also comes with a set of new and updated features: a new BED import functionality for the workbench, improved interactive visualizations for functional enrichments and genome-wide mapping of gene sets, and a fully redesigned and extended API. Taken together, this new version offers extended support for plant biologists working on different families within the green plant lineage and provides an efficient and versatile toolbox for plant genomics. All PLAZA releases are accessible from the portal website: https://bioinformatics.psb.ugent.be/plaza/.

As more and more plant genomes are sequenced, plant researchers have been inundated with an avalanche of novel methodologies to identify the function of tens of thousands of plant genes. In Plant Functional Genomics, Erich Grotewold has assembled a team of leading plant scientists to describe in detail the most commonly used methods for investigating plant gene function in a wide variety of plants, during plant pathogen interactions, and even in algae. These readily reproducible protocols include computational, molecular, and genetic methodologies designed for both general and specific problems. Here the reader will learn how to identify genes in complex systems that have large genomes, few cells, and mixed cell systems. Readers will also learn the use of powerful computational and statistical tools to help predict gene function, either on the basis of comparative genomics, or from the analysis of complex genome sequences. Because establishing gene function relies on the identification of phenotypes, the authors expand the concept of phenotypes, including the use of multiple outputs as the ultimate phenotypic result of changes in gene activity. Numerous loss-of-function and gain-of-function techniques for discovering gene function are presented in step-by-step detail. Comprehensive and highly practical, Plant Functional Genomics offers plant biologists readily reproducible computational, molecular, and genetic protocols, powerful tools that will enable them, with little or no experience, successfully to investigate any gene function with the most recent methodologies

A Model of Elegance

Although the evolutionarily younger nitrogen-fixing symbioses (NFS) occurring between plants and rhizobia are predominantly confined to legume species, they exhibit a series of highly conserved characteristics in common with the more ancestral arbuscular mycorrhizal symbiosis (AMS). A growing number of symbiosis-regulated genes have been characterized through either genetic analysis or phylogenomic profiling. However, the underlying similarities and specificities of the transcription regulatory machinery in AMS and NFS remain largely unclarified. Here, we systematically profiled the gene expression changes in three legume species, namely Medicago truncatula, Glycine max, and Lotus japonicus, during AMS and NFS. Additionally, we investigated gene expression changes in three non-legume plants, Solanum lycopersicum, Zea mays, and Oryza sativa, during AMS. We identified thousands of genes that were activated by AMS or NFS in their respective host plants. Through comparative genomics analysis, we systematically explored the conservation and specificity of genes responsive to AMS or NFS. Employing M. truncatula and G. max as illustrative cases, we harnessed the XGboost machine-learning model to construct co-expression-based gene regulatory networks (GRNs) for AMS and NFS within these two species. Through this approach, we successfully illuminated the similarities and unique features of the two symbiotic types at the GRN level. Further, utilizing known symbiosis genes as queries, we pinpointed a multitude of genes that are intimately associated with AMS and NFS. Overall, via in-depth gene expression profiling and regulatory network analysis, our results indicate that, while NFS in legumes has regulatory circuits similar to those of AMS, there exist certain symbiosis type-specific molecular components.

Comparative genomics is the comparison of genetic information within and across organisms to understand the evolution, structure, and function of genes, proteins, and non-coding regions (Sivashankari and Shanmughavel, Bioinformation 1:376-8, 2007). Advances in sequencing technology and assembly algorithms have resulted in the ability to sequence large genomes and provided a wealth of data that are being used in comparative genomic analyses. Comparative analysis can be leveraged to systematically explore and evaluate the biological relationships and evolution between species, aid in understanding the structure and function of genes, and gain a better understanding of disease and potential drug targets. As our knowledge of genetics expands, comparative genomics can help identify emerging model organisms among a broader span of the tree of life, positively impacting human health. This impact includes, but is not limited to, zoonotic disease research, therapeutics development, microbiome research, xenotransplantation, oncology, and toxicology. Despite advancements in comparative genomics, new challenges have arisen around the quantity, quality assurance, annotation, and interoperability of genomic data and metadata. New tools and approaches are required to meet these challenges and fulfill the needs of researchers. This paper focuses on how the National Institutes of Health (NIH) Comparative Genomics Resource (CGR) can address both the opportunities for comparative genomics to further impact human health and confront an increasingly complex set of challenges facing researchers.

GreenPhylDB is a database designed for comparative and functional genomics based on complete genomes. Version 2 now contains sixteen full genomes of members of the plantae kingdom, ranging from algae to angiosperms, automatically clustered into gene families. Gene families are manually annotated and then analyzed phylogenetically in order to elucidate orthologous and paralogous relationships. The database offers various lists of gene families including plant, phylum and species specific gene families. For each gene cluster or gene family, easy access to gene composition, protein domains, publications, external links and orthologous gene predictions is provided. Web interfaces have been further developed to improve the navigation through information related to gene families. New analysis tools are also available, such as a gene family ontology browser that facilitates exploration. GreenPhylDB is a component of the South Green Bioinformatics Platform (http://southgreen.cirad.fr/) and is accessible at http://greenphyl.cirad.fr. It enables comparative genomics in a broad taxonomy context to enhance the understanding of evolutionary processes and thus tends to speed up gene discovery.

Xanthomonas campestris pathovar campestris (Xcc) is the causative agent of crucifer black rot disease, which causes severe losses in agricultural yield world-wide. This bacterium is a model organism for studying plant-bacteria interactions. We sequenced the complete genome of Xcc 8004 (5,148,708 bp), which is highly conserved relative to that of Xcc ATCC 33913. Comparative genomics analysis indicated that, in addition to a significant genomic-scale rearrangement cross the replication axis between two IS1478 elements, loss and acquisition of blocks of genes, rather than point mutations, constitute the main genetic variation between the two Xcc strains. Screening of a high-density transposon insertional mutant library (16,512 clones) of Xcc 8004 against a host plant (Brassica oleraceae) identified 75 nonredundant, single-copy insertions in protein-coding sequences (CDSs) and intergenic regions. In addition to known virulence factors, full virulence was found to require several additional metabolic pathways and regulatory systems, such as fatty acid degradation, type IV secretion system, cell signaling, and amino acids and nucleotide metabolism. Among the identified pathogenicity-related genes, three of unknown function were found in Xcc 8004-specific chromosomal segments, revealing a direct correlation between genomic dynamics and Xcc virulence. The present combination of comparative and functional genomic analyses provides valuable information about the genetic basis of Xcc pathogenicity, which may offer novel insight toward the development of efficient methods for prevention of this important plant disease.

Regulons, which serve as co-regulated gene groups contributing to the transcriptional regulation of microbial genomes, have the potential to aid in understanding of underlying regulatory mechanisms. In this study, we designed a novel computational pipeline, regulon identification based on comparative genomics and transcriptomics analysis (RECTA), for regulon prediction related to the gene regulatory network under certain conditions. To demonstrate the effectiveness of this tool, we implemented RECTA on Lactococcus lactis MG1363 data to elucidate acid-response regulons. A total of 51 regulons were identified, 14 of which have computational-verified significance. Among these 14 regulons, five of them were computationally predicted to be connected with acid stress response. Validated by literature, 33 genes in Lactococcus lactis MG1363 were found to have orthologous genes which were associated with six regulons. An acid response related regulatory network was constructed, involving two trans-membrane proteins, eight regulons (llrA, llrC, hllA, ccpA, NHP6A, rcfB, regulons #8 and #39), nine functional modules, and 33 genes with orthologous genes known to be associated with acid stress. The predicted response pathways could serve as promising candidates for better acid tolerance engineering in Lactococcus lactis. Our RECTA pipeline provides an effective way to construct a reliable gene regulatory network through regulon elucidation, and has strong application power and can be effectively applied to other bacterial genomes where the elucidation of the transcriptional regulation network is needed.

Since 2003, MicrobesOnline (http://www.microbesonline.org) has been providing a community resource for comparative and functional genome analysis. The portal includes over 1000 complete genomes of bacteria, archaea and fungi and thousands of expression microarrays from diverse organisms ranging from model organisms such as Escherichia coli and Saccharomyces cerevisiae to environmental microbes such as Desulfovibrio vulgaris and Shewanella oneidensis. To assist in annotating genes and in reconstructing their evolutionary history, MicrobesOnline includes a comparative genome browser based on phylogenetic trees for every gene family as well as a species tree. To identify co-regulated genes, MicrobesOnline can search for genes based on their expression profile, and provides tools for identifying regulatory motifs and seeing if they are conserved. MicrobesOnline also includes fast phylogenetic profile searches, comparative views of metabolic pathways, operon predictions, a workbench for sequence analysis and integration with RegTransBase and other microbial genome resources. The next update of MicrobesOnline will contain significant new functionality, including comparative analysis of metagenomic sequence data. Programmatic access to the database, along with source code and documentation, is available at http://microbesonline.org/programmers.html.

The strain chosen for genome DNA sequencing was Enterococcus faecalis V583, the first vancomycin-resistant clinical isolate in the United States. The genome of strain V583 was sequenced by The Institute for Genome Research (TIGR) using the random sequencing method. The predicted open reading frames (ORFs) are organized by functional category in the online annotation database and are summarized in a table. The strain V583 contains four DNA molecules: the main 3,218,030-bp bacterial chromosome and three circular plasmids. The three plasmids are circular DNA molecules identified as Plasmid-1, Plasmid-2, and Plasmid-3, containing 66,320, 17,963, and 57,660 bp, respectively. TTGR has assembled a number of tools for the analysis of the E. faecalis genome and its comparison to other bacterial genomes through the Comprehensive Microbial Resource (CMR). A particularly useful tool is the CMR Gene Attribute Download resource, which allows a user to configure and download a database from the TTGR annotation based on all or part of the assigned role categories. The information contained within the genome of E. faecalis V583 greatly aids one's understanding of how this organism has adapted to be a versatile, opportunistic human pathogen. Comparative genomics and functional genome analysis will begin to unravel the role that regulatory elements play in physiologic responses to environmental stress and in the expression of potential virulence factors.

What gives an organism the ability to regrow tissues and to recover function where another organism fails is the central problem of regenerative biology. The challenge is to describe the mechanisms of regeneration at the molecular level, delivering detailed insights into the many components that are cross-regulated. In other words, a broad, yet deep dissection of the system-wide network of molecular interactions is needed. Functional genomics has been used to elucidate gene regulatory networks (GRNs) in developing tissues, which, like regeneration, are complex systems. Therefore, we reason that the GRN approach, aided by next generation technologies, can also be applied to study the molecular mechanisms underlying the complex functions of regeneration. We ask what characteristics a model system must have to support a GRN analysis. Our discussion focuses on regeneration in the central nervous system, where loss of function has particularly devastating consequences for an organism. We examine a cohort of cells conserved across all vertebrates, the reticulospinal (RS) neurons, which lend themselves well to experimental manipulations. In the lamprey, a jawless vertebrate, there are giant RS neurons whose large size and ability to regenerate make them particularly suited for a GRN analysis. Adding to their value, a distinct subset of lamprey RS neurons reproducibly fail to regenerate, presenting an opportunity for side-by-side comparison of gene networks that promote or inhibit regeneration. Thus, determining the GRN for regeneration in RS neurons will provide a mechanistic understanding of the fundamental cues that lead to success or failure to regenerate.

A data-driven optimization method for coarse-graining gene regulatory networks