RNA and RNP as new molecular parts in synthetic biology

Synthetic biology has a promising outlook in biotechnology and for understanding the self-organizing principle of biological molecules in life. However, synthetic biologists have been looking for new molecular "parts" that function as modular units required in designing and constructing new "devices" and "systems" for regulating cell function because the number of such parts is strictly limited at present. In this review, we focus on RNA/ribonucleoprotein (RNP) architectures that hold promise as new "parts" for synthetic biology. They are constructed with molecular design and an experimental evolution technique. So far, designed self-folding RNAs, RNA (RNP) enzymes, and nanoscale RNA architectures have been successfully constructed by utilizing Watson-Crick base-pairs together with specific RNA-RNA or RNA-protein binding motifs of known defined 3D structures. Riboregulators for regulating targeted gene expression have also been designed and produced in vitro as well as in vivo. Lately, RNA and ribonucleoprotein complexes have been strongly attracting the attention of molecular biologists because a variety of noncoding RNAs discovered in nature perform spatiotemporal gene expressions. Thus we hope that newly accumulating knowledge on naturally occurring RNAs and RNP complexes will provide a variety of new parts, devices and systems for synthetic biology.     

GENEVESTIGATOR. Arabidopsis microarray database and analysis toolbox

High-throughput gene expression analysis has become a frequent and powerful research tool in biology. At present, however, few software applications have been developed for biologists to query large microarray gene expression databases using a Web-browser interface. We present GENEVESTIGATOR, a database and Web-browser data mining interface for Affymetrix GeneChip data. Users can query the database to retrieve the expression patterns of individual genes throughout chosen environmental conditions, growth stages, or organs. Reversely, mining tools allow users to identify genes specifically expressed during selected stresses, growth stages, or in particular organs. Using GENEVESTIGATOR, the gene expression profiles of more than 22,000 Arabidopsis genes can be obtained, including those of 10,600 currently uncharacterized genes. The objective of this software application is to direct gene functional discovery and design of new experiments by providing plant biologists with contextual information on the expression of genes. The database and analysis toolbox is available as a community resource at https://www.genevestigator.ethz.ch.     

From transects to transcripts: Teasing apart the architecture of reproductive isolation

Understanding the processes underlying speciation has long been a challenge to evolutionary biologists. This spurs from difficulties teasing apart the various mechanisms that contribute to the evolution of barriers to reproduction. The study by Rafati et al. ( 2018 ) in this issue of Molecular Ecology combines spatially explicit whole‐genome resequencing with evaluation of differential gene expression across individuals with mixed ancestry to associate the genomic architecture of reproductive barriers with expression of reproductive incompatibilities. In a natural hybrid zone between rabbit subspecies, Oryctolagus cuniculus cuniculus and O. c. algirus (Figure  1 ), Rafati et al. ( 2018 ) use landscape‐level patterns of allele frequency variation to identify potential candidate regions of the genome associated with reproductive isolation. These candidate regions are used to test predictions associated with the genomic architecture of reproductive barriers, including the role of structural rearrangements, enrichment of functional categories associated with incompatibilities, and the contribution of protein‐coding versus regulatory changes. A lack of structural rearrangements and limited protein‐coding changes in candidate regions point towards the importance of regulatory variation as major contributors to genetic incompatibilities, while functional enrichments indicate overrepresentation of genes associated with male infertility. To quantify phenotypic expression of proposed incompatibilities, the authors assess gene expression of experimental crosses. Extensive misregulation of gene expression within the testes of backcross hybrids relative to F1 and parental individuals provides an important link between genotype and phenotype, validating hypotheses developed from assessment of genomic architectures. Together, this work shows how pairing natural hybrid zones with experimental crosses can be used to link observations in nature to mechanistic underpinnings that may be tested experimentally.     

Re-engineering plant gene targeting

The genome sequence of Arabidopsis is complete and the genomes of plants representing legumes (Medicago truncatula) and grasses (rice) will soon follow. The rate at which new genes have been discovered has far outstripped the pace at which their function is determined. The greatest hurdle that plant biologists face in assigning gene function and in crop improvement is the lack of efficient and robust technologies to generate gene replacements or targeted gene knockouts. Many of the factors underlying these events remain to be elucidated. This review addresses the current status of plant gene targeting and what is known about the associated plant DNA repair mechanisms.     

Wrestling with pleiotropy: genomic and topological analysis of the yeast gene expression network

The vast majority (>95%) of single-gene mutations in yeast affect not only the expression of the mutant gene, but also the expression of many other genes. These data suggest the presence of a previously uncharacterized "gene expression network"--a set of interactions between genes which dictate gene expression in the native cell environment. Here, we quantitatively analyze the gene expression network revealed by microarray expression data from 273 different yeast gene deletion mutants.(1) We find that gene expression interactions form a robust, error-tolerant "scale-free" network, similar to metabolic pathways(2) and artificial networks such as power grids and the internet.(3-5) Because the connectivity between genes in the gene expression network is unevenly distributed, a scale-free organization helps make organisms resistant to the deleterious effects of mutation, and is thus highly adaptive. The existence of a gene expression network poses practical considerations for the study of gene function, since most mutant phenotypes are the result of changes in the expression of many genes. Using principles of scale-free network topology, we propose that fragmenting the gene expression network via "genome-engineering" may be a viable and practical approach to isolating gene function.     

Convergence in pigmentation at multiple levels: mutations,genes and function

Convergence—the independent evolution of the same trait by two or more taxa—has long been of interest to evolutionary biologists, but only recently has the molecular basis of phenotypic convergence been identified. Here, we highlight studies of rapid evolution of cryptic coloration in vertebrates to demonstrate that phenotypic convergence can occur at multiple levels: mutations, genes and gene function. We first show that different genes can be responsible for convergent phenotypes even among closely related populations, for example, in the pale beach mice inhabiting Florida''s Gulf and Atlantic coasts. By contrast, the exact same mutation can create similar phenotypes in distantly related species such as mice and mammoths. Next, we show that different mutations in the same gene need not be functionally equivalent to produce similar phenotypes. For example, separate mutations produce divergent protein function but convergent pale coloration in two lizard species. Similarly, mutations that alter the expression of a gene in different ways can, nevertheless, result in similar phenotypes, as demonstrated by sister species of deer mice. Together these studies underscore the importance of identifying not only the genes, but also the precise mutations and their effects on protein function, that contribute to adaptation and highlight how convergence can occur at different genetic levels.     

Toward an unbiased evolutionary platform for unraveling Xenopus developmental gene networks

The availability of both the Xenopus tropicalis genome and the soon to be released Xenopus laevis genome provides a solid foundation for Xenopus developmental biologists. The Xenopus community has presently amassed expression data for ～2,300 genes in the form of published images collected in the Xenbase, the principal Xenopus research database. A few of these genes have been examined in both X. tropicalis and X. laevis and the cross-species comparison has been proven invaluable for studying gene function. A recently published work has yielded developmental expression profiles for the majority of Xenopus genes across fourteen developmental stages spanning the blastula, gastrula, neurula, and the tail-bud. While this data was originally queried for global evolutionary and developmental principles, here we demonstrate its general use for gene-level analyses. In particular, we present the accessibility of this dataset through Xenbase and describe biases in the characterized genes in terms of sequence and expression conservation across the two species. We further indicate the advantage of examining coexpression for gene function discovery relating to developmental processes conserved across species. We suggest that the integration of additional large-scale datasets--comprising diverse functional data--into Xenbase promises to provide a strong foundation for researchers in elucidating biological processes including the gene regulatory programs encoding development.     

Identification of responsive gene modules by network-based gene clustering and extending: application to inflammation and angiogenesis

Background  

Cell responses to environmental stimuli are usually organized as relatively separate responsive gene modules at the molecular level. Identification of responsive gene modules rather than individual differentially expressed (DE) genes will provide important information about the underlying molecular mechanisms. Most of current methods formulate module identification as an optimization problem: find the active sub-networks in the genome-wide gene network by maximizing the objective function considering the gene differential expression and/or the gene-gene co-expression information. Here we presented a new formulation of this task: a group of closely-connected and co-expressed DE genes in the gene network are regarded as the signatures of the underlying responsive gene modules; the modules can be identified by finding the signatures and then recovering the "missing parts" by adding the intermediate genes that connect the DE genes in the gene network.     

GAAD: A Gene and Autoimmiune Disease Association Database

Autoimmune diseases (ADs) arise from an abnormal immune response of the body against substances and tissues normally present in the body. More than a hundred of ADs have been described in the literature so far. Although their etiology remains largely unclear, various types of ADs tend to share more associated genes with other types of ADs than with non-AD types. Here we present GAAD, a gene and AD association database. In GAAD, we collected 44,762 associations between 49 ADs and 4249 genes from public databases and MEDLINE documents. We manually verified the associations to ensure the quality and credibility. We reconstructed and recapitulated the relationships among ADs using their shared genes, which further validated the quality of our data. We also provided a list of significantly co-occurring gene pairs among ADs; with embedded tools, users can query gene co-occurrences and construct customized co-occurrence network with genes of interest. To make GAAD more straightforward to experimental biologists and medical scientists, we extracted additional information describing the associations through text mining, including the putative diagnostic value of the associations, type and position of gene polymorphisms, expression changes of implicated genes, as well as the phenotypical consequences, and grouped the associations accordingly. GAAD is freely available at http://gaad.medgenius.info.     

Prokaryotic gene clusters: a rich toolbox for synthetic biology

Bacteria construct elaborate nanostructures, obtain nutrients and energy from diverse sources, synthesize complex molecules, and implement signal processing to react to their environment. These complex phenotypes require the coordinated action of multiple genes, which are often encoded in a contiguous region of the genome, referred to as a gene cluster. Gene clusters sometimes contain all of the genes necessary and sufficient for a particular function. As an evolutionary mechanism, gene clusters facilitate the horizontal transfer of the complete function between species. Here, we review recent work on a number of clusters whose functions are relevant to biotechnology. Engineering these clusters has been hindered by their regulatory complexity, the need to balance the expression of many genes, and a lack of tools to design and manipulate DNA at this scale. Advances in synthetic biology will enable the large-scale bottom-up engineering of the clusters to optimize their functions, wake up cryptic clusters, or to transfer them between organisms. Understanding and manipulating gene clusters will move towards an era of genome engineering, where multiple functions can be "mixed-and-matched" to create a designer organism.     

Population genetic variation in genome-wide gene expression

Evolutionary biologists seek to understand which traits display variation, are heritable, and influence differential reproduction, because such traits respond to natural selection and underlie organic evolution. Selection acts upon individual differences within a population. Whether individual differences within a natural population include variation in gene expression levels has not yet been addressed on a genome-wide scale. Here we use DNA microarray technology for measuring comparative gene expression and a refined statistical analysis for the purpose of comparing gene expression levels in natural isolates of the wine yeast Saccharomyces cerevisiae. A method for the Bayesian analysis of gene expression levels is used to compare four natural isolates of S. cerevisiae from Montalcino, Italy. Widespread variation in amino acid metabolism, sulfur assimilation and processing, and protein degradation-primarily consisting of differences in expression level smaller than a factor of 2-is demonstrated. Genetic variation in gene expression among isolates from a natural population is present on a genomic scale. It remains to be determined what role differential gene expression may play in adaptation to new or changing environments.     

ZooDDD: a cross-species database for digital differential display analysis

In this article, we combined EST information from the UniGene database and orthologous relationships from the Ensembl database to construct a ZooDDD database. The primary function of ZooDDD is to mine evolutionary conserved, highly expressed, tissue-specific orthologues in model animals. The candidate genes of interest derived from the ZooDDD database will provide biologists with a good step for comparing the expression, functions and evolution of animal genomes. AVAILABILITY: http://bio301.iis.sinica.edu.tw/~ZooDDDNew/main.php.