Germline Expression Influences Operon Organization in the Caenorhabditis elegans Genome

Operons are found across multiple kingdoms and phyla, from prokaryotes to chordates. In the nematode Caenorhabditis elegans, the genome contains >1000 operons that compose ~15% of the protein-coding genes. However, determination of the force(s) promoting the origin and maintenance of operons in C. elegans has proved elusive. Compared to bacterial operons, genes within a C. elegans operon often show poor coexpression and only sometimes encode proteins with related functions. Using analysis of microarray and large-scale in situ hybridization data, we demonstrate that almost all operon-encoded genes are expressed in germline tissue. However, genes expressed during spermatogenesis are excluded from operons. Operons group together along chromosomes in local clusters that also contain monocistronic germline-expressed genes. Additionally, germline expression of genes in operons is largely independent of the molecular function of the encoded proteins. These analyses demonstrate that mechanisms governing germline gene expression influence operon origination and/or maintenance. Thus, gene expression in a specific tissue can have profound effects on the evolution of genome organization.     

Functions of the duplicated hik31 operons in central metabolism and responses to light, dark, and carbon sources in Synechocystis sp. strain PCC 6803

There are two closely related hik31 operons involved in signal transduction on the chromosome and the pSYSX plasmid in the cyanobacterium Synechocystis sp. strain PCC 6803. We studied the growth, cell morphology, and gene expression in operon and hik mutants for both copies, under different growth conditions, to examine whether the duplicated copies have the same or different functions and gene targets and whether they are similarly regulated. Phenotype analysis suggested that both operons regulated common and separate targets in the light and the dark. The chromosomal operon was involved in the negative control of autotrophic events, whereas the plasmid operon was involved in the positive control of heterotrophic events. Both the plasmid and double operon mutant cells were larger and had division defects. The growth data also showed a regulatory role for the chromosomal hik gene under high-CO(2) conditions and the plasmid operon under low-O(2) conditions. Metal stress experiments indicated a role for the chromosomal hik gene and operon in mediating Zn and Cd tolerance, the plasmid operon in Co tolerance, and the chromosomal operon and plasmid hik gene in Ni tolerance. We conclude that both operons are differentially and temporally regulated. We suggest that the chromosomal operon is the primarily expressed copy and the plasmid operon acts as a backup to maintain appropriate gene dosages. Both operons share an integrated regulatory relationship and are induced in high light, in glucose, and in active cell growth. Additionally, the plasmid operon is induced in the dark with or without glucose.     

Comparison of mammalian cell entry operons of mycobacteria: in silico analysis and expression profiling

Mammalian cell entry (mce) operons, implicated in the entry of mycobacteria into host cells, are present in pathogenic and saprophytic species. It is likely that the genes in these operons have functions other than those required for entry into host cells. Using in silico analysis we have identified domains within the mce operons that might justify their occurrence in saprophytic species like Mycobacterium smegmatis. Our analysis identified in addition to the mce domain, the presence of the Ttg2B and Ttg2C domains, typical of proteins involved in transport. We have also analysed and compared the expression profile between mce operons of Mycobacterium tuberculosis, Mycobacterium bovis and M. smegmatis under different growth conditions. In case of M. smegmatis, each operon presented domain truncation for at least one gene. We observe differential expression among the operons in M. smegmatis growing under different culture conditions. Bacilli growing in nutritionally rich medium with aeration, only the mce4 operon was expressed while during stationary phase of a standing culture, all four mce operons were expressed. In M. bovis, in addition to the absence of the mce3 operon, several protein domains encoded by the other operons were truncated. We detected expression of the mce2 operon in the exponential and stationary growth phase, while the mce1 operon was only expressed in the stationary growth phase. Differential expression of mce operons and their redundancy in the genome of the majority members of mycobacteria are discussed in view of our results.     

Computational analysis of Ciona intestinalis operons

Operons are clusters of genes that are co-regulated from a common promoter. Operons are typically associated with prokaryotes, although a small number of eukaryotes have been shown to possess them. Among metazoans, operons have been extensively characterized in the nematode Caenorhabditis elegans in which ～15% of the total genes are organized into operons. The most recent genome assembly for the ascidian Ciona intestinalis placed ～20% of the genes (2909 total) into 1310 operons. The majority of these operons are composed of two genes, while the largest are composed of six. Here is reported a computational analysis of the genes that comprise the Ciona operons. Gene ontology (GO) terms were identified for about two-thirds of the operon-encoded genes. Using the extensive collection of public EST libraries, estimates of temporal patterns of gene expression were generated for the operon-encoded genes. Lastly, conservation of operons was analyzed by determining how many operon-encoded genes were present in the ascidian Ciona savignyi and whether these genes were organized in orthologous operons. Over 68% of the operon-encoded genes could be assigned one or more GO terms and 697 of the 1310 operons contained genes in which all genes had at least one GO term. Of these 697 operons, GO terms were shared by all of the genes within 146 individual operons, suggesting that most operons encode genes with unrelated functions. An analysis of operon gene expression from nine different EST libraries indicated that for 587 operons, all of the genes that comprise an individual operon were expressed together in at least one EST library, suggesting that these genes may be co-regulated. About 50% (74/146) of the operons with shared GO terms also showed evidence of gene co-regulation. Comparisons with the C. savignyi genome identified orthologs for 1907 of 2909 operon genes. About 38% (504/1310) of the operons are conserved between the two Ciona species. These results suggest that like C. elegans, operons in Ciona are comprised of a variety of genes that are not necessarily related in function. The genes in only 50% of the operons appear to be co-regulated, suggesting that more complex gene regulatory mechanisms are likely operating.     

The genomic pattern of tDNA operon expression in E. coli

In fast-growing microorganisms, a tRNA concentration profile enriched in major isoacceptors selects for the biased usage of cognate codons. This optimizes translational rate for the least mass invested in the translational apparatus. Such translational streamlining is thought to be growth-regulated, but its genetic basis is poorly understood. First, we found in reanalysis of the E. coli tRNA profile that the degree to which it is translationally streamlined is nearly invariant with growth rate. Then, using least squares multiple regression, we partitioned tRNA isoacceptor pools to predicted tDNA operons from the E. coli K12 genome. Co-expression of tDNAs in operons explains the tRNA profile significantly better than tDNA gene dosage alone. Also, operon expression increases significantly with proximity to the origin of replication, oriC, at all growth rates. Genome location explains about 15% of expression variation in a form, at a given growth rate, that is consistent with replication-dependent gene concentration effects. Yet the change in the tRNA profile with growth rate is less than would be expected from such effects. We estimated per-copy expression rates for all tDNA operons that were consistent with independent estimates for rDNA operons. We also found that tDNA operon location, and the location dependence of expression, were significantly different in the leading and lagging strands. The operonic organization and genomic location of tDNA operons are significant factors influencing their expression. Nonrandom patterns of location and strandedness shown by tDNA operons in E. coli suggest that their genomic architecture may be under selection to satisfy physiological demand for tRNA expression at high growth rates.     

The life-cycle of operons

Operons are a major feature of all prokaryotic genomes, but how and why operon structures vary is not well understood. To elucidate the life-cycle of operons, we compared gene order between Escherichia coli K12 and its relatives and identified the recently formed and destroyed operons in E. coli. This allowed us to determine how operons form, how they become closely spaced, and how they die. Our findings suggest that operon evolution may be driven by selection on gene expression patterns. First, both operon creation and operon destruction lead to large changes in gene expression patterns. For example, the removal of lysA and ruvA from ancestral operons that contained essential genes allowed their expression to respond to lysine levels and DNA damage, respectively. Second, some operons have undergone accelerated evolution, with multiple new genes being added during a brief period. Third, although genes within operons are usually closely spaced because of a neutral bias toward deletion and because of selection against large overlaps, genes in highly expressed operons tend to be widely spaced because of regulatory fine-tuning by intervening sequences. Although operon evolution may be adaptive, it need not be optimal: new operons often comprise functionally unrelated genes that were already in proximity before the operon formed.     

Optimal gene partition into operons correlates with gene functional order

Gene arrangement into operons varies between bacterial species. Genes in a given system can be on one operon in some organisms and on several operons in other organisms. Existing theories explain why genes that work together should be on the same operon, since this allows for advantageous lateral gene transfer and accurate stoichiometry. But what causes the frequent separation into multiple operons of co-regulated genes that act together in a pathway? Here we suggest that separation is due to benefits made possible by differential regulation of each operon. We present a simple mathematical model for the optimal distribution of genes into operons based on a balance of the cost of operons and the benefit of regulation that provides 'just-when-needed' temporal order. The analysis predicts that genes are arranged such that genes on the same operon do not skip functional steps in the pathway. This prediction is supported by genomic data from 137 bacterial genomes. Our work suggests that gene arrangement is not only the result of random historical drift, genome re-arrangement and gene transfer, but has elements that are solutions of an evolutionary optimization problem. Thus gene functional order may be inferred by analyzing the operon structure across different genomes.     

A Bayesian Model for Pooling Gene Expression Studies That Incorporates Co-Regulation Information

Current Bayesian microarray models that pool multiple studies assume gene expression is independent of other genes. However, in prokaryotic organisms, genes are arranged in units that are co-regulated (called operons). Here, we introduce a new Bayesian model for pooling gene expression studies that incorporates operon information into the model. Our Bayesian model borrows information from other genes within the same operon to improve estimation of gene expression. The model produces the gene-specific posterior probability of differential expression, which is the basis for inference. We found in simulations and in biological studies that incorporating co-regulation information improves upon the independence model. We assume that each study contains two experimental conditions: a treatment and control. We note that there exist environmental conditions for which genes that are supposed to be transcribed together lose their operon structure, and that our model is best carried out for known operon structures.     

Operons Are a Conserved Feature of Nematode Genomes

The organization of genes into operons, clusters of genes that are co-transcribed to produce polycistronic pre-mRNAs, is a trait found in a wide range of eukaryotic groups, including multiple animal phyla. Operons are present in the class Chromadorea, one of the two main nematode classes, but their distribution in the other class, the Enoplea, is not known. We have surveyed the genomes of Trichinella spiralis, Trichuris muris, and Romanomermis culicivorax and identified the first putative operons in members of the Enoplea. Consistent with the mechanism of polycistronic RNA resolution in other nematodes, the mRNAs produced by genes downstream of the first gene in the T. spiralis and T. muris operons are trans-spliced to spliced leader RNAs, and we are able to detect polycistronic RNAs derived from these operons. Importantly, a putative intercistronic region from one of these potential enoplean operons confers polycistronic processing activity when expressed as part of a chimeric operon in Caenorhabditis elegans. We find that T. spiralis genes located in operons have an increased likelihood of having operonic C. elegans homologs. However, operon structure in terms of synteny and gene content is not tightly conserved between the two taxa, consistent with models of operon evolution. We have nevertheless identified putative operons conserved between Enoplea and Chromadorea. Our data suggest that operons and “spliced leader” (SL) trans-splicing predate the radiation of the nematode phylum, an inference which is supported by the phylogenetic profile of proteins known to be involved in nematode SL trans-splicing.