Comparative genomics reveals unusually long motifs in mammalian genomes

MOTIVATION: The recent discovery of the first small modulatory RNA (smRNA) presents the challenge of finding other molecules of similar length and conservation level. Unlike short interfering RNA (siRNA) and micro-RNA (miRNA), effective computational and experimental screening methods are not currently known for this species of RNA molecule, and the discovery of the one known example was partly fortuitous because it happened to be complementary to a well-studied DNA binding motif (the Neuron Restrictive Silencer Element). RESULTS: The existing comparative genomics approaches (e.g., phylogenetic footprinting) rely on alignments of orthologous regions across multiple genomes. This approach, while extremely valuable, is not suitable for finding motifs with highly diverged "non-alignable" flanking regions. Here we show that several unusually long and well conserved motifs can be discovered de novo through a comparative genomics approach that does not require an alignment of orthologous upstream regions. These motifs, including Neuron Restrictive Silencer Element, were missed in recent comparative genomics studies that rely on phylogenetic footprinting. While the functions of these motifs remain unknown, we argue that some may represent biologically important sites. AVAILABILITY: Our comparative genomics software, a web-accessible database of our results and a compilation of experimentally validated binding sites for NRSE can be found at http://www.cse.ucsd.edu/groups/bioinformatics.     

The regulation of genes and genomes by small RNAs

A recent Keystone Symposium on 'MicroRNAs and siRNAs: Biological Functions and Mechanisms' was organized by David Bartel and Shiv Grewal (and was held in conjunction with 'RNAi for Target Validation and as a Therapeutic', organized by Stephen Friend and John Maraganore). The 'MicroRNAs and siRNAs' meeting brought together scientists working on diverse biological aspects of small regulatory RNAs, including microRNAs, small interfering RNAs (siRNAs) and Piwi-interacting RNAs (piRNAs and rasiRNAs). Among the themes discussed were the diversity of small regulatory RNAs and their developmental functions, their biogenesis, the identification of their regulatory targets, their mechanisms of action, and their roles in the elaboration of multicellular complexity.     

Identification of small RNAs in diverse bacterial species

Small, non-coding bacterial RNAs (sRNAs) have been shown to regulate a plethora of biological processes. Up until recently, most sRNAs had been identified and characterized in E. coli. However, in the past few years, dozens of sRNAs have been discovered in a wide variety of bacterial species. Whereas numerous sRNAs have been isolated or detected through experimental approaches, most have been identified in predictive bioinformatic searches. Recently developed computational tools have greatly facilitated the efficient prediction of sRNAs in diverse species. Although the number of known sRNAs has dramatically increased in recent years, many challenges in the identification and characterization of sRNAs lie ahead.     

An in silico model for identification of small RNAs in whole bacterial genomes: characterization of antisense RNAs in pathogenic Escherichia coli and Streptococcus agalactiae strains

Characterization of small non-coding ribonucleic acids (sRNA) among the large volume of data generated by high-throughput RNA-seq or tiling microarray analyses remains a challenge. Thus, there is still a need for accurate in silico prediction methods to identify sRNAs within a given bacterial species. After years of effort, dedicated software were developed based on comparative genomic analyses or mathematical/statistical models. Although these genomic analyses enabled sRNAs in intergenic regions to be efficiently identified, they all failed to predict antisense sRNA genes (asRNA), i.e. RNA genes located on the DNA strand complementary to that which encodes the protein. The statistical models enabled any genomic region to be analyzed theorically but not efficiently. We present a new model for in silico identification of sRNA and asRNA candidates within an entire bacterial genome. This model was successfully used to analyze the Gram-negative Escherichia coli and Gram-positive Streptococcus agalactiae. In both bacteria, numerous asRNAs are transcribed from the complementary strand of genes located in pathogenicity islands, strongly suggesting that these asRNAs are regulators of the virulence expression. In particular, we characterized an asRNA that acted as an enhancer-like regulator of the type 1 fimbriae production involved in the virulence of extra-intestinal pathogenic E. coli.     

Computational approaches for the discovery of bacterial small RNAs

Recent work has uncovered a growing number of bacterial small RNAs (sRNAs), some of which have been shown to regulate critical cellular processes. Computational approaches, in combination with experiments, have played an important role in the discovery of these sRNAs. In this article, we first give an overview of different computational approaches for genome-wide prediction of sRNAs. These approaches have led to the discovery of several novel sRNAs, however the regulatory roles are not yet known for a majority of these sRNAs. By contrast, several recent studies have highlighted the inverse problem where the functional role of the sRNA is already known and the challenge is to identify its genomic location. The focus of this article is on computational tools and strategies for identifying these specific sRNAs which function as key components of known regulatory pathways.     

Identification of bacterial small non-coding RNAs: experimental approaches

Almost 140 bacterial small RNAs (sRNAs; sometimes referred to as non-coding RNAs) have been discovered in the past six years. The majority of these sRNAs were discovered in Escherichia coli, and a smaller subset was characterized in other bacteria, many of which were pathogenic. Many of these genes were identified as a result of systematic screens using computational prediction of sRNAs and experimental-based approaches, including microarray and shotgun cloning. A smaller number of sRNAs were discovered by direct labeling or by functional genetic screens. Many of the discovered genes, ranging in size from 50 to 500 nucleotides, are conserved and located in intergenic regions, in-between open reading frames. The expression of many of these genes is growth phase dependent or stress related. As each search employed specific parameters, this led to the identification of genes with distinct characteristics. Consequently, unique sRNAs such as those that are species-specific, sRNA genes that are transcribed under unique conditions or genes located on the antisense strand of protein-encoding genes, were probably missed.     

Functional annotations in bacterial genomes based on small RNA signatures

One of the key challenges in computational genomics is annotating coding genes and identification of regulatory RNAs in complete genomes. An attempt is made in this study which uses the regulatory RNA locations and their conserved flanking genes identified within the genomic backbone of template genome to search for similar RNA locations in query genomes. The search is based on recently reported coexistence of small RNAs and their conserved flanking genes in related genomes. Based on our study, 54 additional sRNA locations and functions of 96 uncharacterized genes are predicted in two draft genomes viz., Serratia marcesens Db1 and Yersinia enterocolitica 8081. Although most of the identified additional small RNA regions and their corresponding flanking genes are homologous in nature, the proposed anchoring technique could successfully identify four non-homologous small RNA regions in Y. enterocolitica genome also. The KEGG Orthology (KO) based automated functional predictions confirms the predicted functions of 65 flanking genes having defined KO numbers, out of the total 96 predictions made by this method. This coexistence based method shows more sensitivity than controlled vocabularies in locating orthologous gene pairs even in the absence of defined Orthology numbers. All functional predictions made by this study in Y. enterocolitica 8081 were confirmed by the recently published complete genome sequence and annotations. This study also reports the possible regions of gene rearrangements in these two genomes and further characterization of such RNA regions could shed more light on their possible role in genome evolution.     

Comparative bacterial genomics: defining the minimal core genome

A comparative genomics analysis revealed 702 genes present in the bacterial Gram-negative core gene set (92 species analyzed) and 959 genes in the Gram-positive core gene set (93 species analyzed). Mycoplasma genitalium, which has the smallest known genome (517 genes) of a non-symbiont, was used in a three-way reciprocal analysis with the Gram-negative core genes and the Gram-positive core genes, and 151 common bacterial core genes were found. Of these 151 core genes, 39 were putative genes encoding the 30S and 50S ribosomal subunits, whilst among recognized cell division genes, only one gene, the major ftsZ, was present. In addition, 86 reciprocal matches were identified between the 151 common bacterial genes and a previously determined 2,723 common eukaryotic core gene set. An analysis was also done to optimize the threshold bit score used to declare that genes were homologous, and a bit score cutoff of 40 was selected.     

Comparative approach to correction of annotated gene starts in complete bacterial genomes

A method for refining the beginnings of genes and a search for shifts of the reading frame is proposed. The method is based on a comparison of nucleotide and amino acid sequences of homologous genes of related organisms. The algorithm is based on the fact that the rate of changes in the protein-coding regions of the genome is substantially lower than that of noncoding regions. A modification of the Smith-Waterman algorithm is proposed, which makes it possible to align the amino acid sequences obtained by formal translation of the starting nucleotide sequences by taking into account a possible shift of the reading frame. The algorithm has been implemented in the package of ORTOLOGATOR-GeneCorrector programs. Testing the program showed that the approach enables one to detect a wrong annotation of the beginnings in 1% of genes (even in well-studied organisms such as Escherichia coli) and identify several (approximately 10) shifts of the open reading frame. Thus, the algorithm can be used at both the initial and final stages of analysis of the genome.     

Molecular call and response: the physiology of bacterial small RNAs

The vital role of bacterial small RNAs (sRNAs) in cellular regulation is now well-established. Although many diverse mechanisms by which sRNAs bring about changes in gene expression have been thoroughly described, comparatively less is known about their biological roles and effects on cell physiology. Nevertheless, for some sRNAs, insight has been gained into the intricate regulatory interplay that is required to sense external environmental and internal metabolic cues and turn them into physiological outcomes. Here, we review examples of regulation by selected sRNAs, emphasizing signals and regulators required for sRNA expression, sRNA regulatory targets, and the resulting consequences for the cell. We highlight sRNAs involved in regulation of the processes of iron homeostasis (RyhB, PrrF, and FsrA) and carbon metabolism (Spot 42, CyaR, and SgrS).     

Why genomics is more than genomes

A report on the 2004 meeting on Molecular Genetics of Bacteria and Bacteriophages, Cold Spring Harbor, USA, 25-29 August 2004.     

Comparative genomics of 274 Vibrio cholerae genomes reveals mobile functions structuring three niche dimensions

Background

Vibrio cholerae is a globally dispersed pathogen that has evolved with humans for centuries, but also includes non-pathogenic environmental strains. Here, we identify the genomic variability underlying this remarkable persistence across the three major niche dimensions space, time, and habitat.

Results

Taking an innovative approach of genome-wide association applicable to microbial genomes (GWAS-M), we classify 274 complete V. cholerae genomes by niche, including 39 newly sequenced for this study with the Ion Torrent DNA-sequencing platform. Niche metadata were collected for each strain and analyzed together with comprehensive annotations of genetic and genomic attributes, including point mutations (single-nucleotide polymorphisms, SNPs), protein families, functions and prophages.

Conclusions

Our analysis revealed that genomic variations, in particular mobile functions including phages, prophages, transposable elements, and plasmids underlie the metadata structuring in each of the three niche dimensions. This underscores the role of phages and mobile elements as the most rapidly evolving elements in bacterial genomes, creating local endemicity (space), leading to temporal divergence (time), and allowing the invasion of new habitats. Together, we take a data-driven approach for comparative functional genomics that exploits high-volume genome sequencing and annotation, in conjunction with novel statistical and machine learning analyses to identify connections between genotype and phenotype on a genome-wide scale.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-654) contains supplementary material, which is available to authorized users.     

Comparative genomics suggests local adaptations in the invasive small hive beetle

Invasive species are a major driver of ecological and environmental changes that affect human health, food security, and natural biodiversity. The success and impact of biological invasions depend on adaptations to novel abiotic and biotic selective pressures. However, the molecular mechanisms underlying adaptations in invasive parasitic species are inadequately understood. Small hive beetles, Aethina tumida, are parasites of bee nests. Originally endemic to sub‐Saharan Africa, they are now found nearly globally. Here, we investigated the molecular bases of the adaptations to novel environments underlying their invasion routes. Genomes of historic and recent adults A. tumida from both the endemic and introduced ranges were compared. Analysis of gene–environment association identified 3049 candidate loci located in 874 genes. Functional annotation showed a significant bias toward genes linked to growth and reproduction. One of the genes from the apoptosis pathway encodes an “ecdysone‐related protein,” which is a crucial regulator in controlling body size in response to environmental cues for holometabolous insects during cell death and renewal. Genes whose proteins regulate organ size, ovary activation, and oviposition were also detected. Functions of these enriched pathways parallel behavioral differences between introduced and native A. tumida populations, which may reflect patterns of local adaptation. The results considerably improve our understanding of the underlying mechanisms and ecological factors driving adaptations of invasive species. Deep functional investigation of these identified loci will help clarify the mechanisms of local adaptation in A. tumida.     

Comparative genomics analysis of completely sequenced microbial genomes reveals the ubiquity of N-linked glycosylation in prokaryotes

Glycosylation of proteins in prokaryotes has been known for the last few decades. Glycan structures and/or the glycosylation pathways have been experimentally characterized in only a small number of prokaryotes. Even this has become possible only during the last decade or so, primarily due to technological and methodological developments. Glycosylated proteins are diverse in their function and localization. Glycosylation has been shown to be associated with a wide range of biological phenomena. Characterization of the various types of glycans and the glycosylation machinery is critical to understand such processes. Such studies can help in the identification of novel targets for designing drugs, diagnostics, and engineering of therapeutic proteins. In view of this, the experimentally characterized pgl system of Campylobacter jejuni, responsible for N-linked glycosylation, has been used in this study to identify glycosylation loci in 865 prokaryotes whose genomes have been completely sequenced. Results from the present study show that only a small number of organisms have homologs for all the pgl enzymes and a few others have homologs for none of the pgl enzymes. Most of the organisms have homologs for only a subset of the pgl enzymes. There is no specific pattern for the presence or absence of pgl homologs vis-à-vis the 16S rRNA sequence-based phylogenetic tree. This may be due to differences in the glycan structures, high sequence divergence, horizontal gene transfer or non-orthologous gene displacement. Overall, the presence of homologs for pgl enzymes in a large number of organisms irrespective of their habitat, pathogenicity, energy generation mechanism, etc., hints towards the ubiquity of N-linked glycosylation in prokaryotes.