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Abstract Background The evolution of multicellularity is accompanied by the occurrence of differentiated tissues, of organismal developmental programs, and of mechanisms keeping the balance between proliferation and differentiation. Initially, the SET-domain proteins were associated exclusively with regulation of developmental genes in metazoa. However, finding of SET-domain genes in the unicellular yeasts Saccharomyces cerevisiae and Schizosaccharomyces pombe suggested that SET-domain proteins regulate a much broader variety of biological programs. Intuitively, it is expected that the numbers, types, and biochemical specificity of SET-domain proteins of multicellular versus unicellular forms would reflect the differences in their biology. However, comparisons across the unicellular and multicellular domains of life are complicated by the lack of knowledge of the ancestral SET-domain genes. Even within the crown group, different biological systems might use the epigenetic 'code' differently, adapting it to organism-specific needs. Simplifying the model, we undertook a systematic phylogenetic analysis of one monophyletic fungal group (Ascomycetes) containing unicellular yeasts, Saccharomycotina (hemiascomycetes), and a filamentous fungal group, Pezizomycotina (euascomycetes). Results Systematic analysis of the SET-domain genes across an entire eukaryotic phylum has outlined clear distinctions in the SET-domain gene collections in the unicellular and in the multicellular (filamentous) relatives; diversification of SET-domain gene families has increased further with the expansion and elaboration of multicellularity in animal and plant systems. We found several ascomycota-specific SET-domain gene groups; each was unique to either Saccharomycotina or Pezizomycotina fungi. Our analysis revealed that the numbers and types of SET-domain genes in the Saccharomycotina did not reflect the habitats, pathogenicity, mechanisms of sexuality, or the ability to undergo morphogenic transformations. However, novel genes have appeared for functions associated with the transition to multicellularity. Descendents of most of the SET-domain gene families found in the filamentous fungi could be traced in the genomes of extant animals and plants, albeit as more complex structural forms. Conclusion SET-domain genes found in the filamentous species but absent from the unicellular sister group reflect two alternative evolutionary events: deletion from the yeast genomes or appearance of novel structures in filamentous fungal groups. There were no Ascomycota-specific SET-domain gene families (i.e., absent from animal and plant genomes); however, plants and animals share SET-domain gene subfamilies that do not exist in the fungi. Phylogenetic and gene-structure analyses defined several animal and plant SET-domain genes as sister groups while those of fungal origin were basal to them. Plants and animals also share SET-domain subfamilies that do not exist in fungi.

Abstract Background Codon usage bias (CUB), the uneven use of synonymous codons, is a ubiquitous observation in virtually all organisms examined. The pattern of codon usage is generally similar among closely related species, but differs significantly among distantly related organisms, e.g., bacteria, yeast, and Drosophila. Several explanations for CUB have been offered and some have been supported by observations and experiments, although a thorough understanding of the evolutionary forces (random drift, mutation bias, and selection) and their relative importance remains to be determined. The recently available complete genome DNA sequences of twelve phylogenetically defined species of Drosophila offer a hitherto unprecedented opportunity to examine these problems. We report here the patterns of codon usage in the twelve species and offer insights on possible evolutionary forces involved. Results (1) Codon usage is quite stable across 11/12 of the species: G- and especially C-ending codons are used most frequently, thus defining the preferred codons. (2) The only amino acid that changes in preferred codon is Serine with six species of the melanogaster group favoring TCC while the other species, particularly subgenus Drosophila species, favor AGC. (3) D. willistoni is an exception to these generalizations in having a shifted codon usage for seven amino acids toward A/T in the wobble position. (4) Amino acids differ in their contribution to overall CUB, Leu having the greatest and Asp the least. (5) Among two-fold degenerate amino acids, A/G ending amino acids have more selection on codon usage than T/C ending amino acids. (6) Among the different chromosome arms or elements, genes on the non-recombining element F (dot chromosome) have the least CUB, while genes on the element A (X chromosome) have the most. (7) Introns indicate that mutation bias in all species is approximately 2:1, AT:GC, the opposite of codon usage bias. (8) There is also evidence for some overall regional bias in base composition that may influence codon usage. Conclusion Overall, these results suggest that natural selection has acted on codon usage in the genus Drosophila, at least often enough to leave a footprint of selection in modern genomes. However, there is evidence in the data that random forces (drift and mutation) have also left patterns in the data, especially in genes under weak selection for codon usage for example genes in regions of low recombination. The documentation of codon usage patterns in each of these twelve genomes also aids in ongoing annotation efforts.

Byline: Stephen O. Opiyo, Etsuko N. Moriyama Cytochrome b561 (Cyt-b561) proteins are important for plant growth, development, and prevention of damage to plants. Because of their high sequence divergence, thorough mining of Cyt-b561 proteins from plant genomes are not easy. Currently there is only one Cyt-b561 gene found in the maize and none in the soybean genome. However, 22 have been identified in the Arabidopsis thaliana genome. We tested alignment-free protein classifiers based on partial least squares (PLS) and support vector machines to identify Cyt-b561. These classifiers performed better than profile hidden Markov models and PSI-BLAST. Using these classifiers we identified new Cyt-b561-related proteins from four plant genomes.

The interplay among diet, gut microbial ecology and cholesterol metabolism in a hamster model of hypercholesterolemia is characterized. The analysis has shown that modulation of the gut microbiota-host metabolic interrelationship by dietary intervention can be used for improving mammalian cholesterol homeostasis, which has relevance for cardiovascular health.

Motivation: Proteins often include multiple conserved domains. Various evolutionary events including duplication and loss of domains, domain shuffling, as well as sequence divergence contribute to generating complexities in protein structures, and consequently, in their functions. The evolutionary history of proteins is hence best modeled through networks that incorporate information both from the sequence divergence and the domain content. Here, a game-theoretic approach proposed for protein network construction is adapted into the framework of multi-objective optimization, and extended to incorporate clustering refinement procedure. Results: The new method, MOCASSIN-prot, was applied to cluster multi-domain proteins from ten genomes. The performance of MOCASSIN-prot was compared against two protein clustering methods, Markov clustering (TRIBE-MCL) and spectral clustering (SCPS). We showed that compared to these two methods, MOCASSIN-prot, which uses both domain composition and quantitative sequence similarity information, generates fewer false positives. It achieves more functionally coherent protein clusters and better differentiates protein families. [ABSTRACT FROM AUTHOR]

Background: Despite a number of recent reports of insect resistance to transgenic crops expressing insecticidal toxins from Bacillus thuringiensis (Bt), little is known about the mechanism of resistance to these toxins. The purpose of this study is to identify genes associated with the mechanism of Cry1F toxin resistance in European corn borer (Ostrinia nubilalis Hübner). For this, we compared the global transcriptomic response of laboratory selected resistant and susceptible O. nubilalis strain to Cry1F toxin. We further identified constitutive transcriptional differences between the two strains. Results: An O. nubilalis midgut transcriptome of 36,125 transcripts was assembled de novo from 106 million Illumina HiSeq and Roche 454 reads and used as a reference for estimation of differential gene expression analysis. Evaluation of gene expression profiles of midgut tissues from the Cry1F susceptible and resistant strains after toxin exposure identified a suite of genes that responded to the toxin in the susceptible strain (n = 1,654), but almost 20-fold fewer in the resistant strain (n = 84). A total of 5,455 midgut transcripts showed significant constitutive expression differences between Cry1F susceptible and resistant strains. Transcripts coding for previously identified Cry toxin receptors, cadherin and alkaline phosphatase and proteases were also differentially expressed in the midgut of the susceptible and resistant strains. Conclusions: Our current study provides a valuable resource for further molecular characterization of Bt resistance and insect response to Cry1F toxin in O. nubilalis and other pest species. [ABSTRACT FROM AUTHOR]

Cellulose is an important nutritional resource for a number of insect herbivores. Digestion of cellulose and other polysaccharides in plant-based diets requires several types of enzymes including a number of glycoside hydrolase (GH) families. In a previous study, we showed that a single GH45 gene is present in the midgut tissue of the western corn rootworm, Diabrotica virgifera virgifera (Coleoptera: Chrysomelidae). However, the presence of multiple enzymes was also suggested by the lack of a significant biological response when the expression of the gene was silenced by RNA interference. In order to clarify the repertoire of cellulose-degrading enzymes and related GH family proteins in D. v. virgifera, we performed next-generation sequencing and assembled transcriptomes from the tissue of three different developmental stages (eggs, neonates, and third instar larvae). Results of this study revealed the presence of seventy-eight genes that potentially encode GH enzymes belonging to eight families (GH45, GH48, GH28, GH16, GH31, GH27, GH5, and GH1). The numbers of GH45 and GH28 genes identified in D. v. virgifera are among the largest in insects where these genes have been identified. Three GH family genes (GH45, GH48, and GH28) are found almost exclusively in two coleopteran superfamilies (Chrysomeloidea and Curculionoidea) among insects, indicating the possibility of their acquisitions by horizontal gene transfer rather than simple vertical transmission from ancestral lineages of insects. Acquisition of GH genes by horizontal gene transfers and subsequent lineage-specific GH gene expansion appear to have played important roles for phytophagous beetles in specializing on particular groups of host plants and in the case of D. v. virgifera, its close association with maize. [ABSTRACT FROM AUTHOR]

Background: With its massive amount of data, gene-expression profiling by RNA-Seq has many advantanges compared with microarray experiments. RNA-Seq analysis, however, is fundamentally different from microarray data analysis. Techniques developed for analyzing microarray data thus cannot be directly applicable for the digital gene expression data. Several statistical methods have been developed for identifying differentially expressed genes specifically from RNA-Seq data over the past few years. Results: In this study, we examined the performance of differential gene-calling methods using RNA-Seq data in practical situations. We focused on two representative methods: one parametric method, DESeq, and one nonparametric method, NOISeq. We examined their performance using both simulated and real datasets. Our simulation followed the RNA-Seq process and produced more realistic short read data. Both DESeq and NOISeq identified over-expressed genes more correctly than under-expressed genes. While DESeq was more likely to call longer genes as differentially expressed than shorter ones, NOISeq did not have such bias. When the underlying variation increased, both methods showed higher rates of false positives. When replicates were not available in the experiments, both methods showed lower rates of true positives and higher rates of false positives. Conclusions: The level of variation clearly affected the performance of both methods, showing the importance of understanding the variation in the data as well as having replications in RNA-Seq experiments. We showed that it is possible to obtain improved differential gene-calling results by combining the results obtained by the two methods. We suggested strategies to use these two methods individually or combined according to the characteristics of the data. [ABSTRACT FROM AUTHOR]

The vertebrate digestive tract, including that of humans, is the habitat to trillions of bacteria that are of significant importance to host biology and health. Although these communities are often postulated to have coevolved with their hosts, evidence is lacking, yet critical for our understanding of microbial symbiosis in vertebrates. To gain insight into the evolution of a gut symbiont, we have characterized the population genetic structure and phylogeny of Lactobacillus reuteri strains isolated from six different host species (human, mouse, rat, pig, chicken and turkey) using Amplified-Fragment Length Polymorphism (AFLP) and Multi-Locus Sequence Analysis (MLSA). The results revealed considerable genetic heterogeneity within the L. reuteri population and distinct monophyletic clades reflecting host origin but not provenance. The evolutionary patterns detected indicate a long-term association of L. reuteri lineages with particular vertebrate species and host-driven diversification. Results from a competition experiment in a gnotobiotic mouse model revealed that rodent isolates showed elevated ecological performance, indicating that evolution of L. reuteri lineages was adaptive. These findings provide evidence that some vertebrate gut microbes are not promiscuous, but have diversified into host-adapted lineages by a long-term evolutionary process, allowing the development of a highly specialized symbiosis. [ABSTRACT FROM AUTHOR]

Background: Lipid A is the highly immunoreactive endotoxic center of lipopolysaccharide (LPS). It anchors the LPS into the outer membrane of most Gram-negative bacteria. Lipid A can be recognized by animal cells, triggers defense-related responses, and causes Gram-negative sepsis. The biosynthesis of Kdo2-lipid A, the LPS substructure, involves with nine enzymatic steps. Results: In order to elucidate the evolutionary pathway of Kdo2-lipid A biosynthesis, we examined the distribution of genes encoding the nine enzymes across bacteria. We found that not all Gram-negative bacteria have all nine enzymes. Some Gram-negative bacteria have no genes encoding these enzymes and others have genes only for the first four enzymes (LpxA, LpxC, LpxD, and LpxB). Among the nine enzymes, five appeared to have arisen from three independent gene duplication events. Two of such events happened within the Proteobacteria lineage, followed by functional specialization of the duplicated genes and pathway optimization in these bacteria. Conclusions: The nine-enzyme pathway, which was established based on the studies mainly in Escherichia coli K12, appears to be the most derived and optimized form. It is found only in E. coli and related Proteobacteria. Simpler and probably less efficient pathways are found in other bacterial groups, with Kdo2-lipid A variants as the likely end products. The Kdo2-lipid A biosynthetic pathway exemplifies extremely plastic evolution of bacterial genomes, especially those of Proteobacteria, and how these mainly pathogenic bacteria have adapted to their environment. [ABSTRACT FROM AUTHOR]

Background: Seven-transmembrane region-containing receptors (7TMRs) play central roles in eukaryotic signal transduction. Due to their biomedical importance, thorough mining of 7TMRs from diverse genomes has been an active target of bioinformatics and pharmacogenomics research. The need for new and accurate 7TMR/GPCR prediction tools is paramount with the accelerated rate of acquisition of diverse sequence information. Currently available and often used protein classification methods (e.g., profile hidden Markov Models) are highly accurate for identifying their membership information among already known 7TMR subfamilies. However, these alignment-based methods are less effective for identifying remote similarities, e.g., identifying proteins from highly divergent or possibly new 7TMR families. In this regard, more sensitive (e.g., alignment-free) methods are needed to complement the existing protein classification methods. A better strategy would be to combine different classifiers, from more specific to more sensitive methods, to identify a broader spectrum of 7TMR protein candidates. Description: We developed a Web server, 7TMRmine, by integrating alignment-free and alignment-based classifiers specifically trained to identify candidate 7TMR proteins as well as transmembrane (TM) prediction methods. This new tool enables researchers to easily assess the distribution of GPCR functionality in diverse genomes or individual newly-discovered proteins. 7TMRmine is easily customized and facilitates exploratory analysis of diverse genomes. Users can integrate various alignment-based, alignment-free, and TM-prediction methods in any combination and in any hierarchical order. Sixteen classifiers (including two TM-prediction methods) are available on the 7TMRmine Web server. Not only can the 7TMRmine tool be used for 7TMR mining, but also for general TM-protein analysis. Users can submit protein sequences for analysis, or explore pre-analyzed results for multiple genomes. The server currently includes prediction results and the summary statistics for 68 genomes. Conclusion: 7TMRmine facilitates the discovery of 7TMR proteins. By combining prediction results from different classifiers in a multi-level filtering process, prioritized sets of 7TMR candidates can be obtained for further investigation. 7TMRmine can be also used as a general TM-protein classifier. Comparisons of TM and 7TMR protein distributions among 68 genomes revealed interesting differences in evolution of these protein families among major eukaryotic phyla. [ABSTRACT FROM AUTHOR]

Background: Comparative genomics has become an essential approach for identifying homologous gene candidates and their functions, and for studying genome evolution. There are many tools available for genome comparisons. Unfortunately, most of them are not applicable for the identification of unique genes and the inference of phylogenetic relationships in a given set of genomes. Results: GenomeBlast is a Web tool developed for comparative analysis of multiple small genomes. A new parameter called "coverage" was introduced and used along with sequence identity to evaluate global similarity between genes. With GenomeBlast, the following results can be obtained: (1) unique genes in each genome; (2) homologous gene candidates among compared genomes; (3) 2D plots of homologous gene candidates along the all pairwise genome comparisons; and (4) a table of gene presence/absence information and a genome phylogeny. We demonstrated the functions in GenomeBlast with an example of multiple herpesviral genome analysis and illustrated how GenomeBlast is useful for small genome comparison. Conclusion: We developed a Web tool for comparative analysis of small genomes, which allows the user not only to identify unique genes and homologous gene candidates among multiple genomes, but also to view their graphical distributions on genomes, and to reconstruct genome phylogeny. GenomeBlast runs on a Linux server with 4 CPUs and 4 GB memory. [ABSTRACT FROM AUTHOR]