Chromosomal mapping of ANTP class homeobox genes in amphioxus: piecing together ancestral genomes

Homeobox genes encode DNA-binding proteins, many of which are implicated in the control of embryonic development. Evolutionarily, most homeobox genes fall into two related clades: the ANTP and the PRD classes. Some genes in ANTP class, notably Hox, ParaHox, and NK genes, have an intriguing arrangement into physical clusters. To investigate the evolutionary history of these gene clusters, we examined homeobox gene chromosomal locations in the cephalochordate amphioxus, Branchiostoma floridae. We deduce that 22 amphioxus ANTP class homeobox genes localize in just three chromosomes. One contains the Hox cluster plus AmphiEn, AmphiMnx, and AmphiDll. The ParaHox cluster resides in another chromosome, whereas a third chromosome contains the NK type homeobox genes, including AmphiMsx and ArnphiTlx. By comparative analysis we infer that clustering of ANTP class homeobox genes evolved just once, during a series of extensive cis-duplication events of genes early in animal evolution. A trans-duplication event occurred later to yield the Hox and ParaHox gene clusters on different chromosomes. The results obtained have implications for understanding the origin of homeobox gene clustering, the diversification of the ANTP class of homeobox genes, and the evolution of animal genomes.

The poliovirus 2C cis-acting replication element-mediated uridylylation of VPg is not required for synthesis of negative-sense genomes

Nucleotides in the terminal loop of the poliovirus 2C cis-acting replication element (2C(CRE)), a 61 nt structured RNA, function as the template for the addition of two uridylate (U) residues to the viral protein VPg. This uridylylation reaction leads to the formation of VPgpUpU, which is used by the viral RNA polymerase as a nucleotide-peptide primer for genome replication. Although VPg primes both positive- and negative-strand replication, the specific requirement for 2C(CRE)-mediated uridylylation for one or both events has not been demonstrated. We have used a cell-free in vitro translation and replication reaction to demonstrate that 2C(CRE) is not required for the initiation of the negative-sense strand, which is synthesized in the absence of 2C(CRE)-mediated VPgpUpU formation. We propose that the 3' poly(A) tail could serve as the template for the formation of a VPg-poly(U) primer that functions in the initiation of negative-sense strands.

Synapsing variable length crossover: Biologically inspired crossover for variable length genomes

Biological Crossover occurs during the early stages of meiosis. During this process the chromosomes undergoing crossover are synapsed together at a number of homogenous sequence sections, it is within such synapsed sections that crossover occurs. The SVLC (Synapsing Variable Length Crossover) Algorithm recurrently synapses homogenous genetic sequences together in order of length. The genomes are considered to be flexible with crossover only being permitted within the synapsed sections. Consequently, common sequences are automatically preserved with only the genetic differences being exchanged, independent of the length of such differences. In addition to providing a rationale for variable length crossover it also provides a genotypic similarity metric for variable length genomes enabling standard niche formation techniques to be utilised. In a simple variable length test problem the SVLC algorithm outperforms current variable length crossover techniques.

Synapsing variable length crossover: An algorithm for crossing and comparing variable length genomes

The Synapsing Variable Length Crossover (SVLC) algorithm provides a biologically inspired method for performing meaningful crossover between variable length genomes. In addition to providing a rationale for variable length crossover it also provides a genotypic similarity metric for variable length genomes enabling standard niche formation techniques to be used with variable length genomes. Unlike other variable length crossover techniques which consider genomes to be rigid inflexible arrays and where some or all of the crossover points are randomly selected, the SVLC algorithm considers genomes to be flexible and chooses non-random crossover points based on the common parental sequence similarity. The SVLC Algorithm recurrently "glues" or synapses homogenous genetic sub-sequences together. This is done in such a way that common parental sequences are automatically preserved in the offspring with only the genetic differences being exchanged or removed, independent of the length of such differences. In a variable length test problem the SVLC algorithm is shown to outperform current variable length crossover techniques. The SVLC algorithm is also shown to work in a more realistic robot neural network controller evolution application.

Synapsing variable-length crossover: Meaningful crossover for variable-length genomes

The synapsing variable-length crossover (SVLC algorithm provides a biologically inspired method for performing meaningful crossover between variable-length genomes. In addition to providing a rationale for variable-length crossover, it also provides a genotypic similarity metric for variable-length genomes, enabling standard niche formation techniques to be used with variable-length genomes. Unlike other variable-length crossover techniques which consider genomes to be rigid inflexible arrays and where some or all of the crossover points are randomly selected, the SVLC algorithm considers genomes to be flexible and chooses non-random crossover points based on the common parental sequence similarity. The SVLC algorithm recurrently "glues" or synapses homogenous genetic subsequences together. This is done in such a way that common parental sequences are automatically preserved in the offspring with only the genetic differences being exchanged or removed, independent of the length of such differences. In a variable-length test problem, the SVLC algorithm compares favorably with current variable-length crossover techniques. The variable-length approach is further advocated by demonstrating how a variable-length genetic algorithm (GA) can obtain a high fitness solution in fewer iterations than a traditional fixed-length GA in a two-dimensional vector approximation task.

Pseudomonas genomes: diverse and adaptable

Members of the genus Pseudomonas inhabit a wide variety of environments, which is reflected in their versatile metabolic capacity and broad potential for adaptation to fluctuating environmental conditions. Here, we examine and compare the genomes of a range of Pseudomonas spp. encompassing plant, insect and human pathogens, and environmental saprophytes. In addition to a large number of allelic differences of common genes that confer regulatory and metabolic flexibility, genome analysis suggests that many other factors contribute to the diversity and adaptability of Pseudomonas spp. Horizontal gene transfer has impacted the capability of pathogenic Pseudomonas spp. in terms of disease severity (Pseudomonas aeruginosa) and specificity (Pseudomonas syringae). Genome rearrangements likely contribute to adaptation, and a considerable complement of unique genes undoubtedly contributes to strain- and species-specific activities by as yet unknown mechanisms. Because of the lack of conserved phenotypic differences, the classification of the genus has long been contentious. DNA hybridization and genome-based analyses show close relationships among members of P. aeruginosa, but that isolates within the Pseudomonas fluorescens and P. syringae species are less closely related and may constitute different species. Collectively, genome sequences of Pseudomonas spp. have provided insights into pathogenesis and the genetic basis for diversity and adaptation.

The Genomic Threading Database: a comprehensive resource for structural annotations of the genomes from key organisms

Currently, the Genomic Threading Database (GTD) contains structural assignments for the proteins encoded within the genomes of nine eukaryotes and 101 prokaryotes. Structural annotations are carried out using a modified version of GenTHREADER, a reliable fold recognition method. The Gen THREADER annotation jobs are distributed across multiple clusters of processors using grid technology and the predictions are deposited in a relational database accessible via a web interface at http://bioinf.cs.ucl.ac.uk/GTD. Using this system, up to 84% of proteins encoded within a genome can be confidently assigned to known folds with 72% of the residues aligned. On average in the GTD, 64% of proteins encoded within a genome are confidently assigned to known folds and 58% of the residues are aligned to structures.

A process for analysis of microarray comparative genomics hybridisation studies for bacterial genomes

Background: Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results: The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion: After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.

Do variations in substitution rates and male mutation bias correlate with life-history traits? A study of 32 mammalian genomes

Life-history traits vary substantially across species, and have been demonstrated to affect substitution rates. We compute genomewide, branch-specific estimates of male mutation bias (the ratio of male-to-female mutation rates) across 32 mammalian genomes and study how these vary with life-history traits (generation time, metabolic rate, and sperm competition). We also investigate the influence of life-history traits on substitution rates at unconstrained sites across a wide phylogenetic range. We observe that increased generation time is the strongest predictor of variation in both substitution rates (for which it is a negative predictor) and male mutation bias (for which it is a positive predictor). Although less significant, we also observe that estimates of metabolic rate, reflecting replication-independent DNA damage and repair mechanisms, correlate negatively with autosomal substitution rates, and positively with male mutation bias. Finally, in contrast to expectations, we find no significant correlation between sperm competition and either autosomal substitution rates or male mutation bias. Our results support the important but frequently opposite effects of some, but not all, life history traits on substitution rates. KEY WORDS: Generation time, genome evolution, metabolic rate, sperm competition.

High Resolution Melt (HRM) analysis is an efficient tool to genotype EMS mutants in complex crop genomes

Background: Targeted Induced Loci Lesions IN Genomes (TILLING) is increasingly being used to generate and identify mutations in target genes of crop genomes. TILLING populations of several thousand lines have been generated in a number of crop species including Brassica rapa. Genetic analysis of mutants identified by TILLING requires an efficient, high-throughput and cost effective genotyping method to track the mutations through numerous generations. High resolution melt (HRM) analysis has been used in a number of systems to identify single nucleotide polymorphisms (SNPs) and insertion/deletions (IN/DELs) enabling the genotyping of different types of samples. HRM is ideally suited to high-throughput genotyping of multiple TILLING mutants in complex crop genomes. To date it has been used to identify mutants and genotype single mutations. The aim of this study was to determine if HRM can facilitate downstream analysis of multiple mutant lines identified by TILLING in order to characterise allelic series of EMS induced mutations in target genes across a number of generations in complex crop genomes. Results: We demonstrate that HRM can be used to genotype allelic series of mutations in two genes, BraA.CAX1a and BraA.MET1.a in Brassica rapa. We analysed 12 mutations in BraA.CAX1.a and five in BraA.MET1.a over two generations including a back-cross to the wild-type. Using a commercially available HRM kit and the Lightscanner™ system we were able to detect mutations in heterozygous and homozygous states for both genes. Conclusions: Using HRM genotyping on TILLING derived mutants, it is possible to generate an allelic series of mutations within multiple target genes rapidly. Lines suitable for phenotypic analysis can be isolated approximately 8-9 months (3 generations) from receiving M3 seed of Brassica rapa from the RevGenUK TILLING service.

Azotobacter genomes: the genome of Azotobacter chroococcum NCIMB 8003 (ATCC 4412)

The genome of the soil-dwelling heterotrophic N2-fixing Gram-negative bacterium Azotobacter chroococcum NCIMB 8003 (ATCC 4412) (Ac-8003) has been determined. It consists of 7 circular replicons totalling 5,192,291 bp comprising a circular chromosome of 4,591,803 bp and six plasmids pAcX50a, b, c, d, e, f of 10,435 bp, 13,852, 62,783, 69,713, 132,724, and 311,724 bp respectively. The chromosome has a G+C content of 66.27% and the six plasmids have G+C contents of 58.1, 55.3, 56.7, 59.2, 61.9, and 62.6% respectively. The methylome has also been determined and 5 methylation motifs have been identified. The genome also contains a very high number of transposase/inactivated transposase genes from at least 12 of the 17 recognised insertion sequence families. The Ac-8003 genome has been compared with that of Azotobacter vinelandii ATCC BAA-1303 (Av-DJ), a derivative of strain O, the only other member of the Azotobacteraceae determined so far which has a single chromosome of 5,365,318 bp and no plasmids. The chromosomes show significant stretches of synteny throughout but also reveal a history of many deletion/insertion events. The Ac-8003 genome encodes 4628 predicted protein-encoding genes of which 568 (12.2%) are plasmid borne. 3048 (65%) of these show > 85% identity to the 5050 protein-encoding genes identified in Av-DJ, and of these 99 are plasmid-borne. The core biosynthetic and metabolic pathways and macromolecular architectures and machineries of these organisms appear largely conserved including genes for CO-dehydrogenase, formate dehydrogenase and a soluble NiFe-hydrogenase. The genetic bases for many of the detailed phenotypic differences reported for these organisms have also been identified. Also many other potential phenotypic differences have been uncovered. Properties endowed by the plasmids are described including the presence of an entire aerobic corrin synthesis pathway in pAcX50f and the presence of genes for retro-conjugation in pAcX50c. All these findings are related to the potentially different environmental niches from which these organisms were isolated and to emerging theories about how microbes contribute to their communities.

Comparison of the genomes of two Xanthomonas pathogens with differing host specificities

The genus Xanthomonas is a diverse and economically important group of bacterial phytopathogens, belonging to the gamma-subdivision of the Proteobacteria. Xanthomonas axonopodis pv. citri (Xac) causes citrus canker, which affects most commercial citrus cultivars, resulting in significant losses worldwide. Symptoms include canker lesions, leading to abscission of fruit and leaves and general tree decline(1). Xanthomonas campestris pv. campestris (Xcc) causes black rot, which affects crucifers such as Brassica and Arabidopsis. Symptoms include marginal leaf chlorosis and darkening of vascular tissue, accompanied by extensive wilting and necrosis(2). Xanthomonas campestris pv. campestris is grown commercially to produce the exopolysaccharide xanthan gum, which is used as a viscosifying and stabilizing agent in many industries(3). Here we report and compare the complete genome sequences of Xac and Xcc. Their distinct disease phenotypes and host ranges belie a high degree of similarity at the genomic level. More than 80% of genes are shared, and gene order is conserved along most of their respective chromosomes. We identified several groups of strain-specific genes, and on the basis of these groups we propose mechanisms that may explain the differing host specificities and pathogenic processes.

Genetic relationships among Arachis hypogaea L. (AABB) and diploid Arachis species with AA and BB genomes

The cultivated peanut (Arachis hypogaea L.) is an allotetraploid, with two types of genomes, classified as AA and BB, according to cytogenetic characters. Similar genomes to those of A. hypogaea are found in the wild diploid species of section Arachis, which is one of the nine Arachis sections. The wild species have resistances to pests and diseases that affect the cultivated peanut and are a potential source of genes to increase the resistance levels in peanut. The aim of this study was to analyze the genetic variability within AA and BB genome species and to evaluate how they are related to each other and to A. hypogaea, using RAPD markers. Eighty-seven polymorphic bands amplified by ten 10-mer primers were analyzed. The species were divided into two major groups, and the AA and the BB genome species were, in general, separated from each other. The results showed that high variation is available within species that have genomes similar to the AA and the BB genomes of A. hypogaea.