Presented here is the complete genome sequence of Thiomicrospira crunogena XCL-2, representative of ubiquitous chemolithoautotrophic sulfur-oxidizing bacteria isolated from deep-sea hydrothermal vents. This gammaproteobacterium has a single chromosome (2,427,734 base pairs), and its genome illustrates many of the adaptations that have enabled it to thrive at vents globally. It has 14 methyl-accepting chemotaxis protein genes, including four that may assist in positioning it in the redoxcline. A relative abundance of coding sequences (CDSs) encoding regulatory proteins likely control the expression of genes encoding carboxysomes, multiple dissolved inorganic nitrogen and phosphate transporters, as well as a phosphonate operon, which provide this species with a variety of options for acquiring these substrates from the environment. Thiom. crunogena XCL-2 is unusual among obligate sulfur-oxidizing bacteria in relying on the Sox system for the oxidation of reduced sulfur compounds. The genome has characteristics consistent with an obligately chemolithoautotrophic lifestyle, including few transporters predicted to have organic allocrits, and Calvin-Benson-Bassham cycle CDSs scattered throughout the genome.

BackgroundAdaptive alleles may rise in frequency as a consequence of positive selection, creating a pattern of decreased variation in the neighboring loci, known as a selective sweep. When the region containing this pattern is compared to another population with no history of selection, a rise in variance of allele frequencies between populations is observed. One challenge presented by large genome-wide datasets is the ability to differentiate between patterns that are remnants of natural selection from those expected to arise at random and/or as a consequence of selectively neutral demographic forces acting in the population.FindingsSmileFinder is a simple program that looks for diversity and divergence patterns consistent with selection sweeps by evaluating allele frequencies in windows, including neighboring loci from two or more populations of a diploid species against the genome-wide neutral expectation. The program calculates the mean of heterozygosity and FST in a set of sliding windows of incrementally increasing sizes, and then builds a resampled distribution (the baseline) of random multi-locus sets matched to the sizes of sliding windows, using an unrestricted sampling. Percentiles of the values in the sliding windows are derived from the superimposed resampled distribution. The resampling can easily be scaled from 1 K to 100 M; the higher the number, the more precise the percentiles ascribed to the extreme observed values.ConclusionsThe output from SmileFinder can be used to plot percentile values to look for population diversity and divergence patterns that may suggest past actions of positive selection along chromosome maps, and to compare lists of suspected candidate genes under random gene sets to test for the overrepresentation of these patterns among gene categories. Both applications of the algorithm have already been used in published studies. Here we present a publicly available, open source program that will serve as a useful tool for preliminary scans of selection using worldwide databases of human genetic variation, as well as population datasets for many non-human species, from which such data is rapidly emerging with the advent of new genotyping and sequencing technologies.

Using the (near) complete genome sequences of the yeasts Candida albicans, Saccharomyces cerevisiae, and Schizosaccharomyces pombe, we address the evolution of a unique genetic code change, which involves decoding of the standard leucine-CTG codon as serine in Candida spp. By using two complementary comparative genomics approaches, we have been able to shed new light on both the origin of the novel Candida spp. Ser-tRNA CAG , which has mediated CTG reassignment, and on the evolution of the CTG codon in the genomes of C. albicans, S. cerevisiae, and S. pombe. Sequence analyses of newly identified tRNAs from the C. albicans genome demonstrate that the Ser-tRNA CAG is derived from a serine and not a leucine tRNA in the ancestor yeast species and that this codon reassignment occurred ∼170 million years ago, but the origin of the Ser-tRNA CAG is more ancient, implying that the ancestral Leu-tRNA that decoded the CTG codon was lost after the appearance of the Ser-tRNA CAG . Ambiguous CTG decoding by the Ser-tRNA CAG combined with biased AT pressure forced the evolution of CTG into TTR codons and have been major forces driving evolution of the CTN codon family in C. albicans. Remarkably, most of the CTG codons present in extant C. albicans genes are encoded by serine and not leucine codons in homologous S. cerevisiae and S. pombe genes, indicating that a significant number of serine TCN and AGY codons evolved into CTG codons either directly by simultaneous double mutations or indirectly through an intermediary codon. In either case, CTG reassignment had a major impact on the evolution of the coding component of the Candida spp. genome.

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The genetic code has the remarkable property of error minimization, whereby the arrangement of amino acids to codons is highly efficient at reducing the deleterious effects of random point mutations and transcriptional and translational errors. Whether this property has been explicitly selected for is unclear. Here, three scenarios of genetic code evolution are examined, and their effects on error minimization assessed. First, a simple model of random stepwise addition of physicochemically similar amino acids to the code is demonstrated to result in substantial error minimization. Second, a model of random addition of physicochemically similar amino acids in a codon expansion scheme derived from the Ambiguity Reduction Model results in improved error minimization over the first model. Finally, a recently introduced 213 Model of genetic code evolution is examined by the random addition of physicochemically similar amino acids to a primordial core of four amino acids. Under certain conditions, 22% of the resulting codes produced according to the latter model possess equivalent or superior error minimization to the standard genetic code. These analyses demonstrate that a substantial proportion of error minimization is likely to have arisen neutrally, simply as a consequence of code expansion, facilitated by duplication of the genes encoding adaptor molecules and charging enzymes. This implies that selection is at best only partly responsible for the property of error minimization. These results caution against assuming that selection is responsible for every beneficial trait observed in living organisms.