Detection and validation of single gene inversions

MOTIVATION: The biologically meaningful algorithmic study of genome rearrangement should take into account the distribution of sizes of the rearranged genomic fragments. In particular, it is important to know the prevalence of short inversions in order to understand the patterns of gene order disruption observed in comparative genomics. RESULTS: We find a large excess of short inversions, especially those involving a single gene, in comparison with a random inversion model. This is demonstrated through comparison of four pairs of bacterial genomes, using a specially-designed implementation of the Hannenhalli-Pevzner theory, and validated through experimentation on pairs of random genomes matched to the real pairs.     

Replication Orientation Affects the Rate and Direction of Bacterial Gene Evolution

In many bacterial genomes, the leading and lagging strands have different skews in base composition; for example, an excess of guanosine compared to cytosine on the leading strand. We find that Chlamydia genes that have switched their orientation relative to the direction of replication, for example by inversion, acquire the skew of their new ``host' strand. In contrast to most evolutionary processes, which have unpredictable effects on the sequence of a gene, replication-related skews reflect a directional evolutionary force that causes predictable changes in the base composition of switched genes, resulting in increased DNA and amino acid sequence divergence. Received: 27 April 2000 / Accepted: 1 August 2000     

Spatio‐temporal scaling of biodiversity and the species–time relationship in a stream fish assemblage

1. The increase of species richness with the area of the habitat sampled, that is the species–area relationship, and its temporal analogue, the species–time relationship (STR), are among the few general laws in ecology with strong conservation implications. However, these two scale‐dependent phenomena have rarely been considered together in biodiversity assessment, especially in freshwater systems. 2. We examined how the spatial scale of sampling influences STRs for a Central‐European stream fish assemblage (second‐order Bernecei stream, Hungary) using field survey data in two simulation‐based experiments. 3. In experiment one, we examined how increasing the number of channel units, such as riffles and pools (13 altogether), and the number of field surveys involved in the analyses (12 sampling occasions during 3 years), influence species richness. Complete nested curves were constructed to quantify how many species one observes in the community on average for a given number of sampling occasions at a given spatial scale. 4. In experiment two, we examined STRs for the Bernecei fish assemblage from a landscape perspective. Here, we evaluated a 10‐year reach level data set (2000–09) for the Bernecei stream and its recipient watercourse (third‐order Kemence stream) to complement results on experiment one and to explore the mechanisms behind the observed patterns in more detail. 5. Experiment one indicated the strong influence of the spatial scale of sampling on the accumulation of species richness, although time clearly had an additional effect. The simulation methodology advocated here helped to estimate the number of species in a diverse combination of spatial and temporal scale and, therefore, to determine how different scale combinations influence sampling sufficiency. 6. Experiment two revealed differences in STRs between the upstream (Bernecei) and downstream (Kemence) sites, with steeper curves for the downstream site. Equations of STR curves were within the range observed in other studies, predominantly from terrestrial systems. Assemblage composition data suggested that extinction–colonisation dynamics of rare, non‐resident (i.e. satellite) species influenced patterns in STRs. 7. Our results highlight that the determination of species richness can benefit from the joint consideration of spatial and temporal scales in biodiversity inventory surveys. Additionally, we reveal how our randomisation‐based methodology may help to quantify the scale dependency of diversity components (α, β, γ) in both space and time, which have critical importance in the applied context.     

The mitochondrial genome of Pocillopora (Cnidaria: Scleractinia) contains two variable regions: the putative D-loop and a novel ORF of unknown function

The complete mitochondrial genomes of two individuals attributed to different morphospecies of the scleractinian coral genus Pocillopora have been sequenced. Both genomes, respectively 17,415 and 17,422 nt long, share the presence of a previously undescribed ORF encoding a putative protein made up of 302 amino acids and of unknown function. Surprisingly, this ORF turns out to be the second most variable region of the mitochondrial genome (1% nucleotide sequence difference between the two individuals) after the putative control region (1.5% sequence difference). Except for the presence of this ORF and for the location of the putative control region, the mitochondrial genome of Pocillopora is organized in a fashion similar to the other scleractinian coral genomes published to date. For the first time in a cnidarian, a putative second origin of replication is described based on its secondary structure similar to the stem-loop structure of O(L), the origin of L-strand replication in vertebrates.