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1.  Distinct Patterns of Expression and Evolution of Intronless and Intron-Containing Mammalian Genes 
Molecular Biology and Evolution  2010;27(8):1745-1749.
Comparison of expression levels and breadth and evolutionary rates of intronless and intron-containing mammalian genes shows that intronless genes are expressed at lower levels, tend to be tissue specific, and evolve significantly faster than spliced genes. By contrast, monomorphic spliced genes that are not subject to detectable alternative splicing and polymorphic alternatively spliced genes show similar statistically indistinguishable patterns of expression and evolution. Alternative splicing is most common in ancient genes, whereas intronless genes appear to have relatively recent origins. These results imply tight coupling between different stages of gene expression, in particular, transcription, splicing, and nucleocytosolic transport of transcripts, and suggest that formation of intronless genes is an important route of evolution of novel tissue-specific functions in animals.
PMCID: PMC2908711  PMID: 20360214
alternative splicing; intronless genes; monomorphic genes; polymorphic genes; mammalian gene evolution
2.  Trends in Prokaryotic Evolution Revealed by Comparison of Closely Related Bacterial and Archaeal Genomes ▿  
Journal of Bacteriology  2008;191(1):65-73.
In order to explore microevolutionary trends in bacteria and archaea, we constructed a data set of 41 alignable tight genome clusters (ATGCs). We show that the ratio of the medians of nonsynonymous to synonymous substitution rates (dN/dS) that is used as a measure of the purifying selection pressure on protein sequences is a stable characteristic of the ATGCs. In agreement with previous findings, parasitic bacteria, notwithstanding the sometimes dramatic genome shrinkage caused by gene loss, are typically subjected to relatively weak purifying selection, presumably owing to relatively small effective population sizes and frequent bottlenecks. However, no evidence of genome streamlining caused by strong selective pressure was found in any of the ATGCs. On the contrary, a significant positive correlation between the genome size, as well as gene size, and selective pressure was observed, although a variety of free-living prokaryotes with very close selective pressures span nearly the entire range of genome sizes. In addition, we examined the connections between the sequence evolution rate and other genomic features. Although gene order changes much faster than protein sequences during the evolution of prokaryotes, a strong positive correlation was observed between the “rearrangement distance” and the amino acid distance, suggesting that at least some of the events leading to genome rearrangement are subjected to the same type of selective constraints as the evolution of amino acid sequences.
PMCID: PMC2612427  PMID: 18978059
3.  ATGC: a database of orthologous genes from closely related prokaryotic genomes and a research platform for microevolution of prokaryotes 
Nucleic Acids Research  2008;37(Database issue):D448-D454.
The database of Alignable Tight Genomic Clusters (ATGCs) consists of closely related genomes of archaea and bacteria, and is a resource for research into prokaryotic microevolution. Construction of a data set with appropriate characteristics is a major hurdle for this type of studies. With the current rate of genome sequencing, it is difficult to follow the progress of the field and to determine which of the available genome sets meet the requirements of a given research project, in particular, with respect to the minimum and maximum levels of similarity between the included genomes. Additionally, extraction of specific content, such as genomic alignments or families of orthologs, from a selected set of genomes is a complicated and time-consuming process. The database addresses these problems by providing an intuitive and efficient web interface to browse precomputed ATGCs, select appropriate ones and access ATGC-derived data such as multiple alignments of orthologous proteins, matrices of pairwise intergenomic distances based on genome-wide analysis of synonymous and nonsynonymous substitution rates and others. The ATGC database will be regularly updated following new releases of the NCBI RefSeq. The database is hosted by the Genomics Division at Lawrence Berkeley National laboratory and is publicly available at
PMCID: PMC2686458  PMID: 18845571
4.  Genome-Wide Molecular Clock and Horizontal Gene Transfer in Bacterial Evolution 
Journal of Bacteriology  2004;186(19):6575-6585.
We describe a simple theoretical framework for identifying orthologous sets of genes that deviate from a clock-like model of evolution. The approach used is based on comparing the evolutionary distances within a set of orthologs to a standard intergenomic distance, which was defined as the median of the distribution of the distances between all one-to-one orthologs. Under the clock-like model, the points on a plot of intergenic distances versus intergenomic distances are expected to fit a straight line. A statistical technique to identify significant deviations from the clock-like behavior is described. For several hundred analyzed orthologous sets representing three well-defined bacterial lineages, the α-Proteobacteria, the γ-Proteobacteria, and the Bacillus-Clostridium group, the clock-like null hypothesis could not be rejected for ∼70% of the sets, whereas the rest showed substantial anomalies. Subsequent detailed phylogenetic analysis of the genes with the strongest deviations indicated that over one-half of these genes probably underwent a distinct form of horizontal gene transfer, xenologous gene displacement, in which a gene is displaced by an ortholog from a different lineage. The remaining deviations from the clock-like model could be explained by lineage-specific acceleration of evolution. The results indicate that although xenologous gene displacement is a major force in bacterial evolution, a significant majority of orthologous gene sets in three major bacterial lineages evolved in accordance with the clock-like model. The approach described here allows rapid detection of deviations from this mode of evolution on the genome scale.
PMCID: PMC516599  PMID: 15375139

Results 1-4 (4)