Specific sets of brain-expressed genes, such as aerobic energy metabolism genes, evolved adaptively in the ancestry of humans and may have evolved adaptively in the ancestry of other large-brained mammals. The recent addition of genomes from two afrotherians (elephant and tenrec) to the expanding set of publically available sequenced mammalian genomes provided an opportunity to test this hypothesis. Elephants resemble humans by having large brains and long life spans; tenrecs, in contrast, have small brains and short life spans. Thus, we investigated whether the phylogenomic patterns of adaptive evolution are more similar between elephant and human than between either elephant and tenrec lineages or human and mouse lineages, and whether aerobic energy metabolism genes are especially well represented in the elephant and human patterns. Our analyses encompassed ≈6,000 genes in each of these lineages with each gene yielding extensive coding sequence matches in interordinal comparisons. Each gene's nonsynonymous and synonymous nucleotide substitution rates and dN/dS ratios were determined. Then, from gene ontology information on genes with the higher dN/dS ratios, we identified the more prevalent sets of genes that belong to specific functional categories and that evolved adaptively. Elephant and human lineages showed much slower nucleotide substitution rates than tenrec and mouse lineages but more adaptively evolved genes. In correlation with absolute brain size and brain oxygen consumption being largest in elephants and next largest in humans, adaptively evolved aerobic energy metabolism genes were most evident in the elephant lineage and next most evident in the human lineage.

The human genome evolution project seeks to reveal the genetic underpinnings of key phenotypic features that are distinctive of humans, such as a greatly enlarged cerebral cortex, slow development, and long life spans. This project has focused predominantly on genotypic changes during the 6-million-year descent from the last common ancestor (LCA) of humans and chimpanzees. Here, we argue that adaptive genotypic changes during earlier periods of evolutionary history also helped shape the distinctive human phenotype. Using comparative genome sequence data from 10 vertebrate species, we find a signature of human ancestry-specific adaptive evolution in 1,240 genes during their descent from the LCA with rodents. We also find that the signature of adaptive evolution is significantly different for highly expressed genes in human fetal and adult-stage tissues. Functional annotation clustering shows that on the ape stem lineage, an especially evident adaptively evolved biological pathway contains genes that function in mitochondria, are crucially involved in aerobic energy production, and are highly expressed in two energy-demanding tissues, heart and brain. Also, on this ape stem lineage, there was adaptive evolution among genes associated with human autoimmune and aging-related diseases. During more recent human descent, the adaptively evolving, highly expressed genes in fetal brain are involved in mediating neuronal connectivity. Comparing adaptively evolving genes from pre-and postnatal-stage tissues suggests that different selective pressures act on the development vs. the maintenance of the human phenotype.fetal ͉ human disease ͉ mitochondria ͉ placenta ͉ thyroid

The insertion sequence element IS 8301 isolated from the radiation resistant bacterium Deinococcus radiodurans strain KD8301 was characterized. IS 8301 is comprised of 1,736-bp, lacks terminal inverted repeats and does not duplicate target DNA upon its insertion. The amino acid sequence homology of two open reading frames encoded in IS 8301 indicates that this insertion sequence element belongs to the IS 200 /IS 605 group. There were seven loci completely identical with the IS 8301 sequence in the published D. radiodurans R 1 genome sequence. The genome distribution profiles of IS 8301 in strain KD8301 as well as in the three different laboratory isolates (KR 1 , MR 1 , and R 1 ) of wild-type D. radiodurans were investigated using genomic hybridization analysis. At least 21 strong hybridization signals were detected in strain KD8301 while only one hybridization signal was detected in strain KR 1 , the parent strain of KD8301. In strain MR 1 , a different wild-type isolate, six strong hybridization signals were detected. In spite of the identification of seven copies of IS 8301 in the published D. radiodurans R 1 genome sequence, only one hybridization signal was detected in strain R 1 purchased from American Type Culture Collection. Using inverse PCR and sequencing analyses, total 13 different insertion loci of IS 8301 in the D. radiodurans genome were identified. Sequence comparison of the flanking region of insertion sites indicated that the sequence 5'-TTGAT-3' preceded the left end of IS 8301 in all cases.

The OCPAT program facilitates large-scale evolutionary and phylogenetic analyses of entire biological processes, pathways, and diseases.

BackgroundCross-species gene expression analyses using oligonucleotide microarrays designed to evaluate a single species can provide spurious results due to mismatches between the interrogated transcriptome and arrayed probes. Based on the most recent human and chimpanzee genome assemblies, we developed updated and accessible probe masking methods that allow human Affymetrix oligonucleotide microarrays to be used for robust genome-wide expression analyses in both species. In this process, only data from oligonucleotide probes predicted to have robust hybridization sensitivity and specificity for both transcriptomes are retained for analysis.ResultsTo characterize the utility of this resource, we applied our mask protocols to existing expression data from brains, livers, hearts, testes, and kidneys derived from both species and determined the effects probe numbers have on expression scores of specific transcripts. In all five tissues, probe sets with decreasing numbers of probes showed non-linear trends towards increased variation in expression scores. The relationships between expression variation and probe number in brain data closely matched those observed in simulated expression data sets subjected to random probe masking. However, there is evidence that additional factors affect the observed relationships between gene expression scores and probe number in tissues such as liver and kidney. In parallel, we observed that decreasing the number of probes within probe sets lead to linear increases in both gained and lost inferences of differential cross-species expression in all five tissues, which will affect the interpretation of expression data subject to masking.ConclusionWe introduce a readily implemented and updated resource for human and chimpanzee transcriptome analysis through a commonly used microarray platform. Based on empirical observations derived from the analysis of five distinct data sets, we provide novel guidelines for the interpretation of masked data that take the number of probes present in a given probe set into consideration. These guidelines are applicable to other customized applications that involve masking data from specific subsets of probes.