Munirul Islam

Phylogenomic analyses reveal convergent patterns of adaptive evolution in elephant and human ancestries

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 genes 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.

Distinct genomic signatures of adaptation in pre-and postnatal environments during human evolution

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.

Development and evaluation of new mask protocols for gene expression profiling in humans and chimpanzees

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.

PhyQL: A Web-Based Phylogenetic Visual Query Engine

Biologists are often interested to query published phylogenetic data for research purposes. PhyQL, a Web-based visual phylogenetic query engine, can be quite useful on this regard. In PhyQL, we have implemented a data model and a visual query language to interact with hierarchically classified tree elements. To hide textual query submission, PhyQL provides a design interface to build the query visually. The users can build simple to complex queries using the query operators. PhyQL separates the application layer from the data layer by a logic layer leading to reduced query tools development time. Moreover,PhyQL provides interactive tree views in radial, phylogram and dendrogram layout. It can be accessed online at http://integra.cs.wayne.edu/softwares/phyql/.

Clinical Pattern of Neonatal Infections

Neonatal infection is an important cause of morbidity and mortality among infants. Clinical pattern of neonatal infection in the neonatal unit of Institute of Post Graduate Medicine & Research (IPGM&R), Dhaka has been reported. Out of total 2160 Neonatal admission from July 1991 to June 1993, 320 (14.8%) cases of neonatal infections were found. Septicemia was the commonest type found in 118 (5.5%) cases. Other infections included umbilical sepsis (14.7%), Skin infections (1.6%), Meningitis (1.2%). Tetanus neonatorum were not included. Out of 320 cases, 20 patients died (6.2%). Preterm low birth weight and birth asphyxia were the common risk factors. DOI: http://dx.doi.org/10.3329.bjms.v1i3.17909 Normal 0 false false false EN-US X-NONE AR-SA