系统发生学与进化生物学杂志

The need of giving rise to a stable and soluble protein system generates constraints that limit the mutation space by imposing a co-variation structure across different residues. While protein scientists widely use this property in order to predict protein-protein interaction and peptide-receptor pairing, there is no equivalent interest to make use of mutation correlation structures to get information inside single protein systems. Here we present a methodological essay that, using a statistical approach typical of medicinal chemistry, faces the problem to locate ‘mutational correlation units’ in a viral RNA polymerase. These ‘units’ are invisible to ordinary sequence alignment methods and can be important in virus characterization and vaccine developments as well as for evolution theorists.

Currently data mining is an essential tool to discover the hidden data and important patterns from a large data set. The present work is a pilot study that compares the result of sequence based phylogenetic study and some of the physicochemical and structural feature based clustering of Laccase enzyme sequences. Total of 50 homologous sequences were obtained specific to each of the organism like plant, fungi and bacteria. Multiple sequences alignment of sequences was performed followed by phylogenetic tree construction and consistency study also to observe the major clusters. Again the major domain and motif analysis was done to support the study in the divergence pattern of Laccase enzyme sequences. There after 13 numbers of physicochemical and structural features were computed for each enzyme sequences. Then data normalisation and k-means clustering technique revealed that the fungi, bacteria and plant were obtained in three distinct clusters. The analysis indicates that the result of sequence based classification is in a good agreement with physicochemical basis of classification of proteins. The methods can be further optimised for different clustering algorithm to obtain specific physicochemical features that would help to classification of proteins.

Teeth are quintessential elements of evolutionary evidence imposed by ecological niches and determined by dietary demands. By virtue of their postmortem durability, teeth are often the only remaining remnants of long extinct species to provide presumption of their previous paleontological existence. That teeth are intimately associated with dietary intake provides unambiguous evidence of ancient ambient environments and extinct cultural practices. Spectroscopic analysis of enamel and attritional dental wear reveal archaic food composition. Genetic inheritance patterns contained in varying dental configurations reveal permutations of evolutionary trends. Analysis of the preserved mitochondrial DNA of archaic dental pulp tissue of long–deceased antecedents and historical figures of mankind is the current research focus of phylogenetics and evolutionary biology.

Many rapid radiations, or bushes, throughout the Tree of Life remain unresolved. Here, we investigated how the shape of a bush interacts with two key processes - coalescence and mutation - that can lead to errors in phylogenetic inference under specific conditions. For this study, we focused on the tradeoff between sampling more individuals per species and sampling more loci as well as the utility of a species tree method based upon gene tree reconciliation and the concatenation of multiple loci for resolving bushes. We examined different bush shapes, varying both the speciation rate during the radiation and the depth of the radiation, to encompass a broad range of situations. Using simulations based upon parameters derived from empirical studies, we investigated the performance of phylogenetic analyses under different conditions to identify approaches with the greatest potential to resolve difficult phylogenies. Sampling a single individual for more loci outperformed sampling multiple individuals for one locus in all cases except the most recent radiations. We found that error due to homoplastic mutations increased with depth, while error due to the coalescent process remained unchanged. These simulations also revealed that, for certain ancient bushes, analyses of concatenated data matrices surprisingly resulted in more accurate phylogenies than gene tree reconciliation. The poor performance of gene tree reconciliation in this study appeared to reflect the poor estimation of gene trees, not the superiority of concatenation per se. Our results suggest concatenation remains a useful approximate method for species tree estimation, even for rapid evolutionary radiations. However, improved estimation of gene trees combined with use of gene tree reconciliation has the greatest potential for resolving the remaining bushes of the Tree of Life.