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From experimental, structural probability distributions to the theoretical causality analysis of molecular changes

Daniluk P., Dziubiński M., Lesyng B., Hallay-Suszek M., Rakowski F., Walewski Ł.

Computer Assisted Methods in Engineering and Science

2012

Vol. 19, no. 3

257-276

A brief overview of causality analysis (CA) methods applied to MD simulations data for model biomolecular systems is presented. A CausalMD application for postprocessing of MD data was designed and implemented. MD simulations of two model systems, porphycene (ab initio MD) and HIV-1 protease (coarse-grained MD) were carried out and analyzed. Granger’s causality methodology based on a Multivariate Autoregressive (MVAR) formalism, followed by the Directed Transfer Function (DTF) analysis was applied. A novel approach based on the descriptors of local structure was also presented and prelim- inary results were reported. Casuality analyses are required for a better understanding of biomolecular functioning mechanisms. In particular, such analyses can link physics-based structural dynamics with functions inferred from molecular evolution processes. Current limitations and future developments of the presented methodologies are indicated.

Genetic variation and molecular evolution of endangered Kozlov.s pika (Ochotona koslowi Buchner) based on mitochondrial cytochrome b gene

Lin G., Ci H., Thirgood S., Zhang T., Su J.

Polish Journal of Ecology

2010

Vol. 58, nr 3

563-568

Kozlov's pika is a rare and endangered lagomorph species with a limited distribution in the southern Kunlun Mountains in western China. Because of its endangered status, Kozlov's pika is considered a priority species for research and conservation action. Genetic variation and molecular evolution of the Kozlov's pika were studied based on a total of 14 individuals from four locations along the eastern boundary between Xinjiang and Tibet province (35.20-36.48[degrees]N, 86.08-83.04[degrees]E) on extremely high elevation (usually over 4800 m a.s.l.). The density of local populations was about 3-4 per ha, living in a typical alpine desert grassland habitat. The complete mitochondrial cytochrome b (cytb) gene was amplified and sequenced. Based on the cytb gene sequences the genetic variation and molecular evolution were analyzed. Unexpected high haplotype diversity (0.956 [plus or minus] 0.045) but low nucleotide diversity (0.00537 [plus or minus] 0.00126) was found, indicating past demographic expansion. Significant partitioning of variance (P <0.01) among populations (46.7%), and within populations (53.3%), indicating low level of genetic differentiations among local populations. Our results gave an optimistic survival status of Kozlov's pika at the genetic level. Bayes Empirical Bayes analysis with model M2a and M8 detected three positively selected amino acid sites at the significance level of 0.05. The mutant types with either or both of the mutations aspartic acid to asparagine and glutamic acid to lysine had higher isoelectric point values. We suggested these mutant types might have biological significance to help individuals to adapt to the extremely high elevation habitats.

Sampling Properties of Estimators of Nucleotide Diversity at Discovered snp Sites

Renwick A., Bonnen P. E., Trikka D., Nelson D. L., Chakraborty R., Kimmel M.

International Journal of Applied Mathematics and Computer Science

2003

Vol. 13, no 3

385-394

SNP sites are generally discovered by sequencing regions of the human genome in a limited number of individuals. This may leave SNP sites present in the region, but containing rare mutant nucleotides, undetected. Consequently, estimates of nucleotide diversity obtained from assays of detected SNP sites are biased. In this research we present a statistical model of the SNP discovery process, which is used to evaluate the extent of this bias. This model involves the symmetric Beta distribution of variant frequencies at SNP sites, with an additional probability that there is no SNP at any given site. Under this model of allele frequency distributions at SNP sites, we show that nucleotide diversity is always underestimated. However, the extent of bias does not seem to exceed 10-15% for the analyzed data. We find that our model of allele frequency distributions at SNP sites is consistent with SNP statistics derived based on new SNP data at ATM, BLM, RQL and WRN gene regions. The application of the theory to these new SNP data as well as to the literature data at the LPL gene region indicates that in spite of ascertainment biases, the observed differences of nucleotide diversity across these gene regions are real. This provides interesting evidence concerning the heterogeneity of the rates of nucleotide substitution across the genome.