In vivo rat assay: bone remodeling and steroid effects on juvenile bone by pQCT quantification in 7 days

Anesthetized Sprague-Dawley weanling rats were scanned for bone mineral density (BMD) values after 7 days of treatment to determine whether resorption/growth at the proximal tibia can be quantified by peripheral quantitative computed tomography scanning techniques. Because the weanling rat is in a rapid growth stage, all groups showed significant increases in change from baseline values of BMD. Bisphosphonate treatment produced significant dose-related changes in BMD with average increases of 195 and 241% (10 and 20 microg/kg) vs. 86% in control rats. We further characterized this model to determine effects of steroids on growing bone. Graded doses of glucocorticoid (3.5, 7.0, 10.5, 14.0, 28.0, and 42.0 mg x kg(-1) x wk(-1)) caused no significant differences in trabecular BMD in 7 days between control and treated rats. Significant decreases in growth (weights) and increases in cortical bone area were observed, indicating that this model may be useful in comparing effects of nonsteroid, anti-inflammatory alternatives on juvenile bone. Although the relevance of this model to adult disease remains to be elucidated, it also provides a tool for mechanistic evaluation of therapeutic modalities or efficacy assessment for dose selection for longerterm models.     

A web server to locate periodicities in a sequence

Summary : FT is a tool written in C++, which implements the Fourier analysis method to locate periodicities in aminoacid or DNA sequences. It is provided for free public use on a WWW server with a Java interface. Availability : The server address is http://o2.db. uoa.gr/FT Contact : shamodr@atlas.uoa.gr      

Evolution of population structure in a highly social top predator, the killer whale

Intraspecific resource partitioning and social affiliations both have the potential to structure populations, though it is rarely possible to directly assess the impact of these mechanisms on genetic diversity and population divergence. Here, we address this for killer whales (Orcinus orca), which specialize on prey species and hunting strategy and have long-term social affiliations involving both males and females. We used genetic markers to assess the structure and demographic history of regional populations and test the hypothesis that known foraging specializations and matrifocal sociality contributed significantly to the evolution of population structure. We find genetic structure in sympatry between populations of foraging specialists (ecotypes) and evidence for isolation by distance within an ecotype. Fitting of an isolation with migration model suggested ongoing, low-level migration between regional populations (within and between ecotypes) and small effective sizes for extant local populations. The founding of local populations by matrifocal social groups was indicated by the pattern of fixed mtDNA haplotypes in regional populations. Simulations indicate that this occurred within the last 20,000 years (after the last glacial maximum). Our data indicate a key role for social and foraging behavior in the evolution of genetic structure among conspecific populations of the killer whale.     

On the number of New World founders: a population genetic portrait of the peopling of the Americas

The founding of New World populations by Asian peoples is the focus of considerable archaeological and genetic research, and there persist important questions on when and how these events occurred. Genetic data offer great potential for the study of human population history, but there are significant challenges in discerning distinct demographic processes. A new method for the study of diverging populations was applied to questions on the founding and history of Amerind-speaking Native American populations. The model permits estimation of founding population sizes, changes in population size, time of population formation, and gene flow. Analyses of data from nine loci are consistent with the general portrait that has emerged from archaeological and other kinds of evidence. The estimated effective size of the founding population for the New World is fewer than 80 individuals, approximately 1% of the effective size of the estimated ancestral Asian population. By adding a splitting parameter to population divergence models it becomes possible to develop detailed portraits of human demographic history. Analyses of Asian and New World data support a model of a recent founding of the New World by a population of quite small effective size.     

Increased immortalization‐upregulated protein 2 (IMUP‐2) by hypoxia induces apoptosis of the trophoblast and pre‐eclampsia

In regulation of the developmental process, the balance between cellular proliferation and cell death is critical. Placental development tightly controls this mechanism, and increased apoptosis of placental trophoblasts can cause a variety of gynecological diseases. Members of the immortalization‐upregulated protein (IMUP) family are nuclear proteins implicated in SV40‐mediated immortalization and cellular proliferation; however, the mechanisms by which their expression is regulated in placental development are still unknown. We compared IMUP‐2 expression in normal and pre‐eclamptic placental tissues and evaluated the function of IMUP‐2 in HTR‐8/SVneo trophoblast cells under hypoxic conditions. IMUP‐2 was expressed in syncytiotrophoblasts and syncytial knots of the placental villi. IMUP‐2 expression was significantly higher in preterm pre‐eclampsia patients than in patients who went to term (P < 0.001); however, we observed no differences in IMUP‐2 expression between normal term patients with and without pre‐eclampsia. Hypoxic conditions increased apoptosis of HTR8/SVneo trophoblast cells and induced IMUP‐2 expression. Also, apoptosis of HTR‐8/SVneo trophoblast cells was increased after IMUP‐2 gene transfection. These results suggest that IMUP‐2 expression is specifically elevated in preterm pre‐eclampsia and under hypoxic conditions, and that IMUP‐2 induces apoptosis of the trophoblast. Therefore, IMUP‐2 might have functional involvement in placental development and gynecological diseases such as pre‐eclampsia. J. Cell. Biochem. 110: 522–530, 2010. © 2010 Wiley‐Liss, Inc.     

Estimating Divergence Parameters With Small Samples From a Large Number of Loci

Most methods for studying divergence with gene flow rely upon data from many individuals at few loci. Such data can be useful for inferring recent population history but they are unlikely to contain sufficient information about older events. However, the growing availability of genome sequences suggests a different kind of sampling scheme, one that may be more suited to studying relatively ancient divergence. Data sets extracted from whole-genome alignments may represent very few individuals but contain a very large number of loci. To take advantage of such data we developed a new maximum-likelihood method for genomic data under the isolation-with-migration model. Unlike many coalescent-based likelihood methods, our method does not rely on Monte Carlo sampling of genealogies, but rather provides a precise calculation of the likelihood by numerical integration over all genealogies. We demonstrate that the method works well on simulated data sets. We also consider two models for accommodating mutation rate variation among loci and find that the model that treats mutation rates as random variables leads to better estimates. We applied the method to the divergence of Drosophila melanogaster and D. simulans and detected a low, but statistically significant, signal of gene flow from D. simulans to D. melanogaster.IN the study of speciation researchers often inquire of the extent that populations have exchanged genes as they diverged and on the time since populations began to diverge. Answers to questions about historical divergence and gene flow potentially lie in patterns of genetic variation that are found in present day populations. To bridge the gap between population history and current genetic data, population geneticists can make use of a gene genealogy, G, a bifurcating tree that represents the history of ancestry of sampled gene copies. The probability of a particular value of G can be calculated for a particular parameter set using coalescent models. Then given a particular genealogy, genetic variation can be examined using a mutation model that is appropriate for the kind of data being used. Finally by considering multiple values of G, the connection can be made between the population evolution history and the data. A mathematical representation that treats G as a key interstitial variable was given by Felsenstein (1988),(1)where X represents the sequence data, G represents gene genealogy, Ψ represents the set of all possible genealogies, and Θ represents the vector of population parameters included in the model.Unless sample sizes are very small, (1) cannot be solved analytically, and so considerable effort has gone into finding approximate solutions (Kuhner et al. 1995; Griffiths and Marjoram 1996; Wilson and Balding 1998). One general approach is to sample genealogies using a Markov chain Monte Carlo (MCMC) simulation. This is the approach developed by Kuhner and colleagues (Kuhner et al. 1995) and that has since been extended to models with migration (Beerli and Felsenstein 1999, 2001; Nielsen and Wakeley 2001). A general problem for these methods is that they usually require long running times to generate sufficiently large and independent samples, especially when the MCMC simulation is mixing slowly.With fast-improving DNA sequencing techniques, more and more genome sequences are becoming available, and alignments of these whole-genome sequences are a very useful source of information for the study of divergence. However, traditional MCMC methods are likely to be slow on genome-scale data because running times are proportional to the number of loci. To overcome this difficulty Yang developed a likelihood method (Yang 2002) for data sets containing one sample from each of the three populations at every locus. This method uses numerical integration to calculate the likelihood function in Equation 1. By using a very large number of loci, the method can make up for using a very small number of individuals (i.e., genomes).Yang''s method is based on a divergence model that assumes no gene flow between separated populations. However, there are many situations where gene flow may have been occurring and where it is preferable to include it within the divergence model. One model that has been used a lot in this context is the isolation-with-migration (IM) model, which incorporates both population separation and migration (Nielsen and Wakeley 2001). Under an IM model the genealogies include not only some fixed number of coalescent events and speciation events, but also any possible number of migration events. The potential for very large numbers of migration events complicates the sample space of G and makes the numerical integration seemingly impossible. Innan and Watanabe (2006) circumvent this problem by using a recursion method to estimate the coalescent rates on a series of time points. In their recursion, the accuracy in calculating coalescent rate at one time point depends on the accuracy of calculations at previous time points, and this may impair the precision of the overall likelihood calculation. Therefore we developed a method that relies on numerical integration to calculate the likelihood under an IM model. We tested the accuracy of this method on simulated data sets of various sample sizes and applied it to a genome alignment of Drosophila melanogaster and D. simulans (with D. yakuba as an outgroup).