Mitochondrial DNA Sequence Analyses and Phylogenetic Relationships Among Two Nigerian Goat Breeds and the South African Kalahari Red

The first hypervariable (HV1) region of mitochondrial DNA (mtDNA) of two popular Nigerian goat breeds: West African Dwarf (WAD) (n = 35) and Red Sokoto (RS) (n = 37) and one exotic breed: Kalahari Red (KR) (n = 38) imported from South Africa were sequenced to investigate sequence diversity, genetic structure, origin, and demographic history of the populations. A total of 68 polymorphic sites were found in 110 sequences that grouped into 68 haplotypes. Average haplotype and nucleotide diversities for all breeds were 0.982 ± 0.005 and 0.02350 ± 0.00213, respectively. Phylogenetic analysis revealed two mtDNA lineages (A and B). Lineage A was predominant and included all haplotypes from WAD and RS and 5 out of 11 haplotypes of KR goats. The remaining haplotypes (6 Amills M, Ramírez O, Tomàs A, et al. Mitochondrial DNA diversity and origins of South and Central American goats. Animal Genetics 2009; 40(3): 315–322.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) of KR belong to lineage B. The analysis of molecular variance revealed a high-within breed genetic variance of 82.4% and a low-between breed genetic variance of 17.6%. The three breeds clustered with Capra aegagrus as their wild ancestor. Mismatch distribution analysis showed that WAD, RS and haplogroup A have experienced population expansion events. The study has revealed very high diversity within the three breeds which are not strongly separated from each other based on mtDNA analysis. The information obtained on the genetic structure of the breeds will be useful in planning improvement and conservation programs for the local populations.     

Genetic Diversity and Population Structure Analysis Between Indian Red Jungle Fowl and Domestic Chicken Using Microsatellite Markers

The present study was conducted to assess the genetic diversity, population structure, and relatedness in Indian red jungle fowl (RJF, Gallus gallus murgi) from northern India and three domestic chicken populations (gallus gallus domesticus), maintained at the institute farms, namely White Leghorn (WL), Aseel (AS) and Red Cornish (RC) using 25 microsatellite markers. All the markers were polymorphic, the number of alleles at each locus ranged from five (MCW0111) to forty-three (LEI0212) with an average number of 19 alleles per locus. Across all loci, the mean expected heterozygosity and polymorphic information content were 0.883 and 0.872, respectively. Population-specific alleles were found in each population. A UPGMA dendrogram based on shared allele distances clearly revealed two major clusters among the four populations; cluster I had genotypes from RJF and WL whereas cluster II had AS and RC genotypes. Furthermore, the estimation of population structure was performed to understand how genetic variation is partitioned within and among populations. The maximum ?K value was observed for K = 4 with four identified clusters. Furthermore, factorial analysis clearly showed four clustering; each cluster represented the four types of population used in the study. These results clearly, demonstrate the potential of microsatellite markers in elucidating the genetic diversity, relationships, and population structure analysis in RJF and domestic chicken populations.     

A simulation model of the Devils Hole pupfish population using monthly length-frequency distributions

The Devils Hole pupfish, Cyprinodon diabolis, is a federally-endangered fish that is endemic to Devils Hole, a discontiguous part of Death Valley National Park in Nye County, Nevada. Due to its status, Devils Hole pupfish monitoring must be non-obtrusive and thereby exclude techniques that require handling fish. Due to a recent decline in pupfish abundance, Devils Hole pupfish managers have expressed a need for a model that describes population dynamics. This population model would be used to identify vulnerable life history stage(s) and inform management actions. We constructed a set of individual-based simulation models designed to explore effects of population processes and evaluate assumptions. We developed a baseline model, whose output best resembled both observed length-frequency data and predicted intra-annual abundance patterns. We then ran simulations with 5 % increases in egg-larval, juvenile, and adult survival rates to better understand Devils Hole pupfish life history, thereby helping identify vulnerable life history stages that should become the target of management actions. Simulation models with temporally constant adult, juvenile, and egg-larval survival rates were able to reproduce observed length-frequency distributions and predicted intra-annual population patterns. In particular, models with monthly adult and juvenile survival rates of 80 % and an egg-larval survival rate of 4.7 % replicated patterns in observed data. Population growth was most affected by 5 % increases in egg-larval survival, whereas adult and juvenile survival rates had similar but lesser effects on population growth. Outputs from the model were used to assess factors suspected of influencing Devils Hole pupfish population decline.     

Coupling-induced population synchronization in an excitatory population of subthreshold Izhikevich neurons

We consider an excitatory population of subthreshold Izhikevich neurons which exhibit noise-induced firings. By varying the coupling strength J, we investigate population synchronization between the noise-induced firings which may be used for efficient cognitive processing such as sensory perception, multisensory binding, selective attention, and memory formation. As J is increased, rich types of population synchronization (e.g., spike, burst, and fast spike synchronization) are found to occur. Transitions between population synchronization and incoherence are well described in terms of an order parameter $\mathcal{O}$ . As a final step, the coupling induces oscillator death (quenching of noise-induced spikings) because each neuron is attracted to a noisy equilibrium state. The oscillator death leads to a transition from firing to non-firing states at the population level, which may be well described in terms of the time-averaged population spike rate $\overline{R}$ . In addition to the statistical-mechanical analysis using $\mathcal{O}$ and $\overline{R}$ , each population and individual state are also characterized by using the techniques of nonlinear dynamics such as the raster plot of neural spikes, the time series of the membrane potential, and the phase portrait. We note that population synchronization of noise-induced firings may lead to emergence of synchronous brain rhythms in a noisy environment, associated with diverse cognitive functions.     

Could the intrinsic rate of increase represent the fitness in terrestrial ectotherms?

The intrinsic rate of increase (r_m) has been considered as an important indicator of fitness in terrestrial ectotherms since long. It is actually an equivalent to the instantaneous growth rate of the exponential equation for describing the density-independent population growth. In terrestrial ectotherms, r_m has been demonstrated to be temperature-dependent. The temperature at which r_m was maximal, was considered to be the “optimal” temperature for fitness in Amarasekare and Savage (2012), but this definition needs further analysis. Only r_m cannot provide thorough representation of fitness. Because body size can affect the competitive abilities in many terrestrial ectotherms, both population size and body size should be considered in measuring the fitness of ectotherms. The rule of “bigger is better” requires relatively low temperature to increase in body size, whereas relatively high temperature is required for a rapid increase in population size. Thus, there is presumably a trade-off in temperature for adjusting individual body size and population size to achieve maximum fitness. We hypothesized that this temperature could be reflected by the intrinsic optimum temperature for developmental rate in the Sharpe–Schoolfield–Ikemoto model, and it led to a temperature estimate around 20 °C. However, the traditional viewpoint based on the temperature corresponding to the maximal intrinsic rate of increase provides a temperature estimate around 30 °C. This study suggests that a low temperature around 20 °C might authentically represent the optimal ambient temperature for fitness in terrestrial ectotherms. It implies that thermal biologists who are interested in the effect of temperature on the fitness in terrestrial ectotherms should pay more attention to their performance at low temperature rather than high temperature.     

Effect of Tillage and Water Management on the Population Behaviour of Root-Knot Nematodes Meloidogyne Triticoryzae in Rice Crop

The effects of puddling and water regimes on hydraulic conductivity (cm/day) of soil and on bulk density (mg/m 3 ) during rice culture, soil physical characteristics of the experimental field population densities of plant-parasitic nematodes have been studied. Puddling reduced the bulk density of soil and decreased the hydraulic conductivity in the upper layers but not in the deeper layers of soil aeration was reduced due to high moisture levels retained in the puddled soil. Population density of M. triticoryzae declined in puddled soil. The invasion of the roots by the second-generation infective juveniles was reduced. The population density of the root-knot nematodes was higher in the non-puddled soil especially in unsubmerged condition compared to puddled and submerged soil. However, if the seedlings were already infected before transplanting and submergence, the nematode could survive well and reproduce within the aerenchyma of the root.     

Microsecond Scale Replica Exchange Molecular Dynamic Simulation of Villin Headpiece: An Insight into the Folding Landscape

Abstract

Reaching the experimental time scale of millisecond is a grand challenge for protein folding simulations. The development of advanced Molecular Dynamics techniques like Replica Exchange Molecular Dynamics (REMD) makes it possible to reach these experimental timescales. In this study, an attempt has been made to reach the multi microsecond simulation time scale by carrying out folding simulations on a three helix bundle protein, Villin, by combining REMD and Amber United Atom model. Twenty replicas having different temperatures ranging from 295 K to 390 K were simulated for 1.5 μs each. The lowest Root Mean Square Deviation (RMSD) structure of 2.5 Å was obtained with respect to native structure (PDB code 1VII), with all the helices formed. The folding population landscapes were built using segment-wise RMSD and Principal Components as reaction coordinates. These analyses suggest the two-stage folding for Villin. The combination of REMD and Amber United Atom model may be useful to understand the folding mechanism of various fast folding proteins     

Modeling the circadian variability of ambulatorily monitored blood pressure by multiple-component analysis

The use of a set of new end points derived from ambulatory blood pressure monitoring (ABPM), in addition to the blood pressure (BP) values themselves, has been advocated to improve the sensitivity and specificity in diagnosing hypertension and to evaluate a person's response to treatment. An adequate estimation of rhythmic parameters depends, however, on the ability to describe properly the circadian pattern of BP variability. The purpose of this study was to identify a simple model that could characterize sufficiently well the circadian pattern of BP in normotensive healthy volunteers sampled by ambulatory monitoring. We studied 278 clinically healthy Spanish adults (184 men), 22.7±3.3 yr of age, without medical history of hypertension and mean BP from ambulatory profiles always below 135/85 mmHg for systolic/diastolic BP, who underwent sequential ABPM providing a total of 1115 series of BPs and heart rates (HRs), sampled on each occasion at 0.5h intervals for 48 h. Subjects were assessed while adhering to their usual diurnal activity and nocturnal sleep routine, without restrictions but avoiding the use of medication. The circadian rhythm in BP and HR for each subject was established by multiple-component analysis. A statistically significant 24h component is documented for 97% of the BP profiles, with a significant second (12h) harmonic documented in 65% of the profiles. Other ultradian harmonic components were significant in less than 20% of the profiles. A statistically significant increase in the coefficient of determination (percent of overall variability explained by the function fitted to the data) was only obtained after including the periods of 24 and 12 h for BP, and periods of 24, 12, and 6 h for HR in the model components. Although other ultradian components can be demonstrated as statistically significant in a small percent of subjects, a rather simple model including only the two first harmonics of the 24h period describes sufficiently well, at the specified sampling rate, the circadian pattern of BP in normotensive subjects. Departure from this model could characterize overt pathology, as recently demonstrated in the diagnosis of preeclampsia.     

Unraveling Seasonality in Population Averages: An Examination of Seasonal Variation in Glucose Levels in Diabetes Patients Using a Large Population-based Data Set

It has been shown that the population average blood glucose level of diabetes patients shows seasonal variation, with higher levels in the winter than summer. However, seasonality in the population averages could be due to a tendency in the individual to seasonal variation, or alternatively due to occasional high winter readings (spiking), with different individuals showing this increase in different winters. A method was developed to rule out spiking as the dominant pattern underlying the seasonal variation in the population averages. Three years of data from three community-serving laboratories in Israel were retrieved. Diabetes patients (N?=?3243) with a blood glucose result every winter and summer over the study period were selected. For each individual, the following were calculated: seasonal average glucose for all winters and summers over the period of study (2006–2009), winter-summer difference for each adjacent winter-summer pair, and average of these five differences, an index of the degree of spikiness in the pattern of the six seasonal levels, and number of times out of five that each winter-summer difference was positive. Seasonal population averages were examined. The distribution of the individual's differences between adjacent seasons (winter minus summer) was examined and compared between subgroups. Seasonal population averages were reexamined in groups divided according to the index of the degree of spikiness in the individual's glucose pattern over the series of seasons. Seasonal population averages showed higher winter than summer levels. The overall median winter-summer difference on the individual level was 8?mg/dL (0.4?mmol/L). In 16.9% (95% confidence interval [CI]: 15.6–18.2%) of the population, all five winter-summer differences were positive versus 3.6% (95% CI: 3.0–4.2%) where all five winter-summer differences were negative. Seasonal variation in the population averages was not attenuated in the group having the lowest spikiness index; comparison of the distributions of the winter-summer differences in the high-, medium-, and low-spikiness groups showed no significant difference (p?=?.213). Therefore, seasonality in the population average blood glucose in diabetes patients is not just the result of occasional high measurements in different individuals in different winters, but presumably reflects a general periodic tendency in individuals for winter glucose levels to be higher than summer levels. (Author correspondence: anneke@clalit.org.il)