Multitrait analysis of quantitative trait loci using Bayesian composite space approach

<p>Abstract</p> <p>Background</p> <p>Multitrait analysis of quantitative trait loci can capture the maximum information of experiment. The maximum-likelihood approach and the least-square approach have been developed to jointly analyze multiple traits, but it is difficult for them to include multiple QTL simultaneously into one model.</p> <p>Results</p> <p>In this article, we have successfully extended Bayesian composite space approach, which is an efficient model selection method that can easily handle multiple QTL, to multitrait mapping of QTL. There are many statistical innovations of the proposed method compared with Bayesian single trait analysis. The first is that the parameters for all traits are updated jointly by vector or matrix; secondly, for QTL in the same interval that control different traits, the correlation between QTL genotypes is taken into account; thirdly, the information about the relationship of residual error between the traits is also made good use of. The superiority of the new method over separate analysis was demonstrated by both simulated and real data. The computing program was written in FORTRAN and it can be available for request.</p> <p>Conclusion</p> <p>The results suggest that the developed new method is more powerful than separate analysis.</p

Molecular-beam Epitaxy of Monolayer MoSe2: Growth Characteristics and Domain Boundary Formation

published_or_final_versio

The Classical Harmonic Vibrations of the Atomic Centers of Mass with Micro Amplitudes and Low Frequencies Monitored by the Entanglement between the Two Two-level Atoms in a Single mode Cavity

We study the entanglement dynamics of the two two-level atoms coupling with a single-mode polarized cavity field after incorporating the atomic centers of mass classical harmonic vibrations with micro amplitudes and low frequencies. We propose a quantitative vibrant factor to modify the concurrence of the two atoms states. When the vibrant frequencies are very low, we obtain that: (i) the factor depends on the relative vibrant displacements and the initial phases rather than the absolute amplitudes, and reduces the concurrence to three orders of magnitude; (ii) the concurrence increases with the increase of the initial phases; (iii) the frequency of the harmonic vibration can be obtained by measuring the maximal value of the concurrence during a small time. These results indicate that even the extremely weak classical harmonic vibrations can be monitored by the entanglement of quantum states.Comment: 10 pages, 3 figure

Star forming dwarf galaxies

Star forming dwarf galaxies (SFDGs) have a high gas content and low metallicities, reminiscent of the basic entities in hierarchical galaxy formation scenarios. In the young universe they probably also played a major role in the cosmic reionization. Their abundant presence in the local volume and their youthful character make them ideal objects for detailed studies of the initial stellar mass function (IMF), fundamental star formation processes and its feedback to the interstellar medium. Occasionally we witness SFDGs involved in extreme starbursts, giving rise to strongly elevated production of super star clusters and global superwinds, mechanisms yet to be explored in more detail. SFDGs is the initial state of all dwarf galaxies and the relation to the environment provides us with a key to how different types of dwarf galaxies are emerging. In this review we will put the emphasis on the exotic starburst phase, as it seems less important for present day galaxy evolution but perhaps fundamental in the initial phase of galaxy formation.Comment: To appear in JENAM Symposium "Dwarf Galaxies: Keys to Galaxy Formation and Evolution", P. Papaderos, G. Hensler, S. Recchi (eds.). Lisbon, September 2010, Springer Verlag, in pres

Bayesian shrinkage mapping of quantitative trait loci in variance component models

<p>Abstract</p> <p>Background</p> <p>In this article, I propose a model-selection-free method to map multiple quantitative trait loci (QTL) in variance component model, which is useful in outbred populations. The new method can estimate the variance of zero-effect QTL infinitely to zero, but nearly unbiased for non-zero-effect QTL. It is analogous to Xu's Bayesian shrinkage estimation method, but his method is based on allelic substitution model, while the new method is based on the variance component models.</p> <p>Results</p> <p>Extensive simulation experiments were conducted to investigate the performance of the proposed method. The results showed that the proposed method was efficient in mapping multiple QTL simultaneously, and moreover it was more competitive than the reversible jump MCMC (RJMCMC) method and may even out-perform it.</p> <p>Conclusions</p> <p>The newly developed Bayesian shrinkage method is very efficient and powerful for mapping multiple QTL in outbred populations.</p

A Connection between Colony Biomass and Death in Caribbean Reef-Building Corals

Increased sea-surface temperatures linked to warming climate threaten coral reef ecosystems globally. To better understand how corals and their endosymbiotic dinoflagellates (Symbiodinium spp.) respond to environmental change, tissue biomass and Symbiodinium density of seven coral species were measured on various reefs approximately every four months for up to thirteen years in the Upper Florida Keys, United States (1994–2007), eleven years in the Exuma Cays, Bahamas (1995–2006), and four years in Puerto Morelos, Mexico (2003–2007). For six out of seven coral species, tissue biomass correlated with Symbiodinium density. Within a particular coral species, tissue biomasses and Symbiodinium densities varied regionally according to the following trends: Mexico≥Florida Keys≥Bahamas. Average tissue biomasses and symbiont cell densities were generally higher in shallow habitats (1–4 m) compared to deeper-dwelling conspecifics (12–15 m). Most colonies that were sampled displayed seasonal fluctuations in biomass and endosymbiont density related to annual temperature variations. During the bleaching episodes of 1998 and 2005, five out of seven species that were exposed to unusually high temperatures exhibited significant decreases in symbiotic algae that, in certain cases, preceded further decreases in tissue biomass. Following bleaching, Montastraea spp. colonies with low relative biomass levels died, whereas colonies with higher biomass levels survived. Bleaching- or disease-associated mortality was also observed in Acropora cervicornis colonies; compared to A. palmata, all A. cervicornis colonies experienced low biomass values. Such patterns suggest that Montastraea spp. and possibly other coral species with relatively low biomass experience increased susceptibility to death following bleaching or other stressors than do conspecifics with higher tissue biomass levels

Reverse Engineering a Signaling Network Using Alternative Inputs

One of the goals of systems biology is to reverse engineer in a comprehensive fashion the arrow diagrams of signal transduction systems. An important tool for ordering pathway components is genetic epistasis analysis, and here we present a strategy termed Alternative Inputs (AIs) to perform systematic epistasis analysis. An alternative input is defined as any genetic manipulation that can activate the signaling pathway instead of the natural input. We introduced the concept of an “AIs-Deletions matrix” that summarizes the outputs of all combinations of alternative inputs and deletions. We developed the theory and algorithms to construct a pairwise relationship graph from the AIs-Deletions matrix capturing both functional ordering (upstream, downstream) and logical relationships (AND, OR), and then interpreting these relationships into a standard arrow diagram. As a proof-of-principle, we applied this methodology to a subset of genes involved in yeast mating signaling. This experimental pilot study highlights the robustness of the approach and important technical challenges. In summary, this research formalizes and extends classical epistasis analysis from linear pathways to more complex networks, facilitating computational analysis and reconstruction of signaling arrow diagrams

Bistability, Probability Transition Rate and First-Passage Time in an Autoactivating Positive-Feedback Loop

A hallmark of positive-feedback regulation is bistability, which gives rise to distinct cellular states with high and low expression levels, and that stochasticity in gene expression can cause random transitions between two states, yielding bimodal population distribution (Kaern et al., 2005, Nat Rev Genet 6: 451-464). In this paper, the probability transition rate and first-passage time in an autoactivating positive-feedback loop with bistability are investigated, where the gene expression is assumed to be disturbed by both additive and multiplicative external noises, the bimodality in the stochastic gene expression is due to the bistability, and the bistability determines that the potential of the Fokker-Planck equation has two potential wells. Our main goal is to illustrate how the probability transition rate and first-passage time are affected by the maximum transcriptional rate, the intensities of additive and multiplicative noises, and the correlation of additive and multiplicative noises. Our main results show that (i) the increase of the maximum transcription rate will be useful for maintaining a high gene expression level; (ii) the probability transition rate from one potential well to the other one will increase with the increase of the intensity of additive noise; (iii) the increase of multiplicative noise strength will increase the amount of probability in the left potential well; and (iv) positive (or negative) cross-correlation between additive and multiplicative noises will increase the amount of probability in the left (or right) potential well