Astrophysical Reaction Rates for 10^{10}B(p,α\alpha)7^{7}Be and 11^{11}B(p,α\alpha)8^{8}Be From a Direct Model

The reactions $^{10}$B(p,$\alpha$)$^{7}$Be and $^{11}$B(p,$\alpha$)$^{8}$Be are studied at thermonuclear energies using DWBA calculations. For both reactions, transitions to the ground states and first excited states are investigated. In the case of $^{10}$B(p,$\alpha$)$^{7}$Be, a resonance at $E_{Res}=10$ keV can be consistently described in the potential model, thereby allowing the extension of the astrophysical $S$-factor data to very low energies. Strong interference with a resonance at about $E_{Res}=550$ keV require a Breit-Wigner description of that resonance and the introduction of an interference term for the reaction $^{10}$B(p,$\alpha_1$)$^{7}$Be$^*$. Two isospin $T=1$ resonances (at $E_{Res1}=149$ keV and $E_{Res2}=619$ keV) observed in the $^{11}$B+p reactions necessitate Breit-Wigner resonance and interference terms to fit the data of the $^{11}$B(p,$\alpha$)$^{8}$Be reaction. $S$-factors and thermonuclear reaction rates are given for each reaction. The present calculation is the first consistent parametrization for the transition to the ground states and first excited states at low energies.Comment: 27 pages, 5 Postscript figures, uses RevTex and aps.sty; preprint also available at http://quasar.physik.unibas.ch/ Phys. Rev. C, in pres

Visualizing RAD51-mediated joint molecules: implications for recombination mechanism and the effect of sequence heterology

The defining event in homologous recombination is the exchange of base-paired partners between a single-stranded (ss) DNA and a homologous duplex driven by recombinase proteins, such as human RAD51. To understand the mechanism of this essential genome maintenance event, we analyzed the structure of RAD51–DNA complexes representing strand exchange intermediates at nanometer resolution by scanning force microscopy. Joint molecules were formed between substrates with a defined ssDNA segment and homologous region on a double-stranded (ds) partner. We discovered and quantified several notable architectural features of RAD51 joint molecules. Each end of the RAD51-bound joints had a distinct structure. Using linear substrates, a 10-nt region of mispaired bases blocked extension of joint molecules in all examples observed, whereas 4 nt of heterology only partially blocked joint molecule extension. Joint molecules, including 10 nt of heterology, had paired DNA on either side of the heterologous substitution, indicating that pairing could initiate from the free 3′end of ssDNA or from a region adjacent to the ss–ds junction. RAD51 filaments covering joint ss–dsDNA regions were more stable to disassembly than filaments covering dsDNA. We discuss how distinct structural features of RAD51-bound DNA joints can play important roles as recognition sites for proteins that facilitate and control strand exchange

Accounting For Alignment Uncertainty in Phylogenomics

Uncertainty in multiple sequence alignments has a large impact on phylogenetic analyses. Little has been done to evaluate the quality of individual positions in protein sequence alignments, which directly impact the accuracy of phylogenetic trees. Here we describe ZORRO, a probabilistic masking program that accounts for alignment uncertainty by assigning confidence scores to each alignment position. Using the BALIBASE database and in simulation studies, we demonstrate that masking by ZORRO significantly reduces the alignment uncertainty and improves the tree accuracy

Efficient representation of uncertainty in multiple sequence alignments using directed acyclic graphs

Background A standard procedure in many areas of bioinformatics is to use a single multiple sequence alignment (MSA) as the basis for various types of analysis. However, downstream results may be highly sensitive to the alignment used, and neglecting the uncertainty in the alignment can lead to significant bias in the resulting inference. In recent years, a number of approaches have been developed for probabilistic sampling of alignments, rather than simply generating a single optimum. However, this type of probabilistic information is currently not widely used in the context of downstream inference, since most existing algorithms are set up to make use of a single alignment. Results In this work we present a framework for representing a set of sampled alignments as a directed acyclic graph (DAG) whose nodes are alignment columns; each path through this DAG then represents a valid alignment. Since the probabilities of individual columns can be estimated from empirical frequencies, this approach enables sample-based estimation of posterior alignment probabilities. Moreover, due to conditional independencies between columns, the graph structure encodes a much larger set of alignments than the original set of sampled MSAs, such that the effective sample size is greatly increased. Conclusions The alignment DAG provides a natural way to represent a distribution in the space of MSAs, and allows for existing algorithms to be efficiently scaled up to operate on large sets of alignments. As an example, we show how this can be used to compute marginal probabilities for tree topologies, averaging over a very large number of MSAs. This framework can also be used to generate a statistically meaningful summary alignment; example applications show that this summary alignment is consistently more accurate than the majority of the alignment samples, leading to improvements in downstream tree inference. Implementations of the methods described in this article are available at http://statalign.github.io/WeaveAlign webcite