Inference of multiple sequence alignments (MSAs) is a critical part of phylogenetic and comparative genomics studies. However, from the same set of sequences different MSAs are often inferred, depending on the methodologies used and the assumed parameters. Much effort has recently been devoted to improving the ability to identify unreliable alignment regions. Detecting such unreliable regions was previously shown to be important for downstream analyses relying on MSAs, such as the detection of positive selection. Here we developed GUIDANCE2, a new integrative methodology that accounts for: (i) uncertainty in the process of indel formation, (ii) uncertainty in the assumed guide tree and (iii) co-optimal solutions in the pairwise alignments, used as building blocks in progressive alignment algorithms. We compared GUIDANCE2 with seven methodologies to detect unreliable MSA regions using extensive simulations and empirical benchmarks. We show that GUIDANCE2 outperforms all previously developed methodologies. Furthermore, GUIDANCE2 also provides a set of alternative MSAs which can be useful for downstream analyses. The novel algorithm is implemented as a web-server, available at: http://guidance.tau.ac.il.

Bacteria and archaea typically possess small genomes that are tightly packed with protein-coding genes. The compactness of prokaryotic genomes is commonly perceived as evidence of adaptive genome streamlining caused by strong purifying selection in large microbial populations. In such populations, even the small cost incurred by nonfunctional DNA because of extra energy and time expenditure is thought to be sufficient for this extra genetic material to be eliminated by selection. However, contrary to the predictions of this model, there exists a consistent, positive correlation between the strength of selection at the protein sequence level, measured as the ratio of nonsynonymous to synonymous substitution rates, and microbial genome size. Here, by fitting the genome size distributions in multiple groups of prokaryotes to predictions of mathematical models of population evolution, we show that only models in which acquisition of additional genes is, on average, slightly beneficial yield a good fit to genomic data. These results suggest that the number of genes in prokaryotic genomes reflects the equilibrium between the benefit of additional genes that diminishes as the genome grows and deletion bias (i.e., the rate of deletion of genetic material being slightly greater than the rate of acquisition). Thus, new genes acquired by microbial genomes, on average, appear to be adaptive. The tight spacing of protein-coding genes likely results from a combination of the deletion bias and purifying selection that efficiently eliminates nonfunctional, noncoding sequences. T he majority of bacterial and archaeal genomes are small, at least compared with the genomes of multicellular and many unicellular eukaryotes (1, 2). Also, with the exception of deteriorating genomes of some parasitic bacteria, the prokaryotic genomes are highly compact, with densely packed protein-coding genes and a low fraction of noncoding sequences (3). The small genome size is thought to be selected for fast replication, whereas the high gene density additionally facilitates coregulation of gene expression via the operon organization (4, 5). Across the full range of cellular life forms, a significant positive correlation has been shown to exist between genome size and N e u, where N e is the effective population size, and u is the mutation rate per nucleotide (6-9). Accordingly, a simple and appealing population genetic theory has been developed, under which selection strength controls genome size and complexity (6, 9). Prokaryotes, with the exception of some parasites, have large effective population sizes on the order of 10 9 or even higher, which implies strong selection enabling prokaryotes to maintain compact genomes (10). Under this strong selection regime, even short nonfunctional sequences incur cost that is "visible" to selection, conceivably through a combination of increasing energy expenditure and reducing the replication rate, and are efficiently weeded out (11). In eukaryotes, at least the multicellular forms, the effective population ...

Transcription factors (TFs) are regulatory proteins that bind DNA in promoter regions of the genome and either promote or repress gene expression. Here, we predict analytically that enhanced homooligonucleotide sequence correlations, such as poly(dA:dT) and poly(dC:dG) tracts, statistically enhance nonspecific TF-DNA binding affinity. This prediction is generic and qualitatively independent of microscopic parameters of the model. We show that nonspecific TF binding affinity is universally controlled by the strength and symmetry of DNA sequence correlations. We perform correlation analysis of the yeast genome and show that DNA regions highly occupied by TFs exhibit stronger homooligonucleotide sequence correlations, and thus a higher propensity for nonspecific binding, than do poorly occupied regions. We suggest that this effect plays the role of an effective localization potential that enhances quasi-one-dimensional diffusion of TFs in the vicinity of DNA, speeding up the stochastic search process for specific TF binding sites. The effect is also predicted to impose an upper bound on the size of TF-DNA binding motifs.

Poor reading skills of developmental dyslexics persist into adulthood with standard remediation protocols having little effect. Nevertheless, reading improves if readers are induced to read faster. Here we show that this improvement can be enhanced by training. Training follows a multi-session procedure adapted to silent sentence reading, with individually set, increasingly more demanding, time constraints (letter-by-letter masking). In both typical and dyslexic adult readers, reading times are shortened and comprehension improves. After training, the dyslexic readers' performance is similar to that of typical readers; moreover, their connected text reading times and comprehension scores significantly improve in standard reading tests and are retained at 6 months post training. Identical training without time constraints proves ineffective. Our results suggest that fluent reading depends in part on rapid information processing, which then might affect perception, cognitive processing and possibly eye movements. These processes remain malleable in adulthood, even in individuals with developmental dyslexia.

Bacterial and archaeal evolution involve extensive gene gain and loss. Thus, phylogenetic trees of prokaryotes can be constructed both by traditional sequence-based methods (gene trees) and by comparison of gene compositions (genome trees). Comparing the branch lengths in gene and genome trees with identical topologies for 34 clusters of closely related bacterial and archaeal genomes, we show here that terminal branches of gene trees are systematically compressed compared to those of genome trees. Thus, sequence evolution is delayed compared to genome evolution by gene gain and loss. The extent of this delay differs widely among bacteria and archaea. Mathematical modeling shows that the divergence delay can result from sequence homogenization by homologous recombination. The model explains how homologous recombination maintains the cohesiveness of the core genome of a species while allowing extensive gene gain and loss within the accessory genome. Once evolving genomes become isolated by barriers impeding homologous recombination, gene and genome evolution processes settle into parallel trajectories, and genomes diverge, resulting in speciation.

Quantitative understanding of the principles regulating nucleosome occupancy on a genome-wide level is a central issue in eukaryotic genomics. Here, we address this question using budding yeast, Saccharomyces cerevisiae, as a model organism. We perform a genome-wide computational analysis of the nonspecific transcription factor (TF)-DNA binding free-energy landscape and compare this landscape with experimentally determined nucleosome-binding preferences. We show that DNA regions with enhanced nonspecific TF-DNA binding are statistically significantly depleted of nucleosomes. We suggest therefore that the competition between TFs with histones for nonspecific binding to genomic sequences might be an important mechanism influencing nucleosome-binding preferences in vivo. We also predict that poly(dA:dT) and poly(dC:dG) tracts represent genomic elements with the strongest propensity for nonspecific TF-DNA binding, thus allowing TFs to outcompete nucleosomes at these elements. Our results suggest that nonspecific TF-DNA binding might provide a barrier for statistical positioning of nucleosomes throughout the yeast genome. We predict that the strength of this barrier increases with the concentration of DNA binding proteins in a cell. We discuss the connection of the proposed mechanism with the recently discovered pathway of active nucleosome reconstitution.

In prokaryotes, the number of genes in different functional classes shows apparent universal scaling with the total number of genes that can be approximated by a power law, with a sublinear, near-linear, or superlinear scaling exponent. These dependences are gene class specific but hold across the entire diversity of bacteria and archaea. Several models have been proposed to explain these universal scaling laws, primarily based on the specifics of the respective biological functions. However, a population-genetic theory of universal scaling is lacking. We employ a simple mathematical model for prokaryotic genome evolution, which, together with the analysis of 34 clusters of closely related bacterial genomes, allows us to identify the underlying factors that govern the evolution of the genome content. Evolution of the gene content is dominated by two functional class-specific parameters: selection coefficient and genome plasticity. The selection coefficient quantifies the fitness cost associated with deletion of a gene in a given functional class or the advantage of successful incorporation of an additional gene. Genome plasticity reflects both the availability of the genes of a given class in the external gene pool that is accessible to the evolving population and the ability of microbes to accommodate these genes in the short term, that is, the class-specific horizontal gene transfer barrier. The selection coefficient determines the gene loss rate, whereas genome plasticity is the principal determinant of the gene gain rate.

The results suggest high reliability for peak and mean velocity as measured by the interactive Neck VR assessment of neck motion kinematics. VR appears to provide a reliable and more ecologically valid method of cervical motion evaluation than previous conventional methodologies.