PhyloCSF: a comparative genomics method to distinguish protein-coding and non-coding regions

As high-throughput transcriptome sequencing provides evidence for novel transcripts in many species, there is a renewed need for accurate methods to classify small genomic regions as protein-coding or non-coding. We present PhyloCSF, a novel comparative genomics method that analyzes a multi-species nucleotide sequence alignment to determine whether it is likely to represent a conserved protein-coding region, based on a formal statistical comparison of phylogenetic codon models. We show that PhyloCSF's classification performance in 12-species _Drosophila_ genome alignments exceeds all other methods we compared in a previous study, and we provide a software implementation for use by the community. We anticipate that this method will be widely applicable as the transcriptomes of many additional species, tissues, and subcellular compartments are sequenced, particularly in the context of ENCODE and modENCODE

The evolutionary dynamics of the Saccharomyces cerevisiae protein interaction network after duplication

Gene duplication is an important mechanism in the evolution of protein interaction networks. Duplications are followed by the gain and loss of interactions, rewiring the network at some unknown rate. Because rewiring is likely to change the distribution of network motifs within the duplicated interaction set, it should be possible to study network rewiring by tracking the evolution of these motifs. We have developed a mathematical framework that, together with duplication data from comparative genomic and proteomic studies, allows us to infer the connectivity of the preduplication network and the changes in connectivity over time. We focused on the whole-genome duplication (WGD) event in Saccharomyces cerevisiae. The model allowed us to predict the frequency of intergene interaction before WGD and the post duplication probabilities of interaction gain and loss. We find that the predicted frequency of self-interactions in the preduplication network is significantly higher than that observed in today's network. This could suggest a structural difference between the modern and ancestral networks, preferential addition or retention of interactions between ohnologs, or selective pressure to preserve duplicates of self-interacting proteins

HAMSTRINGS COACTIVATION IN TRAINED LONG JUMPERS AND UNTRAINED INDIVIDUALS DURING DROP JUMPING

The purpose of this study was to examine the EMG activity patterns of the hamstrings during drop jumping from different heights in trained longer jumpers and controls. A group of trained long jumpers and a group of untrained subjects performed maximal drop jumps from 20cm, 40cm and 60 cm on a force platform. The surface EMG activity of the hamstrings was recorded using bipolar electrodes. The ground reaction forces (GRF) and 3-D kinematic data were also recorded. Two-way analysis of variance tests indicated non-significant differences in hamstring EMG amplitude between trained and untrained athletes. However, the long jumpers had significantly higher vertical GRF values and some kinematic differences compared to untrained individuals. The absence of higher hamstrings activity in the long jumpers may have been a contributing factor in their higher performance compared to controls. However, the same result indicates that this increased performance may be accompanied by a possible increased risk of knee joint instability

Electronic color charts for dielectric films on silicon

This paper presents the calculation of the perceived color of dielectric films on silicon. A procedure is shown for computing the perceived color for an arbitrary light source, light incident angle, and film thickness. The calculated color is converted into RGB parameters that can be displayed on a color monitor, resulting in the generation of electronic color charts for dielectric films. This paper shows generated electronic color charts for both silicon dioxide and silicon nitride films on silicon

Electronic color charts for dielectric films on silicon

This paper presents the calculation of the perceived color of dielectric films on silicon. A procedure is shown for computing the perceived color for an arbitrary light source, light incident angle, and film thickness. The calculated color is converted into RGB parameters that can be displayed on a color monitor, resulting in the generation of electronic color charts for dielectric films. This paper shows generated electronic color charts for both silicon dioxide and silicon nitride films on silicon

Genome-wide probing of RNA structure reveals active unfolding of mRNA structures in vivo

RNA has a dual role as an informational molecule and a direct effector of biological tasks. The latter function is enabled by RNA’s ability to adopt complex secondary and tertiary folds and thus has motivated extensive computational and experimental efforts for determining RNA structures. Existing approaches for evaluating RNA structure have been largely limited to in vitro systems, yet the thermodynamic forces which drive RNA folding in vitro may not be sufficient to predict stable RNA structures in vivo. Indeed, the presence of RNA-binding proteins and ATP-dependent helicases can influence which structures are present inside cells. Here we present an approach for globally monitoring RNA structure in native conditions in vivo with single-nucleotide precision. This method is based on in vivo modification with dimethyl sulphate (DMS), which reacts with unpaired adenine and cytosine residues, followed by deep sequencing to monitor modifications. Our data from yeast and mammalian cells are in excellent agreement with known messenger RNA structures and with the high-resolution crystal structure of the Saccharomyces cerevisiae ribosome. Comparison between in vivo and in vitro data reveals that in rapidly dividing cells there are vastly fewer structured mRNA regions in vivo than in vitro. Even thermostable RNA structures are often denatured in cells, highlighting the importance of cellular processes in regulating RNA structure. Indeed, analysis of mRNA structure under ATP-depleted conditions in yeast shows that energy-dependent processes strongly contribute to the predominantly unfolded state of mRNAs inside cells. Our studies broadly enable the functional analysis of physiological RNA structures and reveal that, in contrast to the Anfinsen view of protein folding whereby the structure formed is the most thermodynamically favourable, thermodynamics have an incomplete role in determining mRNA structure in vivo

A Bayesian Approach for Fast and Accurate Gene Tree Reconstruction

Supplementary tables S1, sections 2.1–2.3, and figures S1–S11 are available at Molecular Biology and Evolution online (http://www.mbe.oxfordjournals.org/).Recent sequencing and computing advances have enabled phylogenetic analyses to expand to both entire genomes and large clades, thus requiring more efficient and accurate methods designed specifically for the phylogenomic context. Here, we present SPIMAP, an efficient Bayesian method for reconstructing gene trees in the presence of a known species tree. We observe many improvements in reconstruction accuracy, achieved by modeling multiple aspects of evolution, including gene duplication and loss (DL) rates, speciation times, and correlated substitution rate variation across both species and loci. We have implemented and applied this method on two clades of fully sequenced species, 12 Drosophila and 16 fungal genomes as well as simulated phylogenies and find dramatic improvements in reconstruction accuracy as compared with the most popular existing methods, including those that take the species tree into account. We find that reconstruction inaccuracies of traditional phylogenetic methods overestimate the number of DL events by as much as 2–3-fold, whereas our method achieves significantly higher accuracy. We feel that the results and methods presented here will have many important implications for future investigations of gene evolution.National Science Foundation (U.S.) (CAREER award NSF 0644282

Position specific variation in the rate of evolution in transcription factor binding sites

BACKGROUND: The binding sites of sequence specific transcription factors are an important and relatively well-understood class of functional non-coding DNAs. Although a wide variety of experimental and computational methods have been developed to characterize transcription factor binding sites, they remain difficult to identify. Comparison of non-coding DNA from related species has shown considerable promise in identifying these functional non-coding sequences, even though relatively little is known about their evolution. RESULTS: Here we analyse the genome sequences of the budding yeasts Saccharomyces cerevisiae, S. bayanus, S. paradoxus and S. mikatae to study the evolution of transcription factor binding sites. As expected, we find that both experimentally characterized and computationally predicted binding sites evolve slower than surrounding sequence, consistent with the hypothesis that they are under purifying selection. We also observe position-specific variation in the rate of evolution within binding sites. We find that the position-specific rate of evolution is positively correlated with degeneracy among binding sites within S. cerevisiae. We test theoretical predictions for the rate of evolution at positions where the base frequencies deviate from background due to purifying selection and find reasonable agreement with the observed rates of evolution. Finally, we show how the evolutionary characteristics of real binding motifs can be used to distinguish them from artefacts of computational motif finding algorithms. CONCLUSION: As has been observed for protein sequences, the rate of evolution in transcription factor binding sites varies with position, suggesting that some regions are under stronger functional constraint than others. This variation likely reflects the varying importance of different positions in the formation of the protein-DNA complex. The characterization of the pattern of evolution in known binding sites will likely contribute to the effective use of comparative sequence data in the identification of transcription factor binding sites and is an important step toward understanding the evolution of functional non-coding DNA

A Bibliometric Analysis of Soccer Biomechanics

Soccer biomechanics is a field that applies principles of mechanics to improve performance and reduce the risk of injury for soccer players. The purpose of this research is to perform a mapping review of the existing knowledge in the current literature, identify leading researchers and institutions, and explore emerging research topics. After conducting a mini literature review, a bibliometric analysis was carried out using the VOSviewer software. The data imported into VOSviewer was obtained from the Scopus database and included 951 records. The analysis performed included: (a) performance analysis to calculate the number of records per year and the authors with the most citations; (b) science mapping analysis (co-authorship, co-citation, and bibliographic coupling); and (c) clustering analysis through the co-occurrence analysis of author keywords. Our findings highlight a significant growth in research publications on soccer biomechanics over the past few decades, with a notable increase in the number of articles published in high-impact journals. Additionally, the clustering analysis resulted in seven clusters, with each cluster providing valuable insights into different aspects of soccer biomechanics, which clearly reflects the multifaceted nature of the field

High-resolution genome-wide functional dissection of transcriptional regulatory regions and nucleotides in human

Genome-wide epigenomic maps have revealed millions of putative enhancers and promoters, but experimental validation of their function and high-resolution dissection of their driver nucleotides remain limited. Here, we present HiDRA (High-resolution Dissection of Regulatory Activity), a combined experimental and computational method for high-resolution genome-wide testing and dissection of putative regulatory regions. We test ~7 million accessible DNA fragments in a single experiment, by coupling accessible chromatin extraction with self-transcribing episomal reporters (ATAC-STARR-seq). By design, fragments are highly overlapping in densely-sampled accessible regions, enabling us to pinpoint driver regulatory nucleotides by exploiting differences in activity between partially-overlapping fragments using a machine learning model (SHARPR-RE). In GM12878 lymphoblastoid cells, we find ~65,000 regions showing enhancer function, and pinpoint ~13,000 high-resolution driver elements. These are enriched for regulatory motifs, evolutionarily-conserved nucleotides, and disease-associated genetic variants from genome-wide association studies. Overall, HiDRA provides a high-throughput, high-resolution approach for dissecting regulatory regions and driver nucleotides.National Institutes of Health (U.S.) (R01 HG008155)Broad NextGen AwardNational Institutes of Health (U.S.) (R01 GM113708)National Institutes of Health (U.S.) (U01 HG007610