Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

The use of some multiple-sequence alignments in phylogenetic analysis, particularly those that are not very well conserved, requires the elimination of poorly aligned positions and divergent regions, since they may not be homologous or may have been saturated by multiple substitutions. A computerized method that eliminates such positions and at the same time tries to minimize the loss of informative sites is presented here. The method is based on the selection of blocks of positions that fulfill a simple set of requirements with respect to the number of contiguous conserved positions, lack of gaps, and high conservation of flanking positions, making the final alignment more suitable for phylogenetic analysis. To illustrate the efficiency of this method, alignments of 10 mitochondrial proteins from several completely sequenced mitochondrial genomes belonging to diverse eukaryotes were used as examples. The percentages of removed positions were higher in the most divergent alignments. After removing divergent segments, the amino acid composition of the different sequences was more uniform, and pairwise distances became much smaller. Phylogenetic trees show that topologies can be different after removing conserved blocks, particularly when there are several poorly resolved nodes. Strong support was found for the grouping of animals and fungi but not for the position of more basal eukaryotes. The use of a computerized method such as the one presented here reduces to a certain extent the necessity of manually editing multiple alignments, makes the automation of phylogenetic analysis of large data sets feasible, and facilitates the reproduction of the final alignment by other researchers.

/pdf/selection-of-conserved-blocks-from-multiple-alignments-for-i0qfazjwh5.pdf

Selection of Conserved Blocks from Multiple Alignments for Their Use in Phylogenetic Analysis

Multiple sequence alignments (MSA) are central to many areas of bioinformatics, including phylogenetics, homology modeling, database searches and motif finding. Recently, such MSA-based techniques have been incorporated in high-throughput pipelines such as genome annotation and phylogenomics analyses. In all these applications, the reliability and accuracy of the analyses depend critically on the quality of the underlying alignments. A plethora of computer programs and algorithms for MSA are currently available (Notredame, 2007), which implement different heuristics to find mathematically optimal solutions to the MSA problem. Accuracies of 80–90% have been reported for the best algorithms, but even the best scoring alignment algorithms may fail with certain protein families or at specific regions in the alignment. The situation worsens in large-scale analyses, where faster but less reliable algorithms and large numbers of automatically selected sequences are used. It is therefore generally assumed that trimming the alignment, so that poorly aligned regions are eliminated, increases the accuracy of the resulting MSA-based applications (Talavera and Castresana, 2007). Some programs such as G-blocks (Castresana, 2000) have been developed to assist in the MSA trimming phase by selecting blocks of conserved regions. They have become very popular and are extensively used, with good performance, in small-to-medium scale datasets, where several parameters can be tested manually (Talavera and Castresana, 2007). However, their use over larger datasets is hampered by the need for defining, prior to the analysis, the set of parameters that will be used for all sequence families. Here, we present trimAl, a tool for automated alignment trimming. Its speed and the possibility for automatically adjusting the parameters to improve the phylogenetic signal-to-noise ratio, makes trimAl especially suited for large-scale phylogenomic analyses, involving thousands of large alignments.

trimAl has been developed in a GNU/Linux environment using C++ programming language and has been tested on various UNIX, Mac and Windows platforms. Moreover, we have developed a web server to run trimAl online (http://phylemon2.bioinfo.cipf.es/), which has been included in the Phylemon suite for phylogenetic and phylogenomic tools (Tarraga et al., 2007). The documentation, source files and additional information for trimAl are available through a wiki page (http://trimal.cgenomics.org).

trimAl reads and renders protein or nucleotide alignments in several standard formats. trimAl starts by reading all columns in an alignment and computes a score (Sx) for each of them. This score can be a gap score (Sg), a similarity score (Ss) or a consistency score (Sc). The score for each column can be computed based only on the information from that column or, if a window size of w is specified, it corresponds to the average value of w columns around the position considered.

The gap score (Sg) for a column is the fraction of sequences without a gap in that position. The residue similarity score (Ss) consists of mean distance (MD) scores as described in Thompson et al. (2001) and Supplementary Material. This score uses the MD between pairs of residues, as defined by a given scoring matrix. Finally, the consistency score (Sc) can only be computed when more than one alignment for the same set of sequences is provided. Details on how these scores are computed are provided in the Supplementary Material. In brief, Sc measures the level of consistency of all the residue pairs found in a column as compared with the other alignments. The alignment with the highest consistency is chosen and then trimmed to remove the columns that are less conserved, according to Sc or other thresholds set by the user.

Once all column scores have been computed trimAl can proceed in two ways. If both a score and a minimum conservation threshold are provided, trimAl renders a trimmed alignment in which only the columns with scores above the score threshold are included, as far as the number of selected columns is above a conservation threshold defined by the user. If this number is below the conservation threshold, trimAl will add more columns to the trimmed alignment in a decreasing order of scores until the conservation threshold is reached. The conservation threshold corresponds to the minimum percentage of columns, from the original alignment, which the user wants to include in the trimmed alignment.

Alternatively, if the automatic selection of parameters options is selected, trimAl will compute specific score thresholds depending on the inherent characteristics of each alignment. So far, trimAl incorporates three modes for the automated selection of parameters, gappyout, strict and strictplus, which are based on the different use of gap and similarity scores. Moreover, the option automated1 implements a heuristic to decide the most appropriate mode depending on the alignment characteristics. The heuristics to define such parameters have been designed based on the results of a benchmark. Details on the heuristics and the benchmark can be found in the online documentation of the program. In brief, the automatic selection of parameters approximate optimal cutoffs by plotting, internally, the cumulative graphs of gap and similarity scores of the columns in the alignment (see online documentation).

We expanded, using ROSE simulations (Stoye et al., 1998) a benchmark set that has been used previously to test the improvement in phylogenetic performance after an alignment trimming phase (Talavera and Castresana, 2007). This dataset simulates several evolutionary scenarios varying in the number and length of the sequences, the topology of the underlying tree and the level of sequence divergence considered. We compared the results obtained from MUSCLE alignments before and after trimming with trimAl using automated selection of parameters. The accuracy of the resulting trees was measured by comparing them with the original trees used to generate the sequence sets, and measuring the Robinson Foulds distance (Robinson and Foulds, 1981). We observed an overall improvement of the phylogenetic accuracy after trimming. Using -automated1 option of trimAl, the trimmed alignment always produced Maximum Likelihood trees that were of equal (36%) or significantly better (64%) quality as compared with the tree derived from the complete alignment. For Neighbor Joining reconstruction the -strictplus option of trimAl worked best, improving the phylogenetic accuracy in 89% of the scenarios. In most scenarios (90%), trimAl outperformed Gblocks v0.91b with default parameters. Most importantly, the use of Gblocks default parameters diminished the accuracy of the subsequent tree reconstruction in half of the scenarios considered. In contrast, the use of trimAl automated methods rarely (1.5%) undermined the topological accuracy of the resulting phylogenetic tree (see Supplementary Material for more details).

To test the applicability of trimAl on real datasets as well as its suitability for large-scale phylogenetic datasets, we ran trimAl on the complete set of MUSCLE alignments generated for the Human Phylome project (Huerta-Cepas et al., 2007). This includes a total of 31 182 alignments, containing, on average, 67 sequences of 1472 positions of length. Trimming these alignments using the -gappyout and automated1 options used 5 min 45 s and 125 min, 2 s, respectively, on a computer with an Intel QuadCore XEON E5410 processors and 8 GB of RAM.

trimAl has been used previously in a pipeline to reconstruct complete collections of gene trees. In this case, the parameter sets used were a minimum conservation threshold of 60% and a gap threshold of 90% (-cons 60 -gt 0.9). Complete and trimmed alignments used to generate the phylomes included in PhylomeDB (Huerta-Cepas et al., 2008) can be viewed through this database.

/pdf/trimal-a-tool-for-automated-alignment-trimming-in-large-3dj0obyexv.pdf

trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses

The sequence of the mouse genome is a key informational tool for understanding the contents of the human genome and a key experimental tool for biomedical research. Here, we report the results of an international collaboration to produce a high-quality draft sequence of the mouse genome. We also present an initial comparative analysis of the mouse and human genomes, describing some of the insights that can be gleaned from the two sequences. We discuss topics including the analysis of the evolutionary forces shaping the size, structure and sequence of the genomes; the conservation of large-scale synteny across most of the genomes; the much lower extent of sequence orthology covering less than half of the genomes; the proportions of the genomes under selection; the number of protein-coding genes; the expansion of gene families related to reproduction and immunity; the evolution of proteins; and the identification of intraspecies polymorphism.

/pdf/initial-sequencing-and-comparative-analysis-of-the-mouse-5a9n62pifj.pdf

Initial sequencing and comparative analysis of the mouse genome.

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Modern Applied Statistics With S

The protonation constant in 1.0 mol-dm−3 KNO3, and partition coefficient of 4-methylpyridine (B) between 1.0 mol-dm−3 KNO3, and toluene have been determined at 25°C by measuring the H3O+ ion concentration with a glass electrode. The experimental work consisted of two sets of potentiometric titrations. In the first case, the titrations were carried out in an aqueous system of constant ionic strength and in the second, two-phase titrations using toluene as organic phase were performed. All the titrations were conducted automatically by the use of a computer controlled potentiometric system. The results were treated using graphical and numerical methods and the systematic erros were also considered. The formation constant of the protonated 4-methylpyridine was correlated with the composition of the aqueous phase by means of Bromley's theory.

Determination of the protonation constant and partition coefficient of 4-methylpyridine in KNO3-toluene at 25°C

On the extraction with long-chain amines—XXXVII. The extraction of lead(II) by trilaurylamine and trilaurylammonium, tri-n- octylammonium and tri-n-hexylammonium chlorides dissolved in benzene

The acid-base equilibrium constant of the active component of the commercial extractant LIX 54, 1-phenyl-1, 3-decanedione, has been determined in a water/alcohol mixed solvent (25% ethanol) at 298K using 1.0mol dm-3 KCl as an ionic medium. Graphical and numerical treatment of spectrophotometric data have led to the value pKa=9.73±0.05. The distribution, aggregation and interactions of the reagent with other extractants used in synergistic mixtures are also discussed. A comparison of the extraction of Cu(II), Ni(II) and Zn(II) from nitrate solutions by the reagent and by mixtures of the reagent with additional ligands in toluene has been made.

Acid-Base Equilibria and Metal Extraction Properties of 1-Phenyl-1, 3-decanedione

Interaction of SDS with β-galactosidase. A FT-IR study of the influence of detergent concentration and temperature.

Molecular dating methods of population splits are crucial in evolutionary biology, but they present important difficulties due to the complexity of the genealogical relationships of genes and past migrations between populations. Using the double digest restriction-site associated DNA (ddRAD) technique and an isolation-with-migration (IM) model, we studied the evolutionary history of water vole populations of the genus Arvicola, a group of complex evolution with fossorial and semi-aquatic ecotypes. To do this, we first estimated mutation rates of ddRAD loci using a phylogenetic approach. An IM model was then used to estimate split times and other relevant demographic parameters. A set of 300 ddRAD loci that included 85 calibrated loci resulted in good mixing and model convergence. The results showed that the two populations of A. scherman present in the Iberian Peninsula split 34 thousand years ago, during the last glaciation. In addition, the much greater divergence from its sister species, A. amphibius, may help to clarify the controversial taxonomy of the genus. We conclude that this approach, based on ddRAD data and an IM model, is highly useful for analyzing the origin of populations and species. 

/pdf/divergence-time-estimation-using-ddrad-data-and-an-isolation-2t5s7kel.pdf

Jose Castresana

Papers

Determination of the protonation constant and partition coefficient of 4-methylpyridine in KNO3-toluene at 25°C

On the extraction with long-chain amines—XXXVII. The extraction of lead(II) by trilaurylamine and trilaurylammonium, tri-n- octylammonium and tri-n-hexylammonium chlorides dissolved in benzene

Acid-Base Equilibria and Metal Extraction Properties of 1-Phenyl-1, 3-decanedione

Interaction of SDS with β-galactosidase. A FT-IR study of the influence of detergent concentration and temperature.

Divergence time estimation using ddRAD data and an isolation-with-migration model applied to water vole populations of Arvicola