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1,199 results for “Alignement”
Data from: Accurate inference of tree topologies from multiple sequence alignments using deep learning
Reconstructing the phylogenetic relationships between species is one of the most formidable tasks in evolutionary biology. Multiple methods exist to reconstruct phylogenetic trees, each with their own strengths and weaknesses. Both simulation and empirical studies have identified several "zones" of parameter space where accuracy of some methods can plummet, even for four-taxon trees. Further, some methods can have undesirable statistical properties such as statistical inconsistency and/or the tendency to be positively misleading (i.e. assert strong support for the incorrect tree topology). Recently, deep learning techniques have made inroads on a number of both new and longstanding problems in biological research. Here we designed a deep convolutional neural network (CNN) to infer quartet topologies from multiple sequence alignments. This CNN can readily be trained to make inferences using both gapped and ungapped data. We show that our approach is highly accurate on simulated data, often outperforming traditional methods, and is remarkably robust to bias-inducing regions of parameter space such as the Felsenstein zone and the Farris zone. We also demonstrate that the confidence scores produced by our CNN can more accurately assess support for the chosen topology than bootstrap and posterior probability scores from traditional methods. While numerous practical challenges remain, these findings suggest that deep learning approaches such as ours have the potential to produce more accurate phylogenetic inferences.
Data from: Concatenated alignments and the case of the disappearing tree
BackgroundAnalyzed individually, gene trees for a given taxon set tend to harbour incongruent or conflicting signals. One popular approach to deal with this circumstance is to use concatenated data. But especially in prokaryotes, where lateral gene transfer (LGT) is a natural mechanism of generating genetic diversity, there are open questions as to whether concatenation amplifies or averages phylogenetic signals residing in individual genes. Here we investigate concatenations of prokaryotic and eukaryotic datasets to investigate possible sources of incongruence in phylogenetic trees and to examine the level of overlap between individual and concatenated alignments.ResultsWe analyzed prokaryotic datasets comprising 248 invidual gene trees from 315 genomes at three taxonomic depths spanning gammaproteobacteria, proteobacteria, and prokaryotes (bacteria plus archaea), and eukaryotic datasets comprising 279 invidual gene trees from 85 genomes at two taxonomic depths: across plants-animals-fungi and within fungi. Consistent with previous findings, the branches in trees made from concatenated alignments are, in general, not supported by any of their underlying individual gene trees, even though the concatenation trees tend to possess high bootstrap proportions values. For the prokaryote data, this observation is independent of phylogenetic depth and sequence conservation. The eukaryotic data show much better agreement between concatenation and single gene trees. LGT frequencies in trees were estimated using established methods. Sequence length in individual alignments, but not sequence divergence, was found to correlate with the generation of branches that correspond to the concatenated tree.ConclusionsThe weak correspondence of concatenation trees with single gene trees gives rise to the question where the phylogenetic signal in concatenated trees is coming from. The eukaryote data reveals a better correspondence between individual and concatenation trees than the prokaryote data. The question of whether the lack of correspondence between individual genes and the concatenation tree in the prokaryotic data is due to LGT or phylogenetic artefacts is remains unanswered. If LGT is the cause of incongruence between concatenation and individual trees, we would have expected to see greater degrees of incongruence for more divergent prokaryotic data sets, which was not observed, although estimated rates of LGT suggest that LGT is responsible for at least some of the observed incongruence.
Data from: In silico site-directed mutagenesis informs species-specific predictions of chemical susceptibility derived from the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool
Chemical hazard assessment requires extrapolation of information from model organisms to all species of concern. The Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed as a rapid, cost effective method to aid cross-species extrapolation of susceptibility to chemicals acting on specific protein targets through evaluation of protein structural similarities and differences. The greatest resolution for extrapolation of chemical susceptibility across species involves comparisons of individual amino acid residues at key positions involved in protein-chemical interactions. However, a lack of understanding of whether specific amino acid substitutions among species at key positions in proteins affect interaction with chemicals made manual interpretation of alignments time consuming and potentially inconsistent. Therefore, this study used in silico site-directed mutagenesis coupled with docking simulations of computational models for acetylcholinesterase (AChE) and ecdysone receptor (EcR) to investigate how specific amino acid substitutions impact protein-chemical interaction. This study found that computationally derived substitutions in identities of key amino acids caused no change in protein-chemical interaction if residues share the same side chain functional properties and have comparable molecular dimensions, while differences in these characteristics can change protein-chemical interaction. These findings were considered in the development of capabilities for automatically generated species-specific predictions of chemical susceptibility in SeqAPASS. These predictions for AChE and EcR were shown to agree with SeqAPASS predictions comparing the primary sequence and functional domain sequence of proteins for more than 90 % of the investigated species, but also identified dramatic species-specific differences in chemical susceptibility that align with results from standard toxicity tests. These results provide a compelling line-of-evidence for use of SeqAPASS in deriving screening level, species-specific, susceptibility predictions across broad taxonomic groups for application to human and ecological hazard assessment.
Data from: Phylogenetic tree estimation with and without alignment: new distance methods and benchmarking
Phylogenetic tree inference is a critical component of many systematic and evolutionary studies. The majority of these studies are based on the two-step process of multiple sequence alignment followed by tree inference, despite persistent evidence that the alignment step can lead to biased results. Here we present a two-part study that first presents PaHMM-Tree, a novel neighbour joining-based method that estimates pairwise distances without assuming a single alignment. We then use simulations to benchmark its performance against a wide-range of other phylogenetic tree inference methods, including the first comparison of alignment-free distance-based methods against more conventional tree estimation methods. Our new method for calculating pairwise distances based on statistical alignment provides distance estimates that are as accurate as those obtained using standard methods based on the true alignment. Pairwise distance estimates based on the two-step process tend to be substantially less accurate. This improved performance carries through to tree inference, where PaHMM-Tree provides more accurate tree estimates than all of the pairwise distance methods assessed. For close to moderately divergent sequence data we find that the two-step methods using statistical inference, where information from all sequences is included in the estimation procedure, tend to perform better than PaHMM-Tree, particularly full statistical alignment, which simultaneously estimates both the tree and the alignment. For deep divergences we find the alignment step becomes so prone to error that our distance-based PaHMM-Tree outperforms all other methods of tree inference. Finally, we find that the accuracy of alignment-free methods tends to decline faster than standard two-step methods in the presence of alignment uncertainty, and identify no conditions where alignment-free methods are equal to or more accurate than standard phylogenetic methods even in the presence of substantial alignment error.
Data from: Simple chained guide trees give poorer multiple sequence alignments than inferred trees in simulation and phylogenetic benchmarks
Multiple sequence aligners typically work by progressively aligning the most closely related sequences or group of sequences according to guide trees. In PNAS, Boyce et al. report that alignments reconstructed using simple chained trees (i.e., comb-like topologies) with random leaf assignment performed better in protein structure-based benchmarks than those reconstructed using phylogenies estimated from the data as guide trees. The authors state that this result could turn decades of research in the field on its head. In light of this statement, it is important to check immediately whether their result holds under evolutionary criteria: recovery of homologous sequence residues and inference of phylogenetic trees from the alignments. We have done this and the results are entirely opposed to Boyce et al.'s findings.
Data from: A simulation-based approach to statistical alignment
Classic alignment algorithms utilize scoring functions which maximize similarity or minimize edit distances. These scoring functions account for both insertion-deletion (indel) and substitution events. In contrast, alignments based on stochastic models aim to explicitly describe the evolutionary dynamics of sequences by inferring relevant probabilistic parameters from input sequences. Despite advances in stochastic modeling during the last two decades, scoring-based methods are still dominant, partially due to slow running times of probabilistic approaches. Alignment inference using stochastic models involves estimating the probability of events, such as the insertion or deletion of a specific number of characters. In this work, we present SimBa-SAl, a simulation-based approach to statistical alignment inference, which relies on an explicit continuous Markov process for both indels and substitutions. SimBa-SAl has several advantages. First, using simulations, it decouples the estimation of event probabilities from the inference stage, which allows the introduction of accelerations to the alignment inference procedure. Second, it is general and can accommodate various stochastic models of indel formation. Finally, it allows computing the maximum-likelihood alignment, the probability of a given pair of sequences integrated over all possible alignments, and sampling alternative alignments according to their probability. We first show that SimBa-SAl allows accurate estimation of parameters of the long-indel model previously developed by Miklós, Lunter and Holmes in 2004. We next show that SimBa-SAl is more accurate than previously developed pairwise alignment algorithms, when analyzing simulated as well as empirical datasets. Finally, we study the goodness-of-fit of the long-indel and TKF91 models. We show that while the long-indel model fits the datasets better than TKF91, there is still room for improvement concerning the realistic modeling of evolutionary sequence dynamics.
Data from: Current methods for automated filtering of multiple sequence alignments frequently worsen single-gene phylogenetic inference
Phylogenetic inference is generally performed on the basis of multiple sequence alignments (MSA). Because errors in an alignment can lead to errors in tree estimation, there is a strong interest in identifying and removing unreliable parts of the alignment. In recent years several automated filtering approaches have been proposed, but despite their popularity, a systematic and comprehensive comparison of different alignment filtering methods on real data has been lacking. Here, we extend and apply recently introduced phylogenetic tests of alignment accuracy on a large number of gene families and contrast the performance of unfiltered versus filtered alignments in the context of single-gene phylogeny reconstruction. Based on multiple genome-wide empirical and simulated data sets, we show that the trees obtained from filtered MSAs are on average worse than those obtained from unfiltered MSAs. Furthermore, alignment filtering often leads to an increase in the proportion of well-supported branches that are actually wrong. We confirm that our findings hold for a wide range of parameters and methods. Although our results suggest that light filtering (up to 20% of alignment positions) has little impact on tree accuracy and may save some computation time, contrary to widespread practice, we do not generally recommend the use of current alignment filtering methods for phylogenetic inference. By providing a way to rigorously and systematically measure the impact of filtering on alignments, the methodology set forth here will guide the development of better filtering algorithms.
Data from: Controlling population of the molecular rotational state and the alignment theoretically by tailored femtosecond laser pulse
We demonstrate that the population of the molecular rotational state through a stimulated impulsive Raman excitation can be controlled by tailoring the femtosecond laser pulse with a V-style phase modulation. The results show that, by precisely manipulating the modulation parameters, both the odd and even populations of the molecular rotational state can be completely suppressed or reconstructed. Meanwhile, the relative excitation between the odd and even populations can be obtained. Finally, we show that field-free molecular alignment can be controlled due to the modulation of the molecular rotational state populations.
Data from: Cross-platform compatibility of de novo-aligned SNPs in a non-model butterfly genus
High-throughput sequencing methods for genotyping genome-wide markers are being rapidly adopted for phylogenetics of non-model organisms in conservation and biodiversity studies. However, the reproducibility of SNP genotyping and degree of marker overlap or compatibility between datasets from different methodologies have not been tested in non-model systems. Using double-digest restriction site associated DNA sequencing, we sequenced a common set of 22 specimens from the butterfly genus Speyeria on two different Illumina platforms, using two variations of library preparation. We then used a de novo approach to bioinformatic locus assembly and SNP discovery for subsequent phylogenetic analyses. We found a high rate of locus recovery despite differences in library preparation and sequencing platforms, as well as overall high levels of data compatibility after data processing and filtering. These results provide the first application of NGS methods for phylogenetic reconstruction in Speyeria, and support the use and long-term viability of SNP genotyping applications in non-model systems.
Data from: Effects of mis-alignment between dispersal traits and landscape structure on dispersal success in fragmented landscapes
Dispersal is fundamental to population dynamics and hence extinction risk. The dispersal success of animals depends on the biophysical structure of their environments and their biological traits; however, comparatively little is known about how evolutionary trade-offs among suites of biological traits affect dispersal potential. We developed a spatially explicit agent-based simulation model to evaluate the influence of trade-offs among a suite of biological traits on the dispersal success of vagile animals in fragmented landscapes. We specifically chose traits known to influence dispersal success: speed of movement, perceptual range, risk of predation, need to forage during dispersal, and amount of suitable habitat required for successful settlement in a patch. Using the metric of relative dispersal success rate, we assessed how the costs and benefits of evolutionary investment in these biological traits varied with landscape structure. In heterogeneous environments with low habitat availability and scattered habitat patches, individuals with more equal allocation across the trait spectrum dispersed most successfully. Our analyses suggest that the dispersal success of animals in heterogeneous environments is highly dependent on hierarchical interactions between trait trade-offs and the geometric configurations of the habitat patches in the landscapes through which they disperse. In an applied sense, our results indicate potential for ecological mis-alignment between species' evolved suites of dispersal-related traits and altered environmental conditions as a result of rapid global change. In many cases identifying the processes that shape patterns of animal dispersal, and the consequences of abiotic changes for these processes, will require consideration of complex relationships among a range of organism-specific and environmental factors.
Data from: Exploring data interaction and nucleotide alignment in a multiple gene analysis of Ips (Coleoptera: Scolytinae)
The possibility of gene tree incongruence in a species-level phylogenetic analysis of the genus Ips (Coleoptera: Scolytidae) was investigated based on mitochondrial 16S rRNA and nuclear Elongation factor-1α sequences, and existing Cytochrome Oxidase I and non-molecular data sets. Separate cladistic analyses of the data partitions resulted in partially discordant most-parsimonious trees but revealed only low conflict of the phylogenetic signal. Interactions among data partitions, which differed in the level of sequence divergence (COI > 16S > EF-1α), base composition, and homoplasy, revealed that much of the branch support only emerges in the simultaneous analysis, in particular for deeper nodes in the tree which are almost entirely supported due to "hidden support" (sensu Gatesy et al., 1999). Apparent incongruence between data partitions is in part due to suboptimal alignments and bias of character transformations, but there is little evidence to invoke incongruent phylogenetic histories of genetic loci. There is also no justification for eliminating or downweighting gene partitions based on their level of homoplasy or apparent incongruence with other partitions, as the signal only emerges in the interaction of all data. In comparison to the traditional taxonomy, the pini, plastographus and perturbatus groups are polyphyletic, whereas the grandicollis group is monophyletic except for the inclusion of the (monophyletic) calligraphus group. The latidens group and some European species are distantly related and closer to other genera within Ipini. Our robust cladogram was used to revise the classification of Ips. We provide new diagnoses for Ips and four subgeneric taxa.
Data from: ALS drug development guidances and trial guidelines: consensus and opportunities for alignment
The Food and Drug Administration (FDA) developed a draft guidance for drug development in Amyotrophic Lateral Sclerosis (ALS) that was issued in February 2018. The FDA draft guidance considered the recommendations developed by the ALS community which incorporated the views of a large group of clinical investigators, industry representatives, advocacy groups, patients, and caregivers. This external input from the ALS community reviewed the current state of clinical research in ALS and made suggestions over a wide range of drug development topics and served as an educational tool to provide the Agency with additional inputs about ALS, the state of the science and the community's views on key topics. In parallel to this effort, there was an independent effort to revise and update the ALS clinical trial guidelines. We discuss the areas of agreement of these three documents, and the areas that provide opportunities to improve the efficiency of drug development in ALS. It is likely that further research into biomarkers, efficacy endpoints, and predictive algorithms will provide greater alignment among community stakeholders and increase clarity on drug development efforts going forward. Continued patient engagement and inclusion of patient experience data in every aspect of the drug development process will further facilitate the approval of new treatments.
Data from: Diversity measures in environmental sequences are highly dependent on alignment quality—data from ITS and new LSU primers targeting basidiomycetes
The ribosomal DNA comprised of the ITS1-5.8S-ITS2 regions is widely used as a fungal marker in molecular ecology and systematics but cannot be aligned with confidence across genetically distant taxa. In order to study the diversity of Agaricomycotina in forest soils, we designed primers targeting the more alignable 28S (LSU) gene, which should be more useful for phylogenetic analyses of the detected taxa. This paper compares the performance of the established ITS1F/4B primer pair, which targets basidiomycetes, to that of two new pairs. Key factors in the comparison were the diversity covered, off-target amplification, rarefaction at different Operational Taxonomic Unit (OTU) cutoff levels, sensitivity of the method used to process the alignment to missing data and insecure positional homology, and the congruence of monophyletic clades with OTU assignments and BLAST-derived OTU names. The ITS primer pair yielded no off-target amplification but also exhibited the least fidelity to the expected phylogenetic groups. The LSU primers give complementary pictures of diversity, but were more sensitive to modifications of the alignment such as the removal of difficult-to align stretches. The LSU primers also yielded greater numbers of singletons but also had a greater tendency to produce OTUs containing sequences from a wider variety of species as judged by BLAST similarity. We introduced some new parameters to describe alignment heterogeneity based on Shannon entropy and the extent and contents of the OTUs in a phylogenetic tree space. Our results suggest that ITS should not be used when calculating phylogenetic trees from genetically distant sequences obtained from environmental DNA extractions and that it is inadvisable to define OTUs on the basis of very heterogeneous alignments.
Data from: GHOST: Recovering Historical Signal from Heterotachously-evolved Sequence Alignments
<p><span>Molecular sequence data that have evolved under the influence of heterotachous evolutionary processes are known to mislead phylogenetic inference. We introduce the General Heterogeneous evolution On a Single Topology (GHOST) model of sequence evolution, implemented under a maximum-likelihood framework in the phylogenetic program IQ-TREE (</span><a class="link link-uri" href="http://www.iqtree.org/">http://www.iqtree.org</a><span>). Simulations show that using the GHOST model, IQ-TREE can accurately recover the tree topology, branch lengths, and substitution model parameters from heterotachously evolved sequences. We investigate the performance of the GHOST model on empirical data by sampling phylogenomic alignments of varying lengths from a plastome alignment. We then carry out inference under the GHOST model on a phylogenomic data set composed of 248 genes from 16 taxa, where we find the GHOST model concurs with the currently accepted view, placing turtles as a sister lineage of archosaurs, in contrast to results obtained using traditional variable rates-across-sites models. Finally, we apply the model to a data set composed of a sodium channel gene of 11 fish taxa, finding that the GHOST model is able to elucidate a subtle component of the historical signal, linked to the previously established convergent evolution of the electric organ in two geographically distinct lineages of electric fish. We compare inference under the GHOST model to partitioning by codon position and show that, owing to the minimization of model constraints, the GHOST model offers unique biological insights when applied to empirical data.</span></p>
MtDNA genomes from Ranis individuals aligned with previously published ancient & modern humans
<p>The Middle to Upper Palaeolithic transition in Europe is associated with the regional disappearance of Neanderthals and the spread of Homo sapiens. Archaeological evidence indicates the presence of technocomplexes at the interface of this transition, complicating our understanding of the period and the association of those with specific hominin groups. One such technocomplex where the maker is unknown is the Lincombian-Ranisian-Jerzmanowician (LRJ), which covers an area in northwestern and central Europe from the UK to Poland. This paper presents the morphological and proteomic species identification, mitochondrial DNA analysis, and direct radiocarbon dating of human remains directly associated to an LRJ assemblage at the cave site of Ilsenhöhle in Ranis (Germany). </p>
HCV IVT 002 - Aligned Signals to HCV [Two Replicates]
Open the record for dataset details and reuse information.
Alignments of Sequence Data for Phylogenetic Analysis of Damsel
<p>Initially described in 1882, <i>Chromis enchrysurus</i>, the Yellowtail Reeffish, was redescribed in 1982 to account for an observed color morph that possesses a white tail instead of a yellow one, but morphological and geographic boundaries between the two color morphs were not well understood. Taking advantage of newly collected material from submersible studies of deep reefs and photographs from rebreather dives, we sought to determine whether the white-tailed <i>Chromis</i> is actually a color morph of <i>Chromis enchrysurus</i> or a distinct species. These alignments for mitochondrial genes cytochrome b and cytochrome c oxidase subunit I were used to generate phylogenetic trees that separated <i>Chromis enchrysurus</i> and the white-tailed <i>Chromis</i> into two reciprocally monophyletic clades. Genetic, morphological, and biogeographic data all indicate that the white-tailed <i>Chromis</i> is a distinct species, herein described as <i>Chromis vanbebberae </i>sp. nov. The discovery of a new species within a conspicuous group such as damselfishes in a well-studied region of the world highlights the importance of deep-reef exploration in documenting undiscovered biodiversity.</p>
Molecular systematics of the tribe Physarieae (Brassicaceae) based on the nuclear ITS, LUMINIDEPENDENS, and chloroplast ndhF: Sequence alignments, trees, and supplemental figures
<p>Physarieae is a small tribe of herbaceous annual and woody perennial mustards that are mostly endemic to North America, with its members including a large amount of variation in floral, fruit and chromosomal variation. Building on a previous study of Physarieae based on morphology and <i>ndhF</i> plastid DNA, we reconstructed the evolutionary history of the tribe using new sequence data from two nuclear markers, and compared the new topologies against previously published cpDNA-based phylogenetic hypotheses. The novel analyses included ca. 420 new sequences of ITS and <i>LUMINIDEPENDENS</i> (<i>LD</i>) markers for 39 and 47 species, respectively, with sampling accounting for all seven genera of Physarieae, including nomenclatural type species, and 11 outgroup taxa. Maximum parsimony, maximum likelihood, and Bayesian analyses showed that these additional markers were largely consistent with the previous <i>ndh</i>F data that supported the monophyly of Physarieae and resolved two major clades within the tribe, i.e. DDNLS (<i>Dithyrea</i>, <i>Dimorphocarpa</i>, <i>Nerisyrenia</i>, <i>Lyrocarpa</i>, and <i>Synthlipsis</i>) and PP (<i>Paysonia</i> and <i>Physaria</i>). New analyses also increased internal resolution for some closely related species and lineages within both clades. The monophyly<i> </i>of <i>Dithyrea</i> and the sister relationship of <i>Paysonia</i> to <i>Physaria</i> was consistent in all trees, with the sister relationship of <i>Nerisyrenia </i>to <i>Lyrocarpa </i>supported by <i>ndhF</i> and <i>ITS</i>, and the positions of <i>Dimorphocarpa</i> and <i>Synthlipsis</i> shifted within the DDNLS Clade depending on the employed data set. Finally, using the strong, new phylogenetic framework of combined cpDNA + nDNA data, we discussed standing hypotheses of trichome evolution in the tribe suggested by <i>ndhF</i>.</p>
Phenotypic plasticity is aligned with phenological adaptation on micro- and macroevolutionary timescales
<p><span><span><span><span><span><span><span><span><span><span><span>In seasonally-variable environments, phenotypic plasticity in phenology may be critical for adaptation to fluctuating environmental conditions. Using an 18-generation longitudinal dataset from natural damselfly populations, we show that phenology has strongly advanced. Individual fitness data suggest this is likely an adaptive response towards a temperature-dependent optimum. A laboratory experiment revealed that developmental plasticity qualitatively matches the temperature-dependence of selection, partially explaining observed advance in phenology. Expanding our analysis to the macroevolutionary level, we use a database of over 1-million occurrence records and spatiotemporally-matched temperature data from 49 Swedish Odonate species to infer macroevolutionary dynamics of phenology. Phenological plasticity was more closely aligned with adaptation for species that have recently colonized northern latitudes, but with higher phenological mismatch at lower latitudes. Our results show that phenological plasticity plays a key role in microevolutionary dynamics within a single species, and such plasticity may have facilitated post-Pleistocene range expansion in this insect clade. </span></span></span></span></span></span></span></span></span></span></span></p>
Raw data accompanying "A supramolecular and liquid crystalline water‐based alignment medium based on azobenzene‐substituted 1,3,5‐benzenetricarboxamides"
<p>Raw spectral data files for NMR, CD and UV/VIs measurements.</p>
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