The recently discovered DPANN archaea are a potentially deep-branching, monophyletic radiation of organisms with small cells and genomes. However, the monophyly and early emergence of the various ...DPANN clades and their role in life's evolution are debated. Here, we reconstructed and analysed genomes of an uncharacterized archaeal phylum (Candidatus Undinarchaeota), revealing that its members have small genomes and, while potentially being able to conserve energy through fermentation, likely depend on partner organisms for the acquisition of certain metabolites. Our phylogenomic analyses robustly place Undinarchaeota as an independent lineage between two highly supported 'DPANN' clans. Further, our analyses suggest that DPANN have exchanged core genes with their hosts, adding to the difficulty of placing DPANN in the tree of life. This pattern can be sufficiently dominant to allow identifying known symbiont-host clades based on routes of gene transfer. Together, our work provides insights into the origins and evolution of DPANN and their hosts.
GHOST Crotty, Stephen M.; Minh, Bui Quang; Bean, Nigel G. ...
Systematic biology,
03/2020, Letnik:
69, Številka:
2
Journal Article
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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 (http://www.iqtree.org). Simulations showthat 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 themodel 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.
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BFBNIB, DOBA, IZUM, KILJ, NMLJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We present a reversible Polymorphism-Aware Phylogenetic Model (revPoMo) for species tree estimation from genome-wide data. revPoMo enables the reconstruction of large scale species trees for many ...within-species samples. It expands the alphabet of DNA substitution models to include polymorphic states, thereby, naturally accounting for incomplete lineage sorting. We implemented revPoMo in the maximum likelihood software IQ-TREE. A simulation study and an application to great apes data show that the runtimes of our approach and standard substitution models are comparable but that revPoMo has much better accuracy in estimating trees, divergence times and mutation rates. The advantage of revPoMo is that an increase of sample size per species improves estimations but does not increase runtime. Therefore, revPoMo is a valuable tool with several applications, from speciation dating to species tree reconstruction.
•Species tree inference from genome-wide population data.•Takes incomplete lineage sorting into account.•Analytical solution of stationary distribution and formal proof of reversibility.•Reversibility ensures swiftness and stability.•Increase of sample size per species improves estimations without raising runtime.•Comparison to the Wright-Fisher diffusion.
Adaptive Neuro-Fuzzy Inference System (ANFIS) is a robust method in solving non-linear classification by employing a human-readable interpretation manner. This paper verified a hybrid model, named ...WANFIS, where Whale Optimization Algorithm (WOA) was used for feature selection and tuning parameters of the ANFIS for land-cover classification. Hanoi, the capital of Vietnam, was selected as a case study, because of its complex surface morphology. The model was trained and validated with different data sets, which were subsets of the segmented objects from SPOT 7 satellite data (1.5 m in panchromatic and 6 m multiple spectral bands). The image segmentation was carried out by using PCI Geomatics software (evaluation version), and output objects with associated spectral, shape, and metric information were selected as input data to train and validate the proposed model. For accuracy assessment, the performance of the model was compared to several benchmarked classifiers by using standard statistical indicators such as Receiver Operator Characteristics, Area under ROC, Root Mean Square Error, Absolute Mean Error, Kappa index, and Overall accuracy. The results showed that WANFIS outperformed the other in almost all training data sets for both operations. It could be concluded that the examination of the classification model in different training data sizes is significant, and the proper determination of predictor variables and training sizes would improve the quality of classification of remotely sensed data.
Molecular phylogenetics has neglected polymorphisms within present and ancestral populations for a long time. Recently, multispecies coalescent based methods have increased in popularity, however, ...their application is limited to a small number of species and individuals. We introduced a polymorphism-aware phylogenetic model (PoMo), which overcomes this limitation and scales well with the increasing amount of sequence data whereas accounting for present and ancestral polymorphisms. PoMo circumvents handling of gene trees and directly infers species trees from allele frequency data. Here, we extend the PoMo implementation in IQ-TREE and integrate search for the statistically best-fit mutation model, the ability to infer mutation rate variation across sites, and assessment of branch support values. We exemplify an analysis of a hundred species with ten haploid individuals each, showing that PoMo can perform inference on large data sets. While PoMo is more accurate than standard substitution models applied to concatenated alignments, it is almost as fast. We also provide bmm-simulate, a software package that allows simulation of sequences evolving under PoMo. The new options consolidate the value of PoMo for phylogenetic analyses with population data.
The nonparametric bootstrap is widely used to measure the branch support of phylogenetic trees. However, bootstrapping is computationally expensive and remains a bottleneck in phylogenetic analyses. ...Recently, an ultrafast bootstrap approximation (UFBoot) approach was proposed for maximum likelihood analyses. However, such an approach is still missing for maximum parsimony.
To close this gap we present MPBoot, an adaptation and extension of UFBoot to compute branch supports under the maximum parsimony principle. MPBoot works for both uniform and non-uniform cost matrices. Our analyses on biological DNA and protein showed that under uniform cost matrices, MPBoot runs on average 4.7 (DNA) to 7 times (protein data) (range: 1.2-20.7) faster than the standard parsimony bootstrap implemented in PAUP*; but 1.6 (DNA) to 4.1 times (protein data) slower than the standard bootstrap with a fast search routine in TNT (fast-TNT). However, for non-uniform cost matrices MPBoot is 5 (DNA) to 13 times (protein data) (range:0.3-63.9) faster than fast-TNT. We note that MPBoot achieves better scores more frequently than PAUP* and fast-TNT. However, this effect is less pronounced if an intensive but slower search in TNT is invoked. Moreover, experiments on large-scale simulated data show that while both PAUP* and TNT bootstrap estimates are too conservative, MPBoot bootstrap estimates appear more unbiased.
MPBoot provides an efficient alternative to the standard maximum parsimony bootstrap procedure. It shows favorable performance in terms of run time, the capability of finding a maximum parsimony tree, and high bootstrap accuracy on simulated as well as empirical data sets. MPBoot is easy-to-use, open-source and available at http://www.cibiv.at/software/mpboot .
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Assembling the global eukaryotic tree of life has long been a major effort of Biology. In recent years, pushed by the new availability of genome-scale data for microbial eukaryotes, it has become ...possible to revisit many evolutionary enigmas. However, some of the most ancient nodes, which are essential for inferring a stable tree, have remained highly controversial. Among other reasons, the lack of adequate genomic datasets for key taxa has prevented the robust reconstruction of early diversification events. In this context, the centrohelid heliozoans are particularly relevant for reconstructing the tree of eukaryotes because they represent one of the last substantial groups that was missing large and diverse genomic data. Here, we filled this gap by sequencing high-quality transcriptomes for four centrohelid lineages, each corresponding to a different family. Combining these new data with a broad eukaryotic sampling, we produced a gene-rich taxon-rich phylogenomic dataset that enabled us to refine the structure of the tree. Specifically, we show that (i) centrohelids relate to haptophytes, confirming Haptista; (ii) Haptista relates to SAR; (iii) Cryptista share strong affinity with Archaeplastida; and (iv) Haptista + SAR is sister to Cryptista + Archaeplastida. The implications of this topology are discussed in the broader context of plastid evolution.
In the present work, bio‐polyol has been synthesized via controlled hydroxylation from sunflower oil in one conversion step using a mixture of hydrogen peroxide and formic acid. The influences of ...various reaction conditions for bio‐polyol synthesis such as reaction time, temperature, the dosage of hydrogen peroxide, and formic acid were investigated. The bio‐polyol was obtained from sunflower oil with hydroxyl number of 180 mg KOH/g, and functionality of 3.5 OH groups/mol. The as‐synthesized sunflower oil‐based polyol was then used for replacing fossil‐based polyol in synthesis of bio‐based polyurethane (PU), which was then simultaneously combined with coir biomass filler to fabricate the porous material with high oil adsorption capacity. The oil adsorption capacity of the new bio‐based sorbent material was relatively high, up to 14.89 g/g. In comparison with pristine PU or lignocellulosic materials, the new sorbents had higher oil adsorption capacity.
The new designed porous bio‐sorbent with high oil adsorption capacity was fabricated by combining coir biomass with bio‐polyurethane.
This study aimed to investigate the effect of a surfactant on the liquid-liquid phase separation, dissolution, diffusion, and the oral bioavailability of a weakly basic drug (l-tetrahydropalmatine; ...l-THP) from an amorphous solid dispersion (ASD). The carrier used in the ASD was optimized by the application of casting film, solvent shift, and pH shift methods. The interaction between the optimized carrier (HPMCP) and l-THP was then evaluated by Fourier transform-infrared spectroscopy and powder X-ray diffraction. The impact of the surfactant on ASD prepared by the spray-drying method was evaluated by both in vitro and in vivo studies. The results of in vitro studies, including liquid-liquid phase separation, drug diffusion, and pH-shift dissolution, indicated that the addition of a surfactant at a certain concentration below critical micelle concentration to ASD caused the precipitation of and a reduction in the membrane diffusion of l-THP in pH 6.8. This observation was confirmed in an in vivo study in which the drug concentration of l-THP in rabbit plasma was determined by the LC-MS/MS analysis method. Then the absolute and relative bioavailability of l-THP was calculated from the obtained pharmacokinetic parameters. Specifically, the addition of 1.5% surfactant (Poloxamer 188) to the binary ASD decreased the relative bioavailability of l-THP by approximately 2.4 times compared with the original binary ASD. Besides, the study proved that l-THP had low absolute bioavailability (around 1.24%), and the application of binary ASD was meaningful in enhancing the oral bioavailability of l-THP by around 334.77% compared to the raw material. The study is expected to provide a better understanding of how different dosage forms influence the bioavailability of l-THP, thereby allowing the selection of the optimal approach for this weakly basic drug.
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Advances in earth observation and machine learning techniques have created new options for forest monitoring, primarily because of the various possibilities that they provide for classifying forest ...cover and estimating aboveground biomass (AGB).
This study aimed to introduce a novel model that incorporates the atom search algorithm (ASO) and adaptive neuro-fuzzy inference system (ANFIS) into mangrove forest classification and AGB estimation. The Ca Mau coastal area was selected as a case study since it has been considered the most preserved mangrove forest area in Vietnam and is being investigated for the impacts of land-use change on forest quality. The model was trained and validated with a set of Sentinel-1A imagery with VH and VV polarizations, and multispectral information from the SPOT image. In addition, feature selection was also carried out to choose the optimal combination of predictor variables. The model performance was benchmarked against conventional methods, such as support vector regression, multilayer perceptron, random subspace, and random forest, by using statistical indicators, namely, root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2).
The results showed that all three indicators of the proposed model were statistically better than those from the benchmarked methods. Specifically, the hybrid model ended up at RMSE = 70.882, MAE = 55.458, R2 = 0.577 for AGB estimation.
From the experiments, such hybrid integration can be recommended for use as an alternative solution for biomass estimation. In a broader context, the fast growth of metaheuristic search algorithms has created new scientifically sound solutions for better analysis of forest cover.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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