Triple Combination Antiviral Drug (TCAD) Composed of Amantadine, Oseltamivir, and Ribavirin Impedes the Selection of Drug-Resistant Influenza A Virus

Written by on December 29, 2011 – 10:00 pm -

by Justin D. Hoopes, Elizabeth M. Driebe, Erin Kelley, David M. Engelthaler, Paul S. Keim, Alan S. Perelson, Libin Rong, Gregory T. Went, Jack T. Nguyen

Widespread resistance among circulating influenza A strains to at least one of the anti-influenza drugs is a major public health concern. A triple combination antiviral drug (TCAD) regimen comprised of amantadine, oseltamivir, and ribavirin has been shown to have synergistic and broad spectrum activity against influenza A strains, including drug resistant strains. Here, we used mathematical modeling along with three different experimental approaches to understand the effects of single agents, double combinations, and the TCAD regimen on resistance in influenza in vitro, including: 1) serial passage at constant drug concentrations, 2) serial passage at escalating drug concentrations, and 3) evaluation of the contribution of each component of the TCAD regimen to the suppression of resistance. Consistent with the modeling which demonstrated that three drugs were required to suppress the emergence of resistance in influenza A, treatment with the TCAD regimen resulted in the sustained suppression of drug resistant viruses, whereas treatment with amantadine alone or the amantadine-oseltamivir double combination led to the rapid selection of resistant variants which comprised ∼100% of the population. Furthermore, the TCAD regimen imposed a high genetic barrier to resistance, requiring multiple mutations in order to escape the effects of all the drugs in the regimen. Finally, we demonstrate that each drug in the TCAD regimen made a significant contribution to the suppression of virus breakthrough and resistance at clinically achievable concentrations. Taken together, these data demonstrate that the TCAD regimen was superior to double combinations and single agents at suppressing resistance, and that three drugs at a minimum were required to impede the selection of drug resistant variants in influenza A virus. The use of mathematical modeling with multiple experimental designs and molecular readouts to evaluate and optimize combination drug regimens for the suppression of resistance may be broadly applicable to other infectious diseases.

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Time-Course Global Expression Profiles of Chlamydomonas reinhardtii during Photo-Biological H2 Production

Written by on December 29, 2011 – 10:00 pm -

by Anh Vu Nguyen, Joerg Toepel, Steven Burgess, Andreas Uhmeyer, Olga Blifernez, Anja Doebbe, Ben Hankamer, Peter Nixon, Lutz Wobbe, Olaf Kruse

We used a microarray study in order to compare the time course expression profiles of two Chlamydomonas reinhardtii strains, namely the high H2 producing mutant stm6glc4 and its parental WT strain during H2 production induced by sulfur starvation. Major cellular reorganizations in photosynthetic apparatus, sulfur and carbon metabolism upon H2 production were confirmed as common to both strains. More importantly, our results pointed out factors which lead to the higher H2 production in the mutant including a higher starch accumulation in the aerobic phase and a lower competition between the H2ase pathway and alternative electron sinks within the H2 production phase. Key candidate genes of interest with differential expression pattern include LHCSR3, essential for efficient energy quenching (qE). The reduced LHCSR3 protein expression in mutant stm6glc4 could be closely related to the high-light sensitive phenotype. H2 measurements carried out with the LHCSR3 knock-out mutant npq4 however clearly demonstrated that a complete loss of this protein has almost no impact on H2 yields under moderate light conditions. The nuclear gene disrupted in the high H2 producing mutant stm6glc4 encodes for the mitochondrial transcription termination factor (mTERF) MOC1, whose expression strongly increases during –S-induced H2 production in WT strains. Studies under phototrophic high-light conditions demonstrated that the presence of functional MOC1 is a prerequisite for proper LHCSR3 expression. Furthermore knock-down of MOC1 in a WT strain was shown to improve the total H2 yield significantly suggesting that this strategy could be applied to further enhance H2 production in other strains already displaying a high H2 production capacity. By combining our array data with previously published metabolomics data we can now explain some of the phenotypic characteristics which lead to an elevated H2 production in stm6glc4.

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Analysis of Biological Features Associated with Meiotic Recombination Hot and Cold Spots in Saccharomyces cerevisiae

Written by on December 29, 2011 – 10:00 pm -

by Loren Hansen, Nak-Kyeong Kim, Leonardo Mariño-Ramírez, David Landsman

Meiotic recombination is not distributed uniformly throughout the genome. There are regions of high and low recombination rates called hot and cold spots, respectively. The recombination rate parallels the frequency of DNA double-strand breaks (DSBs) that initiate meiotic recombination. The aim is to identify biological features associated with DSB frequency. We constructed vectors representing various chromatin and sequence-based features for 1179 DSB hot spots and 1028 DSB cold spots. Using a feature selection approach, we have identified five features that distinguish hot from cold spots in Saccharomyces cerevisiae with high accuracy, namely the histone marks H3K4me3, H3K14ac, H3K36me3, and H3K79me3; and GC content. Previous studies have associated H3K4me3, H3K36me3, and GC content with areas of mitotic recombination. H3K14ac and H3K79me3 are novel predictions and thus represent good candidates for further experimental study. We also show nucleosome occupancy maps produced using next generation sequencing exhibit a bias at DSB hot spots and this bias is strong enough to obscure biologically relevant information. A computational approach using feature selection can productively be used to identify promising biological associations. H3K14ac and H3K79me3 are novel predictions of chromatin marks associated with meiotic DSBs. Next generation sequencing can exhibit a bias that is strong enough to lead to incorrect conclusions. Care must be taken when interpreting high throughput sequencing data where systematic biases have been documented.

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Controlling the Spread of Disease in Schools

Written by on December 29, 2011 – 10:00 pm -

by Benjamin J. Ridenhour, Alexis Braun, Thomas Teyrasse, David Goldsman

Pandemic and seasonal infectious diseases such as influenza may have serious negative health and economic consequences. Certain non-pharmaceutical intervention strategies – including school closures – can be implemented rapidly as a first line of defense against spread. Such interventions attempt to reduce the effective number of contacts between individuals within a community; yet the efficacy of closing schools to reduce disease transmission is unclear, and closures certainly result in significant economic impacts for caregivers who must stay at home to care for their children. Using individual-based computer simulation models to trace contacts among schoolchildren within a stereotypical school setting, we show how alternative school-based disease interventions have great potential to be as effective as traditional school closures without the corresponding loss of workforce and economic impacts.

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Prognostic Significance of Vitamin D Receptor Polymorphisms in Head and Neck Squamous Cell Carcinoma

Written by on December 29, 2011 – 10:00 pm -

by Takanori Hama, Chihiro Norizoe, Hiroaki Suga, Takeshi Mimura, Takakuni Kato, Hiroshi Moriyama, Mitsuyoshi Urashima

Background

In patients with advanced non-small-cell lung cancer, vitamin D receptor (VDR) polymorphisms and haplotypes are reported to be associated with survival. We hypothesized that a similar association would be observed in patients with head and neck squamous-cell carcinoma (HNSCC).

Methods

In a post-hoc analysis of our previous prospective cohort study, VDR polymorphisms including Cdx2 G/A (rs11568820), FokI C/T (rs10735810), BsmI A/G (rs1544410), ApaI G/T (rs7976091), and TaqI T/C (rs731236) were genotyped by sequencing in 204 consecutive patients with HNSCC who underwent tumor resection. Progression-free survival was compared between VDR polymorphisms using Kaplan-Meier survival curves with log-rank tests and Cox proportional hazard models adjusting for age, gender, smoking status, primary tumor sites, postoperative stages, existence of residual tumor, and postoperative treatment with chemotherapy or radiotherapy.

Results

During a median follow-up of 1,047 days, tumor progression and death occurred in 76 (37.3%) and 27 (13.2%) patients, respectively. The FokI T/T genotype was associated with poor progression-free survival: median survival for T/T was 265 days compared with 1,127 days for C/C or C/T (log-rank test: P = 0.0004; adjusted hazard ratio, 3.03; 95% confidence interval, 1.62 to 5.67; P = 0.001). In contrast, the other polymorphisms (Cdx2, BsmI, ApaI, TaqI) showed no significant association with progression-free survival. The A-T-G (Cdx2-FokI-ApaI) haplotype demonstrated a significant association with a higher progression rate (P = 0.02).

Conclusion

These results suggest that VDR polymorphisms and haplotypes may be associated with prognosis in patients with HNSCC, although the sample size is not large enough to draw definitive conclusions.


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Probing the SELEX Process with Next-Generation Sequencing

Written by on December 29, 2011 – 10:00 pm -

by Tatjana Schütze, Barbara Wilhelm, Nicole Greiner, Hannsjörg Braun, Franziska Peter, Mario Mörl, Volker A. Erdmann, Hans Lehrach, Zoltán Konthur, Marcus Menger, Peter F. Arndt, Jörn Glökler

Background

SELEX is an iterative process in which highly diverse synthetic nucleic acid libraries are selected over many rounds to finally identify aptamers with desired properties. However, little is understood as how binders are enriched during the selection course. Next-generation sequencing offers the opportunity to open the black box and observe a large part of the population dynamics during the selection process.

Methodology

We have performed a semi-automated SELEX procedure on the model target streptavidin starting with a synthetic DNA oligonucleotide library and compared results obtained by the conventional analysis via cloning and Sanger sequencing with next-generation sequencing. In order to follow the population dynamics during the selection, pools from all selection rounds were barcoded and sequenced in parallel.

Conclusions

High affinity aptamers can be readily identified simply by copy number enrichment in the first selection rounds. Based on our results, we suggest a new selection scheme that avoids a high number of iterative selection rounds while reducing time, PCR bias, and artifacts.


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Role of Conserved Non-Coding Regulatory Elements in LMW Glutenin Gene Expression

Written by on December 29, 2011 – 10:00 pm -

by Angéla Juhász, Szabolcs Makai, Endre Sebestyén, László Tamás, Ervin Balázs

Transcriptional regulation of LMW glutenin genes were investigated in-silico, using publicly available gene sequences and expression data. Genes were grouped into different LMW glutenin types and their promoter profiles were determined using cis-acting regulatory elements databases and published results. The various cis-acting elements belong to some conserved non-coding regulatory regions (CREs) and might act in two different ways. There are elements, such as GCN4 motifs found in the long endosperm box that could serve as key factors in tissue-specific expression. Some other elements, such as the AACA/TA motifs or the individual prolamin box variants, might modulate the level of expression. Based on the promoter sequences and expression characteristic LMW glutenin genes might be transcribed following two different mechanisms. Most of the s- and i-type genes show a continuously increasing expression pattern. The m-type genes, however, demonstrate normal distribution in their expression profiles. Differences observed in their expression could be related to the differences found in their promoter sequences. Polymorphisms in the number and combination of cis-acting elements in their promoter regions can be of crucial importance in the diverse levels of production of single LMW glutenin gene types.

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Predicting Biological Functions of Compounds Based on Chemical-Chemical Interactions

Written by on December 29, 2011 – 10:00 pm -

by Le-Le Hu, Chen Chen, Tao Huang, Yu-Dong Cai, Kuo-Chen Chou

Given a compound, how can we effectively predict its biological function? It is a fundamentally important problem because the information thus obtained may benefit the understanding of many basic biological processes and provide useful clues for drug design. In this study, based on the information of chemical-chemical interactions, a novel method was developed that can be used to identify which of the following eleven metabolic pathway classes a query compound may be involved with: (1) Carbohydrate Metabolism, (2) Energy Metabolism, (3) Lipid Metabolism, (4) Nucleotide Metabolism, (5) Amino Acid Metabolism, (6) Metabolism of Other Amino Acids, (7) Glycan Biosynthesis and Metabolism, (8) Metabolism of Cofactors and Vitamins, (9) Metabolism of Terpenoids and Polyketides, (10) Biosynthesis of Other Secondary Metabolites, (11) Xenobiotics Biodegradation and Metabolism. It was observed that the overall success rate obtained by the method via the 5-fold cross-validation test on a benchmark dataset consisting of 3,137 compounds was 77.97%, which is much higher than 10.45%, the corresponding success rate obtained by the random guesses. Besides, to deal with the situation that some compounds may be involved with more than one metabolic pathway class, the method presented here is featured by the capacity able to provide a series of potential metabolic pathway classes ranked according to the descending order of their likelihood for each of the query compounds concerned. Furthermore, our method was also applied to predict 5,549 compounds whose metabolic pathway classes are unknown. Interestingly, the results thus obtained are quite consistent with the deductions from the reports by other investigators. It is anticipated that, with the continuous increase of the chemical-chemical interaction data, the current method will be further enhanced in its power and accuracy, so as to become a useful complementary vehicle in annotating uncharacterized compounds for their biological functions.

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Bidirectional Coupling between Astrocytes and Neurons Mediates Learning and Dynamic Coordination in the Brain: A Multiple Modeling Approach

Written by on December 29, 2011 – 10:00 pm -

by John J. Wade, Liam J. McDaid, Jim Harkin, Vincenzo Crunelli, J. A. Scott Kelso

In recent years research suggests that astrocyte networks, in addition to nutrient and waste processing functions, regulate both structural and synaptic plasticity. To understand the biological mechanisms that underpin such plasticity requires the development of cell level models that capture the mutual interaction between astrocytes and neurons. This paper presents a detailed model of bidirectional signaling between astrocytes and neurons (the astrocyte-neuron model or AN model) which yields new insights into the computational role of astrocyte-neuronal coupling. From a set of modeling studies we demonstrate two significant findings. Firstly, that spatial signaling via astrocytes can relay a “learning signal” to remote synaptic sites. Results show that slow inward currents cause synchronized postsynaptic activity in remote neurons and subsequently allow Spike-Timing-Dependent Plasticity based learning to occur at the associated synapses. Secondly, that bidirectional communication between neurons and astrocytes underpins dynamic coordination between neuron clusters. Although our composite AN model is presently applied to simplified neural structures and limited to coordination between localized neurons, the principle (which embodies structural, functional and dynamic complexity), and the modeling strategy may be extended to coordination among remote neuron clusters.

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Genome Analysis of Cytochrome P450s and Their Expression Profiles in Insecticide Resistant Mosquitoes, Culex quinquefasciatus

Written by on December 29, 2011 – 10:00 pm -

by Ting Yang, Nannan Liu

Here we report a study of the 204 P450 genes in the whole genome sequence of larvae and adult Culex quinquefasciatus mosquitoes. The expression profiles of the P450 genes were compared for susceptible (S-Lab) and resistant mosquito populations, two different field populations of mosquitoes (HAmCq and MAmCq), and field parental mosquitoes (HAmCq G0 and MAmCqG0) and their permethrin selected offspring (HAmCq G8 and MAmCqG6). While the majority of the P450 genes were expressed at a similar level between the field parental strains and their permethrin selected offspring, an up- or down-regulation feature in the P450 gene expression was observed following permethrin selection. Compared to their parental strains and the susceptible S-Lab strain, HAmCqG8 and MAmCqG6 were found to up-regulate 11 and 6% of total P450 genes in larvae and 7 and 4% in adults, respectively, while 5 and 11% were down-regulated in larvae and 4 and 2% in adults. Although the majority of these up- and down-regulated P450 genes appeared to be developmentally controlled, a few were either up- or down-regulated in both the larvae and adult stages. Interestingly, a different gene set was found to be up- or down-regulated in the HAmCqG8 and MAmCqG6 mosquito populations in response to insecticide selection. Several genes were identified as being up- or down-regulated in either the larvae or adults for both HAmCqG8 and MAmCqG6; of these, CYP6AA7 and CYP4C52v1 were up-regulated and CYP6BY3 was down-regulated across the life stages and populations of mosquitoes, suggesting a link with the permethrin selection in these mosquitoes. Taken together, the findings from this study indicate that not only are multiple P450 genes involved in insecticide resistance but up- or down-regulation of P450 genes may also be co-responsible for detoxification of insecticides, insecticide selection, and the homeostatic response of mosquitoes to changes in cellular environment.

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Minimal Absent Words in Four Human Genome Assemblies

Written by on December 29, 2011 – 10:00 pm -

by Sara P. Garcia, Armando J. Pinho

Minimal absent words have been computed in genomes of organisms from all domains of life. Here, we aim to contribute to the catalogue of human genomic variation by investigating the variation in number and content of minimal absent words within a species, using four human genome assemblies. We compare the reference human genome GRCh37 assembly, the HuRef assembly of the genome of Craig Venter, the NA12878 assembly from cell line GM12878, and the YH assembly of the genome of a Han Chinese individual. We find the variation in number and content of minimal absent words between assemblies more significant for large and very large minimal absent words, where the biases of sequencing and assembly methodologies become more pronounced. Moreover, we find generally greater similarity between the human genome assemblies sequenced with capillary-based technologies (GRCh37 and HuRef) than between the human genome assemblies sequenced with massively parallel technologies (NA12878 and YH). Finally, as expected, we find the overall variation in number and content of minimal absent words within a species to be generally smaller than the variation between species.

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The Role of Osteopontin (OPN/SPP1) Haplotypes in the Susceptibility to Crohn’s Disease

Written by on December 29, 2011 – 10:00 pm -

by Jürgen Glas, Julia Seiderer, Corinna Bayrle, Martin Wetzke, Christoph Fries, Cornelia Tillack, Torsten Olszak, Florian Beigel, Christian Steib, Matthias Friedrich, Julia Diegelmann, Darina Czamara, Stephan Brand

Background

Osteopontin represents a multifunctional molecule playing a pivotal role in chronic inflammatory and autoimmune diseases. Its expression is increased in inflammatory bowel disease (IBD). The aim of our study was to analyze the association of osteopontin (OPN/SPP1) gene variants in a large cohort of IBD patients.

Methodology/Principal Findings

Genomic DNA from 2819 Caucasian individuals (n = 841 patients with Crohn's disease (CD), n = 473 patients with ulcerative colitis (UC), and n = 1505 healthy unrelated controls) was analyzed for nine OPN SNPs (rs2728127, rs2853744, rs11730582, rs11739060, rs28357094, rs4754 = p.Asp80Asp, rs1126616 = p.Ala236Ala, rs1126772 and rs9138). Considering the important role of osteopontin in Th17-mediated diseases, we performed analysis for epistasis with IBD-associated IL23R variants and analyzed serum levels of the Th17 cytokine IL-22. For four OPN SNPs (rs4754, rs1126616, rs1126772 and rs9138), we observed significantly different distributions between male and female CD patients. rs4754 was protective in male CD patients (p = 0.0004, OR = 0.69). None of the other investigated OPN SNPs was associated with CD or UC susceptibility. However, several OPN haplotypes showed significant associations with CD susceptibility. The strongest association was found for a haplotype consisting of the 8 OPN SNPs rs2728127-rs2853744-rs11730582-rs11439060-rs28357094-rs112661-rs1126772-rs9138 (omnibus p-value = 2.07×10−8). Overall, the mean IL-22 secretion in the combined group of OPN minor allele carriers with CD was significantly lower than that of CD patients with OPN wildtype alleles (p = 3.66×10−5). There was evidence for weak epistasis between the OPN SNP rs28357094 with the IL23R SNP rs10489629 (p = 4.18×10−2) and between OPN SNP rs1126616 and IL23R SNP rs2201841 (p = 4.18×10−2) but none of these associations remained significant after Bonferroni correction.

Conclusions/Significance

Our study identified OPN haplotypes as modifiers of CD susceptibility, while the combined effects of certain OPN variants may modulate IL-22 secretion.


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Influence of Statistical Estimators of Mutual Information and Data Heterogeneity on the Inference of Gene Regulatory Networks

Written by on December 29, 2011 – 10:00 pm -

by Ricardo de Matos Simoes, Frank Emmert-Streib

The inference of gene regulatory networks from gene expression data is a difficult problem because the performance of the inference algorithms depends on a multitude of different factors. In this paper we study two of these. First, we investigate the influence of discrete mutual information (MI) estimators on the global and local network inference performance of the C3NET algorithm. More precisely, we study different MI estimators (Empirical, Miller-Madow, Shrink and Schürmann-Grassberger) in combination with discretization methods (equal frequency, equal width and global equal width discretization). We observe the best global and local inference performance of C3NET for the Miller-Madow estimator with an equal width discretization. Second, our numerical analysis can be considered as a systems approach because we simulate gene expression data from an underlying gene regulatory network, instead of making a distributional assumption to sample thereof. We demonstrate that despite the popularity of the latter approach, which is the traditional way of studying MI estimators, this is in fact not supported by simulated and biological expression data because of their heterogeneity. Hence, our study provides guidance for an efficient design of a simulation study in the context of network inference, supporting a systems approach.

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Automated Discovery of Food Webs from Ecological Data Using Logic-Based Machine Learning

Written by on December 29, 2011 – 10:00 pm -

by David A. Bohan, Geoffrey Caron-Lormier, Stephen Muggleton, Alan Raybould, Alireza Tamaddoni-Nezhad

Networks of trophic links (food webs) are used to describe and understand mechanistic routes for translocation of energy (biomass) between species. However, a relatively low proportion of ecosystems have been studied using food web approaches due to difficulties in making observations on large numbers of species. In this paper we demonstrate that Machine Learning of food webs, using a logic-based approach called A/ILP, can generate plausible and testable food webs from field sample data. Our example data come from a national-scale Vortis suction sampling of invertebrates from arable fields in Great Britain. We found that 45 invertebrate species or taxa, representing approximately 25% of the sample and about 74% of the invertebrate individuals included in the learning, were hypothesized to be linked. As might be expected, detritivore Collembola were consistently the most important prey. Generalist and omnivorous carabid beetles were hypothesized to be the dominant predators of the system. We were, however, surprised by the importance of carabid larvae suggested by the machine learning as predators of a wide variety of prey. High probability links were hypothesized for widespread, potentially destabilizing, intra-guild predation; predictions that could be experimentally tested. Many of the high probability links in the model have already been observed or suggested for this system, supporting our contention that A/ILP learning can produce plausible food webs from sample data, independent of our preconceptions about “who eats whom.” Well-characterised links in the literature correspond with links ascribed with high probability through A/ILP. We believe that this very general Machine Learning approach has great power and could be used to extend and test our current theories of agricultural ecosystem dynamics and function. In particular, we believe it could be used to support the development of a wider theory of ecosystem responses to environmental change.

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Advantages of a Mechanistic Codon Substitution Model for Evolutionary Analysis of Protein-Coding Sequences

Written by on December 29, 2011 – 10:00 pm -

by Sanzo Miyazawa

Background

A mechanistic codon substitution model, in which each codon substitution rate is proportional to the product of a codon mutation rate and the average fixation probability depending on the type of amino acid replacement, has advantages over nucleotide, amino acid, and empirical codon substitution models in evolutionary analysis of protein-coding sequences. It can approximate a wide range of codon substitution processes. If no selection pressure on amino acids is taken into account, it will become equivalent to a nucleotide substitution model. If mutation rates are assumed not to depend on the codon type, then it will become essentially equivalent to an amino acid substitution model. Mutation at the nucleotide level and selection at the amino acid level can be separately evaluated.

Results

The present scheme for single nucleotide mutations is equivalent to the general time-reversible model, but multiple nucleotide changes in infinitesimal time are allowed. Selective constraints on the respective types of amino acid replacements are tailored to each gene in a linear function of a given estimate of selective constraints. Their good estimates are those calculated by maximizing the respective likelihoods of empirical amino acid or codon substitution frequency matrices. Akaike and Bayesian information criteria indicate that the present model performs far better than the other substitution models for all five phylogenetic trees of highly-divergent to highly-homologous sequences of chloroplast, mitochondrial, and nuclear genes. It is also shown that multiple nucleotide changes in infinitesimal time are significant in long branches, although they may be caused by compensatory substitutions or other mechanisms. The variation of selective constraint over sites fits the datasets significantly better than variable mutation rates, except for 10 slow-evolving nuclear genes of 10 mammals. An critical finding for phylogenetic analysis is that assuming variable mutation rates over sites lead to the overestimation of branch lengths.


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