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An accurate understanding of the evolutionary history of rapidly-evolving viruses like SARS-CoV-2, responsible for the COVID-19 pandemic, is crucial to tracking and preventing the spread of emerging pathogens. However, viruses undergo frequent recombination, which makes it difficult to trace their evolutionary history using traditional phylogenetic methods. In this study, we present a phylogenetic workflow, virDTL, for analyzing viral evolution in the presence of recombination. Our approach leverages reconciliation methods developed for inferring horizontal gene transfer in prokaryotes and, compared to existing tools, is uniquely able to identify ancestral recombinations while accounting for several sources of inference uncertainty, including in the construction of a strain tree, estimation and rooting of gene family trees, and reconciliation itself. We apply this workflow to the Sarbecovirus subgenus and demonstrate how a principled analysis of predicted recombination gives insight into the evolution of SARS-CoV-2. In addition to providing confirming evidence for the horseshoe bat as its zoonotic origin, we identify several ancestral recombination events that merit further study. [ABSTRACT FROM AUTHOR]

Almost all standard phylogenetic methods for reconstructing gene trees result in unrooted trees; yet, many of the most useful applications of gene trees require that the gene trees be correctly rooted. As a result, several computational methods have been developed for inferring the root of unrooted gene trees. However, the accuracy of such methods has never been systematically evaluated on prokaryotic gene families, where horizontal gene transfer is often one of the dominant evolutionary events driving gene family evolution. In this work, we address this gap by conducting a thorough comparative evaluation of five different rooting methods using large collections of both simulated and empirical prokaryotic gene trees. Our simulation study is based on 6000 true and reconstructed gene trees on 100 species and characterizes the rooting accuracy of the four methods under 36 different evolutionary conditions and 3 levels of gene tree reconstruction error. The empirical study is based on a large, carefully designed data set of 3098 gene trees from 504 bacterial species (406 Alphaproteobacteria and 98 Cyanobacteria) and reveals insights that supplement those gleaned from the simulation study. Overall, this work provides several valuable insights into the accuracy of the considered methods that will help inform the choice of rooting methods to use when studying microbial gene family evolution. Among other findings, this study identifies parsimonious Duplication-Transfer-Loss (DTL) rooting and Minimal Ancestor Deviation (MAD) rooting as two of the most accurate gene tree rooting methods for prokaryotes and specifies the evolutionary conditions under which these methods are most accurate, demonstrates that DTL rooting is highly sensitive to high evolutionary rates and gene tree error, and that rooting methods based on branch-lengths are generally robust to gene tree reconstruction error. [ABSTRACT FROM AUTHOR]

Motivation A reconciliation is an annotation of the nodes of a gene tree with evolutionary events—for example, speciation, gene duplication, transfer, loss, etc.—along with a mapping onto a species tree. Many algorithms and software produce or use reconciliations but often using different reconciliation formats, regarding the type of events considered or whether the species tree is dated or not. This complicates the comparison and communication between different programs. Results Here, we gather a consortium of software developers in gene tree species tree reconciliation to propose and endorse a format that aims to promote an integrative—albeit flexible—specification of phylogenetic reconciliations. This format, named recPhyloXML, is accompanied by several tools such as a reconciled tree visualizer and conversion utilities. Availability and implementation http://phylariane.univ-lyon1.fr/recphyloxml/. [ABSTRACT FROM AUTHOR]

Motivation: Phylogenetic tree reconciliation is a widely used method for reconstructing the evolutionary histories of gene families and species, hosts and parasites and other dependent pairs of entities. Reconciliation is typically performed using maximum parsimony, in which each evolutionary event type is assigned a cost and the objective is to find a reconciliation of minimum total cost. It is generally understood that reconciliations are sensitive to event costs, but little is understood about the relationship between event costs and solutions. Moreover, choosing appropriate event costs is a notoriously difficult problem.Results: We address this problem by giving an efficient algorithm for computing Pareto-optimal sets of reconciliations, thus providing the first systematic method for understanding the relationship between event costs and reconciliations. This, in turn, results in new techniques for computing event support values and, for cophylogenetic analyses, performing robust statistical tests. We provide new software tools and demonstrate their use on a number of datasets from evolutionary genomic and cophylogenetic studies.Availability and implementation: Our Python tools are freely available at www.cs.hmc.edu/∼hadas/xscape.Contact: mukul@engr.uconn.eduSupplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM PUBLISHER]

The laboratory mouse shares the majority of its protein-coding genes with humans, making it the premier model organism in biomedical research, yet the two mammals differ in significant ways. To gain greater insights into both shared and species-specific transcriptional and cellular regulatory programs in the mouse, the Mouse ENCODE Consortium has mapped transcription, DNase I hypersensitivity, transcription factor binding, chromatin modifications and replication domains throughout the mouse genome in diverse cell and tissue types. By comparing with the human genome, we not only confirm substantial conservation in the newly annotated potential functional sequences, but also find a large degree of divergence of sequences involved in transcriptional regulation, chromatin state and higher order chromatin organization. Our results illuminate the wide range of evolutionary forces acting on genes and their regulatory regions, and provide a general resource for research into mammalian biology and mechanisms of human diseases. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Body packer syndrome" by V. M. Kulkarni, J. A. Gandhi, R. A. Gupta, R. B. Deokar, N. D. Karnik, and M. Y. Nadkar.

Somatic copy number alterations (sCNAs) are valuable phylogenetic markers for inferring evolutionary relationships among tumor cell subpopulations. Advances in single-cell DNA sequencing technologies are making it possible to obtain such sCNAs datasets at ever-larger scales. However, existing methods for reconstructing phylogenies from sCNAs are often too slow for large datasets. We propose two new distance-based methods, DICE-bar and DICE-star , for reconstructing single-cell tumor phylogenies from sCNA data. Using carefully simulated datasets, we find that DICE-bar matches or exceeds the accuracies of all other methods on noise-free datasets and that DICE-star shows exceptional robustness to noise and outperforms all other methods on noisy datasets. Both methods are also orders of magnitude faster than many existing methods. Our experimental analysis also reveals how noise/error in copy number inference, as expected for real datasets, can drastically impact the accuracies of most methods. We apply DICE-star, the most accurate method on error-prone datasets, to several real single-cell breast and ovarian cancer datasets and find that it rapidly produces phylogenies of equivalent or greater reliability compared with existing methods., (© 2024 Weiner and Bansal.)

Ayurveda is one of the oldest systems of traditional medicine that provides treatments for a wide range of acute and chronic health problems. It is a common myth amongst people that Ayurvedic drugs have no side effects, whereas the fact is that these drugs can cause adverse effects. Despite their wide use, the safety data of many Ayurvedic formulations are still unavailable. Tapyadi loha is an Ayurvedic formulation traditionally claimed for iron deficiency anemia in pregnant and non-pregnant patients. However, no scientific study has been conducted to evaluate its oral toxicity. Hence, the present study evaluated the acute and subacute oral toxicity of the Tapyadi loha according to the OECD test guidelines 425 and 407, respectively. Tapyadi loha did not cause mortality nor any signs of toxicity when given once orally at a dose of 2000 mg/kg. Subacute toxicity study showed no mortality as well as no behavioral, hematological, biochemical and histopathological abnormalities in rats treated with Tapyadi loha formulation at 250, 500 and 1000 mg/kg for 28 days. It is concluded that the Tapyadi loha is safe at a single dose of 2000 mg/kg and 28 days repeated dose of 1000 mg/kg by oral route in rats.

Background: Breast cancer is the most predominant and heterogeneous cancer in women. Moreover, breast cancer has a high prevalence to metastasize to distant organs, such as the brain, lungs, and bones. Patients with breast cancer metastasis to the bones have poor overall and relapse-free survival. Moreover, treatment using chemotherapy and immunotherapy is ineffective in preventing or reducing cancer metastasis., Recent Findings: Microorganisms residing in the gut and breast, termed as the resident microbiome, have a significant influence on the formation and progression of breast cancer. Recent studies have identified some microorganisms that induce breast cancer metastasis to the bone. These organisms utilize multiple mechanisms, including induction of epithelial-mesenchymal transition, steroid hormone metabolism, immune modification, bone remodeling, and secretion of microbial products that alter tumor microenvironment, and enhance propensity of breast cancer cells to metastasize. However, their involvement makes these microorganisms suitable as novel therapeutic targets. Thus, studies are underway to prevent and reduce breast cancer metastasis to distant organs, including the bone, using chemotherapeutic or immunotherapeutic drugs, along with probiotics, antibiotics or fecal microbiota transplantation., Conclusions: The present review describes association of gut and breast microbiomes with bone metastases. We have elaborated on the mechanisms utilized by breast and gut microbiomes that induce breast cancer metastasis, especially to the bone. The review also highlights the current treatment options that may target both the microbiomes for preventing or reducing breast cancer metastases. Finally, we have specified the necessity of maintaining a diverse gut microbiome to prevent dysbiosis, which otherwise may induce breast carcinogenesis and metastasis especially to the bone. The review may facilitate more detailed investigations of the causal associations between these microbiomes and bone metastases. Moreover, the potential treatment options described in the review may promote discussions and research on the modes to improve survival of patients with breast cancer by targeting the gut and breast microbiomes., (© 2024 The Author(s). Cancer Reports published by Wiley Periodicals LLC.)

Protein domains play an important role in the function and evolution of many gene families. Previous studies have shown that domains are frequently lost or gained during gene family evolution. Yet, most computational approaches for studying gene family evolution do not account for domain-level evolution within genes. To address this limitation, a new three-level reconciliation framework, called the Domain-Gene-Species (DGS) reconciliation model, has been recently developed to simultaneously model the evolution of a domain family inside one or more gene families and the evolution of those gene families inside a species tree. However, the existing model applies only to multi-cellular eukaryotes where horizontal gene transfer is negligible. In this work, we generalize the existing DGS reconciliation model by allowing for the spread of genes and domains across species boundaries through horizontal transfer. We show that the problem of computing optimal generalized DGS reconciliations, though NP-hard, is approximable to within a constant factor, where the specific approximation ratio depends on the "event costs" used. We provide two different approximation algorithms for the problem and demonstrate the impact of the generalized framework using both simulated and real biological data. Our results show that our new algorithms result in highly accurate reconstructions of domain family evolution for microbes.

Background: Breast cancer, the leading cancer type in women worldwide, is affected by reproductive and nonreproductive factors. Estrogen and progesterone influence the incidence and progression of breast cancer. The microbiome of the gut, a complex organ that plays a vital role in digestion and homeostasis, enhances availability of estrogen and progesterone in the host. Thus, an altered gut microbiome may influence the hormone-induced breast cancer incidence. This review describes the current understanding of the roles of gut microbiome in influencing the incidence and progression of breast cancer, with an emphasis on the microbiome-induced metabolism of estrogen and progesterone., Recent Findings: Microbiome has been recognized as a promising hallmark of cancer. Next-generation sequencing technologies have aided in rapid identification of components of the gut microbiome that are capable of metabolizing estrogen and progesterone. Moreover, studies have indicated a wider role of the gut microbiome in metabolizing chemotherapeutic and hormonal therapy agents and reducing their efficacy in patients with breast cancer, with a predominant effect in postmenopausal women., Conclusion: The gut microbiome and variations in its composition significantly alter the incidence and therapy outcomes of patients with breast cancer. Thus, a healthy and diverse microbiome is required for better response to anticancer therapies. Finally, the review emphasizes the requirement of studies to elucidate mechanisms that may aid in improving the gut microbiome composition, and hence, survival outcomes of patients with breast cancer., (© 2023 The Authors. Cancer Reports published by Wiley Periodicals LLC.)

Summary: CNAsim is a software package for improved simulation of single-cell copy number alteration (CNA) data from tumors. CNAsim can be used to efficiently generate single-cell copy number profiles for thousands of simulated tumor cells under a more realistic error model and a broader range of possible CNA mechanisms compared with existing simulators. The error model implemented in CNAsim accounts for the specific biases of single-cell sequencing that leads to read count fluctuation and poor resolution of CNA detection. For improved realism over existing simulators, CNAsim can (i) generate WGD, whole-chromosomal CNAs, and chromosome-arm CNAs, (ii) simulate subclonal population structure defined by the accumulation of chromosomal CNAs, and (iii) dilute the sampled cell population with both normal diploid cells and pseudo-diploid cells. The software can also generate DNA-seq data for sampled cells., Availability and Implementation: CNAsim is written in Python and is freely available open-source from https://github.com/samsonweiner/CNAsim., (© The Author(s) 2023. Published by Oxford University Press.)

A practice-changing, randomized, controlled clinical study established that preoperative hydroxyprogesterone administration improves disease-free and overall survival in patients with node-positive breast cancer. This research perspective summarizes evidences from our studies that preoperative hydroxyprogesterone administration may improve disease-free and overall survival in patients with node-positive breast cancer by modulating cellular stress response and negative regulation of inflammation. Non-coding RNAs, particularly DSCAM-AS1 , play a regulatory role in this process, along with the upregulation of the kinase gene SGK1 and activation of the SGK1/AP-1/NDRG1 axis. Progesterone-induced modification of the progesterone receptor and estrogen receptor genomic binding pattern is also involved in orchestrating estrogen signaling in breast cancer, preventing cell migration and invasion, and improving patient outcomes. We also highlight the role of progesterone in endocrine therapy resistance, which could lead to novel treatment options for patients with hormone receptor-positive breast cancer and for those who develop resistance to traditional endocrine therapies.

Diabetes mellitus is the most widely recognized endocrine disorder which is influencing a bigger populace on the planet. There are various causes of diabetes, such as physical inactivity, obesity, family history, race, and age. Diabetes mellitus is associated with some life-threatening complications, such as neuropathy, nephropathy, various eye diseases or retinopathy, and cardiovascular disorders. Many synthetic antihyperglycemic agents are available in the market for the treatment of diabetes and its complications. But, due to some serious side effects of these synthetic agents, people are opting for herbal remedies and, therefore, they are now becoming popular. Herbal remedies have lesser side effects and higher affordability and therefore can be preferably used over synthetic agents for a long-term disorder like diabetes mellitus. In the present study, scientific research and review studies on the topic were collected from Science Direct, Scopus, PubMed, Google Scholar, and other relevant sources. The references of all the articles were screened manually for any additional information on popular polyherbal formulations in traditional Ayurvedic, Chinese, and Unani medicinal systems. It is found that these polyherbal formulations are studied for anti-diabetic potential. Furthermore, some are also investigated for mechanism of action of anti-diabetic effects. This review highlights various Ayurvedic, Chinese, and Unani polyherbal formulations commonly utilized in the management of diabetes mellitus along with their pre-clinical and clinical investigations, which will enhance the existing knowledge of the researchers., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Murudkar, Tambe, Chandrasekar, Boddeda and Pawar.)

Phylogenetic reconciliation has emerged as a principled, highly effective technique for investigating the origin, spread, and evolutionary history of microbial gene families. Proper application of phylogenetic reconciliation requires a clear understanding of potential pitfalls and sources of error, and knowledge of the most effective reconciliation-based tools and protocols to use to maximize accuracy. In this book chapter, we provide a brief overview of Duplication-Transfer-Loss (DTL) reconciliation, the standard reconciliation model used to study microbial gene families and provide a step-by-step computational protocol to maximize the accuracy of DTL reconciliation and minimize false-positive evolutionary inferences., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

The inference of disease transmission networks is an important problem in epidemiology. One popular approach for building transmission networks is to reconstruct a phylogenetic tree using sequences from disease strains sampled from infected hosts and infer transmissions based on this tree. However, most existing phylogenetic approaches for transmission network inference are highly computationally intensive and cannot take within-host strain diversity into account. Here, we introduce a new phylogenetic approach for inferring transmission networks, TNet, that addresses these limitations. TNet uses multiple strain sequences from each sampled host to infer transmissions and is simpler and more accurate than existing approaches. Furthermore, TNet is highly scalable and able to distinguish between ambiguous and unambiguous transmission inferences. We evaluated TNet on a large collection of 560 simulated transmission networks of various sizes and diverse host, sequence, and transmission characteristics, as well as on 10 real transmission datasets with known transmission histories. Our results show that TNet outperforms two other recently developed methods, phyloscanner and SharpTNI, that also consider within-host strain diversity. We also applied TNet to a large collection of SARS-CoV-2 genomes sampled from infected individuals in many countries around the world, demonstrating how our inference framework can be adapted to accurately infer geographical transmission networks. TNet is freely available from https://compbio.engr.uconn.edu/software/TNet/.

Horizontal gene transfer (HGT) is central to prokaryotic evolution. However, little is known about the "scale" of individual HGT events. In this work, we introduce the first computational framework to help answer the following fundamental question: How often does more than one gene get horizontally transferred in a single HGT event? Our method, called HoMer, uses phylogenetic reconciliation to infer single-gene HGT events across a given set of species/strains, employs several techniques to account for inference error and uncertainty, combines that information with gene order information from extant genomes, and uses statistical analysis to identify candidate horizontal multigene transfers (HMGTs) in both extant and ancestral species/strains. HoMer is highly scalable and can be easily used to infer HMGTs across hundreds of genomes. We apply HoMer to a genome-scale data set of over 22,000 gene families from 103 Aeromonas genomes and identify a large number of plausible HMGTs of various scales at both small and large phylogenetic distances. Analysis of these HMGTs reveals interesting relationships between gene function, phylogenetic distance, and frequency of multigene transfer. Among other insights, we find that 1) the observed relative frequency of HMGT increases as divergence between genomes increases, 2) HMGTs often have conserved gene functions, and 3) rare genes are frequently acquired through HMGT. We also analyze in detail HMGTs involving the zonula occludens toxin and type III secretion systems. By enabling the systematic inference of HMGTs on a large scale, HoMer will facilitate a more accurate and more complete understanding of HGT and microbial evolution., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Many existing methods for estimation of infectious disease transmission networks use a phylogeny of the infecting strains as the basis for transmission network inference, and accurate network inference relies on accuracy of this underlying evolutionary history. However, phylogenetic reconstruction can be highly error prone and more sophisticated methods can fail to scale to larger outbreaks, negatively impacting downstream transmission network inference.We introduce a new method, TreeFix-TP, for accurate and scalable reconstruction of transmission phylogenies based on an error-correction framework. Our method uses intra-host strain diversity and host information to balance a parsimonious evaluation of the implied transmission network with statistical hypothesis testing on sequence data likelihood. The reconstructed tree minimizes the number of required disease transmissions while being as well supported by sequence data as the maximum likelihood phylogeny. Using a simulation framework for viral transmission and evolution and real data from ten HCV outbreaks, we demonstrate that error-correction with TreeFix-TP improves phylogenetic accuracy and outbreak source detection. Our results show that using TreeFix-TP can lead to significant improvement in transmission phylogeny inference and that its performance is robust to variations in transmission and evolutionary parameters. TreeFix-TP is freely available open-source from https://compbio.engr.uconn.edu/software/treefix-tp/.

Background: We consider two fundamental computational problems that arise when comparing phylogenetic trees, rooted or unrooted, with non-identical leaf sets. The first problem arises when comparing two trees where the leaf set of one tree is a proper subset of the other. The second problem arises when the two trees to be compared have only partially overlapping leaf sets. The traditional approach to handling these problems is to first restrict the two trees to their common leaf set. An alternative approach that has shown promise is to first complete the trees by adding missing leaves, so that the resulting trees have identical leaf sets. This requires the computation of an optimal completion that minimizes the distance between the two resulting trees over all possible completions., Results: We provide optimal linear-time algorithms for both completion problems under the widely-used Robinson-Foulds (RF) distance measure. Our algorithm for the first problem improves the time complexity of the current fastest algorithm from quadratic (in the size of the two trees) to linear. No algorithms have yet been proposed for the more general second problem where both trees have missing leaves. We advance the study of this general problem by proposing a useful restricted version of the general problem and providing optimal linear-time algorithms for the restricted version. Our experimental results on biological data sets suggest that completion-based RF distances can be very different compared to traditional RF distances., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s) 2020.)

Summary: SaGePhy is a software package for improved phylogenetic simulation of gene and subgene evolution. SaGePhy can be used to generate species trees, gene trees and subgene or (protein) domain trees using a probabilistic birth-death process that allows for gene and subgene duplication, horizontal gene and subgene transfer and gene and subgene loss. SaGePhy implements a range of important features not found in other phylogenetic simulation frameworks/software. These include (i) simulation of subgene or domain level evolution inside one or more gene trees, (ii) simultaneous simulation of both additive and replacing horizontal gene/subgene transfers and (iii) probabilistic sampling of species tree and gene tree nodes, respectively, for gene- and domain-family birth. SaGePhy is open-source, platform independent and written in Java and Python., Availability and Implementation: Executables, source code (open-source under the revised BSD license) and a detailed manual are freely available from http://compbio.engr.uconn.edu/software/sagephy/., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Duplication-Transfer-Loss (DTL) reconciliation is a powerful method for studying gene family evolution in the presence of horizontal gene transfer. DTL reconciliation seeks to reconcile gene trees with species trees by postulating speciation, duplication, transfer, and loss events. Efficient algorithms exist for finding optimal DTL reconciliations when the gene tree is binary. In practice, however, gene trees are often non-binary due to uncertainty in the gene tree topologies, and DTL reconciliation with non-binary gene trees is known to be NP-hard. In this paper, we present the first exact algorithms for DTL reconciliation with non-binary gene trees. Specifically, we (i) show that the DTL reconciliation problem for non-binary gene trees is fixed-parameter tractable in the maximum degree of the gene tree, (ii) present an exponential-time, but in-practice efficient, algorithm to track and enumerate all optimal binary resolutions of a non-binary input gene tree, and (iii) apply our algorithms to a large empirical data set of over 4,700 gene trees from 100 species to study the impact of gene tree uncertainty on DTL-reconciliation and to demonstrate the applicability and utility of our algorithms. The new techniques and algorithms introduced in this paper will help biologists avoid incorrect evolutionary inferences caused by gene tree uncertainty.

Competing Interests: There are no conflicts of interest.

The objective of the study was to evaluate and compare the relative efficacy of treating linear non-comminuted mandibular fracture of symphysis and parasymphysis region using single 2.0-mm AO locking reconstruction plate or using two conventional miniplates. In this study, 80 patients of symphysis or parasymphysis fracture were divided randomly in two equal groups and treated with open reduction and internal fixation using two 2.5-mm miniplates or with a single 2.0-mm AO locking reconstruction plate. Operating time in case of open reduction and fixation using a single 2.0-mm locking reconstruction plate was significantly less when compared to open reduction and fixation using two conventional miniplates. Both groups showed satisfactory fracture reduction and healing. No postoperative malocclusion was noted, and both groups showed comparable improvement in masticatory efficiency. In conclusion, fracture fixation using a single 2.0-mm AO locking reconstruction plate without use of a second plate at the superior border for treatment of linear non comminuted mandibular fracture in symphysis and parasymphysis region gives comparable results as with treatment by conventional miniplate system and provides significant savings in operating time, ease of use and decrease in amount of hardware incorporated in the body., (Copyright © 2018 Elsevier Masson SAS. All rights reserved.)

The majority of genes in eukaryotes consists of one or more protein domains that can be independently lost or gained during evolution. This gain and loss of protein domains, through domain duplications, transfers, or losses, has important evolutionary and functional consequences. Yet, even though it is well understood that domains evolve inside genes and genes inside species, there do not exist any computational frameworks to simultaneously model the evolution of domains, genes, and species and account for their inter-dependency. Here, we develop an integrated model of domain evolution that explicitly captures the interdependence of domain-, gene-, and species-level evolution. Our model extends the classical phylogenetic reconciliation framework, which infers gene family evolution by comparing gene trees and species trees, by explicitly considering domain-level evolution and decoupling domain-level events from gene-level events. In this paper, we (i) introduce the new integrated reconciliation framework, (ii) prove that the associated optimization problem is NP-hard, (iii) devise an efficient heuristic solution for the problem, (iv) apply our algorithm to a large biological dataset, and (v) demonstrate the impact of using our new computational framework compared to existing approaches. The implemented software is freely available from http://compbio.engr.uconn.edu/software/seadog/.

Summary: RANGER-DTL 2.0 is a software program for inferring gene family evolution using Duplication-Transfer-Loss reconciliation. This new software is highly scalable and easy to use, and offers many new features not currently available in any other reconciliation program. RANGER-DTL 2.0 has a particular focus on reconciliation accuracy and can account for many sources of reconciliation uncertainty including uncertain gene tree rooting, gene tree topological uncertainty, multiple optimal reconciliations and alternative event cost assignments. RANGER-DTL 2.0 is open-source and written in C++ and Python., Availability and Implementation: Pre-compiled executables, source code (open-source under GNU GPL) and a detailed manual are freely available from http://compbio.engr.uconn.edu/software/RANGER-DTL/., Supplementary Information: Supplementary data are available at Bioinformatics online.

Background: Duplication-Transfer-Loss (DTL) reconciliation is a powerful and increasingly popular technique for studying the evolution of microbial gene families. DTL reconciliation requires the use of rooted gene trees to perform the reconciliation with the species tree, and the standard technique for rooting gene trees is to assign a root that results in the minimum reconciliation cost across all rootings of that gene tree. However, even though it is well understood that many gene trees have multiple optimal roots, only a single optimal root is randomly chosen to create the rooted gene tree and perform the reconciliation. This remains an important overlooked and unaddressed problem in DTL reconciliation, leading to incorrect evolutionary inferences. In this work, we perform an in-depth analysis of the impact of uncertain gene tree rooting on the computed DTL reconciliation and provide the first computational tools to quantify and negate the impact of gene tree rooting uncertainty on DTL reconciliation., Results: Our analysis of a large data set of over 4500 gene families from 100 species shows that a large fraction of gene trees have multiple optimal rootings, that these multiple roots often, but not always, appear closely clustered together in the same region of the gene tree, that many aspects of the reconciliation remain conserved across the multiple rootings, that gene tree error has a profound impact on the prevalence and structure of multiple optimal rootings, and that there are specific interesting patterns in the reconciliation of those gene trees that have multiple optimal roots., Conclusions: Our results show that unrooted gene trees can be meaningfully reconciled and high-quality evolutionary information can be obtained from them even after accounting for multiple optimal rootings. In addition, the techniques and tools introduced in this paper make it possible to systematically avoid incorrect evolutionary inferences caused by incorrect or uncertain gene tree rooting. These tools have been implemented in the phylogenetic reconciliation software package RANGER-DTL 2.0, freely available from http://compbio.engr.uconn.edu/software/RANGER-DTL/ .

Unusual metallic states involving breakdown of the standard Fermi-liquid picture of long-lived quasiparticles in well-defined band states emerge at low temperatures near correlation-driven Mott transitions. Prominent examples are ill-understood metallic states in d- and f-band compounds near Mott-like transitions. Finding of superconductivity in solid O 2 on the border of an insulator-metal transition at high pressures close to 96 GPa is thus truly remarkable. Neither the insulator-metal transition nor superconductivity are understood satisfactorily. Here, we undertake a first step in this direction by focussing on the pressure-driven insulator-metal transition using a combination of first-principles density-functional and many-body calculations. We report a striking result: the finding of an orbital-selective Mott transition in a pure p-band elemental system. We apply our theory to understand extant structural and transport data across the transition, and make a specific two-fluid prediction that is open to future test. Based thereupon, we propose a novel scenario where soft multiband modes built from microscopically coexisting itinerant and localized electronic states are natural candidates for the pairing glue in pressurized O 2 .

Duplication-Transfer-Loss (DTL) reconciliation has emerged as a powerful technique for studying gene family evolution in the presence of horizontal gene transfer. DTL reconciliation takes as input a gene family phylogeny and the corresponding species phylogeny, and reconciles the two by postulating speciation, gene duplication, horizontal gene transfer, and gene loss events. Efficient algorithms exist for finding optimal DTL reconciliations when the gene tree is binary. However, gene trees are frequently non-binary. With such non-binary gene trees, the reconciliation problem seeks to find a binary resolution of the gene tree that minimizes the reconciliation cost. Given the prevalence of non-binary gene trees, many efficient algorithms have been developed for this problem in the context of the simpler Duplication-Loss (DL) reconciliation model. Yet, no efficient algorithms exist for DTL reconciliation with non-binary gene trees and the complexity of the problem remains unknown. In this work, we resolve this open question by showing that the problem is, in fact, NP-hard. Our reduction applies to both the dated and undated formulations of DTL reconciliation. By resolving this long-standing open problem, this work will spur the development of both exact and heuristic algorithms for this important problem.

Accurate gene tree-species tree reconciliation is fundamental to inferring the evolutionary history of a gene family. However, although it has long been appreciated that population-related effects such as incomplete lineage sorting (ILS) can dramatically affect the gene tree, many of the most popular reconciliation methods consider discordance only due to gene duplication and loss (and sometimes horizontal gene transfer). Methods that do model ILS are either highly parameterized or consider a restricted set of histories, thus limiting their applicability and accuracy. To address these challenges, we present a novel algorithm DLCpar for inferring a most parsimonious (MP) history of a gene family in the presence of duplications, losses, and ILS. Our algorithm relies on a new reconciliation structure, the labeled coalescent tree (LCT), that simultaneously describes coalescent and duplication-loss history. We show that the LCT representation enables an exhaustive and efficient search over the space of reconciliations, and, for most gene families, the least common ancestor (LCA) mapping is an optimal solution for the species mapping between the gene tree and species tree in an MP LCT. Applying our algorithm to a variety of clades, including flies, fungi, and primates, as well as to simulated phylogenies, we achieve high accuracy, comparable to sophisticated probabilistic reconciliation methods, at reduced run time and with far fewer parameters. These properties enable inferences of the complex evolution of gene families across a broad range of species and large data sets.

Phylogenetic tree reconciliation is a powerful approach for inferring evolutionary events like gene duplication, horizontal gene transfer, and gene loss, which are fundamental to our understanding of molecular evolution. While duplication-loss (DL) reconciliation leads to a unique maximum-parsimony solution, duplication-transfer-loss (DTL) reconciliation yields a multitude of optimal solutions, making it difficult to infer the true evolutionary history of the gene family. This problem is further exacerbated by the fact that different event cost assignments yield different sets of optimal reconciliations. Here, we present an effective, efficient, and scalable method for dealing with these fundamental problems in DTL reconciliation. Our approach works by sampling the space of optimal reconciliations uniformly at random and aggregating the results. We show that even gene trees with only a few dozen genes often have millions of optimal reconciliations and present an algorithm to efficiently sample the space of optimal reconciliations uniformly at random in O(mn(2)) time per sample, where m and n denote the number of genes and species, respectively. We use these samples to understand how different optimal reconciliations vary in their node mappings and event assignments and to investigate the impact of varying event costs. We apply our method to a biological dataset of approximately 4700 gene trees from 100 taxa and observe that 93% of event assignments and 73% of mappings remain consistent across different multiple optima. Our analysis represents the first systematic investigation of the space of optimal DTL reconciliations and has many important implications for the study of gene family evolution.

The use of genomic data sets for phylogenetics is complicated by the fact that evolutionary processes such as gene duplication and loss, or incomplete lineage sorting (deep coalescence) cause incongruence among gene trees. One well-known approach that deals with this complication is gene tree parsimony, which, given a collection of gene trees, seeks a species tree that requires the smallest number of evolutionary events to explain the incongruence of the gene trees. However, a lack of efficient algorithms has limited the use of this approach. Here, we present efficient algorithms for SPR and TBR-based local search heuristics for gene tree parsimony under the 1) duplication, 2) loss, 3) duplication-loss, and 4) deep coalescence reconciliation costs. These novel algorithms improve upon the time complexities of previous algorithms for these problems by a factor of n, where n is the number of species in the collection of gene trees. Our algorithms provide a substantial improvement in runtime and scalability compared to previous implementations and enable large-scale gene tree parsimony analyses using any of the four reconciliation costs. Our algorithms have been implemented in the software packages DupTree and iGTP, and have already been used to perform several compelling phylogenetic studies.

Motivation: Horizontal gene transfer (HGT) plays a crucial role in the evolution of prokaryotic species. Typically, no more than a few genes are horizontally transferred between any two species. However, several studies identified pairs of species (or linages) between which many different genes were horizontally transferred. Such a pair is said to be linked by a highway of gene sharing. Inferring such highways is crucial to understanding the evolution of prokaryotes and for inferring past symbiotic and ecological associations among different species., Results: We present a new improved method for systematically detecting highways of gene sharing. As we demonstrate using a variety of simulated datasets, our method is highly accurate and efficient, and robust to noise and high rates of HGT. We further validate our method by applying it to a published dataset of >22 000 gene trees from 144 prokaryotic species. Our method makes it practical, for the first time, to perform accurate highway analysis quickly and easily even on large datasets with high rates of HGT., Availability and Implementation: An implementation of the method can be freely downloaded from: http://acgt.cs.tau.ac.il/hide.

Motivation: Gene family evolution is driven by evolutionary events such as speciation, gene duplication, horizontal gene transfer and gene loss, and inferring these events in the evolutionary history of a given gene family is a fundamental problem in comparative and evolutionary genomics with numerous important applications. Solving this problem requires the use of a reconciliation framework, where the input consists of a gene family phylogeny and the corresponding species phylogeny, and the goal is to reconcile the two by postulating speciation, gene duplication, horizontal gene transfer and gene loss events. This reconciliation problem is referred to as duplication-transfer-loss (DTL) reconciliation and has been extensively studied in the literature. Yet, even the fastest existing algorithms for DTL reconciliation are too slow for reconciling large gene families and for use in more sophisticated applications such as gene tree or species tree reconstruction., Results: We present two new algorithms for the DTL reconciliation problem that are dramatically faster than existing algorithms, both asymptotically and in practice. We also extend the standard DTL reconciliation model by considering distance-dependent transfer costs, which allow for more accurate reconciliation and give an efficient algorithm for DTL reconciliation under this extended model. We implemented our new algorithms and demonstrated up to 100 000-fold speed-up over existing methods, using both simulated and biological datasets. This dramatic improvement makes it possible to use DTL reconciliation for performing rigorous evolutionary analyses of large gene families and enables its use in advanced reconciliation-based gene and species tree reconstruction methods., Availability: Our programs can be freely downloaded from http://compbio.mit.edu/ranger-dtl/.

Phylogenetic analyses using genome-scale data sets must confront incongruence among gene trees, which in plants is exacerbated by frequent gene duplications and losses. Gene tree parsimony (GTP) is a phylogenetic optimization criterion in which a species tree that minimizes the number of gene duplications induced among a set of gene trees is selected. The run time performance of previous implementations has limited its use on large-scale data sets. We used new software that incorporates recent algorithmic advances to examine the performance of GTP on a plant data set consisting of 18,896 gene trees containing 510,922 protein sequences from 136 plant taxa (giving a combined alignment length of >2.9 million characters). The relationships inferred from the GTP analysis were largely consistent with previous large-scale studies of backbone plant phylogeny and resolved some controversial nodes. The placement of taxa that were present in few gene trees generally varied the most among GTP bootstrap replicates. Excluding these taxa either before or after the GTP analysis revealed high levels of phylogenetic support across plants. The analyses supported magnoliids sister to a eudicot + monocot clade and did not support the eurosid I and II clades. This study presents a nuclear genomic perspective on the broad-scale phylogenic relationships among plants, and it demonstrates that nuclear genes with a history of duplication and loss can be phylogenetically informative for resolving the plant tree of life.

The gene-duplication problem is to infer a species supertree from gene trees that are confounded by complex histories of gene duplications. This problem is NP-hard and thus requires efficient and effective heuristics. Existing heuristics perform a stepwise search of the tree space, where each step is guided by an exact solution to an instance of a local search problem. We improve on the time complexity of the local search problem by a factor of n2= log n, where n is the size of the resulting species supertree. Typically, several thousand instances of the local search problem are solved throughout a stepwise heuristic search. Hence, our improvement makes the gene-duplication problem much more tractable for large-scale phylogenetic analyses.

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Plasminogen activators (PAs; e.g., tissue-type, tPA) coupled to red blood cells (RBCs) display in vivo features useful for thromboprophylaxis: prolonged circulation, minimal extravasation, and preferential lysis of nascent versus preexisting clots. Yet, factors controlling the activity of RBC-bound PAs in vivo are not defined and may not mirror the profile of soluble PAs. We tested the role of RBC/PA binding to fibrin in fibrinolysis. RBC/tPA and RBC/tPA variant with low fibrin affinity (rPA) bound to and lysed plasminogen-containing fibrin clots in vitro comparably. In contrast, when coinjected in mice with fibrin emboli lodging in pulmonary vasculature, only RBC/tPA accumulated in lungs, which resulted in a more extensive fibrinolysis versus RBC/rPA (p < 0.01). Reconciling this apparent divergence between in vitro and in vivo behaviors, RBC/tPA, but not RBC/rPA perfused over fibrin in vitro at physiological shear stress bound to fibrin clots and caused greater fibrinolysis versus RBC/rPA (p < 0.001). These results indicate that because of high fibrin affinity, RBC/tPA binding to clots endures hemodynamic stress, which enhances fibrinolysis. Behavior of RBC/PAs under hemodynamic pressure is an important predictor of their performance in vivo.

Human neutrophil proteases cathepsin G and elastase can directly alter platelet function and/or participate in coagulation cascade reactions on the platelet or neutrophil surface to enhance fibrin formation. The clotting of recalcified platelet-free plasma (PFP) or platelet-rich plasma (PRP) supplemented with corn trypsin inhibitor (to shut down contact activation) was studied in well-plates or flow assays. Inhibitors of cathepsin G or elastase significantly delayed the burst time (t(50)) of thrombin generation in neutrophil-supplemented PRP from 49 min to 59 and 77 min, respectively, in well-plate assays as well as reduced neutrophil-promoted fibrin deposition on fibrinogen-adherent platelets under flow conditions. In flow assays, purified cathepsin G was a far more potent activator of platelet-dependent coagulation than elastase. Anti-tissue factor had no effect on neutrophil protease-enhanced thrombin formation in PRP. The addition of cathepsin G (425 nm) or convulxin (10 nm) to PRP dramatically reduced the t(50) of thrombin generation from 53 min to 17 or 23 min, respectively. In contrast, the addition of elastase to PRP left the t(50) unaltered. Whereas perfusion of PFP (gamma(w) = 62.5 s(-1)) over fibrinogen-adherent platelets did not result in fibrin formation until 50 min, massive fibrin could be observed on cathepsin G-treated platelets even at 35 min. Cathepsin G addition to corn trypsin inhibitor-treated PFP produced little thrombin unless anionic phospholipid was present. However, further activation inhibition studies indicated that cathepsin G enhances fibrin deposition under flow conditions by elevating the activation state of fibrinogen-adherent platelets rather than by cleaving coagulation factors.

Deep vein thrombosis (DVT) is a low flow pathology often prevented by vascular compression to increase blood movement. We report new heterotypic adhesive interactions of normal erythrocytes operative at low wall shear rates (gamma(w)) below 100 s(-1). Adhesion at gamma(w) = 50 s(-1) of washed red blood cells (RBCs) to fibrinogen-adherent platelets was 4-fold less (P <.005) than to collagen-adherent platelets (279 +/- 105 RBC/mm(2)). This glycoprotein VI (GPVI)-triggered adhesion was antagonized (> 80% reduction) by soluble fibrinogen (3 mg/mL) and ethylenediaminetetraacetic acid (EDTA). RBC-platelet adhesion was reduced in half by antibodies against CD36 or GPIb, but not by antibodies against GPIIb/IIIa, von Willebrand factor (VWF), thrombospondin (TSP), P-selectin, beta(1), alpha(v), or CD47. Adhesion of washed RBCs to fibrinogen-adherent neutrophils was increased 6-fold in the presence of 20 microM N-formyl-Met-Leu-Phe to a level of 67 RBCs per 100 neutrophils after 5 minutes at 50 s(-1). RBC-neutrophil adhesion was diminished by anti-CD11b (76%), anti-RBC Landsteiner-Wiener (LW) (ICAM4; 40%), or by EDTA (> 80%), but not by soluble fibrinogen or antibodies against CD11a, CD11c, CD36, TSP, beta(1), alpha(v), or CD47. RBC adhesion to activated platelets and activated neutrophils was prevented by wall shear stress above 1 dyne/cm(2) (at 100 s(-1)). Whereas washed RBCs did not adhere to fibrin formed from purified fibrinogen, adhesion was marked when pure fibrin was precoated with TSP or when RBCs were perfused over fibrin formed from recalcified plasma. Endothelial activation and unusually low flow may be a setting prone to receptor-mediated RBC adhesion to adherent neutrophils (or platelets/fibrin), all of which may contribute to DVT.