Magnetic resonance imaging findings of high myopic strabismus with sagging eye-like symptoms, heavy eye syndrome, and non-highly myopic eyes with sagging eye syndrome.

INTRODUCTION: Progressive esotropia accompanied by restricted abduction and supraduction due to high myopia is known as esotropia fixus with high myopia or heavy eye syndrome (HES). Some conditions, such as sagging eye syndrome (SES), show esotropia for distance or cyclovertical strabismus with no abduction limitations despite highly myopic eyes. We evaluated the magnetic resonance imaging (MRI) findings and clinical features of HES, high myopia with SES-like symptoms (highly myopic SES), and SES. METHODS: We reviewed all patients diagnosed with HES, highly myopic SES, and SES who underwent MRI of the orbits and brain over 6 years. To quantitatively assess the orbital anatomy, we compared the conditions of the superior rectus muscle (SR), lateral rectus muscle (LR), and inferior rectus muscle (IR) using orbital MRI among the three groups. RESULTS: Among the 14 patients (27 eyes) with high myopia, 5 (9 eyes) had HES, and 9 (18 eyes) had highly myopic SES. Eleven patients (22 eyes) with SES were also compared with these 14 patients. The mean axial length was 29.6 ± 1.0 mm in participants with HES, 29.0 ± 1.5 mm in those with HES-SES, and 23.7 ± 0.9 mm in those with SES. The average distance esotropia was 48.0 ± 19.9Δprism, 4.6 ± 1.5Δprism, and 6.1 ± 4.6Δprism for participants with HES, highly myopic SES and SES, respectively. The average distance hypertropia was 5.3 ± 5.9Δprism in participants with highly myopic SES and 4.8 ± 2.7Δprism in those with SES. The mean vertical angle of the LR was 32.6 ± 10.8°, 18.1 ± 5.4°, and 14.6 ± 6.8°; the mean tilting angle of the LR was 31.6 ± 9.2°, 15.9 ± 6.0°, and 13.8 ± 5.9°; and the mean displacement angle between the LR and SR was 152.3 ± 16.7°, 125.0 ± 7.1°, and 112.5 ± 7.5° for participants with HES, highly myopic SES and SES, respectively. The LR-SR displacement angle in HES-SES was significantly larger than in SES (p < .001) but the vertical and tilting angles were not. Also, the IR shift showed no significant difference with HES-SES and HES (5.8 ± 1.4 mm and 5.3 ± 1.2 mm) but not with SES (4.0 ± 0.8 mm) (p < .0001). DISCUSSION: SES-like symptoms can develop in highly myopic eyes; however, MRI showed that the state of the LR muscle in highly myopic SES deviated almost similarly to that in SES; however, the eyeball was more dislocated than in SES. This may be useful in deciding the appropriate operative procedure.

Skeleton phylogeny reconstructed with transcriptomes for the tribe Drosophilini (Diptera: Drosophilidae).

The family Drosophilidae is one of the most important model systems in evolutionary biology. Thanks to advances in high-throughput sequencing technology, a number of molecular phylogenetic analyses have been undertaken by using large data sets of many genes and many species sampled across this family. Especially, recent analyses using genome sequences have depicted the family-wide skeleton phylogeny with high confidence. However, the taxon sampling is still insufficient for minor lineages and non-Drosophila genera. In this study, we carried out phylogenetic analyses using a large number of transcriptome-based nucleotide sequences, focusing on the largest, core tribe Drosophilini in the Drosophilidae. In our analyses, some noise factors against phylogenetic reconstruction were taken into account by removing putative paralogy from the datasets and examining the effects of missing data, i.e. gene occupancy and site coverage, and incomplete lineage sorting. The inferred phylogeny has newly resolved the following phylogenetic positions/relationships at the genomic scale: (i) the monophyly of the subgenus Siphlodora including Zaprionus flavofasciatus to be transferred therein; (ii) the paraphyly of the robusta and melanica species groups within a clade comprised of the robusta, melanica and quadrisetata groups and Z. flavofasciatus; (iii) Drosophila curviceps (representing the curviceps group), D. annulipes (the quadrilineata subgroup of the immigrans group) and D. maculinotata clustered into a clade sister to the Idiomyia + Scaptomyza clade, forming together the expanded Hawaiian drosophilid lineage; (iv) Dichaetophora tenuicauda (representing the lineage comprised of the Zygothrica genus group and Dichaetophora) placed as the sister to the clade of the expanded Hawaiian drosophilid lineage and Siphlodora; and (v) relationships of the subgenus Drosophila and the genus Zaprionus as follows: (Zaprionus, (the quadrilineata subgroup, ((D. sternopleuralis, the immigrans group proper), (the quinaria radiation, the tripunctata radiation)))). These results are to be incorporated into the so-far published phylogenomic tree as a backbone (constraint) tree for grafting much more species based on sequences of a limited number of genes. Such a comprehensive, highly confident phylogenetic tree with extensive and dense taxon sampling will provide an essential framework for comparative studies of the Drosophilidae.

Computational Reproducibility of Molecular Phylogenies.

Repeated runs of the same program can generate different molecular phylogenies from identical data sets under the same analytical conditions. This lack of reproducibility of inferred phylogenies casts a long shadow on downstream research employing these phylogenies in areas such as comparative genomics, systematics, and functional biology. We have assessed the relative accuracies and log-likelihoods of alternative phylogenies generated for computer-simulated and empirical data sets. Our findings indicate that these alternative phylogenies reconstruct evolutionary relationships with comparable accuracy. They also have similar log-likelihoods that are not inferior to the log-likelihoods of the true tree. We determined that the direct relationship between irreproducibility and inaccuracy is due to their common dependence on the amount of phylogenetic information in the data. While computational reproducibility can be enhanced through more extensive heuristic searches for the maximum likelihood tree, this does not lead to higher accuracy. We conclude that computational irreproducibility plays a minor role in molecular phylogenetics.

Shared evolutionary trajectories of three independent neo-sex chromosomes in Drosophila.

Dosage compensation (DC) on the X Chromosome counteracts the deleterious effects of gene loss on the Y Chromosome. However, DC is not efficient if the X Chromosome also degenerates. This indeed occurs in Drosophila miranda, in which both the neo-Y and the neo-X are under accelerated pseudogenization. To examine the generality of this pattern, we investigated the evolution of two additional neo-sex chromosomes that emerged independently in D. albomicans and D. americana and reanalyzed neo-sex chromosome evolution in D. miranda Comparative genomic and transcriptomic analyses revealed that the pseudogenization rate on the neo-X is also accelerated in D. albomicans and D. americana although to a lesser extent than in D. miranda In males, neo-X-linked genes whose neo-Y-linked homologs are pseudogenized tended to be up-regulated more than those whose neo-Y-linked homologs remain functional. Moreover, genes under strong functional constraint and genes highly expressed in the testis tended to remain functional on the neo-X and neo-Y, respectively. Focusing on the D. miranda and D. albomicans neo-sex chromosomes that emerged independently from the same autosome, we further found that the same genes tend to become pseudogenized in parallel on the neo-Y. These genes include Idgf6 and JhI-26, which may be unnecessary or even harmful in males. Our results indicate that neo-sex chromosomes in Drosophila share a common evolutionary trajectory after their emergence, which may prevent sex chromosomes from being an evolutionary dead end.

MEGA11: Molecular Evolutionary Genetics Analysis Version 11.

The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor, and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net.

PathFinder: Bayesian inference of clone migration histories in cancer.

SUMMARY: Metastases cause a vast majority of cancer morbidity and mortality. Metastatic clones are formed by dispersal of cancer cells to secondary tissues, and are not medically detected or visible until later stages of cancer development. Clone phylogenies within patients provide a means of tracing the otherwise inaccessible dynamic history of migrations of cancer cells. Here, we present a new Bayesian approach, PathFinder, for reconstructing the routes of cancer cell migrations. PathFinder uses the clone phylogeny, the number of mutational differences among clones, and the information on the presence and absence of observed clones in primary and metastatic tumors. By analyzing simulated datasets, we found that PathFinder performes well in reconstructing clone migrations from the primary tumor to new metastases as well as between metastases. It was more challenging to trace migrations from metastases back to primary tumors. We found that a vast majority of errors can be corrected by sampling more clones per tumor, and by increasing the number of genetic variants assayed per clone. We also identified situations in which phylogenetic approaches alone are not sufficient to reconstruct migration routes.In conclusion, we anticipate that the use of PathFinder will enable a more reliable inference of migration histories and their posterior probabilities, which is required to assess the relative preponderance of seeding of new metastasis by clones from primary tumors and/or existing metastases. AVAILABILITY AND IMPLEMENTATION: PathFinder is available on the web at https://github.com/SayakaMiura/PathFinder.

A new method for inferring timetrees from temporally sampled molecular sequences.

Pathogen timetrees are phylogenies scaled to time. They reveal the temporal history of a pathogen spread through the populations as captured in the evolutionary history of strains. These timetrees are inferred by using molecular sequences of pathogenic strains sampled at different times. That is, temporally sampled sequences enable the inference of sequence divergence times. Here, we present a new approach (RelTime with Dated Tips [RTDT]) to estimating pathogen timetrees based on a relative rate framework underlying the RelTime approach that is algebraic in nature and distinct from all other current methods. RTDT does not require many of the priors demanded by Bayesian approaches, and it has light computing requirements. In analyses of an extensive collection of computer-simulated datasets, we found the accuracy of RTDT time estimates and the coverage probabilities of their confidence intervals (CIs) to be excellent. In analyses of empirical datasets, RTDT produced dates that were similar to those reported in the literature. In comparative benchmarking with Bayesian and non-Bayesian methods (LSD, TreeTime, and treedater), we found that no method performed the best in every scenario. So, we provide a brief guideline for users to select the most appropriate method in empirical data analysis. RTDT is implemented for use via a graphical user interface and in high-throughput settings in the newest release of cross-platform MEGA X software, freely available from http://www.megasoftware.net.

Molecular Evolutionary Genetics Analysis (MEGA) for macOS.

The Molecular Evolutionary Genetics Analysis (MEGA) software enables comparative analysis of molecular sequences in phylogenetics and evolutionary medicine. Here, we introduce the macOS version of the MEGA software. This new version eliminates the need for virtualization and emulation programs previously required to use MEGA on Apple computers. MEGA for macOS utilizes memory and computing resources efficiently for conducting evolutionary analyses on macOS. It has a native Cocoa graphical user interface that is programmed to provide a consistent user experience across macOS, Windows, and Linux. MEGA for macOS is available from www.megasoftware.net free of charge.

Reliable Confidence Intervals for RelTime Estimates of Evolutionary Divergence Times.

Confidence intervals (CIs) depict the statistical uncertainty surrounding evolutionary divergence time estimates. They capture variance contributed by the finite number of sequences and sites used in the alignment, deviations of evolutionary rates from a strict molecular clock in a phylogeny, and uncertainty associated with clock calibrations. Reliable tests of biological hypotheses demand reliable CIs. However, current non-Bayesian methods may produce unreliable CIs because they do not incorporate rate variation among lineages and interactions among clock calibrations properly. Here, we present a new analytical method to calculate CIs of divergence times estimated using the RelTime method, along with an approach to utilize multiple calibration uncertainty densities in dating analyses. Empirical data analyses showed that the new methods produce CIs that overlap with Bayesian highest posterior density intervals. In the analysis of computer-simulated data, we found that RelTime CIs show excellent average coverage probabilities, that is, the actual time is contained within the CIs with a 94% probability. These developments will encourage broader use of computationally efficient RelTime approaches in molecular dating analyses and biological hypothesis testing.

Inferring the demographic history of Japanese cedar, Cryptomeria japonica, using amplicon sequencing.

The evolution of a species depends on multiple forces, such as demography and natural selection. To understand the trajectory and driving forces of evolution of a target species, it is first necessary to uncover that species' population history, such as past and present population sizes, subdivision and gene flow, by using appropriate genetic markers. Cryptomeria japonica is a long-lived monoecious conifer species that is distributed in Japan. There are two main lines (omote-sugi and ura-sugi), which are distinguished by apparent differences in morphological traits that may have contributed to their local adaptation. The evolution of these morphological traits seems to be related to past climatic changes in East Asia, but no precise estimate is available for the divergence time of these two lines and the subsequent population dynamics in this species. Here, we analyzed the nucleotide variations at 120 nuclear genes in 94 individuals by using amplicon sequencing in combination with high-throughput sequencing technologies. Our analysis indicated that the population on Yakushima Island, the southern distribution limit of C. japonica in Japan, diverged from the other populations 0.85 million years ago (MYA). The divergence time of the other populations on mainland Japan was estimated to be 0.32 MYA suggesting that the divergence of omote-sugi and ura-sugi might have occurred before the last glacial maximum. Although we found modest levels of gene flow between the present populations, the long-term isolation and environmental heterogeneity caused by climatic changes might have contributed to the differentiation of the lines and their local adaptation.

A Machine Learning Method for Detecting Autocorrelation of Evolutionary Rates in Large Phylogenies.

New species arise from pre-existing species and inherit similar genomes and environments. This predicts greater similarity of the tempo of molecular evolution between direct ancestors and descendants, resulting in autocorrelation of evolutionary rates in the tree of life. Surprisingly, molecular sequence data have not confirmed this expectation, possibly because available methods lack the power to detect autocorrelated rates. Here, we present a machine learning method, CorrTest, to detect the presence of rate autocorrelation in large phylogenies. CorrTest is computationally efficient and performs better than the available state-of-the-art method. Application of CorrTest reveals extensive rate autocorrelation in DNA and amino acid sequence evolution of mammals, birds, insects, metazoans, plants, fungi, parasitic protozoans, and prokaryotes. Therefore, rate autocorrelation is a common phenomenon throughout the tree of life. These findings suggest concordance between molecular and nonmolecular evolutionary patterns, and they will foster unbiased and precise dating of the tree of life.

Theoretical Foundation of the RelTime Method for Estimating Divergence Times from Variable Evolutionary Rates.

RelTime estimates divergence times by relaxing the assumption of a strict molecular clock in a phylogeny. It shows excellent performance in estimating divergence times for both simulated and empirical molecular sequence data sets in which evolutionary rates varied extensively throughout the tree. RelTime is computationally efficient and scales well with increasing size of data sets. Until now, however, RelTime has not had a formal mathematical foundation. Here, we show that the basis of the RelTime approach is a relative rate framework (RRF) that combines comparisons of evolutionary rates in sister lineages with the principle of minimum rate change between evolutionary lineages and their respective descendants. We present analytical solutions for estimating relative lineage rates and divergence times under RRF. We also discuss the relationship of RRF with other approaches, including the Bayesian framework. We conclude that RelTime will be useful for phylogenies with branch lengths derived not only from molecular data, but also morphological and biochemical traits.

RelTime Relaxes the Strict Molecular Clock throughout the Phylogeny.

The RelTime method estimates divergence times when evolutionary rates vary among lineages. Theoretical analyses show that RelTime relaxes the strict molecular clock throughout a molecular phylogeny, and it performs well in the analyses of empirical and computer simulated data sets in which evolutionary rates are variable. Lozano-Fernandez et al. (2017) found that the application of RelTime to one metazoan data set (Erwin et al. 2011) produced equal rates for several ancient lineages, which led them to speculate that RelTime imposes a strict molecular clock for deep animal divergences. RelTime does not impose a strict molecular clock. The pattern observed by Lozano-Fernandez et al. (2017) was a result of the use of an option to assign the same rate to lineages in RelTime when the rates are not statistically significantly different. The median rate difference was 5% for many deep metazoan lineages for the Erwin et al. (2011) data set, so the rate equality was not rejected. In fact, RelTime analyses with and without the option to test rate differences produced very similar time estimates. We also found that the Bayesian time estimates vary widely depending on the root priors assigned, and that the use of less restrictive priors produces Bayesian divergence times that are concordant with those from RelTime for the Erwin et al. (2011) data set. Therefore, it is prudent to discuss Bayesian estimates obtained under a range of priors in any discourse about molecular dating, including method comparisons.

Adaptive Landscape of Protein Variation in Human Exomes.

The human genome contains hundreds of thousands of missense mutations. However, only a handful of these variants are known to be adaptive, which implies that adaptation through protein sequence change is an extremely rare phenomenon in human evolution. Alternatively, existing methods may lack the power to pinpoint adaptive variation. We have developed and applied an Evolutionary Probability Approach (EPA) to discover candidate adaptive polymorphisms (CAPs) through the discordance between allelic evolutionary probabilities and their observed frequencies in human populations. EPA reveals thousands of missense CAPs, which suggest that a large number of previously optimal alleles experienced a reversal of fortune in the human lineage. We explored nonadaptive mechanisms to explain CAPs, including the effects of demography, mutation rate variability, and negative and positive selective pressures in modern humans. Many nonadaptive hypotheses were tested, but failed to explain the data, which suggests that a large proportion of CAP alleles have increased in frequency due to beneficial selection. This suggestion is supported by the fact that a vast majority of adaptive missense variants discovered previously in humans are CAPs, and hundreds of CAP alleles are protective in genotype-phenotype association data. Our integrated phylogenomic and population genetic EPA approach predicts the existence of thousands of nonneutral candidate variants in the human proteome. We expect this collection to be enriched in beneficial variation. The EPA approach can be applied to discover candidate adaptive variation in any protein, population, or species for which allele frequency data and reliable multispecies alignments are available.

MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.

Polymorphism and structure of style-specific arabinogalactan proteins as determinants of pollen tube growth in Nicotiana.

BACKGROUND: Pollen tube growth and fertilization are key processes in angiosperm sexual reproduction. The transmitting tract (TT) of Nicotiana tabacum controls pollen tube growth in part by secreting pistil extensin-like protein III (PELPIII), transmitting-tract-specific (TTS) protein and 120 kDa glycoprotein (120 K) into the stylar extracellular matrix. The three arabinogalactan proteins (AGP) are referred to as stylar AGPs and are the focus of this research. The transmitting tract regulates pollen tube growth, promoting fertilization or rejecting pollen tubes. RESULTS: The N-terminal domain (NTD) of the stylar AGPs is proline rich and polymorphic among Nicotiana spp. The NTD was predicted to be mainly an intrinsically disordered region (IDR), making it a candidate for protein-protein interactions. The NTD is also the location for the majority of the predicted O-glycosylation sites that were variable among Nicotiana spp. The C-terminal domain (CTD) contains an Ole e 1-like domain, that was predicted to form beta-sheets that are similar in position and length among Nicotiana spp. and among stylar AGPs. The TTS protein had the greatest amino acid and predicted O-glycosylation conservation among Nicotiana spp. relative to the PELPIII and 120 K. The PELPIII, TTS and 120 K genes undergo negative selection, with dn/ds ratios of 0.59, 0.29 and 0.38 respectively. The dn/ds ratio for individual species ranged from 0.4 to 0.9 and from 0.1 to 0.8, for PELPIII and TTS genes, respectively. These data indicate that PELPIII and TTS genes are under different selective pressures. A newly discovered AGP gene, Nicotiana tabacum Proline Rich Protein (NtPRP), was found with a similar intron-exon configuration and protein structure resembling other stylar AGPs, particularly TTS. CONCLUSIONS: Further studies of the NtPRP gene are necessary to elucidate its biological role. Due to its high similarity to the TTS gene, NtPRP may be involved in pollen tube guidance and growth. In contrast to TTS, both PELPIII and 120 K genes are more diverse indicating a possible role in speciation or mating preference of Nicotiana spp. We hypothesize that the stylar AGPs and NtPRP share a common origin from a single gene that duplicated and diversified into four distinct genes involved in pollen-style interactions.

Semi-automated quantitative Drosophila wings measurements.

BACKGROUND: Drosophila melanogaster is an important organism used in many fields of biological research such as genetics and developmental biology. Drosophila wings have been widely used to study the genetics of development, morphometrics and evolution. Therefore there is much interest in quantifying wing structures of Drosophila. Advancement in technology has increased the ease in which images of Drosophila can be acquired. However such studies have been limited by the slow and tedious process of acquiring phenotypic data. RESULTS: We have developed a system that automatically detects and measures key points and vein segments on a Drosophila wing. Key points are detected by performing image transformations and template matching on Drosophila wing images while vein segments are detected using an Active Contour algorithm. The accuracy of our key point detection was compared against key point annotations of users. We also performed key point detection using different training data sets of Drosophila wing images. We compared our software with an existing automated image analysis system for Drosophila wings and showed that our system performs better than the state of the art. Vein segments were manually measured and compared against the measurements obtained from our system. CONCLUSION: Our system was able to detect specific key points and vein segments from Drosophila wing images with high accuracy.

Deciphering the Routes of invasion of Drosophila suzukii by Means of ABC Random Forest.

Deciphering invasion routes from molecular data is crucial to understanding biological invasions, including identifying bottlenecks in population size and admixture among distinct populations. Here, we unravel the invasion routes of the invasive pest Drosophila suzukii using a multi-locus microsatellite dataset (25 loci on 23 worldwide sampling locations). To do this, we use approximate Bayesian computation (ABC), which has improved the reconstruction of invasion routes, but can be computationally expensive. We use our study to illustrate the use of a new, more efficient, ABC method, ABC random forest (ABC-RF) and compare it to a standard ABC method (ABC-LDA). We find that Japan emerges as the most probable source of the earliest recorded invasion into Hawaii. Southeast China and Hawaii together are the most probable sources of populations in western North America, which then in turn served as sources for those in eastern North America. European populations are genetically more homogeneous than North American populations, and their most probable source is northeast China, with evidence of limited gene flow from the eastern US as well. All introduced populations passed through bottlenecks, and analyses reveal five distinct admixture events. These findings can inform hypotheses concerning how this species evolved between different and independent source and invasive populations. Methodological comparisons indicate that ABC-RF and ABC-LDA show concordant results if ABC-LDA is based on a large number of simulated datasets but that ABC-RF out-performs ABC-LDA when using a comparable and more manageable number of simulated datasets, especially when analyzing complex introduction scenarios.

Fast and Accurate Estimates of Divergence Times from Big Data.

Ongoing advances in sequencing technology have led to an explosive expansion in the molecular data available for building increasingly larger and more comprehensive timetrees. However, Bayesian relaxed-clock approaches frequently used to infer these timetrees impose a large computational burden and discourage critical assessment of the robustness of inferred times to model assumptions, influence of calibrations, and selection of optimal data subsets. We analyzed eight large, recently published, empirical datasets to compare time estimates produced by RelTime (a non-Bayesian method) with those reported by using Bayesian approaches. We find that RelTime estimates are very similar to Bayesian approaches, yet RelTime requires orders of magnitude less computational time. This means that the use of RelTime will enable greater rigor in molecular dating, because faster computational speeds encourage more extensive testing of the robustness of inferred timetrees to prior assumptions (models and calibrations) and data subsets. Thus, RelTime provides a reliable and computationally thrifty approach for dating the tree of life using large-scale molecular datasets.

MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.