The use of discrete morphological data in Bayesian phylogenetics has increased significantly over the last years with the proposal of total evidence analysis and the treatment of fossils as terminal taxa in Bayesian molecular dating. Both approaches rely on the assumption that probabilistic Markov models reasonably accommodate all the complexity of morphological evolution of discrete traits. The performance of such morphological models used in Bayesian phylogenetics has been thoroughly investigated, but conclusions so far were based mostly on simulated data. In this study, we have surveyed MorphoBank and obtained a large number of morphological matrices to evaluate Bayesian phylogenetic inference (BI) under Lewis' Mk model in comparison with the maximum parsimony (MP) algorithm. We found that trees estimated by both methods frequently differed and that BI generated a larger amount of polytomic tree topologies. The number of trees contained in the 95% Bayesian credibility interval was significantly greater than the number of equally parsimonious trees. We also investigated which factors mostly influenced the topological difference between maximum parsimony and Bayesian tree topologies and found that the number of terminals in morphological matrices was the variable with the highest association with the topological distance between trees inferred by BI and MP. Surprisingly, we show that differences between both approaches were not influenced by increasing sample size. Our results, which were based on a large set of empirical matrices, corroborate recent findings that BI is less precise than MP.
The abrupt appearance of primates and hystricognath rodents in early Oligocene deposits of South America has puzzled mastozoologists for decades. Based on the geoclimatic changes that occurred during the Eocene/Oligocene transition period that may have favoured their dispersal, researchers have proposed the hypothesis that these groups arrived in synchrony. Nevertheless, the hypothesis of synchronous origins of platyrrhine and caviomorph in South America has not been explicitly evaluated. Our aim in this work was to apply a formal test for synchronous divergence times to the Platyrrhini and Caviomorpha splits. We have examined a previous work on platyrrhine and hystricognath origins, applied the test to a case where synchrony is known to occur and conducted simulations to show that it is possible to formally test the age of synchronous nodes. We show that the absolute ages of Platyrrhini/Catarrhini and Caviomorpha/Phiomorpha splits depend on data partitioning and that the test applied consistently detected synchronous events when they were known to have happened. The hypothesis that the arrival of primates and hystricognaths to the New World consisted of a unique event cannot be rejected
Phylogenetics has a central role in the biological sciences. We suggest a hands-on exercise to demonstrate the task of character coding and its importance in phylogenetic systematics. This exercise is appropriate for undergraduate students in life sciences and related courses. The teacher must provide a single group of masks in which color patterns, textures, and formats provide the characters to fill the data matrix. (The masks could be replaced by a set of other complex objects.) In this case, because there is no actual phylogeny, students will not be concerned with recovering the correct topology. Character coding is the aim of the exercise. After the character matrix is completed, a phylogenetic tree is drawn and the students interpret the evolution of a single character, starting from the common ancestor, based on the topological pattern of the tree and on the data matrix. In sequence, the students name and provide a full diagnosis for the group of masks as revealed by the topological pattern. The comparison between group results is also educational: there will be some common patterns between trees, but others will differ as in biological systematics.
Phylogenetic analysis based on multi-loci data sets is performed by means of supermatrix (SM) or supertree (ST) approaches. Recently, methods that rely on species tree (SppT) inference by the multi-species coalescence have also been implemented to tackle this problem. Generally, the relative performance of these three major strategies has been calculated using simulation of biological sequences. However, sequence simulation may not entirely replicate the complexity of the evolutionary process. Thus, issues regarding the usefulness of in silico sequences in studying the performance of phylogenetic methods have been raised. Here, we used both classical simulation and empirical data to investigate the relative performance of ST, SM, and the SppT methods. SM analyses performed better than the ST and SppTs in simulations, but not in empirical analyses where some ST methods significantly outperformed the others. Additionally, SM was the only method that was robust under evolutionary model violations in simulations. These results show that conventional biological sequence simulation cannot adequately resolve which method is most efficient to recover the SppT. In such simulations, the SM approach recovers the established phylogeny in most instances, whereas the performance of the ST and SppT methods is downgraded in simpler cases. When compared, the analyses based on empirical and simulated sequences yielded largely inconsistent results, with the latter showing a bias towards a seemingly superiority of SM approaches.
Submit Manuscript | http://medcraveonline.com of new technologies and the subsequent accessibility of refined methods due to cost reduction contributed to an immeasurable expansion of molecular facilities worldwide [1]. The rate of sequence submission has recently intensified for three primary reasons: the numerous and successful DNA barcoding projects [2,3], the advent of Next Generation Sequencing [4] and the subsequent decrease in prices for molecular sequencing services [5].As a consequence, genetic data repositories such as GenBank have been doubling in size every 18 months [6], rising from 606 sequences in the first 1982 release to close to 200 million sequences in the 218 th release in February 2017. Molecular data from more than 260 thousand nominal species is now widely accepted as a paramount source of biological information in all life sciences [7]. This is an exciting time. Many long existing controversies are in the process of being resolved by an unparalleled amount of data [6,8,9]. Phylogenomics, a dream just a few decades ago, is now changing the face of molecular phylogenetics. It is a revolution second only to the introduction of molecules in the field of phylogenetics in the 1960's.However, the availability of large number of sequences is not necessarily associated with an accurate estimation of phylogenies, due to analytical errors associated with very large sets of sequence data [10][11][12]. Hence, the contentious matter of molecular marker sampling is inhibiting this new breakthrough. Different genes may yield strikingly contradictory topological patterns for a given diversity group [13,14]. Thus, the selection of suitable markers is critical in obtaining accurate estimates, but it is not a straightforward task. In this review, we aim to provide some guidelines for newcomers weighing the suitability of particular molecular markers for a given phylogenetic problem. Homology in Molecular MarkersIn phylogenetic reconstruction, as in comparative biology studies, the single most important concern lies in the matter of homology, a concept that occupies a central position in evolutionary biology [15]. Homology is a qualitative term, defined by equivalence of parts due to inherited common origin [16][17][18].Homology has been more recently defined as the relationship that binds all states of a single character and sets them apart from the states of other characters, supporting the logical equivalence of the notions of homology and synapomorphy (for review see [19]). The comparison of homologous sequences is critical in a phylogenetic analysis, because only homologous characters may reveal the actual phylogenetic pattern.Nevertheless, a number of authors erroneously refer to homology as a synonym for similarity. Molecular biologists are particularly prone to this error, as they assert that 'two sequences share 70% homology' (for reviews on this problem see [15,20]). Two sequences might show 70% similarity, if 7 out of 10 aligned base pairs are identical between them.In molecular sequences, the high...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.