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      Phylogenetic and morphological analyses of Pilosocereus leucocephalus group s.s. (Cactaceae) reveal new taxonomical implications

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          Abstract

          Pilosocereus is one of the Cactaceae family’s most relevant genera in terms of the number of species and its wide geographical range in the Americas. Within Pilosocereus, five informal taxonomic groups have been recognized, one of which is P. leucocephalus group s.s., whose phylogenetic relationships remain unresolved. Therefore, our objectives are to recognize the circumscriptions of the species in P. leucocephalus group s.s. and to corroborate the monophyly and phylogenetic relationships of this group through a set of morphological and molecular characters. This study is based on representative sampling along the broad distribution of this group in Mexico and Central America using multivariate and phylogenetic analyses. The morphological characters identified to contribute to species recognition and group formation are branch diameter, areole length, the areole length-width ratio, the distance between areoles, the length of the longest radial spine, and branch and spines colors. The chloroplast markers rpl16, trnL-trnF, and petL-psbE and the nuclear marker AT1G18270 support the monophyly of the P. leucocephalus group s.s., and two probable synapomorphies are suggested, including one transversion in rpl16 and another in petL-psbE. Together, our results demonstrate that sampled species of P. leucocephalus group s.s. encompass six species distributed in Mexico and Central America: P. alensis and P. purpusii in the western region, P. chrysacanthus and P. collinsii in the central region, and P. gaumeri and P. leucocephalus in the eastern region. A taxonomic key to recognized species is provided.

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          The online version contains supplementary material available at 10.1007/s10265-022-01384-x.

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          RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

          Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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            MUSCLE: multiple sequence alignment with high accuracy and high throughput.

            We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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              MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

              Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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                Author and article information

                Contributors
                daniel.franco@st.ib.unam.mx
                sarias@ib.unam.mx
                Journal
                J Plant Res
                J Plant Res
                Journal of Plant Research
                Springer Nature Singapore (Singapore )
                0918-9440
                1618-0860
                19 March 2022
                19 March 2022
                2022
                : 135
                : 3
                : 423-442
                Affiliations
                [1 ]GRID grid.9486.3, ISNI 0000 0001 2159 0001, Posgrado en Ciencias Biológicas, Instituto de Biología, , Universidad Nacional Autónoma de México, Ciudad Universitaria, Coyoacán, ; 04510 Mexico City, Mexico
                [2 ]GRID grid.9486.3, ISNI 0000 0001 2159 0001, Jardín Botánico, Instituto de Biología, , Universidad Nacional Autónoma de México, Tercer Circuito Exterior, Ciudad Universitaria, Coyoacán, ; 04510 Mexico City, Mexico
                [3 ]GRID grid.412165.5, ISNI 0000 0004 0401 9462, Grupo de Ecología y Conservación, , Jardín Botánico Nacional, Universidad de La Habana, ; Carretera El Rocío km 3½, Calabazar, Boyeros, 19 230 Havana, Cuba
                Author information
                http://orcid.org/0000-0002-8788-0025
                http://orcid.org/0000-0002-7876-7645
                http://orcid.org/0000-0001-6158-9099
                http://orcid.org/0000-0001-7570-4211
                http://orcid.org/0000-0002-7674-7050
                Article
                1384
                10.1007/s10265-022-01384-x
                9081079
                35305187
                ed75c793-3c03-48a9-a5f6-ea187849bb73
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 22 September 2021
                : 22 February 2022
                Funding
                Funded by: UNAM-DGAPA-PAPIIT
                Award ID: IN208619
                Award Recipient :
                Categories
                Regular Paper – Taxonomy/Phylogenetics/Evolutionary Biology
                Custom metadata
                © The Author(s) under exclusive licence to The Botanical Society of Japan 2022

                Plant science & Botany
                central america,mesoamerican dominion,mexico,multivariate analysis,phylogenetic analysis,pilosocereus

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