Phylogenetics of subtribe Orchidinae s.l. (Orchidaceae; Orchidoideae) based on seven markers (plastid  matK ,  psaB, rbcL, trnL-F, trnH-psba,  and nuclear nrITS,  Xdh ): implications for generic delimitation

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

Subtribe Orchidinae (Orchidaceae, Orchidoideae) are a nearly cosmopolitan taxon of terrestrial orchids, comprising about 1800 species in 47 to 60 genera. Although much progress has been made in recent years of phylogenetics of Orchidinae, considerable problems remain to be addressed. Based on molecular phylogenetics, we attempt to illustrate the phylogenetic relationships and discuss generic delimitation within Orchidinae. Seven DNA markers (five plastid and two nuclear), a broad sampling of Orchidinae (400 species in 52 genera) and three methods of phylogenetic analysis (maximum likelihood, maximum parsimony and Bayesian inference) were used.

Results

Orchidinae s.l. are monophyletic. Satyrium is sister to the rest of Orchidinae s.l. Brachycorythis and Schizochilus are successive sister to Asian-European Orchidinae s.s. Sirindhornia and Shizhenia are successive sister to clade formed by Tsaiorchis- Hemipilia- Ponerorchis alliance. Stenoglottis is sister to the Habenaria-Herminium-Peristylus alliance. Habenaria, currently the largest genus in Orchidinae, is polyphyletic and split into two distant clades: one Asian-Australian and the other African–American–Asian. Diplomeris is sister to Herminium s.l. plus Asian-Australian Habenaria.

Conclusions

We propose to recognize five genera in the Ponerorchis alliance: Hemipilia, Ponerorchis s.l., Sirindhornia, Shizhenia and Tsaiorchis. Splitting Habenaria into two genera based on morphological characters and geographical distribution may be the least disruptive approach, and it is reasonable to keep Satyrium in Orchidinae.

Electronic supplementary material

The online version of this article (10.1186/s12870-017-1160-x) contains supplementary material, which is available to authorized users.

Related collections

Most cited references 50

Record: found
Abstract: found
Article: not found

SequenceMatrix: concatenation software for the fast assembly of multi-gene datasets with character set and codon information

Gaurav Vaidya, David Lohman, Rudolf Meier (2011)

We present SequenceMatrix, software that is designed to facilitate the assembly and analysis of multi-gene datasets. Genes are concatenated by dragging and dropping FASTA, NEXUS, or TNT files with aligned sequences into the program window. A multi-gene dataset is concatenated and displayed in a spreadsheet; each sequence is represented by a cell that provides information on sequence length, number of indels, the number of ambiguous bases ("Ns"), and the availability of codon information. Alternatively, GenBank numbers for the sequences can be displayed and exported. Matrices with hundreds of genes and taxa can be concatenated within minutes and exported in TNT, NEXUS, or PHYLIP formats, preserving both character set and codon information for TNT and NEXUS files. SequenceMatrix also creates taxon sets listing taxa with a minimum number of characters or gene fragments, which helps assess preliminary datasets. Entire taxa, whole gene fragments, or individual sequences for a particular gene and species can be excluded from export. Data matrices can be re-split into their component genes and the gene fragments can be exported as individual gene files. SequenceMatrix also includes two tools that help to identify sequences that may have been compromised through laboratory contamination or data management error. One tool lists identical or near-identical sequences within genes, while the other compares the pairwise distance pattern of one gene against the pattern for all remaining genes combined. SequenceMatrix is Java-based and compatible with the Microsoft Windows, Apple MacOS X and Linux operating systems. The software is freely available from http://code.google.com/p/sequencematrix/. © The Willi Hennig Society 2010.

0 comments Cited 743 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Bayesian phylogenetic analysis of combined data.

Johan Nylander, Fredrik Ronquist, John P. Huelsenbeck … (2004)

The recent development of Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) techniques has facilitated the exploration of parameter-rich evolutionary models. At the same time, stochastic models have become more realistic (and complex) and have been extended to new types of data, such as morphology. Based on this foundation, we developed a Bayesian MCMC approach to the analysis of combined data sets and explored its utility in inferring relationships among gall wasps based on data from morphology and four genes (nuclear and mitochondrial, ribosomal and protein coding). Examined models range in complexity from those recognizing only a morphological and a molecular partition to those having complex substitution models with independent parameters for each gene. Bayesian MCMC analysis deals efficiently with complex models: convergence occurs faster and more predictably for complex models, mixing is adequate for all parameters even under very complex models, and the parameter update cycle is virtually unaffected by model partitioning across sites. Morphology contributed only 5% of the characters in the data set but nevertheless influenced the combined-data tree, supporting the utility of morphological data in multigene analyses. We used Bayesian criteria (Bayes factors) to show that process heterogeneity across data partitions is a significant model component, although not as important as among-site rate variation. More complex evolutionary models are associated with more topological uncertainty and less conflict between morphology and molecules. Bayes factors sometimes favor simpler models over considerably more parameter-rich models, but the best model overall is also the most complex and Bayes factors do not support exclusion of apparently weak parameters from this model. Thus, Bayes factors appear to be useful for selecting among complex models, but it is still unclear whether their use strikes a reasonable balance between model complexity and error in parameter estimates.

0 comments Cited 510 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: not found
Article: not found

Constructing a Significance Test for Incongruence

J. S. Farris, M Källersjö, A. G. Kluge … (1995)

0 comments Cited 148 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Wei-Tao Jin: jinweitao@ibcas.ac.cn

André Schuiteman: A.Schuiteman@kew.org

Mark W. Chase: M.Chase@kew.org

Jian-Wu Li: ljw@xtbg.org.cn

Shih-Wen Chung: biflora@gmail.com

Tian-Chuan Hsu: lecanorchis@gmail.com

Xiao-Hua Jin: 86-10-62836582 , xiaohuajin@ibcas.ac.cn

Journal

Journal ID (nlm-ta): BMC Plant Biol

Journal ID (iso-abbrev): BMC Plant Biol

Title: BMC Plant Biology

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2229

Publication date (Electronic): 25 November 2017

Publication date PMC-release: 25 November 2017

Publication date Collection: 2017

Volume: 17

Electronic Location Identifier: 222

Affiliations

[1 ]ISNI 0000 0004 0596 3367, GRID grid.435133.3, State Key Laboratory of Systematic and Evolutionary Botany, , Institute of Botany, Chinese Academy of Sciences, ; Beijing, 10093 China

[2 ]ISNI 0000 0001 2097 4353, GRID grid.4903.e, Identification and Naming Department, Royal Botanic Gardens, Kew, ; Richmond, Surrey TW9 3AB UK

[3 ]ISNI 0000 0001 2097 4353, GRID grid.4903.e, Jodrell Laboratory, Royal Botanic Gardens, Kew, ; Richmond, Surrey TW9 3DS UK

[4 ]ISNI 0000 0004 1936 7910, GRID grid.1012.2, School of Plant Biology, , University of Western Australia, ; Crawley, Perth, 6009 Australia

[5 ]ISNI 0000000119573309, GRID grid.9227.e, Xishuangbanna Tropical Botanical Garden, , Chinese Academy of Sciences, ; Menglun Township, Mengla County, Yunnan 666303 China

[6 ]GRID grid.410768.c, Botanical Garden Division, , Taiwan Forestry Research Institute, ; 53 Nanhai Road, Taipei, Taiwan 10066 China

[7 ]ISNI 0000 0004 0532 0580, GRID grid.38348.34, Department of Molecular and Cellular Biology, , National Tsing Hua University, ; Hsinchu, Taiwan 30013 China

[8 ]Southeast Asia Biodiversity Research Institute, Chinese Academy of Science (CAS-SEABRI), Yezin, Nay Pyi Taw, Myanmar

Article

Publisher ID: 1160

DOI: 10.1186/s12870-017-1160-x

PMC ID: 5702240

PubMed ID: 29178835

SO-VID: b929c7c1-a750-46c3-88a3-03d7810bde51

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 18 April 2017

Date accepted : 8 November 2017

Funding

Funded by: National Natural Science Foundation of China

Award ID: 31470299, 31670194, J1310002

Funded by: Southeast Asia Biodiversity Research Institute, Chinese Academy of Sciences

Award ID: Y4ZK111B01

Custom metadata

ScienceOpen disciplines: Plant science & Botany

Keywords: gennaria,habenaria,orchidinae s.l.,orchid generic delimitation,ponerorchis alliance,platanthera

Data availability:

ScienceOpen disciplines: Plant science & Botany

Keywords: gennaria, habenaria, orchidinae s.l., orchid generic delimitation, ponerorchis alliance, platanthera

Phylogenetics of subtribe Orchidinae s.l. (Orchidaceae; Orchidoideae) based on seven markers (plastid matK, psaB, rbcL, trnL-F, trnH-psba, and nuclear nrITS, Xdh): implications for generic delimitation

Read this article at

Abstract

Background

Results

Conclusions

Electronic supplementary material

Related collections

Plant MYBs

Most cited references 50

SequenceMatrix: concatenation software for the fast assembly of multi-gene datasets with character set and codon information

Bayesian phylogenetic analysis of combined data.

Constructing a Significance Test for Incongruence

Author and article information

Contributors

Journal

Affiliations

Article

History

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 182

Cited by 14

Most referenced authors 873