@ARTICLE{TreeBASE2Ref23398,
author = {Seraina Klopfstein and Lars Vilhelmsen and Fredrik Ronquist},
title = {A non-stationary Markov model detects directional evolution in hymenopteran morphology},
year = {2015},
keywords = {continuous-time Markov model, Bayesian inference, directional selection, positive selection, neutral evolution, Symphyta, Hymenoptera, morphology, non-stationary},
doi = {10.1093/sysbio/syv052},
url = {http://sysbio.oxfordjournals.org/content/64/6/1089},
pmid = {},
journal = {Systematic Biology},
volume = {64},
number = {6},
pages = {1089--1103},
abstract = {Directional evolution has played an important role in shaping the morphological, ecological and molecular diversity of life. However, standard substitution models assume stationarity of the evolutionary process over the time scale examined, thus hampering the study of directionality. Here we explore a simple, non-stationary model of evolution for discrete data, which assumes that the state frequencies at the root differ from the equilibrium frequencies of the homogeneous evolutionary process along the rest of the tree (i.e., the process is non-stationary, non-reversible, but homogeneous). Within this framework, we develop a Bayesian approach for testing directional versus stationary evolution using a reversible-jump algorithm. Simulations show that when only data from extant taxa is available, the success in inferring directionality is strongly dependent on the evolutionary rate, the shape of the tree, the relative branch lengths, and the number of taxa. Given suitable evolutionary rates (0.1 to 0.5 expected substitutions between root and tips), accounting for directionality improves tree inference and often allows correct rooting of the tree without the use of an outgroup. As an empirical test, we apply our method to study directional evolution in hymenopteran morphology. We focus on three character systems: wing veins, muscles, and sclerites. We find strong support for a trend towards loss of wing veins and muscles, while stationarity cannot be ruled out for sclerites. Adding fossil and time information in a total-evidence dating approach, we show that accounting for directionality results in more precise estimates not only of the ancestral state at the root of the tree, but also of the divergence times. Our model relaxes the assumption of stationarity and reversibility by adding a minimum of additional parameters, and is thus well suited to studying the nature of the evolutionary process in datasets of limited size, such as morphology.}
}
Citation for Study 16060
Citation title:
"A non-stationary Markov model detects directional evolution in hymenopteran morphology".
Study name:
"A non-stationary Markov model detects directional evolution in hymenopteran morphology".
This study is part of submission 16060
(Status: Published).
Citation
Klopfstein S., Vilhelmsen L., & Ronquist F. 2015. A non-stationary Markov model detects directional evolution in hymenopteran morphology. Systematic Biology, 64(6): 1089-1103.
Authors
-
Klopfstein S.
-
Vilhelmsen L.
-
Ronquist F.
+46-8 5195 4094
Abstract
Directional evolution has played an important role in shaping the morphological, ecological and molecular diversity of life. However, standard substitution models assume stationarity of the evolutionary process over the time scale examined, thus hampering the study of directionality. Here we explore a simple, non-stationary model of evolution for discrete data, which assumes that the state frequencies at the root differ from the equilibrium frequencies of the homogeneous evolutionary process along the rest of the tree (i.e., the process is non-stationary, non-reversible, but homogeneous). Within this framework, we develop a Bayesian approach for testing directional versus stationary evolution using a reversible-jump algorithm. Simulations show that when only data from extant taxa is available, the success in inferring directionality is strongly dependent on the evolutionary rate, the shape of the tree, the relative branch lengths, and the number of taxa. Given suitable evolutionary rates (0.1 to 0.5 expected substitutions between root and tips), accounting for directionality improves tree inference and often allows correct rooting of the tree without the use of an outgroup. As an empirical test, we apply our method to study directional evolution in hymenopteran morphology. We focus on three character systems: wing veins, muscles, and sclerites. We find strong support for a trend towards loss of wing veins and muscles, while stationarity cannot be ruled out for sclerites. Adding fossil and time information in a total-evidence dating approach, we show that accounting for directionality results in more precise estimates not only of the ancestral state at the root of the tree, but also of the divergence times. Our model relaxes the assumption of stationarity and reversibility by adding a minimum of additional parameters, and is thus well suited to studying the nature of the evolutionary process in datasets of limited size, such as morphology.
Keywords
continuous-time Markov model, Bayesian inference, directional selection, positive selection, neutral evolution, Symphyta, Hymenoptera, morphology, non-stationary
External links
About this resource
- Canonical resource URI:
http://purl.org/phylo/treebase/phylows/study/TB2:S16060
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- Show BibTeX reference
@ARTICLE{TreeBASE2Ref23398,
author = {Seraina Klopfstein and Lars Vilhelmsen and Fredrik Ronquist},
title = {A non-stationary Markov model detects directional evolution in hymenopteran morphology},
year = {2015},
keywords = {continuous-time Markov model, Bayesian inference, directional selection, positive selection, neutral evolution, Symphyta, Hymenoptera, morphology, non-stationary},
doi = {10.1093/sysbio/syv052},
url = {http://sysbio.oxfordjournals.org/content/64/6/1089},
pmid = {},
journal = {Systematic Biology},
volume = {64},
number = {6},
pages = {1089--1103},
abstract = {Directional evolution has played an important role in shaping the morphological, ecological and molecular diversity of life. However, standard substitution models assume stationarity of the evolutionary process over the time scale examined, thus hampering the study of directionality. Here we explore a simple, non-stationary model of evolution for discrete data, which assumes that the state frequencies at the root differ from the equilibrium frequencies of the homogeneous evolutionary process along the rest of the tree (i.e., the process is non-stationary, non-reversible, but homogeneous). Within this framework, we develop a Bayesian approach for testing directional versus stationary evolution using a reversible-jump algorithm. Simulations show that when only data from extant taxa is available, the success in inferring directionality is strongly dependent on the evolutionary rate, the shape of the tree, the relative branch lengths, and the number of taxa. Given suitable evolutionary rates (0.1 to 0.5 expected substitutions between root and tips), accounting for directionality improves tree inference and often allows correct rooting of the tree without the use of an outgroup. As an empirical test, we apply our method to study directional evolution in hymenopteran morphology. We focus on three character systems: wing veins, muscles, and sclerites. We find strong support for a trend towards loss of wing veins and muscles, while stationarity cannot be ruled out for sclerites. Adding fossil and time information in a total-evidence dating approach, we show that accounting for directionality results in more precise estimates not only of the ancestral state at the root of the tree, but also of the divergence times. Our model relaxes the assumption of stationarity and reversibility by adding a minimum of additional parameters, and is thus well suited to studying the nature of the evolutionary process in datasets of limited size, such as morphology.}
}
- Show RIS reference
TY - JOUR
ID - 23398
AU - Klopfstein,Seraina
AU - Vilhelmsen,Lars
AU - Ronquist,Fredrik
T1 - A non-stationary Markov model detects directional evolution in hymenopteran morphology
PY - 2015
KW - continuous-time Markov model
KW - Bayesian inference
KW - directional selection
KW - positive selection
KW - neutral evolution
KW - Symphyta
KW - Hymenoptera
KW - morphology
KW - non-stationary
UR - http://sysbio.oxfordjournals.org/content/64/6/1089
N2 - Directional evolution has played an important role in shaping the morphological, ecological and molecular diversity of life. However, standard substitution models assume stationarity of the evolutionary process over the time scale examined, thus hampering the study of directionality. Here we explore a simple, non-stationary model of evolution for discrete data, which assumes that the state frequencies at the root differ from the equilibrium frequencies of the homogeneous evolutionary process along the rest of the tree (i.e., the process is non-stationary, non-reversible, but homogeneous). Within this framework, we develop a Bayesian approach for testing directional versus stationary evolution using a reversible-jump algorithm. Simulations show that when only data from extant taxa is available, the success in inferring directionality is strongly dependent on the evolutionary rate, the shape of the tree, the relative branch lengths, and the number of taxa. Given suitable evolutionary rates (0.1 to 0.5 expected substitutions between root and tips), accounting for directionality improves tree inference and often allows correct rooting of the tree without the use of an outgroup. As an empirical test, we apply our method to study directional evolution in hymenopteran morphology. We focus on three character systems: wing veins, muscles, and sclerites. We find strong support for a trend towards loss of wing veins and muscles, while stationarity cannot be ruled out for sclerites. Adding fossil and time information in a total-evidence dating approach, we show that accounting for directionality results in more precise estimates not only of the ancestral state at the root of the tree, but also of the divergence times. Our model relaxes the assumption of stationarity and reversibility by adding a minimum of additional parameters, and is thus well suited to studying the nature of the evolutionary process in datasets of limited size, such as morphology.
L3 - 10.1093/sysbio/syv052
JF - Systematic Biology
VL - 64
IS - 6
SP - 1089
EP - 1103
ER -