Award details

Next generation comparative methods

Reference	BB/L018594/1
Principal Investigator / Supervisor	Dr Andrew Meade
Co-Investigators / Co-Supervisors	Dr Chris Venditti
Institution	University of Reading
Department	Sch of Biological Sciences
Funding type	Research
Value (£)	143,208
Status	Completed
Type	Research Grant
Start date	27/04/2015
End date	26/10/2016
Duration	18 months

Abstract

The majority of comparative methods in use today assume a homogenous evolutionary process, through time and across the tree, this assumption is known to be wrong and the problem is exacerbated when homogenous comparative methods are used with large phylogenies, which span large time depth and include a diverse range of taxa. These methods can be shown to be positively misleading when only a small amount of heterogeneity exists. Results from homogeneous methods have been shown to produce incorrect results with high levels of certainty when compared against known measures such as the fossil record. This project aims to produce a range of comparative methods capable of accurately analysing the current and next generation of large scale phylogenies. The methods will remove the assumption of a homogenous evolutionary process through time and across the tree. Reverse Jump Markov chain Monte Carlo (RJ MCMC) will be used to detect and model change in evolutionary processes. This method extends pervious work which used RJ MCMC to detect and model heterogeneous evolutionary processes. The methods will be made available in the comparative methods software package BayesTraits.

Summary

Understanding evolutionary relationships and how characteristics of species (e.g. behaviours, genomes, morphological characteristics and proteins) evolve over time is a fundamental pursuit, either directly or indirectly, for all biologists. Computational tools to study how species characteristics change over time are called comparative methods. Among other things comparative methods are used to reconstruct ancestral forms, calculate how fast (or slow) characteristics change through time and to test if the evolution of species characteristics are correlated. Comparative methods are used thousands of time each year in scientific publications by biologists from all research areas. Recent advances in molecular sequencing technology and computer power have produced large and highly detailed maps of how species are related to each other. These maps are represented in a tree like form analogous to a family tree, they are known as phylogenies or phylogenetic trees. Phylogenetic trees are used in conjunction with species characteristics and comparative methods to help biologists infer historical processes of evolution. In 2013 two of the largest phylogenies were published, a near complete phylogeny of birds, comprising of almost 10,000 species and a large fish phylogeny of 8,000 species. These join a mammal phylogeny 5,000 species (2007), a 55,000 species tree of plants (2009) and a 6,000 species phylogeny of amphibians (2012). In contrast in the early 2000s a phylogeny of 100-200 species was considered very large. While the data and computing power have advanced inordinately over the last 20 years, the underlying statistics used in most comparative methods analysis has failed to keep pace. The statistical framework was laid down when a 30 species tree were considered large. This means that the vast majority of comparative methods assume that evolutionary processes are constant and homogeneous through time and through the tree. This assumption was not unreasonable when first introduced, as the available phylogenies consisted of a small number of closely related taxa which covered a narrow time period. Today the size of available phylogenies have grown enormously, they now cover more divergent groups and larger time frames and include a comprehensive sample of species. Using these trees we can now see that the homogenous assumption has been shown to produce incorrect results and hides important evolutionary information. Consider the evolution of body size in mammals, traditional comparative methods assume a homogeneous evolutionary process over hundreds of millions of years, affecting all species, at all time periods the same. But the evolutionary processes affecting some groups have been shown to be radically different, for example, flight in bats limit their body size, while being aquatic allows body size to increase. The assumption of a homogeneous process creates an averaging effect which is unable to detect important changes in evolutionary processes and produces results which are known to be wrong. This project will develop novel statistical methods which remove the assumption of a homogenous evolutionary process across the phylogenetic tree and through time. The methods will not only more accurately model heterogeneous evolutionary processes but of equal importance is their ability to automatically detect, without prior knowledge, the number and location of these shifts. The ability to automatically detect changes in evolutionary processes provides valuable biological insights allowing researchers to understand evolutionary processes on a finer scale than previously possible. These methods will directly benefit the thousands of researchers using comparative methods and bridge the gap between advances in data and the methods used to analyse them.

Impact Summary

The project aims to develop a range of advanced statistical methods to analyse a variety of data in an evolutionary context, the focus of the project is methodological development opposed to application. The impacts require the application of the methods which is outside of the scope of this project. The application of methods developed in this project will have a range of possible impacts. Environmental sustainability, protection and impact reduction Comparative methods are used to predict and evaluate extinction risk, Fisher and Owens highlights three main areas comparative methods are used by conservation biologists (i) identify mechanisms which cause conservation problems, (ii) as a basis to priorities funding / research and (iii) predict which species are most at risk. The use of comparative methods is a key tool in conservation biology and the ability to more accurately model evolutionary processes will be invaluable in conservation biology. Economic and Societal impact Comparative methods have been used to study cultural, social and linguistic change. BayesTraits is used for a wide variety of studies, these include understanding social structure and change, cross-cultural analysis, cultural development, impacts of technological advances and wealth transfer. Improved comparative methods models will allow many cultural systems to be studied more accurately and in greater detail.

Committee	Research Committee C (Genes, development and STEM approaches to biology)
Research Topics	Technology and Methods Development
Research Priority	X – Research Priority information not available
Research Initiative	Tools and Resources Development Fund (TRDF) [2006-2015]
Funding Scheme	X – not Funded via a specific Funding Scheme

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