Xun Gu
- Published in print:
- 2010
- Published Online:
- January 2011
- ISBN:
- 9780199213269
- eISBN:
- 9780191594762
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199213269.001.0001
- Subject:
- Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies
Evolutionary genomics is a relatively new research field with the ultimate goal of understanding the underlying evolutionary and genetic mechanisms for the emergence of genome complexity under ...
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Evolutionary genomics is a relatively new research field with the ultimate goal of understanding the underlying evolutionary and genetic mechanisms for the emergence of genome complexity under changing environments. It stems from an integration of high throughput data from functional genomics, statistical modelling and bioinformatics, and the procedure of phylogeny-based analysis. This book summarises the statistical framework of evolutionary genomics, and illustrates how statistical modelling and testing can enhance our understanding of functional genomic evolution. The book reviews the recent developments in methodology from an evolutionary perspective of genome function, and incorporates substantial examples from high throughput data in model organisms. In addition to phylogeny-based functional analysis of DNA sequences, the book includes discussion on how new types of functional genomic data (e.g., microarray) can provide exciting new insights into the evolution of genome function, which can lead in turn to an understanding of the emergence of genome complexity during evolution.Less
Evolutionary genomics is a relatively new research field with the ultimate goal of understanding the underlying evolutionary and genetic mechanisms for the emergence of genome complexity under changing environments. It stems from an integration of high throughput data from functional genomics, statistical modelling and bioinformatics, and the procedure of phylogeny-based analysis. This book summarises the statistical framework of evolutionary genomics, and illustrates how statistical modelling and testing can enhance our understanding of functional genomic evolution. The book reviews the recent developments in methodology from an evolutionary perspective of genome function, and incorporates substantial examples from high throughput data in model organisms. In addition to phylogeny-based functional analysis of DNA sequences, the book includes discussion on how new types of functional genomic data (e.g., microarray) can provide exciting new insights into the evolution of genome function, which can lead in turn to an understanding of the emergence of genome complexity during evolution.
Xun Gu
- Published in print:
- 2010
- Published Online:
- January 2011
- ISBN:
- 9780199213269
- eISBN:
- 9780191594762
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199213269.003.0010
- Subject:
- Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies
As evolutionary biologists have always been concerned with the genetic basis for the emergence of complex phenotypes, advances in genomics and systems biology are facilitating a paradigm shift of ...
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As evolutionary biologists have always been concerned with the genetic basis for the emergence of complex phenotypes, advances in genomics and systems biology are facilitating a paradigm shift of molecular evolutionary biology toward a better understanding of the relationship of genotypes and phenotypes. From an evolutionary perspective, the central question is whether natural selection is a necessary and/or sufficient force to explain the emergence of genomic and cellular features that underlie the building of complex organisms. Lynch has criticized the adaptive hypothesis for the origins of organismal complexity, claiming that nothing in evolution makes sense in light of population genetics that takes the effects of mutation, genetic drift, and natural selection into account. The importance of mutation types and genetic drifts on the phenotype evolution has also been emphasized by Nei and his associates. One plausible approach to resolving these fundamental issues is to model the features of biological complexity as parameters instead of emerged properties, under the principle of population genetics and molecular evolution. This chapter discusses some recent results in this trend.Less
As evolutionary biologists have always been concerned with the genetic basis for the emergence of complex phenotypes, advances in genomics and systems biology are facilitating a paradigm shift of molecular evolutionary biology toward a better understanding of the relationship of genotypes and phenotypes. From an evolutionary perspective, the central question is whether natural selection is a necessary and/or sufficient force to explain the emergence of genomic and cellular features that underlie the building of complex organisms. Lynch has criticized the adaptive hypothesis for the origins of organismal complexity, claiming that nothing in evolution makes sense in light of population genetics that takes the effects of mutation, genetic drift, and natural selection into account. The importance of mutation types and genetic drifts on the phenotype evolution has also been emphasized by Nei and his associates. One plausible approach to resolving these fundamental issues is to model the features of biological complexity as parameters instead of emerged properties, under the principle of population genetics and molecular evolution. This chapter discusses some recent results in this trend.
Xun Gu
- Published in print:
- 2010
- Published Online:
- January 2011
- ISBN:
- 9780199213269
- eISBN:
- 9780191594762
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199213269.003.0001
- Subject:
- Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies
Molecular evolution is the study of the process of evolution at the level of DNA, RNA, and proteins, in which the neutral or nearly neutral evolution model has provided the theoretical basis. Yet, ...
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Molecular evolution is the study of the process of evolution at the level of DNA, RNA, and proteins, in which the neutral or nearly neutral evolution model has provided the theoretical basis. Yet, the role of positive selection at the molecular level remains a controversial issue. Recent advances in genomics, including whole-genome sequencing, high-throughput protein characterization, and bioinformatics have led to a dramatic increase in studies in comparative and evolutionary genomics. This chapter introduces some widely-used methods in genomic analysis. These include distance method, parsimony methods, maximum-likelihood methods, Bayesian methods, and ancestral sequence inference.Less
Molecular evolution is the study of the process of evolution at the level of DNA, RNA, and proteins, in which the neutral or nearly neutral evolution model has provided the theoretical basis. Yet, the role of positive selection at the molecular level remains a controversial issue. Recent advances in genomics, including whole-genome sequencing, high-throughput protein characterization, and bioinformatics have led to a dramatic increase in studies in comparative and evolutionary genomics. This chapter introduces some widely-used methods in genomic analysis. These include distance method, parsimony methods, maximum-likelihood methods, Bayesian methods, and ancestral sequence inference.
Xun Gu
- Published in print:
- 2010
- Published Online:
- January 2011
- ISBN:
- 9780199213269
- eISBN:
- 9780191594762
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199213269.003.0002
- Subject:
- Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies
The available web-based genome resources provide great opportunities for biomedical scientists to identify functional elements in a particular genome region or explore the evolutionary pattern of ...
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The available web-based genome resources provide great opportunities for biomedical scientists to identify functional elements in a particular genome region or explore the evolutionary pattern of genome dynamics. This chapter gives a brief review of the availability of web-based databases and software for selected important topics. Topics covered include bioinformatic resources for evolutionary genomics, basic statistics for homologous search, sequence alignment, microarrays and statistics, and Markov chain Monte Carlo algorithms.Less
The available web-based genome resources provide great opportunities for biomedical scientists to identify functional elements in a particular genome region or explore the evolutionary pattern of genome dynamics. This chapter gives a brief review of the availability of web-based databases and software for selected important topics. Topics covered include bioinformatic resources for evolutionary genomics, basic statistics for homologous search, sequence alignment, microarrays and statistics, and Markov chain Monte Carlo algorithms.
Gregory A. Wray
- Published in print:
- 2010
- Published Online:
- August 2013
- ISBN:
- 9780262513678
- eISBN:
- 9780262315142
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262513678.003.0005
- Subject:
- Biology, Evolutionary Biology / Genetics
This chapter characterizes the consequences of a shift of focus from individual genes to gene networks. It describes some of the opportunities and challenges that the genomic era brings to ...
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This chapter characterizes the consequences of a shift of focus from individual genes to gene networks. It describes some of the opportunities and challenges that the genomic era brings to evolutionary biology, and some of the ways current research into genome evolution is extending the Modern Synthesis. The chapter also discusses three extensions to the Modern Synthesis that are emerging out of the tumult and excitement of evolutionary genomics. It suggests that applying the traditional approaches of population genetics, evolutionary genetics, and molecular evolution to genomic data sets presents nontrivial challenges.Less
This chapter characterizes the consequences of a shift of focus from individual genes to gene networks. It describes some of the opportunities and challenges that the genomic era brings to evolutionary biology, and some of the ways current research into genome evolution is extending the Modern Synthesis. The chapter also discusses three extensions to the Modern Synthesis that are emerging out of the tumult and excitement of evolutionary genomics. It suggests that applying the traditional approaches of population genetics, evolutionary genetics, and molecular evolution to genomic data sets presents nontrivial challenges.
W. Brian Simison and Jeffrey L. Boore
- Published in print:
- 2008
- Published Online:
- March 2012
- ISBN:
- 9780520250925
- eISBN:
- 9780520933705
- Item type:
- chapter
- Publisher:
- University of California Press
- DOI:
- 10.1525/california/9780520250925.003.0017
- Subject:
- Biology, Animal Biology
This chapter focuses on studies of the evolutionary genomics of molluscans. It provides an overview of the state of molluscan mitochondrial genomics and outlines the promise of a broadening of this ...
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This chapter focuses on studies of the evolutionary genomics of molluscans. It provides an overview of the state of molluscan mitochondrial genomics and outlines the promise of a broadening of this data set. It explains how comparisons of mitochondrial genomes have reconstructed the relationships among Annelida, Sipuncula, and Mollusca and describes upcoming projects involving the sequencing of whole mollusc nuclear genome.Less
This chapter focuses on studies of the evolutionary genomics of molluscans. It provides an overview of the state of molluscan mitochondrial genomics and outlines the promise of a broadening of this data set. It explains how comparisons of mitochondrial genomes have reconstructed the relationships among Annelida, Sipuncula, and Mollusca and describes upcoming projects involving the sequencing of whole mollusc nuclear genome.
Rama S. Singh, Jianping Xu, and Rob J. Kulathinal
- Published in print:
- 2012
- Published Online:
- December 2013
- ISBN:
- 9780199642274
- eISBN:
- 9780191774751
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199642274.003.0001
- Subject:
- Biology, Evolutionary Biology / Genetics
Evolutionary rates not only reflect the tempo at which genotypes, phenotypes, and species lineages are transformed over time but also offer valuable insight into the evolutionary processes involved ...
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Evolutionary rates not only reflect the tempo at which genotypes, phenotypes, and species lineages are transformed over time but also offer valuable insight into the evolutionary processes involved in divergence. For the last century and a half, biologists have been, and to a large degree still remain, steeped in the paradigm of slow and steady gradual evolutionary change. New findings and technologies are beginning to change this view as significant rate variations are seen in a large number of examples across and within all levels of biological organization. This introductory chapter provides a brief historical account and broad survey of recent findings on evolution rates and highlights examples demonstrating rapid and/or non-gradual evolutionary change. What do these exceptions to slow and gradual rates of evolution tell us about higher-level processes? How does such episodic change fit into our neo-Darwinian notions of gradualism? And what exciting prospects do we expect to discover in the future?Less
Evolutionary rates not only reflect the tempo at which genotypes, phenotypes, and species lineages are transformed over time but also offer valuable insight into the evolutionary processes involved in divergence. For the last century and a half, biologists have been, and to a large degree still remain, steeped in the paradigm of slow and steady gradual evolutionary change. New findings and technologies are beginning to change this view as significant rate variations are seen in a large number of examples across and within all levels of biological organization. This introductory chapter provides a brief historical account and broad survey of recent findings on evolution rates and highlights examples demonstrating rapid and/or non-gradual evolutionary change. What do these exceptions to slow and gradual rates of evolution tell us about higher-level processes? How does such episodic change fit into our neo-Darwinian notions of gradualism? And what exciting prospects do we expect to discover in the future?
Glenn-Peter Sætre and Mark Ravinet
- Published in print:
- 2019
- Published Online:
- July 2019
- ISBN:
- 9780198830917
- eISBN:
- 9780191868993
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780198830917.001.0001
- Subject:
- Biology, Evolutionary Biology / Genetics, Biomathematics / Statistics and Data Analysis / Complexity Studies
Evolutionary genetics is the study of how genetic variation leads to evolutionary change. With the recent explosion in the availability of whole genome sequence data, vast quantities of genetic data ...
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Evolutionary genetics is the study of how genetic variation leads to evolutionary change. With the recent explosion in the availability of whole genome sequence data, vast quantities of genetic data are being generated at an ever-increasing pace with the result that programming has become an essential tool for researchers. Most importantly, a thorough understanding of evolutionary principles is essential for making sense of this genetic data. This up-to-date textbook covers all the major components of modern evolutionary genetics, carefully explaining fundamental processes such as mutation, natural selection, genetic drift, and speciation, together with their consequences. In addition to the text, study questions are provided to motivate the reader to think and reflect on the concepts in each chapter. Practical experience is essential when it comes to developing an understanding of how to use genetic data to analyze and address interesting questions in the life sciences and how to interpret results in meaningful ways. Throughout the book, a series of online, computer-based tutorials serves as an introduction to programming and analysis of evolutionary genetic data centered on the R programming language, which stands out as an ideal all-purpose platform to handle and analyze such data. The book and its online materials take full advantage of the authors’ own experience in working in a post-genomic revolution world, and introduce readers to the plethora of molecular and analytical methods that have only recently become available.Less
Evolutionary genetics is the study of how genetic variation leads to evolutionary change. With the recent explosion in the availability of whole genome sequence data, vast quantities of genetic data are being generated at an ever-increasing pace with the result that programming has become an essential tool for researchers. Most importantly, a thorough understanding of evolutionary principles is essential for making sense of this genetic data. This up-to-date textbook covers all the major components of modern evolutionary genetics, carefully explaining fundamental processes such as mutation, natural selection, genetic drift, and speciation, together with their consequences. In addition to the text, study questions are provided to motivate the reader to think and reflect on the concepts in each chapter. Practical experience is essential when it comes to developing an understanding of how to use genetic data to analyze and address interesting questions in the life sciences and how to interpret results in meaningful ways. Throughout the book, a series of online, computer-based tutorials serves as an introduction to programming and analysis of evolutionary genetic data centered on the R programming language, which stands out as an ideal all-purpose platform to handle and analyze such data. The book and its online materials take full advantage of the authors’ own experience in working in a post-genomic revolution world, and introduce readers to the plethora of molecular and analytical methods that have only recently become available.
