- Email: [email protected]
New York, USA, 2000, xiv + 333 pages (hardback) $75; (paperback) $35.00
MOLECULAR PHYLOGENETICS AND EVOLUTION Molecular Phylogenetics and Evolution 25 (2002) 569–570 www.academicpress.com
Book review Molecular evolution and phylogenetics, Masatoshi Nei and Sudhir Kumar. Oxford University Press, Oxford, England/New York, USA, 2000, xiv + 333 pages (hardback) $75; (paperback) $35.00 Consisting of 14 chapters and four appendices, ‘Molecular Evolution and Phylogenetics’ is a monograph that describes the most popular, useful and currently used statistical methods of data analysis for studying molecular evolution, and illustrates their applications through actual examples. However, this description is somewhat misleading, since this work is certainly more than a simple ‘cookbook’ of recipes for sequence data analysis in molecular evolutionary studies. The authors emphatically differentiated the purpose of this book from that of a previous commendable work, ‘Molecular Evolutionary Genetics’ (Nei, 1987). However, even the beginning students of molecular evolution will find enough background material in this text to understand the framework of the suggested techniques of molecular data analysis, so that the methods described do not appear to be imposed upon the readers simply for the sake of their utility and/or popularity. Thus, topics such as molecular basis of evolution (chapter 1), different types of changes that may occur in DNA sequences (chapters 2 and 3), and detailed discussion of phylogenetic tree reconstruction from sequence data (chapters 5–10) have a certain flavor of ‘framework,’ and several of these methods are truly based on ‘interdisciplinary’ principles. Mathematical models of data analyses are not derived, but some of them are described in sufficient detail (see e.g., chapter 6, section 6.4; chapter 8, section 8.1; chapter 10, section 10.2; chapter 13, section 13.2), to make the uninitiated readers aware of the underlying assumptions of these data analysis methods. In this sense, this volume perfectly serves the purpose of being a true instructional companion of the authors’ free computer software MEGA2 (http://www.megasoftware.net) (Kumar et al., 2000) for conducting molecular evolutionary genetic analyses of sequence and allele frequency data. Since the word ‘phylogenetics’ appears in the title of the book, it is not surprising that discussions on phylogenetic tree reconstruction methods received more than one-third of the attention (6 of the 14 chapters are on this subject). The authors justified this with the rationale that recent advances of recombinant DNA
technologies have helped this objective (i.e., reconstruction of evolutionary history of organisms) of studying evolution at a molecular level more effectively than understanding the mechanism of evolution. Furthermore, accompanied by the advances of computational biology electronic tools, refinements of phylogenetic analysis tools have occurred at a faster pace during the last decade. For these reasons, the somewhat unbalanced contents of this volume should not be viewed as a criticism. It simply reflects the state of art of the discipline of molecular evolutionary studies. Nonetheless, it should be noted that the advances in recombinant DNA technology have also opened other uses of the DNA/RNA sequence data, and some of these certainly meet the need of examining the issues of the mechanism of evolutionary changes through analyses of such data. A few of such methods are briefly addressed (see e.g., section 12.6, discussing methods of detecting effects of natural selection), but there are certainly others (e.g., detecting functional role of domains of sequence data, Gu, 1999; evolutionary changes affecting gene expression, Holstege et al., 1998; and estimation of the age of mutations, Slatkin and Rannala, 1997), which deserved attention for the purpose of understanding the consequences of different mechanisms of evolutionary changes affecting the current make up of genomes that are fully sequenced. Unarguably, the goal of this book is to focus on the study of log-term evolution, but the composition of DNA sequence plays a role in answering several biomedical questions such as localization of genes underlying complex phenotypes, including that of the role of gene–gene interactions on phenotypic variation. Also of importance is to know the origin and spread of mutations controlling specific monogenic diseases such as cystic fibrosis (Bertranpetit and Calafell, 1996), and resistance to AIDS progression after HIV-I infection (Stephens et al., 1998), for which molecular evolutionary models have been successfully used in recent studies. Likewise, the subject of linkage disequilibrium is not discussed, while this has become a popular tool of utilizing DNA sequence variation for fine mapping of genes underlying phenotypes, or complex diseases (Daly et al., 2001). Indeed, use of such tools in conjunction with reasonable models of mutations in interpreting fulllength genome sequence data have given indications that at certain regions of the genome, genetic variation can-
1055-7903/02/$ - see front matter Ó 2002 Elsevier Science (USA). All rights reserved. PII: S 1 0 5 5 - 7 9 0 3 ( 0 2 ) 0 0 2 4 5 - 2
570
Book review / Molecular Phylogenetics and Evolution 25 (2002) 569–570
not be explained without invoking natural selection (Venter et al., 2001). Thus, in the context of understanding mechanisms of evolution, omission of these topics may reflect a deficiency of this volume. To some extent the absence of these topics reflects the authors’ personal research interest, and as a consequence the use of this volume may be restricted to a somewhat narrower audience, including the readers of this journal. Nevertheless, I recommend that instructors who teach utility of molecular tools for genetic epidemiology and genome analysis should cover the contents of this book to expose students to the techniques of effective utilization of DNA sequence data. On a more minor note, other relatively benign flaws of this book include a somewhat incomplete description of the mutation models applicable to repeat polymorphism (pp. 246–248). Only the infinite-allele and (singlestep) stepwise mutation models are discussed; yet, there is sufficient direct as well as indirect evidence available now that suggest that other mutation models are necessary for at least some of these loci (Jin et al., 1996; Kimmel et al., 1996). For some repeat loci, the probabilities of mutation, causing allele size changes, are dependent on the size of the progenitor alleles (Jin et al., 1996), and even when the mutations occur in a stepwise fashion, allele size changes often involve more than a single step change (see e.g., Deka et al., 1999). As a consequence, expected gene diversity at such loci may not equal the one represented by the simple formula (12.40, p. 247). Also, there is evidence that at some of these loci, more than one mutational process may be conjointly occurring governing the mode and tempo of evolution (Kruglyak et al., 1998). Another relatively inconsequential but amusing typographical error is the mistaken middle initial of R.E. Ferrell in the citation list (p. 306), who was a lone-time colleague of the senior author at Houston, Texas. These comments notwithstanding, I highly recommend this book to the beginning as well as advanced researchers of molecular evolution. It is lucidly written, and it is not unnecessarily cluttered with methods that are relatively less efficient and less useful. This quality places ‘Molecular Evolution and Phylogenetics’ in a different class of books describing genetic data analysis methods than some others available in related fields (e.g., Weir, 1996). In this sense, the contents and their presentation, truly meet the objective implied in the quotation of Efron and Tibashirani (1993) that the authors used in the preface of the volume. Every practitioner who employs computer tools for analyzing molecular data will find this volume useful as a reference source to understand the basis of the analytical methods underlying such data analysis methods. I, for myself,
find that my bookshelf place is well spent with it, and I hope that like other widely used books of my research group, it does not grow legs to walk away from my library. The authors should be commended for their work and efforts to produce this soon to be frequently cited monograph. References Bertranpetit, J., Calafell, F., 1996. Genetic and geographical variability in cystic fibrosis: evolutionary considerations. Ciba Foundation Symp. 197, 97–114. Daly, M.J., Rioux, J.D., Schaffner, S.F., Hudosn, T.J., Lander, E.S., 2001. High-resolution haplotype structure in the human genome. Nat. Genet. 29, 229–232. Deka, R., Guangyun, S., Wiest, J., Smelser, D., Chunhua, S., Zhong, Y., Chakraborty, R., 1999. Patterns of instability of expanded, C.A.G. repeats at the, E.R.D.A1 locus in general populations. Am. J. Hum. Genet. 65, 192–198. Efron, B., Tibashirani, R.J., 1993. An Introduction to the Bootstrap. Chapman & Hill, New York. Gu, X., 1999. Statistical methods for testing functional divergence after gene duplication. Mol. Biol. Evol. 16, 1664–1674. Holstege, F.C.P., Jennings, E.G., Wyrick, J.J., et al., 1998. Dissecting the regulatory circuitry of a eukaryotic genome. Cell 95, 717–728. Jin, L., Macaubas, C., Hallmayer, J., Kimura, A., Mignot, E., 1996. Mutation rate varies among alleles at a microsatellite locus: phylogenetic evidence. Proc. Natl. Acd. Sci. USA 93, 15285–15288. Kimmel, M., Chakraborty, R., Stivers, D.N., Deka, R., 1996. Dynamics of repeat polymorphisms under a forward-backward mutation model: within and between-population variability at microsatellite loci. Genetics 143, 549–555. Kumar, S., Tamura, K., Jakobsen, I., Nei, M., 2000. MEGA: Molecular Evolutionary Genetics Analysis, ver. 2. Pennsylvania State University, University Park, and Arizona State University, Tempe (http://www.megasoftware.net). Kruglyak, S., Durrett, R.T., Schug, M.D., Aquadro, C.F., 1998. Equilibrium distributions of microsatellite repeat length resulting from a balance between splippage events and point mutations. Proc. Natl. Acad. Sci. USA 95, 10774–10778. Nei, M., 1987. Molecular Evolutionary Genetics. Columbia University Press, New York. Slatkin, M., Rannala, B., 1997. The sampling distribution of diseaseassociated alleles. Genetics 147, 1855–1861. Stephens, J.C., Reich, D.E., Goldstein, D.B., et al., 1998. Dating the origin of the, C.C.R.5-Delta32 AIDS-resistance allele by the coalescence of haplotypes. Am. J. Hum. Genet. 62, 1507–1515. Venter, J.C., Adams, M.D., Myers, E.W., et al., 2001. The sequence of the human genome. Science 291, 1304–1351. Weir, B.S., 1996. Genetic Data Analysis—II. Sinauer Associates, Sunderland, MA.
Ranajit Chakraborty Center for Genome Information Department of Environmental Health University of Cincinnati Cincinnati, OH 45267 USA E-mail address: [email protected]
Book review Molecular evolution and phylogenetics, Masatoshi Nei and Sudhir Kumar. Oxford University Press, Oxford, England/New York, USA, 2000, xiv + 333 pages (hardback) $75; (paperback) $35.00 Consisting of 14 chapters and four appendices, ‘Molecular Evolution and Phylogenetics’ is a monograph that describes the most popular, useful and currently used statistical methods of data analysis for studying molecular evolution, and illustrates their applications through actual examples. However, this description is somewhat misleading, since this work is certainly more than a simple ‘cookbook’ of recipes for sequence data analysis in molecular evolutionary studies. The authors emphatically differentiated the purpose of this book from that of a previous commendable work, ‘Molecular Evolutionary Genetics’ (Nei, 1987). However, even the beginning students of molecular evolution will find enough background material in this text to understand the framework of the suggested techniques of molecular data analysis, so that the methods described do not appear to be imposed upon the readers simply for the sake of their utility and/or popularity. Thus, topics such as molecular basis of evolution (chapter 1), different types of changes that may occur in DNA sequences (chapters 2 and 3), and detailed discussion of phylogenetic tree reconstruction from sequence data (chapters 5–10) have a certain flavor of ‘framework,’ and several of these methods are truly based on ‘interdisciplinary’ principles. Mathematical models of data analyses are not derived, but some of them are described in sufficient detail (see e.g., chapter 6, section 6.4; chapter 8, section 8.1; chapter 10, section 10.2; chapter 13, section 13.2), to make the uninitiated readers aware of the underlying assumptions of these data analysis methods. In this sense, this volume perfectly serves the purpose of being a true instructional companion of the authors’ free computer software MEGA2 (http://www.megasoftware.net) (Kumar et al., 2000) for conducting molecular evolutionary genetic analyses of sequence and allele frequency data. Since the word ‘phylogenetics’ appears in the title of the book, it is not surprising that discussions on phylogenetic tree reconstruction methods received more than one-third of the attention (6 of the 14 chapters are on this subject). The authors justified this with the rationale that recent advances of recombinant DNA
technologies have helped this objective (i.e., reconstruction of evolutionary history of organisms) of studying evolution at a molecular level more effectively than understanding the mechanism of evolution. Furthermore, accompanied by the advances of computational biology electronic tools, refinements of phylogenetic analysis tools have occurred at a faster pace during the last decade. For these reasons, the somewhat unbalanced contents of this volume should not be viewed as a criticism. It simply reflects the state of art of the discipline of molecular evolutionary studies. Nonetheless, it should be noted that the advances in recombinant DNA technology have also opened other uses of the DNA/RNA sequence data, and some of these certainly meet the need of examining the issues of the mechanism of evolutionary changes through analyses of such data. A few of such methods are briefly addressed (see e.g., section 12.6, discussing methods of detecting effects of natural selection), but there are certainly others (e.g., detecting functional role of domains of sequence data, Gu, 1999; evolutionary changes affecting gene expression, Holstege et al., 1998; and estimation of the age of mutations, Slatkin and Rannala, 1997), which deserved attention for the purpose of understanding the consequences of different mechanisms of evolutionary changes affecting the current make up of genomes that are fully sequenced. Unarguably, the goal of this book is to focus on the study of log-term evolution, but the composition of DNA sequence plays a role in answering several biomedical questions such as localization of genes underlying complex phenotypes, including that of the role of gene–gene interactions on phenotypic variation. Also of importance is to know the origin and spread of mutations controlling specific monogenic diseases such as cystic fibrosis (Bertranpetit and Calafell, 1996), and resistance to AIDS progression after HIV-I infection (Stephens et al., 1998), for which molecular evolutionary models have been successfully used in recent studies. Likewise, the subject of linkage disequilibrium is not discussed, while this has become a popular tool of utilizing DNA sequence variation for fine mapping of genes underlying phenotypes, or complex diseases (Daly et al., 2001). Indeed, use of such tools in conjunction with reasonable models of mutations in interpreting fulllength genome sequence data have given indications that at certain regions of the genome, genetic variation can-
1055-7903/02/$ - see front matter Ó 2002 Elsevier Science (USA). All rights reserved. PII: S 1 0 5 5 - 7 9 0 3 ( 0 2 ) 0 0 2 4 5 - 2
570
Book review / Molecular Phylogenetics and Evolution 25 (2002) 569–570
not be explained without invoking natural selection (Venter et al., 2001). Thus, in the context of understanding mechanisms of evolution, omission of these topics may reflect a deficiency of this volume. To some extent the absence of these topics reflects the authors’ personal research interest, and as a consequence the use of this volume may be restricted to a somewhat narrower audience, including the readers of this journal. Nevertheless, I recommend that instructors who teach utility of molecular tools for genetic epidemiology and genome analysis should cover the contents of this book to expose students to the techniques of effective utilization of DNA sequence data. On a more minor note, other relatively benign flaws of this book include a somewhat incomplete description of the mutation models applicable to repeat polymorphism (pp. 246–248). Only the infinite-allele and (singlestep) stepwise mutation models are discussed; yet, there is sufficient direct as well as indirect evidence available now that suggest that other mutation models are necessary for at least some of these loci (Jin et al., 1996; Kimmel et al., 1996). For some repeat loci, the probabilities of mutation, causing allele size changes, are dependent on the size of the progenitor alleles (Jin et al., 1996), and even when the mutations occur in a stepwise fashion, allele size changes often involve more than a single step change (see e.g., Deka et al., 1999). As a consequence, expected gene diversity at such loci may not equal the one represented by the simple formula (12.40, p. 247). Also, there is evidence that at some of these loci, more than one mutational process may be conjointly occurring governing the mode and tempo of evolution (Kruglyak et al., 1998). Another relatively inconsequential but amusing typographical error is the mistaken middle initial of R.E. Ferrell in the citation list (p. 306), who was a lone-time colleague of the senior author at Houston, Texas. These comments notwithstanding, I highly recommend this book to the beginning as well as advanced researchers of molecular evolution. It is lucidly written, and it is not unnecessarily cluttered with methods that are relatively less efficient and less useful. This quality places ‘Molecular Evolution and Phylogenetics’ in a different class of books describing genetic data analysis methods than some others available in related fields (e.g., Weir, 1996). In this sense, the contents and their presentation, truly meet the objective implied in the quotation of Efron and Tibashirani (1993) that the authors used in the preface of the volume. Every practitioner who employs computer tools for analyzing molecular data will find this volume useful as a reference source to understand the basis of the analytical methods underlying such data analysis methods. I, for myself,
find that my bookshelf place is well spent with it, and I hope that like other widely used books of my research group, it does not grow legs to walk away from my library. The authors should be commended for their work and efforts to produce this soon to be frequently cited monograph. References Bertranpetit, J., Calafell, F., 1996. Genetic and geographical variability in cystic fibrosis: evolutionary considerations. Ciba Foundation Symp. 197, 97–114. Daly, M.J., Rioux, J.D., Schaffner, S.F., Hudosn, T.J., Lander, E.S., 2001. High-resolution haplotype structure in the human genome. Nat. Genet. 29, 229–232. Deka, R., Guangyun, S., Wiest, J., Smelser, D., Chunhua, S., Zhong, Y., Chakraborty, R., 1999. Patterns of instability of expanded, C.A.G. repeats at the, E.R.D.A1 locus in general populations. Am. J. Hum. Genet. 65, 192–198. Efron, B., Tibashirani, R.J., 1993. An Introduction to the Bootstrap. Chapman & Hill, New York. Gu, X., 1999. Statistical methods for testing functional divergence after gene duplication. Mol. Biol. Evol. 16, 1664–1674. Holstege, F.C.P., Jennings, E.G., Wyrick, J.J., et al., 1998. Dissecting the regulatory circuitry of a eukaryotic genome. Cell 95, 717–728. Jin, L., Macaubas, C., Hallmayer, J., Kimura, A., Mignot, E., 1996. Mutation rate varies among alleles at a microsatellite locus: phylogenetic evidence. Proc. Natl. Acd. Sci. USA 93, 15285–15288. Kimmel, M., Chakraborty, R., Stivers, D.N., Deka, R., 1996. Dynamics of repeat polymorphisms under a forward-backward mutation model: within and between-population variability at microsatellite loci. Genetics 143, 549–555. Kumar, S., Tamura, K., Jakobsen, I., Nei, M., 2000. MEGA: Molecular Evolutionary Genetics Analysis, ver. 2. Pennsylvania State University, University Park, and Arizona State University, Tempe (http://www.megasoftware.net). Kruglyak, S., Durrett, R.T., Schug, M.D., Aquadro, C.F., 1998. Equilibrium distributions of microsatellite repeat length resulting from a balance between splippage events and point mutations. Proc. Natl. Acad. Sci. USA 95, 10774–10778. Nei, M., 1987. Molecular Evolutionary Genetics. Columbia University Press, New York. Slatkin, M., Rannala, B., 1997. The sampling distribution of diseaseassociated alleles. Genetics 147, 1855–1861. Stephens, J.C., Reich, D.E., Goldstein, D.B., et al., 1998. Dating the origin of the, C.C.R.5-Delta32 AIDS-resistance allele by the coalescence of haplotypes. Am. J. Hum. Genet. 62, 1507–1515. Venter, J.C., Adams, M.D., Myers, E.W., et al., 2001. The sequence of the human genome. Science 291, 1304–1351. Weir, B.S., 1996. Genetic Data Analysis—II. Sinauer Associates, Sunderland, MA.
Ranajit Chakraborty Center for Genome Information Department of Environmental Health University of Cincinnati Cincinnati, OH 45267 USA E-mail address: [email protected]