At a time when much of human genetics research seems to be driven towards the hypothesis-free acquisition and exploratory analysis of high-throughput ‘-omics’ data, why bother with a new book on population genetics? The answer is very simple. Over the last decade, our Weld has undoubtedly undergone a change of paradigm, moving from the quest for Mendelian disease genes to unravelling the genetic causes of multi-factorial, so-called ‘complex’, disorders. However, since this research is no longer familybased but rather population-based, a reasonable understanding of population genetics principles has become a sine qua non for the planning, execution or interpretation of gene mapping experiments to be both sensible and successful. Unfortunately, the teaching of population genetics is often not accorded the central position it deserves in human genetics curricula. Matthew Hamilton’s book is a selfdeclared attempt to help to close this gap. The structure and design of the book as well as the style of writing are clearly targeted at post-graduate students in biology or related Welds, although the book may equally well function as a refresher for experienced human geneticists who wish to re-visit population genetics. However, as Hamilton rightly reminds us in the preface to his book, “population genetics is built on basic mathematics” which means that, without a solid background in mathematics and a natural love of numbers and formulae, even this book will be hard to take in for many readers. The most catching aspect of Hamilton’s book is its extremely well thought-out structure and pedagogical
M. Krawczak (&) Institute of Medical Informatics and Statistics, Christian Albrechts University of Kiel, Brunswiker Straße 10, 24105 Kiel, Germany e-mail: [email protected]
concept. All sections are well motivated in the respective introduction and all chapters have reviews at the end. A large number of problems have been interspersed throughout the text for students to work on, and the solutions are provided at the end of each chapter. A very interesting and novel feature is the use of so-called ‘interact boxes’, which are essentially links to interactive learning and simulation software available on the internet. These programs can be reached through the internet site that the publishers set up especially for this book. As the author makes very clear in his preface, many of these programmes have been produced by scientists and not by professional computer programmers, so their emphasis has simply been on functioning rather than on user-friendliness or fancy design. PopGene S2, e.g., the most frequently referenced software, was only available for download as a beta version at the time of writing this review. This notwithstanding the book beneWts greatly from its inspired didactical concept. ‘Population Genetics’ is organized into 11 chapters plus an Appendix with some statistical background and further reading. Chapter 1 provides an interesting introduction to population genetics thinking and sets the stage for what follows. Chapter 2 is essentially centred on the Hardy–Weinberg equilibrium and shows how deviations from this basic population genetic principle may provide interesting scientiWc insights. Chapters 3–5 give an astute account of the evolution of neutral genetic variation in diVerent types of populations. Starting from an introduction to the idea of genetic drift, models of gene genealogy, population structure and gene Xow are developed before the inXuence of mutations upon the genetic structures of populations is highlighted in Chapter 5. Selection is only introduced comparatively late in the book (Chapter 6) but receives a very detailed and knowledgeable treatment, including concepts of frequency- and density-dependent Wtness in Chapter 7.
Chapter 8 is devoted to molecular evolution, introducing the neutral theory and the molecular clock hypothesis (if you always wanted to know what Tajima’s D is about, this is the place for you to look). After two chapters on the evolution of quantitative traits (9) and the Mendelian basis of their variation (10), the book closes with a summary of historical and synthetic topics in Chapter 11. This part highlights the historical controversies in population genetics (between the classical and the balanced hypotheses) and gives a decent account of the shifting balance theory of Sewall Wright. If there is anything to criticise in Hamilton’s book, it is the occasionally imbalanced treatment of mathematical issues. In Chapter 3, e.g., the author takes several paragraphs to introduce the binomial distribution (a concept that should be familiar to most undergraduate students after high school), but then devotes an almost similar amount of space to the derivation of the diVusion equation, a concept
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that is challenging even for mathematics students. Another minor drawback (most likely outside the author’s sphere of responsibility) is the book’s limitation to two-colour print, which impedes the informativity and clarity of some of the Wgures. One unfortunate example is a photograph of beakers Wlled with micro-centrifuge tubes, meant to illustrate genetic drift, which all look grey in the main text Wgure and equally blue-whitish in the (single page) multicolour inset at the centre of the book. In summary, Matthew Hamilton’s ‘Population Genetics’ is a nice addition to the list of concise guides to population genetics, which it somehow supersedes by its elaborate pedagogical concept and interactive learning capabilities. The book is a good basis for teaching, a useful guide for students, and a nice companion for all those human geneticists who wish to learn a little bit more about the theoretical basis of their Weld of research.