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My summers at Saint Michael's College are the time that I plan new courses, reinvigorate my research program, and catch up on my science fiction reading. I spent part of this summer developing a new undergraduate course on genomics and bioinformatics by perusing several recently published texts in this area. My search for an appropriate undergraduate genomics text led me to a recently published book entitled A Primer of Genome Science, by North Carolina State University professors Greg Gibson and Spencer Muse. Both authors are well qualified to write this text, for their research interests involve genomics and span multiple disciplines. Gibson is a developmental biologist who works with Drosophila, and his research incorporates molecular biology, genetics, and genomics. Muse, a geneticist and statistician, represents the next generation of quantitative biologists who are part geneticist, statistician, programmer, and molecular biologist.

The postgenomic era has sparked a cultural and intellectual revolution among biologists and is embodied by a shift from linear thinking to a systems approach in molecular biology, biochemistry, and genetics. The questions we are asking ourselves are, What is this new field, how did it evolve, and how does it differ from molecular biology on steroids? Although this book does not answer these questions, it will provide you with an up-to-date introduction to the tools of the genomicist.

Perhaps understanding any new field begins by defining the language, and Muse and Gibson do a wonderful job of introducing genomics vocabulary. If you continue to confuse words like “phred” and “phrap” or if you haven't yet learned them, then this text will be of use to you. In addition to defining the unique terminology of this new field, the text also contains a tour de force of emerging technologies, molecular biology techniques, sequence analysis tools, and information about useful databases and Web sites. The authors have clearly made a concerted effort to be comprehensive in their summary and touch upon topics such as shotgun sequencing, library construction, microarrays, SAGE, SNPs, and two-hybrid screens, just to name a few. This thorough coverage also applies to the current databases and sequencing projects. I was pleased to see that less publicized projects, such as those on grasses and legumes, are presented in addition to the yeast, fruitfly, worm, and human genome projects.

The authors cast a wide net in defining the field of genomics and include topics such as proteomics and transcriptome analysis. The text is therefore remarkably comprehensive and organized given its length, covering most model organisms and many new and emerging techniques. Broad coverage in such a short text requires that all explanations be brief. I found the brevity of the explanations to be a plus, for the authors convey the information without overwhelming the reader. The text is roughly organized along the lines of “the central dogma”: genome sequencing projects, transcriptome analyses, proteomics, and functional and integrative genomics. Furthermore, the text reads well, and each individual section is presented in a logical progression: principles, techniques, uses, databases, and limitations of the technology. The format makes the information readily accessible and lends itself well to use as a quick reference book, particularly for molecular biology and biochemistry labs that are trying to integrate genomic technologies into their research. I particularly appreciated the one- and two-page math boxes that explain the principles behind many of the commonly used algorithms. Topics such as hidden Markov models, pairwise sequence alignments, phylogenetics, and clustering methods are covered in these sections. Finally, illustrations and color figures, from simple sequence alignments to hierarchical clustering of microarray data, successfully complement the text.

The target audience of this introductory text is advanced undergraduates and early graduate students. While this text does a good job presenting the tools of the trade for this audience, I was hoping that more attention would be given to asking and answering biological questions within the field. Because understanding the text requires literacy in molecular biology, I would be hesitant about adopting it as the sole text for an advanced undergraduate course. For graduate students, it lacks the depth to be the basis of an entire genomics course but could be effectively used as a reference or supplemental text. A Primer of Genome Science will be most useful to those who are already primed, but it is a useful resource, nevertheless.

The authors dedicate much of their writing to explaining standard molecular biology techniques as well as new technologies, and both sections are well reviewed. My only concern is that many standard molecular biology techniques are presented as recently developed genomic tools. The authors miss an opportunity to convey how established approaches and new approaches have been integrated into a new discipline. This text fails to illustrate that the genomics revolution is not only the technologies but also the way we view our field as a result of the technologies. For example, standard molecular biology techniques are presented as new science simply because they are being used on a larger scale. The field of genomics is not solely about the scale of experiments; rather, the cultural revolution of genomics is that molecular biologists and biochemists have been brought into the realm of systems biology. Despite this pedagogical oversight, I am glad I have a copy of the text in my lab and on my bioinformatics workstation. I foresee using it whenever I need a refresher on a database, algorithm, sequencing project, or molecular biology technique.

MARK LUBKOWITZ "GENOMICS 2002: GETTING PRIMED," BioScience 53(3), 290-291, (1 March 2003).[0290:GGP]2.0.CO;2
Published: 1 March 2003

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