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Introduction to evolutionary genomics
Saitou N., Springer Publishing Company, Incorporated, London, UK, 2013. 495 pp. Type: Book (978-1-447153-03-0)
Date Reviewed: Sep 25 2014

Evolutionary genomics is the study of genetic data with the intent to understand two main areas: how closely related are different species or individuals of a species, and how living things evolved over time, diverging from an assumed single ancestor into the diverse forms we observe today. More specifically, genetic data taken from the analysis of deoxyribonucleic acid (DNA), ribonucleic acid (RNA), amino acids, and so on is compared across different species. One can think of the field as solving a giant jigsaw puzzle. The pieces are the nucleotides extracted from the base molecules; the puzzle is determining how they are arranged, how they differ from one species to a related species, and how they have changed over generations.

As with many areas, the problem space grows exponentially with the number of objects being compared, causing researchers to search for simplifying assumptions and algorithms that balance accuracy against computational resource requirements needed to produce solutions. The present text provides an overview of the field for someone somewhat knowledgeable of the basics of genetics plus college freshman-level calculus and statistics. Network theory is also employed, explained as needed in the text.

Over millions of years, sequences of DNA can be modified by the insertion or deletion of sequences or the substitution of its fundamental chemical building blocks, nucleotides. That the various nucleotides involved can change with or without effecting change in an organism complicates the analysis, requiring statistical methods to make predictions. As species diverged, they retained common elements of nucleotides but with subtle differences, increasing the difficulty of making comparisons. Further, the genome of a single mammal, say, involves huge masses of data, requiring the use of databases. Many of these databases are available on the Internet. The complexity issue is addressed by use of algorithms that make simplifying assumptions to generate theoretical results that can be compared with real data and, of course, operate on real data.

The text is in three parts. Part 1 begins with a discussion of metabolism and mutation, and moves on from there to phylogeny, the evolutionary development of genes, individuals, and species. Tree networks (or graphs) are introduced as a way to describe the evolution over time of biological entities. Trees are also used to show genetic differences among two or more species. Following are chapters on neutral evolution, the theory that most mutations are selectively neutral and how natural selection operates.

In Part 2, the author discusses evolving genomes, beginning at the origin of life and proceeding from simple to complex organisms, culminating in a discussion of the human genome. Part 3 describes mathematical, algorithmic, and computational methods of evolutionary genomics. It begins with a description of how genomes are sequenced, that is, taken apart for analysis. It moves on to describe data collection, genomic databases, and the heart of the area, the comparison of sequences of nucleotides looking for similarities. This essentially is an optimization problem; a number of algorithms are presented, including the use of dynamic programming. This leads to a mathematical formulation of evolutionary distance, or how nucleotide sequences change with time. The following chapter describes tree and network building, showing various methods used to create phylogenetic trees that show evolutionary descent. Included here is a discussion and comparison of several methods.

The book concludes with a chapter on population genomics, a comparison of genomes of different groups, primarily humans. The goal is to identify distance in both time and phenotype among groups being compared. This can lead to estimates as to when the ancestral line between humans and chimpanzees diverged, or when certain human populations migrated from one part of the world to another.

When an author who is not a native English speaker writes in English, the publisher should ensure the book is edited to present correct English. Failing to do this is a disservice to both the author and the book’s readers. The publisher here is Springer, a number of whose books show this problem. The author has produced a fine work technically, but frequent English errors detract from it. I fault the publisher for poor editing, not the author. Here is an example sentence (page 217): “Eukaryotic viruses are relying most of metabolic pathways to their eukaryote host species,” which in my perception should read “Eukaryotic viruses rely mostly on the metabolic pathways of their eukaryote host species.” Similar corrections of English could be made on every page. That said, reading becomes easier with familiarity with the author’s writing style. In addition, there are a number, fortunately few, of nontrivial typographical errors, such as equation number references that clearly refer to different equations.

The author’s writing, although imperfect, is technically clear and precise. He provides voluminous references at the end of each chapter, sometimes over 100. The book provides a fine overview of evolutionary genomics, the processes and techniques used, and some of the results that have been achieved.

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Reviewer:  G. R. Mayforth Review #: CR142766 (1501-0038)
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Biology And Genetics (J.3 ... )
 
 
Graphs And Networks (E.1 ... )
 
 
Scientific Databases (H.2.8 ... )
 
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