Population Genomics with R

Emmanuel Paradis

• Publisher: Chapman and Hall/CRC
• Year: 2020
• eBook ISBN: 9780429882425
• Edition: 1
• Topic: Mathematics
• Subtopic: Probability & Statistics
• Index: Mathematics

Population Genomics With R presents a multidisciplinary approach to the analysis of population genomics. The methods treated cover a large number of topics from traditional population genetics to large-scale genomics with high-throughput sequencing data. Several dozen R packages are examined and integrated to provide a coherent software environment with a wide range of computational, statistical, and graphical tools. Small examples are used to illustrate the basics and published data are used as case studies. Readers are expected to have a basic knowledge of biology, genetics, and statistical inference methods. Graduate students and post-doctorate researchers will find resources to analyze their population genetic and genomic data as well as help them design new studies.

The first four chapters review the basics of population genomics, data acquisition, and the use of R to store and manipulate genomic data. Chapter 5 treats the exploration of genomic data, an important issue when analysing large data sets. The other five chapters cover linkage disequilibrium, population genomic structure, geographical structure, past demographic events, and natural selection. These chapters include supervised and unsupervised methods, admixture analysis, an in-depth treatment of multivariate methods, and advice on how to handle GIS data. The analysis of natural selection, a traditional issue in evolutionary biology, has known a revival with modern population genomic data. All chapters include exercises. Supplemental materials are available on-line (http://ape-package.ird.fr/PGR.html).

1

Introduction

1.1 Heredity, Genetics, and Genomics

One of the greatest achievements of biology during the twentieth century was to discover the mechanisms of heredity. One can hardly imagine all the theories formulated during many centuries before this discovery. Today, the double helix of DNA structure is an icon of science, and DNA has now a wide range of technological and commercial applications.

Heredity and its associated concepts are deeply rooted in the history of mankind. The emergence of agriculture in different parts of the world between 10,000 and 5000 years ago clearly interacted with knowledge on the heredity of some plants and animals. During thousands of years, breeders have observed the consequences of heredity on the domesticated forms of these species. In the nineteenth century, the scientific investigation of heredity took a significant turn with the generalization of microscopic observations, the formulation of the laws of heredity by Mendel, and Miescher’s discovery of “nuclein,” later renamed nucleic acids. An often overlooked feature of the history of genetics is that it took almost eight decades to demonstrate that DNA is the support of heredity, and even the brillant experiments by Avery and his colleagues were not convincing for some geneticists who thought that heredity was coded by proteins [52]. Therefore, population genetics originated well before the discovery of the physical support of heredity.

Historical Landmarks: Heredity, Genetics, and Genomics

1866: Mendel publishes his laws of heredity [184].

1869: Miescher discovers DNA [47].

1944: Avery et al. demonstrate that DNA is the support of heredity [10].

1953: Watson et al. discover the double helix structure of DNA [290].

1961: Crick et al. decipher the genetic code [44].

1973: Gilbert and Maxam publish the first DNA sequencing data [95].

1984: Discovery of microsatellites [295].

1996: First high-throughput sequencing technology [237].

2001: First human genome published [127].

2010: Completion of the first phase of the 1000 Genomes Project [270].

During the twentieth century, the methods used by biologists to study heredity and later DNA progressively increased in power (see Chap. 2). The growth of high-throughput sequencing technologies has been a very significant factor in the development of population genomics. Genomics has taken considerable importance during the last decade as a scientific field and a subject of considerable societal interest. This development has also impacted the field of population genetics.

This book adopts the following definitions. Population genetics is the study of the variation in genotypes among individuals across space and time, including the forces behind this variation. Genomics is the study of the structure and functions of genomes. Population genomics is similar to population genetics but applied to a very large number of loci, usually across the whole genome of a species. Thus, population genomics can be seen as a “scaled-up” version of population genetics dealing with at least a large number of loci up to the whole genome of the species of interest [20].

Historical Landmarks: Population Genetics

1930: Publication of Fisher’s Genetical Theory of Natural Selection [77].

1949: Publication of Wright s paper on population genetic structure [303].

1955: Kimura’s paper on allele fixation under genetic drift [142].

1966: Empirical studies show the importance of molecular variation in natural populations [107, 160].

1982: Kingman publishes three founding papers on the coalescent [147].

2005: Publication of the sequentially Markov coalescent facilitating the analysis of genomic data with recombination [182].

1.2 Principles of Population Genomics

This section starts with some explanations on the units used in this book. The biological meanings of some terms used here (bases, double-stranded, … ) are explained in the following subsection.

1.2.1 Units

The basic unit of the genome is the base, the part of the nucleotide that is variable: its symbol is ‘b’. Genomes can be small or (very) big, thus it is common to use prefixes borrowed from the International System of Units to express the size of a genome or the length of a DNA sequence:

$\begin{array}{ll}\text{one kilobase}\hfill & =...\hfill \end{array}$

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Dedication
• Table of Contents
• Preface
• Symbol Description
• 1 Introduction
• 2 Data Acquisition
• 3 Genomic Data in R
• 4 Data Manipulation
• 5 Data Exploration and Summaries
• 6 Linkage Disequilibrium and Haplotype Structure
• 7 Population Genetic Structure
• 8 Geographical Structure
• 9 Past Demographic Events
• 10 Natural Selection
• A Installing R Packages
• B Compressing Large Sequence Files
• C Sampling of Alleles in a Population
• D Glossary
• Bibliography
• Index