Genomic and Personalized Medicine. Volume I & II

1480 Pages·80.002 MB·English

by  Huntington F. Willard, Ph.D., and Geoffrey S. Ginsburg, M.D., Ph.D. (Eds.)

T
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One
A
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Genomic Approaches to
Biology and Medicine

1
Principles of
Human
Genomics

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1. Organization, Variation and Expression of the Human Genome as
a Foundation of Genomic and Personalized Medicine
2. Concepts of Population Genomics
3. Genomic Approaches to Complex Disease
4. Human Health and Disease: Interaction Between the
Genome and the Environment
5. Epigenomics and Its Implications for Medicine
6. Systems Biology and the Emergence of Systems Medicine
CHAPTER
1
Organization, Variation and Expression
of the Human Genome as a
Foundation of Genomic and
Personalized Medicine
Huntington F. Willard
Variation in the human genome has long been the cor-
INTRODUCTION
nerstone of the fi eld of human genetics (see Box 1.1), and its
The genetic variation that can infl uence health and disease has study led to the establishment of the medical specialty of medi-
been a central, if not widely practiced, principle of medicine cal genetics (N ussbaum et al., 2007 ). A crucial set of connec-
for over a hundred years, since the prescient observations of the tions joining Mendel’s principles of heredity, Garrod’s concept
British physician Sir Archibald Garrod established the concept of chemical individuality, the practice of medicine and the
of “chemical individuality ” over a century ago ( Garrod, 1902 ). sequence of the genome came with Pauling’s discovery of the
What has limited broad application of this principle until now molecular basis of sickle cell anemia and the direct correspond-
has been the generally presumed rarity or special nature of clini- ence between an individual’s genetic make-up and the type
cal circumstances or conditions to which genetic variation was of hemoglobins present in that individual’s red cells ( Pauling
relevant – rare disorders such as Garrod’s alkaptonuria, inherited et al., 1949 ). The general nature and frequency of gene variants
conditions limited to specifi c populations such as sickle cell ane- in the human genome became apparent with the classic work in
mia, or specialized situations such as the role of ABO incompat- the 1960s on the incidence of polymorphic protein variants in
ibility in blood transfusion. Now, however, with the availability populations of healthy individuals ( Harris and Hopkinson, 1972;
of a “reference sequence ” of the human genome, with emerging Lewontin, 1967 ; reviewed in Harris, 1980 ).
appreciation of the extent of genome variation among differ- Calculations based on those protein polymorphism data – now
ent individuals, and with a growing understanding of the role of extended in a robust and comprehensive manner with the analysis
common, not just rare, variation in disease, we are poised to begin of variation on a genome scale – lead to the inescapable conclu-
to exploit the impact of that variation on human health on a sion that virtually every individual should be found to have his or
broad scale, in the context of genomic and personalized medicine. her own unique constitution of gene products, the implications
Genomic and Personalized Medicine, 2-vol set Copyright © 2009, Elsevier Inc.
by Willard & Ginsburg All rights reserved.
4
Introduction ■ 5
BOX 1.1 Genetics and Genomics
Throughout this and the many other chapters in this volume, the It is the paired combination of the genome and the epigenome that
terms “ genetics” and “genomics” are used repeatedly, both as nouns best characterize and determine one’s phenotype.
and in their adjectival forms. While these terms seem similar, they Medical genetics is the application of genetics to medicine with a
in fact describe quite distinct (though frequently overlapping) particular emphasis on inherited disease. Medical genetics is a broad
approaches in biology and in medicine. Having said that, there are and varied field, encompassing many different subfields, including
inconsistencies in the way the terms are used, even by those who clinical genetics, biochemical genetics, cytogenetics, molecular genet-
work in the field. To some, genetics is a subfield of genomics; to ics, the genetics of common diseases and genetic counseling. Medical
others, genomics is a subfield of genetics. Arguably, depending on genetics is one of 24 medical specialties recognized by The American
the perspective one has in mind, both may be right! Board of Medical Specialties, the preeminent medical organization
Here, we provide operational definitions to distinguish the vari- overseeing physician certification in the United States. As of 2007,
ous terms and the subfields of medicine to which they contribute. there were approximately 2300 board-certified medical geneticists in
The field of genetics is the scientific study of heredity and of the United States.
the genes that provide the physical, biological and conceptual bases Genetic medicine is a term sometimes used to refer to the appli-
for heredity and inheritance. To say that something – a trait, a dis- cation of genetic principles to the practice of medicine and thus
ease, a code or information – is “genetic” refers to its basis in genes overlaps medical genetics. However, genetic medicine is somewhat
and in DNA. broader, as it is not limited to the specialty of Medical Genetics but
Heredity refers to the familial phenomenon whereby traits is relevant to health professionals in many, if not all, specialties and
(including clinical traits) are transmitted from generation to gen- subspecialties. Both medical genetics and genetic medicine approach
eration, due to the transmission of genes from parent to child. A clinical care largely through consideration of individual genes and
disease that is said to be inherited or hereditary is certainly genetic; their effects on patients and their families.
however, not all genetic diseases are hereditary (witness cancer, By contrast, g enomic medicine refers to the use of large-scale
which is always a genetic disease, but is only occasionally an inher- genomic information and to consideration of the full extent of an
ited disease). individual’s genome, proteome, transcriptome, metabolome and/or
Genomics is the scientific study of a genome or genomes. A epigenome in the practice of medicine and medical decision-making.
genome is the complete DNA sequence, containing the entire The principles and approaches of genomic medicine are relevant
genetic information of a gamete, an individual, a population or well beyond the traditional purview of medical genetics and include,
a species. As such, it is a subfield of genetics when describing an as examples, gene expression profiling to characterize tumors or to
approach taken to study genes. The word “ genome” originated as define prognosis in cancer, genotyping variants in the set of genes
an analogy with the earlier term “ chromosome, ” referring to the involved in drug metabolism or action to determine an individual’s
physical entities (visible under the microscope) that carry genes correct therapeutic dosage, scanning the entire genome for millions
from one cell to its daughter cells or from one generation to the of variants that influence one’s susceptibility to disease, or analyzing
next. “ Genomics” gave birth to a series of other “-omics” that refer multiple protein biomarkers to monitor therapy and to provide pre-
to the comprehensive study of the full complement of genome dictive information in presymptomatic individuals.
products – for example, proteins (hence, proteomics), transcripts ( tran- Finally, p ersonalized medicine refers to a rapidly advancing field of
scriptomics) or metabolites ( metabolomics). The essential feature of the health care that is informed by each person’s unique clinical, genetic,
“ omes” is that they refer to the complete collection of genes or genomic and environmental information. The goals of personalized
their derivative proteins, transcripts or metabolites, not just to the medicine are to take advantage of a molecular understanding of dis-
study of individual entities. While formally the field of genomics ease to optimize preventive health care strategies and drug therapies
refers to the study of genomes (and hence, DNA) only, it some- while people are still well or at the earliest stages of disease. Because
times takes on the broader meaning of referring to any large-scale these factors are different for every person, the nature of disease, its
approach; the less specific term “genome sciences” is also sometimes onset, its course, and how it might respond to drug or other inter-
used to refer to all of the “ -omics” to connote global and compre- ventions are as individual as the people who have them. In order
hensive approaches to the study of biology and medicine. for personalized medicine to be used by health care providers and
By analogy with genetics and genomics, epigenetics andepigenom- their patients, these findings must be translated into precision diag-
ics refer to the study of factors that affect gene (or, more globally, nostic tests and targeted therapies. Since the overarching goal is to
genome) function, but without an accompanying change in genes optimize medical care and outcomes for each individual, treatments,
or the genome. As presented later in this chapter and others, some medication types and dosages, and/or prevention strategies may dif-
typical epigenetic factors involve changes in DNA methylation fer from person to person – resulting in unprecedented customiza-
or modifications to chromatin that change genome structure and tion of patient care.
hence influence gene expression even in the absence of changes in The principles underlying genomic and personalized medicine
the DNA sequence. The e pigenome is the comprehensive set of epi- and their applications to the practice of clinical medicine are pre-
genetic changes in a given individual, tissue, tumor or population. sented throughout the chapters that comprise this volume.
of which provide a conceptual foundation for what today we call the extent of human genome variation, both within and among
“personalized medicine ” as a new-age rediscovery of Garrod’s populations ( International HapMap Consortium, 2003, 2007 )
“chemical individuality.” Thus, with the availability of the human and within individual genomes (L evy et al., 2007; Wheeler et al.,
genome sequence (I nternational Human Genome Sequencing 2008), awareness of widespread human variation can begin to be
Consortium, 2001, 2004; Venter et al., 2001) and determination of applied generally to the exploration of common human disease.
6 CHAPTER 1 ■ Organization, Variation and Expression of the Human Genome as a Foundation of Genomic and Personalized Medicine
In this chapter, the organization, variation and expression TABLE 1.1 Characteristics of the human genomea
of the human genome is presented as a foundation for the many
chapters to follow on human genomics, on genome technology Length of the human genome (basepairs) 3,253,037,807
and informatics, on approaches in translational genomics and,
Number of known protein-coding genes 21,541
fi nally, on the principles of genomic and personalized medicine
as applied to specifi c diseases. Average gene density (genes/Mb)b 6.6
Number of non-coding RNA genes 4421
Number of SNPsb 13,022,900
THE HUMAN GENOME
The typical human genome consists of approximately 3 billion aFrom Ensembl v. 48 (accessed February 2008)
(3 (cid:4) 109 ) bp of DNA, divided among the 24 types of nuclear bMb(cid:5) megabasepairs; SNP (cid:5) single nucleotide polymorphism
chromosomes (22 autosomes, plus the sex chromosomes, X and
Y) and the much smaller mitochondrial chromosome (T ables
1.1, 1.2 ). The genome can be represented and evaluated in dif-
ferent ways, with different levels of resolution and degrees of TABLE 1.2 Variation among human chromosomesa
sensitivity, depending on the clinical need ( Figure 1.1 ).
Chromosome Mb Protein- Genes/ miRNA
Individual chromosomes can best be studied at metaphase coding genes Mb genes
in dividing cells, and karyotyping of patient chromosomes
1 247.25 2153 8.7 68
has been a valuable and routine clinical laboratory procedure
for decades (T rask, 2002) ; various staining or hybridization- 2 242.95 1315 5.4 60
based analytical techniques have the ability to detect chromo-
3 199.50 1105 5.5 57
some abnormalities ranging from an extra or missing whole
chromosome (aneuploidy), to translocations or rearrangements 4 191.27 786 4.1 42
involving just a portion of a chromosome(s), to deletions or
5 180.86 894 4.9 46
duplications involving as little as perhaps a megabase (106 bp;
6 170.90 1109 6.5 36
Mb) of DNA.
More recent technologies involving overlapping sets (called 7 158.82 1008 6.3 43
“ tiling paths” ) of isolated segments of the genome arrayed on
8 146.27 743 5.1 38
microscope slides have provided vastly improved resolution
and precision capable of evaluating in a rapid and comprehen- 9 140.27 904 6.4 40
sive way the proper dosage (and in some cases the organization)
10 135.37 819 6.1 35
of the corresponding DNA segments within an individual’s
genome (F igure 1.1b) (see Chapter 9). The ultimate resolution, 11 134.45 1368 10.2 37
of course, comes from direct sequence analysis, and a number 12 132.35 1069 8.1 43
of new technologies have reduced the cost and improved the
13 114.14 356 3.1 23
throughput of sequencing individual genomes, facilitating com-
parisons with the reference human genome sequence and ena- 14 106.37 662 6.2 62
bling medical resequencing of patient samples (see later section
15 100.34 634 6.3 21
in this chapter) to search for novel variants or mutations that
might be of clinical importance (B entley, 2006 ) ( Figure 1.1c, d) 16 88.83 902 10.2 20
(see Chapter 7).
17 78.77 1217 15.5 40
18 76.12 289 3.8 15
Genes in the Human Genome
19 63.81 1427 22.4 82
While the human genome contains a currently estimated
20,000–25,000 genes (C lamp et al., 2007; International Human 20 62.44 603 9.7 28
Genome Sequencing Consortium, 2004 ), the coding segments
21 46.94 283 6.0 10
of those genes comprise less than 2% of the genome; as rep-
resented in Figure 1.1c , most of the genome, therefore, con- 22 49.69 508 10.2 18
sists of DNA that lies between genes, far from genes or in vast
X 154.91 874 5.6 97
areas spanning several Mb that appear to contain no genes at
Y 57.77 80 1.4 3
all (“ gene deserts ”). A c aveat for this statement is that the proc-
ess of gene identifi cation and genome annotation remains Mitochondrial 0.016 22 – –
very much a work-in-progress; despite the apparent robustness
aFrom Ensembl v. 48
of recent estimates ( Clamp et al., 2007) , it is conceivable that
The Human Genome ■ 7
(a) (d)
>chr1:2040588,2043588
actgcaacctccacctcctgggttcaagtgattctgctgcctcagcctcctgagtagctg
ggattacaggtgcccaccaccatgcccaactattttttgtatttttagtagaggcagggt
ttcaccatattgaccaggctggtatcgaattcctggcctcaagtgatctgtctgccttgg
cctcccaaagtgctggg[t/a]ttacaggcatgagccactgtgcctggcctaattattct
tctttccttattgttagtttgtgctattattttatcagtctttgtgctgttattatcatg
cctgtaaattctacgtgtatttcagacccacaaaccaagtgttgtcttagacagtggtcc
ttcagatttacccccaggttacccttctagtcttcctgcaggacggcgcttacatggaga
1 2 3 4 5
ccagcttccttctgcctgaagtagtccctttagtattcctttcagcacagacttgtaatt
aattctttttatttcttttcttttcttttttttttttttgagatggatttttgctcttgt
tgcccaggctggagtgcagtggtgtgattttggctcactgcagcctccacctcccaggtt
caagcgattctcctggctcagcctcctgaggagctaggattgcaggtgtgcgccaccacg
cccagttgttttttgtttgtgtgggaaatgtctttggcattctttctggagggtgttctc
cactctgtgtggagttctaggcaggtagggggtttcccccaacaggtttttgtgttggct
tggagtgtt[t/g]gtcatttctgtggtgagggcgccttccagcctcactgccacccctg
gaaggcaacatctcttttctctgactcctgttaaaagtgttttcatcacaacagcagcct
6 7 8 9 10 11 12
tgtgaaggacagaggaatcgagaatttctcctaattgagattggtagagcttcttgaatc
agggacatgatagcttttgtctcttttggaaaatatcagcccttgacttttcgttttttt
ttttttttttttttttttttttgagtctcgctcttgttgcccaggctggagtgcaatggc
gcgatctcgactcactgcaatctccacctccccggttcaagtgattctcctgcctcagcg
tcccgagtagctgggattacaggcacttgccaccatgaccggctaattttttttgcattt
ataggagagacagggtttcaccatgttgaccaggctggtctggaactcctgatcatacat
ccaccttggcctcccaaagtgctgggattacaggtgtgagccaccgtgcccggccagccc
13 14 15 16 17 18 ttggcttttcaaatagcatcctgttctctctcccctgggacccccacacttcacacctgt
gtgtctaatgtgctcttttttctgggtttcttctgcgttggttttttcccgctttgtgct
tcaatgtggatttttttctactgttatctcttatttcacccaatctactcttaaatctac
cctttaaattattaatttcagtcacttcattttttacttttagaatttccatttgattct
ttttttttttttttttgcccaggatggcaatggcacgctctcggctcactgcaacctccg
cctcccaggttcaagcaatattcctgccccagcctcccaagcagctgggattacagggtc
acactaccacgccccactaatttttatgtttttattagagacggggttttgccatgttgg
19 20 21 22 X Y ccaggctggtctcgaactcctgaccttgggtgatccg[c/t]ttgcctcagcctcccaaa
gtgttgggattacaggcgtgagccactgcgcctggcatcgtagttctctcttctggggtg
ggaatgtctattctgtgtccttctcacgtgcaaaatactgtcattacatcccaatggccc
cagaacccttaactcctcccagtgtggcgggggcagtcttgtctgaacaaggcatggggg
agcctggaggcccattcctcctgaggccaagt[t/a]cctccctggctgtgggccagcat
(b) aagcgaacaaggcgtgtacttccggaatgctatggactgagtgtgtgtctccccagaatc
catatgttgaagccctaaccctccagtgtgatggtgtttggagacgaagcctttgacagg
tagttagagtcatggcggtagttagttagagtcatggcggtagttagttagggtcacggt
ggtagttaggatcatggtggtacttaaggtcatggcagtagttagggttatatcagtagt
tagggctatggctgtagttagggtgatggtggtagttaaggtcacagcagtaattagggt
catggtggtggttagggtcacagtggtagttagggtcacggtggtggttagggtcgtggt
ggtggttagggtcacggtggtggttagggtcacggtggtagttagggtcacggcggtact
tagggtcacggcggtggttagggtcacggcggtggttagggtcacggtggtggttagggt
cacggcggtggttagggtcacggtggtggttagggtcgtggtagttaggttcatggtggt
ggttagggtcgtggtggttagggtcacggtggtggttagggtcacggtggtagttagggt
cacggctgtagttagcgtcatggtggtggttagggtcacggcggtggttagggtcacggt
ggtggttagggtcacggcggtggttagggtcacggtggtggttagggtcgtggtagttag
gttcatggtggtggttagggtcgtggtggttagggtcacggtggtagttagggtcgtggt
ggttagggtcatggtggtggttagggtcacggtggtggttagggtcgtggtggttagggt
cgtggtggttagggtcgtggtggttagggttgtggtggttagggtggtggtggttagggt
cgtggcggtggttagggtcgtggcggtggttagggttgtggtggttagggtcacggtggt
ggttagggtcacggtgg…
0Mb 1Mb 2Mb 3Mb 4Mb 5Mb 6Mb
(c)
6
e
m
o
s
o
m
o
hr
C
p25.2
Figure 1.1 Four views of the human genome. (a) Karyotype of a normal male donor, HuRef, whose genome was the fi rst individual dip-
loid genome to be sequenced (Levy et al., 2007). The 24 types of human chromosome are shown after conventional G-banding – 22 pairs
of autosomes and the two sex chromosomes, X and Y. (b) An array of genomic segments, showing 244,000 genomic elements hybridized
to DNA from HuRef. (c) Schematic representation of the content of (cid:2)6 Mb from the short arm of chromosome 6, including the location
of various genes and other features from the HuRef genome. (d) DNA sequence from the genome of James D. Watson, showing 3000 bp
from chromosome 1. Watson’s sequence is heterozygous at four positions, three (in yellow) that are known polymorphisms in various pop-
ulations and one (in red) that is a novel variant. Figures in (a) and (b) were provided courtesy of Steve Scherer, Hospital for Sick Children,
Toronto, Canada. (c) is part of a large poster representing the complete diploid HuRef genome (Levy et al., 2007).
there are some genes, including clinically relevant genes, that are well conserved through evolution, one indication of an impor-
currently undetected or that display characteristics that we do tant function. These and other considerations have led to the
not currently recognize as being associated with genes. A maxi- estimate that at most 20% of the genome is of functional impor-
mum of 5% of the genome consists of DNA that has been quite tance (P heasant and Mattick, 2007) . Nonetheless, the statement
8 CHAPTER 1 ■ Organization, Variation and Expression of the Human Genome as a Foundation of Genomic and Personalized Medicine
that the vast majority of the genome consists of spans of DNA developmental disorders and heart disease ( Chang and Mendell,
that are non-genic, of no obvious function, and of uncertain 2007;van Rooij et al., 2008 ).
clinical relevance remains true.
In addition to being relatively sparse in the genome, genes Genome Composition and Landscape
are distributed quite non-randomly along the different human As observed earlier, the distribution of genes in the genome is
chromosomes. Some chromosomes are relatively gene-rich, non-random, both within and between chromosomes. This
while others are quite gene-poor, ranging from a high of (cid:2) 22 in part is a refl ection of the distribution of different types of DNA
genes/Mb to a low of (cid:2) 3 genes/Mb (excluding the Y chromo- sequence, as the genome is partitioned into domains spanning
some and the mitochrondrial chromosome) ( Table 1.2) . And hundreds of kilobasepairs to megabases, refl ecting large-scale
even within a chromosome, genes tend to cluster in certain variation in the G (cid:2) C content of DNA. These so-called “ iso-
regions or in particular bands, a point of clear clinical signifi - chores ” have been known for decades and, at a very gross
cance when evaluating genome integrity, dosage or arrangement level, mimic the pattern of light- and dark-staining bands that
in different patient samples. one observes in metaphase chromosomes (e.g., F igure 1.1a, c )
(Eyre-Walker and Hurst, 2001 ). While the driving force behind
the evolution of isochores is not clear, they infl uence the
Coding and Non-Coding Genes G (cid:2) C content of genes contained within them (and, by virtue
There are a number of different types of gene in the human of the genetic code, therefore, the amino acid composition of
genome. Most genes are protein-coding and are transcribed the encoded proteins), the patterns of mutation and polymor-
into messenger RNAs (mRNAs) that are ultimately translated phism detected, and the nature of various families of repeated
into their respective proteins; their products comprise the list of DNA that reside there. Further – and most strikingly – differ-
enzymes, structural proteins, receptors and regulatory proteins ent isochore domains contain clusters of genes that are highly
that are found in various human tissues and cell types. However, or weakly expressed in a coordinated manner in different tissues
there are additional genes whose functional product appears (Caron et al., 2001 ; Gierman et al., 2007 ; Hurst et al., 2004 ).
to be the RNA itself. These so-called non-coding RNAs Thus, isochores refl ect both the functional as well as structural
(ncRNAs) have a range of functions in the cell, and some do organization of the genome. (See later section on “Expression of
not as yet have any identifi ed function. But the genes whose the Human Genome” for further discussion.)
transcripts make up the collection of ncRNAs represent about a
sixth of all identifi ed human genes ( Table 1.1 ). Repetitive DNA
Some of the types of ncRNA play largely generic roles in Overall, only about half of the total linear length of the genome
cellular infrastructure, including transfer RNAs (tRNAs) and consists of so-called single-copy or unique DNA, whose sequence
ribosomal RNAs (rRNAs) involved in translation of mRNAs is represented only once or at most a few times ( International
on ribosomes, spliceosomal RNAs involved in control of RNA Human Genome Sequencing Consortium, 2001, 2004 ;Venter
splicing, and small nucleolar RNAs (snoRNAs) involved in et al., 2001 ). The rest of the genome consists of several classes of
modifying rRNAs (G riffi ths-Jones, 2007 ;Mattick and Makunini, repetitive DNA and includes DNA whose sequence is repeated,
2006). Other ncRNAs play roles in gene regulation, for example either perfectly or with some variation, hundreds to millions of
in epigenetic gene silencing ( Ogawa and Lee, 2002 ). times in the genome. Several different categories of repetitive
A class of small RNAs of growing importance are the DNA are recognized. Clustered repeated sequences constitute an
microRNAs, ncRNAs of only (cid:2)22 bases in length that suppress estimated 10–15% of the genome and consist of arrays of various
translation of target genes by binding to their respective mRNAs short repeats organized tandemly in a head-to-tail fashion. Such
and thus regulate protein production from the target transcript(s) arrays can stretch several Mb or more in length and constitute up
(Filipowicz et al., 2008 ). Some 255 microRNA genes were iden- to several percent of the DNA content of individual human chro-
tifi ed in the human genome initially ( Lim et al., 2003 ), although mosomes; a notable outlier in this respect is the male-specifi c Y
the total number of such genes is now thought to be closer to chromosome, of which more than half consists of such repeated
1000 (B entwich, 2005 ;Griffi ths-Jones, 2007 ) ( Table 1.2 ). Some DNA families (S kaletsky et al., 2003) . Other tandem repeat fami-
are evolutionarily conserved, while others appear to be of quite lies are based on somewhat longer basic repeats. For example, the
recent origin during primate evolution, thus underscoring alpha-satellite family of DNA is composed of tandem arrays of
the diffi culty of determining the precise number and identity different copies of an (cid:2)171 bp unit, found at the centromere of
of human genes (C lamp et al., 2007 ). MicroRNAs have been each human chromosome, which is critical for proper segregation
shown to downregulate hundreds of mRNAs each, with differ- of chromosomes during cell division ( Rudd and Willard, 2004;
ent combinations of target RNAs in different tissues ( Lim et al., Schueler and Sullivan, 2006 ). Another highly signifi cant family of
2005); combined, the microRNAs are thus predicted to control repeats is found at the very ends of chromosomes, the telomeres.
the activity of as many as 30% of all protein-coding genes in While the repeats at the functional telomeres consist of relatively
the genome ( Filipowicz et al., 2008 ). While this is a fast-mov- short stretches of perfect (TTAGGG)n repeats, different subtelom-
ing area of genome biology, several microRNAs have already eric regions (just proximal to the telomere repeats) share patterns
been implicated in various human diseases, including cancer, of homology with other subtelomeres around the genome that
Variation in the Human Genome ■ 9
create clinically relevant hotspots of interchromosomal recombi- populations to be considered polymorphic in our species. In
nation ( Linardopoulou et al., 2005; Riethman et al., 2005) . addition, there are countless very rare variants, many of which
Other major types of repetitive DNA in the genome probably exist in only a single or a few individuals. In fact,
consist of related sequences that are dispersed throughout the given the number of individuals in our species, essentially each
genome rather than localized. Among the best-studied dispersed and every base pair in the human genome is expected to vary
repetitive elements are short, interspersed nuclear elements in someone somewhere around the globe. It is for this rea-
(SINEs). The most prominent family of these contains repeats son that the original genome sequence is considered a “refer-
that are about 300 bp in length and are recognizably related to ence” sequence, derived as a consensus of the limited number of
each other although not identical in DNA sequence. In total, individual genomes whose sequencing was part of the Human
members of this family make up at least 10% of human DNA, Genome Project, but actually identical to no individual’s genome.
although they make up a much higher percentage of the DNA
in some isochores. A second major dispersed, repetitive Types of Variation
DNA family is called the LINE (where the L stands for long) Early estimates were that any two randomly selected individu-
family, whose members range in size up to 6 kp in length and als have sequences that are 99.9% identical or, put another way,
account for about 20% of the genome. that an individual genome would be heterozygous at approxi-
Families of repeats dispersed throughout the genome are mately 3–5 million positions, with different bases (i.e., a T or
clearly of medical importance. Both SINE and LINE sequences a G) at the maternally and paternally inherited copies of that
have been implicated as the cause of mutations in genetic dis- particular sequence position. The majority of these differences
ease. At least a few copies of these families generate copies of involve simply a single unit in the DNA code and are referred
themselves that can integrate elsewhere in the genome, occa- to as single nucleotide polymorphisms (SNPs) (T able 1.1 ) (see
sionally causing insertional inactivation of a medically impor- Chapter 7). The remaining variation consists of insertions or
tant gene. The frequency of such events causing genetic disease deletions (in/dels) of (usually) short sequence stretches, varia-
in humans is largely unknown, but they have been suggested tion in the number of copies of repeated elements or inversions
to account for as many as 1 in 500 mutations (D eininger et al., in the order of sequences at a particular locus in the genome
2003;Kazazian and Moran, 1998) . In addition, aberrant recom- (Figure 1.2 ) . The total amount of in/del variation is more than
bination events between different LINE or SINE repeats can originally anticipated and approaches 0.5%, not 0.1%, between
also be a cause of mutation in some genetic diseases. any two randomly selected individuals ( Levy et al., 2007 ). Any
and all of these types of variation can infl uence disease and thus
Segmental Duplications must be accounted for in any attempt to understand the contri-
An important subclass of repetitive DNA, distinct from the large bution of genetics to human health (T able 1.3 ).
families just mentioned, includes blocks of different sequences
(hence, not defi ning a particular family of sequences) that are
present in multiple copies, often with extraordinarily high
A B C D
sequence conservation, in many different locations around the
genome. Duplications involving substantial segments of a chro- Reference
mosome, called segmental duplications, account for at least 5%
A B C C D
of the genome ( Bailey and Eichler, 2006 ). When the duplicated
regions contain genes, genomic rearrangements can result in Segmental duplication – Biallelic CNV (C)2
the deletion of the region (and the genes) between the copies
and thus give rise to disease (C onrad and Antonarakis, 2007 ). A B C C C D
In addition, rearrangements between duplicated segments are Multiallelic copy number variant (C)0-n
a source of signifi cant variation between individuals in the
number of copies of these DNA sequences (S harp et al., 2005 ), A B C D D D D C D C D C D
as will be discussed in the next section. Complex CNV (D)4(CD)3
A C B D
Inversion (CB)
VARIATION IN THE HUMAN GENOME
With completion of the reference human genome sequence,
Chromosome
attention turned to the discovery and cataloging of variation
in that sequence among different individuals (including both Figure 1.2 Schematic representation of different types of
healthy individuals and those with various diseases) and among structural polymorphism in the human genome, leading to dele-
different populations. It has been estimated that there are some tions, duplications, inversions and CNV changes relative to the
10–15 million common sequence variants that are of suffi - reference arrangement. From Estivill and Armengol (2007),
cient frequency (minor allele frequency (cid:6) 5%) in one or more with permission.
10 CHAPTER 1 ■ Organization, Variation and Expression of the Human Genome as a Foundation of Genomic and Personalized Medicine
TABLE 1.3 Common variation in the human genome
Type of variation Size range (approx.)a Effect(s) in biology and medicine
Single nucleotide polymorphisms 1 bp →
Non-synonymous functional change in encoded
(SNPs)
protein?
→
Others potential regulatory variants?
→
Most no effect? (“neutral”)
→
Copy number variants (CNVs) 10 kb to 1 Mb Gene dosage variation functional consequences?
→
Most no effect or uncertain effect
→
Insertion/deletion polymorphisms 1 bp to 1 Mb In coding sequence: frameshift mutation? functional
(in/dels) change
→
Most uncertain effects
Inversions Few bp to 100 kb ? break in gene sequence
? long-range effect on gene expression
? indirect effects on reproductive fi tness
→
Most no effect? (“neutral”)
→
Segmental duplications 10 kb to (cid:6)1 Mb Hotspots for recombination polymorphism (CNVs)
aAbbreviations: bp (cid:5) basepair; kb (cid:5) kilobasepair; Mb (cid:5) megabasepair
While the overall estimate of SNP heterozygosity is approxi- novel CNVs are uncovered with every new population studied,
mately 1 in 1500 bp, there is much more variation in non-coding a dedicated effort is underway to cataloged CNVs in the human
sequences than in the coding segments of genes, refl ecting strong genome worldwide and to associate these with clinical phenotype
selective pressure during evolution against certain types of change (Feuk et al., 2006; Scherer et al., 2007 ;Sharp et al., 2006 ). While
in gene sequences. The combination of particular alleles along most variation of this type is inherited, some CNVs occur de novo
chromosomes is also non-random, with particular combinations or even in somatic cells; in these cases, an individual will have dif-
(haplotypes) being more prevalent over short distances, due to the ferent repeat lengths than do either of his or her parents.
relative ineffi ciency of meiotic recombination to separate alleles Array-based methods (see Chapter 9) have rapidly gained
at sites that are physically close together (I nternational HapMap acceptance for evaluating the association of both inherited and
Consortium, 2007; Nussbaum et al., 2007 ). The resulting patterns de novo CNVs with mental retardation and other developmental
of linkage disequilibrium are relevant for designing strategies to disorders ( de Vries et al., 2005; Friedman et al., 2006 ;Lee et al.,
examine genetic variation genome-wide, both as a practical mat- 2007;Weiss et al., 2008) . It is of considerable ongoing interest to
ter (i.e., reducing the number of SNPs that need to be tested to evaluate the role of CNVs and other structural variants includ-
reveal the underlying patterns of variation) and for evaluating the ing deletions ( Conrad et al., 2006) and inversions ( Korbel et al.,
potential functional importance of any particular SNP allele (see 2007; Stefansson et al., 2005 ;Tuzun et al., 2005 ) in the etiol-
Chapters 2, 8 and 27). ogy of more common, complex diseases or traits of adulthood,
including neurological and psychiatric conditions as well as
pharmacogenetic traits ( Beckmann et al., 2007; Buckland, 2003 ).
Copy Number Variation
Over the past few years, a number of important studies have
identifi ed a previously unanticipated prevalence of structural Variation in a Single Genome
variants in the genome, which collectively account for more The most extensive current inventory of the amount and type of
variation in genome sequence than do SNPs (e.g., Levy et al., variation to be expected in any given genome comes from the
2007;Redon et al., 2006 ;Sebat et al., 2004 ;Tuzun et al., 2005) . direct analysis of the diploid genome sequence of a single male
The most common type of structural variation involves changes individual, HuRef ( Levy et al., 2007) . Over 4 million variants
in the local copy number of sequences (including genes) in the were described, spanning some 12.3 Mb of DNA. About 20 Mb
genome, and these are generally referred to as copy number var- of “ new ” sequence was determined that was not previously
iants (CNVs) ( Figure 1.2 ) (see Chapter 9). available as part of the human reference sequence, refl ecting in
A number of different technology platforms are now being part the still unfi nished nature of the human genome sequence
used to detect CNVs, including arrays and direct genome and in part the particular patterns of inserted or deleted
sequencing (K orbel et al., 2007; Levy et al., 2007; Wong et al., sequences that distinguish different genomes. Several hundred
2007). As many such CNVs encompass genes (including micro- thousand in/dels were also found in this single genome. In addi-
RNA genes; W ong et al., 2007) and as a signifi cant number of tion, several hundred CNVs were detected, which overlapped at
Expression of the Human Genome ■ 11
least 95 well-annotated genes. While most of these variants are SNPs that are informative for such studies (so-called “ancestry
identical to those found in other individuals in the population, informative markers,” AIMs) (K ittles and Weiss, 2003 ; Paschou
others are likely to be what are termed “private ” mutations, spe- et al., 2007; Tian et al., 2008) . This had led to two related, but
cifi c to HuRef and his family. distinct applications of such markers. First is the use of admix-
In the HuRef genome, at least 850 genes known to be ture mapping, tracing the location of particular SNPs associ-
involved in inherited disease contained at least one heterozygous ated with disease in populations of patients whose genomes are
variant, and over 300 of them contained at least one non- a mixture from at least two original populations, for example,
synonymous SNP (i.e., a SNP that, by virtue of the genetic African-Americans or Latinos ( Price et al., 2007 ; Smith et al.,
code, is predicted to change the encoded amino acid). Of 2004). Such an approach has already been used to map genes
course, additional genes may also impact disease, and, overall, associated with several phenotypes whose frequency differs
more than 4000 genes in the HuRef genome contained one or markedly between different population groups, including pros-
more non-synonymous SNP. Thus, at least 17% and perhaps as tate cancer (F reedman et al., 2006 ), hypertension ( Deo et al,
many as 44% of the genes in the HuRef genome were heter- 2007), skin pigmentation (M cEvoy et al., 2006 ) and white blood
ozygous and could encode proteins that differ in their amino cell count (N alls et al., 2008) .
acid sequence and/or are produced in different amounts ( Levy The second use of AIMs is for ancestry testing unrelated
et al., 2007) . These estimates underscore the impact of gene and to disease studies ( Kittles and Weiss, 2003 ; Shriver and Kittles,
genome variation on human biology and on medicine. They also 2004). While the motivations behind such testing and the
provide remarkable validation of the original estimates of Harris potential uses (and, some fear, abuses) of biogeographic infor-
and Lewontin decades ago of the proportion of genes that mation are varied, the commercial availability and interpretation
are heterozygous in any given individual ( Harris, 1980 ; of genetic ancestry testing is controversial (B olnick et al., 2007) .
Lewontin, 1967) . Nonetheless, the availability of such information as an inten-
Table 1.3 and Figure 1.2 capture the general types of and tional or unwitting by-product of wide-scale genome analysis is
characteristics of the most common variation in the human inevitable, and both consumers/patients and health professionals
genome and in human genes. However, it is clear that we are need to be aware of this as genetic variation is explored in the
still in a mode of discovery, as relatively few genomes or popula- context of individual genomes (see Chapter 33).
tions have been assessed to date; no doubt millions of additional
SNPs remain to be uncovered, as well as many additional in/
dels, inversions and CNVs, a portion of which will be expected
EXPRESSION OF THE HUMAN
to involve genes and other sequences of direct relevance to
GENOME
medicine. The issue of “ what is normal? ” – an essential con-
cept in clinical medicine – remains very much an open ques- A key question in exploring the origins, structure and function
tion when it comes to the human genome (S hianna and of the human genome is to understand how proper expres-
Willard, 2006) . sion of our 20,000–25,000 genes is determined, how it can be
infl uenced by either genetic variation or by environmental
Variation in Populations exposures or inputs, and by what mechanisms such alterations
Most of the heterozygosity in the human genome is believed in gene expression can lead to pathology evident in the prac-
to be due to variants with a minor allele frequency of at least tice of clinical medicine. The control of gene activity – in devel-
1%. Taking advantage of major technological developments opment, in different tissues, during the cell cycle, and during
that have greatly increased the throughput of genotyping on a the lifetime of an individual both in sickness and in health – is
genome-wide scale, several large-scale projects have validated determined by a complex interplay of genetic and epigenetic
these estimates by gathering genotypic information on millions features.
of SNPs worldwide ( Hinds et al., 2005 ;International HapMap By“genetic” features, we here refer to those found in the
Consortium, 2003, 2007) . Most of the studies to date, how- genome sequence (see Box 1.1), which plays a role, of course,
ever, have been restricted to a small number of populations of in determining the identity of each gene, its particular form
Northern European, African and Asian origin used for SNP (alleles), its level of expression (regulatory elements such as pro-
detection. From these and a large number of earlier studies moters, enhances, splice sites, etc.), and its particular genomic
that examined more populations but for many fewer variants, it landscape (domains, isochores). By “ epigenetic” features, here
has been concluded that some 85–90% of the variation found we mean packaging of the DNA into chromatin, in which it
in our species is shared among different population groups; a is complexed with a variety of histones as well as innumerable
relative minority of variants, therefore, are specifi c to or highly non-histone proteins that infl uence the accessibility and activity
enriched/depleted in genomes from a particular population. of genes and other genomic sequences. The structure of chro-
It is possible to use population-specifi c variants to obtain matin – unlike the genome sequence itself – is highly dynamic
information on the geographic origin of a genome or of par- and underlies the control of gene expression that shapes in a
ticular segments within a genome. Given the many millions of profound way both cellular and organismal function ( Felsenfeld
SNPs now available, there are at least hundreds of thousands of and Groudine, 2003 ).