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Basic research
Personal genomes in progress: from the
Human Genome Project to the Personal
Genome Project
Jeantine E. Lunshof, PhD; Jason Bobe, MS; John Aach, PhD;
Misha Angrist, PhD; Joseph V. Thakuria, MD; Daniel B. Vorhaus, JD, MA;
Margret R. Hoehe, MD, PhD; George M. Church, PhD

T

he dawning of a new decade is an appropriate
time to reflect on the tremendous progress that has been
made in human genomic research. In 2010, with wholegenome sequencing becoming increasingly affordable,
the promise of large-scale human genomic research studies involving hundreds, thousands, and even hundreds ofthousands of individuals is rapidly becoming a reality.
The next generation of human genomic research will
occur on a scale that would have been nearly unfathomable at the start of the last decade, when the publication of the Human Genome Project’s first draft results
was still pending.
The cost of a diploid human genome sequence has dropped from about $70M to $2000 since 2007—even as the standards
for redundancy have increased from 7x to 40x in order to improve call rates. Coupled with the low return on investment
for common single-nucleotide polylmorphisms, this has caused a significant rise in interest in correlating genome sequenceswith comprehensive environmental and trait data (GET). The cost of electronic health records, imaging, and microbial,
immunological, and behavioral data are also dropping quickly. Sharing such integrated GET datasets and their interpretations with a diversity of researchers and research subjects highlights the need for informed-consent models capable ofaddressing novel privacy and other issues, as well as for flexible data-sharing resources that make materials and data available with minimum restrictions on use. This article examines the Personal Genome Project’s effort to develop a GET database as a public genomics resource broadly accessible to both researchers and research participants, while pursuing thehighest standards in research ethics.
© 2010, LLS SAS

Keywords: Personal Genome Project; personal genomics; DNA sequencing technology; whole-genome sequencing; phenome; envirome; microbiome; GET data
set; open consent; public genome; ELSI
Author affiliations: Department of Genetics, Harvard Medical School, Boston,
Massachusetts, USA (Jason Bobe*, John Aach, George M. Church**);PersonalGenomes.org, Boston, Massachusetts, USA (Jason Bobe, Daniel B.
Vorhaus, Joseph V. Thakuria, George M. Church**); European Centre for
Public Health Genomics, FHML, Maastricht University, Maastricht, The
Netherlands; Department of Molecular Cell Physiology, VU University
Amsterdam, The Netherlands (Jeantine E. Lunshof*); Institute for Genome
Copyright © 2009 LLS SAS. All rights reserved

Dialogues Clin Neurosci. 2010;12:47-60.

Sciences & Policy, Duke University, Durham, North Carolina, USA (Misha
Angrist); Harvard Medical School, Massachusetts General Hospital, Boston,
Massachusetts, USA (Joseph V. Thakuria); Robinson, Bradshaw & Hinson, P.A.,
Charlotte, North Carolina, USA (Daniel B. Vorhaus); Department of Vertebrate
Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany(Margret R. Hoehe**) * Co-first authors ** Co-last authors
Address for correspondence: Department of Genetics, Harvard Medical School, 77
Avenue Louis Pasteur, Boston, MA 02115, USA, Tel: +1 617/432-7562;
PersonalGenomes.org, 77 Avenue Louis Pasteur, Boston, MA 02115 USA(e-mail: jason@personalgenomes.org)
www.dialogues-cns.org

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When the Human Genome Project published its draft
results on June 26, 2000, it published a compound humangenome sequence containing genetic information from several volunteers. Seventy percent of the final sequence wasobtained from one anonymous individual, while the remaining 30% came from a number of different individuals. From
the first amalgamated human genome sequence—which
was refined in 2003 and continues to be updated and refinedto this day—private and public research efforts have goneon to sequence numerous individual human genomes withincreasing speed and detail and decreasing time and cost.
The acceleration of whole-genome sequencing in the
research context necessitates new perspectives and models
that enable scientists and society to learn as much as possible from this rapidly expanding dataset while still respecting important ethical, legal, and social norms.
The Personal Genome Project (PGP),1 an ambitious
research study directed by faculty members in the
Department of Genetics at Harvard Medical School, aims
to recruit as many as 100 000 informed participants to contribute genomic sequence data, tissues, and extensive environmental, trait, and other information to a publicly accessible and identifiable research database.
In this review we describe the Personal Genome Project
itself, focusing on its unique structural features and therationale behind the project’s design. We also elucidate thechanging scientific and social landscape that makes the
PGP’s model of open consent and public data accessincreasingly important to the furtherance of humangenomic research.

The PGP’s mission
In contrast to research studies that focus on small subsets of traits within narrowly defined human populations
exhibiting single diseases, the PGP was conceived withan expansive mission. From the outset, the mission of the
project (Table I) has been to develop a broad-based, longitudinal, and participatory research study that will facilitate a comprehensive understanding of the project’s
participants at the genomic level and beyond.
The PGP is constructed with the recognition that ourdesire to truly understand the genesis of most complex
human traits—from dread diseases to the talents andquirks that make us each uniquely human—could only
be satisfied by examining genomic information in context and by surrounding it with the richest possible datafrom the widest possible array of supplemental sources.
By supplementing genomic sequence data with the collection and analysis of tissues and extensive environmental and trait data, and by making these data publicly
accessible to researchers worldwide, the PGP aims to
improve understanding of the ways in which genomes
plus environments ultimately equal traits (Figure 1).
The PGP is more than just a research repository. In addition to its publicly accessible research database, the PGP,
which is supported by the nonprofit PersonalGenomes.org,
also works to disseminate genomic technology and knowledge at a global level, thereby producing tangible andwidely available improvements in the understanding andmanagement of human health and disease. The PGP also

The Personal Genome Project’s Mission Statement
The mission of the Personal Genome Project is to encourage the development of personal genomics technology and practices that:• are effective, informative, and responsible• yield identifiable and improvable benefits at manageable levels of risk
• are broadly available for the good of the general public
To achieve this mission we will build a framework for prototyping and evaluating personal genomics technology and practices at increasing
scales. In support of this goal, we will:• develop a broad vision for how personal genomes may be used to improve the understanding and management of human health anddisease• provide educational and informational resources for improving general understanding of personal genomics and its potential• recruit individuals interested in obtaining and openly sharing their genome sequences, related health and physical information, andreporting their experiences as a participant of the project on an ongoing basis• develop technologies to improve the accessibility of personal genome sequencing• foster dialog with research communities, industries, and public and governmental bodies with interests in personal genomics, and related
ethical, legal, and social issues (ELSI)• develop tools for interpreting genomic information and correlating it with personal medical and biological information
Table I. PGP’s Mission Statement, available at: htttp://www.personalgenomes.org/mission.html.1

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Personal genomes in progress - Lunshof et alfinds itself at the forefront of discourse surrounding the
ethical, legal, and social issues (ELSI) associated withlarge-scale whole-genome sequencing, particularly in theareas of privacy, informed consent, and data accessibility.
The PGP is, and is intended to be, a research project thatis constantly in progress, exploring the boundaries ofhuman genomic research in a way that produces maximal advances in scientific understanding and public
understanding and well-being, while striving to reachbeyond what is minimally required to satisfy its ethical,
legal, and social obligations to its participants. In the sections that follow we report on unique aspects of the PGP
relating to technology development, integrative
genomics, and human subject research protocols, as well
as describe the development and current state of the
PGP.

Key developments inhuman genome sequencing
The PGP derives its impetus and importance from historic breakthroughs in understanding and analysis ofDNA. DNA comprises only a very small fraction of acell (~3% dry weight E. coli), and its role as the molecule primarily responsible for transmission of genetic
traits was not recognized until a series of discoveries
beginning in the 1940s. The emergence in 1953 of a clear
concept of DNA as a double-helical structure comprising a pair of complementary strings of four elementarybases (the nucleotides A, C, G, and T) crystallized interest in determining the DNA sequences of genes and thesequence differences responsible for disease, and set thestage for over four decades of development of ever more
efficient and comprehensive sequencing methods. Table
II describes this history by a set of milestones that takeone from the early beginnings of DNA sequencing up
through delivery of draft human genome sequences in2001 to 2003. In the 38 years between 1965, when Robert
Holley and colleagues at Cornell and the US
Department of Agriculture sequenced a 77 nt RNA
gene after 4 years of effort, and 2003, when the public
Human Genome Project (HGP) declared that it had met
its goals regarding delivery of a ~3Gbp human genome
sequence, the size of DNA sequence that could beaccommodated by sequencing technology improved ~30
million-fold.

Post-HGP sequencing—towards
whole diploid genomes
Notably, the HGP had delivered only a single humangenome sequence that was a composite built from a small
number of deidentified individuals, while the competing
nonpublic human genome project merged in data from an
identified individual (Craig Venter); both were haploid
estimates. As recognized from the beginning of the HGP,
many additional resources would be needed to understand the functions of the genes laid out in these “reference” human genomes, and to identify the sequence differences between individuals that contribute to individual
traits, health, and disease. Indeed, as the HGP ended, projects were already under way to identify large numbers ofgenetic differences from the HGP-derived reference
genome in different human populations that could sub-VDJ-ome
Personal
genome
6 Gbp
3M+ alleles

Personal
stem cells
andepigenome+=

Envirome

TRAITS(phenome)

Microbiome

Figure 1. Genome + Environment = Traits (GET) equation. Envirome: the totality of environmental influences; VDJ-ome: the DNA sequences of the entire
repertoire of an individual’s immunoglobulin and T-cell receptors, which reflect a lifetime of antigenic exposures; Microbiome: the billions ofcommensal, symbiotic, and pathogenic micro-organisms that share our body space; Epigenome: the totality of programmed biochemical andstructural modifications to genomic DNA that regulate organism or phenotype development. (see overview in Table III).

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Basic researchsequently be analyzed using low-cost array methods inlarge numbers of individuals, a strategy that has since
given rise to more than 480 published genome-wide association studies.16,17 At the same time, however, interest was
rising in the second approach: to significantly improve
DNA sequencing technology to a point where an individual’s entire genome could be sequenced at very low
cost. A combination of two kinds of arguments wereadvanced supporting this approach, focusing on functional
utility and economics, respectively.
The gist of the functional arguments was that sequencing of individuals is intrinsically more informative andflexible than array-based interrogation of known sites ofvariation and that, variation aside, any improvements insequencing cost and capability could be quickly applied
to numerous general aspects of biology that are criticalto understanding gene function, traits, and health anddisease.18,19 The relative advantages of sequencing havelong been recognized. Unlike array analyses, sequencing: (i) does not require variations to be preidentified;(ii) can more readily accommodate more complex variations than single nucleotide changes and very short
inserts or deletions; and (iii) need not focus on variations
that are common in large populations vs rare or uniquevariations. In consequence, as sequencing technology has
improved, it has increasingly been integrated into association studies of variation.20-23
However, these advantages of sequencing were counterbalanced by their high cost, a situation well illustrated
Date
1957

Event
First sequence mutation identified responsible for disease

1965
First sequence of a single complete gene
1976-1977 Sequencing of first viral genomes
1975-1977 Maxam/Gilbert and Sanger DNA sequencing methods

1994
First commercial bacterial genome sequence
1995
First published bacterial genome sequence
1998-2000 Genome sequences of first animals

2001

Two draft sequences of human genome

2003

Completion of public Human Genome Project

Table II. Development of DNA sequencing.

by the $3 billion US cost of the HGP itself. It is here that
economic arguments were advanced suggesting that dramatic improvements in sequencing were feasible thatmight ultimately enable an individual’s genome to besequenced for 1000 to 10 000 USD.18 On an empiricallevel, sequencing technology has appeared to exhibit ahistorical trend of exponentially decreasing costs withtime as measured by sequenced base pairs per dollar at
a given error rate, a situation frequently compared with
“Moore’s Law” in computing,24 which noted that computing power measured by the integrated circuit transistor density doubled roughly every 2 years at constantcost (Figure 2).18,25 To get genome sequencing costs down
to $1000 would require cost and throughput improvements of an additional 4 to 5 orders of magnitude, so thequestion of economic feasibility ultimately turned onwhether new methods could enable this very large
improvement.
Here, the HGP again gave grounds for optimism, foreven though the HGP itself only achieved 100-foldimprovements, it achieved this largely by refining, miniaturizing, and robotically scaling up, but not fundamentally changing, a Sanger sequencing method initiallydeveloped over 20 years earlier (Table II). If such methods were capable of 100-fold improvement, considerably
greater improvements might be expected from more radically changing sequencing chemistry, signal generationand detection, and instrumentation in ways that could
integrate some of the vast advances in chemistry andSize of sequence (bp)
1 amino acid(sickle cell vs normal hemoglobin)
77 bases3562 bases (MS2 RNA phage)
5375 bases (φ X174 DNA phage)

Reference(Ingram 19572)(Holley, Apgar et al 19653)(Fiers, Contreras et al 19764;
Sanger, Air et al 19775)(Sanger and Coulson 19756;
Maxam and Gilbert 19777;
Sanger, Nicklen et al 19778)
1.7Mbp (Helicobacter pylori)(Nature Genetics, May 19969)
1.83Mbp (Haemophilus influenzae) (Fleischmann, Adams et al 199510)
100Mbp (Caenorhabditis elegans)(C. elegans Sequencing
120Mbp (Drosophila melanogaster)
Consortium 1998,11 Adams,
Celniker et al 200012)~3Gbp(Lander, Linton et al 2001,13
Venter, Adams et al 200114)(Collins, Morgan et al 200315)

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Personal genomes in progress - Lunshof et al

Next-generation sequencing
Researchers were quick to work out sequencing
approaches along the lines indicated in these arguments,
and commercial products emerged soon, giving rise tonext-generation sequencing (NGS). Soon granting agencies promised funding for support, and a ~10M USD
competition was announced for rapid, accurate genomic
sequencing, generating increased coalescence aroundtarget goals for dramatic improvements to sequencing
technology.26,27,28 Detailed reviews and comparisons of
NGS approaches have been published.18,29,30
Among the earliest NGS methods were polony sequencing (the Polonator) and 454 Life Sciences.31,32,33 Both methods amplify DNA templates onto microbeads that are
packed onto two-dimensional arrays for sequencing,
thereby achieving enormous economies of scale compared with Sanger sequencing, and each achieved ~25fold better cost per bp compared with HGP (Figure 2).
However, each uses different sequencing chemistry andarraying technology, giving rise to many technical tradeoffs. Together they proved the general point that great
improvements in sequencing efficiency were indeed
within reach, but also that the precise character anddegree of improvement would depend closely on thenovel technologies employed and the ingenuity withwhich they could be integrated. A second wave of development introduced methods by Illumina and ABI that, byvery different means, have improved the utility and costs,(Figure 2)34,35 and hence use of these systems is becoming
widespread for both large scale and “deep” sequencing
applications, and both are under continuous development.

Two complete cancer genomes were recently sequenced,
one with each platform.36,37 Further rounds of innovation
have yielded a diverse set of newer NGS methods. For
instance, a number of “single-molecule” sequencing methods are now available or in development. These methods
avoid the need to make thousands to millions of copies of
DNA template molecules on microbeads or surfaces toassure that sequencing operations generate sufficient signal to read individual bases accurately, and instead use
highly sensitive optics to detect bases at the single molecule level; this allows even denser packing of DNA templates and further efficiencies in sequencing chemistry.
While Helicos Biosciences has commercialized a singlemolecule system that simply arrays single template molecules on a surface and uses sequencing cycle similar to
the methods above, Pacific Biosciences is developing asystem in which enzymes and templates are tethered tothe bottom of nanofabricated wells and which monitors
the signals generated by sequencing chemistry in realtime vs artificial cycles.38,39 Here, the nanofabricated wells
enable substantially increased accuracy of single moleculebase incorporation events. Finally, on another track, thecompany Complete Genomics, Inc has developed amethod whereby very compact self-assembling amplicons
of template DNAs called “nanoballs” are flowed onto a
nanofabricated grid of ~300nm spots at 700 to 1300 nm
center-to-center distances. Three complete humangenomes were sequenced with this method (as of January2010) with an average consumable cost of $4400 and as
low as $1500 for 40X coverage.40
10000000
CGI$5K human genome

1000000

Illumina GA & ABISOLID

100000
10000

bp/$

enzymology, optics and electronics, materials science,microfabrication, and process control that had accrued
over the preceding 20 years and been put to good use inmany other fields. The HGP also directly provided an
important resource for realizing this strategy: the reference human genome sequence itself, as this could serve
as a template against which reads obtained by new technologies could be located, allowing new human genomes
to be assembled at least initially by “resequencing” vs denovo assembly. This reduces the burden on new sequencing methods by allowing them to generate useful datawith shorter reads and higher base call error rates thanwould generally be needed for de novo assembly,
although de novo assembly of genomes using new
sequencing technology remains an important goal.

Watson (454)1000
Venter (3730)

100

454 & Polony

10
HGP

1

HGP
0.1
0.01

CMV
pBR322

1980

1985

1990

1995

2000

2005

2010

Figure 2. Exponential trend of sequencing costs in base pairs per USD(bp/$), a trend often compared with Moore's Law (see text). See
ref 25 for details.

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Towards affordable personal genomes
These developments suggest that technology capable ofmeeting the cost target of $1000 or less for a diploid
human genome sequence is within reach. Indeed, the indepth resequencing of individual human genomes has now
been demonstrated several times by NGS developers todemonstrate that their methods have come of age. There
are now published full genome sequences for at least
seven individuals,40 with some having been sequenced bymore than one method. There are also tens—and perhaps
hundreds—of additional unpublished or partly publishedgenomes (see, eg, refs 36,37),while the lower-coverage 1000
Genomes Project20,21 continues. Clearly, the age of personal
genomics is now close at hand.

The PGPAs described in the first section, one of the PGP’s central
aims is to develop a publicly available, fully consented
database containing comprehensive human genome andphenome data for its research participants. Such integrated datasets are fundamental drivers of progress infunctional genomics and enable systems biology-based
insights into the mechanisms of human health and disease.41 PGP studies will look beyond inherited genomes
to include somatic and epigenetic variation data, as well
as relevant microbiome, transcriptome, immunity-reflecting “VDJ-ome” and phenome data to develop comprehensive profiles. By developing high-resolution data profiles for each participant, and multiplying that by a large(up to 100 000) participant population, the PGP will also
generate valuable data describing the kinds and distributions of variation that exist in populations. Although an
improved understanding of human health and disease isa central aim of the PGP, its focus is considerably broader
and will enable research into the social and behavioral
sciences using personal genomic data. Finally, the PGP’s
flexible study protocol and public and distributed
approach to research enables it to keep pace withsequencing and other technological advances while
simultaneously driving these developments.
Integrated personal genomes: inherited, somatic, environmental genomics
If the PGP is to fulfill its mission to address the multidimensional complexity of human biology, it must encom-

pass multiple interacting “-omes.” For example, a person’s diet will have a profound influence upon her or his
somatic gene expression as well as the genomic and proteomic activity of the person’s microbiome. It will also
affect the metabolome. Similarly, an individual’s environmental exposures to pollutants will have a direct
bearing on her or his immunological response and therefore, on the VDJ-ome. Germline alleles will affect how
one metabolizes drugs, which will have myriad effects on
an individual’s physiological and behavioral phenotypes.
Genomes (vs exomes)
In its early phase, given the then-current cost of genomic
sequencing, the PGP planned to focus on exomes rather
than whole genomes as a way to affordably expand the
project to large numbers of participants. Despite representing only 1% to 2% of the 6 billion base pairs in ahuman genome, the exome contains all protein-codingexons and therefore provides access to the majority ofknown functional variants.48,49,50 However, continued
improvements in genomic sequencing have produced
price declines that have rendered whole-genome
sequencing significantly cheaper per base pair thanexome sequencing. The PGP, as a result, has determinedthat whole-genome sequencing is cost-justified given therelatively high price of exomes and the additional information supplied by whole-genome sequences of PGP
participants.51 See also Table III for the various “omes.”
Phenomes
Detailed phenotype data is required to categorize and,ultimately, understand the phenotypes that the PGP
seeks to explore. However, the vastness of the humanphenome, defined as the physical totality of human traits
at all levels, from the molecular to the behavioral, will
require new strategies that permit high-throughput trait
collection while yielding accurate and standardized phenotypic data. With regard to the cellular and molecular
phenotypes, the PGP collects participant tissue samples
and develops cell lines that are then deposited and publicly accessible through established biobanks.52,53
As the PGP expands it is exploring Web-based, highthroughput behavioral phenotype data-collection models pioneered by leading public and private researchers.
While the reliability and validity of self-reported traits
is a concern, particularly for phenome research con-

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ducted online,54,55 Web-based assessments provide distinct opportunities for “dynamic phenotyping” based ona particular individual’s prior genotype-phenotype associations.56 The multimodal capabilities of Web-based trait
collection instruments, combined with their low cost of
implementation at large scales, seem likely to accelerate
the ability of studies like the PGP to effectively explore
new corners of the human phenome.
The PGP is also taking advantage of recent advancements in health information technologies to assist participants and researchers alike in structuring and accessing the massive amounts of personalized data generated
by the project. The emergence of online PersonallyControlled Health Record (PCHR) platforms and othernovel tools enables individuals to collect and manage
their own health data—including health history, medication, allergy, immunization, biometric and other datatypes57,58,59—and can be developed for integrated data
entry, access and dissemination by both the individual
and third-party researchers or data providers, including
health care providers.
Enviromes
The picture of genome and phenome is incomplete without the envirome. The envirome can be described as thetotality of equivalent environmental influences contributing to all disorders and organisms.60 The mode of
response of an organism to the environment that isreflected in its phenotype is constrained by its unique setof genetic variations and the environmental influences ongene expression. Therefore, a comprehensive approach is
required to describe the envirome systematically in con-

Dialogues in Clinical Neuroscience - Vol 12 . No. 1 . 2010

junction with genome and phenome information. The relevant envirome data is too large and complex to bereported, managed, or analyzed manually. The creation ofphenome-genome and genome-envirome networks has
been suggested in order to relate phenome and envirome
information to potential disease-associated genes.61
Microbiomes
Even though microbial cells are estimated to outnumber
human cells in a single individual by a factor of ten, weknow very little about the microbes that live in and on us,
including what mixture of bacteria, viruses, and othermicro-organisms constitute a “normal” human microbiome and how those organisms impact different biological states.62 Major efforts such as the Human Microbiome
Project are under way to characterize the microbiota at
different body sites in humans and to assess how variationin microbial communities is associated with states ofhealth and disease.63 The PGP takes advantage of theunique availability of comprehensive participant profiles
and uses them to explore interactions between hostgenetic and phenotypic variability alongside the genomic
variation in the microbes that colonize them.64
The VDJ-ome
The Church Lab at Harvard Medical School is developing techniques for characterizing the repertoires of Band T-cell receptors in individual humans from blood
samples and correlated across time with personal exposure histories, with an ultimate goal of characterizing
individuals repertoires of linked VDJ and VJ sequences.

Personal genome: Entire diploid human genome of a single individual representing 6 billion base pairs.
Exome: All exons, representing 1% to 2% of the entire human genome.
Phenome: Set of all traits in an organism, at all levels, or one of its subsystems, including morphology, physiology, and behavior.42,43
Envirome: The totality of equivalent environmental influences contributing to all disorders and organisms.44
Microbiome (human): The ecological community of commensal, symbiotic, and pathogenic microorganisms that share our body space.45
VDJ-ome: The repertoire of rearranged V, D, and J genome segments present in an individuals's B and T immune cells at any given time (seeTable IV).
Transcriptome: The set of all RNA molecules, including mRNA, rRNA, tRNA, and noncoding RNA produced in one or a population of cells.46
Epigenome: The totality of programmed biochemical and structural modifications to genomic DNA that regulate organism or phenotype
development.
Metabolome: Total set of metabolites generated by an organism, or subsystem.
Proteome: The entire set of proteins expressed by a genome, cell, tissue or organism at a given time under defined conditions. There are
more proteins than genes.47
Table III. The “omes.”

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These techniques will be directly applicable to PGP participants and their self-reported data, and will yield adatabase of unprecedented depth describing the diversity and time development of human immune responsesof large numbers of individuals in their life contexts.
The adaptive immune system
The adaptive immune system enables individuals to respond totheir unique exposure histories to pathogens and environmental
antigens, and possibly to cancerous mutations in their own cells, bygenerating and modulating expression of >1012 unique antibodies
from B cells and T cell receptors.65 Antibody diversity derives fromprogrammed stochastic rearrangements in maturing B cells of ~40
V, 23 D, and ~5 J functional genomic segments into VDJ heavy
chains, and ~35 V and ~5 J segments into VJ light chains (κ or λ) in
B cells, that are further randomized by somatic hypermutation; asimilar process occurs in T cells.66 NGS methods are now allowing
researchers to identify and analyze expressed VDJ sequences in
depth.67
Table IV. The adaptive immune system and the VDJ-ome.

Tissue reprogramming
The PGP also applies advances in tissue reprogramming
techniques to tissue samples collected from PGP participants. Cells from collected somatic tissues are reprogrammed into induced pluripotent stem (iPS) cells68 andmade to differentiate into the cell types that are targeted
for functional analysis. These methods enable experimental access to diverse tissue types that would otherwise be unobtainable from human subjects but are routinely analyzed in model organisms, and thus, PGP
participants can effectively serve as human model organisms. By examining multiple cell types from a single individual, differences in physiological states within andbetween tissues can be compared within a single PGP
participant and/or across the entire PGP cohort. Thisapproach also permits researchers to elucidate connections between genetic variation and variation in othermolecular traits, such as gene expression or epigenetic
modifications.69 Stored fibroblast cell lines provide
researchers with access to renewable supplies of different tissue types from PGP participants.

The PGP: from personal to public genomes
The potential benefits arising from large-scale and integrated human genomic datasets are immense.70 The util-

ity of such research, however, depends upon the responsible development and widespread availability of suchcomprehensive datasets, which in turn depends on
describing and addressing the various ethical, legal andsocial challenges. Those challenges include a standard set
that are inherent to any research involving human subjects, as well as certain challenges that are unique to“public genomics”71 research involving publicly available,
identifiable whole-genome sequence data, such as themodel pioneered by the PGP. We use the term “publicgenomics” to denote research studies that possess thefollowing three critical attributes.
Integrated data
The various data types, including genomic and phenomic
or trait data, are accessible in a linked format, such as a
PCHR or other integrated data structure. Through thisexplicit linkage of data it is possible to ascertain thecomplete list of available traits and genetic variants forany given participant. Integration also facilitates participant-researcher interactions, longitudinal study andrecontact and, crucially, simultaneous investigation of thefull range of complex trait associations. Although participants need not be explicitly identified, integrated data
sets that include both genomic and phenomic data willbe identifiable in most cases. For this reason, participants
must be made explicitly aware of the probability thatthey will be identified with their publicly available data,
rendering promises of perfect privacy, anonymity, or confidentiality impermissible within the public genomics
model. However, the promise of privacy need not give
way to a promise of publicity.
Open access
Data sets and tissues are made publicly available withminimal or no access restrictions (including researcher
qualifications and cost), and are generally transferable
outside the original research study to be utilized by andcombined with data from third parties. Well-developed
data structures and intellectual property licenses areimportant components of this characteristic. Developing
datasets that are not only publicly available but also easily portable fosters the development of a genomic commons, allows data validation by third parties, and enables
the use and application of data in novel contexts that
may not be foreseeable at the time of collection, thereby

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Personal genomes in progress - Lunshof et alfacilitating hypothesis generation, encouraging serendipity and broadening the genomic research community.
Voluntary and informed participation
Satisfaction of the first two criteria publication of an integrated dataset in an open-access format necessitates thata premium be placed on receiving truly voluntary andinformed consent from participants in public genomics
research projects. Given the yet-unknown outcomes andthe potential personal, familial, and social risks associatedwith such research, enrollment is only acceptable under
an informed consent protocol that is specially designed
to meet the highest standards of human research subjects
protection in view of these conditions.
The study protocol
The PGP aims to produce public genomics research—and to develop and evaluate associated technologies

Dialogues in Clinical Neuroscience - Vol 12 . No. 1 . 2010

and research—on a large and expanding scale. In
October of 2008, the PGP published the first integrated set of DNA sequences, traits, and tissues collected from ten participants (the “PGP-10”) enrolled
in a pilot study initiated in 2005. Today, the PGP is
incrementally expanding its cohort toward 100 000
participants. More than 12 000 individuals had registered to participate in the PGP as of February 2010. In
the following section we highlight significant featuresof the PGP study protocol as it is implemented for theenrollment of the first 100 participants (“PGP-100”)and summarized in Table V.

Public genomes: adding to ELSIThe practice of public genomics poses its own challenges,
especially for the organization and governance of humansubjects’ research, forcing us to critically reassess current
frameworks and practices. In order to pursue innovative
research in a responsible manner, the PGP has devel-

Eligibility
screening• Review and sign “mini-consent” form.
• Eligibility questionnaire about family circumstances and privacy preferences.
• Entrance exam to ensure informed consent; includes potential risks of participating, project protocols, and basic
genetics.
• Review of full PGP consent form.
• Submit information or delete account.

Preenrollment• Consent to participate.
• Collection of baseline trait data via questionnaire and a personal health record. Includes allergies,
immunizations, medical history, medications, physical traits and measurements, diet, ethnicity/ancestry, lifestyle,and environmental exposures.
• Participants asked to make a financial pledge (does not impact enrollment decisions).
• Identity verification and provision of mailing address.
• Submission of application for enrollment. Individuals selected to continue the enrollment process will receive anenrolment kit by mail, including saliva collection materials.

Enrollment• Participants may be interviewed by one or more PGP staff to verify identity and consent, confirm familiarity withstudy protocols, and/or review trait questionnaire responses. Blood samples, saliva sample, and/or skin cells may
be collected.
• Tissue samples prepared for DNA sequencing and other biological analyses.
• Participants opt-in to have their profiles made available on a publicly accessible Web site, or withdraw from thestudy.
• Establishment, distribution and analysis of cell lines for research.

• Information collected for 25 years. Participants can leave the study at any time.
Ongoing
participation • Data Safety Monitoring Board monitors the impacts of the PGP on enrolled participants. Quarterly emails
inquire about adverse events.
• Additional trait data and tissue samples may be requested periodically.
Table V. Overview of PGP study protocol.
Adapted from ref 52: Angrist M. Eyes wide open: the personal genome project, citizen science and veracity in informed consent. Pers Med. 2009;6:691-699.
Copyright © Future Medicine 2009

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oped a number of project-specific tools and resources
relevant to ELSI.
Open consent
The “open consent” model developed by the PGP is
designed to address the set of challenges associated withthe creation of datasets where it may be possible to identify individual participants with their genomic and otherdata. The open consent model assumes that, in such acontext, conventional assurances of anonymity, privacy
and confidentially are impossible and should not serveas any part of the foundation for the informed consent
protocol.72,73 Due to the structure of public genomics projects such as the PGP, and their associated datasets, while
privacy and confidentiality can be protected they cannot
and should not be guaranteed to participants. This practice ensures veracity, which we regard as a necessary—
though not sufficient—prerequisite for the exertion ofsubstantive autonomy. It is only through veracity that thecriteria underlying truly informed consent can be satisfied.
Open consent is therefore based on complete openness
and transparency with regard to all aspects of participation, including the potential for reidentification and thereality that there may be other risks that are unidentifiable at the time of consent. Predicting all potential risks
is by definition impossible and even a list of known possible risks is unlikely ever to be comprehensive.

Data sharing—and the risks of public genomes
The PGP’s informed consent process begins with anextensive pre-enrollment educational examination
designed to ensure a potential participant’s ability tounderstand the specific nature of the data collected andthe risks presented by public genomics research. For individuals who demonstrate the needed proficiency, the specific informed consent agreement that follows includes alengthy but “noncomprehensive list of hypothetical scenarios that could pose risks” for participants and theirfamilies (Table VI). Participants are warned that “the complete set and magnitude of the risks that the public availability of [your genomic data] poses to you and your relatives is not known at this time.” It is crucial thatparticipants understand that once identifying genetic andtrait data and tissues are released into the public domain
for the express intent of broad dissemination and use by
third parties it will be, in all likelihood, impossible to effecta meaningful retraction at a later date.
The PGP’s informed consent agreements and broader
study protocol are developed in continuous close interaction with the Harvard Medical School Committee on
Human Studies. The project is also overseen by an independent Data Safety Monitoring Board. Removing potentially disingenuous promises of anonymity, privacy, andconfidentiality, while seeking to comprehensively andopenly describe both known and unknown risks of participation, helps to ensure that research participants are as

Potential risks of participation in the PGP as described in the consent form (Abbreviated)• The risks of public disclosure of your genetic and trait information could affect your employment, insurance and financial well-being andsocial interactions for you and your family.
• Anyone with sufficient knowledge and resources could take your DNA sequence data and/or posted trait information and use that data,with or without modification, to: (i) infer paternity or other features of your genealogy; (ii) claim statistical evidence that could affect youremployment, insurance or ability to obtain financial services; (iii) claim relatedness to criminals or incriminate relatives; (iv) make synthetic
DNA and plant it at a crime scene, or otherwise use it to falsely identify you; or (v) reveal the possibility of a disease or unknown propensity
for a disease.
• Whether or not it is lawful to do so, you could be subject to actual or attempted employment, insurance, financial, or other forms of
discrimination or negative treatment on the basis of the public disclosure of your genetic and trait information by the PGP or by a third party.
• The distribution of your cell lines could result in the creation and further distribution by a third party of additional cell lines, organs, or
tissues containing your DNA for research, commercial, clinical, or other uses, including certain forms of assisted reproduction, some of which
you may find objectionable or upsetting.
• If you have previously made available or intend to make available genetic information in a confidential setting, for example in anotherresearch study or in a clinical trial, the data that you provide as part of the PGP may be used, on its own or in combination with yourpreviously shared data, to identify you as a participant in otherwise confidential genetic research or trials.
Table VI. Potential risks of participation.

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informed as possible about the nature of public genomics
research and, simultaneously, safeguards the trustworthiness of scientists and of scientific research in general.
Return of research data to participants
Research volunteers have been traditionally treated as“objects” of study who have no intrinsic rights to thedata generated by their participation.74 Today, we seethat study participants are increasingly asking for accessto their data75 and that available information and communication technologies have turned the return ofresearch results into a feasible option. While someresearchers adhere to the traditional viewpoint that
research subjects should not or cannot receive identifiable research data, some have suggested legal and ethical grounds for finding that researchers possess theobligation to inform their participants of certain results,
particularly when they are clinically actionable. 76
However, defining the scenarios in which research
results should be reported—and how to report such
results—remains a challenging issue. The medical, financial, and psychosocial risks of disclosing variants ofknown and unknown clinical significance require that acareful distinction be made between those variants inwhich convincing clinical observational data exists andthose in which disease association is less robust; a distinction that can influence both when and how to returnresults. Other concerns that have been voiced include
the uncertainty surrounding regulations governing thereturn of genomics research results directly to participants, the impact of false-positive and/or false-negative
results, as well as the “incidentalome,”77 and in the context of commercial direct-to-consumer testing, the concern that obtaining results could lead to a “raiding of the
medical commons.”78
As new models of genomic research and commerce
emerge, new mechanisms for communicating results toparticipants are also being explored. Many of these newmodels embrace a high level of involvement from their
participants and, in return, may rely on some combination of education, informed consent, and intermediation
to return data in a responsible fashion.79
The public genomics model adopted by the PGP utilizes
the first two approaches while foregoing the third, opting
to return data directly to research participants without
the required intervention of an intermediary. The advantages of direct data return and participant communica-

Dialogues in Clinical Neuroscience - Vol 12 . No. 1 . 2010tion are blunted by the partial shifting of the interpretative burden from the clinician to the researcher. The PGP
has approached this issue by focusing on data disclosure
via the Preliminary Research Report (PRR), which contains a noncomprehensive list of genetic variants present
in the participant’s DNA sequence data currently
thought to have a likelihood of clinical relevance amongindividuals possessing such variants.
This preliminary identification of potentially significant
variants is not intended to substitute in any way for professional medical advice, diagnosis or treatment. It leverages current knowledge by combining an evolving set offiltering algorithms and the use of existing variant databases— neither of which can be expected to have 100%
accuracy in identifying truly pathogenic variants given
the gaps in current scientific understanding. Participants
are specifically instructed to confirm any potentially significant findings in consultation with their health careprovider. It is possible that the increased rate of data
return from public genomics research—as well as fromcommercial providers of personal genomic data—will
help speed the creation of universal standards for clinical genomic interpretation that will help shift some of
the interpretative burden back away from publicgenomics researchers.

Outlook: the PGP from 10 to 100 000
After publishing initial data from its first 10 participantsin 2008, the PGP has continued to broaden the scope of
the information it is collecting and publishing while
simultaneously commencing the next stages of participant enrollment. From exome to whole-genome
sequence data, the development and release of the GETEvidenceBase tool80 for generation of Preliminary
Research Reports, and the publication of substantial
scholarship based on the PGP data generated to date,
the project’s progress has been substantial. The PGP is
now supported by PersonalGenomes.org, a 501(c)(3)non-profit charity that coordinates the international
efforts of the PGP with other collaborative publicgenomics research projects around the world. Both the
PGP and PersonalGenomes.org continue to strive todevelop and disseminate genomic technologies, phenotyping strategies, and knowledge on a global scale andto produce tangible and widely available improvementsin the understanding and management of human healthin a responsible fashion.

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Avances en el genoma personal:
desde el Proyecto Genoma Humano al
Proyecto Genoma Personal

Les progrès du génome personnel :de l’étude du génome humain à l’étude dugénome personnel

El costo de una secuencia del genoma humano diploide se ha
reducido desde cerca de 70 millones de dólares a 2000 dólares
desde 2007, aunque los estándares de la redundancia han
aumentado de 7 a 40 veces para mejorar los índices dedemanda de genotipo. Junto con el bajo retorno de inversión
para los polimorfismos de nucleótidos únicos comunes, esta
situación ha causado un aumento significativo del interés encorrelacionar las secuencias genómicas con una completa
información ambiental y de rasgos (GAR). El costo de las fichas
médicas electrónicas, de las imágenes y de la información
microbiológica, inmunológica y conductual también está
reduciéndose rápidamente. El compartir tal conjunto de información y sus interpretaciones con una diversidad de investigadores y sujetos de investigación pone de relieve la necesidad de contar con modelos de consentimiento informado
capaces de estar orientados hacia nuevos temas de privacidad
y otros, además de flexibilizar los recursos de datos compartidos que permitan disponer de materiales e información con
mínimas restricciones de uso. Este artículo examina el esfuerzodel Proyecto de Genoma Personal para desarrollar una basede datos de GAR como un recurso de genómica pública
ampliamente accesible tanto a investigadores como a participantes de las investigaciones, respetando los estándares máselevados de la ética de la investigación.

Le coût de séquençage d'un génome diploïde humain achuté de 70 millions de dollars à 2 000 dollars depuis 2007,
bien que les standards de redondance aient augmenté de 7
à 40 fois afin d'améliorer le taux d'identification des bases.
Associé au faible retour sur investissement des polymorphismes de simples nucléotides (SNP), cette situation expliquel’intérêt accru pour la corrélation des séquences des génomes
avec des données complètes environnementales et de traits(GET). Les coûts des enregistrements numériques médicaux,de l’imagerie et des données microbiennes, immunologiques
et comportementales chutent aussi rapidement. Le partagede telles bases de données GET intégrées et de leurs interprétations avec un grand nombre de chercheurs et de sujets
de recherche souligne la nécessité de modèles de consentement éclairé nécessaires à cette nouvelle protection des données personnelles et autres problématiques, en plus desbesoins de flexibilité des ressources requises pour le partage
des données, permettant en plus une utilisation peu restrictive de ces matériels et données. Cet article analyse les efforts
du Projet du Génome Personnel afin de développer une basede données GET en tant que ressource génomique publique,largement accessible à la fois aux chercheurs et aux participants à la recherche, tout en respectant les standards les plusélevés de l’éthique de la recherche.

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