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In the mid-1980s, the united states department of Energy initiated a
number of projects to construct detailed genetic and physical maps of
the human genome, to determine its complete nucleotide sequence, and
to localize its estimated 100000 genes. Work on this scale required
the development of new computational methods for analysing genetic map
and DNA sequence data, and demanded the design of new techniques and
instrumentation for detecting and analysing DNA. To benefit the public
most effectively, the projects also necessitated the use of advanced
means of information dissemination in order to make the results
available as rapidly as possible to scientists and physicians. The
international effort arising from this vast initiative became known as
the human genome project.
Similar research efforts were also launched to map and sequence the
genomes of a variety of organisms used extensively in research labs as
model systems. In April 1998, although the sequencing projects of only
a small number of relatively small genomes had been completed, and the
human genome is not expected to be complete until after the year 2003,
the results of such projects were already beginning to pour into the
public sequence databases in overwhelming numbers.

Goals for Advancements in Sequencing Technology
DNA sequencing technology has improved dramatically since the genome
projects began. The amount of sequence produced each year is
increasing steadily; individual centers are now producing tens of
millions of base pairs of sequence annually. In the future, de novo
sequencing of additional genomes, comparative sequencing of closely
related genomes, and sequencing to assess variation within genomes
will become increasingly indispensable tools for biological and
medical research. Much more efficient sequencing technology will be
needed than is currently available. The incremental improvements made
to date have not yet resulted in any fundamental paradigm shifts.
Nevertheless, the current state-of-the-art technology can still be
significantly improved, and resources should be invested to accomplish
this. Beyond that, research must be supported on new technologies that
will make even higher throughput DNA sequencing efficient, accurate,
and cost-effective, thus providing the foundation for other advanced
genomic analysis tools. Progress must be achieved in three areas:
a) Continue to increase the throughput and reduce the cost of current
sequencing technology.
Increased automation, miniaturization, and integration of the
approaches currently in use, together with incremental, evolutionary
improvements in all steps of the sequencing process, are needed to
yield further increases in throughput (to at least 500 Mb of finished
sequence per year by 2003) and reductions in cost. At least a twofold
cost reduction from current levels (which average $0.50 per base for
finished sequence in large-scale centers) should be achieved in the
next 5 years. Production of the working draft of the human sequence
will cost considerably less per base pair.
b) Support research on novel technologies that can lead to significant
improvements in sequencing technology.
New conceptual approaches to DNA sequencing must be supported to
attain substantial improvements over the current sequencing paradigm.
For example, microelectromechanical systems (MEMS) may allow
significant reduction of reagent use, increase in assay speed, and
true integration of sequencing functions. Rapid mass spectrometric
analysis methods are achieving impressive results in DNA fragment
identification and offer the potential for very rapid DNA sequencing.
Other more revolutionary approaches, such as single-molecule
sequencing methods, must be explored as well. Significant investment
in interdisciplinary research in instrumentation, combining chemistry,
physics, biology, computer science, and engineering, will be required
to meet this goal. Funding of far-sighted projects that may require 5
to 10 years to reach fruition will be essential. Ultimately,
technologies that could, for example, sequence one vertebrate genome
per year at affordable cost are highly desirable.
c) Develop effective methods for the advanced development and
introduction of new sequencing technologies into the sequencing
process.
As the scale of sequencing increases, the introduction of improvements
into the production stream becomes more challenging and costly. New
technology must therefore be robust and be carefully evaluated and
validated in a high-throughput environment before its implementation
in a production setting. A strong commitment from both the technology
developers and the technology users is essential in this process. It
must be recognized that the advanced development process will often
require significantly more funds than proof-of-principle studies.
Targeted funding allocations and dedicated review mechanisms are
needed for advanced technology development.
Developing Technology to handle Sequence Variations
Natural sequence variation is a fundamental property of all genomes.
Any two haploid human genomes show multiple sites and types of
polymorphism. Some of these have functional implications, whereas many
probably do not. The most common polymorphisms in the human genome are
single base-pair differences, also called single-nucleotide
polymorphisms (SNPs). When two haploid genomes are compared, SNPs
occur every kilobase, on average. Other kinds of sequence variation,
such as copy number changes, insertions, deletions, duplications, and
rearrangements also exist, but at low frequency and their distribution
is poorly understood. Basic information about the types, frequencies,
and distribution of polymorphisms in the human genome and in human
populations is critical for progress in human genetics. Better
high-throughput methods for using such information in the study of
human disease are also needed.
SNPs are abundant, stable, widely distributed across the genome, and
lend themselves to automated analysis on a very large scale, for
example, with DNA array technologies. Because of these properties,
SNPs will be a boon for mapping complex traits such as cancer,
diabetes, and mental illness. Dense maps of SNPs will make possible
genome-wide association studies, which are a powerful method for
identifying genes that make a small contribution to disease risk. In
some instances, such maps will also permit prediction of individual
differences in drug response. Publicly available maps of large numbers
of SNPs distributed across the whole genome, together with technology
for rapid, large-scale identification and scoring of SNPs, must be
developed to facilitate this research.
a) Develop technologies for rapid, large-scale identification of SNPs
and other DNA sequence variants. The study of sequence variation
requires efficient technologies that can be used on a large scale and
that can accomplish one or more of the following tasks: rapid
identification of many thousands of new SNPs in large numbers of
samples. Although the immediate emphasis is on SNPs, ultimately
technologies that can be applied to polymorphisms of any type must be
developed. Technologies are also needed that can rapidly compare, by
large-scale identification of similarities and differences, the DNA of
a species that is closely related to one whose DNA has already been
sequenced. The technologies that are developed should be
cost-effective and broadly accessible.
b) Identify common variants in the coding regions of the majority of
identified genes Initially, association studies involving complex
diseases will likely test a large series of candidate genes;
eventually, sequences in all genes may be systematically tested. SNPs
in coding sequences (also known as cSNPs) and the associated
regulatory regions will be immediately useful as specific markers for
disease. An effort should be made to identify such SNPs as soon as
possible. Ultimately, a catalog of all common variants in all genes
will be desirable. This should be cross-referenced with cDNA sequence
data.
c) Create an SNP map of at least 100,000 markers. A publicly available
SNP map of sufficient density and informativeness to allow effective
mapping in any population is the ultimate goal. A map of 100,000 SNPs
(one SNP per 30,000 nucleotides) is likely to be sufficient for
studies in some relatively homogeneous populations, while denser maps
may be required for studies in large, heterogeneous populations. Thus,
during this 5-year period, the HGP authorities have planned to create
a map of at least 100,000 SNPs. If technological advances permit, a
map of greater density is desirable. Research should be initiated to
estimate the number of SNPs needed in different populations.
d) Develop the intellectual foundations for studies of sequence
variation. The methods and concepts developed for the study of
single-gene disorders are not sufficient for the study of complex,
multigene traits. The study of the relationship between human DNA
sequence variation, phenotypic variation, and complex diseases depends
critically on better methods. Effective research design and analysis
of linkage, linkage disequilibrium, and association data are areas
that need new insights. Questions such as which study designs are
appropriate to which specific populations, and with which population
genetics characteristics, must be answered. Appropriate statistical
and computational tools and rigorous criteria for establishing and
confirming associations must also be developed.
e) Create public resources of DNA samples and cell lines. To
facilitate SNP discovery it is critical that common public resources
of DNA samples and cell lines be made available as rapidly as
possible. To maximize discovery of common variants in all human
populations, a resource is needed that includes individuals whose
ancestors derive from diverse geographic areas. It should encompass as
much of the diversity found in the human population as possible.
Samples in this initial public repository should be totally anonymous
to avoid concerns that arise with linked or identifiable samples.
DNA samples linked to phenotypic data and identified as to their
geographic and other origins will be needed to allow studies of the
frequency and distribution of DNA polymorphisms in specific
populations and their relevance to disease. However, such collections
raise many ethical, legal, and social concerns that must be addressed.
Credible scientific strategies must be developed before creating these
resources.