Biology Reference
In-Depth Information
modest cost, and within the time frame of a small experiment. In other
words, next-gen may have the effect of recentering biological work on
the individual investigator and the individual lab. The Personal Genome
Machine may make biology “personal” once again.
Anne Wojcicki of 23andMe has spoken about how rapid and large-
scale sequencing projects might overhaul the biomedical research pro-
cess. Rather than writing research grants and waiting for funding from
the NIH, 23andMe aims to become a “research engine” in its own right.
The amount of genomic data already accumulated from its customers
allows researchers at 23andMe enough statistical power to pose and
answer signifi cant biomedical questions. By surveying its customers
online about their habits, diseases, or family histories, 23andMe can
rapidly generate statistical associations between phenotypes and genetic
loci.
7
This kind of crowd-sourced genome-wide association study poses
a range of ethical dilemmas,
8
but it once again suggests the potential
of cheap and large-scale sequencing to transform research practices:
large-scale sequencing centers requiring massive funding and central-
ized planning might give way to cheaper, more widely distributed forms
of research. The who, where, and how of research is shifting rapidly.
This observation also reminds us that next-generation sequencing
is—for the most part—strongly driven by commercial considerations
(the exception is the work of George Church at Harvard Medical
School). It is fi rmly a part of the highly competitive biotech world.
Therefore, it also generates the possibility for further entanglement of
commercial enterprise with basic science—commercial considerations
could become central to the biological enterprise, structuring the types
of work and the knowledge made from it. Next generation sequencing
could contribute to the creation of the new kinds of value and new
kinds of accounting that I have tracked here.
But next-gen may also entail shifts in how biologists understand or-
ganisms. One possibility is that it may allow biologists to understand the
genome as a more dynamic object. At least at present, next-generation
machines are used largely to generate short reads of DNA and RNA,
providing snapshots of all the species of sequence inside a cell at a par-
ticular instant. Rather than simply allowing the sequencing of more and
more complete genomes, next-gen is opening up possibilities for see-
ing cellular processes in action. Combined with the bioinformatic tools
that have been described here, this shift opens up more possibilities for
drawing genomic, transcriptomic, and epigenomic elements into new
relationships with one another, studying them not as static elements, but
as dynamically interacting parts. In other words, next-gen may gener-
