Beyond the Genome

Hallam Stevens and Sarah S. Richardson

In the celebrations surrounding the completion of the Human Genome Project (HGP), few anticipated the bewildering developments that were to come. Expectations that the follow-up work would involve routine puzzle solving gave way to a series of surprising biological revelations. Debates over fundamental problems became more controversial and unsettled. Some important questions — which in the immediate aftermath of the HGP seemed near a solution — now, a decade on, seem even more difficult and mysterious.

The genome sequencing projects promised a future in which human traits would be linked to common genomic differences. Beginning in 2005, biologists began genotyping thousands of individuals, searching for correlations between single nucleotide polymorphisms and phenotypic traits. This technique for probing the meaning and function of the genome is known as the genome-wide association study (GWAS). To study obesity, for example, GWAS sampled thousands of obese individuals and thousands of nonobese individuals. If a particular mutation at location x occurred in a high fraction of obese people and a relatively low fraction of nonobese people, this suggested that location x might have something to do with obesity. This analysis was repeated for millions of locations on the genome, building up an overall picture of locations associated with particular traits.

By 2010, over seven hundred GWAS had been published on over four hundred different diseases and traits. As more and more studies were conducted, two trends began to appear. First, many traits — even traits that biologists might have supposed to be quite straightforward — turned out to be associated with hundreds or even thousands of locations on the genome. One 2010 study associated 180 distinct locations with human height. Second, even with all these locations taken together, the numbers just did not add up. With height, for instance, studies of monozygotic twins suggested that 80–90 percent of the variation in human height is heritable. However, using GWAS to measure the contribution of each location to the overall variability in height showed that the contribution of each location to the overall variation was very small. Adding up all the contributions of the hundreds of locations only accounted for about 13 percent of the overall variation in human height.

This persistent question of "missing heritability" has continued to dog genome research. Despite the many locations on the genome responsible for influencing particular traits or diseases, there does not seem to be "enough" to actually account for what is going on. Biologists have put forward numerous suggestions to explain what might be going wrong: rare variants, copy-number variations, network effects, environmental effects, and epigenetic effects. The evolutionary biologist Leonid Kruglyak argues that the problem is conceptual: "It's a possibility that there's something we just don't understand, that is so different from what we're thinking about that we're not thinking about it yet." Attempts to solve this problem have been a major motivation for studies of epigenetics and gene-environment interactions, as well as for projects to sequence large numbers of complete genomes (such as the 1000 Genomes Project). The missing heritability problem suggested that the working of the genome was far more complex than biologists hoped or expected it to be: traits and diseases seemed to depend on a mysterious set of unknown unknowns. This indicated the need not only for new experimental tools but also for a fundamental rethinking of the working of genes and genomes.

GWAS constitute only one of the promising developments within biology over the past decade. Yet, the kinds of problems they have encountered — more data, increasing complexity, greater uncertainties — are exemplary. Today, "postgenomics" is an increasingly prevalent term within the life sciences. Dozens of recent texts in bioinformatics, genetics, and medicine promise to situate research in these fields in "the postgenomic age." Biologists invoke the term "postgenomics" to signal powerful new methods and approaches to complex biological problems. Similarly, social science analysts of the life sciences use the term "postgenomic" to refer to widespread transformations said to be sweeping these fields since the completion of the major genome projects. A recent editorial in the Economist titled "Biology 2.0" predicted that "It seems quite likely that future historians of science will divide biology into the pre- and post-genomic eras."

This book aims to reflect on the postgenomic moment by posing a set of critical questions: What are the continuities and discontinuities between the postgenomic life sciences and previous biology? Which of the hopes and ambitions of the genome projects have been realized, and which have not? How does postgenomics transform fundamental conceptual debates in the life sciences, such as those over holistic versus genetic determinist approaches, biological and socio-environmental explanations, and how to conceptualize human racial and sexual differences? And how should we characterize the relationship between new high- throughput data technologies and new modes of postgenomic investigation?

Biology has come a very long way from the iconic 1992 moment when Walter Gilbert waved around a compact disk and asserted that the As, Ts, Cs, and Gs of the DNA sequences encoded on it were us. As the essays in this book demonstrate, science studies scholars examining the life sciences, too, are reimagining their role and refreshing their theoretical toolkits in the postgenomic age.

This book explores postgenomics as a live and evolving frame for discussions of changes and trends in the post-HGP life sciences. Following Richardson, we define postgenomics both temporally, as the period after the completion of the sequencing of the human genome, and technically, in reference to the advent of whole-genome technologies as a shared platform for biological research across many fields and...