According to evolutionary biologist Patrick Phillips at the University of Oregon in Eugene, projects such as ENCODE are showing scientists that they don't really understand how genotypes map to phenotypes, or how exactly evolutionary forces shape any given genome.
The ENCODE findings join several other discoveries in unsettling old assumptions. For example, epigenetic molecular alterations to DNA, such as the addition of a methyl group, can affect the activity of genes without altering their nucleotide sequences. Many of these regulatory chemical markers are inherited, including some that govern susceptibility to diabetes and cardiovascular disease. Genes can also be regulated by the spatial organization of the chromosomes, in turn affected by epigenetic markers. Although such effects have long been known, their prevalence may be much greater than previously thought.
Another source of ambiguity in the genotype–phenotype relationship comes from the way in which many genes operate in complex networks. For example, many differently structured gene networks might result in the same trait or phenotype. Also, new phenotypes that are viable and potentially superior may be more likely to emerge through tweaks to regulatory networks than through more risky alterations to protein-coding sequences. In a sense this is still natural selection pulling out the best from a bunch of random mutations, but not at the level of the DNA sequence itself.
One consequence of this complex genotype–phenotype relationship is that it may impose constraints on natural selection. If the same phenotypes can result from many similarly structured gene networks, it might take a long time for a 'fitter' phenotype to arise. Alternatively, mutations may accumulate, free from selective 'weeding', thanks to the robustness of networks in maintaining a particular phenotype. Such hidden variation might be unmasked by some new environmental stress, enabling fresh adaptations to emerge. These sorts of constraints and opportunities are poorly understood; evolutionary theory does not help biologists to predict what kinds of genetic network they should expect to see in any one context.
Researchers are also still not agreed on whether natural selection is the dominant driver of genetic change at the molecular level. Evolutionary geneticist Michael Lynch of Indiana University Bloomington has shown through modeling that random genetic drift can play a major part in the evolution of genomic features, for example the scattering of non-coding sections, called introns, through protein-coding sequences. He has also shown that rather than enhancing fitness, natural selection can generate a redundant accumulation of molecular 'defenses', such as systems that detect folding problems in proteins. At best, this is burdensome. At worst, it can be catastrophic.
In short, the current picture of how and where evolution operates, and how this shapes genomes, is something of a mess. That should not be a criticism, but rather a vote of confidence in the healthy, dynamic state of molecular and evolutionary biology.
A problem shared
Barely a whisper of this vibrant debate reaches the public. Take evolutionary biologist Richard Dawkins' description in Prospect magazine last year of the gene as a replicator with “its own unique status as a unit of Darwinian selection”. It conjures up the decades-old picture of a little, autonomous stretch of DNA intent on getting itself copied, with no hint that selection operates at all levels of the biological hierarchy, including at the supraorganismal level, or that the very idea of 'gene' has become problematic.
Why this apparent reluctance to acknowledge the complexity? One roadblock may be sentimentality. Biology is so complicated that it may be deeply painful for some to relinquish the promise of an elegant core mechanism. In cosmology, a single, shattering fact (the Universe's accelerating expansion) cleanly rewrote the narrative. But in molecular evolution, old arguments, for instance about the importance of natural selection and random drift in driving genetic change, are now colliding with questions about non-coding RNA, epigenetics and genomic network theory. It is not yet clear which new story to tell.