  Molecular traits, such as gene expression levels or protein binding
affinities, are increasingly accessible to quantitative measurement by modern
high-throughput techniques. Such traits measure molecular functions and, from
an evolutionary point of view, are important as targets of natural selection.
We review recent developments in evolutionary theory and experiments that are
expected to become building blocks of a quantitative genetics of molecular
traits. We focus on universal evolutionary characteristics: these are largely
independent of a trait's genetic basis, which is often at least partially
unknown. We show that universal measurements can be used to infer selection on
a quantitative trait, which determines its evolutionary mode of conservation or
adaptation. Furthermore, universality is closely linked to predictability of
trait evolution across lineages. We argue that universal trait statistics
extends over a range of cellular scales and opens new avenues of quantitative
evolutionary systems biology.
