Universality and predictability in molecular quantitative genetics

TL;DR

This paper discusses universal principles in molecular trait evolution, emphasizing how universal measurements can infer selection and predict evolutionary outcomes across lineages, advancing quantitative evolutionary systems biology.

Contribution

It introduces the concept of universal evolutionary characteristics of molecular traits that are independent of genetic basis, enabling inference of selection and predictability of evolution.

Findings

Universal measurements can infer selection on molecular traits.

Trait universality links to predictability of evolution across lineages.

Universal trait statistics apply across cellular scales.

Abstract

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.