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.
Universality and predictability in molecular quantitative genetics
Armita Nourmohammad,Torsten Held,M. Lässig
Published 2013 in bioRxiv
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- Publication year
2013
- Venue
bioRxiv
- Publication date
2013-09-12
- Fields of study
Biology, Medicine
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Semantic Scholar, PubMed
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