Study Explores the Promises and Pitfalls of Evolutionary Genomics
Published:14 Sep.2022 Source:Arizona State University
A new study examines mathematical models designed to draw inferences about how evolution operates at the level of populations of organisms. The study concludes that such models must be constructed with the greatest care, avoiding unwarranted initial assumptions, weighing the quality of existing knowledge and remaining open to alternate explanations. Such theoretical frameworks may offer compelling but ultimately flawed pictures of how evolution actually acts on populations over time, be these populations of bacteria, shoals of fish, or human societies and their various migrations during prehistory.
The study can provide guidance for future research. Together, they describe a range of criteria that can be used to better ensure the accuracy of models that produce statistical inferences in population genomics -- a scientific discipline concerned with large-scale comparisons of DNA sequences within and across populations and species. One of the key messages is the importance of considering the contributions of evolutionary processes certain to be in constant operation (such as purifying selection and genetic drift), before simply relying on hypothesized or rare evolutionary processes as the primary drivers of observed population variation (such as positive selection).