Multiple-line inference of selection on quantitative traits

TL;DR

This paper introduces a new population-genetic test using multiple-line crosses to detect and distinguish lineage-specific selection on quantitative traits, significantly improving detection power and scope.

Contribution

The authors develop a novel multiple-line cross test for selection on quantitative traits, enhancing detection sensitivity and enabling differentiation of lineage-specific selection scenarios.

Findings

Multiple-line test detects selection with higher significance.

The test distinguishes different lineage-specific selection patterns.

Application reveals lineage-specific selection in plant traits.

Abstract

Trait differences between species may be attributable to natural selection. However, quantifying the strength of evidence for selection acting on a particular trait is a difficult task. Here we develop a population-genetic test for selection acting on a quantitative trait which is based on multiple-line crosses. We show that using multiple lines increases both the power and the scope of selection inference. First, a test based on three or more lines detects selection with strongly increased statistical significance, and we show explicitly how the sensitivity of the test depends on the number of lines. Second, a multiple-line test allows to distinguish different lineage-specific selection scenarios. Our analytical results are complemented by extensive numerical simulations. We then apply the multiple-line test to QTL data on floral character traits in plant species of the Mimulus genus and on photoperiodic traits in different maize strains, where we find a signatures of lineage-specific selection not seen in a two-line test.