# Powerful one-dimensional scan to detect heterotic quantitative trait loci

## TL;DR

This paper introduces a new method to efficiently detect genetic factors contributing to increased crop yields through hybrid vigor.

## Contribution

The novel hQTL-ODS method enables efficient detection of heterotic quantitative trait loci by reducing computational complexity.

## Key findings

- hQTL-ODS reduces computational time while maintaining high power and low false-positive rates.
- Application to wheat hybrids reveals key epistatic hubs influencing grain yield heterosis.
- Cumulative epistatic effects are pervasive in determining heterosis for grain yield.

## Abstract

To meet the growing global demand for food, increasing yields through heterosis in agriculture is crucial. A deep understanding of the genetic basis of heterosis has led to the development of a quantitative genetic framework that incorporates both dominance and epistatic effects. However, incorporating all pairwise epistatic interactions is computationally challenging due to the large sequencing depth and population sizes needed to uncover the genes behind complex traits. In this study, we develop hQTL-ODS, a one-dimensional scanning method that directly assesses the net contribution of each quantitative trait locus to heterosis. Simulations show that hQTL-ODS reduces computational time while offering higher power and lower false-positive rate. We apply this method to a population of 5243 wheat hybrids with whole-genome sequenced profile, revealing key epistatic hubs that play a critical role in determining heterosis.

Enhanced performance of offspring compared to their parents is termed heterosis. This study presents a powerful and computationally efficient tool for detecting heterotic quantitative trait loci. Applying it to a large hybrid wheat dataset reveals pervasive cumulative epistatic effects for grain yield heterosis.