# Assessing the opportunity for selection to impact morphological traits in crosses between two Solanum species

## TL;DR

This study explores how genetic factors influence morphological traits in crosses between two Solanum species to understand how traits respond to selection.

## Contribution

The study introduces a novel application of information-theoretic line cross analysis to estimate genetic architectures in interspecies Solanum crosses.

## Key findings

- Maternal and epistatic effects play a significant role in the genetic architecture of the studied traits.
- The genetic architecture of traits determines their accessibility to selection.
- Crosses between Solanum pennellii and S. lycopersicum reveal non-additive genetic effects for morphological traits.

## Abstract

Within biology, there have been long-standing goals to understand how traits impact fitness, determine the degree of adaptation, and predict responses to selection. One key step in answering these questions is to study the mode of gene action or genetic architecture of traits. The genetic architecture underlying a trait will ultimately determine whether selection can lead to a change in the phenotype. Theoretical and empirical research have shown that additive architectures are most responsive to selection. The genus Solanum offers a unique system to quantify the genetic architecture of traits. Crosses between Solanum pennellii and S. lycopersicum, which have evolved unique adaptive traits for very different environments, offer an opportunity to investigate the genetic architecture of a variety of morphological traits that often are not variable within species. We generated cohorts between strains of these two Solanum species and collected phenotypic data for eight morphological traits. The genetic architectures underlying these traits were estimated using an information-theoretic approach to line cross analysis. By estimating the genetic architectures of these traits, we were able to show a key role for maternal and epistatic effects and infer the accessibility of these traits to selection.