BiologyEnvironmental ScienceMedicine

Katarina C. Stuart, Rebekah A. Oomen, Anna Tigano, Maren Wellenreuther, Jana R. Wold, David L Field, C. Mérot

2026.1.1MOLECULAR ECOLOGY

DOI: 10.1111/mec.70216

tlooto Summary

This review provides the necessary fundamentals to help researchers generate and analyse population‐level SV data, and examines the heterogeneous nature of SV properties that should be considered when studying them in ecology and evolution.

Abstract

Whole‐genome sequencing (WGS) has greatly expanded researchers' ability to study structural variants (SVs), that is, the variation in the presence, number, orientation or position of a DNA sequence. This has paved the way to study the eco‐evolutionary dynamics of SVs across the tree of life and within a population genomics framework. In this review, we provide the necessary fundamentals to help researchers generate and analyse population‐level SV data. We discuss the unique properties of different SV groups and how these fundamental differences interact with important biological and evolutionary processes using both empirical results and theory. This includes discussion of unresolved issues around SVs, such as technical difficulties in identification, accounting for diversity and evaluating functional effects. We explicitly integrate into this discussion transposable elements, which are an important component of SVs often identified in population‐level variant data. Finally, we focus on the practical side of SV analysis, offering a framework for SV identification and data analysis. In particular, we examine the heterogeneous nature of SV properties (type, length, sequence identity) that should be considered when studying them in ecology and evolution. This review aims to provide resources and guidelines to help researchers navigate the complexities of a relatively new field of eco‐evolutionary genomics research.

Citation format

STUART, Katarina C., et al. A beginner's guide to structural variants in eco‐evolutionary population genomics. MOLECULAR ECOLOGY, 2026, 35(2): e70216.