Back

Transposable element activity and polymorphisms drive structural variability within and between individual in bivalves

Martelossi, J.; Luchetti, A.; Suh, A.; Ghiselli, F.; Peona, V.

2026-02-11 evolutionary biology
10.64898/2026.02.10.705023 bioRxiv
Show abstract

Structural variants (SVs) represent one of the most abundant sources of genetic variation across eukaryotes, with transposable elements (TEs) standing out as primary contributors in their emergence. While the growing availability of chromosome-scale genomes has revealed the central role of SVs in species diversification and adaptation, non-model invertebrates remain critically understudied in this context. Here, we explore how SVs and their interaction with TEs shape genetic diversity at both the individual and population levels. To achieve this, we leverage four high-quality oyster genomes and a large-scale dataset of the Estuarine oyster (Crassostrea ariakensis) collected across a wide range of different temperature and salinity conditions. We explicitly account for strengths and limitations of current SV-calling software, and benchmark our results through simulations. We uncover pervasive within-individual structural variability, with up to 14% of oyster genome basepairs being in an hemizygous state. The strong enrichment of TEs within these SVs is driven by a prevalence of insertions over deletions, reflecting population-level TE activity. Strikingly, both SVs and de novo TE insertions -- driven by the concurrent mobilization of diverse TE families -- segregate among C. ariakensis populations and contribute to genomic differentiation associated with local adaptation to contrasting sea salinity and temperature levels. Our study demonstrates the power of integrating long- and short-read sequencing to recover a high-confidence catalogue of SVs and de novo TE insertions, and provides empirical evidence that structural variation is an active evolutionary force generating potentially adaptive genetic variation in a key lineage of ecologically and economically important bivalves.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.