Back

Genome size variation is attributed to adaptive purging of transposable elements

Potapenko, E. V.; Hubner, S. V.; Shermeister, B.; Mandel, T.

2025-09-28 evolutionary biology
10.1101/2025.09.26.678839 bioRxiv
Show abstract

A substantial variation in genome size has been observed among individuals of the same species. Theory predicts that increased genome size may confer an advantage in populations with small effective size. However, contradictory evidence for the correlation with environmental variation, and limited understanding of the underlying genetic mechanisms, has cast doubts on the adaptive role of genome size variation. To address this, we studied two Hordeum species which were collected at the same sites along a wide range of environments but different in life habit (annual/perrenial) and mating strategy (self/out-crossing). We observed significant variation in genome size, with differences of up to 10% consistently detected in both species. Mating system influenced only the proportion of variation maintained within populations but not the overall range of genome size. In both species, drought emerged as the primary environmental factor associated with genome expansion, with transposable elements (TE) accumulation identified as the main driver of this expansion. Genome-wide association studies revealed that TE silencing is the key mechanism regulating genome size, and that selection favors smaller genomes among individuals growing at suitable habitats. Under increasingly stressful conditions, the regulation of TE activity fades, leading to TE accumulation and genome expansion, thereby increasing genetic variation available for selection. This integrative study provides a comprehensive view of how genome size is regulated in natural populations and highlights its exaptive role in inducing genetic variation under environmental stress.

Matching journals

The top 5 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.