Back

NK cell receptor repertoires evolve under increased constraint butare not more diverse in menstruating mammals

Lavergne, C.; Daunesse, M.; BERTHELOT, C.

2026-03-06 evolutionary biology
10.64898/2026.03.05.709850 bioRxiv
Show abstract

The immune system plays key roles in the mammalian uterine cycle, particularly for menstruation, a dramatic tissue renewal mechanism independently acquired four times in eutherians. These roles specifically involve NK cells through the expression of KIR and KLR surface receptors, respectively part of the immunoglobulin-like and lectin-like gene superfamilies with poorly resolved phylogenetic histories. Acquisition of menstruation in primates reportedly coincides with a large expansion of the KIR family, suggesting that gains and losses in NK cell receptor families may have been crucial for the evolution of menstruation. To test this hypothesis, we performed an in-depth analysis of the evolutionary histories of the KIR and KLR gene families across 41 mammalian genomes, including all four clades that acquired menstruation. Our results reveal the existence of undescribed KIR and KLR genes across many mammalian species, including elephants, armadillos, rhinoceroses, and leaf-nosed bats, as well as a novel subfamily within the KLR phylogeny. Altogether, we identify more than twice as many NK cell receptor genes across mammals than currently reported in reference genomes. Further, we show that the KIR gene family has experienced intensified selection in menstruating species compared non-menstruating species, suggesting specific evolutionary pressures related to menstruation. Our data however do not support that menstruation coincides with expansions or contractions in NK cell receptor repertoires, even in primates, invalidating a current hypothesis regarding how menstruation evolved.

Matching journals

The top 3 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.