Back

Alfalfa varieties can weakly choose beneficial nitrogen-fixing bacteria from a population isolated from a single field

Guha, S.;Polo, M.;Paillan, E.;Sutherland, J.;Bingham, E.;Clouse, K.;Burghardt, L.

2026-06-15 Plant Biology
10.64898/2026.06.12.731664 bioRxiv
Show abstract

O_LIIn natural and agricultural systems, legumes recruit rhizobia from diverse soil populations to fix nitrogen in root nodules. A few legumes, including the model legume Medicago truncatula, can select and enrich beneficial rhizobia. Here, we investigated whether its perennial relative, Medicago sativa (alfalfa), a globally important forage crop, also possesses this ability. C_LIO_LIWe developed a genetically variable collection of 117 Sinorhizobium meliloti strains sampled from three field-grown alfalfa varieties, performed multi-strain and single-strain inoculations in a nitrogen-free greenhouse experiment across the same hosts, and evaluated plant benefits and relative strain fitness in nodules. C_LIO_LIAlfalfa varieties differed in which strains best promoted plant growth and which strains had high fitness in nodules. Regressing strain fitness and host benefit revealed that two of three alfalfa varieties selected and enriched more beneficial strains during symbiosis, though the strength of selection was weak. In alignment with these results, no variety produced as much biomass in mixed inoculation as it did with the best-performing single strain. C_LIO_LILegumes ability to enrich beneficial rhizobial populations from field-representative strain diversity warrants further study to develop optimized varieties. Ultimately, identifying crop varieties that naturally select for beneficial bacteria could reduce the need for repeated inoculant applications. C_LI

Matching journals

The top 10 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.