Back

The palisade-specific gene IQD22 enhances photosynthetic capacity by phenocopying sun leaf architecture

Matthes, M. C.; Pennacchi, J.; Napier, J.; Kurup, S.

2022-08-28 plant biology
10.1101/2022.08.27.505449 bioRxiv
Show abstract

The world requires a rise in crop production which needs to be increased significantly in order to satisfy demand by 20501. However traditional plant breeding approaches are anticipated to fall short in delivering the increases in yield required and therefore targeted manipulation of plant metabolism is increasingly being pursued with the aim to achieve this goal2. Improving photosynthetic efficiency is predicted to have a significant influence on enhancing crop productivity and several ambitious genetic engineering projects are currently under way to achieve higher photosynthetic rates in crops3,4. A naturally evolved adaptive trait which allows plants to increase photosynthetic efficiency specifically under high light is the differentiation of sun leaves which are characterised by an increase in palisade cell layers and more elongated cells within this layer5. These morphological changes allow a more efficient distribution of light within the leaf and provide an increased cell surface to which chloroplasts can relocate thereby increasing the capacity for CO up-take6. Here we show that, surprisingly, this complex morphological trait can be phenocopied by the modulation of the expression of a single palisade specific gene, IQD22, in Arabidopsis. Furthermore, we could show that the architectural changes were reflected in an increase of photosynthetic rate of 30%. The simplicity with which we could enhance photosynthesis by phenocopying sun leave traits is in stark contrast to the complex and challenging metabolic engineering approaches currently being pursued.

Matching journals

The top 6 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.