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Curation of the Deep Green list of unannotated green lineage proteins to enable structural and functional characterization

Knoshaug, E.; Sun, P.; Nag, A.; Nguyen, H.; Mattoon, E.; Zhang, N.; Liu, J.; Chen, C.; Cheng, J.; Zhang, R.; St. John, P. C.; Umen, J. G.

2022-10-03 plant biology
10.1101/2022.09.30.510186 bioRxiv
Show abstract

An explosion of sequenced genomes and predicted proteomes enabled by low cost deep sequencing has revolutionized biology. Unfortunately, protein functional annotation is more complex, and has not kept pace with the sequencing revolution. We identified unannotated proteins in three model organisms representing distinct parts of the green lineage (Viridiplantae); Arabidopsis thaliana (dicot), Setaria viridis (monocot), and Chlamydomonas reinhardtii (Chlorophyte alga). Using similarity searching we found the subset of unannotated proteins that were conserved between these species and defined them as Deep Green proteins. Informatic, genomic, and structural predictions were leveraged to begin inferring functional information about Deep Green genes and proteins. The Deep Green set was enriched for proteins with predicted chloroplast targeting signals that are predictive of photosynthetic or plastid functions. Strikingly, structural predictions using AlphaFold and comparisons to known structures show that a significant proportion of Deep Green proteins may possess novel protein tertiary structures. The Deep Green genes and proteins provide a starting resource of high value targets for further investigation of potentially new protein structures and functions that are conserved in the green lineage.

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