Comparative proteomic analyses of potato leaves from field-grown plants grown under extremely long days.
JSON
Resjö S, Willforss J, Large A, Siino V, Alexandersson E, Levander F, Andreasson E
Plant Physiol Biochem 215 (-) 109032 [2024-10-00; online 2024-08-10]
There are limited molecular data and few biomarkers available for studies of field-grown plants, especially for plants grown during extremely long days. In this study we present quantitative proteomics data from 3 years of field trials on potato, conducted in northern and southern Sweden and analyze over 3000 proteins per year of the study and complement the proteomic analysis with metabolomic and transcriptomic analyses. Small but consistent differences linked to the longer days (an average of four more hours of light per day) in northern Sweden (20 h light/day) compared to southern Sweden can be observed, with a high correlation between the mRNA determined by RNA-seq and protein abundances. The majority of the proteins with differential abundances between northern and southern Sweden could be divided into three groups: metabolic enzymes (especially GABA metabolism), proteins involved in redox metabolism, and hydrolytic enzymes. The observed differences in metabolic enzyme abundances corresponded well with untargeted metabolite data determined by GC and LC mass-spectrometry. We also analyzed differences in protein abundance between potato varieties that performed relatively well in northern Sweden in terms of yield with those that performed relatively less well. This comparison indicates that the proteins with higher abundance in the high-yield quotient group are more anabolic in their character, whereas the proteins with lower abundance are more catabolic. Our results create a base of information about potato "field-omics" for improved understanding of physiological and molecular processes in field-grown plants, and our data indicate that the potato plant is not generally stressed by extremely long days.
NGI Uppsala (SNP&SEQ Technology Platform) [Service]
National Genomics Infrastructure [Service]
PubMed 39181085
DOI 10.1016/j.plaphy.2024.109032
Crossref 10.1016/j.plaphy.2024.109032
pii: S0981-9428(24)00700-9