Black sheep, dark horses, and colorful dogs: a review on the current state of the Gene Ontology with respect to iron homeostasis in Arabidopsis thaliana

Cellular homeostasis of the micronutrient iron is highly regulated in plants and responsive to nutrition, stress, and developmental signals. Genes for iron management encode metal and other transporters, enzymes synthesizing chelators and reducing substances, transcription factors, and several types of regulators. In transcriptome or proteome datasets, such iron homeostasis-related genes are frequently found to be differentially regulated. A common method to detect whether a specific cellular pathway is affected in the transcriptome data set is to perform Gene Ontology (GO) enrichment analysis. Hence, the GO database is a widely used resource for annotating genes and identifying enriched biological pathways in Arabidopsis thaliana. However, iron homeostasis-related GO terms do not consistently reflect gene associations and levels of evidence in iron homeostasis. Some genes in the existing iron homeostasis GO terms lack direct evidence of involvement in iron homeostasis. In other aspects, the existing GO terms for iron homeostasis are incomplete and do not reflect the known biological functions associated with iron homeostasis. This can lead to potential errors in the automatic annotation and interpretation of GO term enrichment analyses. We suggest that applicable evidence codes be used to add missing genes and their respective ortholog/paralog groups to make the iron homeostasis-related GO terms more complete and reliable. There is a high likelihood of finding new iron homeostasis-relevant members in gene groups and families like the ZIP, ZIF, ZIFL, MTP, OPT, MATE, ABCG, PDR, HMA, and HMP. Hence, we compiled comprehensive lists of genes involved in iron homeostasis that can be used for custom enrichment analysis in transcriptomic or proteomic studies, including genes with direct experimental evidence, those regulated by central transcription factors, and missing members of small gene families or ortholog/paralog groups. As we provide gene annotation and literature alongside, the gene lists can serve multiple computational approaches. In summary, these gene lists provide a valuable resource for researchers studying iron homeostasis in A. thaliana, while they also emphasize the importance of improving the accuracy and comprehensiveness of the Gene Ontology.

Comparative Transcriptomics of Lowland Rice Varieties Uncovers Novel Candidate Genes for Adaptive Iron Excess Tolerance

Iron (Fe) toxicity is a major challenge for plant cultivation in acidic waterlogged soil environments, where lowland rice is a major staple food crop. Only few studies have addressed the molecular characterization of excess Fe tolerance in rice, and these highlight different mechanisms for Fe tolerance. Out of 16 lowland rice varieties, we identified a pair of contrasting lines, Fe-tolerant Lachit and -susceptible Hacha. The two lines differed in their physiological and morphological responses to excess Fe, including leaf growth, leaf rolling, reactive oxygen species generation and Fe and metal contents. These responses were likely due to genetic origin as they were mirrored by differential gene expression patterns, obtained through RNA sequencing, and corresponding gene ontology term enrichment in tolerant vs. susceptible lines. Thirty-five genes of the metal homeostasis category, mainly root expressed, showed differential transcriptomic profiles suggestive of an induced tolerance mechanism. Twenty-two out of these 35 metal homeostasis genes were present in selection sweep genomic regions, in breeding signatures, and/or differentiated during rice domestication. These findings suggest that Fe excess tolerance is an important trait in the domestication of lowland rice, and the identified genes may further serve to design the targeted Fe tolerance breeding of rice crops.

Cytokinin-promoted secondary growth and nutrient storage in the perennial stem zone of Arabis alpina

Perennial plants maintain their lifespan through several growth seasons. Arabis alpina serves as a model Brassicaceae species to study perennial traits. Lateral stems of A. alpina have a proximal vegetative zone with a dormant bud zone and a distal senescing seed-producing inflorescence zone. We addressed how this zonation is distinguished at the anatomical level, whether it is related to nutrient storage and which signals affect the zonation. We found that the vegetative zone exhibits secondary growth, which we termed the perennial growth zone (PZ). High-molecular-weight carbon compounds accumulate there in cambium and cambium derivatives. Neither vernalization nor flowering were requirements for secondary growth and the sequestration of storage compounds. The inflorescence zone with only primary growth, termed the annual growth zone (AZ), or roots exhibited different storage characteristics. Following cytokinin application cambium activity was enhanced and secondary phloem parenchyma was formed in the PZ and also in the AZ. In transcriptome analysis, cytokinin-related genes represented enriched gene ontology terms and were expressed at a higher level in the PZ than in the AZ. Thus, A. alpina primarily uses the vegetative PZ for nutrient storage, coupled to cytokinin-promoted secondary growth. This finding lays a foundation for future studies addressing signals for perennial growth.

Iron homeostasis in Arabidopsis thaliana: transcriptomic analyses reveal novel FIT-regulated genes, iron deficiency marker genes and functional gene networks

BACKGROUND

FIT (FER-LIKE IRON DEFICIENCY-INDUCED TRANSCRIPTION FACTOR) is the central regulator of iron uptake in Arabidopsis thaliana roots. We performed transcriptome analyses of six day-old seedlings and roots of six week-old plants using wild type, a fit knock-out mutant and a FIT over-expression line grown under iron-sufficient or iron-deficient conditions. We compared genes regulated in a FIT-dependent manner depending on the developmental stage of the plants. We assembled a high likelihood dataset which we used to perform co-expression and functional analysis of the most stably iron deficiency-induced genes.

RESULTS

448 genes were found FIT-regulated. Out of these, 34 genes were robustly FIT-regulated in root and seedling samples and included 13 novel FIT-dependent genes. Three hundred thirty-one genes showed differential regulation in response to the presence and absence of FIT only in the root samples, while this was the case for 83 genes in the seedling samples. We assembled a virtual dataset of iron-regulated genes based on a total of 14 transcriptomic analyses of iron-deficient and iron-sufficient wild-type plants to pinpoint the best marker genes for iron deficiency and analyzed this dataset in depth. Co-expression analysis of this dataset revealed 13 distinct regulons part of which predominantly contained functionally related genes.

CONCLUSIONS

We could enlarge the list of FIT-dependent genes and discriminate between genes that are robustly FIT-regulated in roots and seedlings or only in one of those. FIT-regulated genes were mostly induced, few of them were repressed by FIT. With the analysis of a virtual dataset we could filter out and pinpoint new candidates among the most reliable marker genes for iron deficiency. Moreover, co-expression and functional analysis of this virtual dataset revealed iron deficiency-induced and functionally distinct regulons.