Arabidopsis thaliana was the first plant genome to be fully sequenced, almost a quarter of a century ago, thanks to The Arabidopsis Genome Initiative, with contributions from scientists worldwide. This milestone was welcomed enthusiastically within the plant science community, for its potential in terms of fine understanding of biological processes. Since then, tens of genomes from other plant species, including staple crops, have been fully sequenced and annotated. However, for each sequenced plant genome, several genes still lack any assigned molecular activity, or their biological in vivo function has not yet been clarified. Here we show how transcript correlation analysis (TCA) has allowed us to identify novel candidate genes involved in iron (Fe) metabolism in plants, together with experimental validation of such predictions. This bioinformatics approach has also been applied to other plant metabolic pathways. Suggestions for exploitation of TCA for research into plant Fe and beyond is discussed.

Transcript correlation analysis for the identification of novel plant genes involved in iron metabolism and beyond: what next? / I. Murgia, P. Morandini. - In: PLANT BIOLOGY. - ISSN 1435-8603. - (2025), pp. 1-10. [Epub ahead of print] [10.1111/plb.70068]

Transcript correlation analysis for the identification of novel plant genes involved in iron metabolism and beyond: what next?

I. Murgia
;
P. Morandini
2025

Abstract

Arabidopsis thaliana was the first plant genome to be fully sequenced, almost a quarter of a century ago, thanks to The Arabidopsis Genome Initiative, with contributions from scientists worldwide. This milestone was welcomed enthusiastically within the plant science community, for its potential in terms of fine understanding of biological processes. Since then, tens of genomes from other plant species, including staple crops, have been fully sequenced and annotated. However, for each sequenced plant genome, several genes still lack any assigned molecular activity, or their biological in vivo function has not yet been clarified. Here we show how transcript correlation analysis (TCA) has allowed us to identify novel candidate genes involved in iron (Fe) metabolism in plants, together with experimental validation of such predictions. This bioinformatics approach has also been applied to other plant metabolic pathways. Suggestions for exploitation of TCA for research into plant Fe and beyond is discussed.
Arabidopsis thaliana; iron nutrition; metabolic pathways; Pearson's correlation coefficient; Transcript Correlation Analysis
Settore BIOS-02/A - Fisiologia vegetale
2025
2-lug-2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1200975
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