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Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.)

Authors :
Zhu Yang
Wenjie Kan
Ziqi Wang
Caiguo Tang
Yuan Cheng
Dacheng Wang
Yameng Gao
Lifang Wu
Source :
Frontiers in Plant Science, Vol 15 (2025)
Publication Year :
2025
Publisher :
Frontiers Media S.A., 2025.

Abstract

Phytochromes are essential photoreceptors in plants that sense red and far-red light, playing a vital role in regulating plant growth and development through light signal transduction. Despite extensive research on phytochromes in model plants like Arabidopsis and rice, they have received relatively little attention in wheat. In this study, we employed bioinformatics methods to identify eight TaAkPHY genes in the Aikang58 wheat variety. Based on gene structure, conserved domains, and phylogenetic relationships, the TaAkPHY gene family exhibits a high degree of conservation. Synteny analysis revealed the evolutionary history of the PHY genes in Aikang58 and Chinese Spring wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), rice (Oryza sativa L.), maize (Zea mays L.), quinoa (Chenopodium quinoa Willd.), soybean [Glycine max (L.) Merr.], and Arabidopsis [Arabidopsis thaliana (L.) Heynh.]. Among these species, wheat is most closely related to barley, followed by rice and maize. The cis-acting element analysis indicates that the promoter regions of TaAkPHY genes contain a large number of CAT-box, CGTCA-motif, GC-motif, etc., which are mainly involved in plant development, hormone response, and stress response. Gene expression profiling demonstrated that TaAkPHY genes exhibit varying expression levels across different tissues and are induced by various stress conditions and plant hormone treatments. Co-expression network analysis suggested that TaAkPHY genes may specifically regulate downstream genes associated with stress responses, chloroplast development, and circadian rhythms. Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. This method helps to quickly extract key influencing factors from a large amount of complex data. Overall, these findings provide new insights into the role of phytochromes in wheat growth, development, and stress responses, laying a foundation for future research on phytochromes in wheat.

Details

Language :
English
ISSN :
1664462X
Volume :
15
Database :
Directory of Open Access Journals
Journal :
Frontiers in Plant Science
Publication Type :
Academic Journal
Accession number :
edsdoj.800b661cfbbd46879f69ed06c98dd5da
Document Type :
article
Full Text :
https://doi.org/10.3389/fpls.2024.1520457