Characterisation and expression profiles of the NPF gene family in Cannabis sativa L. under low nitrogen
Year: 2026
Type: article
Abstract: BACKGROUND: The Nitrate transporter1/peptide transporter family (NPF) affects nitrate use efficiency (NUE) by regulating plant nitrate absorption and distribution. Many NPF-related genes identified across various crops have been shown to improve NUE. However, the characteristics of NPF in cannabis sativa L. and their functions remain unclear. RESULTS: In this study, 66 NPF genes of hemp (Cannabis sativa L.) were identified from the pink pepper genome. The phylogenetic analysis showed that these genes could be divided into eight subfamilies. The NPF genes of Cannabis sativa were renamed according to their chromosomal locations and characterised through bioinformatic analysis. Transcriptome analysis of roots from two hemp varieties with distinct NUE under two nitrogen concentrations (2-hour treatment) showed varied expression patterns across all NPF genes. Among those with higher expression levels, quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis successfully screened out two candidate genes, CsNPF4.3 and CsNPF5.14, as potentially involved in NUE regulation. CONCLUSIONS: This work deepens our understanding of the gene structure and expression of NPF genes in hemp, and their roles in nitrate response, paving the way for improving hemp nitrogen efficiency through molecular breeding. Altogether, these findings suggest that the expansion of these gene families in hemp could provide valuable genetic variability for identifying NUE-related candidate genes in future breeding programs in the context of low-impact, sustainable agriculture.
Source: BMC Plant Biology
Authors: Zhao Yue, Wang Huiquan, Chu Peiyu, Sarahani Harun, Wang Xiaonan, Jei Vincent, Xu Lei, Zeti-Azura Mohamed-Hussein
Language: English
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $3,090
Funder: Heilongjiang Academy of Sciences
OpenAlex ID: W7164906390
