Screening and validation of reference genes for quantitative real-time PCR in <i>Polygonatum hunanense</i>

<italic>Polygonatum hunanense</italic> H.H. Liu &amp; B.Z. Wang (syn. <italic>P. kingianum</italic> var. <italic>grandifolium</italic>), is a perennial Liliaceae species with ethnopharmaceutical and nutraceutical value. It exhibits traditional medicinal properties such as qi-tonifying, yin-nourishing, kidney-benefiting, and antioxidant activities. <italic>P. hunanense</italic> maintains evergreen foliage year-round and shows significantly higher biomass accumulation than congener taxa. These traits are linked to phytohormone regulation, as indicated by previous studies. The absence of validated reference genes in <italic>P. hunanense</italic> has hindered molecular-level investigations in this species to date. In this study, 11 candidate reference genes (<italic>GAPDH</italic>, <italic>H2A</italic>, <italic>EF-1α</italic>, <italic>ACT</italic>, <italic>TUA</italic>, <italic>UBC</italic>, <italic>RPL</italic>, <italic>PP2A</italic>, <italic>18S</italic>, <italic>TUB</italic>, and <italic>UBQ</italic>) were identified from the <italic>P. hunanense</italic> transcriptome dataset. Expression profiles of these genes were analyzed by qRT-PCR across three experimental conditions: different tissues, hormone treatments, and abiotic stresses. Gene expression stability was analyzed using GeNorm, NormFinder, Delta Cᴛ, BestKeeper, and RefFinder software. The stability of candidate reference genes was validated through expression analysis of target genes (<italic>KO</italic>, <italic>KAM</italic>, <italic>GA13-ox</italic>, <italic>GA44-dio</italic>, <italic>ALDH7A1</italic>, <italic>IPM</italic>) involved in phytohormone metabolic pathways. Overall, the stability of the 11 candidate reference genes varied among different <italic>P. hunanense</italic> samples. <italic>EF-1α</italic>, <italic>18S</italic> and <italic>ACT</italic> were identified as the most stable in tissue samples. <italic>EF-1α</italic>, <italic>H2A</italic> and <italic>PP2A</italic> showed the highest stability under hormone treatments, and <italic>18S</italic>, <italic>UBC,</italic> and <italic>EF-1α</italic> exhibited consistent stability in abiotic stresses. This study establishes <italic>EF-1α</italic> as the optimal pan-experimental reference gene for qRT-PCR normalization in <italic>P. hunanense</italic>, demonstrating consistent expression stability across diverse tissues, hormone treatments, and abiotic stresses, thereby providing a significant reference for future gene expression studies.

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Journal
Medicinal Plant Biology
Published
2025-01-01
DOI
https://doi.org/10.48130/mpb-0025-0018
Primary Topic
Molecular Biology Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Screening and validation of reference genes for quantitative real-time PCR in Polygonatum hunanense

Runcheng Zhang, Caiyun Peng, Luyun Ning, Qian Xiao et al.
Medicinal Plant Biology
Molecular Biology Techniques and Applications
article

Screening and validation of reference genes for quantitative real-time PCR in Polygonatum hunanense

Runcheng Zhang, Caiyun Peng, Luyun Ning, Qian Xiao, Qin Xia, Limin Gong, Chensi Tan, Wei Wang
article en

Abstract

<italic>Polygonatum hunanense</italic> H.H. Liu &amp; B.Z. Wang (syn. <italic>P. kingianum</italic> var. <italic>grandifolium</italic>), is a perennial Liliaceae species with ethnopharmaceutical and nutraceutical value. It exhibits traditional medicinal properties such as qi-tonifying, yin-nourishing, kidney-benefiting, and antioxidant activities. <italic>P. hunanense</italic> maintains evergreen foliage year-round and shows significantly higher biomass accumulation than congener taxa. These traits are linked to phytohormone regulation, as indicated by previous studies. The absence of validated reference genes in <italic>P. hunanense</italic> has hindered molecular-level investigations in this species to date. In this study, 11 candidate reference genes (<italic>GAPDH</italic>, <italic>H2A</italic>, <italic>EF-1α</italic>, <italic>ACT</italic>, <italic>TUA</italic>, <italic>UBC</italic>, <italic>RPL</italic>, <italic>PP2A</italic>, <italic>18S</italic>, <italic>TUB</italic>, and <italic>UBQ</italic>) were identified from the <italic>P. hunanense</italic> transcriptome dataset. Expression profiles of these genes were analyzed by qRT-PCR across three experimental conditions: different tissues, hormone treatments, and abiotic stresses. Gene expression stability was analyzed using GeNorm, NormFinder, Delta Cᴛ, BestKeeper, and RefFinder software. The stability of candidate reference genes was validated through expression analysis of target genes (<italic>KO</italic>, <italic>KAM</italic>, <italic>GA13-ox</italic>, <italic>GA44-dio</italic>, <italic>ALDH7A1</italic>, <italic>IPM</italic>) involved in phytohormone metabolic pathways. Overall, the stability of the 11 candidate reference genes varied among different <italic>P. hunanense</italic> samples. <italic>EF-1α</italic>, <italic>18S</italic> and <italic>ACT</italic> were identified as the most stable in tissue samples. <italic>EF-1α</italic>, <italic>H2A</italic> and <italic>PP2A</italic> showed the highest stability under hormone treatments, and <italic>18S</italic>, <italic>UBC,</italic> and <italic>EF-1α</italic> exhibited consistent stability in abiotic stresses. This study establishes <italic>EF-1α</italic> as the optimal pan-experimental reference gene for qRT-PCR normalization in <italic>P. hunanense</italic>, demonstrating consistent expression stability across diverse tissues, hormone treatments, and abiotic stresses, thereby providing a significant reference for future gene expression studies.

Medicinal Plant BiologyVol. 4(1)
Macau University of Science and Technology (MO), Hunan University of Traditional Chinese Medicine (CN), Second Affiliated Hospital of Hunan University of Traditional Chinese Medicine (CN)
Hunan Provincial Science and Technology Department, Hunan University, Hunan University of Chinese Medicine
Openalex Percentile: Top 87%
Molecular Biology Techniques and Applications
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