Evidence map›Paper›PMID 39984589›Full record

ArticleScientific reports2025

Selection and validation of reference genes in alfalfa based on transcriptome sequence data.

Wenna Fan, Yaqi Shi, Pengfei Shi, Yixin Yang, Mengyao Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Screening of Reference Gene for RT-qPCR inInternational journal of molecular sciences · 2026
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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Wenna FanAnimal Science and Technology College, Henan University of Science and Technology, Luoyang, 471003, Henan, China. chou0516@163.com.
Yaqi ShiAnimal Science and Technology College, Henan University of Science and Technology, Luoyang, 471003, Henan, China.
Pengfei ShiAnimal Science and Technology College, Henan University of Science and Technology, Luoyang, 471003, Henan, China.
Yixin YangAnimal Science and Technology College, Henan University of Science and Technology, Luoyang, 471003, Henan, China.
Mengyao ZhangAnimal Science and Technology College, Henan University of Science and Technology, Luoyang, 471003, Henan, China.

Funding

National Natural Science Foundation of China 32102585
6 · The paper itself

Abstract

Compared with the traditional gene expression techniques of quantitative analysis, RT-qPCR is most widely used because of its low cost, time-saving, and accuracy. It is essential to introduce suitable internal reference genes as reference corrections in RT-qPCR experiments to reduce the RNA quality and reverse transcription efficiency of different samples. In our study, we chose the candidate internal reference genes of alfalfa from transcriptome sequence datasets (162 RNA-seq sequencing data) through comparative analysis. Finally, 10 candidate reference genes were selected. These candidate reference gene expressions were determined by RT-qPCR under five abiotic stresses of drought, alkali, high temperature, low temperature, and acid treatments. The stability index of these candidate genes was calculated and evaluated correspondently using specific software and different lgorithms, such as GeNorm, Normfinder, Bestkeeper, ΔCt method, and an online analysis tool RefFinder. Then the appropriate candidate genes were screened strictly; and validated by the phyA gene. GAPDH and Actin are taken as traditional reference genes on gene expression of quantitative analysis commonly used in alfalfa, Our results showed GAPDH and Actin aren't the most appropriate reference genes of alfalfa under different abiotic stresses, under alkaline stress, the optimal reference gene is UBL-2a, and the optimal combination of reference genes is MS.65,463 (some candidate reference genes haven't been annotated yet, using gene ID abbreviation number of Medicago sativa L. instead )and UBL-2a; Under drought stress, the optimal reference gene is Ms.33,066, and the optimal combination of reference genes is MS.65,463 and UBL-2a; Under high-temperature stress, the optimal reference gene is Actin, and the optimal combination of reference genes is Rer1, Actin, MS.00617, MS.74,923, UBL-2a, MS.33,066, MS.99,505, and MS.65,463; Under low-temperature stress, the optimal reference gene is Actin, and the optimal combination of reference genes is Rer1, Actin, MS.99,505, MS.073307, and UBL-2a. The optimal reference genes and their combinations need further validation under acid stress. This paper provides scientific evidence for quantitative analysis of the genes of alfalfa.

Indexed as

Gene Expression ProfilingGenes, PlantMedicago sativaTranscriptomeDroughtsGene Expression Regulation, PlantReal-Time Polymerase Chain ReactionReference StandardsStress, PhysiologicalAlfalfaReference geneSelectionTranscriptome sequence

Identifiers

PMID39984589
PMCPMC11845610

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.