Alfalfa, often dubbed the 'King of Forage,' has long been acknowledged for its exceptional protein content, making it a staple for livestock feed globally. Recent advances drawn from transcriptome sequencing now promise to refine how researchers study gene expression in this important legume, particularly under challenging environmental stressors.
Researchers from China’s agricultural sector have undertaken a significant study to evaluate and validate internal reference genes for quantitative real-time PCR (RT-qPCR) expressions in alfalfa, focusing on 162 RNA-seq data points. Their results challenge previously accepted norms for gene expression normalization during abiotic stress conditions, paving the way for more accurate assessments of plant responses.
The study identifies ten candidate reference genes using data analysis methods such as GeNorm, NormFinder, BestKeeper, and the broader analysis platform RefFinder. Crucially, it assesses how these genes perform under five distinct abiotic stress conditions: drought, high temperatures, low temperatures, alkaline conditions, and acidic treatments.
While traditional reference genes like GAPDH and Actin have been commonly used, the findings reveal flaws in their suitability across varying stress conditions. For example, under alkaline stress conditions, the gene UBL-2a emerged as the best reference gene, accompanied by the combination of MS.65,463. Similarly, under drought stress, Ms.33,066 was noted as the optimal reference gene.
The research methodology involved exposing alfalfa seedlings to the various stress conditions over set periods and extracting total RNA to measure the relative expression of phytochrome A (phyA), the only far-red light receptor, to evaluate the selected reference genes.
The results indicated distinct fluctuations in phyA expression levels based on the reference gene employed for normalization. For example, using the most stable candidate, UBL-2a, during alkaline treatments showed no significant differences among control and treated groups, contrastingly, results derived from less stable genes exposed considerable variation.
Importantly, the study emphasizes the increasing need for careful selection of reference genes in RT-qPCR experiments, as misrepresentation due to inappropriate gene choice can lead to significant biases. With challenges such as poor acid resistance identified previously, particularly for alfalfa grown under lower soil pH conditions, the researchers illustrated the value of identifying new reference genes.
Moving forward, the optimal reference genes identified, such as UBL-2a and Ms.33,066, along with their combinations, necessitate additional validation under various environmental contexts to refine the quantitative analysis of alfalfa’s gene expressions. This comprehensive approach enhances the reliability of molecular studies on alfalfa, positioning the findings as pivotal for advancing agricultural practices and improving crop resilience under stress.
All data arising from this study are accessible via the NCBI repository, paving the way for future investigations aimed at improving alfalfa's gene expression reliability when faced with environmental challenges.