A protocol for identifying universal reference genes within a genus based on RNA-Seq data: a case study of poplar stem gene expression.

Forestry research Pub Date : 2024-06-01 eCollection Date: 2024-01-01 DOI:10.48130/forres-0024-0017
Qi Xie, Umair Ahmed, Cheng Qi, Kebing Du, Jie Luo, Pengcheng Wang, Bo Zheng, Xueping Shi
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Abstract

Real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) plays a crucial role in relative gene expression analysis, and accurate normalization relies on suitable reference genes (RGs). In this study, a pipeline for identifying candidate RGs from publicly available stem-related RNA-Seq data of different Populus species under various developmental and abiotic stress conditions is presented. DESeq2's median of ratios yielded the smallest coefficient of variance (CV) values in a total of 292 RNA-Seq samples and was therefore chosen as the method for sample normalization. A total of 541 stably expressed genes were retrieved based on the CV values with a cutoff of 0.3. Universal gene-specific primer pairs were designed based on the consensus sequences of the orthologous genes of each Populus RG candidate. The expression levels of 12 candidate RGs and six reported RGs in stems under different abiotic stress conditions or in different Populus species were assessed by RT-qPCR. The expression stability of selected genes was further evaluated using ΔCt, geNorm, NormFinder, and BestKeeper. All candidate RGs were stably expressed in different experiments and conditions in Populus. A test dataset containing 117 RNA-Seq samples was then used to confirm the expression stability, six candidate RGs and three reported RGs met the requirement of CV ≤ 0.3. In summary, this study was to propose a systematic and optimized protocol for the identification of constitutively and stably expressed genes based on RNA-Seq data, and Potri.001G349400 (CNOT2) was identified as the best candidate RG suitable for gene expression studies in poplar stems.

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基于 RNA-Seq 数据确定属内通用参考基因的方案:杨树茎基因表达的案例研究。
实时定量反转录聚合酶链反应(RT-qPCR)在相对基因表达分析中起着至关重要的作用,而准确的归一化依赖于合适的参考基因(RGs)。在本研究中,介绍了一种从公开的不同杨树物种在各种发育和非生物胁迫条件下的茎相关 RNA-Seq 数据中识别候选 RG 的方法。在总共 292 个 RNA-Seq 样本中,DESeq2 的比率中值产生的方差系数(CV)值最小,因此被选为样本归一化的方法。根据以 0.3 为临界值的 CV 值,共检索到 541 个稳定表达的基因。根据每个杨树 RG 候选基因的同源基因共识序列设计了通用基因特异引物对。通过 RT-qPCR 评估了 12 个候选 RG 和 6 个已报道的 RG 在不同非生物胁迫条件下或不同杨树品种的茎中的表达水平。利用 ΔCt、geNorm、NormFinder 和 BestKeeper 进一步评估了所选基因的表达稳定性。所有候选 RG 都在杨树的不同实验和条件下稳定表达。然后使用包含 117 个 RNA-Seq 样本的测试数据集来确认其表达的稳定性,其中 6 个候选 RGs 和 3 个已报告的 RGs 符合 CV ≤ 0.3 的要求。总之,本研究提出了基于 RNA-Seq 数据鉴定组成型稳定表达基因的系统优化方案,并确定 Potri.001G349400 (CNOT2) 为适合杨树茎基因表达研究的最佳候选 RG。
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