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. 2023 Nov 28;8(1):bpad034.
doi: 10.1093/biomethods/bpad034. eCollection 2023.

Exogenous spike-in mouse RNAs for accurate differential gene expression analysis in barley using RT-qPCR

Marcus A Vinje  1 , David A Friedman  1
Affiliations

Exogenous spike-in mouse RNAs for accurate differential gene expression analysis in barley using RT-qPCR

Marcus A Vinje et al. Biol Methods Protoc. .

Abstract

Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) followed by the 2-ΔΔCt method is the most common way to measure transcript levels for relative gene expression assays. The quality of an RT-qPCR assay is dependent upon the identification and validation of reference genes to normalize gene expression data. The so-called housekeeping genes are commonly used as internal reference genes because they are assumed to be ubiquitously expressed at stable levels. Commonly, researchers do not validate their reference genes but rely on historical reference genes or previously validated genes from an unrelated experiment. Using previously validated reference genes to assess gene expression changes occurring during malting resulted in extensive variability. Therefore, a new method was tested and validated to circumvent the use of internal reference genes. Total mouse RNA was chosen as the external reference RNA and a suite of primer sets to putatively stable mouse genes was created to identify stably expressed genes for use as an external reference gene. cDNA was created by co-amplifying total mouse RNA, as an RNA spike-in, and barley RNA. When using the external reference genes to normalize malting gene expression data, standard deviations were significantly reduced and significant differences in transcript abundance were observed, whereas when using the internal reference genes, standard deviations were larger with no significant differences seen. Furthermore, external reference genes were more accurate at assessing expression levels in malting and developing grains, whereas the internal reference genes overestimated abundance in developing grains and underestimated abundance in malting grains.

Keywords: barley; grain development; malting; normalization; real-time PCR; spike-in RNA.

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Figures

Figure 1.
Figure 1.
RBOH transcript accumulation throughout micromalting using barley internal reference genes and external mouse RNA spike-in reference genes for normalization. Panel (A) represents RBOHA normalized to barley Act and Hsp70. Panel (B) represents RBOHA normalized to mouse Bmp-1, Igf1, and Hba-a1. Panel (C) represents RBOHC normalized to barley Act and Hsp70. Panel (D) represents RBOHC normalized to mouse Bmp-1, Igf1, and Hba-a1. Panel € represents Act normalized to mouse Bmp-1, Igf1, and Hba-a1. Panel (F) represents Hsp70 normalized to mouse Bmp-1, Igf1, and Hba-a1. Dry seed samples were used as the calibrator for each panel. Error bars represent standard deviation. Significant differences were determined using Dunnett’s test with significant differences from the calibrator denoted by asterisks (panels (A) and (C) were not significant, P = .0927 and P = .6858, respectively; panels (B) and (D) were significant at P < .0001; panel € was significant at P = .0192; and panel (F) was significant at P = .0094).
Figure 2.
Figure 2.
Comparative RBOHA and RBOHC gene expression in twelve malting and one feed cultivar during the steeping stage of malting. Panel (A) represents RBOHA normalized to barley Act and Hsp70. Panel (B) represents RBOHA normalized to mouse Bmp-1, Igf1, and Hba-a1. Panel (C) represents RBOHC normalized to barley Act and Hsp70. Panel (D) represents RBOHC normalized to mouse Bmp-1, Igf1, and Hba-a1. Panel (E) represents Act normalized to mouse Bmp-1, Igf1, and Hba-a1. Panel (F) represents Hsp70 normalized to mouse Bmp-1, Igf1, and Hba-a1. The relative expression ratio represents the expression change between dry and out of steep. Each cultivar was calibrated to dry seeds. Error bars represent standard deviation. Panels (A) and (C) were not significantly different using Fisher’s Least Significant Differences (LSD) test (P = .1477 and P = .7452, respectively). Significant differences were found in panels (B) and (D) and are denoted by different letters (panel (B) LSD = 8.3, P < .0001; panel (D) LSD = 1.86, P < .0001; panel (E) LSD = 2.85, P < .0001; panel (F) LSD = 6.03, P < .0001).
Figure 3.
Figure 3.
Bmy1 transcript accumulation throughout grain development using barley internal reference genes and mouse external RNA spike-in reference genes for normalization in a wild-type and beta-amylase mutant. Panel (A) represents Bmy1 normalized to barley Act and Hsp70 in wild-type. Panel (B) represents Bmy1 normalized to mouse Bmp-1, Igf1, and Hba-a1 in wild-type. Panel (C) represents Bmy1 normalized to barley Act and Hsp70 in mutant. Panel (D) represents Bmy1 normalized to mouse Bmp-1, Igf1, and Hba-a1 in mutant. Panel (E) represents Hsp70, Hsp90, and GAPDH normalized to mouse Bmp-1, Igf1, and Hba-a1 in wild-type. Panel (F) represents Hsp70, Hsp90, and GAPDH normalized to mouse Bmp-1, Igf1, and Hba-a1 in mutant. 5 days after anthesis was used as the calibrator for each panel. Error bars represent standard deviation. Significant differences compared to the calibrator were determined using Dunnett’s test and denoted with asterisks (panel (A), P = .0008; panel (B), P < .0001; panel (C), P = .0031; panel (D), P < .0001; panel (E) Hsp70, P = .0001; panel (E) Hsp90, P = .0001; panel (E) GAPDH, P = .0001; panel (F) Hsp70, P = .0001; panel (F) Hsp90, P = .0001; panel (F) GAPDH, P = .0001).
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