Incorporating Primer Amplification Efficiencies in Quantitative Reverse Transcription Polymerase Chain Reaction Experiments;Considerations for Differential Gene Expression Analyses in Zebrafish

Abstract

Quantitative reverse transcription polymerase chain reaction (RT-qPCR) is commonly used to measure the mRNA expression of target genes in zebrafish. Gene expression values from RT-qPCR are typically reported as relative fold-changes, and relative quantification of RT-qPCR data incorporates primer amplification efficiency values for each target gene. We describe the influence of the primer amplification efficiency analysis method on RT-qPCR gene expression fold-change calculations. This report describes (1) a sample analysis demonstrating incorporation of primer amplification efficiency into RT-qPCR analysis for comparing gene expression of a gene of interest between two groups when normalized to multiple reference genes, (2) the influence of differences in primer amplification efficiencies between measured genes on gene expression differences calculated from theoretical delta-C_q (dC_q) values, and (3) an empirical comparison of the influence of three methods of defining primer amplification efficiency in gene expression analyses (delta-delta-C_q [ddC_q], standard curve, LinRegPCR) using mRNA measurements of a set of genes in zebrafish embryonic development. Given the need to account for the influence of primer amplification efficiency along with the simplicity of using software programs (LinRegPCR) to measure primer amplification efficiency from RT-qPCR data, we encourage using empirical measurements of primer amplification efficiency for RT-qPCR analysis of differential gene expression in zebrafish.

Introduction

Quantitative reverse transcription polymerase chain reaction (RT-qPCR) is a method used to measure mRNA expression of target genes across many biology-based disciplines. RT-qPCR is frequently used to assess gene expression in zebrafish. RT-qPCR involves a series of steps from sample collection to gene expression analysis (e.g., polymerase chain reaction [PCR] primer design, sample generation and RNA extraction, complementary DNA synthesis, RT-qPCR data collection and analysis). Many RT-qPCR studies measuring gene expression in zebrafish utilize SYBR Green reagents, using an intercalating dye that binds to double-stranded PCR products to quantify the amount of a specific target in a sample. RT-qPCR analyses are based on the quantification cycle (C_q), which is the PCR cycle at which the fluorescence signal increases to a detectable level above background.¹ This C_q value is proportional to the concentration of target DNA in the sample.

Most RT-qPCR gene expression studies make relative comparisons among experimental groups between expression of a gene of interest (GOI) and genes that are not affected by the experimental variable (i.e., reference genes [RGs], housekeeping genes). Measuring these unaffected genes accounts for variation in the sample amount in each RT-qPCR. Although many studies use a single RG for RT-qPCR analysis, using multiple RGs in analysis is needed for accurate comparisons and is best practice for RT-qPCR experiments.^2,3 Testing RG expression consistency is a recommended RT-qPCR control experiment, and multiple studies have characterized RGs for zebrafish RT-qPCR analysis,^4–7 including specific experimental conditions.^8–10 In terms of RT-qPCR analysis standards, the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines describe detailed recommendations for experimental design and reporting considerations related to RT-qPCR.¹¹ One of the essential information factors to address is primer amplification efficiency.

Primer amplification efficiency refers to how well a PCR primer pair amplifies a DNA target and can be defined as the average number of copies of a target gene from a single PCR cycle. The theoretical maximum for primer amplification efficiency is 2; for every PCR cycle, the product amplifies one copy to two copies. In practice, primer amplification efficiency is often less than two based on various experimental factors (e.g., secondary structure and sequence of the target DNA) as well as individual primer sequences and binding characteristics (e.g., GC content).¹² The impact of variable PCR efficiency on gene expression analysis has been reported to be a significant factor in clinical diagnostics,¹³ and MIQE recommendations encourage empirical measurements of primer amplification efficiency.¹¹

However, many RT-qPCR studies assume a primer amplification efficiency of two for all genes using the delta-delta-C_q (ddC_q) analysis method.¹⁴ In reviewing recent articles involving RT-qPCR gene expression studies in zebrafish, we noted significant variability in the methods for addressing primer amplification efficiency. A literature search in June 2022 using Google Scholar was filtered for 2022 publications associated with the keywords “embryonic development zebrafish RT-qPCR.” Of the 3870 publications identified in this search, 101 primary research articles involving RT-qPCR analysis of zebrafish gene expression were individually reviewed for RT-qPCR analysis methodology regarding primer amplification efficiency^15–114 (Fig. 1).

FIG. 1.

Relative proportion of reported analysis methods addressing primer amplification efficiency among surveyed primary research articles involving RT-qPCR analysis with zebrafish. RT-qPCR, quantitative reverse transcription polymerase chain reaction.

Among this sample of articles, the vast majority either used ddC_q methodology for analysis and assumed a primer amplification efficiency of two for all RT-qPCR measurements (n = 72, 71%) or did not specify analysis details regarding primer amplification efficiency (n = 21, 21%). Only 8% of these studies empirically accounted for primer amplification efficiency (n = 8).^15–22

Commercial PCR primers can have close to absolute efficiency based on experimental evidence from associated informatics pipelines (e.g., Applied Biosystems TaqMan assay efficiencies = 100% ± 10%), but empirical testing for primer amplification efficiency of custom primer reagents is recommended (e.g., SYBR Green RT-qPCR).^115,116 Standard curve analysis using serial dilutions of experimental samples has been used to empirically determine primer amplification efficiencies. However, this approach requires additional reagent and does not directly measure primer amplification efficiency in experimental samples. Empirically determining RT-qPCR primer amplification efficiencies under low gene expression (e.g., embryonic development) can be challenging for standard curves because serial dilutions of samples may not span the necessary range of C_q values or may produce greater technical variability of measurements (e.g., >35 C_q interpreted as a less reliable measure, near sensitivity limits of equipment).

This challenge can be partially addressed using diluted PCRs or synthetic oligonucleotides to allow the measurement of a wide range of target concentrations to assess primer amplification efficiency.^117,118 Another approach is to assess primer amplification efficiency in each experimental reaction using software programs. Multiple algorithms have been developed for differential expression analyses using RT-qPCR equipment data file formats (e.g., improve background subtraction,¹¹⁹ application of linear regression, and window-of-linearity approaches¹²⁰). A prominent program to measure primer amplification efficiency per sample is LinRegPCR, which was developed for clinical diagnostic PCR^120,121 and has both an .exe and online versions available.¹²²

Here, we describe RT-qPCR analysis methods that incorporate primer amplification efficiency for comparing mRNA expression of genes of interest when normalized to multiple RGs. We also present theoretical data and empirical data to demonstrate the influence of primer amplification efficiency on gene expression fold-change measures in RT-qPCR analyses.

Materials and Methods

Zebrafish husbandry

Adult AB strain zebrafish were maintained in an Aquaneering housing environment at 28.5°C in a 14:10 h light-dark cycle. Zebrafish embryos were collected and placed in E3 media in a 28.5°C incubator until use. All protocols were performed in accordance with the guidelines of the UWEC Institutional Animal Care and Use Committee (IACUC).

RNA extraction and cDNA synthesis

Embryos were collected for RNA extraction at seven developmental stages (n = 6 samples per time point, ∼10 embryos per sample): 6, 12, 24, 48, 72, 96, and 120 hours postfertilization (hpf). RNA extraction was performed using the Qiagen RNeasy Mini Kit according to the manufacturer's protocol; samples were homogenized using a sonicator (Fisherbrand). DNA contamination was removed using a Qiagen RNase-Free DNase Set. RNA concentration and purity were measured using a NanoDrop One (Thermo Scientific) without additional RNA quality measures (e.g., RQI). Total RNA was converted to cDNA using the Bio-Rad iScript cDNA Kit with ∼1 μg total RNA per reaction according to the manufacturer's protocol using a Bio-Rad T100 Thermal Cycler.

PCR primer design and quantitative PCR

Primers for the genes used were created using Primer-BLAST.¹²³ Primer-BLAST design criteria included PCR product size <100 nucleotides, primer melting temperature range of 58–62°C, and used target sequences from the Reference Sequence (RefSeq) mRNA database for zebrafish. PCR template sequences were obtained using NCBI BLAST. Both primer and template oligonucleotides were synthesized as unmodified oligonucleotides under standard desalting conditions (Integrated DNA Technologies). In standard curve experiments, template oligonucleotides were measured at concentrations ranging from 5E-15 to 5E-18 M. Melt curve analysis was used to assess primer specificity. All primers yielded a single PCR product, indicating target specificity (data not shown).

RT-qPCR was conducted using iTaq Universal SYBR Green Supermix (Bio-Rad) according to the manufacturer's protocol. Samples were measured in a 96-well plate format using a CFX Connect Real-Time System RT-qPCR machine (Bio-Rad). The RT-qPCR protocol consisted of a denaturation step (95°C for 30 s), followed by 40 cycles of denaturation and annealing/extension (95°C for 15 s, 60°C for 30 s). The average of the three technical triplicates was used as the gene expression measurement for each sample-primer combination.

Data analysis

Relative gene expression ratios (R) were quantified based on established methods for normalizing with multiple RGs using geometric means^2,124 with RT-qPCR primer amplification efficiency (E): $R = \frac{{(E_{G O I})}^{Δ C_{q G O I} (C o n t r o l - E x p e r i m e n t a l)}}{\sqrt[n]{{(E_{R G 1})}^{Δ C_{q R G 1} (C o n t r o l - E x p e r i m e n t a l)} * {(E_{R G 2})}^{Δ C_{q R G 2} (C o n t r o l - E x p e r i m e n t a l)} * \dots * {(E_{R G n})}^{Δ C_{q R G n} (C o n t r o l - E x p e r i m e n t a l)}}}$

where GOI refers to the target gene of interest, RG refers to the reference genes (e.g., “n” genes not changed by experimental variable), “control” refers to the reference/control sample measurement (e.g., gene expression at initial timepoint), and “experimental” refers to the experimental sample measurement (e.g., gene expression at other time points).

Primer amplification efficiency was empirically measured using (1) standard curves and (2) the LinRegPCR program.^120,121 C_q values were obtained using Bio-Rad CFX Maestro software using default settings with background subtraction for both ddC_q and standard curve calculations. LinRegPCR software used raw RT-qPCR data and includes background subtraction; for LinRegPCR, a primer amplification efficiency was defined by the average of primer amplification efficiency values across all sample measurements per experiment. For standard curves, primer amplification efficiencies were calculated using standard methods based on the equation E = 10^[−1/slope] where the slope is based on the linear regression of the plot of C_q values versus log₁₀[DNA].^124,125

To compare average gene expression measurements across time points and between analysis methods, statistical comparisons were made using single-factor analysis of variance (ANOVA) with Tukey honestly significant difference test (Tukey HSD test) post hoc testing. To make single comparisons among average gene expression measurements, individual comparisons of gene expression values were made using a two-sample t-test assuming unequal variance among samples.

Results

A sample analysis of RT-qPCR gene expression differences with multiple RGs and primer amplification efficiencies is visualized in Table 1. In this sample analysis, a single GOI is normalized with two RGs using corresponding primer amplification efficiencies. Empirical data of C_q values and primer amplification efficiencies (indicated by grey shaded boxes) can be converted into differential gene expression values using the indicated calculations. These calculations can be adapted to incorporate different numbers of genes of interest and RGs.

Table 1.

Theoretical Gene Expression Difference Calculations for Comparing mRNA Expression of One Gene of Interest in Control Treatment Versus Experimental Treatment with Normalization to Two Reference Genes

To determine how theoretical differences in primer amplification efficiencies affect fold-change calculations, fold-change values for a GOI and RG using a range of primer amplification efficiencies and delta-C_q (dC_q) values (e.g., number of cycles different between control and sample groups) were compared (Table 2; hypothetical scenario where RGs have same primer amplification efficiencies and consistent dC_q ratios). While equal primer amplification efficiencies resulted in the same fold-change outcomes across scenarios (grey shaded boxes), differing primer amplification efficiencies between the genes resulted in variation in fold-change calculation (i.e., GOI primer amplification efficiency >RG primer amplification efficiency, then greater calculated fold change; GOI primer amplification efficiency <RG primer amplification efficiency, then smaller calculated fold change).

Table 2.

Theoretical Effect of Primer Amplification Efficiency Differences on Fold-Change Calculations for Different Delta-C_q Values of Gene of Interest and Reference Genes

These differences were also affected by the dC_q of the RGs (greater variance of RGs between groups = greater effect of primer amplification efficiency differences on calculated fold-change values). For example, if the GOI dC_q was 2 and the RGs dC_q was 1, the fold-change values for primer amplification efficiencies of 1.7–2.0 for each gene ranged from 2.46-fold-change to 4.71-fold-change (vs. 4-fold-change for ddCq assumed E values = 2). When RG dC_q was 0.5, the range of fold-change values was smaller (2.66-fold-change to 4.34-fold-change). Overall, differences in primer amplification efficiencies have apparent influence on differential gene expression calculations, which may be particularly relevant when measuring smaller magnitude fold-changes.

To empirically test how empirical differences in primer amplification efficiencies affect fold-change calculations, an RT-qPCR dataset was generated for six genes (gad1b, glyt2, vglut2a, mpz, act1b, rpl13a) across seven timepoints in early zebrafish development (6, 12, 24, 48, 72, 96, and 120 hpf). These genes correspond to markers for different neuronal cell types (gad1b GABAergic neurons, glyt2 glycinergic neurons, vglut2a glutamatergic neurons, mpz oligodendrocytes) and validated RGs for zebrafish research (act1b, rpl13a).^5,6 Primer amplification efficiencies were empirically measured using (1) a standard curve measurement of 10-fold serial dilutions of synthetic DNA oligonucleotide templates of the PCR targets and (2) the software program LinRegPCR measurement of the actual zebrafish samples; these methods yielded similar but not identical primer amplification efficiencies (Table 3).

Table 3.

Quantitative Reverse Transcription Polymerase Chain Reaction Primer Sequences and Calculated Primer Amplification Efficiencies for Measured Genes

Gene	Forward primer	Reverse primer	Primer amplification efficiency; standard curve	Primer amplification efficiency; LinRegPCR
gad1b	ACCTGTGACTCCGTAAGTGTC	ACACCTCAATGCTTTCAGACT	1.857	1.818
glyt2	AAGTCCTCAGGGAAGGTGGT	TGACCAACACCACATACGGG	2.147	1.910
mpz	CCACCCCTCAACCATTCGG	GCCTGCACTGGAACCTTCTC	2.059	1.890
vglut2a	CGGAGAGAGTGCTAAGCTGC	TCCAAGGTGTCTTAAATTTATCTGC	1.858	1.957
actb1 ^a	CGTGCTGTTTTCCCCTCCAT	GCCAACCATCACTCCCTGAT	2.049	1.906
rpl13a ^a	ATCTCCTCGGTCGTCTTTCC	CAATTTTGTGGCCCAACAGC	1.696	1.629

Reference gene.

Fold-change values were calculated with reference to samples from the first time point (6 hpf) using act1b and rpl13a as RGs and then compared for the three methods of incorporating primer amplification efficiency into the calculations (ddC_q vs. standard curve vs. LinRegPCR, Table 4). In comparison to the 6 hpf timepoint (control/reference sample), the statistical differences in gene expression across the seven timepoints for glyt2 (increased at 72, 96, and 120 hpf), vglut2a (increased at 72, 96, and 120 hpf), and mpz (increased at 96 and 120 hpf) were consistent between each primer amplification efficiency methodology (ANOVA, Tukey HSD p < 0.05; dark grey-filled cells). The statistical difference in gene expression for gad1b was consistent among methods (increased at 72, 96, and 120 hpf) apart from the ddC_q calculation not showing increased expression at 72 hpf (ANOVA, Tukey HSD p < 0.05).

Table 4.

Gene Expression Differences of Neuronal Marker Genes Across Zebrafish Embryonic Development as Measured Using Different Primer Amplification Efficiency Calculations

In addition to time course comparisons, many gene expression studies in zebrafish have been based on single comparisons of two experimental groups. When comparing gene expression values individually (e.g., 6 hpf vs. single other timepoint via t-test, test single timepoint comparison), there were consistent differences among the values derived from the three methods (left columns Table 4, light grey-filled cells). Differences between 6 hpf gene expression values and earlier time points were significantly different when compared individually than when compared as an entire time course (e.g., differential gene expression at 12 hpf/24 hpf/48 hpf via t-test vs. after 72 hpf in ANOVA).

In terms of comparing primer amplification efficiency method gene expression changes per gene per time point, there were few statistical differences in the magnitudes of the gene expression values (5/84 comparisons differed, right columns Table 4, black-filled cells). Overall, in almost every case for observed gene expression changes in this time course experiment, the primer amplification efficiency calculation method did not affect the statistical differences and overall interpretation of gene expression changes.

Discussion

We found that most recent publications involving RT-qPCR with zebrafish did not empirically account for primer amplification efficiencies in their analysis and assumed 100% efficiency using a ddC_q approach (>90%, Fig. 1). However, analysis standards in clinical diagnostics using RT-qPCR recommend incorporating efficiency values for an accurate interpretation,¹³ and empirically incorporating primer amplification efficiency is recommended as a field standard.¹¹ The methods section and Table 1 sample calculations show a directed approach to use empirically derived primer amplification values with multiple RGs for RT-qPCR analyses. There are different ways of measuring primer amplification efficiency, and software packages such as LinRegPCR allow for empirical measurements of efficiency in each RT-qPCR experiment.^120–122

This approach allows empirical primer amplification efficiency values to be incorporated into RT-qPCR analysis without additional experiments (e.g., standard curves), making this approach similar to the simplicity of the prominent ddC_q method. Notably, the original publication of the ddC_q method encouraged the empirical measurement of primer amplification efficiency to be incorporated into associated equations.¹⁴

Smaller gene expression changes (e.g., less than twofold, transition from absence/low expression to presence/high expression) may be influenced by primer amplification efficiency variability (Table 2). Variability of RG expression between groups also affects primer amplification efficiency influence on fold-change calculations. Although the same amount of sample is intended for each RT-qPCR, variation in RG expression will increase the impact of differences in primer amplification efficiency among target genes (Table 2). Using the geometric mean of multiple RGs helps control for outliers and abundance differences between RGs while increasing accuracy of RT-qPCR analysis.²

Sample variability can also be limited by using a greater number of samples for analysis (e.g., n = 6 per group in this study; many studies use n = 3 per group). In addition, although the specific magnitude of fold-changes may vary, larger magnitude changes in gene expression measured by RT-qPCR are likely to be authentic results regardless of the primer amplification efficiency calculation methodology (Table 4).

The scale and experimental design of gene expression comparisons may also impact these statistical calculations. In comparing mRNA expression across a time course with large fold-changes (e.g., 10–100+-fold), variability of gene expression appeared to be the main influence for statistical comparison compared to variability of primer amplification efficiency (Table 4). Moreover, many RT-qPCR studies make comparisons between two groups (e.g., vehicle/control group vs. single time point). When comparisons were made between two groups instead of multiple groups (e.g., t-test of 6 hpf vs. another timepoint instead of ANOVA for the entire time course), the conclusions about differential expression per gene were similar; almost every instance of statistical difference was consistent across the three methods (83/84 comparisons consistent, Table 4). These results suggest that primer amplification efficiencies may not have a major impact on interpreting large gene expression changes, regardless of the experimental design and statistical approach.

In addition to primer amplification efficiency, there are other factors known to affect RT-qPCR data and analyses (e.g., sample storage conditions, RNA integrity, RNA purity, verification of invariant RG expression under specific experimental conditions).¹¹ Accounting for and reporting on these details can help increase accuracy and rigor for zebrafish gene expression studies.

In summary, we have demonstrated a streamlined analysis for incorporating primer amplification efficiencies into RT-qPCR analysis using multiple RGs (Table 1). Primer amplification efficiency can affect the magnitude of calculated gene expression differences in RT-qPCR analysis. Based on theoretical calculations of differential gene expression (Table 2), these differences may be biologically meaningful for small changes (e.g., <twofold) or for assessing the absence or presence of target gene expression (e.g., during zebrafish development). Based on the analysis of the presented gene expression profiles, functional interpretations of differential expression may not be substantially affected by using different methods of incorporating primer amplification efficiency, particularly for large gene expression changes that may be observed in different experimental contexts using zebrafish (e.g., adult vs. embryo, >10–100-fold changes, across developmental time course, Table 4).

Although primer amplification efficiency has not been included in most recent zebrafish RT-qPCR studies (Fig. 1), this factor can be easily incorporated into RT-qPCR analysis using publicly available software packages (e.g., LinRegPCR) to empirically measure primer amplification efficiency per sample without additional experimental measures (e.g., standard curves). The approach described in this report also includes simple calculations for incorporating multiple RGs into RT-qPCR analyses We encourage use of this approach and broader field standards for RT-qPCR (e.g., MIQE guidelines¹¹) to ensure high-quality reporting of RT-qPCR results in zebrafish gene expression studies.

Footnotes

Authors' Contributions

G.D.: Investigation, Formal Analysis, Visualization, Writing—Original Draft, and Writing—Review and Editing. B.H.: Methodology, Investigation, Formal Analysis, Visualization, and Writing—Review and Editing. C.D: Investigation and Writing—Review and Editing. E.V.: Investigation. B.C.: Conceptualization, Methodology, Formal Analysis, Visualization, Writing—Original Draft, Writing—Review and Editing, Supervision, Project Administration, and Funding Acquisition.

Disclosure Statement

The authors declare that they have no affiliations with or involvement in any organization or entity with any financial interest in the subject matter or materials discussed in this article.

Funding Information

Funding was provided by the UWEC Department of Biology, the UWEC Office of Research and Sponsored Programs (ORSP) and Blugold Commitment Differential Tuition, and the UWEC-Mayo Clinic Biomedical Innovator Program.

References

Kralik

, Ricchi

. A basic guide to real time PCR in microbial diagnostics: Definitions, parameters, and everything. Front Microbiol, 2017; 8:108.

Vandesompele

, De Preter

, Pattyn

, et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol, 2002; 3(7):research0034.1; doi: 10.1186/gb-2002-3-7-research0034

Hellemans

, Mortier

, De Paepe

, et al. qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Genome Biol, 2007; 8(2):R19; doi: 10.1186/gb-2007-8-2-r19

Casadei

, Pelleri

, Vitale

, et al. Identification of housekeeping genes suitable for gene expression analysis in the zebrafish. Gene Expr Patterns, 2011; 11(3):271–276; doi: 10.1016/j.gep.2011.01.003

Tang

, Dodd

, Lai

, et al. Validation of zebrafish (Danio rerio) reference genes for quantitative real-time RT-PCR normalization. Acta Biochim Biophys Sin, 2007; 39(5):384–390; doi: 10.1111/j.1745-7270.2007.00283.x

, Li

, Zeng

, et al. Genome-wide identification of suitable zebrafish Danio rerio reference genes for normalization of gene expression data by RT-qPCR. J Fish Biol, 2016; 88(6):2095–2110; doi: 10.1111/jfb.12915

Vanhauwaert

, Van Peer

, Rihani

, et al. Expressed repeat elements improve RT-qPCR normalization across a wide range of zebrafish gene expression studies. PLoS One, 2014; 9(10):e109091; doi: 10.1371/journal.pone.0109091

McCurley

, Callard

. Characterization of housekeeping genes in zebrafish: Male-female differences and effects of tissue type, developmental stage and chemical treatment. BMC Mol Biol, 2008; 9:102; doi: 10.1186/1471-2199-9-102

Rassier

, Silveira

TLR

, Remião

, et al. Evaluation of qPCR reference genes in GH-overexpressing transgenic zebrafish (Danio rerio). Sci Rep, 2020; 10(1):12692; doi: 10.1038/s41598-020-69423-y

10.

Liu

, Zhu

, Yan

, et al. Toxicity evaluation and biomarker selection with validated reference gene in embryonic zebrafish exposed to mitoxantrone. Int J Mol Sci, 2018; 19(11):3516; doi: 10.3390/ijms19113516

11.

Bustin

, Benes

, Garson

, et al. The MIQE guidelines: Minimum Information for Publication of Quantitative Real-Time PCR Experiments. Clin Chem, 2009; 55(4):611–622; doi: 10.1373/clinchem.2008.112797

12.

Benita

, Oosting

, Lok

, et al. Regionalized GC content of template DNA as a predictor of PCR success. Nucleic Acids Res, 2003; 31(16):e99; doi: 10.1093/nar/gng101

13.

Ruijter

, Barnewall

, Marsh

, et al. Efficiency correction is required for accurate quantitative PCR analysis and reporting. Clin Chem, 2021; 67(6):829–842; doi: 10.1093/clinchem/hvab052

14.

Livak

, Schmittgen

. Analysis of relative gene expression data using real-time quantitative PCR and the 2^−ΔΔCT method. Methods, 2001; 25(4):402–408; doi: 10.1006/meth.2001.1262

15.

Barakat

, Campbell

, Espin-Palazon

. Identification of transcription factor binding sites by cleavage under target and release using nuclease in zebrafish. Zebrafish, 2022; 19(3):104–108; doi: 10.1089/zeb.2021.0082

16.

Dubińska-Magiera

, Niedbalska-Tarnowska

, Migocka-Patrzałek

, et al. Characterization of Hspb8 in zebrafish. Cells, 2020; 9(6):1562; doi: 10.3390/cells9061562

17.

Ghaddar

, Gence

, Veeren

, et al. Aqueous extract of Psiloxylon mauritianum, rich in gallic acid, prevents obesity and associated deleterious effects in zebrafish. Antioxidants, 2022; 11(7):1309; doi: 10.3390/antiox11071309

18.

Rodrigues

, Cunha

, Ferreira

, et al. Differential molecular responses of zebrafish larvae to fluoxetine and norfluoxetine. Water, 2022; 14(3):417; doi: 10.3390/w14030417

19.

Niedbalska-Tarnowska

, Ochenkowska

, Migocka-Patrzałek

, et al. Assessment of the preventive effect of L-carnitine on post-statin muscle damage in a zebrafish model. Cells, 2022; 11(8):1297; doi: 10.3390/cells11081297

20.

Tsukazawa

, Li

, Tse

WKF

. 2,4-dichlorophenol exposure induces lipid accumulation and reactive oxygen species formation in zebrafish embryos. Ecotoxicol Environ Safety, 2022; 230:113133; doi: 10.1016/j.ecoenv.2021.113133

21.

Zhou

, Peng

, Li

, et al. Dopamine homeostasis imbalance and dopamine receptors-mediated AC/cAMP/PKA pathway activation are involved in aconitine-induced neurological impairment in zebrafish and SH-SY5Y cells. Front Pharmacol, 2022; 13:837810; doi: 10.3389/fphar.2022.837810

22.

Mikloska

, Zrini

, Bernier

. Severe hypoxia exposure inhibits larval brain development but does not affect the capacity to mount a cortisol stress response in zebrafish. J Exp Biol, 2022; 225(2):jeb243335; doi: 10.1242/jeb.243335

23.

Han

, Luo

, Qu

, et al. kdm4aa is required for reproduction and development of zebrafish. Aquacult Fish, 2023; 8(6):713–719; doi: 10.1016/j.aaf.2022.05.005

24.

Shi

, Qian

, Shen

, et al. The developmental toxicity and transcriptome analyses of zebrafish (Danio rerio) embryos exposed to carbon nanoparticles. Ecotoxicol Environ Safety, 2022; 234:113417; doi: 10.1016/j.ecoenv.2022.113417

25.

Varela

, Varela

, Martins

, et al. Cdkl5 mutant zebrafish shows skeletal and neuronal alterations mimicking human CDKL5 deficiency disorder. Sci Rep, 2022; 12(1):9325; doi: 10.1038/s41598-022-13364-1

26.

Al-Ansari

, Al-Badr

, Zakaria

, et al. Evaluation of Metal-Organic Framework MIL-89 nanoparticles toxicity on embryonic zebrafish development. Toxicol Rep, 2022; 9:951–960; doi: 10.1016/j.toxrep.2022.04.016

27.

Zhao

, Hu

, Gao

, et al. Excessive selenium affects neural development and locomotor behavior of zebrafish embryos. Ecotoxicol Environ Safety, 2022; 238:113611; doi: 10.1016/j.ecoenv.2022.113611

28.

Maleski

ALA

, Rosa

JGS

, Bernardo

JTG

, et al. Recapitulation of retinal damage in zebrafish larvae infected with zika virus. Cells, 2022; 11(9):1457; doi: 10.3390/cells11091457

29.

, Wang

, Zhang

, et al. Claudin-5a is essential for the functional formation of both zebrafish blood-brain barrier and blood-cerebrospinal fluid barrier. Fluids Barriers CNS, 2022; 19(1):40; doi: 10.1186/s12987-022-00337-9

30.

Hawkey-Noble

, Pater

, Kollipara

, et al. Mutation of foxl1 results in reduced cartilage markers in a zebrafish model of otosclerosis. Genes, 2022; 13(7):1107; doi: 10.3390/genes13071107

31.

Chiu

C-C

, Chin

H-K

, Chung

S-Y

, et al. Nitrobenzoate-derived compound X8 impairs vascular development in zebrafish. Int J Mol Sci, 2022; 23(14):7788; doi: 10.3390/ijms23147788

32.

D'Agostino

, Frigato

, Noviello

TMR

, et al. Loss of circadian rhythmicity in bdnf knockout zebrafish larvae. iScience, 2022; 25(4):104054; doi: 10.1016/j.isci.2022.104054

33.

Chen

, Qiu

, Yang

, et al. Perfluorooctane sulfonamide (PFOSA) induces cardiotoxicity via aryl hydrocarbon receptor activation in zebrafish. Environ Sci Technol, 2022; 56(12):8438–8448; doi: 10.1021/acs.est.1c08875

34.

Liu

, Zhang

, Wang

. Environmental relevant concentrations of triclosan affected developmental toxicity, oxidative stress, and apoptosis in zebrafish embryos. Environ Toxicol, 2022; 37(4):848–857; doi: 10.1002/tox.23448

35.

Jin

, Liu

, Wang

, et al. E2f4 is required for intestinal and otolith development in zebrafish. J Cell Physiol, 2022; 237(6):2690–2702; doi: 10.1002/jcp.30734

36.

Wei

, He

, Chen

, et al. Fluoxetine modifies circadian rhythm by reducing melatonin content in zebrafish. Biomed Pharmacother, 2022; 153:113268; doi: 10.1016/j.biopha.2022.113268

37.

Wolińska-Nizioł

, Romaniuk

, Wojciechowska

, et al. Tollip-deficient zebrafish display no abnormalities in development, organ morphology or gene expression in response to lipopolysaccharide. FEBS Open Bio, 2022; 12(8):1453–1464; doi: 10.1002/2211-5463.13423

38.

El-Sammak

, Yang

, Guenther

, et al. A Vegfc-Emilin2a-Cxcl8a signaling axis required for zebrafish cardiac regeneration. Circ Res, 2022; 130(7):1014–1029; doi: 10.1161/CIRCRESAHA.121.319929

39.

, Tan

, Feng

, et al. N-methyl-N-nitrosourea induces zebrafish anomalous angiogenesis through Wnt/β-catenin pathway. Ecotoxicol Environ Safety, 2022; 239:113674; doi: 10.1016/j.ecoenv.2022.113674

40.

Moraes

ACN de

, Fallah

, de Magalhães

, et al. Cylindrospermopsin induces oocyte maturation and disrupts gene expression in zebrafish ovarian follicles. Environ Toxicol Pharmacol, 2022; 94:103915; doi: 10.1016/j.etap.2022.103915

41.

Tang

PW-H

, Wu

P-H

, Lin

Y-T

, et al. Zebrafish model-based assessment of indoxyl sulfate-induced oxidative stress and its impact on renal and cardiac development. Antioxidants, 2022; 11(2):400; doi: 10.3390/antiox11020400

42.

, Wang

, Qin

, et al. Estrogens revert neutrophil hyperplasia by inhibiting Hif1α-cMyb pathway in zebrafish myelodysplastic syndromes models. Cell Death Discov, 2022; 8(1):1–12; doi: 10.1038/s41420-022-01121-2

43.

Yang

, Gu

, Chen

, et al. Transcriptome profiling reveals toxicity mechanisms following sertraline exposure in the brain of juvenile zebrafish (Danio rerio). Ecotoxicol Environ Safety, 2022; 242:113936; doi: 10.1016/j.ecoenv.2022.113936

44.

Md Razip

, Mohd Noor

, Norazit

, et al. An association between insulin resistance and neurodegeneration in zebrafish larval model (Danio rerio). Int J Mol Sci, 2022; 23(15):8290; doi: 10.3390/ijms23158290

45.

Wang

, Nie

, Xu

, et al. Essential role of RIG-I in hematopoietic precursor emergence in primitive hematopoiesis during zebrafish development. ImmunoHorizons, 2022; 6(5):283–298; doi: 10.4049/immunohorizons.2200028

46.

Hatef

, Rajeswari

, Unniappan

. The ghrelinergic system in zebrafish gonads is suppressed during food unavailability. Aquacult Fish, 2022; 7(5):494–499; doi: 10.1016/j.aaf.2022.03.005

47.

Chen

, Zhang

, Zou

, et al. Synergistic protective effects of folic acid and resveratrol against fine particulate matter-induced heart malformations in zebrafish embryos. Ecotoxicol Environ Safety, 2022; 241:113825; doi: 10.1016/j.ecoenv.2022.113825

48.

Liu

, Wang

, Chen

, et al. Combined effects of S-metolachlor and benoxacor on embryo development in zebrafish (Danio rerio). Ecotoxicol Environ Safety, 2022; 238:113565; doi: 10.1016/j.ecoenv.2022.113565

49.

Magner

, Sandoval-Sanchez

, Kramer

, et al. Disruption of miR-18a alters proliferation, photoreceptor replacement kinetics, inflammatory signaling, and microglia/macrophage numbers during retinal regeneration in zebrafish. Mol Neurobiol, 2022; 59(5):2910–2931; doi: 10.1007/s12035-022-02783-w

50.

Ding

, Chen

, Sultan

, et al. Effect of acute exposure to the ionic liquid 1-methyl-3-octylimidazolium chloride on the embryonic development and larval thyroid system of zebrafish. Animals, 2022; 12(11):1353; doi: 10.3390/ani12111353

51.

Wang

, Li

, Zhang

, et al. Acute developmental toxicity of Panax notoginseng in zebrafish larvae. Chin J Integr Med, 2023; 29(4):333–340; doi: 10.1007/s11655-022-3302-8

52.

Dinarello

, Tesoriere

, Martini

, et al. Zebrafish mutant lines reveal the interplay between nr3c1 and nr3c2 in the GC-dependent regulation of gene transcription. Int J Mol Sci, 2022; 23(5):2678; doi: 10.3390/ijms23052678

53.

Dasgupta

, Leong

, Simonich

, et al. Transcriptomic and long-term behavioral deficits associated with developmental 3.5 GHz radiofrequency radiation exposures in zebrafish. Environ Sci Technol Lett, 2022; 9(4):327–332; doi: 10.1021/acs.estlett.2c00037

54.

Liu

, Huang

, Wan

, et al. Lenvatinib induces cardiac developmental toxicity in zebrafish embryos through regulation of Notch mediated-oxidative stress generation. Environ Toxicol, 2022; 37(6):1310–1320; doi: 10.1002/tox.23485

55.

Gyimah

, Zhu

, Zhang

, et al. Oxidative stress and apoptosis in bisphenol AF–induced neurotoxicity in zebrafish embryos. Environ Toxicol Chem, 2022; 41(9):2273–2284; doi: 10.1002/etc.5412

56.

Pedroso

, Schneider

, Lima-Rezende

, et al. Evaluation of resveratrol and piceatannol anticonvulsant potential in adult zebrafish (Danio rerio). Neurochem Res, 2022; 47(11):3250–3260; doi: 10.1007/s11064-022-03656-3

57.

Quelle-Regaldie

, Folgueira

, Yáñez

, et al. A nop56 zebrafish loss-of-function model exhibits a severe neurodegenerative phenotype. Biomedicines, 2022; 10(8):1814; doi: 10.3390/biomedicines10081814

58.

, Lin

, Li

, et al. Rrn3 gene knockout affects ethanol-induced locomotion in adult heterozygous zebrafish. Psychopharmacology, 2022; 239(2):621–630; doi: 10.1007/s00213-021-06056-7

59.

Zizioli

, Mastinu

, Muscò

, et al. Pro-angiogenetic effects of purified extracts from Helix aspersa during zebrafish development. Curr Issues Mol Biol, 2022; 44(8):3364–3377; doi: 10.3390/cimb44080232

60.

Berdowski

, van der Linde

, Breur

, et al. Dominant-acting CSF1R variants cause microglial depletion and altered astrocytic phenotype in zebrafish and adult-onset leukodystrophy. Acta Neuropathol, 2022; 144(2):211–239; doi: 10.1007/s00401-022-02440-5

61.

Jeong

, Jang

, Kim

, et al. Size-dependent seizurogenic effect of polystyrene microplastics in zebrafish embryos. J Hazard Mater, 2022; 439:129616; doi: 10.1016/j.jhazmat.2022.129616

62.

Germano

, Porazzi

, Felix

. Leukemia-associated transcription factor mllt3 is important for primitive erythroid development in zebrafish embryogenesis. Dev Dynam, 2022; 251(10):1728–1740; doi: 10.1002/dvdy.477

63.

Zhang

, Xia

, Zhao

, et al. Photoaging enhanced the adverse effects of polyamide microplastics on the growth, intestinal health, and lipid absorption in developing zebrafish. Environ Int, 2022; 158:106922; doi: 10.1016/j.envint.2021.106922

64.

Dong

, Mao

, Bai

, et al. Characterization of developmental neurobehavioral toxicity in a zebrafish MPTP-induced model: A novel mechanism involving anemia. ACS Chem Neurosci, 2022; 13(13):1877–1890; doi: 10.1021/acschemneuro.2c00089

65.

Nuankaew

, Lee

, Nam

, et al. The effects of persimmon (Diospyros kaki L.f.) oligosaccharides on features of the metabolic syndrome in zebrafish. Nutrients, 2022; 14(16):3249; doi: 10.3390/nu14163249

66.

Huang

, Xiao

, Shi

, et al. Effects of di-(2-ethylhexyl) phthalate (DEHP) on behavior and dopamine signaling in zebrafish (Danio rerio). Environ Toxicol Pharmacol, 2022; 93:103885; doi: 10.1016/j.etap.2022.103885

67.

Toh

PJY

, Lai

JKH

, Hermann

, et al. Optogenetic control of YAP cellular localisation and function. EMBO Rep, 2022; 23(9):e54401; doi: 10.15252/embr.202154401

68.

Patel

, Patel

, Khadayata

, et al. Long-term exposure of the binary mixture of cadmium and mercury damages the developed ovary of adult zebrafish. Environ Sci Pollut Res, 2022; 29(29):44928–44938; doi: 10.1007/s11356-022-18988-4

69.

Liu

, Shangguan

, Zhu

, et al. Developmental toxicity of glyphosate on embryo-larval zebrafish (Danio rerio). Ecotoxicol Environ Safety, 2022; 236:113493; doi: 10.1016/j.ecoenv.2022.113493

70.

Kayvanpour

, Wisdom

, Lackner

, et al. VARS2 depletion leads to activation of the integrated stress response and disruptions in mitochondrial fatty acid oxidation. Int J Mol Sci, 2022; 23(13):7327; doi: 10.3390/ijms23137327

71.

Zhang

, Ji

, Jiang

, et al. Scale development-related genes identified by transcriptome analysis. Fishes, 2022; 7(2):64; doi: 10.3390/fishes7020064

72.

Wang

, Zhou

, Wang

, et al. Developmental cardiotoxicity and hepatotoxicity of flurbiprofen axetil to zebrafish embryo. ASSAY Drug Dev Technol, 2022; 20(3):125–135; doi: 10.1089/adt.2021.127

73.

Kent

, Calderon

, Silvius

, et al. Zebrafish her3 knockout impacts developmental and cancer-related gene signatures. Dev Biol, 2023; 496:1–14; doi: 10.1016/j.ydbio.2023.01.003

74.

Zheng

J-L

, Zhu

Q-L

, Hu

X-C

, et al. Transgenerational effects of zinc in zebrafish following early life stage exposure. Sci Total Environ, 2022; 828:154443; doi: 10.1016/j.scitotenv.2022.154443

75.

Ying

, Hu

, Han

, et al. The non-telomeric evolutionary trajectory of TRF2 in zebrafish reveals its specific roles in neurodevelopment and aging. Nucleic Acids Res, 2022; 50(4):2081–2095; doi: 10.1093/nar/gkac065

76.

Shao

, Ji

, Zheng

, et al. Zbtb46 controls dendritic cell activation by reprogramming epigenetic regulation of cd80/86 and cd40 costimulatory signals in a zebrafish model. J Immunol, 2022; 208(12):2686–2701; doi: 10.4049/jimmunol.2100952

77.

Heredia-García

, Gómez-Oliván

, Elizalde-Velázquez

, et al. Multi-biomarker approach and IBR index to evaluate the effects of bisphenol A on embryonic stages of zebrafish (Danio rerio). Environ Toxicol Pharmacol, 2022; 94:103925; doi: 10.1016/j.etap.2022.103925

78.

, Tang

, Zheng

, et al. Cingulin b is required for zebrafish lateral line development through regulation of mitogen-activated protein kinase and cellular senescence signaling pathways. Front Mol Neurosci, 2022; 15:844668; doi: 10.3389/fnmol.2022.844668

79.

Magnuson

, Qian

, McGruer

, et al. Relationship between miR-203a inhibition and oil-induced toxicity in early life stage zebrafish (Danio rerio). Toxicol Rep, 2022; 9:373–381; doi: 10.1016/j.toxrep.2022.03.006

80.

Geum

, Yeo

M-K

. Reduction in toxicity of polystyrene nanoplastics combined with phenanthrene through binding of jellyfish mucin with nanoplastics. Nanomaterials, 2022; 12(9):1427; doi: 10.3390/nano12091427

81.

Zhang

, Cha

S-H

. Preventive effects of sea cucumber (Apostichopus japonicus) ethanol extract on palmitate-induced vascular injury in vivo. Fish Aquat Sci, 2022; 25(2):90–100; doi: 10.47853/FAS.2022.e9

82.

, Chen

, Liu

, et al. Slc38a9 deficiency induces apoptosis and metabolic dysregulation and leads to premature death in zebrafish. Int J Mol Sci, 2022; 23(8):4200; doi: 10.3390/ijms23084200

83.

Zhang

, Scerbo

, Delagrange

, et al. Fgf8 dynamics and critical slowing down may account for the temperature independence of somitogenesis. Commun Biol, 2022; 5(1):1–10; doi: 10.1038/s42003-022-03053-0

84.

Luo

, Stocker

, Britton

, et al. Haem oxygenase limits Mycobacterium marinum infection-induced detrimental ferrostatin-sensitive cell death in zebrafish. FEBS J, 2022; 289(3):671–681; doi: 10.1111/febs.16209

85.

Weinreb

, Gupta

, Sharvit

, et al. Ddx41 inhibition of DNA damage signaling permits erythroid progenitor expansion in zebrafish. Haematologica, 2021; 107(3):644–654; doi: 10.3324/haematol.2020.257246

86.

, Zhang

, et al. Exposure of zebrafish embryos to sodium propionate disrupts circadian behavior and glucose metabolism-related development. Ecotoxicol Environ Safety, 2022; 241:113791; doi: 10.1016/j.ecoenv.2022.113791

87.

Di Paola

, Natale

, Gugliandolo

, et al. Assessment of 2-pentadecyl-2-oxazoline role on lipopolysaccharide-induced inflammation on early stage development of zebrafish (Danio rerio). Life, 2022; 12(1):128; doi: 10.3390/life12010128

88.

Wang

, Wang

, Jia

, et al. Comparative toxicity of [C8mim]Br and [C8py]Br in early developmental stages of zebrafish (Danio rerio) with focus on oxidative stress, apoptosis, and neurotoxicity. Environ Toxicol Pharmacol, 2022; 92:103864; doi: 10.1016/j.etap.2022.103864

89.

Huang

, Ahmed

, Wang

, et al. Negative elongation factor (NELF) inhibits premature granulocytic development in zebrafish. Int J Mol Sci, 2022; 23(7):3833; doi: 10.3390/ijms23073833

90.

Solman

, Blokzijl-Franke

, Piques

, et al. Inflammatory response in hematopoietic stem and progenitor cells triggered by activating SHP2 mutations evokes blood defects. White RM. ed. eLife, 2022; 11:e73040; doi: 10.7554/eLife.73040

91.

Van

DVLTM

, Van

, Zwart

, et al. Dose addition in the induction of craniofacial malformations in zebrafish embryos exposed to a complex mixture of food-relevant chemicals with dissimilar modes of action. Environ Health Perspect, 2022; 130(4):047003; doi: 10.1289/EHP9888

92.

Chouchene

, Kessabi

, Gueguen

M-M

, et al. Interference with zinc homeostasis and oxidative stress induction as probable mechanisms for cadmium-induced embryo-toxicity in zebrafish. Environ Sci Pollut Res, 2022; 29(26):39578–39592; doi: 10.1007/s11356-022-18957-x

93.

Shen

W-Y

, Fu

X-H

, Cai

, et al. Identification of key genes involved in recovery from spinal cord injury in adult zebrafish. Neural Regen Res, 2021; 17(6):1334–1342; doi: 10.4103/1673-5374.327360

94.

Fox

, Widen

, Asai-Coakwell

, et al. BMP3 is a novel locus involved in the causality of ocular coloboma. Hum Genet, 2022; 141(8):1385–1407; doi: 10.1007/s00439-022-02430-3

95.

Zhao

, Lin

X-H

, Zeng

Y-H

, et al. Knockdown of myorg leads to brain calcification in zebrafish. Mol Brain, 2022; 15(1):65; doi: 10.1186/s13041-022-00953-4

96.

Cacialli

, Mailhe

M-P

, Wagner

, et al. Synergistic prostaglandin E synthesis by myeloid and endothelial cells promotes fetal hematopoietic stem cell expansion in vertebrates. EMBO J, 2022; 41(19):e108536; doi: 10.15252/embj.2021108536

97.

Zhang

, Ma

, He

, et al. Tetramethylpyrazine protects endothelial injury and antithrombosis via antioxidant and antiapoptosis in HUVECs and zebrafish. Oxid Med Cell Longev, 2022; 2022:e2232365; doi: 10.1155/2022/2232365

98.

Dongjie

, Rajendran

, Xia

, et al. Neuroprotective effects of Tongtian oral liquid, a Traditional Chinese Medicine in the Parkinson's disease-induced zebrafish model. Biomed Pharmacother, 2022; 148:112706; doi: 10.1016/j.biopha.2022.112706

99.

, Tu

Y-X

, Wang

, et al. A landscape of differentiated biological processes involved in the initiation of sex differentiation in zebrafish. Water Biol Security, 2022; 1(3):100059; doi: 10.1016/j.watbs.2022.100059

100.

Morales

, Rabahi

, Diaz

, et al. Interleukin-10 regulates goblet cell numbers through Notch signaling in the developing zebrafish intestine. Mucosal Immunol, 2022; 15(5):940–951; doi: 10.1038/s41385-022-00546-3

101.

Yang

, Luan

, Xu

, et al. Cardiotoxicity of zebrafish induced by 6-benzylaminopurine exposure and its mechanism. Int J Mol Sci, 2022; 23(15):8438; doi: 10.3390/ijms23158438

102.

Baronio

, Chen

Y-C

, Decker

, et al. Vesicular monoamine transporter 2 (SLC18A2) regulates monoamine turnover and brain development in zebrafish. Acta Physiol, 2022; 234(1):e13725; doi: 10.1111/apha.13725

103.

Kasica

, Święch

, Saładziak

, et al. The inhibitory effect of selected D2 dopaminergic receptor agonists on VEGF-dependent neovascularization in zebrafish larvae: Potential new therapy in ophthalmic diseases. Cells, 2022; 11(7):1202; doi: 10.3390/cells11071202

104.

Y-X

, You

H-M

, Ren

C-Z

, et al. Proangiogenesis effects of compound danshen dripping pills in zebrafish. BMC Complement Med Ther, 2022; 22(1):112; doi: 10.1186/s12906-022-03589-y

105.

Chen

X-K

, Kwan

JS-K

, Wong

GT-C

, et al. Leukocyte invasion of the brain after peripheral trauma in zebrafish (Danio rerio). Exp Mol Med, 2022; 54(7):973–987; doi: 10.1038/s12276-022-00801-4

106.

, Liu

, Wang

, et al. Polystyrene nanoplastics aggravated ecotoxicological effects of polychlorinated biphenyls in on zebrafish (Danio rerio) embryos. Geosci Front, 2022; 13(3):101376; doi: 10.1016/j.gsf.2022.101376

107.

Hartig

, Zhu

, King

, et al. Chronic cortisol exposure in early development leads to neuroendocrine dysregulation in adulthood. BMC Res Notes, 2020; 13(1):366; doi: 10.1186/s13104-020-05208-w

108.

Uyttebroek

, Remoortel

, Buyssens

, et al. The effect of diet induced obesity on serotonin in zebrafish. J Cell Signal, 2022; 3(2):115–128; doi: 10.33696/Signaling.3.074

109.

Wohlfart

, Lou

, Middel

, et al. Accumulation of acetaldehyde in aldh2.1−/− zebrafish causes increased retinal angiogenesis and impaired glucose metabolism. Redox Biol, 2022; 50:102249; doi: 10.1016/j.redox.2022.102249

110.

Jia

, Chen

, Zeng

, et al. Low trifloxystrobin-tebuconazole concentrations induce cardiac and developmental toxicity in zebrafish by regulating notch mediated-oxidative stress generation. Ecotoxicol Environ Safety, 2022; 241:113752; doi: 10.1016/j.ecoenv.2022.113752

111.

Cacialli

, Lucini

. Analysis of the expression of neurotrophins and their receptors in adult zebrafish kidney. Vet Sci, 2022; 9(6):296; doi: 10.3390/vetsci9060296

112.

Baronio

, Chen

Y-C

, Panula

. Abnormal brain development of monoamine oxidase mutant zebrafish and impaired social interaction of heterozygous fish. Dis Models Mechan, 2022; 15(3):dmm049133; doi: 10.1242/dmm.049133

113.

Fan

, Shen

, Jia

, et al. Pentachloronitrobenzene reduces the proliferative capacity of zebrafish embryonic cardiomyocytes via oxidative stress. Toxics, 2022; 10(6):299; doi: 10.3390/toxics10060299

114.

Xue

, Ly

TTN

, Vijayakar

, et al. HOX epimutations driven by maternal SMCHD1/LRIF1 haploinsufficiency trigger homeotic transformations in genetically wildtype offspring. Nat Commun, 2022; 13(1):3583; doi: 10.1038/s41467-022-31185-8

115.

Application Note: Amplification Efficiency of TaqMan^® Gene Expression Assays. Applied Biosystems.

116.

White Paper: Gene Expression Assay Performance Guaranteed With the TaqMan^® Assays QPCR Guarantee Program. Applied Biosystems.

117.

Dhanasekaran

, Doherty

, Kenneth

. Comparison of different standards for real-time PCR-based absolute quantification. J Immunol Methods, 2010; 354(1):34–39; doi: 10.1016/j.jim.2010.01.004

118.

Conte

, Potoczniak

, Tobe

. Using synthetic oligonucleotides as standards in probe-based qPCR. BioTechniques, 2018; 64(4):177–179; doi: 10.2144/btn-2018-2000

119.

Rao

, Huang

, Zhou

, et al. An improvement of the 2ˆ(–delta delta CT) method for quantitative real-time polymerase chain reaction data analysis. Biostat Bioinform Biomath, 2013; 3(3):71.

120.

Ruijter

, Ramakers

, Hoogaars

WMH

, et al. Amplification efficiency: Linking baseline and bias in the analysis of quantitative PCR data. Nucl Acids Res, 2009; 37(6):e45; doi: 10.1093/nar/gkp045

121.

Ramakers

, Ruijter

, Deprez

RHL

, et al. Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data. Neurosci Lett, 2003; 339(1):62–66; doi: 10.1016/S0304-3940(02)01423-4

122.

Untergasser

, Ruijter

, Benes

, et al. Web-based LinRegPCR: Application for the visualization and analysis of (RT)-qPCR amplification and melting data. BMC Bioinformatics, 2021; 22(1):398; doi: 10.1186/s12859-021-04306-1

123.

, Coulouris

, Zaretskaya

, et al. Primer-BLAST: A tool to design target-specific primers for polymerase chain reaction. BMC Bioinformatics, 2012; 13(1):134; doi: 10.1186/1471-2105-13-134

124.

Pfaffl

. A new mathematical model for relative quantification in real-time RT-PCR. Nucl Acids Res, 2001; 29(9):e45; doi: 10.1093/nar/29.9.e45

125.

Rasmussen

. Quantification on the LightCycler. In: Rapid Cycle Real-Time PCR: Methods and Applications. ( Meuer

, Wittwer

, Nakagawara

K-I

. eds) Springer: Berlin, Heidelberg; 2001; pp. 21–34; doi: 10.1007/978-3-642-59524-0_3