Validation of the Reference Genes for the Gene Expression Studies in Chicken DT40 Cell Line

Dunisławska, Aleksandra; Sławińska, Anna; Siwek, Maria

doi:10.3390/genes11040372

Cited by 8 publications

(10 citation statements)

References 23 publications

(31 reference statements)

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“…The higher the M value is, the worse the stability of gene expression; in contrast, the lower the M value is, the better the stability of gene expression (Vandesompele et al, 2002). To date, some reference genes have been validated for the standardization of RT-qPCR data in chickens, but these genes are only concentrated in the gene expression analysis of a certain tissue or cell, such as muscle, brain, abdominal fat, heart, lung, ovary, uterus, lymphoid organ, articular cartilage, chicken embryo fibroblasts, IEL-NK cell, and DT40 cell line (Yang et al, 2013;Bagés et al, 2015;Nascimento et al, 2015;Mitra et al, 2016;Staines et al, 2016;Katarzyńska-Banasik et al, 2017;Hassanpour et al, 2018Hassanpour et al, , 2019Simon et al, 2018;Boo et al, 2020;Dunislawska et al, 2020;Hul et al, 2020;Marciano et al, 2020). Whether these reference genes are also suitable to the study of gene expression during the growth and development of a specific tissue or cell in chickens, such as adipose tissue and adipocyte, still needs to be further determined.…”

Section: Discussionmentioning

confidence: 99%

Screening of Reference Genes for RT-qPCR in Chicken Adipose Tissue and Adipocytes

et al. 2021

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Reverse transcription quantitative real-time PCR is the most commonly used method to detect gene expression levels. In experiments, it is often necessary to correct and standardize the expression level of target genes with reference genes. Therefore, it is very important to select stable reference genes to obtain accurate quantitative results. Although application examples of reference genes in mammals have been reported, no studies have investigated the use of reference genes in studying the growth and development of adipose tissue and the proliferation and differentiation of preadipocytes in chickens. In this study, GeNorm, a reference gene stability statistical algorithm, was used to analyze the expression stability of 14 candidate reference genes in the abdominal adipose tissue of broilers at 1, 4, and 7 weeks of age, the proliferation and differentiation of primary preadipocytes, as well as directly isolated preadipocytes and mature adipocytes. The results showed that the expression of the TATA box binding protein (TBP) and hydroxymethylbilane synthase (HMBS) genes was most stable during the growth and development of abdominal adipose tissue of broilers, the expression of the peptidylprolyl isomerase A (PPIA) and HMBS genes was most stable during the proliferation of primary preadipocytes, the expression of the TBP and RPL13 genes was most stable during the differentiation of primary preadipocytes, and the expression of the TBP and HMBS genes was most stable in directly isolated preadipocytes and mature adipocytes. These results provide reference bases for accurately detecting the mRNA expression of functional genes in adipose tissue and adipocytes of chickens.

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Section: Discussionmentioning

confidence: 99%

Screening of Reference Genes for RT-qPCR in Chicken Adipose Tissue and Adipocytes

et al. 2021

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“…A large proportion of RGs were selected according to previous literature, of which many were housekeeping genes (HKGs) [ 7 , 36 , 37 ]. Moreover, it is widely accepted that the expression levels of HKGs are not stable in some species or tissues, and cannot meet the criteria of RG normalization [ 38 , 39 , 40 ].…”

Section: Discussionmentioning

confidence: 99%

“…Perfect RGs should be stably expressed in diverse individuals, tissues, and cells without spatiotemporal differences, even under different experimental treatments [ 6 ]. However, several studies have found that the stabilities of RGs turned out to be species-, tissue-, or cell-specific [ 7 , 8 ]. Lee and colleagues revealed considerable variability of 12 commonly used RGs within and across microarray datasets, including in different mammalian cell contexts [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

“…The phenomenon was reported that a more significant expression error was commonly associated with increased noise and inability to detect minor differences [ 13 ]. Besides RNA yield, quality, and reverse transcription efficiency [ 4 , 7 , 14 ], it is also necessary to apply a data normalization strategy to eliminate the variations caused by technology or experiment. At present, the geNorm, NormFinder, and BestKeeper software tools are primarily used to evaluate the expression stability of candidate RGs, and to identify the minimum number of RGs needed under diverse experimental conditions [ 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

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Genome-Wide Identification of Reference Genes for Reverse-Transcription Quantitative PCR in Goat Rumen

Zhao¹,

Cheng²,

Zhang³

et al. 2021

Animals

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As the largest chamber of the ruminant stomach, the rumen not only serves as the principal absorptive surface and nutrient transport pathway from the lumen into the animal, but also plays an important short-chain fatty acid (SCFA) metabolic role in addition to protective functions. Accurate characterization of the gene expression profiles of genes of interest is essential to the exploration of the intrinsic regulatory mechanisms of rumen development in goats. Thus, the selection of suitable reference genes (RGs) is an important prerequisite for real-time quantitative PCR (RT-qPCR). In the present study, 16 candidate RGs were identified from our previous transcriptome sequencing of caprine rumen tissues. The quantitative expressions of the candidate RGs were measured using the RT-qPCR method, and the expression stability of the RGs was assessed using the geNorm, NormFinder, and BestKeeper programs. GeNorm analysis showed that the M values were less than 0.5 for all the RGs except GAPT4, indicating that they were stably expressed in the rumen tissues throughout development. RPS4X and RPS6 were the two most stable RGs. Furthermore, the expressions of two randomly selected target genes (IGF1 and TOP2A), normalized by the selected most stable RGs (RPS4X and RPS6), were consistent with the results of RNA sequencing, while the use of GAPDH and ACTB as RGs resulted in altered profiles. Overall, RPS4X and RPS6 showed the highest expression stability and the lowest coefficients of variation, and could be used as the optimal reference combination for quantifying gene expression in rumen tissues via RT-qPCR analysis.

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“…Peripheral blood mononuclear cells (PBMCs) are a critical part of the immune system used to fight infection (Li et al, 2021). PBMCs were frequently applied as an ex vivo model to characterize cytokine gene expression after stimulation by purified TLR (toll-like receptor) ligands or live probiotics (Slawinska et al, 2021;Lee et al, 2022). Lipopolysaccharide (LPS) is an important pathogenic component present in the cell walls of Gram-negative bacteria (Tartey and Takeuchi, 2017), and Osamu et al (Takeuchi et al, 1999) reported that TLR2 and TLR4 were found to be involved in LPS-mediated signaling.…”

Section: Introductionmentioning

confidence: 99%

Comparative transcriptome analyses of immune responses to LPS in peripheral blood mononuclear cells from the giant panda, human, mouse, and monkey

Li²,

Chen³

et al. 2023

Front. Genet.

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Gram-negative bacteria are major pathogens that can cause illnesses in giant pandas. Lipopolysaccharides (LPS), components of Gram-negative bacteria, can activate immune responses in mammals (i.e., humans and mice) through recognition by toll-like receptors (TLRs). However, the giant pandas’ immune response to LPS stimulation and the differences between the giant panda and other mammals are not fully known. In this study, we administrated peripheral blood mononuclear cells (PBMCs) from giant pandas, humans, C57BL/6 mice, and rhesus monkeys by LPS treatment at 6 h followed by RNA sequencing (RNA-seq), respectively, with control of non-stimulation. KEGG analyses of differentially expressed genes (DEGs) pathways indicated that LPS could activate the classic signaling pathway of NF-κB in PBMCs from those four tested species. Thus, similar to the other three species, NF-κB is an LPS-responsive regulator of innate immune responses in giant pandas. Furthermore, the expression patterns of adapter genes, inflammatory cytokine genes, chemokines, interferon genes, cytokine genes related to cell growth and development, costimulatory molecules, Th1/Th2 cytokine genes, Th17 cytokine genes, Th9, and Th22 cytokine genes were compared among giant pandas and three other species. Our data indicated that in addition to the similar expression patterns of certain genes among giant pandas and other species, the unique expression pattern response to LPS in giant pandas was also discovered. Furthermore, Th9, Th17, and Th22 cells might be involved in the response to LPS in giant pandas at this tested time point. This study reveals that LPS-induced immune responses have different sensitivities and response timelines in giant pandas compared with other mammals. This study facilitates further understanding of the role of the TLR signaling pathway and the immune system in giant pandas, which might be helpful for disease prevention and protection.

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Validation of the Reference Genes for the Gene Expression Studies in Chicken DT40 Cell Line

Cited by 8 publications

References 23 publications

Screening of Reference Genes for RT-qPCR in Chicken Adipose Tissue and Adipocytes

Screening of Reference Genes for RT-qPCR in Chicken Adipose Tissue and Adipocytes

Genome-Wide Identification of Reference Genes for Reverse-Transcription Quantitative PCR in Goat Rumen

Comparative transcriptome analyses of immune responses to LPS in peripheral blood mononuclear cells from the giant panda, human, mouse, and monkey

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