Selection and validation of suitable reference genes in skin tissue of Liaoning cashmere goat during hair follicle cycle

Bai, Wen; Yin, Rong; Yin, Rong; Jiang, Weibo; Wang, Jiao J; Wang, Ze Y; Zhu, Yanbing; Zhao, Zhi; Yang, Rong; Luo, G.B.; He, Jian

doi:10.1016/j.livsci.2013.12.031

Cited by 31 publications

(32 citation statements)

References 37 publications

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“…Those with a lower CV received a higher ranking order (Table 1). In addition, 4 genes outside of the 1325 were considered, including SDHA and YWHAZ, as they had previously been proposed by other researchers [17], and ACTB and GAPDH genes were included as the most commonly used endogenous HKGs for exploring target gene expression in goats. Therefore, 12 candidate HKGs were analyzed in subsequent steps.…”

Section: Selection Of Novel Candidate Hkgs Based On Rna-seq Datamentioning

confidence: 99%

“…Unfortunately, most molecular studies examining goat skin have blindly used a single HKG such as ACTB [12][13][14] or GAPDH [15,16]. In 2014, Bai et al [17] selected 10 commonly used HKGs based on a literature review to explore their stability in different hair follicle cycles of Liaoning cashmere goats. However, due to the lack of materials involved in and restriction of traditional HKGs, that study resulted in a limited impact.…”

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confidence: 99%

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Transcriptome-based Selection and Validation of Optimal House-keeping Genes for Skin Research in Goats (Capra hircus)

Zhang

Deng

et al. 2020

Preprint

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Background: In Quantitative real-time polymerase chain reaction (qRT-PCR) experiments, accurate and reliable target gene expression data is dependent on optimal amplification of house-keeping genes (HKGs). The RNA-seq technology offers a novel approach to detect new HKGs with improved stability. Goat (Capra hircus) is an economically important livestock species, and plays an indispensable role in the world animal fiber and meat industry. Unfortunately, uniform and reliable HKGs be used in skin research of goats have not been identified. Therefore, this study seeks to identify a set of stable HKGs for the skin tissue of C. hircus using the new high-throughput sequencing technology.Results: Based on the transcriptome dataset of 39 goat skin tissues, 8 genes (SRP68, NCBP3, RRAGA, EIF4H, CTBP2, PTPRA, CNBP, and EEF2) with relatively stable expression levels were identified and selected as new candidate HKGs. The classical HKGs including SDHA and YWHAZ from a previous study, and 2 conventional genes (ACTB and GAPDH) were also considered. Four different experimental materials: (1) different development stages, (2) hair follicle cycle stages, (3) breeds and (4) sampling sites were provided for determination and validation. Four algorithms (geNorm, NormFinder, BestKeeper, and ΔCt method) and a comprehensive algorithm (ComprFinder, developed in-house) were used to assess the stability of each HKG. It was observed that NCBP3+SDHA+PTPRA was more stably expressed than previously used genes, in all conditions analyzed. This combination was effective at normalizing target gene expression. Moreover, a new algorithm, ComprFinder, was developed and released for comprehensive analysis.Conclusion: This study presents the first data of candidate HKGs selection for skin tissues of C. hircus based on an RNA-seq dataset. We propose the use of the NCBP3+SDHA+PTPRA combination as the triplet HKGs in skin molecular biology in C. hircus and other closely related species in order to standardize analyses across studies. In addition, we also encourage researchers who are performing candidate HKG evaluations and have the needs of a comprehensive analysis to adopt our new algorithm, ComprFinder.

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Section: Selection Of Novel Candidate Hkgs Based On Rna-seq Datamentioning

confidence: 99%

mentioning

confidence: 99%

Transcriptome-based Selection and Validation of Optimal House-keeping Genes for Skin Research in Goats (Capra hircus)

Zhang

Deng

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…These genes were considered as candidate HKGs and of these, 8 genes (RRAGA, PTPRA, SRP68, EIF4H, NCBP3, CTBP2, CNBP, and EEF2) that with lower CV value, higher FPKM value, and easier primers design were selected for further quali cation. Besides, 4 genes outside of the initial 1325 were considered, including SDHA and YWHAZ as they had previously been proposed by other researchers [17], and ACTB and GAPDH genes were included as the most commonly used endogenous HKGs for exploring target gene expression in goats. In total, 12 candidate HKGs were analyzed in subsequent steps.…”

Section: Selection Of Novel Candidate Hkgs Based On Rna-seq Datamentioning

confidence: 99%

“…But for target genes that show slight changes, these can only be identi ed by optimal HKGs [30]. As far as we know, only one previous HKG study reported on goat skin tissue, Bai et al [17] selected ten commonly used HKGs by consulting the literature. The selected HKGs were tested on 3 stages of hair follicle cycle in Liaoning cashmere goats (referred to here as T1, T2, and T3 of IMCG), and authors nally recommended the SDHA+YWHAZ+UBC as the HKGs.…”

Section: The Hkgs Of Skin Tissue In Goats and Other Speciesmentioning

confidence: 99%

“…Genes with RPKM, CV, MFC, and DPM ful lling the criteria of HKGs were retained for further analysis ( Figure 7B). Moreover, two HKGs (SDHA and YWHAZ) from a previous study by Bai [17], and two commonly used HKGs (ACTB and GAPDH) were also considered as HKGs. All candidate HKGs were ampli ed using qRT-PCR for subsequent determination and validation.…”

Section: Selection Of Candidate Hkgsmentioning

confidence: 99%

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Transcriptome-based Selection and Validation of Optimal House-keeping Genes for Skin Research in Goats (Capra hircus)

Zhang

Deng

et al. 2020

Preprint

View full text Add to dashboard Cite

Abstract Background : In quantitative real-time polymerase chain reaction (qRT-PCR) experiments, accurate and reliable target gene expression results are dependent on optimal amplification of house-keeping genes (HKGs). RNA-seq technology offers a novel approach to detect new HKGs with improved stability. Goat ( Capra hircus ) is an economically important livestock species and plays an indispensable role in the world animal fiber and meat industry. Unfortunately, uniform and reliable HKGs for skin research have not been identified in goat. Therefore, this study seeks to identify a set of stable HKGs for the skin tissue of C. hircus using high-throughput sequencing technology. Results: Based on the transcriptome dataset of 39 goat skin tissue samples, 8 genes ( SRP68 , NCBP3 , RRAGA , EIF4H , CTBP2 , PTPRA , CNBP , and EEF2 ) with relatively stable expression levels were identified and selected as new candidate HKGs. Commonly used HKGs including SDHA and YWHAZ from a previous study, and 2 conventional genes ( ACTB and GAPDH ) were also examined. Four different experimental variables: (1) different development stages, (2) hair follicle cycle stages, (3) breeds, and (4) sampling sites were used for determination and validation. Four algorithms (geNorm, NormFinder, BestKeeper, and ΔCt method) and a comprehensive algorithm (ComprFinder, developed in-house) were used to assess the stability of each HKG. It was shown that NCBP3+SDHA+PTPRA were more stably expressed than previously used genes in all conditions analysis, and that this combination was effective at normalizing target gene expression. Moreover, a new algorithm for comprehensive analysis, ComprFinder, was developed and released. Conclusion: This study presents the first list of candidate HKGs for C. hircus skin tissues based on an RNA-seq dataset. We propose that the NCBP3+SDHA+PTPRA combination could be regarded as a triplet set of HKGs in skin molecular biology experiments in C. hircus and other closely related species. In addition, we also encourage researchers who perform candidate HKG evaluations and who require comprehensive analysis to adopt our new algorithm, ComprFinder.

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Molecular characterization, expression and methylation status analysis of BMP4 gene in skin tissue of Liaoning cashmere goat during hair follicle cycle

et al. 2016

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Bone morphogenetic protein 4 (BMP4) is a member of the bone morphogenetic protein family (BMPs). It is involved in the development and cycle of hair follicle, as well as, is thought to be a potential candidate gene for cashmere traits in goats. In the present study, we isolated and characterized a full-length open reading frame (ORF) of BMP4 cDNA from the skin tissue of Liaoning cashmere goat, and investigated the transcriptional pattern and methylation status of BMP4 gene in skin tissue of this breed during different stages of hair follicle cycle. The sequence analysis indicated that the isolated cDNA was 1264-bp in length containing a complete ORF of 1230-bp. It encoded a precursor peptide of 409 amino acids with a signal peptide of 19 amino acids. The structural analysis indicated that goat BMP4 contains typical TGF-β propeptide and TGF-β domains. In skin tissue, BMP4 is generally transcribed in an ascendant pattern from anagen to telogen. The methylation level of 5' flanking regulatory region of BMP4 gene might be involved in its mRNA expression in skin tissue: a higher BMP4 methylation level in skin coincides with a lower expression of BMP4 mRNA. These results from the present work provided a foundation for further insight into the functional and regulatory characteristics of BMP4 in the development and cycle of hair follicle in Liaoning Cashmere goat.

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Selection and validation of suitable reference genes in skin tissue of Liaoning cashmere goat during hair follicle cycle

Cited by 31 publications

References 37 publications

Transcriptome-based Selection and Validation of Optimal House-keeping Genes for Skin Research in Goats (Capra hircus)

Transcriptome-based Selection and Validation of Optimal House-keeping Genes for Skin Research in Goats (Capra hircus)

Transcriptome-based Selection and Validation of Optimal House-keeping Genes for Skin Research in Goats (Capra hircus)

Molecular characterization, expression and methylation status analysis of BMP4 gene in skin tissue of Liaoning cashmere goat during hair follicle cycle

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