Transcriptome-based selection and validation of optimal house-keeping genes for skin research in goats (Capra hircus)
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...
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| Published in | BMC genomics Vol. 21; no. 1; pp. 493 - 16 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
BioMed Central
18.07.2020
BioMed Central Ltd Springer Nature B.V BMC |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1471-2164 1471-2164 |
| DOI | 10.1186/s12864-020-06912-4 |
Cover
| 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. |
|---|---|
| AbstractList | 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. 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 [DELA]Ct 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. 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. 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. 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. 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. 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. 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.BACKGROUNDIn 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.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.RESULTSBased 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.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.CONCLUSIONThis 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. 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. 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 [DELA]Ct 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. Keywords: House-keeping genes, Reference genes, Goat, Skin, ComprFinder method 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. |
| ArticleNumber | 493 |
| Audience | Academic |
| Author | Deng, Chengchen Zhang, Jipan Zhao, Yongju Li, Jialu |
| Author_xml | – sequence: 1 givenname: Jipan surname: Zhang fullname: Zhang, Jipan organization: College of Animal Science and Technology, Southwest University, Chongqing Key Laboratory of Forage & Herbivore, Chongqing Engineering Research Center for Herbivores Resource Protection and Utilization – sequence: 2 givenname: Chengchen surname: Deng fullname: Deng, Chengchen organization: College of Animal Science and Technology, Southwest University, Chongqing Key Laboratory of Forage & Herbivore, Chongqing Engineering Research Center for Herbivores Resource Protection and Utilization – sequence: 3 givenname: Jialu surname: Li fullname: Li, Jialu organization: College of Animal Science and Technology, Southwest University, Chongqing Key Laboratory of Forage & Herbivore, Chongqing Engineering Research Center for Herbivores Resource Protection and Utilization – sequence: 4 givenname: Yongju orcidid: 0000-0001-9256-8856 surname: Zhao fullname: Zhao, Yongju email: zyongju@163.com organization: College of Animal Science and Technology, Southwest University, Chongqing Key Laboratory of Forage & Herbivore, Chongqing Engineering Research Center for Herbivores Resource Protection and Utilization |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32682387$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1016/j.smallrumres.2020.106164 10.3168/jds.2019-17526 10.1373/clinchem.2008.112797 10.1016/j.tig.2013.05.010 10.1093/nar/gkx875 10.1186/1471-2199-7-33 10.1023/B:BILE.0000019559.84305.47 10.1038/jid.2015.62 10.1038/s41598-020-58328-5 10.1016/j.livsci.2013.12.031 10.1016/j.gene.2018.03.004 10.1038/nprot.2009.61 10.1186/s12864-017-4418-7 10.1007/s11033-019-05187-7 10.1093/bioinformatics/bts169 10.1002/biot.201700259 10.1038/sj.gene.6364190 10.3390/ani10020182 10.1186/gb-2002-3-7-research0034 10.1186/s12864-019-5503-x 10.1186/1471-2105-13-134 10.1016/j.ygeno.2019.02.013 10.1371/journal.pone.0204404 10.1371/journal.pone.0169820 10.1016/j.celrep.2018.11.017 10.1016/j.ymeth.2009.12.006 10.1038/s41598-018-37186-2 10.1677/jme.1.01755 10.1677/jme.0.0290023 10.1038/s41598-018-38247-2 10.1111/dpr.12074 10.1186/s12864-018-4643-8 10.1016/j.jtemb.2019.08.007 10.7717/peerj.7925 10.1186/s13007-018-0311-x 10.1158/0008-5472.CAN-04-0496 10.1007/s13353-013-0173-x 10.1186/1471-2164-10-161 10.1007/s11103-012-9885-2 10.1038/nprot.2008.73 10.1016/j.fsi.2020.01.018 10.1093/bib/bbz134 10.1038/s41598-017-12754-0 10.1007/s11626-016-0023-3 10.1186/s12864-019-6426-2 10.1007/s11427-019-1553-5 |
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| Keywords | Goat Skin ComprFinder method Reference genes House-keeping genes |
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| References_xml | – volume: 191 start-page: 1 year: 2020 ident: 6912_CR42 publication-title: Small Ruminant Res doi: 10.1016/j.smallrumres.2020.106164 – volume: 103 start-page: 4846 issue: 5 year: 2020 ident: 6912_CR25 publication-title: J Dairy Sci doi: 10.3168/jds.2019-17526 – volume: 55 start-page: 611 issue: 4 year: 2009 ident: 6912_CR45 publication-title: Clin Chem doi: 10.1373/clinchem.2008.112797 – volume: 29 start-page: 569 issue: 10 year: 2013 ident: 6912_CR10 publication-title: Trends Genet doi: 10.1016/j.tig.2013.05.010 – volume: 46 start-page: D121 issue: D1 year: 2018 ident: 6912_CR36 publication-title: Nucleic Acids Res doi: 10.1093/nar/gkx875 – volume: 7 start-page: 33 issue: 1 year: 2006 ident: 6912_CR27 publication-title: BMC Mol Biol doi: 10.1186/1471-2199-7-33 – volume: 26 start-page: 509 issue: 6 year: 2004 ident: 6912_CR29 publication-title: Biotechnol Lett doi: 10.1023/B:BILE.0000019559.84305.47 – volume: 135 start-page: 1735 issue: 7 year: 2015 ident: 6912_CR34 publication-title: J Investig Dermatol doi: 10.1038/jid.2015.62 – volume: 10 start-page: 1362 issue: 1 year: 2020 ident: 6912_CR37 publication-title: Sci Rep doi: 10.1038/s41598-020-58328-5 – volume: 161 start-page: 28 year: 2014 ident: 6912_CR17 publication-title: Livest Sci doi: 10.1016/j.livsci.2013.12.031 – volume: 657 start-page: 39 year: 2018 ident: 6912_CR7 publication-title: Gene doi: 10.1016/j.gene.2018.03.004 – volume: 4 start-page: 902 issue: 6 year: 2009 ident: 6912_CR1 publication-title: Nat Protoc doi: 10.1038/nprot.2009.61 – volume: 19 start-page: 1 year: 2018 ident: 6912_CR13 publication-title: BMC Genomics doi: 10.1186/s12864-017-4418-7 – volume: 47 start-page: 953 issue: 2 year: 2020 ident: 6912_CR40 publication-title: Mol Biol Rep doi: 10.1007/s11033-019-05187-7 – volume: 28 start-page: 1544 issue: 11 year: 2012 ident: 6912_CR43 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bts169 – ident: 6912_CR8 doi: 10.1002/biot.201700259 – volume: 6 start-page: 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ident: 6912_CR33 publication-title: Cell Rep doi: 10.1016/j.celrep.2018.11.017 – volume: 50 start-page: 217 issue: 4 year: 2010 ident: 6912_CR46 publication-title: Methods doi: 10.1016/j.ymeth.2009.12.006 – volume: 9 start-page: 1 issue: 1 year: 2019 ident: 6912_CR22 publication-title: Sci Rep doi: 10.1038/s41598-018-37186-2 – volume: 34 start-page: 597 issue: 3 year: 2005 ident: 6912_CR2 publication-title: J Mol Endocrinol doi: 10.1677/jme.1.01755 – volume: 29 start-page: 23 issue: 1 year: 2002 ident: 6912_CR9 publication-title: J Mol Endocrinol doi: 10.1677/jme.0.0290023 – volume: 9 start-page: 1 issue: 1 year: 2019 ident: 6912_CR24 publication-title: Sci Rep doi: 10.1038/s41598-018-38247-2 – volume: 32 start-page: 589 issue: 5 year: 2014 ident: 6912_CR11 publication-title: Dev Policy Rev doi: 10.1111/dpr.12074 – volume: 19 start-page: 251 issue: 1 year: 2018 ident: 6912_CR20 publication-title: BMC Genomics doi: 10.1186/s12864-018-4643-8 – volume: 56 start-page: 192 year: 2019 ident: 6912_CR6 publication-title: J Trace Elem Med Bio doi: 10.1016/j.jtemb.2019.08.007 – volume: 7 start-page: e7925 year: 2019 ident: 6912_CR41 publication-title: PeerJ doi: 10.7717/peerj.7925 – volume: 14 start-page: 42 year: 2018 ident: 6912_CR21 publication-title: Plant Methods doi: 10.1186/s13007-018-0311-x – volume: 64 start-page: 5245 issue: 15 year: 2004 ident: 6912_CR28 publication-title: Cancer Res doi: 10.1158/0008-5472.CAN-04-0496 – volume: 54 start-page: 391 issue: 4 year: 2013 ident: 6912_CR30 publication-title: J Appl Genet doi: 10.1007/s13353-013-0173-x – volume: 10 start-page: 161 issue: 1 year: 2009 ident: 6912_CR35 publication-title: BMC Genomics doi: 10.1186/1471-2164-10-161 – volume: 80 start-page: 75 issue: 1 year: 2012 ident: 6912_CR38 publication-title: Plant Mol Biol doi: 10.1007/s11103-012-9885-2 – volume: 3 start-page: 1101 issue: 6 year: 2008 ident: 6912_CR3 publication-title: Nat Protoc doi: 10.1038/nprot.2008.73 – volume: 98 start-page: 218 year: 2020 ident: 6912_CR23 publication-title: Fish Shellfish Immunol doi: 10.1016/j.fsi.2020.01.018 – ident: 6912_CR5 doi: 10.1093/bib/bbz134 – volume: 7 start-page: 12461 issue: 1 year: 2017 ident: 6912_CR32 publication-title: Sci Rep doi: 10.1038/s41598-017-12754-0 – volume: 52 start-page: 782 issue: 7 year: 2016 ident: 6912_CR15 publication-title: In Vitro Cell Dev Biol Anim doi: 10.1007/s11626-016-0023-3 – volume: 21 start-page: 35 issue: 1 year: 2020 ident: 6912_CR18 publication-title: BMC Genomics doi: 10.1186/s12864-019-6426-2 – ident: 6912_CR19 doi: 10.1007/s11427-019-1553-5 |
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In quantitative real-time polymerase chain reaction (qRT-PCR) experiments, accurate and reliable target gene expression results are dependent on... In quantitative real-time polymerase chain reaction (qRT-PCR) experiments, accurate and reliable target gene expression results are dependent on optimal... Background In quantitative real-time polymerase chain reaction (qRT-PCR) experiments, accurate and reliable target gene expression results are dependent on... Abstract Background In quantitative real-time polymerase chain reaction (qRT-PCR) experiments, accurate and reliable target gene expression results are... |
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| SubjectTerms | Algorithms Animal fibers Animal Genetics and Genomics Animals Biomedical and Life Sciences Capra hircus ComprFinder method Datasets Economic importance Efficiency Experiments Fibroblast Growth Factor 5 - genetics Gene expression Genes Genes, Essential Genetic aspects Genomics Glyceraldehyde-3-phosphate dehydrogenase Goat Goats Goats - genetics Goats - metabolism Hedgehog Proteins - genetics House-keeping genes Intercellular Signaling Peptides and Proteins - genetics Life Sciences Livestock Meat Meat industry Meat processing industry Microarrays Microbial Genetics and Genomics Molecular biology Next-generation sequencing Non-human and non-rodent vertebrate genomics Normalizing Physiological aspects Plant Genetics and Genomics Polymerase chain reaction Proteomics Reference genes Reference Standards Research Article Ribonucleic acid RNA RNA-Seq Skin Skin - metabolism Stability analysis Standard deviation Studies Transcriptome |
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| Title | Transcriptome-based selection and validation of optimal house-keeping genes for skin research in goats (Capra hircus) |
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