The dilution effect and the importance of selecting the right internal control genes for RT-qPCR: a paradigmatic approach in fetal ... View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-12

AUTHORS

Huaisheng Xu, Massimo Bionaz, Deborah M Sloboda, Loreen Ehrlich, Shaofu Li, John P Newnham, Joachim W Dudenhausen, Wolfgang Henrich, Andreas Plagemann, John RG Challis, Thorsten Braun

ABSTRACT

BACKGROUND: The key to understanding changes in gene expression levels using reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) relies on the ability to rationalize the technique using internal control genes (ICGs). However, the use of ICGs has become increasingly problematic given that any genes, including housekeeping genes, thought to be stable across different tissue types, ages and treatment protocols, can be regulated at transcriptomic level. Our interest in prenatal glucocorticoid (GC) effects on fetal growth has resulted in our investigation of suitable ICGs relevant in this model. The usefulness of RNA18S, ACTB, HPRT1, RPLP0, PPIA and TUBB as ICGs was analyzed according to effects of early dexamethasone (DEX) treatment, gender, and gestational age by two approaches: (1) the classical approach where raw (i.e., not normalized) RT-qPCR data of tested ICGs were statistically analyzed and the best ICG selected based on absence of any significant effect; (2) used of published algorithms. For the latter the geNorm Visual Basic application was mainly used, but data were also analyzed by Normfinder and Bestkeeper. In order to account for confounding effects on the geNorm analysis due to co-regulation among ICGs tested, network analysis was performed using Ingenuity Pathway Analysis software. The expression of RNA18S, the most abundant transcript, and correlation of ICGs with RNA18S, total RNA, and liver-specific genes were also performed to assess potential dilution effect of raw RT-qPCR data. The effect of the two approaches used to select the best ICG(s) was compared by normalization of NR3C1 (glucocorticoid receptor) mRNA expression, as an example for a target gene. RESULTS: Raw RT-qPCR data of all the tested ICGs was significantly reduced across gestation. TUBB was the only ICG that was affected by DEX treatment. Using approach (1) all tested ICGs would have been rejected because they would initially appear as not reliable for normalization. However, geNorm analysis (approach 2) of the ICGs indicated that the geometrical mean of PPIA, HPRT1, RNA18S and RPLPO can be considered a reliable approach for normalization of target genes in both control and DEX treated groups. Different subset of ICGs were tested for normalization of NR3C1 expression and, despite the overall pattern of the mean was not extremely different, the statistical analysis uncovered a significant influence of the use of different normalization approaches on the expression of the target gene. We observed a decrease of total RNA through gestation, a lower decrease in raw RT-qPCR data of the two rRNA measured compared to ICGs, and a positive correlation between raw RT-qPCR data of ICGs and total RNA. Based on the same amount of total RNA to performed RT-qPCR analysis, those data indicated that other mRNA might have had a large increase in expression and, as consequence, had artificially diluted the stably expressed genes, such as ICGs. This point was demonstrated by a significant negative correlation of raw RT-qPCR data between ICGs and liver-specific genes. CONCLUSION: The study confirmed the necessity of assessing multiple ICGs using algorithms in order to obtain a reliable normalization of RT-qPCR data. Our data indicated that the use of the geometrical mean of PPIA, HPRT1, RNA18S and RPLPO can provide a reliable normalization for the proposed study. Furthermore, the dilution effect observed support the unreliability of the classical approach to test ICGs. Finally, the observed change in the composition of RNA species through time reveals the limitation of the use of ICGs to normalize RT-qPCR data, especially if absolute quantification is required. More... »

PAGES

58

References to SciGraph publications

  • 2010-03. Selection and reliability of internal reference genes for quantitative PCR verification of transcriptomics during the differentiation process of porcine adult mesenchymal stem cells in STEM CELL RESEARCH & THERAPY
  • 2006-12. Development of a new set of reference genes for normalization of real-time RT-PCR data of porcine backfat and longissimus dorsi muscle, and evaluation with PPARGC1A in BMC BIOTECHNOLOGY
  • 2004-03. Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper – Excel-based tool using pair-wise correlations in BIOTECHNOLOGY LETTERS
  • 2008-09. Translational control plays a prominent role in the hepatocytic differentiation of HepaRG liver progenitor cells in GENOME BIOLOGY
  • 2002-06. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes in GENOME BIOLOGY
  • 2005-06. Real-time RT-PCR normalisation; strategies and considerations in GENES & IMMUNITY
  • 2004-07. Statistical modeling for selecting housekeeper genes in GENOME BIOLOGY
  • 1999-09. MBD2 is a transcriptional repressor belonging to the MeCP1 histone deacetylase complex in NATURE GENETICS
  • 2005-12. Gene expression studies in prostate cancer tissue: which reference gene should be selected for normalization? in JOURNAL OF MOLECULAR MEDICINE
  • 2000-11. Regulation of a multigenic invasion programme by the transcription factor, AP-1: re-expression of a down-regulated gene, TSC-36, inhibits invasion in ONCOGENE
  • 2005-12. Selection of ovine housekeeping genes for normalisation by real-time RT-PCR; analysis of PrPgene expression and genetic susceptibility to scrapie in BMC VETERINARY RESEARCH
  • 2007-12. Expression stability of commonly used reference genes in canine articular connective tissues in BMC VETERINARY RESEARCH
  • 2009-12. Selection of reference genes for normalisation of real-time RT-PCR in brain-stem death injury in Ovis aries in BMC MOLECULAR BIOLOGY
  • 2009-12. Binding characteristics of the ovine membrane progesterone receptor alpha and expression of the receptor during the estrous cycle in REPRODUCTIVE BIOLOGY AND ENDOCRINOLOGY
  • 2008-12. Selection and validation of a set of reliable reference genes for quantitative sod gene expression analysis in C. elegans in BMC MOLECULAR BIOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s13104-015-0973-7

    DOI

    http://dx.doi.org/10.1186/s13104-015-0973-7

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1043629029

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/25881111


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Genetics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Biological Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Algorithms", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Animals", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Dexamethasone", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Female", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Fetus", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gene Expression", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gene Expression Profiling", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Genes, Essential", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gestational Age", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Glucocorticoids", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Hypoxanthine Phosphoribosyltransferase", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Peptidylprolyl Isomerase", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Pregnancy", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "RNA, Messenger", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "RNA, Ribosomal, 18S", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Real-Time Polymerase Chain Reaction", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Receptors, Glucocorticoid", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Reference Standards", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Ribosomal Proteins", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Sheep, Domestic", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Linyi People's Hospital", 
              "id": "https://www.grid.ac/institutes/grid.415946.b", 
              "name": [
                "Departments of Obstetrics and Division of Experimental Obstetrics, Charit\u00e9 - University Berlin, Augustenburger Platz 1, Berlin, Germany", 
                "Departments of Obstetrics and Gynecology, Linyi People\u2019s Hospital, Shandong, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Xu", 
            "givenName": "Huaisheng", 
            "id": "sg:person.0613063304.18", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0613063304.18"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Oregon State University", 
              "id": "https://www.grid.ac/institutes/grid.4391.f", 
              "name": [
                "Animal and Rangeland Sciences, Oregon State University, Corvallis, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Bionaz", 
            "givenName": "Massimo", 
            "id": "sg:person.0676405057.20", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0676405057.20"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "McMaster University", 
              "id": "https://www.grid.ac/institutes/grid.25073.33", 
              "name": [
                "Departments of Biochemistry and Biomedical Sciences, Obstetrics & Gynecology and Pediatrics, McMaster University, Hamilton, Canada"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Sloboda", 
            "givenName": "Deborah M", 
            "id": "sg:person.01134700514.89", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01134700514.89"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Charit\u00e9", 
              "id": "https://www.grid.ac/institutes/grid.6363.0", 
              "name": [
                "Departments of Obstetrics and Division of Experimental Obstetrics, Charit\u00e9 - University Berlin, Augustenburger Platz 1, Berlin, Germany"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ehrlich", 
            "givenName": "Loreen", 
            "id": "sg:person.01270354204.13", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01270354204.13"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "School of Women\u2019s and Infants\u2019 Health, King Edward Memorial Hospital, The University of Western Australia, and Women and Infants Research Foundation of Western Australia, Perth, Australia"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Li", 
            "givenName": "Shaofu", 
            "id": "sg:person.01066565314.14", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01066565314.14"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "School of Women\u2019s and Infants\u2019 Health, King Edward Memorial Hospital, The University of Western Australia, and Women and Infants Research Foundation of Western Australia, Perth, Australia"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Newnham", 
            "givenName": "John P", 
            "id": "sg:person.01021220240.90", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01021220240.90"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Charit\u00e9", 
              "id": "https://www.grid.ac/institutes/grid.6363.0", 
              "name": [
                "Departments of Obstetrics and Division of Experimental Obstetrics, Charit\u00e9 - University Berlin, Augustenburger Platz 1, Berlin, Germany"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Dudenhausen", 
            "givenName": "Joachim W", 
            "id": "sg:person.01314463546.09", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01314463546.09"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Charit\u00e9", 
              "id": "https://www.grid.ac/institutes/grid.6363.0", 
              "name": [
                "Departments of Obstetrics and Division of Experimental Obstetrics, Charit\u00e9 - University Berlin, Augustenburger Platz 1, Berlin, Germany"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Henrich", 
            "givenName": "Wolfgang", 
            "id": "sg:person.0747560146.35", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0747560146.35"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Charit\u00e9", 
              "id": "https://www.grid.ac/institutes/grid.6363.0", 
              "name": [
                "Departments of Obstetrics and Division of Experimental Obstetrics, Charit\u00e9 - University Berlin, Augustenburger Platz 1, Berlin, Germany"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Plagemann", 
            "givenName": "Andreas", 
            "id": "sg:person.0735467504.85", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0735467504.85"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Simon Fraser University", 
              "id": "https://www.grid.ac/institutes/grid.61971.38", 
              "name": [
                "Departments of Physiology, Obstetrics and Gynecology, University of Toronto, Toronto, Canada", 
                "Faculty of Health Sciences, Simon Fraser University, Vancouver, Canada"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Challis", 
            "givenName": "John RG", 
            "id": "sg:person.01323717606.09", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01323717606.09"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Charit\u00e9", 
              "id": "https://www.grid.ac/institutes/grid.6363.0", 
              "name": [
                "Departments of Obstetrics and Division of Experimental Obstetrics, Charit\u00e9 - University Berlin, Augustenburger Platz 1, Berlin, Germany"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Braun", 
            "givenName": "Thorsten", 
            "id": "sg:person.01020452114.36", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01020452114.36"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1023/b:bile.0000019559.84305.47", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000210937", 
              "https://doi.org/10.1023/b:bile.0000019559.84305.47"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0168-1656(99)00163-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000522703"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.bbagen.2012.12.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001961699"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/sj.onc.1203927", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002503210", 
              "https://doi.org/10.1038/sj.onc.1203927"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/sj.onc.1203927", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002503210", 
              "https://doi.org/10.1038/sj.onc.1203927"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/bbrc.1999.0815", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003465627"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0075850", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003506487"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.88.17.7605", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005795726"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1152/ajpendo.00459.2007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006152336"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.88.22.9979", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006174632"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2199-9-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007778040", 
              "https://doi.org/10.1186/1471-2199-9-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1373/clinchem.2008.112797", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007780642"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gad.1372606", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008436634"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1478-3231.2010.02428.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010978113"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1152/physiolgenomics.00223.2006", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012911134"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/scrt7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015786006", 
              "https://doi.org/10.1186/scrt7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0002750", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017643125"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1472-6750-6-41", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019830196", 
              "https://doi.org/10.1186/1472-6750-6-41"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1677/joe.0.1760175", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019853054"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1677/joe.0.1760175", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019853054"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1183/09031936.00129107", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021129863"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1746-6148-3-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022748481", 
              "https://doi.org/10.1186/1746-6148-3-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1128/mcb.19.2.1438", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024112852"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/12659", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024638800", 
              "https://doi.org/10.1038/12659"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/12659", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024638800", 
              "https://doi.org/10.1038/12659"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2008-9-1-r19", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024711501", 
              "https://doi.org/10.1186/gb-2008-9-1-r19"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/10495390903323851", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025158095"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1158/0008-5472.can-04-0496", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025731697"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/emboj/20.6.1383", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027024703"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/14651858.cd004454.pub2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029511630"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1530/rep.1.01203", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030814650"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jhep.2009.03.009", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031348220"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1128/mcb.20.16.5930-5938.2000", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031837532"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1477-7827-7-42", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033497165", 
              "https://doi.org/10.1186/1477-7827-7-42"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.placenta.2011.01.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035325258"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00109-005-0703-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035930415", 
              "https://doi.org/10.1007/s00109-005-0703-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00109-005-0703-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035930415", 
              "https://doi.org/10.1007/s00109-005-0703-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2199-10-72", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036461475", 
              "https://doi.org/10.1186/1471-2199-10-72"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/sj.gene.6364190", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037345611", 
              "https://doi.org/10.1038/sj.gene.6364190"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/sj.gene.6364190", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037345611", 
              "https://doi.org/10.1038/sj.gene.6364190"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1538-7836.2011.04526.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038264644"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2002-3-7-research0034", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039751959", 
              "https://doi.org/10.1186/gb-2002-3-7-research0034"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/abio.1999.4326", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043212400"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1746-6148-1-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043753527", 
              "https://doi.org/10.1186/1746-6148-1-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1677/joe.0.1750535", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043772315"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1677/joe.0.1750535", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043772315"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1152/japplphysiol.91092.2008", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043961411"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1530/eje.0.151u049", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044471343"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1530/eje.0.151u049", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044471343"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1530/eje.0.151u049", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044471343"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1074/jbc.m309393200", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044607953"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1095/biolreprod.108.073569", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045114299"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1172/jci1567", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046138682"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.neuron.2011.08.022", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048933761"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1183/09031936.06.00090405", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049330135"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0165-022x(00)00129-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051089120"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1159/000134827", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053107227"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2004-5-8-r59", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053687676", 
              "https://doi.org/10.1186/gb-2004-5-8-r59"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1017/s204017441200075x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1054959017"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/000155500750012397", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1058254357"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1124/pr.54.1.129", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062438731"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1177/1933719111418374", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064079116"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1177/1933719111418374", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064079116"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1210/en.2009-0086", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064249912"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1530/rep-07-0155", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1067716887"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1530/rep-09-0043", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1067717173"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.4161/org.4.3.6849", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1072306856"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1152/physiolgenomics.2000.2.3.143", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1074707686"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1152/ajpregu.2001.281.3.r960", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1074865670"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1158/0008-5472.can-04-2469", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1077039468"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/jn/138.6.1158", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1077651470"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3168/jds.2008-1164", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1077679311"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3168/jds.2008-1655", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1077890235"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2015-12", 
        "datePublishedReg": "2015-12-01", 
        "description": "BACKGROUND: The key to understanding changes in gene expression levels using reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) relies on the ability to rationalize the technique using internal control genes (ICGs). However, the use of ICGs has become increasingly problematic given that any genes, including housekeeping genes, thought to be stable across different tissue types, ages and treatment protocols, can be regulated at transcriptomic level. Our interest in prenatal glucocorticoid (GC) effects on fetal growth has resulted in our investigation of suitable ICGs relevant in this model. The usefulness of RNA18S, ACTB, HPRT1, RPLP0, PPIA and TUBB as ICGs was analyzed according to effects of early dexamethasone (DEX) treatment, gender, and gestational age by two approaches: (1) the classical approach where raw (i.e., not normalized) RT-qPCR data of tested ICGs were statistically analyzed and the best ICG selected based on absence of any significant effect; (2) used of published algorithms. For the latter the geNorm Visual Basic application was mainly used, but data were also analyzed by Normfinder and Bestkeeper. In order to account for confounding effects on the geNorm analysis due to co-regulation among ICGs tested, network analysis was performed using Ingenuity Pathway Analysis software. The expression of RNA18S, the most abundant transcript, and correlation of ICGs with RNA18S, total RNA, and liver-specific genes were also performed to assess potential dilution effect of raw RT-qPCR data. The effect of the two approaches used to select the best ICG(s) was compared by normalization of NR3C1 (glucocorticoid receptor) mRNA expression, as an example for a target gene.\nRESULTS: Raw RT-qPCR data of all the tested ICGs was significantly reduced across gestation. TUBB was the only ICG that was affected by DEX treatment. Using approach (1) all tested ICGs would have been rejected because they would initially appear as not reliable for normalization. However, geNorm analysis (approach 2) of the ICGs indicated that the geometrical mean of PPIA, HPRT1, RNA18S and RPLPO can be considered a reliable approach for normalization of target genes in both control and DEX treated groups. Different subset of ICGs were tested for normalization of NR3C1 expression and, despite the overall pattern of the mean was not extremely different, the statistical analysis uncovered a significant influence of the use of different normalization approaches on the expression of the target gene. We observed a decrease of total RNA through gestation, a lower decrease in raw RT-qPCR data of the two rRNA measured compared to ICGs, and a positive correlation between raw RT-qPCR data of ICGs and total RNA. Based on the same amount of total RNA to performed RT-qPCR analysis, those data indicated that other mRNA might have had a large increase in expression and, as consequence, had artificially diluted the stably expressed genes, such as ICGs. This point was demonstrated by a significant negative correlation of raw RT-qPCR data between ICGs and liver-specific genes.\nCONCLUSION: The study confirmed the necessity of assessing multiple ICGs using algorithms in order to obtain a reliable normalization of RT-qPCR data. Our data indicated that the use of the geometrical mean of PPIA, HPRT1, RNA18S and RPLPO can provide a reliable normalization for the proposed study. Furthermore, the dilution effect observed support the unreliability of the classical approach to test ICGs. Finally, the observed change in the composition of RNA species through time reveals the limitation of the use of ICGs to normalize RT-qPCR data, especially if absolute quantification is required.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1186/s13104-015-0973-7", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.6724630", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1039457", 
            "issn": [
              "1756-0500"
            ], 
            "name": "BMC Research Notes", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "8"
          }
        ], 
        "name": "The dilution effect and the importance of selecting the right internal control genes for RT-qPCR: a paradigmatic approach in fetal sheep", 
        "pagination": "58", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "cfd203fa6b9fb23014a79fa3bfe29e42414d0bb0b9959b4e0a13fff50ee66ade"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "25881111"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "101462768"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1186/s13104-015-0973-7"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1043629029"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1186/s13104-015-0973-7", 
          "https://app.dimensions.ai/details/publication/pub.1043629029"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T13:06", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000367_0000000367/records_88218_00000000.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1186%2Fs13104-015-0973-7"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s13104-015-0973-7'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13104-015-0973-7'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13104-015-0973-7'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13104-015-0973-7'


     

    This table displays all metadata directly associated to this object as RDF triples.

    445 TRIPLES      21 PREDICATES      113 URIs      41 LITERALS      29 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1186/s13104-015-0973-7 schema:about N05c22706778141819d95bb6630c321af
    2 N1370e2be235d40128eb0f35e80b1558a
    3 N13f44f0b6917424c8f2eda87952e5264
    4 N4d4eaea7e00840fd98baf5c420f96f00
    5 N4dbec545cbe84bab9d79a1f1215ede81
    6 N67ed43a8a70843b7928314f3638d6156
    7 N74dc65f6577e4618a41fd99ff05b3e67
    8 N86a7d83e742d415faa17a5a3b21a3c1c
    9 N8ac169b5901c496caf7d6a4cf399ad6c
    10 N97188b719c9f4fe2924fc7b69306d047
    11 N97a31ec51703494b9dfef33e184d63d2
    12 Na033b1bc159344b696ff95b881073ae4
    13 Nb31bf42db0bd4f79a04eb13bcb20d81f
    14 Nc354caa3738f4b708002c034a6b36047
    15 Nc73211f4516e4161ba64bf081d593e39
    16 Ncb0958a7af0a428e92abe88810be829c
    17 Ncb0c050d185d4e1b9fc73786d0b05bf9
    18 Ne32179d153d34127a0b1703a1d0e4f2d
    19 Nf7475c6cab3d4a6abc9560c7862c2508
    20 Nff39dc0d739f4365ba7632aace36a94b
    21 anzsrc-for:06
    22 anzsrc-for:0604
    23 schema:author N760469d567544d1cbcd6a0a0390e1ac0
    24 schema:citation sg:pub.10.1007/s00109-005-0703-z
    25 sg:pub.10.1023/b:bile.0000019559.84305.47
    26 sg:pub.10.1038/12659
    27 sg:pub.10.1038/sj.gene.6364190
    28 sg:pub.10.1038/sj.onc.1203927
    29 sg:pub.10.1186/1471-2199-10-72
    30 sg:pub.10.1186/1471-2199-9-9
    31 sg:pub.10.1186/1472-6750-6-41
    32 sg:pub.10.1186/1477-7827-7-42
    33 sg:pub.10.1186/1746-6148-1-3
    34 sg:pub.10.1186/1746-6148-3-7
    35 sg:pub.10.1186/gb-2002-3-7-research0034
    36 sg:pub.10.1186/gb-2004-5-8-r59
    37 sg:pub.10.1186/gb-2008-9-1-r19
    38 sg:pub.10.1186/scrt7
    39 https://doi.org/10.1002/14651858.cd004454.pub2
    40 https://doi.org/10.1006/abio.1999.4326
    41 https://doi.org/10.1006/bbrc.1999.0815
    42 https://doi.org/10.1016/j.bbagen.2012.12.013
    43 https://doi.org/10.1016/j.jhep.2009.03.009
    44 https://doi.org/10.1016/j.neuron.2011.08.022
    45 https://doi.org/10.1016/j.placenta.2011.01.007
    46 https://doi.org/10.1016/s0165-022x(00)00129-9
    47 https://doi.org/10.1016/s0168-1656(99)00163-7
    48 https://doi.org/10.1017/s204017441200075x
    49 https://doi.org/10.1073/pnas.88.17.7605
    50 https://doi.org/10.1073/pnas.88.22.9979
    51 https://doi.org/10.1074/jbc.m309393200
    52 https://doi.org/10.1080/000155500750012397
    53 https://doi.org/10.1080/10495390903323851
    54 https://doi.org/10.1093/emboj/20.6.1383
    55 https://doi.org/10.1093/jn/138.6.1158
    56 https://doi.org/10.1095/biolreprod.108.073569
    57 https://doi.org/10.1101/gad.1372606
    58 https://doi.org/10.1111/j.1478-3231.2010.02428.x
    59 https://doi.org/10.1111/j.1538-7836.2011.04526.x
    60 https://doi.org/10.1124/pr.54.1.129
    61 https://doi.org/10.1128/mcb.19.2.1438
    62 https://doi.org/10.1128/mcb.20.16.5930-5938.2000
    63 https://doi.org/10.1152/ajpendo.00459.2007
    64 https://doi.org/10.1152/ajpregu.2001.281.3.r960
    65 https://doi.org/10.1152/japplphysiol.91092.2008
    66 https://doi.org/10.1152/physiolgenomics.00223.2006
    67 https://doi.org/10.1152/physiolgenomics.2000.2.3.143
    68 https://doi.org/10.1158/0008-5472.can-04-0496
    69 https://doi.org/10.1158/0008-5472.can-04-2469
    70 https://doi.org/10.1159/000134827
    71 https://doi.org/10.1172/jci1567
    72 https://doi.org/10.1177/1933719111418374
    73 https://doi.org/10.1183/09031936.00129107
    74 https://doi.org/10.1183/09031936.06.00090405
    75 https://doi.org/10.1210/en.2009-0086
    76 https://doi.org/10.1371/journal.pone.0002750
    77 https://doi.org/10.1371/journal.pone.0075850
    78 https://doi.org/10.1373/clinchem.2008.112797
    79 https://doi.org/10.1530/eje.0.151u049
    80 https://doi.org/10.1530/rep-07-0155
    81 https://doi.org/10.1530/rep-09-0043
    82 https://doi.org/10.1530/rep.1.01203
    83 https://doi.org/10.1677/joe.0.1750535
    84 https://doi.org/10.1677/joe.0.1760175
    85 https://doi.org/10.3168/jds.2008-1164
    86 https://doi.org/10.3168/jds.2008-1655
    87 https://doi.org/10.4161/org.4.3.6849
    88 schema:datePublished 2015-12
    89 schema:datePublishedReg 2015-12-01
    90 schema:description BACKGROUND: The key to understanding changes in gene expression levels using reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) relies on the ability to rationalize the technique using internal control genes (ICGs). However, the use of ICGs has become increasingly problematic given that any genes, including housekeeping genes, thought to be stable across different tissue types, ages and treatment protocols, can be regulated at transcriptomic level. Our interest in prenatal glucocorticoid (GC) effects on fetal growth has resulted in our investigation of suitable ICGs relevant in this model. The usefulness of RNA18S, ACTB, HPRT1, RPLP0, PPIA and TUBB as ICGs was analyzed according to effects of early dexamethasone (DEX) treatment, gender, and gestational age by two approaches: (1) the classical approach where raw (i.e., not normalized) RT-qPCR data of tested ICGs were statistically analyzed and the best ICG selected based on absence of any significant effect; (2) used of published algorithms. For the latter the geNorm Visual Basic application was mainly used, but data were also analyzed by Normfinder and Bestkeeper. In order to account for confounding effects on the geNorm analysis due to co-regulation among ICGs tested, network analysis was performed using Ingenuity Pathway Analysis software. The expression of RNA18S, the most abundant transcript, and correlation of ICGs with RNA18S, total RNA, and liver-specific genes were also performed to assess potential dilution effect of raw RT-qPCR data. The effect of the two approaches used to select the best ICG(s) was compared by normalization of NR3C1 (glucocorticoid receptor) mRNA expression, as an example for a target gene. RESULTS: Raw RT-qPCR data of all the tested ICGs was significantly reduced across gestation. TUBB was the only ICG that was affected by DEX treatment. Using approach (1) all tested ICGs would have been rejected because they would initially appear as not reliable for normalization. However, geNorm analysis (approach 2) of the ICGs indicated that the geometrical mean of PPIA, HPRT1, RNA18S and RPLPO can be considered a reliable approach for normalization of target genes in both control and DEX treated groups. Different subset of ICGs were tested for normalization of NR3C1 expression and, despite the overall pattern of the mean was not extremely different, the statistical analysis uncovered a significant influence of the use of different normalization approaches on the expression of the target gene. We observed a decrease of total RNA through gestation, a lower decrease in raw RT-qPCR data of the two rRNA measured compared to ICGs, and a positive correlation between raw RT-qPCR data of ICGs and total RNA. Based on the same amount of total RNA to performed RT-qPCR analysis, those data indicated that other mRNA might have had a large increase in expression and, as consequence, had artificially diluted the stably expressed genes, such as ICGs. This point was demonstrated by a significant negative correlation of raw RT-qPCR data between ICGs and liver-specific genes. CONCLUSION: The study confirmed the necessity of assessing multiple ICGs using algorithms in order to obtain a reliable normalization of RT-qPCR data. Our data indicated that the use of the geometrical mean of PPIA, HPRT1, RNA18S and RPLPO can provide a reliable normalization for the proposed study. Furthermore, the dilution effect observed support the unreliability of the classical approach to test ICGs. Finally, the observed change in the composition of RNA species through time reveals the limitation of the use of ICGs to normalize RT-qPCR data, especially if absolute quantification is required.
    91 schema:genre research_article
    92 schema:inLanguage en
    93 schema:isAccessibleForFree true
    94 schema:isPartOf N6039eb9b6937494faa999a8e4155842c
    95 Ne564c77060a1455f856331958eb8d96c
    96 sg:journal.1039457
    97 schema:name The dilution effect and the importance of selecting the right internal control genes for RT-qPCR: a paradigmatic approach in fetal sheep
    98 schema:pagination 58
    99 schema:productId N41161a5e26a143a396884c5a76927abc
    100 N67a222a078a84a7f8dc478747a560256
    101 N6db08d164af54c01b10d5b2ceda418cb
    102 N92333aeb00ba433cb3e77ef86b488016
    103 Nc7da9ad3b5364f9e91261afa695ea0ed
    104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043629029
    105 https://doi.org/10.1186/s13104-015-0973-7
    106 schema:sdDatePublished 2019-04-11T13:06
    107 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    108 schema:sdPublisher N2ebb19b778974bb89bb00effb3c4aeb9
    109 schema:url https://link.springer.com/10.1186%2Fs13104-015-0973-7
    110 sgo:license sg:explorer/license/
    111 sgo:sdDataset articles
    112 rdf:type schema:ScholarlyArticle
    113 N05c22706778141819d95bb6630c321af schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    114 schema:name Dexamethasone
    115 rdf:type schema:DefinedTerm
    116 N1370e2be235d40128eb0f35e80b1558a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    117 schema:name Algorithms
    118 rdf:type schema:DefinedTerm
    119 N13f44f0b6917424c8f2eda87952e5264 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    120 schema:name Hypoxanthine Phosphoribosyltransferase
    121 rdf:type schema:DefinedTerm
    122 N18b5e6c25fb54e1d9f805941b7576967 rdf:first sg:person.01021220240.90
    123 rdf:rest N9346dd225b2e4982b8a53e4c583424bb
    124 N2ebb19b778974bb89bb00effb3c4aeb9 schema:name Springer Nature - SN SciGraph project
    125 rdf:type schema:Organization
    126 N3067cb11be2e46c9b023eab7d0e2cc4e rdf:first sg:person.0735467504.85
    127 rdf:rest Nf86970b5fa674b0283eb70cfd3e33bbf
    128 N41161a5e26a143a396884c5a76927abc schema:name pubmed_id
    129 schema:value 25881111
    130 rdf:type schema:PropertyValue
    131 N4a20923821d54308b151292fe453ae41 rdf:first sg:person.01066565314.14
    132 rdf:rest N18b5e6c25fb54e1d9f805941b7576967
    133 N4d4eaea7e00840fd98baf5c420f96f00 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    134 schema:name Gene Expression Profiling
    135 rdf:type schema:DefinedTerm
    136 N4dbec545cbe84bab9d79a1f1215ede81 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    137 schema:name Gene Expression
    138 rdf:type schema:DefinedTerm
    139 N55fa0306c9d740b7b9c23255b15e735a rdf:first sg:person.0747560146.35
    140 rdf:rest N3067cb11be2e46c9b023eab7d0e2cc4e
    141 N6039eb9b6937494faa999a8e4155842c schema:volumeNumber 8
    142 rdf:type schema:PublicationVolume
    143 N67a222a078a84a7f8dc478747a560256 schema:name dimensions_id
    144 schema:value pub.1043629029
    145 rdf:type schema:PropertyValue
    146 N67ed43a8a70843b7928314f3638d6156 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    147 schema:name Female
    148 rdf:type schema:DefinedTerm
    149 N6db08d164af54c01b10d5b2ceda418cb schema:name nlm_unique_id
    150 schema:value 101462768
    151 rdf:type schema:PropertyValue
    152 N74dc65f6577e4618a41fd99ff05b3e67 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    153 schema:name RNA, Messenger
    154 rdf:type schema:DefinedTerm
    155 N760469d567544d1cbcd6a0a0390e1ac0 rdf:first sg:person.0613063304.18
    156 rdf:rest N9ee55690c40f4c6fb62199c6457bdbe5
    157 N7adb26017a814446acbad44f5685b967 schema:name School of Women’s and Infants’ Health, King Edward Memorial Hospital, The University of Western Australia, and Women and Infants Research Foundation of Western Australia, Perth, Australia
    158 rdf:type schema:Organization
    159 N86a7d83e742d415faa17a5a3b21a3c1c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    160 schema:name Peptidylprolyl Isomerase
    161 rdf:type schema:DefinedTerm
    162 N8ac169b5901c496caf7d6a4cf399ad6c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    163 schema:name Ribosomal Proteins
    164 rdf:type schema:DefinedTerm
    165 N92333aeb00ba433cb3e77ef86b488016 schema:name readcube_id
    166 schema:value cfd203fa6b9fb23014a79fa3bfe29e42414d0bb0b9959b4e0a13fff50ee66ade
    167 rdf:type schema:PropertyValue
    168 N9346dd225b2e4982b8a53e4c583424bb rdf:first sg:person.01314463546.09
    169 rdf:rest N55fa0306c9d740b7b9c23255b15e735a
    170 N97188b719c9f4fe2924fc7b69306d047 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    171 schema:name Animals
    172 rdf:type schema:DefinedTerm
    173 N97a31ec51703494b9dfef33e184d63d2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    174 schema:name Pregnancy
    175 rdf:type schema:DefinedTerm
    176 N9db1ad5204d04c73a9b1bb47a49340fe rdf:first sg:person.01270354204.13
    177 rdf:rest N4a20923821d54308b151292fe453ae41
    178 N9ee55690c40f4c6fb62199c6457bdbe5 rdf:first sg:person.0676405057.20
    179 rdf:rest Nfa4b1745d4af4c5f89bfc19e9c63b712
    180 Na033b1bc159344b696ff95b881073ae4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    181 schema:name Gestational Age
    182 rdf:type schema:DefinedTerm
    183 Nb31bf42db0bd4f79a04eb13bcb20d81f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    184 schema:name Genes, Essential
    185 rdf:type schema:DefinedTerm
    186 Nb9428e8784da42f88c15d4ee0fe44769 rdf:first sg:person.01020452114.36
    187 rdf:rest rdf:nil
    188 Nc354caa3738f4b708002c034a6b36047 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    189 schema:name Real-Time Polymerase Chain Reaction
    190 rdf:type schema:DefinedTerm
    191 Nc73211f4516e4161ba64bf081d593e39 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    192 schema:name Fetus
    193 rdf:type schema:DefinedTerm
    194 Nc7da9ad3b5364f9e91261afa695ea0ed schema:name doi
    195 schema:value 10.1186/s13104-015-0973-7
    196 rdf:type schema:PropertyValue
    197 Ncb0958a7af0a428e92abe88810be829c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    198 schema:name Sheep, Domestic
    199 rdf:type schema:DefinedTerm
    200 Ncb0c050d185d4e1b9fc73786d0b05bf9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    201 schema:name Glucocorticoids
    202 rdf:type schema:DefinedTerm
    203 Ne32179d153d34127a0b1703a1d0e4f2d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    204 schema:name Receptors, Glucocorticoid
    205 rdf:type schema:DefinedTerm
    206 Ne564c77060a1455f856331958eb8d96c schema:issueNumber 1
    207 rdf:type schema:PublicationIssue
    208 Nf34f3b4597e34b69933b233c5f2ce951 schema:name School of Women’s and Infants’ Health, King Edward Memorial Hospital, The University of Western Australia, and Women and Infants Research Foundation of Western Australia, Perth, Australia
    209 rdf:type schema:Organization
    210 Nf7475c6cab3d4a6abc9560c7862c2508 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    211 schema:name RNA, Ribosomal, 18S
    212 rdf:type schema:DefinedTerm
    213 Nf86970b5fa674b0283eb70cfd3e33bbf rdf:first sg:person.01323717606.09
    214 rdf:rest Nb9428e8784da42f88c15d4ee0fe44769
    215 Nfa4b1745d4af4c5f89bfc19e9c63b712 rdf:first sg:person.01134700514.89
    216 rdf:rest N9db1ad5204d04c73a9b1bb47a49340fe
    217 Nff39dc0d739f4365ba7632aace36a94b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    218 schema:name Reference Standards
    219 rdf:type schema:DefinedTerm
    220 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
    221 schema:name Biological Sciences
    222 rdf:type schema:DefinedTerm
    223 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
    224 schema:name Genetics
    225 rdf:type schema:DefinedTerm
    226 sg:grant.6724630 http://pending.schema.org/fundedItem sg:pub.10.1186/s13104-015-0973-7
    227 rdf:type schema:MonetaryGrant
    228 sg:journal.1039457 schema:issn 1756-0500
    229 schema:name BMC Research Notes
    230 rdf:type schema:Periodical
    231 sg:person.01020452114.36 schema:affiliation https://www.grid.ac/institutes/grid.6363.0
    232 schema:familyName Braun
    233 schema:givenName Thorsten
    234 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01020452114.36
    235 rdf:type schema:Person
    236 sg:person.01021220240.90 schema:affiliation Nf34f3b4597e34b69933b233c5f2ce951
    237 schema:familyName Newnham
    238 schema:givenName John P
    239 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01021220240.90
    240 rdf:type schema:Person
    241 sg:person.01066565314.14 schema:affiliation N7adb26017a814446acbad44f5685b967
    242 schema:familyName Li
    243 schema:givenName Shaofu
    244 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01066565314.14
    245 rdf:type schema:Person
    246 sg:person.01134700514.89 schema:affiliation https://www.grid.ac/institutes/grid.25073.33
    247 schema:familyName Sloboda
    248 schema:givenName Deborah M
    249 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01134700514.89
    250 rdf:type schema:Person
    251 sg:person.01270354204.13 schema:affiliation https://www.grid.ac/institutes/grid.6363.0
    252 schema:familyName Ehrlich
    253 schema:givenName Loreen
    254 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01270354204.13
    255 rdf:type schema:Person
    256 sg:person.01314463546.09 schema:affiliation https://www.grid.ac/institutes/grid.6363.0
    257 schema:familyName Dudenhausen
    258 schema:givenName Joachim W
    259 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01314463546.09
    260 rdf:type schema:Person
    261 sg:person.01323717606.09 schema:affiliation https://www.grid.ac/institutes/grid.61971.38
    262 schema:familyName Challis
    263 schema:givenName John RG
    264 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01323717606.09
    265 rdf:type schema:Person
    266 sg:person.0613063304.18 schema:affiliation https://www.grid.ac/institutes/grid.415946.b
    267 schema:familyName Xu
    268 schema:givenName Huaisheng
    269 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0613063304.18
    270 rdf:type schema:Person
    271 sg:person.0676405057.20 schema:affiliation https://www.grid.ac/institutes/grid.4391.f
    272 schema:familyName Bionaz
    273 schema:givenName Massimo
    274 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0676405057.20
    275 rdf:type schema:Person
    276 sg:person.0735467504.85 schema:affiliation https://www.grid.ac/institutes/grid.6363.0
    277 schema:familyName Plagemann
    278 schema:givenName Andreas
    279 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0735467504.85
    280 rdf:type schema:Person
    281 sg:person.0747560146.35 schema:affiliation https://www.grid.ac/institutes/grid.6363.0
    282 schema:familyName Henrich
    283 schema:givenName Wolfgang
    284 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0747560146.35
    285 rdf:type schema:Person
    286 sg:pub.10.1007/s00109-005-0703-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1035930415
    287 https://doi.org/10.1007/s00109-005-0703-z
    288 rdf:type schema:CreativeWork
    289 sg:pub.10.1023/b:bile.0000019559.84305.47 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000210937
    290 https://doi.org/10.1023/b:bile.0000019559.84305.47
    291 rdf:type schema:CreativeWork
    292 sg:pub.10.1038/12659 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024638800
    293 https://doi.org/10.1038/12659
    294 rdf:type schema:CreativeWork
    295 sg:pub.10.1038/sj.gene.6364190 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037345611
    296 https://doi.org/10.1038/sj.gene.6364190
    297 rdf:type schema:CreativeWork
    298 sg:pub.10.1038/sj.onc.1203927 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002503210
    299 https://doi.org/10.1038/sj.onc.1203927
    300 rdf:type schema:CreativeWork
    301 sg:pub.10.1186/1471-2199-10-72 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036461475
    302 https://doi.org/10.1186/1471-2199-10-72
    303 rdf:type schema:CreativeWork
    304 sg:pub.10.1186/1471-2199-9-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007778040
    305 https://doi.org/10.1186/1471-2199-9-9
    306 rdf:type schema:CreativeWork
    307 sg:pub.10.1186/1472-6750-6-41 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019830196
    308 https://doi.org/10.1186/1472-6750-6-41
    309 rdf:type schema:CreativeWork
    310 sg:pub.10.1186/1477-7827-7-42 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033497165
    311 https://doi.org/10.1186/1477-7827-7-42
    312 rdf:type schema:CreativeWork
    313 sg:pub.10.1186/1746-6148-1-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043753527
    314 https://doi.org/10.1186/1746-6148-1-3
    315 rdf:type schema:CreativeWork
    316 sg:pub.10.1186/1746-6148-3-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022748481
    317 https://doi.org/10.1186/1746-6148-3-7
    318 rdf:type schema:CreativeWork
    319 sg:pub.10.1186/gb-2002-3-7-research0034 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039751959
    320 https://doi.org/10.1186/gb-2002-3-7-research0034
    321 rdf:type schema:CreativeWork
    322 sg:pub.10.1186/gb-2004-5-8-r59 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053687676
    323 https://doi.org/10.1186/gb-2004-5-8-r59
    324 rdf:type schema:CreativeWork
    325 sg:pub.10.1186/gb-2008-9-1-r19 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024711501
    326 https://doi.org/10.1186/gb-2008-9-1-r19
    327 rdf:type schema:CreativeWork
    328 sg:pub.10.1186/scrt7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015786006
    329 https://doi.org/10.1186/scrt7
    330 rdf:type schema:CreativeWork
    331 https://doi.org/10.1002/14651858.cd004454.pub2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029511630
    332 rdf:type schema:CreativeWork
    333 https://doi.org/10.1006/abio.1999.4326 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043212400
    334 rdf:type schema:CreativeWork
    335 https://doi.org/10.1006/bbrc.1999.0815 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003465627
    336 rdf:type schema:CreativeWork
    337 https://doi.org/10.1016/j.bbagen.2012.12.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001961699
    338 rdf:type schema:CreativeWork
    339 https://doi.org/10.1016/j.jhep.2009.03.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031348220
    340 rdf:type schema:CreativeWork
    341 https://doi.org/10.1016/j.neuron.2011.08.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048933761
    342 rdf:type schema:CreativeWork
    343 https://doi.org/10.1016/j.placenta.2011.01.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035325258
    344 rdf:type schema:CreativeWork
    345 https://doi.org/10.1016/s0165-022x(00)00129-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051089120
    346 rdf:type schema:CreativeWork
    347 https://doi.org/10.1016/s0168-1656(99)00163-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000522703
    348 rdf:type schema:CreativeWork
    349 https://doi.org/10.1017/s204017441200075x schema:sameAs https://app.dimensions.ai/details/publication/pub.1054959017
    350 rdf:type schema:CreativeWork
    351 https://doi.org/10.1073/pnas.88.17.7605 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005795726
    352 rdf:type schema:CreativeWork
    353 https://doi.org/10.1073/pnas.88.22.9979 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006174632
    354 rdf:type schema:CreativeWork
    355 https://doi.org/10.1074/jbc.m309393200 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044607953
    356 rdf:type schema:CreativeWork
    357 https://doi.org/10.1080/000155500750012397 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058254357
    358 rdf:type schema:CreativeWork
    359 https://doi.org/10.1080/10495390903323851 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025158095
    360 rdf:type schema:CreativeWork
    361 https://doi.org/10.1093/emboj/20.6.1383 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027024703
    362 rdf:type schema:CreativeWork
    363 https://doi.org/10.1093/jn/138.6.1158 schema:sameAs https://app.dimensions.ai/details/publication/pub.1077651470
    364 rdf:type schema:CreativeWork
    365 https://doi.org/10.1095/biolreprod.108.073569 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045114299
    366 rdf:type schema:CreativeWork
    367 https://doi.org/10.1101/gad.1372606 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008436634
    368 rdf:type schema:CreativeWork
    369 https://doi.org/10.1111/j.1478-3231.2010.02428.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1010978113
    370 rdf:type schema:CreativeWork
    371 https://doi.org/10.1111/j.1538-7836.2011.04526.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1038264644
    372 rdf:type schema:CreativeWork
    373 https://doi.org/10.1124/pr.54.1.129 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062438731
    374 rdf:type schema:CreativeWork
    375 https://doi.org/10.1128/mcb.19.2.1438 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024112852
    376 rdf:type schema:CreativeWork
    377 https://doi.org/10.1128/mcb.20.16.5930-5938.2000 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031837532
    378 rdf:type schema:CreativeWork
    379 https://doi.org/10.1152/ajpendo.00459.2007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006152336
    380 rdf:type schema:CreativeWork
    381 https://doi.org/10.1152/ajpregu.2001.281.3.r960 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074865670
    382 rdf:type schema:CreativeWork
    383 https://doi.org/10.1152/japplphysiol.91092.2008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043961411
    384 rdf:type schema:CreativeWork
    385 https://doi.org/10.1152/physiolgenomics.00223.2006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012911134
    386 rdf:type schema:CreativeWork
    387 https://doi.org/10.1152/physiolgenomics.2000.2.3.143 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074707686
    388 rdf:type schema:CreativeWork
    389 https://doi.org/10.1158/0008-5472.can-04-0496 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025731697
    390 rdf:type schema:CreativeWork
    391 https://doi.org/10.1158/0008-5472.can-04-2469 schema:sameAs https://app.dimensions.ai/details/publication/pub.1077039468
    392 rdf:type schema:CreativeWork
    393 https://doi.org/10.1159/000134827 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053107227
    394 rdf:type schema:CreativeWork
    395 https://doi.org/10.1172/jci1567 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046138682
    396 rdf:type schema:CreativeWork
    397 https://doi.org/10.1177/1933719111418374 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064079116
    398 rdf:type schema:CreativeWork
    399 https://doi.org/10.1183/09031936.00129107 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021129863
    400 rdf:type schema:CreativeWork
    401 https://doi.org/10.1183/09031936.06.00090405 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049330135
    402 rdf:type schema:CreativeWork
    403 https://doi.org/10.1210/en.2009-0086 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064249912
    404 rdf:type schema:CreativeWork
    405 https://doi.org/10.1371/journal.pone.0002750 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017643125
    406 rdf:type schema:CreativeWork
    407 https://doi.org/10.1371/journal.pone.0075850 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003506487
    408 rdf:type schema:CreativeWork
    409 https://doi.org/10.1373/clinchem.2008.112797 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007780642
    410 rdf:type schema:CreativeWork
    411 https://doi.org/10.1530/eje.0.151u049 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044471343
    412 rdf:type schema:CreativeWork
    413 https://doi.org/10.1530/rep-07-0155 schema:sameAs https://app.dimensions.ai/details/publication/pub.1067716887
    414 rdf:type schema:CreativeWork
    415 https://doi.org/10.1530/rep-09-0043 schema:sameAs https://app.dimensions.ai/details/publication/pub.1067717173
    416 rdf:type schema:CreativeWork
    417 https://doi.org/10.1530/rep.1.01203 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030814650
    418 rdf:type schema:CreativeWork
    419 https://doi.org/10.1677/joe.0.1750535 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043772315
    420 rdf:type schema:CreativeWork
    421 https://doi.org/10.1677/joe.0.1760175 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019853054
    422 rdf:type schema:CreativeWork
    423 https://doi.org/10.3168/jds.2008-1164 schema:sameAs https://app.dimensions.ai/details/publication/pub.1077679311
    424 rdf:type schema:CreativeWork
    425 https://doi.org/10.3168/jds.2008-1655 schema:sameAs https://app.dimensions.ai/details/publication/pub.1077890235
    426 rdf:type schema:CreativeWork
    427 https://doi.org/10.4161/org.4.3.6849 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072306856
    428 rdf:type schema:CreativeWork
    429 https://www.grid.ac/institutes/grid.25073.33 schema:alternateName McMaster University
    430 schema:name Departments of Biochemistry and Biomedical Sciences, Obstetrics & Gynecology and Pediatrics, McMaster University, Hamilton, Canada
    431 rdf:type schema:Organization
    432 https://www.grid.ac/institutes/grid.415946.b schema:alternateName Linyi People's Hospital
    433 schema:name Departments of Obstetrics and Division of Experimental Obstetrics, Charité - University Berlin, Augustenburger Platz 1, Berlin, Germany
    434 Departments of Obstetrics and Gynecology, Linyi People’s Hospital, Shandong, China
    435 rdf:type schema:Organization
    436 https://www.grid.ac/institutes/grid.4391.f schema:alternateName Oregon State University
    437 schema:name Animal and Rangeland Sciences, Oregon State University, Corvallis, USA
    438 rdf:type schema:Organization
    439 https://www.grid.ac/institutes/grid.61971.38 schema:alternateName Simon Fraser University
    440 schema:name Departments of Physiology, Obstetrics and Gynecology, University of Toronto, Toronto, Canada
    441 Faculty of Health Sciences, Simon Fraser University, Vancouver, Canada
    442 rdf:type schema:Organization
    443 https://www.grid.ac/institutes/grid.6363.0 schema:alternateName Charité
    444 schema:name Departments of Obstetrics and Division of Experimental Obstetrics, Charité - University Berlin, Augustenburger Platz 1, Berlin, Germany
    445 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...