Validation of Housekeeping Genes for Normalizing RNA Expression in Real-Time PCR

RESEARCH REPORT

Validation of housekeeping genes for normalizing RNA expression in real-time PCR

Keertan Dheda1, Jim F. Huggett1, Stephen A. Bustin2, Margaret A. Johnson1, Graham Rook1, and Alimuddin Zumla1

BioTechniques 37:112-119 (July 2004)

Analysis of RNA expression using techniques like real-time PCR has traditionally used reference or housekeeping genes to control for error between samples. This practice is being questioned as it becomes increasingly clear that some housekeeping genes may vary considerably in certain biological samples. We used real-time reverse transcription PCR (RT-PCR) to assess the levels of 13 housekeeping genes expressed in peripheral blood mononuclear cell culture and whole blood from healthy individuals and those with tuberculosis. Housekeeping genes were selected from conventionally used ones and from genes reported to be invariant in human T cell culture. None of the commonly used housekeeping genes [e.g., glyceraldehyde-phosphate-dehydrogenase (GAPDH)] were found to be suitable as internal references, as they were highly variable (>30-fold maximal variability). Furthermore, genes previously found to be invariant in human T cell culture also showed large variation in RNA expression (>34-fold maximal variability). Genes that were invariant in blood were highly variable in peripheral blood mononuclear cell culture. Our data show that RNA specifying human acidic ribosomal protein was the most suitable housekeeping gene for normalizing mRNA levels in human pulmonary tuberculosis. Validations of housekeeping genes are highly specific for a particular experimental model and are a crucial component in assessing any new model.

INTRODUCTION the chosen housekeeping gene fluctu- build research capacity (http://www. ates randomly between samples, then eubusiness.com/funding/research/ It is essential to control for error be- small differences between genes of rtd01_en.htm). We therefore required tween samples when measuring RNA interest will be missed. Furthermore, a method with simplicity and relative- expression. This error can be intro- if the experimental condition causes a ly low cost. The housekeeping gene duced at a number of stages throughout directional change in the housekeep- method of normalization was chosen the experimental protocol (input sam- ing gene, the subsequent normaliza- for this reason. Our main genes of in- ple, RNA extraction, reverse transcription will cause an erroneous result. terest specify cytokines that have low tion, etc.). There are many methods to This was shown in a study of human RNA expression (6). Consequently, control for this error. One approach is asthma, where target gene expression we anticipate that differences between to normalize to total RNA. However, between experimental groups became study groups may be small. Therefore this requires a reliable RNA quanti- falsely different when β-actin was it was important to find an internal fication method and fails to take into used as a normalizer (4). It was in fact reference that had minimal variability. account the variability of the reverse the β-actin rather than the target gene Previous reports have used conven- transcription and other steps. A widely that was changing (4). More recently, tional housekeeping genes in models of used alternative is to normalize RNA it has become clear that housekeeping tuberculosis (TB) to normalize for dif- levels to an internal reference or house- genes like β-actin and glyceraldehyde- fering amounts of input RNA (7–9), but keeping gene (1). 3-phosphate-dehydrogenase (GAPDH) there has been no report of studies to The expression levels of reference may be inappropriate as internal refer- check the validity of these housekeep- genes should remain constant between ences because of their variability (5). ing genes in TB or in in vitro lympho- the cells of different tissues and under Appropriate validation of internal ref- cyte cultures. We used real-time reverse different experimental conditions (2). erences is therefore crucial to avoid transcription PCR (RT-PCR) to study If these requirements are not fulfilled, misinterpretations of study findings. the levels of 13 housekeeping genes ex- then normalization to varying inter- Our experimental protocols will pressed in whole blood and peripheral nal references can lead to increased be transferred to sites in the devel- blood mononuclear cell (PBMC) cul- “noise” or erroneous results (3). If oping world as part of a program to ture of healthy volunteers and patients

1Royal Free Medical School, London and 2Queen Mary’s School of Medicine and Dentistry, London, UK

112 BioTechniques Vol. 37, No. 1 (2004) Table 1. Housekeeping Genes Selected for Group 1 and Group 2 Panels as a requirement for suitability Group 1 Housekeeping Genes Group 2 Housekeeping Genes as a reference gene. We did not use ribosomal Human acidic ribosomal protein (HuPO) Human acidic ribosomal protein (HuPO) subunit RNAs as housekeeping β-Actin (BA) Elongation factor-1-α (EF-1-α) Cyclophylin (CYC) Metastatic lymph node 51 (MLN51) genes, as we used oligo(dT) as Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) Ubiquitin conjugating enzyme (UbcH5B) a primer for cDNA synthesis, Phosphoglycerokinase (PGK) and compared to specific down-

β2-Microglobulin (B2M) stream primers, random hexamer β-Glucuronidase (GUS) primers have been shown to Hypoxanthine phosphoribosyltransferase (HPRT) overestimate mRNA copy num- Transcription factor IID TATA binding protein (TBP) bers by up to 19-fold (15). Transferrin receptor (TfR) Isolation of RNA and cDNA with TB. Housekeeping genes were and penicillin-streptomycin) at a cell Synthesis selected from those usually used and concentration of 1 × 106 cells/mL (final others found to be invariant in human volume of 0.5 mL) in 24-well plates. RNA was isolated from whole blood T cell culture (10). Here we report a Cells stimulated with TB antigen (12) collected in PAXgene tubes using the validation exercise to identify the most and harvested at baseline and days 2/3. PreAnalytiX PAXgene blood RNA kit suitable housekeeping gene in studies Days 4/5 were used for housekeeping (Qiagen) and from harvested PBMCs of pulmonary tuberculosis (PTB). gene expression studies. Control wells using the RNeasy® Mini kit (Qiagen). were challenged with phytohemagglu- All samples were DNase (Qiagen) tinin, Mycobacterium vaccae sonicate, treated. The RNA template was quali- MATERIALS AND METHODS or no antigen. Cell viability was as- tatively assessed and quantified us- sessed at each harvest with trypan blue, ing an Agilent 2100 Bioanalyzer with ® Patients and Samples and a proliferation assay was performed the RNA 6000 Nano Labchip kit for on days 4/5 to quantify the proliferative blood-derived RNA and the RNA 6000 Clinical samples (n = 28) were taken response to antigen challenge [bromo- Pico Labchip kit for culture-derived from four patients with smear-positive deoxyuridine (BrdU) cell proliferation RNA (all from Agilent Technologies, PTB, four healthy individuals, and the enzyme-linked immunosorbent assay Palo Alto, CA, USA). Total RNA ex- cells harvested from PBMC cultures of (ELISA); Roche Applied Science, In- traction varied from approximately 1–5 four additional patients with PTB. In dianapolis, IN, USA]. μg for blood and 0.1–0.8 μg from 5 × order to maximize variability, we chose 105 cells. To study the effect on house- subjects of different ages (from 26 to 50 Selection of Housekeeping Genes keeping gene expression, we used a years), sex, and ethnicity (Caucasian, fixed amount of input RNA for each Somalian, Indian, Chinese, Filipino, We first studied the gene expression cDNA reaction. Limited RNA quanti- and Black African). Informed consent levels of 10 housekeeping genes (des- ties dictated input RNA amounts to be was obtained from patients, and the ignated group 1) using a commercially 600 ng for PTB patients, 400 ng for relevant hospital ethics committees ap- available assay (TaqMan® human en- healthy volunteers, and 3 ng for the proved the study. dogenous control plate; Applied Bio- PBMC culture reactions. Reverse tran- Whole blood (20 mL) was taken, systems, Foster City, CA, USA) (13). scription reactions were performed fol- and 2.5 mL was immediately trans- The 10 genes investigated in this as- lowing the manufacturer’s instructions ferred into PreAnalytiX PAXgene™ say are shown in Table 1. We selected using Omniscript® Reverse Transcrip- blood RNA tubes (Qiagen, Valencia, group 2 genes as they were among 47 tase (Qiagen) for blood-derived RNA CA, USA) to fix the mRNA expression out of 535 maintenance genes found by and Sensiscript® Reverse Transcriptase profile (11). The remaining blood was microarray data to be relatively stable (Qiagen) for culture-derived RNA in transferred to a heparinized container in 11 different human tissues (14), and 60-μL reactions. and transported in a thermo flask at since they were found to be invariant in 37°C. Heparinized blood was incubat- human CD4 T cell cultures from cord Real-Time PCR ed at 37°C for a further 4 h on reach- blood (10). ing the laboratory, after which a further Our aim was to identify a house- The PCRs for group 1 genes were 2.5-mL sample was transferred to a keeping gene with minimal variability performed using the ABI Prism® 7700 PAXgene tube. under our different experimental condi- Sequence Detection System (Applied Blood taken from four of the pa- tions. As some of the genes of interest Biosystems). In each reaction, approxi- tients with PTB was layered over a Fi- are low-copy number cytokines, we mately 15 and 0.1 ng of reverse-tran- coll-Paque® gradient (Amersham Bio- anticipated that a significant change scribed RNA (based on the initial RNA sciences, Piscataway, NJ, USA) and the between study groups was likely to be concentration) was used for blood and PBMCs isolated. PBMCs were cultured small. Therefore, a standard deviation cell culture PCRs, respectively. The in triplicate in RPMI (supplemented of less than 2-fold from the mean ex- TaqMan endogenous control plate as- with 5% human AB serum, glutamine, pression level of the gene was chosen say was used according to the manufac- Vol. 37, No. 1 (2004) BioTechniques 113 RESEARCH REPORT

turer’s instructions, with the exception RESULTS ing gene. Figure 2 shows the standard of the 18S ribosomal RNA reaction, deviation expressed as a fold change which was omitted (initial step of 50°C Housekeeping Gene Expression in from the mean and range expressed for 2 min and 95°C for 10 min, fol- Whole Blood as maximum variability for selected lowed by 40 cycles of 95°C for 15 s housekeeping genes in whole blood. and 60°C for 1 min, in a 50-µL reaction The median expression level (Ct The most stable housekeeping gene volume). Using these parameters, the value) of group 1 and group 2 house- in whole blood was HuPO, with an reaction efficiency approaches 100%. keeping genes for whole blood (n = 16) average fold change of <2 and a maxi- The primer and probe sequences for are shown in Figure 1 (A and B). Also mal variability of <5-fold. There was group 2 were obtained from previously shown are Ct 25th and 75th percentile considerably greater variability for published work (10). These sequences values and ranges for each housekeep- GAPDH, β-actin, and hypoxanthine are shown in Table 2. Primers and probes were synthesized by MWG (Eb- ersberg, Germany) and Sigma-Genosys Ltd. (Cambridgeshire, UK), respective- � 40 ly, with the exception of human acidic ribosomal protein (HuPO), which was purchased from Applied Biosystems 35 (Assays-on-Demand™). Primers and

probes were used at 500 and 300 nM, d

respectively, in a 50-μL reaction. The hol 30

reactions were performed on the 7700 res Sequence Detection System with the h e T l

same parameters as the group 1 genes. c y 25

Reaction efficiencies for group 2 genes C (range of 96%–100%) were derived from serial dilutions of purified PCR product. Amplification of the correct 20 product was confirmed by using the Agilent 2100 Bioanalyzer (with the DNA 500 Labchip Kit; Agilent Tech- 15 nologies) (16). All reactions were run �� in duplicate, and cycle threshold (Ct) �� values for group 1 genes were normal- ized to the internal positive control Housekeeping Genes (IPC) to control for interplate variability. HuPO measurements were used to � 35 compare the results between groups 1 and 2. Nontemplate controls were used as recommended (5). d 30 hol s e Data Presentation and Calculations r 25 e Th l

In PCRs with efficiencies approach- c y

ing 100%, the amount of internal refer- C ence gene relative to a calibrator (fold 20 change between two Ct values) is given by the equation (17): 15 Fold difference = 2-∆Ct ��

At a reaction efficiency of 100%, 1 cy- Housekeeping Genes cle (expressed as Ct in real-time PCR) corresponds to a 2-fold change. The Figure 1. Real-time PCR cycle threshold values in blood samples. Expression levels of group 1 genes variability of individual housekeeping (A) and group 2 genes (B) are shown as medians (lines), 25th percentile to the 75th percentile (boxes) genes were reflected as standard devia- and ranges (whiskers) for 16 human blood samples (4 healthy and 4 tuberculosis patients at two time tion and ranges, expressed as an aver- points 4 h apart). HuPO, human acidic ribosomal protein; BA, β-actin; CYC, cyclophylin; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; PGK, phosphoglycerokinase; B2M, β2-microglobulin; GUS, age fold change from the mean or as a β-glucuronidase; HPRT, hypoxanthine phosphoribosyltransferase; TBP, transcription factor IID TATA maximum fold change (maximum vari- binding protein; TfR, transferrin receptorl; UbcH5B, ubiquitin conjugating enzyme; EF-1-α, elongation ability), respectively. factor-1-α; MLN51, metastatic lymph node 51.

114 BioTechniques Vol. 37, No. 1 (2004) RESEARCH REPORT

Table 2. Primer and Probe Sequences Used to Quantify Gene Expression by Real-Time PCR TB revealed only one gene suit- Product able for normalization of RNA Genes Sequences Size R2 levels. According to our selec- (bp) tion criteria of <2-fold, HuPO EF-1-α probe: 5′-(FAM-AGCGCCGGCTATGCCCCTG-TAMRA)-3′ 59 0.992 was the most suitable gene over- primer 1: 5′-CTGAACCATCCAGGCCAAAT-3′ all (blood and PBMC culture). primer 2: 5′-GCCGTGTGGCAATCCAAT-3′ GAPDH and β-actin did not satisfy our suitability criteria MLN51 probe: 5′-(FAM-AGGCCTGTGGAAGCTGGTGGGC-TAMRA)-3′ 72 0.999 and had an unacceptably high primer 1: 5′-CAAGGAAGGTCGTGCTGGTT-3′ maximal variability. Moreover, primer 2: 5′-ACCAGACCGGCCACCAT-3′ genes found to be invariant in mitogen-stimulated human T UbcH5B probe: 5′-(FAM-TGATCTGGCACGGGACCCTCCA-TAMRA)-3′ 64 0.999 cell cultures (10) were found to primer 1: 5′-TGAAGAGAATCCACAAGGAATTGA-3′ be unsuitable when studied in primer 2: 5′-CAACAGGACCTGCTGAACACTG-3′ human PBMC cultures stimu- HuPO Assays-on-Demand (Applied Biosystems) 110 0.999 lated with TB antigen. Other genes like HPRT were more Group 1 TaqMan Human Endogenous Control Plate (Applied Biosystems) N.A. N.A. variable in whole blood than in proliferating PBMC cultures. EF-1-α, elongation factor-1-α; MLN51, metastatic lymph node 51; UbcH5B, ubiquitin conjugating enzyme; HuPO, This report shows that house- human acidic ribosomal protein; N.A., not applicable. keeping genes are highly specific for a particular experimen- phosphoribosyltransferase (HPRT) as fold changes. The most stable house- tal model, and validation for (maximum variability of 20- to 25- keeping genes in PBMC culture were each situation, on an individual basis, is fold). When gene expression at 4 h was HuPO and HPRT with an average fold a crucial requirement. compared to baseline, there was little change of <2 and a maximal variabil- Housekeeping genes can be variable difference in the expression levels of all ity of approximately 5-fold each. The and prone to directional shifts induced 13 genes (average fold change for all most variable genes were GAPDH, β2- by experimental conditions, thereby genes over 4 h = 1.37 ± 0.33x). microglobulin, β-actin, and elongation causing problems for reliable normal- factor 1-α (EF-1-α) with an average ization. An alternative is normalization Housekeeping Gene Expression in fold of >2 and a maximum variability to total RNA. This approach avoids the PBMC Culture of 20- to 35-fold. controversies and validation of housekeeping genes. However, it does not The median expression levels (Ct control for error introduced by the re- value) of group 1 and group 2 house- DISCUSSION verse transcription and other steps and keeping genes for PBMC culture (n = requires significant amounts of RNA. 12) are shown in Figure 3 (A and B). A study of the expression levels of More importantly, there must be an Figure 4 shows the Ct values expressed 13 housekeeping genes in patients with accurate and reliable method of RNA quantification. This can be problem- atic when a spectrophotometer is used 35 because of instrument insensitivity, signal contribution by contaminants, 30 residual DNA despite DNAase treat- 25 ment, and unreliability at concentra- tions below 100 ng/μL (3,5). We have 20 found the Agilent 2100 Bioanalyzer to 15 give consistent results between group

�� 1 and group 2 genes, and it is gener- 10 ally considered to be more reliable 5 than a spectrophotometer (5). The an- 0 alyzer, however, is expensive and may �� not be widely available, especially to laboratories in developing countries �� where the burden of TB is the highest, and there is an urgent need to build re- Figure 2. Fold change in gene expression. Variability of selected group 1 genes and group 2 genes search capacity. in human whole blood shown as an average fold change from the mean (columns) and maximum fold The data presented here describe a change (error bars). HuPO, human acidic ribosomal protein; BA, β-actin; GAPDH, glyceraldehyde-3- practical alternative to RNA normal- phosphate dehydrogenase; HPRT, hypoxanthine phosphoribosyltransferase; B2M, β2-microglobulin; EF-1-α, elongation factor-1-α; UbcH5B, ubiquitin conjugating enzyme. ization and address some of the prob- 116 BioTechniques Vol. 37, No. 1 (2004) RESEARCH REPORT

lems with housekeeping genes. For our number cytokines. The disadvantage of od in small laboratories or those from model of cytokine study in human TB, HK gene validation is that considerable resource-poor settings when studying finding a suitable housekeeping gene effort and cost is expended to perform TB host gene expression in blood and created a convenient way to normal- an exercise like the one presented here. PBMC culture. ize for differing input amounts of RNA This may not be feasible in small stud- In order to create maximum vari- and avoided the errors associated with ies or those with limited budgets. Simi- ability, we used subjects of different GAPDH and β-actin. We also defined lar constraints apply to normalization ages, sex, and ethnic backgrounds. We the limits of the HuPO gene’s vari- with an average of three housekeeping also used different tissues or cell types ability, which is helpful for data inter- genes (18). Our findings will facilitate sampled at different time points, which pretation when normalizing low-copy the use of the housekeeping gene meth- included cells challenged with TB antigen. Our selection of subjects and time points mirrored experimental protocols that we propose to use in our laboratory � 40 to study cytokines. We found that the housekeeping gene variability in blood was largely due to inter-individual differences. There was surprisingly little d difference in gene expression levels at hol

s 35 4 h in the samples of both healthy and e

r TB patients, considering that these h samples had been subjected to in vitro

le T storage conditions for several hours. It c

y is possible that the expression of highly

C 30 regulated genes [e.g., cyclooxygenase- 2 (COX2)] would have shown a large variability between time points. Com- pared to blood, the variability in culture 25 was due to both inter-individual differences and differences between different �� culture time points. These differences �� were not patient specific. Housekeeping Genes We found that using the Applied Biosystems’ commercial plate was a convenient way to do our initial screen � 40 because these genes vary in expression levels and cover a wide range of biological functions. We selected group 2 genes d 35 to increase the number of genes consid-

hol ered in our validation exercise. A variability of 2-fold was chosen, as some res

h cytokines [e.g., interleukin 4 (IL-4)] are 30 both expressed and biologically func- e T l

c tional at low levels (17). A one-log dif- y

C ference is significant in human models 25 of TB (19). A housekeeping gene with wider variability would increase the assay noise, hence limiting sensitivity. In conclusion, HuPO is suitable for 20 use as a housekeeping gene in models �� of human PTB when gene expression is Housekeeping Genes studied in whole blood and PBMC cultures. GAPDH and β-actin are unsuit- Figure 3. Real-time PCR cycle threshold values in peripheral blood mononuclear cell (PBMC) able for this purpose. Whatever strat- culture samples. Expression levels of group 1 genes (A) and group 2 genes (B) are shown as medians egy is used to control for differences (lines), 25th percentile to the 75th percentile (boxes), and ranges (whiskers) for 12 human PBMC in input RNA it must be validated for culture samples (4 tuberculosis patients at 3 time points). HuPO, human acidic ribosomal protein; a particular experimental model on an BA, β-actin; CYC, cyclophylin; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; PGK, phos- individual basis. This is to avoid sig- phoglycerokinase; B2M, β2-microglobulin; GUS, β-glucuronidase; HPRT, hypoxanthine phosphoribosyltransferase; UbcH5B, ubiquitin conjugating enzyme; EF-1-α, elongation factor-1-α; MLN51, nificant inaccuracies when quantifying metastatic lymph node 51. target gene expression.

118 BioTechniques Vol. 37, No. 1 (2004) Evaluation of DNA fragment sizing and quan- 40 tification by the agilent 2100 bioanalyzer. 35 Clin. Chem. 46:1851-1853. 17.Livak, K.J. and T.D. Schmittgen. 2001. 30 Analysis of relative gene expression data us- 25 ing real-time quantitative PCR and the 2(-Del- hange 20 ta Delta C(T)) method. Methods 25:402-408. C d

l 18.Vandesompele, J., K. Preter, F. Pattyn, B.

o 15

F Poppe, N. Van Roy, A. De Paepe, and F. 10 Speleman. 2002. Accurate normalization of 5 real-time quantitative RT-PCR data by geo- metric averaging of multiple internal control 0 genes. Genome Biol. 3:RESEARCH0034. �� 19.Seah, G.T., G.M. Scott, and G.A. Rook. �� 2000. Type 2 cytokine gene activation and its relationship to extent of disease in patients Figure 4. Fold change in gene expression. Variability of selected group 1 genes and group 2 genes in hu- with tuberculosis. J. Infect. Dis. 181:385-389. man peripheral blood mononuclear cell (PBMC) culture shown as an average fold change from the mean (columns) and maximum fold change (error bars). HuPO, human acidic ribosomal protein; BA, β-actin; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; HPRT, hypoxanthine phosphoribosyltransferase; Received 30 January 2004; accepted B2M, β2-microglobulin; EF-1-α, elongation factor-1-α; UbcH5B, ubiquitin conjugating enzyme. 19 March 2004.

Address correspondence to: Jim F. Huggett ACKNOWLEDGMENTS characteristic of nonreplicating persistence. Centre for Infectious Diseases and International Proc. Natl. Acad. Sci. USA 100:241-246. Health This work was supported by a grant 9.Kawahara, M., T. Nakasone, and M. Hon- UCL and Royal Free Medical School da. 2002. Dynamics of gamma interferon, 46 Cleveland Street from the British Lung Foundation. interleukin-12 (IL-12), IL-10, and transform- London W1T 4JF, UK ing growth factor beta mRNA expression in e-mail: [email protected] primary Mycobacterium bovis BCG infection REFERENCES in guinea pigs measured by a real-time fluoro- genic reverse transcription-PCR assay. Infect. 1.Karge III, W.H., E.J. Schaefer, and J.M. Immun. 70:6614-6620. Ordovas. 1998. Quantification of mRNA by 10.Hamalainen, H.K., J.C. Tubman, S. Vik- polymerase chain reaction (PCR) using an in- man, T. Kyrola, E. Ylikoski, J.A. Warring- ternal standard and a nonradioactive detection ton, and R. Lahesmaa. 2001. Identification method. Methods Mol. Biol. 110:43-61. and validation of endogenous reference genes 2.Thellin, O., W. Zorzi, B. Lakaye, B. De Bor- for expression profiling of T helper cell dif- man, B. Coumans, G. Hennen, T. Grisar, A. ferentiation by quantitative real-time RT-PCR. Igout, and E. Heinen. 1999. Housekeeping Anal. Biochem. 299:63-70. genes as internal standards: use and limits. J. 11.Rainen, L., U. Oelmueller, S. Jurgensen, R. Biotechnol. 75:291-295. Wyrich, C. Ballas, J. Schram, C. Herdman, 3.Bustin, S.A. 2000. Absolute quantification of and D. Bankaitis-Davis, et al. 2002. Stabi- mRNA using real-time reverse transcription lization of mRNA expression in whole blood polymerase chain reaction assays. J. Mol. En- samples. Clin. Chem. 48:1883-1890. docrinol. 2:169-193. 12.Seah, GT., and G.A. Rook. 2001. IL-4 influ- 4.Glare, E.M., M. Divjak, M.J. Bailey, and ences apoptosis of mycobacterium-reactive E.H. Walters. 2002. β-Actin and GAPDH lymphocytes in the presence of TNF-alpha. J. housekeeping gene expression in asthmatic Immunol. 167:1230-1237. airways is variable and not suitable for nor- 13.Tricarico, C., P. Pinzani, S. Bianchi, M. malising mRNA levels. Thorax 57:765-770. Paglierani, V. Distante, M. Pazzagli, S.A. 5.Bustin, S.A. 2002. Quantification of mRNA Bustin, and C. Orlando. 2002. Quantitative using real-time reverse transcription PCR real-time reverse transcription polymerase (RT-PCR): trends and problems. J. Mol. En- chain reaction: normalization to rRNA or docrinol. 1:23-39. single housekeeping genes is inappropriate 6.Lewis, D.B., K.S. Prickett, A. Larsen, K. for human tissue biopsies. Anal. Biochem. Grabstein, M. Weaver, and C.B. Wilson. 309:293-300. 1988. Restricted production of interleukin 4 14.Warrington, J.A., A. Nair, M. Mahadevap- by activated human T cells. Proc. Natl. Acad. pa, and M. Tsyganskaya. 2000. Comparison Sci. USA 85:9743-9747. of human adult and fetal expression and iden- 7.Zhu, G., H. Xiao, V.P. Mohan, K. Tanaka, tification of 535 housekeeping/maintenance S. Tyagi, F. Tsen, P. Salgame, and J. Chan. genes. Physiol. Genomics 2:143-147. 2003. Gene expression in the tuberculous 15.Zhang, J. and C.D. Byrne. 1999. Differen- granuloma: analysis by laser capture micro- tial priming of RNA templates during cDNA dissection and real-time PCR. Cell Microbiol. synthesis markedly affects both accuracy 5:445-453. and reproducibility of quantitative competi- 8.Shi, L., Y.J. Jung, S. Tyagi, M.L. Gennaro, tive reverse-transcriptase PCR. Biochem. J. and R.J. North. 2003. Expression of Th1-me- 337:231-241. diated immunity in mouse lungs induces a My- 16.Panaro, N.J., P.K. Yuen, T. Sakazume, P. cobacterium tuberculosis transcription pattern Fortina, L.J. Kricka, and P. Wilding. 2000.

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