Natural Gene-Expression Variation in Down Syndrome Modulates the Outcome of Gene-Dosage Imbalance
2007; Elsevier BV; Volume: 81; Issue: 2 Linguagem: Inglês
10.1086/519248
ISSN1537-6605
AutoresPaola Prandini, Samuel Deutsch, Robert Lyle, Maryline Gagnebin, Céline Delucinge Vivier, Mauro Delorenzi, Corinne Gehrig, Patrick Descombes, Stephanie L. Sherman, F. Dagna Bricarelli, Chiara Baldo, Antonio Novelli, Bruno Dallapiccola, Stylianos E. Antonarakis,
Tópico(s)Genomics and Rare Diseases
ResumoDown syndrome (DS) is characterized by extensive phenotypic variability, with most traits occurring in only a fraction of affected individuals. Substantial gene-expression variation is present among unaffected individuals, and this variation has a strong genetic component. Since DS is caused by genomic-dosage imbalance, we hypothesize that gene-expression variation of human chromosome 21 (HSA21) genes in individuals with DS has an impact on the phenotypic variability among affected individuals. We studied gene-expression variation in 14 lymphoblastoid and 17 fibroblast cell lines from individuals with DS and an equal number of controls. Gene expression was assayed using quantitative real-time polymerase chain reaction on 100 and 106 HSA21 genes and 23 and 26 non-HSA21 genes in lymphoblastoid and fibroblast cell lines, respectively. Surprisingly, only 39% and 62% of HSA21 genes in lymphoblastoid and fibroblast cells, respectively, showed a statistically significant difference between DS and normal samples, although the average up-regulation of HSA21 genes was close to the expected 1.5-fold in both cell types. Gene-expression variation in DS and normal samples was evaluated using the Kolmogorov-Smirnov test. According to the degree of overlap in expression levels, we classified all genes into 3 groups: (A) nonoverlapping, (B) partially overlapping, and (C) extensively overlapping expression distributions between normal and DS samples. We hypothesize that, in each cell type, group A genes are the most dosage sensitive and are most likely involved in the constant DS traits, group B genes might be involved in variable DS traits, and group C genes are not dosage sensitive and are least likely to participate in DS pathological phenotypes. This study provides the first extensive data set on HSA21 gene-expression variation in DS and underscores its role in modulating the outcome of gene-dosage imbalance. Down syndrome (DS) is characterized by extensive phenotypic variability, with most traits occurring in only a fraction of affected individuals. Substantial gene-expression variation is present among unaffected individuals, and this variation has a strong genetic component. Since DS is caused by genomic-dosage imbalance, we hypothesize that gene-expression variation of human chromosome 21 (HSA21) genes in individuals with DS has an impact on the phenotypic variability among affected individuals. We studied gene-expression variation in 14 lymphoblastoid and 17 fibroblast cell lines from individuals with DS and an equal number of controls. Gene expression was assayed using quantitative real-time polymerase chain reaction on 100 and 106 HSA21 genes and 23 and 26 non-HSA21 genes in lymphoblastoid and fibroblast cell lines, respectively. Surprisingly, only 39% and 62% of HSA21 genes in lymphoblastoid and fibroblast cells, respectively, showed a statistically significant difference between DS and normal samples, although the average up-regulation of HSA21 genes was close to the expected 1.5-fold in both cell types. Gene-expression variation in DS and normal samples was evaluated using the Kolmogorov-Smirnov test. According to the degree of overlap in expression levels, we classified all genes into 3 groups: (A) nonoverlapping, (B) partially overlapping, and (C) extensively overlapping expression distributions between normal and DS samples. We hypothesize that, in each cell type, group A genes are the most dosage sensitive and are most likely involved in the constant DS traits, group B genes might be involved in variable DS traits, and group C genes are not dosage sensitive and are least likely to participate in DS pathological phenotypes. This study provides the first extensive data set on HSA21 gene-expression variation in DS and underscores its role in modulating the outcome of gene-dosage imbalance. The clinical presentation of Down syndrome (DS) or trisomy 21 (MIM 190685) is complex and highly variable.1Epstein CJ Down syndrome, trisomy 21.in: Scriver CR Beaudet AL Sly WS Valle D Metabolic basis of inherited disease. McGraw-Hill, New York1989: 291-326Google Scholar Cognitive impairment, muscle hypotonia at birth, and dysmorphic features occur to some extent in all affected individuals. In contrast, the majority of the other associated traits are present in only a fraction of individuals with trisomy 21. In addition, the severity of many phenotypic traits varies greatly.2Roizen NJ Patterson D Down's syndrome.Lancet. 2003; 361: 1281-1289Abstract Full Text Full Text PDF PubMed Scopus (815) Google Scholar Theoretically, the supernumerary copy of human chromosome 21 (HSA21) is expected to result in a 50% increase in the level of transcripts of all genes mapping to HSA21. However, it has been recently observed that there is not always a direct correlation between genomic imbalance (deletion or duplication) and transcript level of genes within the aneuploid segment, suggesting that complex molecular mechanisms regulate RNA transcript levels.3Lyle R Gehrig C Neergaard-Henrichsen C Deutsch S Antonarakis SE Gene expression from the aneuploid chromosome in a trisomy mouse model of Down syndrome.Genome Res. 2004; 14: 1268-1274Crossref PubMed Scopus (150) Google Scholar, 4Merla G Howald C Henrichsen CN Lyle R Wyss C Zabot MT Antonarakis SE Reymond A Submicroscopic deletion in patients with Williams-Beuren syndrome influences expression levels of the nonhemizygous flanking genes.Am J Hum Genet. 2006; 79: 332-341Abstract Full Text Full Text PDF PubMed Scopus (137) Google Scholar, 5Kahlem P Sultan M Herwig R Steinfath M Balzereit D Eppens B Saran NG Pletcher MT South ST Stetten G et al.Transcript level alterations reflect gene dosage effects across multiple tissues in a mouse model of Down syndrome.Genome Res. 2004; 14: 1258-1267Crossref PubMed Scopus (195) Google Scholar An additional level of complexity comes from the recent observations of extensive gene-expression variation among unaffected individuals and that a significant fraction of this variation is controlled by genetic variation, either in cis or trans to the individual gene.6Storey JD Madeoy J Strout JL Wurfel M Ronald J Akey JM Gene-expression variation within and among human populations.Am J Hum Genet. 2007; 80: 502-509Abstract Full Text Full Text PDF PubMed Scopus (209) Google Scholar, 7Cheung VG Conlin LK Weber TM Arcaro M Jen KY Morley M Spielman RS Natural variation in human gene expression assessed in lymphoblastoid cells.Nat Genet. 2003; 33: 422-425Crossref PubMed Scopus (451) Google Scholar, 8Monks SA Leonardson A Zhu H Cundiff P Pietrusiak P Edwards S Phillips JW Sachs A Schadt EE Genetic inheritance of gene expression in human cell lines.Am J Hum Genet. 2004; 75: 1094-1105Abstract Full Text Full Text PDF PubMed Scopus (295) Google Scholar In a previous study, we showed, by quantitative PCR, that there is also extensive expression variation for HSA21 genes, with some genes varying up to 40-fold among individuals.9Deutsch S Lyle R Dermitzakis ET Attar H Subrahmanyan L Gehrig C Parand L Gagnebin M Rougemont J Jongeneel CV et al.Gene expression variation and expression quantitative trait mapping of human chromosome 21 genes.Hum Mol Genet. 2005; 14: 3741-3749Crossref PubMed Scopus (90) Google Scholar, 10Stranger BE Forrest MS Clark AG Minichiello MJ Deutsch S Lyle R Hunt S Kahl B Antonarakis SE Tavare S et al.Genome-wide associations of gene expression variation in humans.PLoS Genet. 2005; 1: e78Crossref PubMed Scopus (416) Google Scholar These findings may have direct implications for the phenotypic variability of DS and underlie the need to re-evaluate our models of dosage imbalance and how they relate to human disorders. To date, very little is known about the genes and pathways involved in DS pathology, although recently the involvement of the nuclear factor of activated T cells (NFAT)11Arron JR Winslow MM Polleri A Chang CP Wu H Gao X Neilson JR Chen L Heit JJ Kim SK et al.NFAT dysregulation by increased dosage of DSCR1 and DYRK1A on chromosome 21.Nature. 2006; 441: 595-600Crossref PubMed Scopus (501) Google Scholar pathway and Sonic hedgehog12Roper RJ Baxter LL Saran NG Klinedinst DK Beachy PA Reeves RH Defective cerebellar response to mitogenic Hedgehog signaling in Down syndrome mice.Proc Natl Acad Sci USA. 2006; 103: 1452-1456Crossref PubMed Scopus (155) Google Scholar pathway has been postulated. Several previous genomewide expression studies analyzed the pattern and extent of gene expression dysregulation in human trisomy 21 and its mouse models, to identify candidate genes responsible for DS phenotypes.13FitzPatrick DR Transcriptional consequences of autosomal trisomy: primary gene dosage with complex downstream effects.Trends Genet. 2005; 21: 249-253Abstract Full Text Full Text PDF PubMed Scopus (62) Google Scholar, 14Gross SJ Ferreira JC Morrow B Dar P Funke B Khabele D Merkatz I Gene expression profile of trisomy 21 placentas: a potential approach for designing noninvasive techniques of prenatal diagnosis.Am J Obstet Gynecol. 2002; 187: 457-462Abstract Full Text Full Text PDF PubMed Scopus (32) Google Scholar, 15Mao R Wang X Spitznagel Jr, EL Frelin LP Ting JC Ding H Kim JW Ruczinski I Downey TJ Pevsner J Primary and secondary transcriptional effects in the developing human Down syndrome brain and heart.Genome Biol. 2005; 6: R107Crossref PubMed Scopus (118) Google Scholar, 16Mao R Zielke CL Zielke HR Pevsner J Global up-regulation of chromosome 21 gene expression in the developing Down syndrome brain.Genomics. 2003; 81: 457-467Crossref PubMed Scopus (160) Google Scholar, 17Tang Y Schapiro MB Franz DN Patterson BJ Hickey FJ Schorry EK Hopkin RJ Wylie M Narayan T Glauser TA et al.Blood expression profiles for tuberous sclerosis complex 2, neurofibromatosis type 1, and Down's syndrome.Ann Neurol. 2004; 56: 808-814Crossref PubMed Scopus (66) Google Scholar, 18Chung IH Lee SH Lee KW Park SH Cha KY Kim NS Yoo HS Kim YS Lee S Gene expression analysis of cultured amniotic fluid cell with Down syndrome by DNA microarray.J Korean Med Sci. 2005; 20: 82-87Crossref PubMed Scopus (24) Google Scholar, 19Li CM Guo M Salas M Schupf N Silverman W Zigman WB Husain S Warburton D Thaker H Tycko B Cell type-specific over-expression of chromosome 21 genes in fibroblasts and fetal hearts with trisomy 21.BMC Med Genet. 2006; 7: 24Crossref PubMed Scopus (65) Google Scholar All these studies detected the expected up-regulation of a fraction of HSA21 transcripts. However, small sample sizes and limitations inherent to microarray technology have precluded detailed analysis of interindividual variation. We hypothesize that natural gene-expression variation of HSA21 genes in individuals with trisomy 21 contributes to the phenotypic variability in DS. We expect that, for a fraction of genes, there is a degree of overlap of expression levels between individuals with DS and unaffected individuals, whereas, for other genes, the distributions of expression levels are distinct. Those genes with expression overlap are thus candidates for the variable phenotypes of DS, likely the result of a threshold effect.20Antonarakis SE Lyle R Dermitzakis ET Reymond A Deutsch S Chromosome 21 and Down syndrome: from genomics to pathophysiology.Nat Rev Genet. 2004; 5: 725-738Crossref PubMed Scopus (453) Google Scholar In contrast, genes with distinct distributions are candidates for the constant features of DS. To classify transcripts according to the overlap of expression levels between DS and normal samples and to determine the impact of natural gene-expression variation in the context of aneuploidies, we studied gene-expression variation by quantitative real-time PCR. We analyzed 14 lymphoblastoid cell lines (LCLs) and 17 fibroblast cell lines from individuals with DS and an equal number of matched controls and assayed HSA21 annotated genes that are expressed in LCLs and fibroblasts. Epstein Barr virus (EBV)–transformed LCLs and fibroblast cell lines were obtained from Coriell cell repositories (Coriell Institute for Medical Research) (14 LCLs and 28 fibroblasts), Galliera Genetic Bank of Genoa (4 LCLs and 5 fibroblasts), Emory University School of Medicine in Atlanta (8 LCLs), and CSS-Mendel Institute in Rome (3 LCLs). All cell lines were assessed for full trisomy by karyotyping. LCLs and fibroblasts were collected from different individuals, and the control samples for both cell lines were matched for sex and ethnicity. Age was matched for fibroblasts, but, for LCLs, individuals with DS were, on average, younger than control individuals (table 1). Informed consent was obtained for all human samples, and the study was approved by the ethics committee of the Geneva University Hospital.Table 1Characteristics of Cell Lines UsedCell Line Type and External IDAgeSexEthnicityNormal LCLs: GM1187218 yearsMWhite GM0735320 yearsMWhite GM0705324 yearsFWhite GM0013025 yearsMWhite GM0371410 yearsFWhite GM1204113 yearsFWhite GM1215322 yearsMWhite GM0767812 yearsMWhite GM0379714 yearsFWhite GM070207 yearsMWhite GM119917 yearsFWhite GM121438 yearsMWhite GM1447420 yearsFWhite GM1611919 yearsMWhiteTrisomic LCLs: DV9540M18 yearsMWhite BM95760M20 yearsMWhite AM952F24 yearsFWhite GM9573M25 yearsMWhite 4710–163<1 yearMWhite 4710–165<1 yearFWhite 4710–175<1 yearFWhite 05422 yearsMWhite 05710 yearsMWhite 4710–204<1 yearFWhite 0697 yearsMWhite 4710–176<1 yearFWhite 4710–172<1 yearMWhite 4710–182<1 yearFWhite 4710–170<1 yearMWhiteNormal fibroblasts: GM08447<1 yearFWhite GM05756<1 yearMWhite GM00041<1 yearFWhite GM08333<1 yearMAfrican GM056581 yearMAfrican GM056591 yearMWhite GM057581 yearMAfrican GM009692 yearsFWhite GM004085 yearsFWhite GM000389 yearsFAfrican GM0203611 yearsFWhite GM0337719 yearsMWhite GM0344020 yearsMWhite GM0452216 fetal wkF… GM0611216 fetal wkFAfrican PM9726F19 fetal wkFWhite GM0616620 fetal wkMAfricanTrisomic fibroblasts: GM04616<1 yearFWhite GM02504<1 yearMAfrican AG07438<1 yearMAfrican AG053971 yearMWhite AG050241 yearF… AG068721 yearFWhite AG074091 yearFWhite AG069222 yearsMWhite AG048235 yearsM… GM0276714 yearsFWhite AG0894119 yearsFWhite AG0894221 yearsMWhite A-A946F18–22 fetal wkFWhite B-R939F18–22 fetal wkFWhite B-C9921F18–22 fetal wkFWhite C-B9538F18–22 fetal wkFWhite Open table in a new tab LCLs were grown in RPMI 1640 with Glutamax I medium (Invitrogen) supplemented with 10% fetal calf serum and 1% mix of penicillin, fungizone, and streptomycin (Invitrogen). Fibroblasts were cultured in Dulbecco's modified Eagle medium with Glutamax I plus Na pyruvate (Invitrogen) supplemented with the same antibiotic mix. The cell lines were treated with a standardized procedure, to minimize environmental variation. Cell lines were harvested at a density of 0.6–1×106 cells/ml or 6.5–10×106 cells/dish and at least 80% viability. LCLs and fibroblasts (after trypsinization) were spun for 5 min at 1,000 g, and the resulting pellets were rinsed with PBS and were lysed with 1 ml lysis solution containing β-mercaptoethanol (RNeasy kit [Qiagen]). Cell pellets were stored at −80°C. Total RNA was extracted using the RNeasy kit (Qiagen), including the DNAse step in accordance with the manufacturer's protocol. RNA samples were then quantified with NanoDrop (NanoDrop Technologies) and were analyzed for quality control on a 2100 BioAnalyzer by use of the RNA 6000 Nano LabChip (Agilent). cDNAs were synthesized from total RNA by use of SuperScriptII reverse transcriptase (Invitrogen) and a poly d(T) primer. For each cell line, 10.5 μg of total RNA was used to perform three reverse-transcriptase reactions, and the resulting cDNA was diluted 1:14 before PCR. On the basis of a combination of the Hattori et al.21Hattori M Fujiyama A Taylor TD Watanabe H Yada T Park HS Toyoda A Ishii K Totoki Y Choi DK et al.The DNA sequence of human chromosome 21.Nature. 2000; 405: 311-319Crossref PubMed Scopus (883) Google Scholar and Ensembl annotations, we initially considered 258 genes on HSA21. We excluded from our analysis (i) pseudogenes, (ii) gene predictions supported by spliced ESTs but not complete mRNAs, (iii) genes supported only by ab initio predictions, (iv) single-exon genes, and (v) two genes for which it was not possible to design assays by use of our default parameters. We also excluded 27 genes from the KRTRAP cluster that are almost exclusively expressed in hair root and for which it was impossible to design specific primer-probe sets. This resulted in a total of 178 genes for which we designed a TaqMan assay. Primers and probes were selected using Primer Express version 2.0 (Applied Biosystems) with default parameters. Assay efficiencies were calculated using five fourfold serial dilutions of a pool of human brain, liver, and testis cDNAs, as described elsewhere.3Lyle R Gehrig C Neergaard-Henrichsen C Deutsch S Antonarakis SE Gene expression from the aneuploid chromosome in a trisomy mouse model of Down syndrome.Genome Res. 2004; 14: 1268-1274Crossref PubMed Scopus (150) Google Scholar, 9Deutsch S Lyle R Dermitzakis ET Attar H Subrahmanyan L Gehrig C Parand L Gagnebin M Rougemont J Jongeneel CV et al.Gene expression variation and expression quantitative trait mapping of human chromosome 21 genes.Hum Mol Genet. 2005; 14: 3741-3749Crossref PubMed Scopus (90) Google Scholar When transcripts were not expressed in brain, liver, and testis, efficiencies were tested in a pool of LCLs and fibroblasts. Of the 178 genes, 43 did not pass our efficiency criteria threshold (0.95–1.05) and were excluded from further analysis. The remaining 135 genes were tested in a pool of five LCL cDNAs and five fibroblast cDNAs, to determine their expression in these cell types. A total of 117 and 114 genes were expressed in LCLs and fibroblasts, respectively, and were retained for subsequent analysis. In addition, we designed assays for 30 non-HSA21 genes. Among these, five genes for LCLs and four genes for fibroblasts were selected for normalization, and the remaining genes were used as additional controls. Selection of normalization genes was performed with GeNorm software.22Vandesompele J De Preter K Pattyn F Poppe B Van Roy N De Paepe A Speleman F Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.Genome Biology. 2002; 3: 34.1-34.11Crossref Google Scholar A list of all the assays used is provided in table 2.Table 2TaqMan AssaysPrimer Sequence (5′→3′)GeneChromosomeForwardReverseProbeLCLsFibroblastsADAMTS121AGGCATTGGCTACTTCTTCGTTGTGGAATCTGGGCTACATGGACCATCTACAACCTTGGGCTGCA−+ADAMTS521GCTGTACAAAGATTGTTGGAACCTTGGGTTGCCCCTTCAGGAACCTCACCACGTCAGTGTAACCCTTACTTTTCTTATT−+ADARB121ACTGTCGCTGGATGCGTGTGGCTTGGTAATCTTGGAGCGTCACGGCAAGGTTCCCTCCCACTT++AGPAT1aGene selected as normalization genes (GeNorm) for LCLs.6CTCCTACCAAGACTTCTACTGCAAGAAGCACCCGCACCTGACAAGCGTCGCTTCACCTCGGGACA++AGPAT321CCTCTCCTGATCCTGACTTTCTTGCAGTTACTCCTATCAGTCTGCGAACTAAAGGAAGCTGCTCCCACAAA++ALAS13CTCACCACACACCCCAGATGAGTTCCAGCCCCACTTGCTTGAACTACTTCCTTGAGAATCTGCTAGTCACATGG++APP21ACAGTACACATCCATTCATCATGGTAGGTGGCGCTCCTCTGGTGGTGGAGGTTGACGCCGCTG++ATP5021TCCATCGCGGAGAGGTACCTGAGGACAGTTTTTAATTCAGAGAGTGCACAGTGACCTCTGCATCTCCTTTAGAAGAAGC++ATP6V1E122CCGGCTGGATCTCATAGCCGGCATTTGCACCAAACAAGGAGCAGATGATGCCAGAAGTCCGGG++B2M15ACTTTGTCACAGCCCAAGATAGTTAACGGCATCTTCAAACCCTCCTGGGATCGAGACATGTAAGCAGCATCA++BACE221TTGCCCGTTGCTGGATCTTCCTTTATACAAACTTGGTTCAATTCCCCCAAGACAAGACTACCTCCGTTG++BACH121TTGAATCAGAAATTGAGAAGCTGCGTCTCACCCAGAGTTGACAAAATGAAGTGAAAAGGAGAGCTTGTTGAAGGAAAGAGATC++BAGE421CGGTTGTGTTGTTTTCTAGCAGTGCCTTCTGCTCCTTGGCCAACCACAAACTACACACATATCCTGATTCAAAGTGAACT++BCL7B7TGATGCCTCAGCCAATTCCTCACGGAACTCTGGTTGCTGTTTCTCCTTCTTGAATTCCAGGACG++BID22GATGGCAACCGCAGCAGCGGATGATGTCTTCTTGACTTTCACCCGCTTGGGAAGAATAGAGGCAGATT++BTG321GCTCACTCTCTGGGTGGACCGCTGGCAACAATGAATGCATATGTGAGGTGTGCTGTCGGTATGGAGAGA++C21orf12821CCTTGCCATCAGAACACTGCTCCCCATACTCCAGCCCCTTGCCAACCCACACCTCTTCCTGG−−C21orf1321ACAACAAAAATGGACGCAAATGCGGCTAAAGGCTCTGCAGTTAACCTCAGTTGTTTTTCCAAGCTCTGTATTTTTTG−−C21orf2521TCAAGTCGCCACGGAAGAACAGCGTCGTGGTCCTGAGATAGCACTATTATCATATCAGGGATCTCCAAGACCTCA++C21orf3321CCCTCAGATGCACGTGATTGCGCAGACTCGGTCAAAACATTCTGCTCTCGCCTTCGGACGGCT++C21orf3421AGCAAGGCCCAACCAGTTCTCCCAGTAAAATTCCTGAAGATCTGTCATCTGGAGACAGTTCAACGTTCTGCAA−+C21orf4121GCCAGAAGATGGGAGAGACATTCGTAGTTGTTGGAAGAATTCACTTTTGCAGACATTATTGGCAGCTTGTTCCTTCAA++C21orf4221AGGTTCCCCACATCTACTTGGATGGGTTTAGATTTTTCTCTCCTTGTTTTCTCCATTGAGCATCCCAAAGAT+−C21orf4521TTTCTGTGGATAAGGAACAGAAGCTGCGCAGCACAAAGTCTCAAGCGCAACCATTTTCCTTTTCACGTTTGG++C21orf5621GCCAACATCCCCGAGAAGACTCGTCCACGGAGCCGCGAGCAGACCTCCACCAAGTCTCTGG++C21orf5721TCACTTGCTGGGATTCACACACGCCTTCTCCTTCTGGAACACTGCTGCCACTCTGCCTCCGTG++C21orf5821CATCAGCAGCAGAGCAAGTGAGTGTGCTCCAGGAATGACTAAGAGTTTCTGTCCCAAGAGCTTCAGCGTCAGT++C21orf5921TGGAGTTTGAAAATAAGGAAGACTTGGCGCCTCTGCCTCTTTAATGTGAGCCCTGCCTGTGTTCCCG++C21orf621GAACCTGGATGTATCTGACGAAAACAGAACTGCCGGGTATTTAAAGGAAGAATACAGGCCAGAGAAAACATCGCCAT++C21orf6321CTGGCAGCCTTTGCTTACATTTGCAGACACTGGACACGAACAAGCCCACCCGGAGAGAGCTGC−+C21orf6621GGGAACAGGAGCAGATAAGGAACATATTCACTTCTGCGGGTTGAAATTAATATCCCTCAGGTTCAAGCCA++C21orf721TTCCTTTGGTCTTTCCAGAATTAGATGGATTCCTCGGAGTCATGACCAGCAGCTACAGCCCCTGCCG++C21orf7021TCAGAGCTCAGCCGGATGATCCTGAAACCGGGTCCTTTCGCAGCCCAGAGACAGCAGCTTCT++C21orf8121CCTCCTGCAAAACATCCTTCCTCTTTCTTTGTACTGCTCCTTTCACACAGGATCTTCCATTTCAGTGCTAGGCTTCA+−C21orf9121GGTGAGGTAGAGCAACTGAATGCTTTTTCTTGCACTTGGTGAGTTAACTAAGCTCCTACAGCAAATCCAGGAAGTTTTTGA++CBR121GTGCACAGAATTACTCCCTCTAATAAAAAGGGCTCTGACGCTCATGACCCAAGGGAGAGTGGTGAACGTATCTAGC++CBR321TGCAACGAGTTACTGCCGATACAAAAGCCCTTAAACACTGCAATGAAACCTCATGGGAGAGTGGTGAATATCAG++CBS21CAGTTCAAACAGATCCGCCTCTCCATCTCCAGGATGTGCGCGGACACGCTGGGCAGGCTC++CCT821CTTTATGCAGTACATCAAGAAGGAAATAAAGCTTCCAGCATGTCCTTTACAGAACGTTGGATTAGATATTGAGGCTGAAGTCCCT++CHAF1B21CACTGCAAGCCTGGAGCAAGAACTTGGTGGAGTGTCCGTCACAACACCCCGGAGAATAAACTTAACACCCTTAA++CHODL21CAAACATCTGGTGCCTGCCGTTCATCTGTGTACCAGTTTCGGTGAATTGCTTCCATCAGACCACTGGTAGAGATCT−−COL18A121TTCTCCTTTGACGGCAAGGAATGCCACACGCTCTTCTGGTCCTGAGGCACCCCACCTGGC−+COL6A121GGACACCACACCGCTCAACGGGATGAAGTCAAACACGTCTTTCTGCAGCCCCGGCATCCAG−+COL6A221ATCAACGTGGTCAACAGGCTGCCACACGCGTCCCTGTCCCATCGCTAAGGACCCCAAGTCCG−+COLEC1218GGTCAGCTCATCAAGAATTTTACAATACCTCTGTCACCTCTTGGACCCTACAAGGTCCACCGGGCCCCA−+COMT22TACCTGCCGGACACGCTTGCCAGTAGCACTGTCCCCTTCTCTTGGAGGAATGTGGCCTGCTGC++CRYAA21ATCCACGGAAAGCACAACGGGTAGCGGCGGTGGAACACGACCACGGCTACATTTCCCGTG−−CRYZL121TGATGGAGAAGTTATCAACTGGTGTTCATGGAAACTTTTGCCTCATACAGTCAGACCTCAGTTGGATGAACCCATTCC++CXADR21GCTGGACATCGAGTGGCTGGTCATCATAAATTTTGTCTCCAGAATATAAAATCACCAGCTGATAATCAGAAGGTGGATCAAG+−CYLN27AAGCTGATGGAGGCCATGAGTTTGCAGAACCGGAATTGCCTGCCCTGACAAGGCCCAGACC++CYYR121CTCAGGACGACTCACATCAACACGCAAGTCTGCACAGTATTCCATCTTCTCCTCCTATCCTGGACCACCACCC−+DDX319GGGAGGAGAGAAGAGAAAATCAGACAGGCGTCCAGGAGTTGAGAAAGGCCAGACTCCGCAAAGGAATAAATATCC++DONSON21TGCCTGCAAATGGACAAAGTACTGCTCCAGAGTGTTAGGGTGCCACAGTTAGTAAGCTCCTTATGAACAACCTCCATATCA++DOPEY221CACAGCTTGAAGAAGATCTAAAAGATGTCCGGGACTGAAACTTTCGTAGATGAGTCATTGAGAAGCACCAACAAAGTAAACA++DSCAM21GGCAGTTCCAAAGGCACATCTCGGTTTAACAAAAAGTCCATTCTAACCAGGTGACCTCATACATTTGCCTCCA−−DSCR121GATGCGACCCCAGTCATAAACTGTGCAATTCATACTTTTCCCCTGTGATCTCTTATATGCCATCTCCAAGCTGGG++DSCR221TCCATTGCTAGAACAACCGAATATAGGCTGGGATTTTCCATACTTGACAACACGACCTTCCTGCAGCAGTTCTAAGC++DSCR321CCTACACTGGAGACCACCAACTTGATGAGGTGGTCAGGGTGAAGCACGATGTTAACCTCAAATTCCACTTT++DYRK1A21GACCAAAGATGGAAAACGGGACCTCCTGTTTCCACTCCAAGAATACAAACCACCAGGAACCCGTAAACTTCATAAC++EEF1A1bGene selected both for LCLs and fibroblasts.6AGCAAAAATGACCCACCAATGGGCCTGGATGGTTCAGGATACACCTGAGCAGTGAAGCCAGCTGCTT++ERG21CGCCCCAGTCGAAAGCTTGAGGACGCTGGTCTTCAGTTCTCAACCATCTCCTTCCACAGTGCCC−+ETS221TGGAGACGGATGGGAGTTTAATTGGGCTTATTTTTCCTCTTTCCCTCGCCGACCCCGATGAGG++FAM3B21CAAAATCCCTGCTCTTCATGGTTGGCATTCTTGGCATCGTTACCTATGACGACGGAAGCACAAGACTGAA−−FLJ1099810AGCATCCATAGGAAAGCAAATTCTTCCTTCCCTGCTTTTCATTTAAACCCCTGTGGAAGAATCAGCCTGTCAGTT++FMOD1ACCTCTACCTCCAAGGCAATAGGCACGACGTCCACCACGGTCAATGAGTTCTCCATCAGCAGCTTCTGC−+GABPA21CAAAGAGCGCCGAGGATTTTGGATTTGGCCATTGTTTCCAGGAGAAGATAGAAGCTCACCTGGGAACAGAA++GART21CCTGGAAACCGGAGTCACACAAAATAATCTGTCCAGCATCCACTTACTGGGTGCACTGTACACTTTGTAGCTGAAGA++GTF3C49GCAAACAGGCAGTCTGTTCCATCAAACTCTGGCAGGACTGGTACCACATTTGGCTCCGGTGCTTCTTAA++HIP17CACTACGAGCTTGCTGGTGTTGTTCTTGCAGTGTAGGTGGAGATGTCTGTTCCTTCTTCCCAGCCCTCA++HLCS21AGGACAAAGGGCCCAACAGCGCTGCCCAGATGGACTTCTTCCCCTTTATTACCGATACTGGGTCCACAG++HMBScGene selected for fibroblasts.11CAAGAGACCATGCAGGCTACCGGTCATCCTCAGGGCCATCTCCATGTCCCTGCCCAGCATGA++HMGN121CGTACGGCATGGTGCTTTTTCCCTTTGCTCCCCTTTTCCTCAGGATAAATCTTCAGACAAAAAAGTGCAAACAAA++HSF2BP21ATTCGGATGAAAGTCAGTTTGTTTTGAATTCACGACCACATGCTATAGCGCAACATTCGTGACAATTCCAGCCAGAG++HUNK21TGAAGGACCGGAAGGCCTGCGGCAGCCAAAGGACCAAGTCCAGCTTCCCCGACAAAGA++ICOSLG21GCTTCTGCAGCAGAACCTGACTGGATTCTCTGTGATCTTGTCTCTCTCTTCGGCAGCCAGACAGGAAATGACA++IFNAR121TGAAAAGCTGAATAAAAGCAGTGTTTTCCAACTATAAGCCAAATTTTAGAGGTTAGTGACGCTGTATGTGAGAAAACAAAACCAGG++IFNAR221AGCAAGCAGTAATAAAGTCTCCCTTAATTTTGGCAGATTCTGCTGATTCATGCACCCTCCTTCCACCTGGCC++IFNGR221GGCCTGATTAAATACTGGTTTCACATGGGCTGAGTTGGGTCTTTTTCCACCAAGCATCCCATTACAGATAGAAGAGTATT++IGSF521CCAGTGATCCTGAACAAAGAAACATGGCCTGGGTGGACGTTCTGTGGCCCTCCTCACCAGCG−+IL10RB21GACAAAGTACGCCTTCTCCCCGTTATGATGAGGATGGCCCAAAGGAATTCTCTTCCACAGCACCTGAAAGAGTT++IL67GCTGAAAAAGATGGATGCTTCCAACTCCAAAAGACCAGTGATGATTTATCTGGATTCAATGAGGAGACTTGCCTGG++IL84AAGGAAAACTGGGTGCAGAGGGATACCACAGAGAATGAATTTTTTTATGATCTCAGCCCTCTTCAAAAACTTCTCCACAA++ITBG221GCCATGGCAAGGGCTTCTTTTTCCCAATGTAGCCAGTGTCTGGAGTGCGGCATCTGCAGGTG++ITSN121GCGTCTATACTCTCCGAGCAGAAAGAGTTCAGAAGCAGCTTTGATTTTTGCACCCAGGCAGTCCTTTCATTTATG−+JAM221AAAACCTGGAAGAGGATACAGTCACTCCACTCAGAGCAGAAGAGGGTACTCACATGATGGAACTGCTGGAGCCACTAATACTT++Kcnj1521CGTTCTACCTGCCTTGAAGAAGACATTGCCAGGCTCTGGAAACCTGGTCACTCACTCCGCAGGTCAGGT++KCNJ621GAGGAACTGGAAATTGTGGTCATCGCTTCGAGCTTGGCATGTCTCCCTGTGGCTTCCACCATTCCTTCTA−+KEO410CAGAAAGTGATGGAAAAAGAAACTGATCGGGCCAGGAATGCACATCTTCGATTTCAGAAATGCGCTT++KIAA017921TCACCTTTGGGCTGAACAGAACCGTGGGACTGACCAAGATACTTTGTCTGTCTTCTTGAATTCGGCAGTCATG++LSS21CAGCTCCCCAATGGCGGGCACAGGACTTGTTGAAGACCCTGGCCGCAGGAAAACATTGCTG++MCM3AP21ACACTATTGAACCTGTGATGAAAACATCCTCTGACAGCTGCAGTTGCTGTAACTACTAGCCCACAGAGTGACATGATGAGG++MEST7CCTATCCAGAGTTTTTGGAGCTGTCATCCAGAATCGACACTGTGGACAGGAAAACGCTGCCGCGG++ML51aGene selected as normalization genes (GeNorm) for LCLs.17GCAGGACCTCCACCTCAGTTTAGCGTTTGGCTCGACCACACCGGATGGAAGAAATGGGTGTCCA++MORC321ATGCAGTATTGAGAGGGACCAGTATCACACTGTGAACGGATTTGTGATTTTCCATTTCCAGCAATTCAACCTCACTTT++MRPL3921TCATAGAAGAGAAGGCATCTCAGAACGGGCCCTCACTCACATCAATTCACCTATTCTGTGTAGCTTGACTATTCTCTCA++MRPS621TTATAGGATCTCTGCCCACAGTCAGCGGTGGGTGCATAAAAATCCAAGAAATACCCGCCTCTGTTGTGCTG++N6AMT121GTAGTATCTGCATTCCTAGCCTCTATGAGCTGCCTCAGGGTTGATATCATGCACATGTACAAAGCCTGAGGGCCT++NCAM221CAGTAAATGAGCCAAATGAAACCATGGATTTAGAGCTTCTTTCCCATCTACCACTGACAGAACCTGAAAAATTGCCTTTAAA−+NDUFV321ACGACCGAGGCGGCATTGTAGGTAGTGTTGTCAAACGGCACAGGAGCCAGCCCCAGTGCC++PCBP321TCCAGTGCGTCAAGCAGATCTGGGCGGTAGGGAATGGTTCATGCTGGAGTCCCCACCGAAA−+PCNT21AATGGCAAGAAGTAGATCGGAAAGGGCTGTCGTGCTCGGGAGCTCTGGCACAAGGCAAAGCCC++PCP421TGAGCGGCGGGACTGATTGCCCCAGCACCTTGTCCTCACTCATGTTGGCTCTAACTCAACAG−−PCQAP22ATGGCACTGTCCACCTGATCTAGCTCCAGTGGTGGCACACCAAGCTGGATGACAAGGACCTCCCA++PDXK21ACCTTGCACCACGTTCTGCCACTCCTTCCCCGGCCAGGACCATCCAGTGTGCAAAAGCCC++PFKL21CAGCCCCGTCACTGAGCTGGCTCAGCCACCACTGCTCGAGCACCGCATGCCACGG++PIGP21TGTTTGGGATTAACATGATGAGTACCTTCTGCTGTTGATTTTTTGCATAGTTTCCACTCGACTCCATCCATACAATCACAGA++PKNOX121GTCGCCTGGGACAATTAGGATCTTGATGCAAGATGCTGAGATCCCAGAACTCCCAGCTTCAGTTACAGTTAAACCA++POFUT221TTCCAGGAGGACTGGATGAAGATTCTCAGGTGGACTCCCAGGTACGCGGAGCCCAGCTTGACCTT++PRDM1521TCGCGCAGAAGGTCAACATTTCCCACACAATTCACACATGAAGCACTGCAAGCGGCACACGG++PRMT221ACACGTGGCAGGATGAAGAGTTGGTCTGCCAACATCTCCAACTTCGGCAGCTATGGAACTCTGAAACTCC++PSMA5bGene selected both for LCLs and fibroblasts.1AGGAGAAGCTGAATGCAACAAACTTCCTTTGTGAACATGTGGAAATTCCAGGCTGCACTGTGGCTAGCTCAA++PTTG1IP21GGAACGGAGAGCAGAGATGAAATCTAGCATACGGGTTTTCTTCTTTAAACAAGACATGATGAAATCAGAAAAAAATATGGCCTG++PWP221GCTCATGTTGCACGGACAGAAGGAACTGAATGACAGGCAGCCTGAAGTCCAGAGCCGGGACGC++RBM1121GGAATTCGTTTATATGGAAGACCAATAACTTTGGTTAGCTGGTTCAGAAGACGAGAACTCCCAAATCGATACTGCACGTT+−REST4GACATATGCGTACTCATTCAGGTGATGGCGGGTTACTTCATGTTG++RIPK421GAGCGGGAACCTTCAACCAGGCATCCACAAGCTTCTTCTTCCGATCTGGGCACCACAGACGTCC++RUNX121TCTGCAGAACTTTCCAGTCGACGGAACTGGCGCGGGTCCTCAACGGCACCCGACCTGACA++S100B21GGGTGAGACAAGGAAGAGGATGGGTGGAAAACGTCGATGAGGCTGAGCTGGAGAAGGCCATGGTGG−−SETD421GAAAGCTAGGAAGTTTCAAGATTCAAAGACTCATCAGCCCTCTTCCTGTATAGCGCCTGCTTGTTTTCCAG++SFRS1521GCACAAAATGAACCACTTACACAGACATATGTCGCTTAACCTCTTGAATACAGTTCTACTTCCATTTCCTGCTGATGCGG++SH3BGR21AACTGTCGAAATGGTTATCAAAGTGTCCACTACTTCTTGCTGTTTCTTCCTTGTTGCTACATCTTCTGGGTCCATAGCGA−+SLC19A121TTGTCTCGGACGTGCGGGGATCAGGAAGTACACGGAGTATAACTCCTCCCGGTCCGCAAGCAGTT++SLC25A122GGAAACACTCCTCTGGATGTGATTCCGGTATTTGTGCGCCTAAGACCCGGATGCAGGGCCTG++SLC37A121TTGCAGATGCCTGTGCCTTATGGGCAGCTCAGCTCCTTTGTTCCTGATCCGCCTCATACA++SNF1LK21ACACCTCACTGACTCAAGGGCTTTGGTCCGCGTGGTCTTCTCAGCTGCTGCCGAAAGGCCTT++SOD121GGTGGGCCAAAGGATGAAGCCACACCATCTTTGTCAGCAGTAGGCATGTTGGAGACTTGGGCAATGT++SON21CAGCAATTTGCCCTCAGAGGCGGGTTGTTTCATCTGTCGTCCCGGGTTAAACGGCAGGGCC++STCH21CAGCAGAATTTGATCTAAAACAGAGAAGTGGGTTCATTTATTACCCTCAAAATCAACAATTGAAGCTGCTAACCTTGCAGG++SUMO321CAGCCAATCAATGAAACTGACACTGCTGGAACACGTCGATGGTTCGTCCTCCATCTCCAGCTGTGCT++SYNJ121GGCATCTGCTGGAAGACTGACTCAGTGGTTCAGGAAGGAAAGTTGCCAAAGCAAAACATCAGAAACGTCGAAAGG++TCP10L21CCTGGGACAAAGATCGTCATCTCCACGAGCTAATTCTTTCTATCTTTAAAACAATTCAGCTCCTCCAAAGCCAATGA++TFF121TCCCCTGGTGCTTCTATCCTAACGTCAGGATGCAGGCAGATACCATCGACGTCCCTCCAGAAGAGG−−TFF321CCATGTCACCCCCAAGGAGGTGCCTCAGAAGGTGCATTCTGCTGCTTTGACTCCAGGATCCCTG−−TIAM121CAAAACTGCTGTGGTCCTTGTGCCTCATAAATGGAAAGCCTGTGATAAAGATGGTTCCAAACAGAAGAAGAAACTTGTAGGA++TMEM121ACAAAGCTTATGTATGAAGTTGTCGACCCACTGGCATGGAGATGACACTGGGCAGTGTGTGGGAAAAGCTGC++TMEM50B21GCTATGAAAGCGGCTGTTTAGGCCCAAACATCAACATGAAACCATGAAAAGCCAAACTCGAGCACCTGTTCT++TMPRSS221CACGGACTGGATTTATCGACAAAAACGACGTCAAGGACGAAGACATGTGGATTAGCCGTCTGCCCTCA−−TMPRSS321CACCTCCTTCCTGGACTGGATGTGGCTACTTGTCCCCTTCCTCAGGTTTTTAGGTCTCTCTCCATCTGCTCGTG+−TRPM221CCGTCTTTTGAAAACTTGCTGAAGTTCCTCGGGTCATCCATGTGCCTTTGTACACCTCCATGCCGCA+−TSGA221TCAATAATGACACCTACACTGGAGAGTGCCCGTCTCCGCGTATAAATGCCCATGCCTTTGATGAGCAA+−TTC321TGAGCTTTCATTTCCTGCCTGGCCATCGTCGCCTGAAGAAACACGGTTCATCCCGA
Referência(s)