Progress in genomic analytical technologies has improved our possibilities to obtain information regarding DNA, RNA, and their dynamic changes that occur over time or in response to specific challenges. This information describes the blueprint for cells, tissues, and organisms and has fundamental importance for all living organisms. This review focuses on the technological challenges to analyze the transcriptome and what is the impact of transcriptomics on precision medicine. The transcriptome is a term that covers all RNA present in cells and a substantial part of it will never be translated into protein but is nevertheless functional in determining cell phenotype. Recent developments in transcriptomics have challenged the fundamentals of the central dogma of biology by providing evidence of pervasive transcription of the genome. Such massive transcriptional activity is challenging the definition of a gene and especially the term “pseudogene” that has now been demonstrated in many examples to be both transcribed and translated. We also review the common sources of biomaterials for transcriptomics and justify the suitability of whole blood RNA as the current optimal analyte for clinical transcriptomics. At the end of the review, a brief overview of the clinical implications of transcriptomics in clinical trial design and clinical diagnosis is given. Finally, we introduce the transcriptome as a target for modern drug development as a tool for extending our capacity for precision medicine in multiple diseases.
MattickJS.Challenging the dogma: the hidden layer of non-protein-coding RNAs in complex organisms. Bioessays2003;
25:930–9
2.
KapranovPCawleySEDrenkowJBekiranovSStrausbergRLFodorSPGingerasTR.Large-scale transcriptional activity in chromosomes 21 and 22. Science (New York, NY)2002;
296:916–9
3.
VelculescuVEZhangLZhouWVogelsteinJBasraiMABassettDEJrHieterPVogelsteinBKinzlerKW.Characterization of the yeast transcriptome. Cell1997;
88:243–51
4.
LanderESLintonLMBirrenBNusbaumCZodyMCBaldwinJDevonKDewarKDoyleMFitzHughWFunkeRGageDHarrisKHeafordAHowlandJKannLLehoczkyJLeVineRMcEwanPMcKernanKMeldrimJMesirovJPMirandaCMorrisWNaylorJRaymondCRosettiMSantosRSheridanASougnezCStange-ThomannNStojanovicNSubramanianAWymanDRogersJSulstonJAinscoughRBeckSBentleyDBurtonJCleeCCarterNCoulsonADeadmanRDeloukasPDunhamADunhamIDurbinRFrenchLGrafhamDGregorySHubbardTHumphraySHuntAJonesMLloydCMcMurrayAMatthewsLMercerSMilneSMullikinJCMungallAPlumbRRossMShownkeenRSimsSWaterstonRHWilsonRKHillierLWMcPhersonJDMarraMAMardisERFultonLAChinwallaATPepinKHGishWRChissoeSLWendlMCDelehauntyKDMinerTLDelehauntyAKramerJBCookLLFultonRSJohnsonDLMinxPJCliftonSWHawkinsTBranscombEPredkiPRichardsonPWenningSSlezakTDoggettNChengJ-FOlsenALucasSElkinCUberbacherEFrazierMGibbsRAMuznyDMSchererSEBouckJBSodergrenEJWorleyKCRivesCMGorrellJHMetzkerMLNaylorSLKucherlapatiRSNelsonDLWeinstockGMSakakiYFujiyamaAHattoriMYadaTToyodaAItohTKawagoeCWatanabeHTotokiYTaylorTWeissenbachJHeiligRSaurinWArtiguenaveFBrottierPBrulsTPelletierERobertCWinckerPRosenthalAPlatzerMNyakaturaGTaudienSRumpASmithDRDoucette-StammLRubenfieldMWeinstockKLeeHMDuboisJYangHYuJWangJHuangGGuJHoodLRowenLMadanAQinSDavisRWFederspielNAAbolaAPProctorMJRoeBAChenFPanHRamserJLehrachHReinhardtRMcCombieWRde la BastideMDedhiaNBlöckerHHornischerKNordsiekGAgarwalaRAravindLBaileyJABatemanABatzoglouSBirneyEBorkPBrownDGBurgeCBCeruttiLChenH-CChurchDClampMCopleyRRDoerksTEddySREichlerEEFureyTSGalaganJGilbertJGRHarmonCHayashizakiYHausslerDHermjakobHHokampKJangWJohnsonLSJonesTAKasifSKaspryzkAKennedySKentWJKittsPKooninEVKorfIKulpDLancetDLoweTMMcLysaghtAMikkelsenTMoranJVMulderNPollaraVJPontingCPSchulerGSchultzJSlaterGSmitAFAStupkaESzustakowkiJThierry-MiegDThierry-MiegJWagnerLWallisJWheelerRWilliamsAWolfYIWolfeKHYangS-PYehR-FCollinsFGuyerMSPetersonJFelsenfeldAWetterstrandKAMyersRMSchmutzJDicksonMGrimwoodJCoxDROlsonMVKaulRRaymondCShimizuNKawasakiKMinoshimaSEvansGAAthanasiouMSchultzRPatrinosAMorganMJ, International Human Genome Sequencing C, Whitehead Institute for Biomedical Research CfGR, The Sanger C, Washington University Genome Sequencing C, Institute UDJG, Baylor College of Medicine Human Genome Sequencing C, Center RGS, Genoscope, Cnrs UMR, Department of Genome Analysis IoMB, Center GTCS, Beijing Genomics Institute/Human Genome C, Multimegabase Sequencing Center TIfSB, Stanford Genome Technology C, University of Oklahoma’s Advanced Center for Genome T, Max Planck Institute for Molecular G, Cold Spring Harbor Laboratory LAHGC, Biotechnology GBGRCf, *Genome Analysis G,Scientific management: National Human Genome Research Institute USNIoH, Stanford Human Genome C, University of Washington Genome C, Department of Molecular Biology KUSoM, University of Texas Southwestern Medical Center at D, Office of Science USDoE, The Wellcome T. Initial sequencing and analysis of the human genome. Nature2001;
409:860–921
KimMSPintoSMGetnetDNirujogiRSMandaSSChaerkadyRMadugunduAKKelkarDSIsserlinRJainSThomasJKMuthusamyBLeal-RojasPKumarPSahasrabuddheNABalakrishnanLAdvaniJGeorgeBRenuseSSelvanLDPatilAHNanjappaVRadhakrishnanAPrasadSSubbannayyaTRajuRKumarMSreenivasamurthySKMarimuthuASatheGJChavanSDattaKKSubbannayyaYSahuAYelamanchiSDJayaramSRajagopalanPSharmaJMurthyKRSyedNGoelRKhanAAAhmadSDeyGMudgalKChatterjeeAHuangTCZhongJWuXShawPGFreedDZahariMSMukherjeeKKShankarSMahadevanALamHMitchellCJShankarSKSatishchandraPSchroederJTSirdeshmukhRMaitraALeachSDDrakeCGHalushkaMKPrasadTSHrubanRHKerrCLBaderGDIacobuzio-DonahueCAGowdaHPandeyA.A draft map of the human proteome. Nature2014;
509:575–81
7.
CarninciPKasukawaTKatayamaSGoughJFrithMCMaedaNOyamaRRavasiTLenhardBWellsCKodziusRShimokawaKBajicVBBrennerSEBatalovSForrestARZavolanMDavisMJWilmingLGAidinisVAllenJEAmbesi-ImpiombatoAApweilerRAturaliyaRNBaileyTLBansalMBaxterLBeiselKWBersanoTBonoHChalkAMChiuKPChoudharyVChristoffelsAClutterbuckDRCroweMLDallaEDalrympleBPde BonoBDella GattaGdi BernardoDDownTEngstromPFagioliniMFaulknerGFletcherCFFukushimaTFurunoMFutakiSGariboldiMGeorgii-HemmingPGingerasTRGojoboriTGreenREGustincichSHarbersMHayashiYHenschTKHirokawaNHillDHuminieckiLIaconoMIkeoKIwamaAIshikawaTJaktMKanapinAKatohMKawasawaYKelsoJKitamuraHKitanoHKolliasGKrishnanSPKrugerAKummerfeldSKKurochkinIVLareauLFLazarevicDLipovichLLiuJLiuniSMcWilliamSMadan BabuMMaderaMMarchionniLMatsudaHMatsuzawaSMikiHMignoneFMiyakeSMorrisKMottagui-TabarSMulderNNakanoNNakauchiHNgPNilssonRNishiguchiSNishikawaSNoriFOharaOOkazakiYOrlandoVPangKCPavanWJPavesiGPesoleGPetrovskyNPiazzaSReedJReidJFRingBZRingwaldMRostBRuanYSalzbergSLSandelinASchneiderCSchonbachCSekiguchiKSempleCASenoSSessaLShengYShibataYShimadaHShimadaKSilvaDSinclairBSperlingSStupkaESugiuraKSultanaRTakenakaYTakiKTammojaKTanSLTangSTaylorMSTegnerJTeichmannSAUedaHRvan NimwegenEVerardoRWeiCLYagiKYamanishiHZabarovskyEZhuSZimmerAHideWBultCGrimmondSMTeasdaleRDLiuETBrusicVQuackenbushJWahlestedtCMattickJSHumeDAKaiCSasakiDTomaruYFukudaSKanamori-KatayamaMSuzukiMAokiJArakawaTIidaJImamuraKItohMKatoTKawajiHKawagashiraNKawashimaTKojimaMKondoSKonnoHNakanoKNinomiyaNNishioTOkadaMPlessyCShibataKShirakiTSuzukiSTagamiMWakiKWatahikiAOkamura-OhoYSuzukiHKawaiJHayashizakiY.The transcriptional landscape of the mammalian genome. Science (New York, NY)2005;
309:1559–63
8.
PennisiE.Genomics ENCODE project writes eulogy for junk DNA. Science (New York, NY)2012;
337:1159–61
9.
WangZGersteinMSnyderM.RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet2009;
10:57–63
10.
DufvaM.Introduction to microarray technology. Methods Mol Biol (Clifton, NJ)2009;
529:1–22
11.
IidaKNishimuraI.Gene expression profiling by DNA microarray technology. Crit Rev Oral Biol Med2002;
13:35–50
12.
Della BeffaCCorderoFCalogeroRA.Dissecting an alternative splicing analysis workflow for GeneChip exon 1.0 ST affymetrix arrays. BMC Genom2008;
9:571
13.
StarkRGrzelakMHadfieldJ.RNA sequencing: the teenage years. Nat Rev Genet2019;
20:631–56
14.
HunterMCPozhitkovAENoblePA.Accurate predictions of postmortem interval using linear regression analyses of gene meter expression data. Forensic Sci Int2017;
275:90–101
15.
PardueSZimmermanALMorrison-BogoradM.Selective postmortem degradation of inducible heat shock protein 70 (hsp70) mRNAs in rat brain. Cell Mol Neurobiol1994;
14:341–57
16.
BeachTG.Alzheimer’s disease and the “valley of death”: not enough guidance from human brain tissue?J Alzheimer’s Dis2013;
33: S219–33
17.
WuCBendriemRMGaramszegiSPSongLLeeCT.RNA sequencing in post-mortem human brains of neuropsychiatric disorders. Psychiatry Clin Neurosci2017;
71:663–72
18.
KoksSSoometsUPaya-CanoJLFernandesCLuukHPlaasMTerasmaaATillmannVNoormetsKVasarESchalkwykLC.Wfs1 gene deletion causes growth retardation in mice and interferes with the growth hormone pathway. Physiol Genom2009;
37:249–59
19.
KoksSSoometsUPlaasMTerasmaaANoormetsKTillmannVVasarEFernandesCSchalkwykLC.Hypothalamic gene expression profile indicates a reduction in G protein signaling in the Wfs1 mutant mice. Physiol Genom2011;
43:1351–8
20.
IvaskMPajusaluSReimannEKoksS.Hippocampus and hypothalamus RNA-sequencing of WFS1-deficient mice. Neuroscience2018;
374:91–103
21.
SchalkwykLCFernandesCNashMWKurrikoffKVasarEKoksS.Interpretation of knockout experiments: the congenic footprint. Genes Brain Behav2007;
6:299–303
22.
KoksSFernandesCKurrikoffKVasarESchalkwykLC.Gene expression profiling reveals upregulation of Tlr4 receptors in Cckb receptor deficient mice. Behav Brain Res2008;
188:62–70
23.
HoXDPhungPQ LeVH NguyenVReimannEPransEKoksGMaasaluKLeNTH TrinhLG NguyenHMartsonAKoksS.Whole transcriptome analysis identifies differentially regulated networks between osteosarcoma and normal bone samples. Exp Biol Med (Maywood)2017;
242:1802–11
24.
PlankenAKurvitsLReimannEKadastik-EermeLKingoKKoksSTabaP.Looking beyond the brain to improve the pathogenic understanding of Parkinson’s disease: implications of whole transcriptome profiling of patients’ skin. BMC Neurol2017;
17:6
25.
KurvitsLReimannEKadastik-EermeLTruuLKingoKErmTKoksSTabaPPlankenA.Serum amyloid alpha is downregulated in peripheral tissues of Parkinson’s disease patients. Front Neurosci2019;
13:13
26.
BillingsleyKJLattekiviFPlankenAReimannEKurvitsLKadastik-EermeLKasterpaluKMBubbVJQuinnJPKoksSTabaP.Analysis of repetitive element expression in the blood and skin of patients with Parkinson’s disease identifies differential expression of satellite elements. Sci Rep2019;
9:4369
27.
GalichonPXu-DuboisYCBuobDTinelCAnglicheauDBenbouzidSDahanKOualiNHertigABrocheriouIRondeauE.Urinary transcriptomics reveals patterns associated with subclinical injury of the renal allograft. Biomark Med2018;
12:427–38
28.
SoleCGoicoecheaIGoniASchrammMArmestoMArestinMManterolaLTellaetxeMAlberdiANogueiraLRoumiguieMLopezJISanz JakaJPUrruticoecheaAVergaraILoizaga-IriarteAUndaMCarracedoAMalavaudBLawrieCH.The urinary transcriptome as a source of biomarkers for prostate cancer. Cancers2020;
12:513
29.
RhoadesRBellDR.Medical physiology. Principles for clinical medicine. Online access with subscription: LWW health library (integrated basic science collection). 4th ed.Philadelphia:
Wolters Kluwer Health/Lippincott Williams & Wilkins, 2013.
30.
HeDYangCXSahinBSinghAShannonCPOliveriaJPGauvreauGMTebbuttSJ.Whole blood vs PBMC: compartmental differences in gene expression profiling exemplified in asthma. Allergy Asthma Clin Immunol2019;
15:67
31.
WhitneyARDiehnMPopperSJAlizadehAABoldrickJCRelmanDABrownPO.Individuality and variation in gene expression patterns in human blood. Proc Natl Acad Sci Usa2003;
100:1896–901
32.
SourvinouISMarkouALianidouES.Quantification of circulating miRNAs in plasma: effect of preanalytical and analytical parameters on their isolation and stability. J Mol Diagn2013;
15:827–34
33.
JonesWGreytakSOdehHGuanPPowersJBavarvaJMooreHM.Deleterious effects of formalin-fixation and delays to fixation on RNA and miRNA-Seq profiles. Sci Rep2019;
9:6980
34.
BuschmannDHaberbergerAKirchnerBSpornraftMRiedmaierISchellingGPfafflMW.Toward reliable biomarker signatures in the age of liquid biopsies – how to standardize the small RNA-Seq workflow. Nucleic Acids Res2016;
44:5995–6018
GressTMWallrappCFrohmeMMuller-PillaschFLacherUFriessHBuchlerMAdlerGHoheiselJD.Identification of genes with specific expression in pancreatic cancer by cDNA representational difference analysis. Genes Chromosom Cancer1997;
19:97–103
37.
HubankMSchatzDG.Identifying differences in mRNA expression by representational difference analysis of cDNA. Nucleic Acids Res1994;
22:5640–8
38.
KoksSLuukHNelovkovAAredaTVasarE.A screen for genes induced in the amygdaloid area during cat odor exposure. Genes Brain Behav2004;
3:80–9
39.
BowlerLD.Representational difference analysis of cDNA. Methods Mol Med2004;
94:49–66
40.
NelovkovAPhilipsMAKoksSVasarE.Rats with low exploratory activity in the elevated plus-maze have the increased expression of limbic system-associated membrane protein gene in the periaqueductal grey. Neurosci Lett2003;
352:179–82
41.
SmithTPGrosseWMFrekingBARobertsAJStoneRTCasasEWrayJEWhiteJChoJFahrenkrugSCBennettGLHeatonMPLaegreidWWRohrerGAChitko-McKownCGPerteaGHoltIKaramychevaSLiangFQuackenbushJKeeleJW.Sequence evaluation of four pooled-tissue normalized bovine cDNA libraries and construction of a gene index for cattle. Genome Res2001;
11:626–30
42.
PerouCMSorlieTEisenMBvan de RijnMJeffreySSReesCAPollackJRRossDTJohnsenHAkslenLAFlugeOPergamenschikovAWilliamsCZhuSXLonningPEBorresen-DaleALBrownPOBotsteinD.Molecular portraits of human breast tumours. Nature2000;
406:747–52
43.
SorlieTPerouCMTibshiraniRAasTGeislerSJohnsenHHastieTEisenMBvan de RijnMJeffreySSThorsenTQuistHMateseJCBrownPOBotsteinDLonningPEBorresen-DaleAL.Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A2001;
98:10869–74
44.
HoXDNguyenHGTrinhLHReimannEPransEKoksGMaasaluKLeVQNguyenVHLeNTNPhungPMartsonALattekiviFKoksS.Analysis of the expression of repetitive DNA elements in osteosarcoma. Front Genet2017;
8:193
45.
SchwaederleMZhaoMLeeJJLazarVLeyland-JonesBSchilskyRLMendelsohnJKurzrockR.Association of biomarker-based treatment strategies with response rates and progression-free survival in refractory malignant neoplasms: a meta-analysis. JAMA Oncol2016;
2:1452–59
46.
RodonJSoriaJCBergerRMillerWHRubinEKugelATsimberidouASaintignyPAckersteinABranaILoriotYAfsharMMillerVWunderFBressonCMartiniJFRaynaudJMendelsohnJBatistGOnnATaberneroJSchilskyRLLazarVLeeJJKurzrockR.Genomic and transcriptomic profiling expands precision cancer medicine: the WINTHER trial. Nat Med2019;
25:751–58
47.
TaylorJCMartinHCLiseSBroxholmeJCazierJ-BRimmerAKanapinALunterGFiddySAllanCAricescuARAttarMBabbsCBecqJBeesonDBentoCBignellPBlairEBuckleVJBullKCaisOCarioHChapelHCopleyRRCornallRCraftJDahanKDavenportEEDendrouCDevuystOFenwickALFlintJFuggerLGilbertRDGorielyAGreenAGregerIHGrocockRGruszczykAVHastingsRHattonEHiggsDHillAHolmesCHowardMHughesLHumburgPJohnsonDKarpeFKingsburyZKiniUKnightJCKrohnJLambleSLangmanCLonieLLuckJMcCarthyDMcGowanSJMcMullinMFMillerKAMurrayLNémethAHNesbitMANuttDOrmondroydEOturaiABPagnamentaAPatelSYPercyMPetousiNPiazzaPPiretSEPolanco-EcheverryGPopitschNPowrieFPughCQuekLRobbinsPARobsonKRussoASahgalNvan SchouwenburgPASchuhASilvermanESimmonsASørensenPSSweeneyETaylorJThakkerRVTomlinsonITrebesATwiggSRUhligHHVyasPVyseTWallSAWatkinsHWhyteMPWittyLWrightBYauCBuckDHumphraySRatcliffePJBellJIWilkieAOBentleyDDonnellyPMcVeanG.Factors influencing success of clinical genome sequencing across a broad spectrum of disorders. Nat Genet2015;
47:717–26
48.
CummingsBBMarshallJLTukiainenTLekMDonkervoortSFoleyARBolducVWaddellLBSandaraduraSAO’GradyGLEstrellaEReddyHMZhaoFWeisburdBKarczewskiKJO’Donnell-LuriaAHBirnbaumDSarkozyAHuYGonorazkyHClaeysKJoshiHBournazosAOatesECGhaouiRDavisMRLaingNGTopfAKangPBBeggsAHNorthKNStraubVDowlingJJMuntoniFClarkeNFCooperSTBonnemannCGMacArthurDG.Improving genetic diagnosis in Mendelian disease with transcriptome sequencing. Sci Transl Med2017;
9:eaal5209
49.
IrigoyenNFirthAEJonesJDChungBYSiddellSGBrierleyI.High-resolution analysis of coronavirus gene expression by RNA sequencing and ribosome profiling. PLoS Pathog2016;
12:e1005473
50.
BensonMDDasguptaNRMoniaBP.Inotersen (transthyretin-specific antisense oligonucleotide) for treatment of transthyretin amyloidosis. Neurodegener Dis Manag2019;
9:25–30
51.
WeinNVulinAFindlayARGumiennyFHuangNWiltonSDFlaniganKM.Efficient skipping of single exon duplications in DMD patient-derived cell lines using an antisense oligonucleotide approach. J Neuromuscul Dis2017;
4:199–207
52.
LiDMastagliaFLFletcherSWiltonSD.Precision medicine through antisense oligonucleotide-mediated exon skipping. Trends Pharmacol Sci2018;
39:982–94
53.
Aung-HtutMTMcIntoshCSHamKAPitoutILFlynnLLGreerKFletcherSWiltonSD.Systematic approach to developing splice modulating antisense oligonucleotides. Int J Mol Sci2019;
20:5030
