Molecular Biology International

Volume 2012 (2012), Article ID 793506, 29 pages

doi:10.1155/2012/793506

Research Article

A Prevalence of Imprinted Genes within the Total Transcriptomes of Human Tissues and Cells

Sergey V. Anisimov1,2

¹Research Unit of Cellular and Genetic Engineering, V. A. Almazov Federal Center for Heart, Blood & Endocrinology, Akkuratova Street 2, Saint-Petersburg 197341, Russia

²Department of Intracellular Signaling and Transport, Institute of Cytology, Russian Academy of Sciences, Tikhoretsky Prosp. 4, Saint-Petersburg 194064, Russia

Received 14 March 2012; Revised 23 June 2012; Accepted 28 June 2012

Academic Editor: Alessandro Desideri

Copyright © 2012 Sergey V. Anisimov. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Genomic imprinting is an epigenetic phenomenon that causes a differential expression of paternally and maternally inherited alleles of a subset of genes (the so-called imprinted genes). Imprinted genes are distributed throughout the genome and it is predicted that about 1% of the human genes may be imprinted. It is recognized that the allelic expression of imprinted genes varies between tissues and developmental stages. The current study represents the first attempt to estimate a prevalence of imprinted genes within the total human transcriptome. In silico analysis of the normalized expression profiles of a comprehensive panel of 173 established and candidate human imprinted genes was performed, in 492 publicly available SAGE libraries. The latter represent human cell and tissue samples in a variety of physiological and pathological conditions. Variations in the prevalence of imprinted genes within the total transcriptomes (ranging from 0.08% to 4.36%) and expression profiles of the individual imprinted genes are assessed. This paper thus provides a useful reference on the size of the imprinted transcriptome and expression of the individual imprinted genes.

1. Introduction

Genomic imprinting is an epigenetic phenomenon that causes a differential expression of paternally and maternally inherited alleles of a minor subset of genes (the so-called imprinted genes). Genomic imprinting was first discovered in 1984 [1, 2], and in 1991 the first imprinted genes (IGF2, paternally expressed; IGF2R and H19, maternally expressed) were identified in the mouse [3–5]. Since then, the imprinting status was confirmed for numerous genes in Homo sapiens and Mus musculus genomes, less for Bos taurus, Rattus norvegicus, Sus scrofa, Canis lupus familiaris, and Ovis aries; many more genes are considered candidates [6]. Functional significance of the genomic imprinting is not yet fully understood [7–9], while alterations in the expression of imprinted genes are linked to certain pathologies, including Angelman syndrome, Prader-Willi syndrome, and particular cancer subtypes. Genomic imprinting varies between species and tissues. Furthermore, it is a dynamic process and may vary depending on the developmental stage [10]. The goal of the study was to estimate a prevalence of imprinted genes within the total human transcriptome, in cell and tissue samples in a variety of physiological and pathological conditions.

Serial analysis of gene expression (SAGE) is a sequence-based technique to study mRNA transcripts quantitatively in cell populations [11]. Two major principles underline SAGE: first, short (10 bp) expressed sequenced tags (ESTs) are sufficient to identify individual gene products, and second, multiple tags can be concatenated and identified by sequence analysis. SAGE results are reported in either absolute or relative numbers of tags, which permits direct comparisons between tag catalogues and datasets [12–15]. Numerous technical adaptations assured a development of similar techniques [16], yet SAGE remains an important tool of modern molecular biology. It is widely used in a number of applications, of which a molecular dissection of cancer genome is the major [17]. In the current study, expression of established and candidate imprinted genes was evaluated in a wide array of cell and tissue samples using a comprehensive set of currently available SAGE data for Homo sapiens. Five hundred eighty-one SAGE catalogues based on the libraries generated with most commonly used NlaIII anchoring enzyme were screened using a conservative set of criteria, and in 492 of these (accounting for nearly 36 million SAGE tags) gene expression profiles of the imprinted genes were analyzed, using a proved algorithm [18]. It was therefore possible to estimate a prevalence of imprinted genes within the total human transcriptome.

2. Methods

2.1. Imprinted Gene Subsets

Established and candidate imprinted gene subset was assembled based on the Geneimprint resource (http://www.geneimprint.com/; credits to R.L. Jirtle) and Luedi et al. study [6]. Of the latter, high-confidence imprinted human gene candidates predicted to be imprinted by both the linear and RBF kernel classifiers learned by Equbits Foresight and by SMLR ([6], supplementary data) were utilized. Redundant entries have been excluded.

2.2. SAGE

SAGE technology is based on isolation of short tags form the appropriate position within the mRNA molecule, followed by the concatemerization of the tags, sequencing, tag extraction and gene annotation [11]. The complete set of publicly available SAGE libraries (GPL4 dataset, NlaIII anchoring enzyme) was downloaded from the Gene Expression Omnibus (GEO) database (National Center of Biotechnology Information (NCBI); http://www.ncbi.nlm.nih.gov/geo/). Following an exclusion of the duplicate entries, SAGE libraries were annotated and sorted based on the number of tags sequenced. Noninformative (A)₁₀ sequences were extracted from SAGE libraries when detected, and tags per million (tpm) values were recalculated accordingly for all libraries as the transcript’s raw tag count divided by the number of reliable tags in the library and multiplied by 1,000,000. SAGE libraries, constructed by Potapova et al. [19], were a subject to a “clean-up” procedure through which all clones containing ≤4 tags were excluded [20], with the remaining tags constituting the pool of “reliable tags.”

2.3. SAGE Tag Annotation

Established and candidate imprinted gene subset has matched CGAP (Cancer Genome Anatomy Project, NCI, NIH) SAGE Anatomic Viewer (SAV) applet [17]. For genes not matching SAV applet entries, and when unreliable/internal tags were suggested by SAV applet (viz., for TIGD1, HOXA3, NTRI genes, etc.), reliable 3′ end tags were extracted from full-length sequences available via GenBank (NCBI, NIH).

2.4. Expression Profiling

SAGE tags was matched the individual SAGE catalogues using MS Access software package Query function. Individual queries (both absolute tag abundance per library and normalized tag per million (tpm) values) were merged using MS Excel software. Calculations of maximal and average expression of transcripts matching established and candidate imprinted genes were performed using normalized tpm values. Particular values could be recalculated to the fraction of the total gene expression by dividing tpm value by 1,000,000.

2.5. Clustering Analysis

Clustering analysis was performed using EPCLUST Expression Profile data CLUSTering and analysis software (http://www.bioinf.ebc.ee/EP/EP/EPCLUST/). K-mean clustering analysis was performed after transposing the data matrix with initial clusters chosen by most distant (average) transcripts. For each dataset, the number of clusters was set to the lowest value yielding one cluster containing a solitary database entry. Hierarchical clustering was performed using correlation measure-based distance/average linkage (average distance) clustering method; hierarchical trees were built for individual datasets.

3. Results

Established and candidate human imprinted gene subset (203 entries total) was assembled based on the Geneimprint resource and Luedi et al. study data [6]. Of the candidate imprinted genes identified in the latter, high-confidence gene candidates (predicted via Equbits Foresight and SMLR means [6]) were selected. Following exclusion of the redundant entries, appropriate short (10 bp) SAGE tags matching NlaIII anchoring enzyme were annotated to gene targets using CGAP (Cancer Genome Anatomy Project, NCI, NIH) SAGE Anatomic Viewer (SAV) applet or manually, as described earlier [18]. For a number of the candidate imprinted genes, a complete sequence was unavailable via GenBank or alternative databases (e.g., GenBank ID: NM_016158, NM_024547, NM_181648, etc.), for that reason, a volume of the human imprinted gene subset subjected to tag annotation was reduced to 174 genes. Of these genes, candidate imprinted gene Q9NYI9 (PPARL; GenBank ID: AF242527) could not be annotated with SAGE tag, missing NlaIII anchoring enzyme recognition sites completely. Therefore, a total of 173 genes (including 53 established imprinted genes and 120 candidate imprinted genes) were annotated with the appropriate SAGE tags (Table 1) and subjected to further analysis.

Table 1: SAGE tag annotation for established and candidate imprinted gene subset.

Gene symbol
Gene name
Aliases

Status
Expressed

allele
NlaIII tag
Notes
GenBank accession number

1
NDUFA4
NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 4, 9 kDa

1p13.3
Candidate
Paternal
TTGGAGATCT

BC105295

2
GFI1
Growth-factor-independent 1 transcription repressor
ZNF163
1p22.1
Candidate
Paternal
TGTACCATAG

NM_001127215

3
NM019610
RNA-binding motif protein, X-linked-like 1 (RBMXL1), transcript variant 2

1p22.2
Candidate
Maternal
GCAGATTTAT

NM_019610

4
DIRAS3
DIRAS family, GTP-binding RAS-like 3
ARHI, NOEY2
1p31
Imprinted
Paternal
CAGAAAAAAA
* b
BC005362

5
BMP8B
Bone morphogenetic protein 8b
OP2, BMP8, MGC131757
1p35–p32
Candidate
Paternal
AGCAAAACTG
*
NM_001720

6
FUCA1
Fucosidase, alpha-L- 1, tissue
FUCA
1p36.11
Candidate
Paternal
CTATTTAGTT

NM_000147

7
TP73
TP73
P73
1p36.3
Imprinted
Maternal
TGGTACCGCC

NM_001126240

8
PRDM16
PR domain containing 16
MEL1
1p36.32
Candidate
Paternal
AGATTGATAT

NM_022114

9
PEX10
Peroxisomal biogenesis factor 10

1p36.32
Candidate
Maternal
GGAGGCGGCG

NM_002617

10
WDR8
WD repeat domain 8

1p36.32
Candidate
Maternal
TCGGTGCAGG

NM_017818

11
DVL1
Dishevelled, dsh homolog 1 (Drosophila)
DVL
1p36.33
Candidate
Maternal
GCCCGCAGGG

NM_004421

12
Q5EBL5
Family with sequence similarity 132, member A
FAM132A
1p36.33
Candidate
Maternal
GTTTCCAGGC

NM_001014980

13
TMEM52
Transmembrane protein 52

1p36.33
Candidate
Paternal
TTACACCGGC

NM_178545

14
HSPA6
Heat shock 70 kDa protein 6 (HSP70B′)

1q23.3
Candidate
Maternal
TATGAATTTT

NM_002155

15
PTPN14
Protein tyrosine phosphatase, nonreceptor type 14
PEZ
1q32.3
Candidate
Maternal
ACTTTTTCAA
*
BC017300

16
HIST3H2BB
Histone cluster 3, H2bb

1q42.13
Candidate
Maternal
AACTCCTTCG
*
NM_175055

17
OBSCN
Obscurin, cytoskeletal calmodulin and titin-interacting RhoGEF
KIAA1556, KIAA1639
1q42.13
Candidate
Paternal
CTGAGCGCCG
*
NM_001098623

18
Q8NGX0
Olfactory receptor, family 11, subfamily L, member 1
OR11L1
1q44
Candidate
Paternal
AGAAGGAAAT
*
NM_001001959

19
VAX2
Ventral anterior homeobox 2
DRES93
2p13.3
Candidate
Maternal
GGCGATGGGG

NM_012476

20
OTX1
Orthodenticle homeobox 1

2p15
Candidate
Maternal
GCGGTTCCAG

BC007621

21
Q96PX6
Coiled-coil domain containing 85A
CCDC85A, KIAA1912
2p16.1
Candidate
Paternal
GCAGATATTC

NM_001080433

22
ABCG8
ATP-binding cassette, subfamily G (WHITE), member 8

2p21
Candidate
Maternal
GGCTCCAAAA

NM_022437

23
ZFP36L2
Zinc finger protein 36, C3H type-like 2
ERF2, TIS11D
2p21
Candidate
Maternal
TAGAAAGGCA

NM_006887

24
CYP1B1
Cytochrome P450, family 1, subfamily B, polypeptide 1
P4501B1
2p22.2
Candidate
Paternal
AATGCTTTTA
*
NM_000104

25
RPL22
Ribosomal protein L22
EAP
2q13
Candidate
Paternal
GATGCTGCCA
*
CR456873

26
TIGD1
Tigger transposable element derived 1
EEYORE
2q37.1
Candidate
Paternal
CGAAAAGCTT
R
BC063500

27
MYEOV2
Myeloma overexpressed 2

2q37.3
Candidate
Paternal
CAGACTTTTT
*
AF487338

28
FTHFD
10-Formyltetrahydrofolate dehydrogenase
ALDH1L1; DKFZp781N0997
3q21.3
Candidate
Maternal
TCTGCATCTT

BC027241

29
ZIC1
Zic family member 1 (odd-paired homolog, Drosophila)
ZIC, ZNF201
3q24
Candidate
Maternal
ATAATAGTGG

NM_003412

30
HES1
Hairy and enhancer of split 1, (Drosophila)
HHL, HRY, HES-1, bHLHb39, FLJ20408
3q29
Candidate
Paternal
CACTATATTT

NM_005524

31
FGFRL1
Fibroblast growth factor receptor-like 1
FHFR, FGFR5
4p16.3
Candidate
Maternal
AAAGTGCATC

NM_001004358

32
SPON2
Spondin 2, extracellular matrix protein
DIL1
4p16.3
Candidate
Paternal
TTATGGATCT

NM_001128325

33
Q9NYJ6
Immunoglobulin superfamily, member 9
IGSF9, 644ETD8, Dasm1, Kiaa1355-hp, NRT1, Ncaml, mKIAA1355
4q13.2
Candidate
Paternal
TTACTGGCCC
R
BC030141

34
NAP1L5
Nucleosome assembly protein 1-like 5
DRLM
4q22.1
Imprinted
Paternal
TAGCTTTTAG

NM_153757

35
DUX2
Double homeobox 2

4q35.2
Candidate
Paternal
AAGGGGTGGA

NM_012147

36
CDH18
Cadherin 18, type 2
CDH14, CDH24, CDH14L, EY-CADHERIN
5p14.3
Candidate
Paternal
ATCGAAACTG

NM_004934

37
ADAMTS16
ADAM metallopeptidase with thrombospondin type 1 motif, 16
FLJ16731, ADAMTS16s
5p15.32
Candidate
Maternal
TACCCCTGAA
*
AK122980

38
Q8TBP5
Family with sequence similarity 174, member A
FAM174A
5q21.1
Candidate
Paternal
ACCCAGCGGG
*
NM_198507

39
CSF2
Colony-stimulating factor 2 (granulocyte-macrophage)
GMCSF, MGC131935, MGC138897
5q23.3
Candidate
Maternal
GTGGGAGTGG

BC108724

40
BTNL2
Butyrophilin-like 2 (MHC class II associated)
SS2, BTLII, HSBLMHC1
6p21.32
Candidate
Maternal
GAAGGAAAGA

NM_019602

41
FAM50B
Family with sequence similarity 50, member B
X5L, D6S2654E
6p25.2
Imprinted
Paternal
CCTCAGTTTG

BC001261

42
C6orf117
Chromosome 6 open-reading frame 117
MRAP2
6q14.2
Candidate
Paternal
GCAAGCTGTT

NM_138409

43
HYMAI
Hydatidiform mole associated and imprinted (nonprotein coding)
NCRNA00020
6q24.2
Imprinted
Paternal
TATATATTGA

BC059359

44
PLAGL1
Pleiomorphic adenoma gene-like 1
ZAC, LOT1, ZAC1, MGC126275, MGC126276, DKFZp781P1017
6q24–q25
Imprinted
Paternal
ATCATAATGT
*
NM_001080951

45
SLC22A2
Solute carrier family 22 (organic cation transporter), member 2
OCT2, MGC32628
6q26
Imprinted
Maternal
AAAATTATAA

BC030978

46
SLC22A3
Solute carrier family 22 (extraneuronal monoamine transporter), member 3
EMT, EMTH, OCT3
6q26–q27
Imprinted
Maternal
TGCGCTAATC

AF078749

47
BRP44L
Brain protein 44-like
CGI-129, dJ68L15.3
6q27
Candidate
Paternal
CAGTGTATAT

BC000810

48
DDC
Dopa decarboxylase (aromatic L-amino acid decarboxylase)
AADC
7p12.2
Imprinted
Isoform Dependent
TGGCTAAATG

NM_000790

49
GRB10
Growth factor receptor-bound protein 10
RSS, IRBP, MEG1, GRB-IR, Grb-10, KIAA0207
7p12–p11.2
Imprinted
Isoform Dependent
TGCTTTGCTT

NM_001001549

50
GLI3
GLI family zinc finger 3
PHS, ACLS, GCPS, PAPA, PAPB, PAP-A, PAPA1, PPDIV
7p14.1
Candidate
Maternal
TAAATACATT
*
NM_000168

51
EVX1
Even-skipped homeobox 1

7p15.2
Candidate
Paternal
ACGCCCGTGG

NM_001989

52
HOXA5
Homeobox A5
HOX1C, HOX1.3, MGC9376
7p15.2
Candidate
Maternal
AGCCTGTTTA

BC013682

53
HOXA2
Homeobox A2
HOX1K
7p15.2
Candidate
Maternal
CATATTTTTT
*
NM_006735

54
HOXA3
Homeobox A3
HOX1E, MGC10155
7p15.2
Candidate
Maternal
CTCTTCCTCG
R
BC015180

55
HOXA11
Homeobox A11
HOX1I
7p15.2
Candidate
Maternal
GAGATAGCCC

BC040948

56
HOXA4
Homeobox A4
HOX1D
7p15.2
Candidate
Maternal
TGCTAAGAAT

NM_002141

57
TMEM60
Transmembrane protein 60
DC32, MGC74482, C7orf35
7q11.23
Candidate
Paternal
AATCTATCCT

NM_032936

58
PEG10
Paternally expressed 10
Edr, HB-1, Mar2, MEF3L, Mart2, RGAG3, KIAA1051
7q21
Imprinted
Paternal
GAAGTTATAA

NM_001040152

59
MAGI2
Membrane-associated guanylate kinase, WW and PDZ domain containing 2
AIP1, SSCAM, KIAA0705
7q21.11
Candidate
Maternal
TATTAATAGT

BC150277

60
PPP1R9A
Protein phosphatase 1, regulatory (inhibitor) subunit 9A
NRB1, NRBI, FLJ20068, KIAA1222, neurabin-I
7q21.3
Imprinted
Maternal
GAAGAGACAA

NM_017650

61
SGCE
Sarcoglycan, epsilon
ESG, DYT11
7q21–q22
Imprinted
Paternal
TTGGCAGTAT
*
NM_001099400

62
TFPI2
Tissue factor pathway inhibitor 2
PP5, REF1, TFPI-2, FLJ21164
7q22
Imprinted
Maternal
TGCTTTTAAC

NM_006528

63
MEST
Mesoderm-specific transcript homolog (mouse)
PEG1, MGC8703, MGC111102, DKFZp686L18234
7q32
Imprinted
Paternal
CTGAATGTAC

NM_002402

64
COPG2IT1
COPG2 imprinted transcript 1 (nonprotein coding)
CIT1, COPG2AS, FLJ41646, NCRNA00170, DKFZP761N09121
7q32
Imprinted
Paternal
GAGGGATGGC
*
AF038190

65
CPA4
Carboxypeptidase A4
CPA3
7q32
Imprinted
Maternal
TCTGTAAATC
*
BC052289

66
MESTIT1
MEST intronic transcript 1 (nonprotein coding)
PEG1-AS, NCRNA00040
7q32
Imprinted
Paternal
TGTAGTGGTG

NR_004382

67
KLF14
Kruppel-like factor 14
BTEB5
7q32.3
Imprinted
Maternal
TGGACTCTGG

NM_138693

68
SLC4A2
Solute carrier family 4, anion exchanger, member 2 (erythrocyte membrane protein band 3-like 1)
AE2, HKB3, BND3L, NBND3, EPB3L1
7q36.1
Candidate
Maternal
CCCCTCCCTC
*
NM_003040

69
FASTK
Fas-activated serine/threonine kinase
FAST
7q36.1
Candidate
Maternal
GGGGGTGGAT

NM_006712

70
PURG
Purine-rich element binding protein G
PURG-A, PURG-B, MGC119274
8p12
Candidate
Paternal
CTGAACAAAG

NM_001015508

71
DLGAP2
Discs, large (Drosophila) homolog-associated protein 2
DAP2, SAPAP2
8p23
Imprinted
Paternal
CCCCAGCCCC
*
NM_004745

72
Q8N9I4
FLJ37098 fis, clone BRACE2019004

8p23.1
Candidate
Paternal
CTAAGCGCAG

AK094417

73
FAM77D
Family with sequence similarity 77, member D
NKAIN3, FLJ39630
8q12.3
Candidate
Paternal
GTGCCCTACC

NM_173688

74
GPT
Glutamic-pyruvate transaminase (alanine aminotransferase)
GPT1, AAT1, ALT1
8q24.3
Candidate
Maternal
CCAAGTTCAC

NM_005309

75
KCNK9
Potassium channel, subfamily K, member 9
KT3.2, TASK3, K2p9.1, TASK-3, MGC138268, MGC138270
8q24.3
Imprinted
Maternal
CCAGGCACTC
*
AK090707

76
LY6D
Lymphocyte antigen 6 complex, locus D
E48
8q24.3
Candidate
Paternal
GAGATAAATG

BC031330

77
APBA1
Amyloid beta (A4) precursor protein-binding, family A, member 1
X11, D9S411E, MINT1, LIN10
9q21.11
Candidate
Paternal
TGTCTCCTTC

NM_001163

78
NM182505
Chromosome 9 open-reading frame 85
C9orf85, MGC61599, RP11-346E17.2
9q21.12
Candidate
Paternal
TAAAAATAAA

NM_182505

79
FAM75D1
Family with sequence similarity 75, member D1
FLJ46321
9q21.32
Candidate
Maternal
CCCCACAGGA

NM_001001670

80
ABCA1
ATP-binding cassette, subfamily A (ABC1), member 1
TGD, ABC1, CERP, ABC-1, HDLDT1, FLJ14958, MGC164864, MGC165011
9q31.1
Imprinted
Unknown
ATGGGGAGAG
*
AK024328

81
LMX1B
LIM homeobox transcription factor 1, beta
NPS1, LMX1.2, MGC138325, MGC142051
9q33.3
Candidate
Maternal
GGAGCCCAGC
*
NM_002316

82
EGFL7
EGF-like-domain, multiple 7
ZNEU1, MGC111117, VE-STATIN, RP11-251M1.2
9q34.3
Candidate
Paternal
GCACAGGCCA

NM_016215

83
PHPT1
Phosphohistidine phosphatase 1
PHP14, CGI-202, HSPC141, bA216L13.10, DKFZp564M173, RP11-216L13.10
9q34.3
Candidate
Maternal
GCCTATGGTC

NM_014172

84
NM144654
Chromosome 9 open-reading frame 116, transcript variant 2
C9orf116, FLJ13945, MGC29761, RP11-426A6.4
9q34.3
Candidate
Paternal
GGAAAGATGC

NM_144654

85
GATA3
GATA binding protein 3
HDR
10p14
Candidate
Paternal
AAGGATGCCA
*
BC003070

86
Q9H6Z8
FLJ21625 fis, clone COL08015

10q23.31
Candidate
Paternal
GCAGCAGCCT

AK025278

87
LDB1
LIM domain binding 1
CLIM2, NLI
10q24.32
Candidate
Maternal
TCCTGACCAC

NM_001113407

88
INPP5F V2
Inositol polyphosphate-5-phosphatase F
SAC2, hSAC2, MSTP007, MSTPO47, FLJ13081, KIAA0966, MGC59773, MGC131851
10q26.11
Imprinted
Paternal
AGATTGAGGC

NR_003252

89
C10orf93
Chromosome 10 open-reading frame 93
bB137A17.3, RP13-137A17.3
10q26.3
Candidate
Maternal
AACAAAATTA

BC044661

90
NKX6-2
NK6 homeobox 2
NK, NKX6B
10q26.3
Candidate
Maternal
ACCGAGAGCC
*
NM_177400

91
PAOX
Polyamine oxidase (exo-N4-amino)
PAO, DKFZp434J245
10q26.3
Candidate
Maternal
GAGACTCTGT

NM_152911

92
C10orf91
Chromosome 10 open-reading frame 91
bA432J24.4, RP11-432J24.4
10q26.3
Candidate
Maternal
GGTTCTCAGC

BC030794

93
VENTX2
VENT-like homeobox-2
NA88A, HPX42B, VENTX2
10q26.3
Candidate
Maternal
TGCTTTTAAA

AF068006

94
WT1-Alt trans
Wilms tumor 1
WT1, GUD, WAGR, WT33, WIT-2
11p13
Imprinted
Paternal
CTGGTATATG

BC032861

95
KCNQ1OT1
KCNQ1 overlapping transcript 1 (nonprotein coding)
LIT1, KvDMR1, KCNQ10T1, KvLQT1-AS, long QT intronic transcript 1
11p15
Imprinted
Paternal
AAATATTTAC

AF086011

96
KCNQ1DN
KCNQ1 downstream neighbor
BWRT, HSA404617
11p15.4
Imprinted
Maternal
GGACCCCAAA

AB039920

97
OSBPL5
Oxysterol binding protein-like 5
ORP5, OBPH1, FLJ42929
11p15.4
Imprinted
Maternal
GGGGATGGAT

NM_001144063

98
PKP3
Plakophilin 3

11p15.5
Candidate
Maternal
AACAGTCAAA

NM_007183

99
Q8N9U2
FLJ36520 fis, clone TRACH2002100

11p15.5
Candidate
Maternal
ACAAGTATTC

AK093839

100
IFITM1
Interferon-induced transmembrane protein 1 (9–27)
IFI17, LEU13, CD225
11p15.5
Candidate
Maternal
ACCATTGGAT

NM_003641

101
PHLDA2
Pleckstrin homology-like domain, family A, member 2
IPL, BRW1C, BWR1C, HLDA2, TSSC3
11p15.5
Imprinted
Maternal
AGCCCGCCGC

NM_003311

102
CDKN1C
Cyclin-dependent kinase inhibitor 1C (p57, Kip2)
BWS, WBS, p57, BWCR, KIP2
11p15.5
Imprinted
Maternal
CCCATCTAGC

NM_000076

103
SLC22A18
Solute carrier family 22, member 18
HET, ITM, BWR1A, IMPT1, TSSC5, ORCTL2, BWSCR1A, SLC22A1L, p45-BWR1A, DKFZp667A184
11p15.5
Imprinted
Maternal
CTGGGCCTCT
*
NM_002555

104
IGF2/INS
Insulin/insulin-like growth factor 2 (somatomedin A)
INSIGF, pp9974, C11orf43, FLJ22066, FLJ44734/ILPR, IRDN
11p15.5
Imprinted
Paternal
CTTGGGTTTT

BC011786

105
IGF2AS
Insulin-like growth factor 2 antisense
PEG8, MGC168198
11p15.5
Imprinted
Paternal
GAGGGCCGTT

AB030733

106
H19
H19, imprinted maternally expressed transcript (nonprotein coding)
ASM, BWS, ASM1, MGC4485, PRO2605, D11S813E
11p15.5
Imprinted
Maternal
GCCACCCCCT
*
BC007513

107
KCNQ1
Potassium voltage-gated channel, KQT-like subfamily, member 1
LQT, RWS, WRS, LQT1, SQT2, ATFB1, ATFB3, JLNS1, KCNA8, KCNA9, Kv1.9, Kv7.1, KVLQT1, FLJ26167
11p15.5
Imprinted
Maternal
GGCAGGAGAC

BC017074

108
B4GALNT4
Beta-1,4-N-acetyl-galactosaminyl transferase 4
FLJ25045
11p15.5
Candidate
Maternal
TGGAGCGTCC

NM_178537

109
RAB1B
RAB1B, member RAS oncogene family

11q13.2
Candidate
Maternal
TCAGGCATTT

BC071169

110
KBTBD3
Kelch repeat and BTB (POZ) domain containing 3
BKLHD3, FLJ30685
11q22.3
Candidate
Paternal
AAACTACAAA

AK092993

111
NTRI
Neurotrimin
NTM, HNT, IGLON2, MGC60329
11q25
Candidate
Paternal
TCCCTCTTCA
R
NM_016522

112
ABCC9
ATP-binding cassette, subfamily C (CFTR/MRP), member 9
SUR2, ABC37, CMD1O, FLJ36852
12p12.1
Candidate
Maternal
TGTCTTTAAA
*
BX537513

113
RBP5
Retinol binding protein 5, cellular
CRBP3, CRBPIII, CRBP-III
12p13.31
Imprinted
Maternal
CTTCCTGTTA
*
AK096947

114
HOXC4
Homeobox C4
HOX3E, CP19
12q13.13
Candidate
Maternal
GTACCTGCTG

NM_153633

115
HOXC9
Homeobox C9
HOX3B
12q13.13
Candidate
Maternal
TACGGCTCGC

BC032769

116
SLC26A10
Solute carrier family 26, member 10

12q13.3
Candidate
Maternal
ACCCTTGAAC

NM_133489

117
CDK4
Cyclin-dependent kinase 4
PSK-J3, CMM3
12q14.1
Candidate
Maternal
GAAGGAAGAA
*
BC005864

118
Q96AV8
E2F transcription factor 7
E2F7, FLJ12981
12q21.2
Candidate
Maternal
TAAACTGATT

BC016658

119
Q9HCM7
Fibrosin-1-like protein
FBRSL1, AUTS2L, KIAA1545, XTP9
12q24.33
Candidate
Maternal
TCAATCAGTG

NM_001142641

120
Q8N7V5
Proline-rich 20A
PRR20A, FLJ40296
13q21.1
Candidate
Maternal
ACTCACTGGA
*
NM_198441

121
FAM70B
Family with sequence similarity 70, member B

13q34
Candidate
Maternal
GTGCCTCTGT

NM_182614

122
FOXG1C
Forkhead box G1
HFK3
14q12
Candidate
Paternal
GAACTATATG

BC050072

123
PLEKHC1
Fermitin family (Drosophila) homolog 2
FERMT2, MIG2, UNC112, KIND2
14q22.1
Candidate
Paternal
GTTCAAAGAC

NM_001134999

124
DLK1
Delta-like 1 homolog (Drosophila)
DLK, FA1, ZOG, pG2, PREF1, Pref-1
14q32
Imprinted
Paternal
ATACAGAATA
*
BC013197

125
MEG3
Maternally expressed 3 (nonprotein coding)
GTL2, FP504, prebp1, PRO0518, PRO2160, FLJ31163, FLJ42589
14q32
Imprinted
Maternal
TGGGAAGTGG

AB032607

126
RTL1
Retrotransposon-like 1
PEG11
14q32.31
Candidate
Maternal
ACGGCCTGCA

NM_001134888

127
ATP10A
ATPase, class V, type 10A
ATPVA, ATPVC, ATP10C, KIAA0566
15q11.2
Imprinted
Maternal
GCCCCCAGAG

BC052251

128
PWCR1
Prader-Willi syndrome chromosome region 1
PET1, noncoding RNA in the Prader-Willi critical region
15q11.2
Imprinted
Paternal
TTGGTGAGGG

AF241255

129
NDN
Necdin homolog (mouse)
HsT16328
15q11.2–q12
Imprinted
Paternal
ACCTTGCTGG

BC008750

130
SNURF/

SNRPN
SNRPN upstream reading frame/small nuclear ribonucleoprotein polypeptide N
SMN, PWCR, SM-D, RT-LI, HCERN3, SNRNP-N, FLJ33569, FLJ36996, FLJ39265, MGC29886, SNURF-SNRPN, DKFZp762N022, DKFZp686C0927, DKFZp761I1912, DKFZp686M12165
15q11.2–q12
Imprinted
Paternal
CCGCCTCCGG

BC000611

131
MAGEL2
MAGE-like 2
nM15, NDNL1
15q11–q12
Imprinted
Paternal
TAGCATTGTA

BC035839

132
MKRN3
Makorin ring finger protein 3
D15S9, RNF63, ZFP127, ZNF127, MGC88288
15q11–q13
Imprinted
Paternal
AAATAATTTA

NM_005664

133
UBE3A
Ubiquitin protein ligase E3A
AS, ANCR, E6-AP, HPVE6A, EPVE6AP, FLJ26981
15q11–q13
Imprinted
Maternal
CTGTAAAACA

BC002582

134
Q9P168
PRO2369

15q13.1
Candidate
Paternal
AGAACTCCAC

AF119879

135
SOX8
SRY (sex-determining region Y)-box 8

16p13.3
Candidate
Paternal
CAGCGTCTCC

BC031797

136
SALL1
Sal-like 1 (Drosophila)
HSAL1
16q12.1
Candidate
Maternal
ACATTTCTAG
R
BC113881

137
C16orf57
Chromosome 16 open-reading frame 57

16q13
Candidate
Maternal
GGATTTTAAT

BC004415

138
ACD
Adrenocortical dysplasia homolog (mouse)
PTOP, PIP1, TINT1, TPP1
16q22.1
Candidate
Maternal
CGGCAAAAAA

BC016904

139
FOXF1
Forkhead box F1
FKHL5, FREAC1, ACDMPV
16q24.1
Candidate
Maternal
TTCCTCCTCT
*
BC089442

140
ANKRD11
Ankyrin repeat domain 11
T13, LZ16, ANCO-1
16q24.3
Imprinted
Maternal
AAAGCTGACA

BC058001

141
Q8N206
FLJ36443 fis, clone THYMU2012891
FLJ36443 fis
16q24.3
Candidate
Maternal
ACATTCAGAA

AK093762

142
TMEM88
Transmembrane protein 88
FLJ20025
17p13.1
Candidate
Maternal
CTGGGCTTCG

NM_203411

143
PYY2
Peptide YY, 2 (seminal plasmin)

17q11.2
Candidate
Paternal
TTCACTCCCG

AF222904

144
HOXB3
Homeobox B3
HOX2G
17q21.32
Candidate
Maternal
AACTCAGCTC

NM_002146

145
HOXB2
Homeobox B2
HOX2H
17q21.32
Candidate
Maternal
AAGCACAAGC

NM_002145

146
Q8N8L1
FLJ39287 fis, clone OCBBF2011897
LOC100131170
17q25.3
Candidate
Paternal
GGGTCTGAGG

AK096606

147
FAM59A
Family with sequence similarity 59, member A
GAREM, Gm944, C18orf11
18q12.1
Candidate
Paternal
TGCAGAGAAA

NM_022751

148
BRUNOL4
Bruno-like 4
CELF4
18q12.2
Candidate
Maternal
GCTGTTCTTG

NM_001025087

149
TCEB3C
Transcription elongation factor B polypeptide 3C (elongin A3)
HsT829, TCEB3L2, elongin A3
18q21.1
Imprinted
Maternal
ACCTCCCAGG
*
NM_145653

150
Q8NE65
Zinc finger protein 738
ZNF738
19p13.11
Candidate
Paternal
TTGGTCAGGC
R
BC034499

151
Q8NB05
FLJ34424 fis, clone HHDPC2008279

19p13.2
Candidate
Paternal
TGCTCGGGAA

AK091743

152
PPAP2C
Phosphatidic acid phosphatase type 2C
PAP2C, LPP2
19p13.3
Candidate
Maternal
GTGTTCTTGG

NM_003712

153
TSH3
Teashirt zinc finger homeobox 3
TSHZ3, ZNF537, FLJ54422, KIAA1474
19q12
Candidate
Paternal
TTCTTATTTT
*
AK291466

154
CHST8
Carbohydrate (N-acetylgalactosamine 4-0) sulfotransferase 8
GalNAc4ST1, GalNAc4ST
19q13.11
Candidate
Maternal
GTTTCCAGAG
*
NM_001127895

155
ZNF225
Zinc finger protein 225
MGC119735
19q13.31
Candidate
Paternal
TGGTATGTAT

NM_013362

156
ZNF229
Zinc finger protein 229
FLJ34222
19q13.31
Candidate
Maternal
TTGTAACCTC

NM_014518

157
ZNF264
Zinc finger protein 264
ZFP264
19q13.4
Imprinted
Maternal
GCTTCAGTGG

NM_003417

158
ZIM2/PEG3
ZIM2 zinc finger, imprinted 2/Paternally expressed 3
ZNF656/PW1, ZSCAN24, KIAA0287, DKFZp781A095
19q13.4
Imprinted
Paternal
TTTTCACCAT

BC037330

159
LILRB4
Leukocyte immunoglobulin-like receptor, subfamily B (with TM and ITIM domains), member 4
LIR5, ILT3, HM18, CD85K
19q13.42
Candidate
Maternal
GGAAAATGGG
*
NM_001081438

160
ZNF550
Zinc finger protein 550

19q13.43
Candidate
Maternal
AGAAATGTAC
*
AK122867

161
CHMP2A
Chromatin-modifying protein 2A
VPS2A, VPS2, BC2
19q13.43
Candidate
Maternal
GGTGATGAGG
*
NM_014453

162
ZNF42
Zinc finger protein 42
MZF1, MZF1B, ZFP98, ZSCAN6
19q13.43
Candidate
Maternal
GTCAGAACAC
*
NM_003422

163
ISM1
Isthmin 1 homolog (zebrafish)
C20orf82
20p12.1
Candidate
Paternal
AATATTATCA

NM_080826

164
NNAT
Neuronatin
PEG5, MGC1439
20q11.2–q12
Imprinted
Paternal
CAGTTGTGGT

NM_005386

165
BLCAP
Bladder cancer-associated protein
BC10
20q11.2–q12
Imprinted
Isoform Dependent
CCTGTCCTTT

NM_006698

166
L3MBTL
L(3)mbt-like (Drosophila)
L3MBTL1, FLJ41181, KIAA0681, H-L(3)MBT, dJ138B7.3, DKFZp586P1522
20q13.12
Imprinted
Paternal
TGTGTATGTG
*
AB014581

167
GNAS
GNAS complex locus
AHO, GSA, GSP, POH, GPSA, NESP, GNAS1, PHP1A, PHP1B, C20orf45, MGC33735, dJ309F20.1.1, dJ806M20.3.3
20q13.3
Imprinted
Isoform Dependent
ATTAACAAAG

NM_000516

168
GNASAS
GNAS antisense RNA 1 (nonprotein coding)
SANG, NESPAS, GNAS1AS, NCRNA00075
20q13.32
Imprinted
Paternal
TCCATTAGAA

AJ251759

169
COL9A3
Collagen, type IX, alpha 3
IDD, MED, EDM3, FLJ90759, DJ885L7.4.1
20q13.33
Candidate
Maternal
AAGGAGCGGG
*
BC011705

170
C20orf20
Chromosome 20 open-reading frame 20
Eaf7, MRGBP, URCC4, MRG15BP, FLJ10914
20q13.33
Candidate
Maternal
ACCTCACTCT

BC009889

171
SIM2
Single-minded homolog 2 (Drosophila)
SIM, bHLHe15, MGC119447
21q22.13
Candidate
Paternal
AAGGAAGATT
*
NM_005069

172
DGCR6
DiGeorge syndrome critical region gene 6

22q11.21
Candidate
Paternal
CAGAAGAGGC
*
NM_005675

173
FLJ20464
Hypothetical protein FLJ20464

22q12.2
Candidate
Paternal
CGTGAAATTC

CR456348

SAGE tags annotated for NlaIII anchoring enzyme.

aEntries are sorted according to the established gene location.

b*: tag maps to other gene(s) according to CGAP (Cancer Genome Anatomy Project, NCI, NIH) SAGE Anatomic Viewer.

c#: highly repetitive tag according to CGAP SAGE Anatomic Viewer.

dR: unreliable/internal tag suggested by CGAP SAGE Anatomic Viewer is replaced with reliable 3′ end tag.

The complete set of publicly available human SAGE catalogues was downloaded from the Gene Expression Omnibus (GEO, NCBI) database. Acquired SAGE catalogues represent 581 SAGE libraries generated from a wide spectrum of cell and tissue samples in a variety of physiological and pathological conditions. Following an exclusion of the numerous duplicate GEO database entries (e.g., GSM785 = GSM383907; GSM1515 = GSM383958; GSM85612 = GSM125353, etc.), the criteria listed below were applied when selecting libraries for the analysis of gene expression. SAGE libraries were selected only if they have represented (i) genetically unaltered/unmodified samples, (ii) SAGE catalogues with a total number of tags 20,000, and (iii) a complete dataset available. For example, samples GSM383929 and GSM180669 were excluded since these did not satisfy criteria (i), representing ovary surface epithelium immortalized with SV40 and lymphocytes from Down syndrome children, respectively; samples GSM384024 (white blood cells, CD45⁺, isolated from a mammary gland carcinoma; 18,741 tags) and GSM1128 (breast cancer cell line; tags detected once are not available) were excluded as not satisfying criteria(ii) and (iii), respectively (Supplementary Table 1). Due to the conservative nature of the criteria listed above, a total number of SAGE catalogues satisfying these and thus selected for further analysis (i.e., to the extraction of tags matching imprinted genes) was reduced to 492. Together, these 492 SAGE catalogues representing human samples account for 35.97 million SAGE tags constructed using NlaIII-anchoring enzyme. The catalogues were assigned into one of the following Clusters: C (cancer tissue; 185 SAGE catalogues), N (normal tissue and cells; 166 SAGE catalogues), IV (cells cultured in vitro; 112 SAGE catalogues), or D (nontumorous disease tissue and cells; 29 SAGE catalogues) (Table 2, and Supplementary Table 1).

Table 2: Summary of SAGE catalogs analyzed.

Clusters
Number of SAGE
Number of SAGE

C (cancer tissue)
185
13,165,432

N (normal tissue and cells)
166
12,953,131

IV (cells cultured in vitro)
112
8,009,673

D (nontumorous disease tissue and cells)
29
1,840,291

Total
492
35,968,527

All SAGE catalogs screened belong to GPL4 Gene Expression Omnibus database (GEO, NCBI) platform (Homo sapiens; NlaIII-anchoring enzyme).

aSAGE catalogs selected for analysis (see Supplementary Table 1 available online at doi:10.1155/2012/793506).

bNumber of tags subjected for analysis (with (A)₁₀ tags excluded).

Figure 1 shows a distribution of the analyzed established and candidate imprinted genes through the human genome. Primary analysis of the normalized expression profiles of the imprinted genes demonstrated a great variability in the cumulative gene expression for 173 genes (Figure 2, Table 3, and Supplementary Table 2). Average cumulative gene expression of those genes in human tissues and cells was 0.90% of the total gene expression: specifically, 0.95% for both cancer and normal tissue and cells (clusters C and N, resp.), 0.77% for cells cultured in vitro (cluster IV), and 0.83% for nontumorous disease tissue and cells (cluster D). In the pool of the assessed SAGE catalogues, it ranged from 0.08% (total blood, GSM389907 [21]) to 4.36% of the total gene expression (bronchial epithelium, GSM125353 [22]). Of 492 human SAGE catalogues tested, the cumulative expression of the imprinted genes constituted >2% of the total gene expression in 21 and <0.2% in 7 catalogues. The SAGE libraries with 10% most and 10% least cumulative and average expression of established and candidate imprinted gene subsets are listed in Table 3.

Table 3: The SAGE libraries with 10% most and 10% least cumulative and average expression of established and candidate imprinted genes subsets.

IDa
Primary IDb
SAGE library
Sample
Clusterc
Sumd
Averagee
Maxf

Top 10% libraries

76
301
GSM125353
Bronchial brushings, former smoker
N
43,563.92
251.81
40,054.67

4
6
GSM574
Central retina (macula)
N
33,159.24
191.67
26,692.01

142
427
GSM383793
Mammary gland, ductal carcinoma in situ
C
29,781.50
172.15
25,275.20

29
104
GSM1730
Breast, ductal carcinoma in situ
C
29,575.98
170.96
25,125.63

75
300
GSM125352
Bronchial brushings, former smoker
N
29,184.64
168.70
24,955.09

145
430
GSM383797
Mammary gland, ductal carcinoma
C
27,222.30
157.35
22,422.27

99
346
GSM194651
Oral biopsy
N
27,066.16
156.45
21,312.29

90
273
GSM112808
Neuroblastoma, primary tumor, stage 4S
C
25,944.14
149.97
17,365.83

55
155
GSM14753
Breast carcinoma metastasis to lung
C
23,941.22
138.39
20,247.08

143
428
GSM383794
Mammary gland, ductal carcinoma in situ
C
23,570.83
136.25
18,977.90

30
105
GSM1731
Breast, ductal carcinoma in situ
C
23,346.84
134.95
18,746.14

167
507
GSM383893
Gallbladder tubular adenocarcinoma
C
23,262.07
134.46
20,154.48

27
561
GSM384016
Vascular endothelium, hemangioma, benign hyperplasia
D
22,688.19
131.15
12,514.88

91
274
GSM112809
Neuroblastoma, primary tumor, stage 4S
C
22,633.99
130.83
11,595.94

28
101
GSM1516
Hemangioma tumor
C
22,622.41
130.77
12,500.82

100
347
GSM194652
Oral biopsy
N
21,279.52
123.00
11,932.33

146
440
GSM383807
Mammary gland, ductal carcinoma in situ
C
20,570.15
118.90
16,071.37

62
433
GSM383800
Breast carcinoma cell line
IV
20,467.40
118.31
12,710.80

140
425
GSM383790
Mammary gland, ductal carcinoma
C
20,417.00
118.02
15,536.62

144
537
GSM383946
Whole body, fetal
N
20,274.33
117.19
9,698.99

149
443
GSM383812
Mammary gland, ductal carcinoma
C
20,036.49
115.82
13,377.93

5
21
GSM688
Breast, ductal carcinoma in situ
C
19,968.16
115.42
15,538.48

118
416
GSM383775
Cortex, pooled sample
N
19,926.52
115.18
13,701.49

54
263
GSM85616
Bronchial epithelium
N
19,665.60
113.67
15,918.74

53
262
GSM85611
Bronchial epithelium
N
19,653.98
113.61
15,655.95

17
340
GSM194386
Metaplastic bronchial epithelium
D
19,376.31
112.00
14,577.13

81
306
GSM125358
Bronchial brushings, never smoker
N
19,369.05
111.96
14,172.30

137
509
GSM383895
Gallbladder
N
19,320.00
111.68
15,346.14

66
437
GSM383804
Breast carcinoma cell line
IV
19,247.28
111.26
9,389.55

31
106
GSM1733
Mammary gland, ductal invasive in situ carcinoma
C
19,126.03
110.56
14,594.68

92
276
GSM112812
Neuroblastoma, primary tumor, stage 4
C
18,914.78
109.33
12,349.04

3
5
GSM573
Peripheral retina
N
18,817.72
108.77
12,293.99

2
4
GSM572
Peripheral retina
N
18,781.47
108.56
8,727.76

96
331
GSM194377
Nonsmall cell lung cancer: squamous cell carcinoma in situ
C
18,122.08
104.75
14,601.68

71
181
GSM14781
Brain desmoplastic medulloblastoma
C
18,106.48
104.66
11,244.70

68
439
GSM383806
Breast carcinoma cell line
IV
17,991.89
104.00
8,886.81

66
291
GSM125343
Bronchial brushings, former smoker
N
17,662.13
102.09
12,756.35

60
285
GSM125337
Bronchial brushings, current smoker
N
17,598.56
101.73
12,699.28

121
387
GSM383710
Ependymoma
C
17,524.27
101.30
10,222.49

51
260
GSM82458
Hippocampus
N
17,289.52
99.94
8,268.90

72
297
GSM125349
Bronchial brushings, former smoker
N
17,225.16
99.57
13,193.26

109
361
GSM296391
Lung biopsy
N
17,223.67
99.56
13,839.55

62
287
GSM125339
Bronchial brushings, current smoker
N
16,871.13
97.52
10,737.09

98
333
GSM194379
Nonsmall cell lung cancer: squamous cell carcinoma in situ
C
16,572.81
95.80
12,713.33

74
299
GSM125351
Bronchial brushings, former smoker
N
16,456.57
95.12
11,137.34

70
295
GSM125347
Bronchial brushings, former smoker
N
16,306.85
94.26
11,835.62

7
216
GSM37212
Adrenal cortex affected by primary pigmented nodular adrenocortical disease
D
16,221.46
93.77
4,205.56

59
284
GSM125336
Bronchial brushings, current smoker
N
16,090.33
93.01
11,242.21

94
329
GSM194375
Nonsmall cell lung cancer: squamous cell carcinoma in situ
C
15,715.04
90.84
11,679.51

Bottom 10% libraries

83
488
GSM383868
Colon carcinoma, cell line
IV
4,179.31
24.16
422.91

38
180
GSM14780
Gastric epithelial tissue from the antrum
N
4,169.95
24.10
1,615.39

84
204
GSM14807
Lung, poorly differentiated adenocarcinoma with lymphoplasmacytic infiltration
C
4,146.18
23.97
460.69

181
553
GSM383998
Gastroesophageal junction adenocarcinoma
C
4,141.08
23.94
1,351.60

1
7
GSM668
Kidney, embryonic cell line 293, uninduced cells
IV
4,119.01
23.81
920.45

4
120
GSM3244
AIDS-KS lesion
D
4,107.85
23.74
1,245.47

25
522
GSM383914
Lung, tumor associated (focal fibrosis and chronic inflammation)
D
4,103.62
23.72
606.45

30
121
GSM3245
CD4+ T cells
N
4,088.74
23.63
978.17

44
137
GSM14734
Medulloblastoma, cerebellum
C
4,081.98
23.60
804.90

56
162
GSM14760
Stomach, poorly differentiated carcinoma
C
4,081.16
23.59
1,340.95

54
153
GSM14751
Skin, melanoma
C
4,072.22
23.54
2,497.12

80
485
GSM383865
Colon carcinoma, cell line
IV
4,048.02
23.40
404.80

130
404
GSM383753
Medulloblastoma
C
3,987.16
23.05
1,069.73

82
487
GSM383867
Colon carcinoma, cell line
IV
3,961.32
22.90
506.24

12
71
GSM747
Colon, cancer cell line
IV
3,945.42
22.81
673.61

166
506
GSM383892
Gallbladder adenocarcinoma
C
3,909.95
22.60
651.66

115
372
GSM311354
CD15+ myeloid progenitor cells
N
3,859.27
22.31
1,108.11

52
261
GSM82459
Spermatozoa
N
3,814.90
22.05
1,288.15

50
259
GSM82243
Spermatozoa, pooled sample
N
3,811.16
22.03
1,429.18

94
328
GSM180670
Lymphocytes from children 1–4 years old (pooled samples)
N
3,794.27
21.93
843.17

81
486
GSM383866
Colon carcinoma, cell line
IV
3,746.12
21.65
378.40

39
183
GSM14784
Bone marrow
N
3,740.58
21.62
962.65

88
318
GSM136195
Cord blood-derived activated Th1 cells
N
3,668.81
21.21
777.29

20
423
GSM383787
Breast stroma, ductal carcinoma in situ associated
D
3,663.78
21.18
334.67

38
234
GSM66698
HL-60 cells
IV
3,661.81
21.17
920.25

168
508
GSM383894
Gallbladder tubular adenocarcinoma
C
3,643.40
21.06
624.22

28
217
GSM37337
Primary bronchial epithelial cells
IV
3,604.30
20.83
804.84

177
546
GSM383970
Retinoblastoma
C
3,561.82
20.59
384.45

71
475
GSM383852
Cartilage chondrosarcoma cell line
IV
3,502.94
20.25
515.14

38
127
GSM7800
Primary gastric cancer, poorly differentiated (scirrhous type)
C
3,413.27
19.73
636.37

130
466
GSM383840
Mammary myoepithelium, CD10+ cells
N
3,364.85
19.45
291.33

39
235
GSM66712
HL-60 cells exposed to 2.45 GHz radiofrequency for 2 h
IV
3,293.77
19.04
982.36

97
344
GSM194649
Oral brushing
N
3,290.72
19.02
996.85

173
523
GSM383915
Lymph node, B-cell lymphoma
C
3,166.97
18.31
555.61

140
514
GSM383902
Leukocytes
N
2,991.69
17.29
439.34

65
436
GSM383803
Breast carcinoma cell line
IV
2,988.12
17.27
597.62

63
434
GSM383801
Breast carcinoma cell line
IV
2,977.71
17.21
297.77

21
84
GSM784
Gastric epithelial tissues
N
2,970.06
17.17
673.21

151
554
GSM384002
Stomach
N
2,813.83
16.26
654.38

170
515
GSM383903
Liver cholangiocarcinoma metastasis
C
2,736.32
15.82
1,575.46

29
578
GSM389908
Total blood after EPO treatment, pooled sample
D
2,684.90
15.52
747.69

68
175
GSM14775
Skin, primary malignant melanoma
C
2,612.99
15.10
653.25

40
236
GSM66714
HL-60 cells exposed to 2.45 GHz radiofrequency for 6 h
IV
1,879.82
10.87
639.52

143
533
GSM383937
Pancreas
N
1,813.11
10.48
278.94

83
308
GSM135389
Skeletal muscle, 5 days training young men
N
1,673.61
9.67
435.14

86
311
GSM135392
Skeletal muscle, detraining young men
N
1,670.43
9.66
510.41

165
576
GSM389906
Total blood, pooled sample
N
1,511.12
8.73
436.55

82
307
GSM135388
Skeletal muscle, pretraining young men
N
1,091.72
6.31
327.52

28
577
GSM389907
Total blood during EPO treatment, pooled sample
D
811.75
4.69
162.35

Indexes (GSM numbers) represent GEO database accession numbers for SAGE libraries (one accession number selected for redundant entries).

aID: listing within each cluster (see Supplementary Table 2).

bPrimary ID: listing within a full dataset (see Supplementary Table 1).

cClusters: C: cancer tissue; N: normal tissue and cells; IV: cells cultured in vitro; D: nontumorous disease tissue and cells.

dSum: cumulative (total) tag per million (tpm) value for SAGE tags matching established and candidate imprinted genes within the SAGE library.

eAverage: tpm value for SAGE tags matching established and candidate imprinted genes within the SAGE library.

fMax: maximum tpm value for SAGE tags matching established and candidate imprinted genes within the SAGE library.

Particular sum: average and maximum values could be recalculated to the fraction of the total gene expression by dividing tpm value to 1,000,000.

Entries are sorted according to the cumulative (total) tpm value.

Figure 1: A schematic representation of the analyzed established (53, filled arrowheads) and candidate (120, empty arrowheads) imprinted genes distribution through the human genome. Chromosome layout is via NCBI (Build 37.2). Numbers next to some of the arrowheads indicate the number of entries per locus.

(a)

(b)

(c)

(d)

(e)

(f)

Figure 2: Histogram of average ((a), (b), and (c)) and maximum ((d), (e), and (f)) tag per million (tpm) values of the pool of imprinted genes and gene candidates for the normalized SAGE catalogues: cancer tissue ((a), (d); 185 catalogues); normal tissues and cells ((b), (e); 166 catalogues); cells cultured in vitro ((c), (f); 112 catalogues). Corresponding histogram pairs are built following a sorting by the maximum value in the pool.

In some samples, a major fraction of the cumulative expression of the imprinted genes was established by only a few highly abundant transcripts. For example, in the GSM125353 SAGE catalogue already mentioned above, 91.9% of the cumulative (total) gene expression of the assayed imprinted genes is represented by the single gene, namely, PTPN14 (ACTTTTTCAA tag). Similarly, in GSM383893 SAGE catalogue (gallbladder tubular adenocarcinoma [17, 23]), the same gene constitutes 86.6% of the cumulative (total) gene expression of the assayed imprinted genes. In many other SAGE catalogues, expression profile of the assayed imprinted genes was rather more balanced. For example, in the GSM383840 SAGE catalogue (mammary myoepithelium, CD10⁺ cells [24]), PTPN14 constitutes just 8.7% of the cumulative (total) gene expression of the assayed imprinted genes, equal to GNAS gene (ATTAACAAAG tag). Some imprinted genes were expressed almost ubiquitously through the samples: for example, genes NDUFA4, RPL22, Q8NE65, PTPN14, GNAS, and RAB1B (Supplementary Table 3). Notably, in other cases, expression of the particular imprinted genes either was not detected at all in all 492 SAGE catalogues screened (EVX1, ACGCCCGTGG tag), or was detected only occasionally (Supplementary Table 3). For example, gene DUX2 (AAGGGGTGGA tag) expression was detected only 3 times (on a minimum level) in 492 SAGE catalogues representing cell and tissue samples in a variety of physiological and pathological conditions: namely, in GSM383692 SAGE catalogue (astrocytoma grade II [25]), GSM383867 SAGE catalogue (colon carcinoma cell line [17, 23]), and GSM383928 SAGE catalogue (ovary preneoplasia cell line [26]). Similarly rare was the expression of FAM75D1 (detected only 3 times altogether), FAM77D, ISM1, FLJ20464, and Q8NB05 (detected only 5 times, in all cases on a minimum level).

To assess variation in the expression of individual imprinted genes in the samples, the clustering analysis of the normalized expression profiles was performed using EPCLUST (Expression Profile data CLUSTering and analysis) software. For each dataset, the number of clusters was set to the lowest value yielding one cluster containing a solitary database entry; 5 for cancer tissue, 6 for normal tissues and cells, 5 for cells cultured in vitro, and 2 for nontumorous disease tissue and cells (Figures 3–7). Notable diversity was observed in the transcription profiles represented by the individual clusters, with relatively high expression levels characteristic for just 1-2 or a higher number of the individual imprinted genes (Figures 4(a), 4(b)–7(a), and 7(b)). Expectedly, in a few cases samples generated from the same tissues/cell types did fell into the same compact cluster of the distinct pattern (Figure 3, Figures 4(a), 4(b)–7(a), and 7(b)). However, in many other cases imprinted gene expression profiles of the same/similar tissue or cell types fall into different clusters. Similarly, though in many cases imprinted gene expression profiles of the same/similar tissue or cell types fell into the closely matching area of the hierarchical tree built for the individual datasets (clusters C, N, IV, and D) (Figures 4(c), 5(c), 5(d), 6(c), and 7(c)), in other cases notable variability was observed in the distribution of imprinted gene expression profiles of the same/similar tissue or cell types. For example, at K-mean clustering, small-size cluster 3 in cancer tissue dataset (3 entries) is composed entirely of neuroblastoma samples (Figures 4(a) and 4(b)); however, other entries representing tumors of the same histological properties [27] fell into cluster 1 (composed of 141 entries in total). Cluster 4 in the same dataset (12 entries) is composed entirely of carcinoma samples, while cluster 2 (28 entries) is composed of carcinoma samples predominantly (19 entries), with other samples representing astrocytoma (3 entries), glioblastoma multiforme (2 entries), cystadenoma (1 entry), rhabdosarcoma (1 entry), and unclassified breast cancer (2 entries). Similarly, only one cluster in the normal tissue and cell dataset has a homogenous composition (cluster 5, 2 entries), matching both available SAGE libraries constructed from placenta (GSM14849, also designated GSM383945; GSM14750, also designated GSM383947 [17]) (Figure 3), with all other clusters composed of the samples of diverse origins. Illustratively, this particular cluster brakes down (i.e., cluster content get redistributed to the clusters of the smaller size) only if the number of K-mean clusters for the dataset is increased from the set value of 6 to 26, while some other clusters break down more readily. In the hierarchical trees, most densely packed areas (representing most similar transcription profiles) are generally composed of the samples of the same/similar tissue or cell types. For example, one of the densest areas in four hierarchical trees built is composed of 19 samples matching bronchial brushings (Figures 5(c) and 5(d)) [22], with all 5 other samples of the same origin falling into the nearest vicinity within the hierarchical tree (Figure 5(c)). At the same time, some SAGE libraries representing the samples of the identical origin fell into the separate K-mean clusters and into well-separated areas of the hierarchical tree. This was observed, for example, for 3 available peripheral retina samples, from which GSM572 and GSM573 [28] fell into cluster 3, and GSM383968 [29] fells into cluster 1 (Figure 4).

(a)

(b)

Figure 3: An example of gene expression pattern recognized by K-mean clustering analysis (normal tissue and cells, cluster 5). Graph line (a) and cluster contents (b). Vertical bars denote individual genes. Exponential shades of grey code (5 colors) are based on the normalized tpm values. GSM14749: first trimester placenta; GSM14750: full-term placenta. Imprinted genes with peak expression values in the cluster are indicated. PTPN14: protein tyrosine phosphatase, nonreceptor type 14; TFPI2: tissue factor pathway inhibitor 2; DLK1: delta-like 1 homolog (Drosophila).

(a)

(b)

(c)

Figure 4: Gene expression patterns recognized by K-mean and hierarchical clustering analysis (cancer tissue, 185 SAGE catalogues). K-mean clustering analysis, (a) graph lines and (b) cluster contents; vertical bars denote individual genes. (c) Hierarchical cluster tree. Exponential shades of red code (15 colors) are based on the normalized tpm values.

(a)

(b)

(c)

(d)

Figure 5: Gene expression patterns recognized by K-mean and hierarchical clustering analysis (normal tissue and cells, 166 SAGE catalogues). K-mean clustering analysis, (a) graph lines and (b) cluster contents; vertical bars denote individual genes. Arrowheads point out 3 SAGE libraries generated from peripheral retinal samples. (c) Hierarchical cluster tree, fragment (d) enlarged is highlighted. Exponential shades of red code (15 colors) are based on the normalized tpm values.

(a)

(b)

(c)

Figure 6: Gene expression patterns recognized by K-mean and hierarchical clustering analysis (cells cultured in vitro, 112 SAGE catalogues). (a) K-mean clustering analysis, graph-lines and (b) cluster contents; vertical bars denote individual genes. (c) Hierarchical cluster tree. Arrowheads point out 13 SAGE libraries generated from undifferentiated embryonic stem cells (ESC). Exponential shades of red code (15 colors) are based on the normalized tpm values.

(a)

(b)

(c)

Figure 7: Gene expression patterns recognized by K-mean and hierarchical clustering analysis (nontumorous disease tissue and cells, 29 SAGE catalogues). (a) K-mean clustering analysis, graph lines and (b) cluster contents; vertical bars denote individual genes. (c) Hierarchical cluster tree. Exponential shades of red code (15 colors) are based on the normalized tpm values.

4. Discussion

Mechanism of genomic imprinting plays important, yet not fully understood role in many physiological processes: in particular, in the control of growth and development. Since the identification of the first imprinted genes (IGF2, IGF2R, and H19) in mouse in 1991, a large volume of information has been accumulated on the identity and biological function of imprinted genes both for Homo sapiens and animal species (Mus musculus in particular). Over the course of the decade, we witness an expansion of the list of the established imprinted genes [6, 30]. It is most probable that novel candidate imprinted genes will be identified in the future, and features of the imprinted genes will be confirmed for some candidates. In the current study, a comprehensive list of the human imprinted genes and high-confidence gene candidates (203 entries total) became a subject for a large-scale in silico gene expression profiling. Available nucleotide sequences (174 genes and gene candidates) have been utilized for the extraction of the appropriate short SAGE tags matching NlaIII anchoring enzyme, most common in generating SAGE libraries. Notably, candidate imprinted gene Q9NYI9 (PPARL) did not bear NlaIII recognition sites. This limitation of the conventional SAGE protocol can generally be overcome by using an alternative anchoring enzyme [16]. However, gene Q9NYI9 does not bear recognition sites for anchoring enzymes Sau3AI and RsaI (second and third most common in generating SAGE libraries) as well, though it bears one for MmeI utilized in LongSAGE protocol. Taken together, not 174 but 173 genes (missing Q9NYI9 (PPARL))—including 53 established imprinted genes and 120 candidate imprinted genes—were annotated with the appropriate SAGE tags. The latter was matched the pool of 492 normalized SAGE catalogues representing libraries derived from human samples, constructed using NlaIII anchoring enzyme and together accounting for 35.97 million SAGE tags. Collectively, these catalogues represent a comprehensive assay of tissues and cell types in physiological and a variety of pathological conditions. Gene expression of imprinted genes was assessed in the normalized SAGE catalogues representing the transcriptomes of these samples, according to the straightforward algorithm of in silico analysis.

As with nearly any other gene, expression of imprinted genes is not a constant, but rather a dynamic function of cell type and state. In the current study, a great variability was observed in both cumulative/total expression of the studied imprinted genes and that of the individual genes. The cumulative expression of 173 studied imprinted genes ranges from 0.08% (total blood) to 4.36% (bronchial epithelium) of the total gene expression (Table 3). In some samples (Table 3 and Supplementary Table 2), imprinted genes-associated proportion of the transcriptome is obviously above what is to be expected from such a limited group of genes, clearly reflecting the importance of the biological roles played by the latter. At the same time, overall expression of the imprinted genes was equal in the clusters of cancer tissues and normal tissue and cells (clusters C and N, 0.95% for both clusters) and lower for the cells cultured in vitro (cluster IV, 0.77%).

The current study apparently represents the first attempt to estimate an impact of imprinted genes on the total volume of the transcriptome. Obvious biases affect an accuracy of the algorithm applied, suggesting both underestimation (probable existence of yet unidentified imprinted genes, unavailable information on gene structure for some imprinted genes, absence of anchoring enzyme recognition sites for at least one gene) and overestimation (unconfirmed imprinting status of some of the candidate imprinted genes, SAGE tags matching more than one gene; see Table 1) of the relative size of the imprinted transcriptome. Despite this, provided data on the estimated cumulative/total expression of the known imprinted genes (their number well corresponding to the predicted number of imprinted genes in human genome [31, 32]) in a variety of tissues and cells is most interesting. Until now, little information was available on the overall expression of imprinted genes in the cells of different types. It is generally believed that many imprinted genes are highly expressed in the developing and adult brain tissue [33], placenta [34], and undifferentiated stem cells [35]. Discrete studies identify certain highly expressed imprinted genes as the potential biomarkers of cancer subtypes [36, 37]. In contrast, imprinted genes are known to be expressed on relatively low level in adult blood cells [38]. This information is supported by the observed values of the cumulative expression of the imprinted genes through the screened samples (Table 3 and Supplementary Table 2): cumulative expression of the imprinted genes is generally high in many assessed brain-derived samples and low in blood samples. It was also observed earlier that major upregulation of gene expression of the numerous imprinted genes is associated with early differentiation and development, rather than with undifferentiated status of stem cells [39, 40]. Concordantly, in the current study, all of the 13 SAGE libraries generated from undifferentiated embryonic stem cells (ESCs)—namely, lines HES3, HES4 [17, 23, 41], BG01, H1, H7, H9, H13, H14, HSF6 [17, 23]—uniformly demonstrate intermediate cumulative expression of the imprinted genes (Supplementary Table 2) and fit closely in the hierarchical tree built for the corresponding cluster (cluster IV; Figure 5(c)). However, many samples with high cumulative expression of the imprinted genes do not fit into any of the groups listed above. Important role of genomic imprinting in particular normal cell and cancer subtypes, suggested by high expression of these genes, thus should be a subject of the follow-up studies. Expression of individual imprinted genes varies to even further extent in the samples screened. Expression of the candidate imprinted gene even-skipped homeobox 1 (EVX1) was not detected in any sample submitted to the analysis, while the expression of many more (DUX2, FAM75D1, Q8NB05, FLJ20464, ISM1, FAM77D, and others) was detected only in a few samples, always on a minimal level. In contrast, further imprinted genes (NDUFA4, RPL22, Q8NE65, GNAS, PTPN14, RAB1B, and others) were expressed in the majority of the samples screened, often on high level (Supplementary Table 3).

Illustratively, a notable variation in the cumulative expression of the imprinted genes and in the expression of individual imprinted genes is observed in the cells cultured in vitro, including cells of the same type (e.g., numerous medulloblastoma, glioblastoma multiforme, and breast carcinoma cell lines) (Supplementary Table 2 and Figure 6). This observation further supports earlier suggestion that cell culture conditions contribute to the maintenance or alteration of the imprinted gene expression [42, 43].

Taken together, a screening of the normalized expression profiles of a comprehensive panel of the established and candidate imprinted genes within the publicly available human SAGE datasets was performed in the current study: the first to estimate a prevalence of imprinted genes within the total human transcriptome in a large scale. This paper thus provides a useful reference on the relative size of the imprinted transcriptome and on the expression of the individual imprinted genes.

Acknowledgments

This study was supported by the grants by The Ministry of Education and Science of the Russian Federation, Federal target program “Research and Pedagogical Cadre for Innovative Russia” for 2009–2013 (State Contract 14.740.11.0004) and by MCB Program, Russian Academy of Sciences. The author is grateful to all GEO database contributors.

References

J. McGrath and D. Solter, “Completion of mouse embryogenesis requires both the maternal and paternal genomes,” Cell, vol. 37, no. 1, pp. 179–183, 1984.

M. A. H. Surani, S. C. Barton, and M. L. Norris, “Development of reconstituted mouse eggs suggests imprinting of the genome during gametogenesis,” Nature, vol. 308, no. 5959, pp. 548–550, 1984.

M. S. Bartolomei, S. Zemel, and S. M. Tilghman, “Parental imprinting of the mouse H19 gene,” Nature, vol. 351, no. 6322, pp. 153–155, 1991.

D. P. Barlow, R. Stoger, B. G. Herrmann, K. Saito, and N. Schweifer, “The mouse insulin-like growth factor type-2 receptor is imprinted and closely linked to the Tme locus,” Nature, vol. 349, no. 6304, pp. 84–87, 1991.

T. M. DeChiara, E. J. Robertson, and A. Efstratiadis, “Parental imprinting of the mouse insulin-like growth factor II gene,” Cell, vol. 64, no. 4, pp. 849–859, 1991.

P. P. Luedi, F. S. Dietrich, J. R. Weidman, J. M. Bosko, R. L. Jirtle, and A. J. Hartemink, “Computational and experimental identification of novel human imprinted genes,” Genome Research, vol. 17, no. 12, pp. 1723–1730, 2007.

D. Lucifero, J. R. Chaillet, and J. M. Trasler, “Potential significance of genomic imprinting defects for reproduction and assisted reproductive technology,” Human Reproduction Update, vol. 10, no. 1, pp. 3–18, 2004.

I. M. Morison, J. P. Ramsay, and H. G. Spencer, “A census of mammalian imprinting,” Trends in Genetics, vol. 21, no. 8, pp. 457–465, 2005.

G. Moore and R. Oakey, “The role of imprinted genes in humans,” Genome Biology, vol. 12, no. 3, article 106, 2011.

W. Reik and J. Walter, “Genomic imprinting: parental influence on the genome,” Nature Reviews Genetics, vol. 2, no. 1, pp. 21–32, 2001.

V. E. Velculescu, L. Zhang, B. Vogelstein, and K. W. Kinzler, “Serial analysis of gene expression,” Science, vol. 270, no. 5235, pp. 484–487, 1995.

A. Lal, A. E. Lash, S. F. Altschul et al., “A public database for gene expression in human cancers,” Cancer Research, vol. 59, no. 21, pp. 5403–5407, 1999.

A. E. Lash, C. M. Tolstoshev, L. Wagner et al., “SAGEmap: a public gene expression resource,” Genome Research, vol. 10, no. 7, pp. 1051–1060, 2000.

A. H. C. van Kampen, J. M. Ruijter, B. D. S. van Schaik, et al., “Gene expression informatics and analysis,” in Bioinformatics for Geneticists, M. R. Barnes and I. C. Gray, Eds., pp. 319–344, John Wiley & Sons, Chichester, UK, 2003.

E. A. Gibb, E. A. Vucic, K. S. Enfield, et al., “Human cancer long non-coding RNA transcriptomes,” PLoS ONE, vol. 6, no. 10, Article ID e25915, 2011.

S. V. Anisimov, “Serial analysis of gene expression (SAGE): 13 years of application in research,” Current Pharmaceutical Biotechnology, vol. 9, no. 5, pp. 338–350, 2008.

K. Boon, E. C. Osório, S. F. Greenhut et al., “An anatomy of normal and malignant gene expression,” The Proceedings of the National Academy of Sciences of the United States of America, vol. 99, no. 17, pp. 11287–11292, 2002.

S. V. Anisimov, “A large-scale screening of the normalized mammalian mitochondrial gene expression profiles,” Genetical Research, vol. 86, no. 2, pp. 127–138, 2005.

O. U. Potapova, S. V. Anisimov, M. Gorospe, et al., “Targets of c-Jun NH2-terminal kinase 2-mediated tumor growth regulation revealed by serial analysis of gene expression,” Cancer Research, vol. 62, no. 11, pp. 3257–3263, 2002.

S. V. Anisimov and A. A. Sharov, “Incidence of “quasi-ditags” in catalogs generated by serial analysis of gene expression (SAGE),” BMC Bioinformatics, vol. 5, article 152, 2004.

E. Varlet-Marie, M. Audran, M. Ashenden, M. T. Sicart, and D. Piquemal, “Modification of gene expression: help to detect doping with erythropoiesis-stimulating agents,” American Journal of Hematology, vol. 84, no. 11, pp. 755–759, 2009.

K. M. Lonergan, R. Chari, R. J. DeLeeuw et al., “Identification of novel lung genes in bronchial epithelium by serial analysis of gene expression,” American Journal of Respiratory Cell and Molecular Biology, vol. 35, no. 6, pp. 651–661, 2006.

G. J. Riggins and R. L. Strausberg, “Genome and genetic resources from the cancer genome anatomy project,” Human Molecular Genetics, vol. 10, no. 7, pp. 663–667, 2001.

M. Allinen, R. Beroukhim, L. Cai et al., “Molecular characterization of the tumor microenvironment in breast cancer,” Cancer Cell, vol. 6, no. 1, pp. 17–32, 2004.

K. Boon, J. B. Edwards, C. G. Eberhart, and G. J. Riggins, “Identification of astrocytoma associated genes including cell surface markers,” BMC Cancer, vol. 4, article 39, 2004.

C. D. Hough, C. A. Sherman-Baust, E. S. Pizer et al., “Large-scale serial analysis of gene expression reveals genes differentially expressed in ovarian cancer,” Cancer Research, vol. 60, no. 22, pp. 6281–6287, 2000.

M. Fischer, A. Oberthuer, B. Brors et al., “Differential expression of neuronal genes defines subtypes of disseminated neuroblastoma with favorable and unfavorable outcome,” Clinical Cancer Research, vol. 12, no. 17, pp. 5118–5128, 2006.

D. Sharon, S. Blackshaw, C. L. Cepko, and T. P. Dryja, “Profile of the genes expressed in the human peripheral retina, macula, and retinal pigment epithelium determined through serial analysis of gene expression (SAGE),” The Proceedings of the National Academy of Sciences of the United States of America, vol. 99, no. 1, pp. 315–320, 2002.

C. B. Rickman, J. N. Ebright, Z. J. Zavodni et al., “Defining the human macula transcriptome and candidate retinal disease genes using EyeSAGE,” Investigative Ophthalmology and Visual Science, vol. 47, no. 6, pp. 2305–2316, 2006.

A. Zhang, D. A. Skaar, Y. Li, et al., “Novel retrotransposed imprinted locus identified at human 6p25,” Nucleic Acids Research, vol. 39, no. 11, pp. 5388–5400, 2011.

A. I. Diplas, L. Lambertini, M. J. Lee et al., “Differential expression of imprinted genes in normal and IUGR human placentas,” Epigenetics, vol. 4, no. 4, pp. 235–240, 2009.

A. Henckel and P. Arnaud, “Genome-wide identification of new imprinted genes,” Briefings in Functional Genomics and Proteomics, vol. 9, no. 4, Article ID elq016, pp. 304–314, 2010.

W. Davies, A. R. Isles, and L. S. Wilkinson, “Imprinted gene expression in the brain,” Neuroscience and Biobehavioral Reviews, vol. 29, no. 3, pp. 421–430, 2005.

D. Haig, “Genomic imprinting and kinship: how good is the evidence?” Annual Review of Genetics, vol. 38, pp. 553–585, 2004.

B. W. Sun, A. C. Yang, Y. Feng et al., “Temporal and parental-specific expression of imprinted genes in a newly derived Chinese human embryonic stem cell line and embryoid bodies,” Human Molecular Genetics, vol. 15, no. 1, pp. 65–75, 2006.

I. Ariel, O. Lustig, T. Schneider et al., “The imprinted H19 gene as a tumor marker in bladder carcinoma,” Urology, vol. 45, no. 2, pp. 335–338, 1995.

M. J. Cooper, M. Fischer, D. Komitowski et al., “Developmentally imprinted genes as markers for bladder tumor progression,” Journal of Urology, vol. 155, no. 6, pp. 2120–2127, 1996.

J. M. Frost, D. Monk, T. Stojilkovic-Mikic et al., “Evaluation of allelic expression of imprinted genes in adult human blood,” PLoS ONE, vol. 5, no. 10, Article ID e13556, 2010.

S. V. Anisimov, K. V. Tarasov, D. Riordon, A. M. Wobus, and K. R. Boheler, “SAGE identification of differentiation responsive genes in P19 embryonic cells induced to form cardiomyocytes in vitro,” Mechanisms of Development, vol. 117, no. 1-2, pp. 25–74, 2002.

J. C. Lui, G. P. Finkielstain, K. M. Barnes, and J. Baron, “An imprinted gene network that controls mammalian somatic growth is down-regulated during postnatal growth deceleration in multiple organs,” American Journal of Physiology—Regulatory Integrative and Comparative Physiology, vol. 295, no. 1, pp. R189–R196, 2008.

M. Richards, S. P. Tan, J. H. Tan, W. K. Chan, and A. Bongso, “The transcriptome profile of human embryonic stem cells as defined by SAGE,” Stem Cells, vol. 22, no. 1, pp. 51–64, 2004.

K. P. Kim, A. Thurston, C. Mummery et al., “Gene-specific vulnerability to imprinting variability in human embryonic stem cell lines,” Genome Research, vol. 17, no. 12, pp. 1731–1742, 2007.

J. M. Frost, D. Monk, D. Moschidou et al., “The effects of culture on genomic imprinting profiles in human embryonic and fetal mesenchymal stem cells,” Epigenetics, vol. 6, no. 1, pp. 52–62, 2011.