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. 2011 Mar 2;6(3):e17125. doi: 10.1371/journal.pone.0017125

Ontogenetic De Novo Copy Number Variations (CNVs) as a Source of Genetic Individuality: Studies on Two Families with MZD Twins for Schizophrenia

Sujit Maiti 1, Kiran Halagur Bhoge Gowda Kumar 1, Christina A Castellani 1, Richard O'Reilly 2, Shiva M Singh 1,2,*
Editor: Branden Nelson3
PMCID: PMC3047561  PMID: 21399695

Abstract

Genetic individuality is the foundation of personalized medicine, yet its determinants are currently poorly understood. One issue is the difference between monozygotic twins that are assumed identical and have been extensively used in genetic studies for decades [1]. Here, we report genome-wide alterations in two nuclear families each with a pair of monozygotic twins discordant for schizophrenia evaluated by the Affymetrix 6.0 human SNP array. The data analysis includes characterization of copy number variations (CNVs) and single nucleotide polymorphism (SNPs). The results have identified genomic differences between twin pairs and a set of new provisional schizophrenia genes. Samples were found to have between 35 and 65 CNVs per individual. The majority of CNVs (∼80%) represented gains. In addition, ∼10% of the CNVs were de novo (not present in parents), of these, 30% arose during parental meiosis and 70% arose during developmental mitosis. We also observed SNPs in the twins that were absent from both parents. These constituted 0.12% of all SNPs seen in the twins. In 65% of cases these SNPs arose during meiosis compared to 35% during mitosis. The developmental mitotic origin of most CNVs that may lead to MZ twin discordance may also cause tissue differences within individuals during a single pregnancy and generate a high frequency of mosaics in the population. The results argue for enduring genome-wide changes during cellular transmission, often ignored in most genetic analyses.

Introduction

Genome-wide constancy and change underlies evolution and familial inheritance but remains ill-defined. An assessment of changes as the genome is passed on from one generation (meiosis) and developmental cycle (mitosis) to the next is needed. It directly contributes to the sum of genetic individuality. At present, these inquiries are difficult [2], and require the development of new quantitative methods to assess genome-wide changes and their significance. This report assesses two common measures of genomic variation: copy number variations and (CNVs) and single nucleotide polymorphism (SNPs) across a generation and between monozygotic twins in two exceptional families. The results offer novel insight into meiotic and mitotic sources of variation, which results in genetic individuality between MZ twins. This individuality may account for discordance in monozygotic twins for a variety of diseases including schizophrenia.

CNVs are structural variants that are both frequent and relevant and may range in size in humans from 1 Kb to several Mb [3]. Given their impact on physiology and function, CNVs have a major influence on evolution and gene expression and on normal and disease related variation [3]. CNVs include duplications and deletions leading to a departure from the classic view that all autosomal genes are present in two copies, with one allele inherited from each parent. The majority of CNVs are copy number polymorphisms (CNPs), existing in a frequency that is greater than 1% and transmitted across generations. However, a small proportion of CNVs are novel events. CNVs may account for a major fraction (∼12%) of the genome, but appear to concentrate in some genomic regions depending on the sequence features [4], [5]. Unlike CNVs, SNPs are relatively small changes, usually involving replacement of a nucleotide with another. SNPs are common and distributed across the entire human genome. Individual SNPs mark a unique genomic location, and are usually neutral in nature. In other cases, they may change amino-acids, cause protein truncation or affect expression. They are easily detected, and have been extensively exploited in genetic analysis including the cloning of disease causing genes, individual identification and establishment of genetic relatedness.

Studies on these two genome-wide variations (SNPs and CNVs) have greatly enhanced our understanding of evolution and genetic individuality. They are also helping to elucidate the cause of genetic, and genomic disorders including schizophrenia [6]. A number of SNPs appear to be linked to this complex neuro-developmental disease, which has a heritability estimate of 80%. However, results of linkage studies have not been consistently reproducible [7], [8]. Individuals affected with schizophrenia (SCZ) have shown an elevated incidence of CNVs [9] and a few rare CNVs appear to have a major effect on the development of SCZ [10]. However, these CNVs account for only a small fraction of schizophrenia cases [11] and the challenge of identifying common genetic cause(s) of SCZ remains. The search for genes in SCZ currently relies on large number of patients and matched controls. The limited progress using these approaches emphasizes the need to pursue alternative approaches. Future studies may benefit from inclusion of two features. The first is a genome-wide comparison of the parents and their progeny affected by SCZ and the second is the assessment of genomes of monozygotic twins (that show ∼52% discordance for SCZ) [12], [13]. The current study reports genome-wide CNV and SNP results on two exceptional families that include monozygotic twins discordant for schizophrenia (Figure 1, Table 1).

Figure 1. Pedigree of two families with monozygotic twins discordant for schizophrenia.

Figure 1

Members of the family one are indicated with (I-) and members of the family two are indicated with (II-). The designations included in this figure are followed in subsequent figures and tables.

Table 1. Demography and Clinical History.

Family 1 Family 2
I-1-1 I-1-2 I-2-1 I-2-2 II-1-1 II-1-2 II-2-1 II-2-2
Age (yr.) at assessment 82 74 53 53 N/A N/A 43 43
Sex Male Female Female Female Male Female Female Female
Declared Race Afro-American Caucasian
Psychiatric features Compulsive Personality Disorder N/A Schizophrenia, Paranoid Type, onset age 22 Bipolar I Disorder, onset age 52 Major depression and panic disorder for 6 months after cardiac surgery, onset age 73 N/A Schizoaffective Disorder, onset age 27 Single episode of Major Depression, fully remitted, onset age 18

Demography and Clinical History of monozygotic (MZ) twins discordant for Schizophrenia (SCZ). Family one is indicated with (I), family two is indicated with (II). N/A = Not Applicable.

Results and Discussion

Familial Distribution of CNVs

The number of CNVs per individual ranged from 35 to 65, with the exception of one individual who is described more fully later (Table 2). This is similar to the number of CNVs per subject reported from most other studies that have used Affymetrix 6.0 Human SNP arrays [14]. The range is also comparable with the number of CNVs found in Venter's genome (62) based on his complete genome sequence [15]. The exception in our study was the father in family 2 (II-1-1) who was found to harbour a rare chromosome 13q deletion containing 40 CNVs at a single genomic location. Although this finding is beyond the scope of this report, it is important to note that II-1-1 underwent chemotherapy treatment and that the samples utilized in this study were obtained towards the end of that treatment. Most CNVs identified were in the range of 100 to 200 Kb, consistent with the size distribution of CNVs reported in the literature [14]. The majority of CNVs observed (Table 3) were copy number gains (78.5%) and ∼10% of the CNVs identified are not listed in the Database of Genomic Variants (http://projects.tcag.ca/variation/) accessed on 8.2.2010. Further, the chromosomal distribution of CNVs was comparable across individuals with the exception of the father in family 2 who had consistently higher CNVs affecting most chromosomes (Table 4). Of the CNVs identified, >50 per cent overlapped RefSeq genes. The identified genes are frequently associated with metabolic pathways such as starch and sucrose metabolism as well as pathways involved in the metabolism of amino acids, for example, , phenylalanine, histidine and tyrosine (AMY2A,AMY1A,ALDH1L1,PSMC1). Structurally, >67% of the CNVs identified were flanked at both the 5′and 3′ end or at just the 5′ (>7%) or 3′ (>8%) end with a set of common repeats, represented by short interspersed nucleotide elements (SINEs), long interspersed nucleotide elements (LINEs), long terminal repeats (LTRs) and low copy repeats (LCRs) near the breakpoints. The majority of the deletion breakpoints had 1–30 bp of microhomology, whereas a small fraction of deletion breakpoints contained inserted sequences. The co-occurrence of microhomology and inserted sequence suggests that both recombination and replication based mutational mechanisms are operational in CNV generation. Recent studies have identified short DNA motifs that both determine the location of meiotic crossover hotspots and are significantly enriched at the breakpoints of recurrent non-allelic homologous recombination (NAHR) syndromes [16]. We found evidence for this mechanism in a subset of the breakpoint events (data not shown). This was true for the de novo (Figure 2a) as well as inherited (Figure 2b) CNVs. Such sequences may represent genomic architecture that is prone to genome instability by a predisposition to genomic rearrangements via non-homologous end joining (NHEJ), template switching and/or non-allelic homologous recombination (NAHR).

Table 2. Distribution of CNV among family members according to size.

CNV Size Family 1 Family 2
I-1-1 I-1-2 I-2-1 I-2-2 II-1-1 II-1-2 II-2-1 II-2-2
< = 100 kb 0 0 0 0 2 0 0 1
>100 to 200 kb 17 18 15 20 119 50 24 24
>200 to 300 kb 11 6 4 10 25 6 13 9
>300 to 400 kb 5 5 6 5 11 3 1 4
>400 to 500 kb 2 0 2 2 6 1 1 2
>500 to 1000 kb 6 2 4 7 7 2 5 2
>1 to 10 Mb 9 4 5 3 5 2 4 5
>10 to 20 Mb 5 0 0 0 0 0 0 0
>20 Mb 3 0 0 0 2 0 2 2
Total 58 35 36 47 177 64 50 49

Numerical values in each cell of the table indicate how many CNVs of that particular size range were observed in that particular individual.

Table 3. Identity of copy number variants across individual family members.

CNVs Family 1 Family 2
I-1-1 I-1-2 I-2-1 I-2-2 II-1-1 II-1-2 II-2-1 II-2-2
No. of Loss 21 6 5 6 52 11 6 4
No. of Gain 37 29 31 41 125 53 44 45
Novel (absent in DGV) 1 1 0 2 42 6 1 0
Present in DGV 57 34 36 45 135 58 49 49
Total (for the individual) 58 35 36 47 177 64 50 49

Frequency of CNVs which are losses (deletion) or gains (duplication) and characterization as present or absent from The Database of Genomic Variants (DGV).

Table 4. Chromosome wise distribution of CNV.

Chr No. Family 1 Family 2
I-1-1 I-1-2 I-2-1 I-2-2 II-1-1 II-1-2 II-2-1 II-2-2
1 4 2 2 2 11 2 6 6
2 4 2 5 5 11 2 2 3
3 1 4 2 3 7 4 4 2
4 4 3 2 4 8 1 3 2
5 0 0 0 0 12 0 2 1
6 0 0 0 0 10 2 0 0
7 2 6 3 4 10 5 3 4
8 1 0 3 3 7 3 3 3
9 1 1 2 3 4 4 3 4
10 2 1 1 1 3 5 1 1
11 3 1 2 1 5 1 2 2
12 0 1 0 1 4 3 0 1
13 0 0 0 0 40 1 1 0
14 4 6 3 5 4 6 5 3
15 4 3 1 3 2 6 6 8
16 2 1 2 3 9 1 1 1
17 4 1 2 3 8 2 2 1
18 0 0 0 0 1 0 0 1
19 0 1 0 0 7 3 2 1
20 0 0 0 0 0 0 0 1
21 1 2 2 3 2 3 2 1
22 3 0 3 2 3 1 1 1
X 18 0 1 1 9 9 1 2
Total 58 35 36 47 177 64 50 49

Chromosome specific distribution of de novo (present in twin(s) and not in parents) and inherited (present in at least one parent) CNVs in family 1 and family 2.

Chr. No = Chromosome number.

Figure 2. Distribution of repeat elements 1 kb upstream (5′) and 1 kb downstream (3′) of the de novo (2a) and inherited (2b) CNVs across eight individuals.

Figure 2

These include LINE (blue), SINE (purple), LTR (yellow), Satellite (sky blue), simple repeats (black) and low complexity repeats (green) with numerical values on top of the bars representing percentage of that repeat.

Familial vs de novo Origin of CNVs

A novel feature of the data included in this report is that we are able to classify observed CNVs into two groups based on their absence or presence in one of the parents. CNVs that were found in one or both twins and not seen in either parent, were classified as de novo. If a de novo CNV was present in both twins, it was considered to have originated during parental meiosis and when present in only one of the two twins, it was assumed to have originated in mitosis during development. This classification allowed us to identify 14 and 26 de novo CNVs in family 1 (Table 5) and family 2 (Table 6) respectively. The table includes genomic locations as well as individual specific break points which allow for the assessment of regions of overlap with the Database of Genomic Variants (Toronto, Ontario). Mitotic origin of CNVs was ∼3 times higher than CNVs generated during parental meiosis. Of the mitotic de novo CNVs identified two (loss at 14q32.11 as well as loss at 8q11.21) were specific to the schizophrenia patient in family 1 and one (gain at 19q13.41) was specific to the patient in family 2. Such results are novel in the literature. Further, it is enticing to ask the question, do the genes disturbed by CNVs contribute to the development of their disease symptoms? Although the answers to such questions are of paramount importance, the results available do not offer a direct assessment of such questions. Nonetheless, it is appropriate to entertain the discussion that the known features of these genes are or are not compatible with disturbances observed in schizophrenia, which is discussed below.

Table 5. de novo CNVs in Family 1.

Sl. No Location Family 1 Status Meiosis Mitosis Novel Genes (Overlapping or Nearby) SD
I-2-1 Size (kb) Breakpoints I-2-2 Size (kb) Breakpoints
1 1p36.13 Yes 112 16724089…16835888 Gain Yes NBPF1, NBPF10 1
2 2p25.3 Yes 152 1407209…1559511 Yes 152 1407209…1559511 Gain Yes TPO 0
3 2p11.2 Yes 1147 89862331…91008912 Yes 1159 89850279…91008912 Loss Yes 0
4 4q28.3 Yes 191 132801221…132992517 Gain Yes 1
5 7q11.21 Yes 118 64706066…64823721 Yes 118 64704377…64822216 Loss Yes 1
6 8p23.1 Yes 126 7847289…7973253 Loss Yes 1
7 8q11.1 Yes 336 47045602…47381308 Yes 250 47131383…47381308 Gain Yes 0
8 8q11.21 Yes 154 48178242…48332398 Loss Yes Yes KIAA0146 0
9 9p11.2 Yes 569 45361389…45929992 Gain Yes FAM27A 1
10 9p13.1 Yes 141 38777481…38918566 Gain Yes 1
11 9q12 Yes 861 65412415…66273526 Gain Yes 1
12 12p13.31 Yes 196 8303317…8499801 Gain Yes CLEC6A 1
13 14q32.11 Yes 103 89780137…89883415 Loss Yes Yes PSMC1, C14orf102 0
14 21q11.2 Yes 119 13891136…14009908 Gain Yes ANKRD21, LOC441956 1
15 Xp11.23 Yes 149 47917899…48066856 Yes 149 47917899…48066856 Gain Yes SSX5, SSX1, SSX9 0

Table 6. de novo CNVs in Family 2.

Sl. No Location Family 2 Status Meiosis Mitosis Novel Genes (Overlapping or Nearby) SD
II-2-1 Size (kb) Breakpoints II-2-2 Size (kb) Breakpoints
1 1q21.1 Yes 120 143867807…143987616 Gain Yes NOTCH2NL 0
2 1q21.1 Yes 104 147353175…147456930 Yes 104 147353175…147456930 Loss Yes 0
3 1q43 Yes 119 241230453…241349107 Gain Yes 0
4 3q21.2 Yes 155 126958012…127112518 Gain Yes 1
5 4p11 Yes 299 48986100…49285347 Gain Yes 0
6 5p15.33 Yes 101 770367…871743 Yes 107 770367…877436 Gain Yes ZDHHC11 1
7 5p13.3 Yes 151 34119387…34269887 Gain Yes 1
8 7q11.21 Yes 202 61761008…61962936 Gain Yes 0
9 7q11.21 Yes 116 64588316…64704125 Yes 125 64579322…64704125 Gain Yes 1
10 7q35 Yes 100 142956516…143056637 Gain Yes LOC441294, FAM139A 1
11 8p23.1 Yes 220 12071704…12291845 Yes 220 12071704…12291845 Gain Yes FAM86B1, DEFB130 0
12 9p12 Yes 2720 41465094…44184864 Yes 1901 42249132…44149779 Gain Yes ANKRD20A2, ANKRD20A3, FOXD4L4, FOXD4L2 1
13 9q12 Yes 250 67416254…67665974 Gain Yes ANKRD20A1, ANKRD20A3 1
14 11q13.2 Yes 267 67239223…67505822 Yes 139 67239223…67378031 Gain Yes 1
15 12p13.31 Yes 189 8310909…8499801 Gain Yes 1
16 13q11 Yes 208 18138676…18346383 Gain Yes 1
17 14q11.1 Yes 601 18072112…18672662 Yes 601 18072112…18672662 Gain Yes OR11H12, ACTBL1 1
18 15q11.1 Yes 106 18276329…18382609 Gain Yes 1
19 15q11.2 Yes 203 19882763…20085783 Yes 221 19864583…20085783 Gain Yes OR4M2, OR4N4, LOC650137 1
20 15q13.1 Yes 227 26808083…27035216 Gain Yes APBA2 0
21 15q13.2 Yes 110 28452853…28563274 Gain Yes CHRFAM7A 1
22 17p11.1 Yes 199 22127012…22326425 Gain Yes 0
23 19q13.41 Yes 109 58847652…58957090 Gain Yes Yes ZNF331, DPRX 0
24 20q11.1 Yes 118 28147331…28264860 Gain Yes 1
25 21p11.2 Yes 3480 10106540…13586186 Yes 3814 9758730…13572586 Gain Yes BAGE2, BAGE4, BAGE 0

Identity of de novo CNVs found in Family 1 (5a) and Family 2 (5b) and the gene regions (overlapping or nearby). De novo CNVs are defined as those that are present in either or both twins but not found in parents. SD displays the percentage of overlap with segmental duplications, ‘0’ indicates no overlap between the CNV and segmental duplication and ‘1’ indicates 90–100% overlap. The table includes genomic locations as well as twin specific breakpoints which allow for the assessment of regions of overlap with the Database of Genomic Variants (Toronto, Ontario). SI No. = Serial number. Novel indicates a CNV which is not present in The Database of Genomic Variants (DGV).

De novo CNVs and Schizophrenia

The genes overlapping disease specific de novo CNVs in family 1 included PSMC1 (proteasome 26S subunit, ATPase, 1) and C14orf102 (chromosome 14 open reading frame 102 gene) on 14q32.11 and KIAA0146 on 8q11.21. PSMC1 (MIM 602706) is an ATP-dependent protease [17] that may include protein ubiquitination in response to DNA damage [18]. It is composed of a 20S catalytic proteasome and 2 PA700 regulatory modules and contains an AAA (ATPases associated with diverse cellular activities) domain [17]. The human and mouse proteins are 99% identical [19] and may play a significant role in ubiquitin-mediated proteasomal proteolysis in the molecular pathogenesis of neurological diseases such as spinocerebellar ataxia type 7 (SCA7). Also, several studies (for review, see [20], [21]), have indicated that the genes related to ubiquitination are altered in the brains of patients with schizophrenia. Further, this CNV also affects another gene (C14orf102; chromosome 14 open reading frame 102) which is conserved across phyla and highly expressed in the brain (Affymetrix GNF Expression Atlas 2 Data). The other CNV affected in this patient of family 1 represents a loss at 8q11.21, that contains the still uncharacterized gene, KIAA0146, which is expressed in the brain, may contain a CAG repeat and is conserved in chimpanzee, dog, cow, mouse, rat, chicken, and zebra fish. It is a transcription factor with CCAAT enhancer binding protein (CEBP) function [22]. Further the gene is highly expressed in the brain and hippocampus that may implicate it in mental disorders (www.genecards.org). Although we cannot rule out a role for these three genes (PSMC1, C14orf102 and KIAA0146) in schizophrenia, such conclusions would be premature. Only a follow up study will establish if any of the three genes directly contribute to the development of schizophrenia in the patient from family 1. A similar analysis of CNVs in family 2 has identified a 109 kb gain at 19q13.41 that is specific to the schizophrenia patient in family 2. Translocations involving 19q13 are a frequent finding in follicular adenomas of the thyroid and may represent the most frequent type of structural aberration in human epithelial tumors [23]. The CNV identified in this region contains two genes; DPRX1 and ZNF331. DPRX1 (divergent-paired related homeobox) is a member of the DPRX homeobox gene family, contains a single conserved homeodomain and may function as a putative transcription factor. It may bind a promoter or enhancer sequence or interact with a DNA binding transcription factor and is involved in early embryonic development and cell differentiation [24]. The drosophila homologue of the DPRX1 gene (dPrx5; Drosophila peroxiredoxin 5) confers protection against oxidative stress, apoptosis and also promotes longevity [25]. The next gene, ZNF331(zinc finger protein 331) affected by this CNV is also involved in DNA-dependent regulation of transcription as a transcriptional repressor [26]. Interestingly, it is one of the imprinted genes that exhibits monoallelic expression in a parent-of-origin specific manner [27]. Imprinted genes are important for development and behaviour and disruption of their expression is associated with many human disorders [28]. In conclusion the three genes affected in the schizophrenia patient in family 1 (PSMC1, C14orf102, KIAA0146) and the two genes affected in the patient of family 2 (DPRX1 and ZNF331) could not be excluded from their potential involvement in the development of schizophrenia in the two patients. If applicable, the biological systems affected in the two patients is hypothesized to be different. The patient in family one is hypothesized to have a ubiquitin-mediated proteasomal proteolysis while the patient of family 2 could have errors in regulatory mechanisms affecting gene regulation. Such conclusions must remain hypothetical until proven by independent supporting evidence.

De novo changes may lead to mosaicism

The genotypes generated by the Affymetrix 6.0 array have also allowed us to establish that ∼0.12% (1086 and 1022 in twin pair 1 and 2 respectively; 11 substitutions shared by both pairs) of the SNPs in the twins represented de novo substitutions, but unlike CNVs, (that primarily originated during ontogeny in mitosis) most (63–65%) originated during parental meiosis. These results suggest that DNA replication fidelity at the level of single base pairs (SNPs) vs replication forks (CNVs) is differentially exercised during meiosis and mitosis. The single base pairing is much more stringent in mitosis (evolved to produce identical daughter cells), compared to meiosis where errors can facilitate potentially beneficial variations. In contrast, CNVs which affect the phenotype may be advantageous when occurring during mitosis and selected for during development. Thus, cell type specific CNVs may play a role in growth and development, offering advantageous variability. This would mean that most individuals are mosaics [29]: a hypothesis that is difficult to assess and evaluate. It is likely that the ratio of mosaic cells may be maintained throughout the differentiated (ectoderm, mesoderm, endoderm, etc) tissues over the lifetime [30], [31]; an exception being when other factors are directly influencing DNA stability. Such a mechanism may generate genomic differences and differential mosaicism in most or all individuals. If this is the case, it will complicate traditional genetic analysis that assumes stability of the genome with rare exceptions.

We have been able to establish genome-wide (CNVs and SNPs) discordance for MZ twin pairs. Also, given that the twins are discordant for schizophrenia, it is possible to assign provisional CNVs (and genes) as well as substitutions (SNPs) that may be associated with the disease status of the affected twins in family 1 and family 2 (Table 7,8). Similarly, we identified substitutions (SNPs) that were different between the affected and unaffected member of the two sets of twins including their distribution along the chromosomes, introns and exons and the predicted effect on the gene product. Identity of de novo CNVs found in Family 1 (Table 5) and Family 2 (Table 6) and the gene regions which they overlap was reported. De novo CNVs are defined as those that are present in either twin but not found in parents. In the tables, SD indicates the percentage of overlap between segmental duplications and the CNVs, ‘0’ means there is no overlap between CNV and segmental duplication and ‘1’ means 90–100% overlap.

Table 7. Inherited CNVs in Family 1.

Sl. No Location Family 1 Status Novel Genes (Overlapping or Nearby) SD
I-1-1 Size(kb) Breakpoints I-1-2 Size(kb) Breakpoints I-2-1 Size(kb) Breakpoints I-2-2 Size(kb) Breakpoints
1 1p36.33 Yes 167 51586…218557 Yes 707 51586…758644 Yes 707 51586…758644 Gain OR4F5, OR4F3, OR4F16, OR4F29 1
2 1q21.1 Yes 765 147303136…148068045 Yes 734 147311699…148045353 Yes 577 147381253…147958358 Gain PPIAL4, FCGR1A, HIST2H2BF 1
3 2p11.2 Yes 338 88917155…89254935 Yes 322 88914734…89236978 Yes 325 88917155…89242149 Yes 327 88914734…89242149 Gain 1
4 2p11.1 Yes 138 91017077…91154841 Yes 143 91017077…91160399 Yes 137 91017077…91154463 Gain 1
5 2q21.2 Yes 236 132597824…132833718 Yes 222 132597824…132819911 Yes 222 132597824…132819911 Gain 1
6 3p12.3 Yes 306 75677859…75984129 Yes 380 75597086…75977210 Yes 182 75583442…75764996 Yes 402 75582277…75984129 Gain 1
7 3q21.2 Yes 132 126907150…127039328 Yes 185 126907150…127091652 Gain 1
8 3q21.3 Yes 170 131198515…131368353 Yes 166 131213377…131379054 Yes 176 131214431…131389948 Gain 1
9 4p16.2 Yes 196 4040542…4236511 Yes 363 3873500…4236511 Yes 366 3870638…4236511 Gain 0
10 4p11 Yes 436 48849363…49285347 Yes 497 48788531…49285347 Yes 497 48788531…49285347 Gain 1
11 4q35.2 Yes 232 191021837…191254119 Yes 195 191059369…191254119 Yes 223 191031042…191254119 Gain FRG1, TUBB4Q, FRG2, DUX4 0
12 7p11.1 Yes 231 57523223…57753919 Yes 101 57640100…57741512 Yes 315 57640100…57954861 Yes 117 57640100…57757406 Gain 1
13 7q11.21 Yes 112 61365830…61477958 Yes 111 61365830…61476918 Gain 0
14 7q11.21 Yes 253 64320173…64573380 Yes 415 64204380…64619667 Yes 385 64204380…64589253 Loss ZNF92 0
15 8p23.1 Yes 694 7209579…7903560 Yes 215 7027251…7242508 Yes 270 7021193…7291135 Loss DEFB103A, DEFB103B, SPAG11B, DEFB104B, DEFB104A, DEFB106B, DEFB106A, DEFB105B, DEFB105A, DEFB107B, DEFB107A, SPAG11A, DEFB4 2
16 9q12 Yes 690 68115006…68805366 Yes 1141 68115006…69256300 Yes 694 68115006…68809437 Gain FOXD4L6, CBWD6, ANKRD20A4, CCDC29 1
17 10q11.1 Yes 183 41972779…42155347 Yes 105 41934430…42039743 Yes 183 41972779…42155347 Yes 239 41934430…42173117 Gain 1
18 11p15.4 Yes 175 3405799…3580813 Yes 131 3430789…3561991 Yes 139 3430789…3569305 Yes 156 3406002…3561991 Gain 1
19 11q13.2 Yes 227 67239223…67466368 Yes 193 67273413…67466368 Gain 1
20 14q11.1 Yes 1322 18138794…19460382 Yes 1103 18072112…19175240 Yes 705 18072112…18776746 Yes 705 18072112…18776746 Gain OR11H12, ACTBL1, OR4Q3, OR4M1, OR4N2, OR4K5 0
21 14q32.33 Yes 126 105265510…105391419 Yes 167 105100670…105268160 Yes 632 105190672…105822317 Yes 181 105149735…105331052 Gain 0
Yes 156 105413825…105569826 Yes 213 105289618…105502685 Yes 178 105827891…106005581 Yes 261 105341035…105601720 Gain 0
Yes 205 105612786…105818132 Yes 279 105508896…105788389 Yes 280 105612786…105892769 Gain 0
22 15q11.1 Yes 471 18370252…18841457 Yes 178 18522238…18700540 Yes 1223 18845990…20068512 Yes 562 18276329…18838423 Gain LOC283755, POTE15, OR4M2 1
Yes 1177 18845990…20022565 Yes 344 18845990…19189673 Yes 1078 18845990…19923712 Gain OR4N4, LOC650137 1
Yes 264 19303160…19566863 Gain 1
23 15q11.2 Yes 189 22026287…22214843 Yes 174 22026287…22200408 Gain 1
24 16p11.2 Yes 1217 32303108…33520394 Yes 1297 32538757…33836128 Yes 1142 32538757…33680554 Yes 249 32538757…32787273 Gain LOC729355, TP53TG3 1
Yes 752 32910319…33662480 Gain 1
25 16p11.2 Yes 250 34374795…34624994 Yes 249 34375533…34624994 Yes 249 34375533…34624994 Gain 1
26 17p11.2 Yes 140 20559979…20700133 Yes 164 20538867…20703365 Gain 1
27 17q21.31 Yes 229 41521621…41750183 Yes 123 41521621…41644356 Yes 123 41521621…41644356 Gain KIAA1267, LRRC37A 0
28 17q21.31 Yes 351 41756820…42107467 Yes 296 41811739…42107467 Yes 392 41700624…42092926 Yes 302 41700624…42002447 Gain/Loss ARL17, LRRC37A2, NSF 1
29 21p11.2 Yes 204 9758730…9962501 Yes 204 9758730…9962501 Yes 204 9758730…9962501 Gain TPTE 0
30 21p11.1 Yes 3411 10106540…13517603 Yes 3419 10106540…13525448 Yes 3419 10106540…13525448 Yes 3477 10106540…13583117 Gain BAGE2, BAGE4, BAGE 2
31 22q11.1 Yes 339 14435171…14774593 Yes 320 14435207…14754960 Yes 320 14435207…14754960 Gain ACTBL1 1
32 22q11.21 Yes 124 20051708…20175282 Yes 136 20145854…20281562 Yes 136 20145854…20281562 Gain HIC2, UBE2L3 1
33 22q11.22 Yes 240 21292462…21532509 Yes 127 21327799…21454509 Gain GGTL4 0

Table 8. Inherited CNVs in Family 2.

Sl. No Location Family 2 Status Novel Genes (Overlapping or Nearby) SD
II-1-1 Size(kb) Breakpoints II-1-2 Size(kb) Breakpoints II-2-1 Size(kb) Breakpoints II-2-2 Size(kb) Breakpoints
1 1p36.33 Yes 707 51586…758644 Yes 537 218557…755132 Gain OR4F5, OR4F3, OR4F16, OR4F29 1
2 1p36.13 Yes 117 16718622…16835888 Yes 167 16718622…16885360 Yes 345 16718622…17063437 Gain NBPF1, NBPF10 1
3 1p21.1 Yes 130 103910749…104041200 Yes 127 103931691…104058426 Gain AMY2B, AMY2A, AMY1A, AMY1C, AMY1B 1
4 1p11.2 Yes 21680 121045307…142725034 Yes 21725 121045307…142770353 Yes 21725 121045307…142770353 Gain 0
5 1q23.3 Yes 121 159775403…159896554 Yes 116 159780383…159896554 Yes 121 159775403…159896554 Loss FCGR3A, FCGR2C, FCGR3B 1
6 2p11.2 Yes 401 88925215…89326446 Yes 759 88914227…89673147 Yes 935 88926972…89861763 Yes 450 88914734…89365010 Gain 1
7 2p11.1 Yes 160 91017077…91176948 Yes 268 91017077…91285520 Yes 1275 89879561…91154463 Gain 1
8 2q21.2 Yes 260 132593436…132853218 Yes 183 132597824…132780848 Yes 222 132597824…132819911 Gain 1
9 3p12.3 Yes 260 75583442…75843060 Yes 226 75538978…75764996 Yes 260 75583442…75843060 Yes 182 75583442…75764996 Gain 1
10 3q12.2 Yes 108 101822746…101930873 Yes 102 101822746…101925168 Gain GPR128, TFG 0
11 3q21.3 Yes 141 131198817…131339424 Yes 195 131194669…131389948 Yes 199 131198515…131397648 Gain 1
12 4p16.2 Yes 407 3870638…4278016 Yes 180 3964803…4144453 Yes 366 3870638…4236511 Yes 357 3870638…4227503 Gain OTOP1 0
13 4q35.2 Yes 200 191053845…191254119 Yes 226 191028537…191254119 Yes 158 191052245…191210542 Gain FRG1, TUBB4Q, FRG2, DUX4 0
14 7p22.1 Yes 157 6838697…6995298 Yes 155 6840798…6995298 Gain 1
15 7p11.1 Yes 117 57640100…57757406 Yes 114 57640100…57753919 Yes 149 57604989…57753919 Yes 123 57597399…57720623 Gain 1
16 8p23.1 Yes 203 12415742…12618442 Yes 199 12415742…12614748 Yes 136 12415742…12551430 Gain 1
17 8p11.23 Yes 139 39349470…39488053 Yes 151 39354748…39506110 Yes 133 39354748…39488053 Yes 151 39354748…39506110 Loss 0
18 9p11.2 Yes 21937 44336683…66273526 Yes 21015 45258754…66273526 Yes 21015 45258754…66273526 Gain FAM27A, FAM75A7 0
9q12 Yes 861 68352238…69213455 Yes 103 68115006…68218485 Yes 1180 68076544…69256300 Yes 1099 68115006…69213671 Gain FOXD4L6, CBWD6, ANKRD20A4, CCDC29 1
Yes 457 68352238…68809437 Gain
19 10q11.1 Yes 129 41974796…42103488 Yes 236 41934430…42170853 Yes 105 41934430…42039743 Yes 239 41934430…42173117 Gain 1
20 11p15.4 Yes 206 3383178…3588946 Yes 205 3376078…3580813 Yes 131 3430789…3561991 Gain 1
21 14q11.2 Yes 186 21602854…21788783 Yes 172 21625813…21787161 Loss 0
22 14q11.2 Yes 226 21804698…22030660 Yes 226 21804698…22030660 Loss 0
23 14q32.33 Yes 386 105190672…105576359 Yes 253 105345270…105597999 Yes 411 105190672…105601397 Yes 336 105265510…105601397 Gain 0
24 14q32.33 Yes 137 105760582…105897672 Yes 173 105645593…105818132 Yes 150 105638133…105788389 Yes 182 105640496…105822317 Gain 0
25 15q11.2 Yes 156 18682380…18838423 Yes 183 18655531…18838423 Yes 156 18682380…18838423 Gain LOC283755, POTE15 1
Yes 1067 18861808…19928521 Yes 572 18850029…19422452 Yes 344 18845990…19189673 Gain OR4M2, OR4N4, LOC650137 1
Yes 624 19207088…19835514 Gain 1
26 15q25.3 Yes 161 83524791…83685356 Yes 228 83524791…83752853 Yes 228 83524791…83752450 Gain AKAP12 0
27 15q25.3 Yes 123 83784507…83907801 Yes 157 83784507…83941483 Yes 159 83790259…83949305 Gain AKAP13 0
28 16p11.2 Yes 118 31882658…32000323 Yes 1131 32531735…33662480 Yes 1377 32303108…33680554 Gain LOC729355, TP53TG3 1
Yes 294 32088275…32382422 Gain 1
Yes 185 32538757…32723310 Gain 1
Yes 474 32962147…33436245 Gain 1
Yes 211 33451476…33662480 Gain 1
29 17q21.31 Yes 586 41521621…42107467 Yes 198 41521621…41719935 Yes 586 41521621…42107467 Yes 407 41700624…42107467 Gain KIAA1267, LRRC37A, ARL17, LRRC37A2, NSF 1
30 18p11.21 Yes 1545 15262486…16807594 Yes 130 15218647…15348836 Gain ROCK1 1
31 19q13.31 Yes 116 47991257…48107552 Yes 133 47991257…48123857 Yes 235 47986218…48221228 Loss PSG1, PSG6, PSG7, PSG11 1
32 21p11.2 Yes 204 9758730…9962501 Yes 204 9758730…9962501 Yes 204 9758730…9962501 Gain TPTE 0
33 22q11.22 Yes 148 21300127…21448190 Yes 200 21298324…21498767 Yes 178 21298324…21476564 Gain GGTL4 0
34 Xp11.23 Yes 112 47917899…48029446 Yes 269 47917899…48186708 Yes 184 47917899…48102337 Yes 257 47935225…48192383 Gain SSX5, SSX1, SSX9, SSX3 1
35 Xq13.1 Yes 185 71869375…72054837 Yes 185 71869375…72054837 Gain Yes DMRTC1 1

Identity of inherited CNVs found in Family 1 (7), Family 2 (8) and the gene regions which they overlap. Inherited CNVs are those which are present in either or both parents and transmitted to either or both twins. All size is in kb. SD indicates the percentage of overlap between segmental duplications and CNVs. ‘0’ means there is no overlap between CNV and segmental duplication, ‘1’ means 90–100% and ‘2’ means 50–90% overlap. Parental CNVs not transmitted to offspring were not included in Table 58 so the total number of CNVs present in Table 24 was not same as Table 58. The table includes genomic locations as well as individual specific break points which allow for the assessment of regions of overlap with the Database of Genomic Variants (Toronto, Ontario). SI No. = Serial number. Novel indicates a CNV which is not present in The Database of Genomic Variants (DGV).

We also analyzed genes that overlapped de novo CNVs (gains and losses) in order to assess their potential effect on physiology and function starting with GO ontology annotation (http://www.geneontology.org). Interestingly, the majority of genes belonged to transcription, DNA replication, transport, and cell signalling pathways, including ‘binding’ or ‘catalytic’ functions. A number of these genes are expressed in the brain, some with potential to affect neurophysiology, neurodevelopment and function and a set of them are known to show altered expression in schizophrenia (www.schizophreniaforum.org). Also of significance is the observation that the FAM19A5 protein encoded by the FAM19A5 gene (22q13.32) belongs to the TAFA protein family which are predominantly expressed in the brain, and are postulated to function as brain-specific chemokines or neurokines, that act as regulators of immune and nervous cells [32]. This finding adds to the existing speculation about the role of the Major Histocompatability Loci (MHC) and infection in SCZ. Functional analysis of this gene and upstream regulatory elements for characteristic patterns of nucleosome occupancy changes associated with enhancers could yield novel insights into the role of this gene in psychiatric disorders. IPA analysis of gene networks of CNVs and SNPs converged on cell cycle, cellular growth and proliferation. Genes involved in genetic disorders such as hematological disease, immunological, inflammatory and developmental disorders were overrepresented. These results support the hypothesis that schizophrenia is a “developmental disorder” at the molecular level. Interestingly, a recent co-expression network analysis of microarray-based brain gene expression data revealed perturbations in developmental processes in schizophrenia [33]. However, given that these results are based on only two twin pairs, and schizophrenia is highly heterogeneous, the results on disease causations cannot be generalized. Also, we have offered other explanations for twin discordance that may involve epigenetic changes [34].

It is not surprising that genomic studies have begun to use monozygotic twins. In fact a number of them have identified copy number variations [35] and epigenetic [36][38] differences between them; an exception to these results is a recent study by Baranzini et al [39]. They studied three pairs of monozygotic twins discordant for Multiple Sclerosis (MS) and found no difference that could account for the disease causation. The results may be viewed as not surprising for a number of reasons. First, MS is known to have significant environmental components including sunlight and viruses, among others, [40] and the concordance rate in monozygotic twins is only ∼30%. Second, they assessed the CD4+ lymphocytes only that may or may not represent the causative cell type. Also, they sequenced the genome of CD4+ cells from a single pair corresponding to 21.7 and 22.5-fold coverage representing 99.6% and 99.5% of the NCBI human reference genome, which may or may not be effective. Only additional genomic and epigenomic studies on MZ twins will offer insights into the dynamics of genomic stability and change, that forms the focus of this report.

In summary, the present study adds to the recent effort in human genetics to define the phenomenon of constancy and change using inheritance and origin of genome-wide CNVs and SNPs. The results demonstrate that CNVs often result from mitosis during early development facilitated by flanking repeats. They may lead to CNV differences among different tissue and make most individuals mosaics. The described approach expands the search for disease related genetic changes, indicates the time of their occurrence and begins to interrogate the mechanisms involved.

Materials and Methods

This research was approved by the Committee on Research Involving Human Subjects at the University of Western Ontario. The families and patients were identified, recruited and clinically assessed by Dr. Richard O'Reilly (Psychiatrist) and all participants (Figure 1) gave informed consent and provided blood and buccal cells for this research. All subjects were interviewed using the Structured Clinical Interview for DSM IV and the SCID II (for personality disorders) and their medical records collected and reviewed. Diagnoses and demographic information are listed in Table 1. DNA was extracted from the collected white blood cells using the perfect pure DNA blood kit (5prime.com) following the manufacturer's protocol. Subsequent microarray analysis was performed using the Affymetrix Genome-Wide Human SNP Array 6.0 at the London Regional Genomics Centre (LRGC) following manufacturer's protocol and stringent quality control measures. Briefly, 5 µg of genomic DNA was labelled and hybridized to Affymetrix SNP 6.0 arrays. CNVs called by both Affymetrix Genotyping Console 4.0 and Partek® Genotyping Suite™ software suites were retained for analysis. In both cases, the CNVs were identified by continuity of markers on a segment. Two CNVs that overlapped by >50% in the two methods of data analysis were given the same identity. Every measure was undertaken to avoid inclusion of false positives including correction for segmental duplications. We found evidence of CNVs associated with segmental duplications which agrees with previous studies [41]. The CNVs identified were further assessed by comparison to the Database of Genomic Variants (http://projects.tcag.ca/variation/) and annotated with gene symbols by importing the annotation file from the UCSC genome browser (NCBI36/hg 18). A CNV that was present in both members of the twin pair and not in either of their two parents was considered to be meiotic de novo (originated during gamete formation), while a CNV that was present in one of the two twins and not present in either parent was considered to be mitotic de novo (originated during development). Further, a CNV present in the SCZ affected twin only (as compared to the two parents and unaffected member of the pair or the database) was classified as “provisional de novo CNV” for this disease. Novel CNVs discovered in this study were validated for predicted CNVs by Real Time PCR analysis with an internal control (RNAseP gene) using TaqMan detection chemistry and the ABI Prism 7300 Sequence Detection System (Applied Biosystems, http://www.appliedbiosystems.org). The copy number of the test locus in each case was defined as 2T−ΔΔC where ΔCT is the difference in threshold cycle number for the test and reference loci.

Additional CNV analysis focused on two aspects. The first deals with identification of putative repeat elements in the flanking regions of CNVs; within a 1 kb region upstream and downstream of the CNV breakpoint which could promote breakage, deletion and duplication. The identification of repeat elements was carried out using repeat masker (http://www.repeatmasker.org/). Secondly, a probable mechanism associated with sequence-specific susceptibility to CNVs was queried. This data was used to test models related to the origin of CNVs. Previously reported candidates for CNV mechanisms include Non-Allelic Homologous Recombination (NAHR), Non-Homologous End Joining (NHEJ), Fork Stalling and Template Switching (FoSTeS) and Microhomology-Mediated Break-Induced Replication (MMBIR) [42]. The second line of investigation involved functional characterization of genes by matching of the identified genes with the Schizophrenia Gene Database (http://www.schizophreniaforum.org/res/sczgene/default.asp) as well as their assessment by GO ontology (http://www.geneontology.org/). The genes identified were also subjected to IPA analysis (www.ingenuity.com) that identified the nature of gene interactions and the pathways involved.

The use of Affymetrix 6.0 Human SNP array also allowed us to assess the transmission of a total of 909622 SNPs that are contained on the array. It allowed us to identify SNPs in the twins that were not present in either of the two parents; considered to be de novo. The origin of the de novo SNPs was assumed to be parental meiosis if both twins carried the novel nucleotide. In contrast, the origin of the de novo SNPs was assumed to be somatic development (mitosis) if only one of the two twins carried the novel nucleotide. We were able to assign novel substitutions to different categories including their potential effect on the gene and gene product, as well as pathways that may be affected.

Acknowledgments

We thank members of the two families who participated in this research.

Footnotes

Competing Interests: The authors have declared that no competing interests exist.

Funding: Work was supported by the Canadian Institutes of Health Research (CIHR) http://www.cihr-irsc.gc.ca/ Grant number: R2258A15; Ontario Mental Health Foundation (OMHF) http://www.omhf.on.ca/ Grant number: R2258A14; and the Schizophrenia Society of Ontario (SSO) http://www.schizophrenia.on.ca/ Grant number: R2258A10. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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