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DNA copy number variation in psychosis trio samples using BAC array CGH and real time quantitative PCR Melnyk, Brianna Leigh 2006

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DNA COPY NUMBER VARIATION IN PSYCHOSIS TRIO SAMPLES USING BAC ARRAY C G H AND REAL TIME QUANTITATIVE PCR by BRIANNA LEIGH MELNYK B.Sc. Hon., The University of British Columbia, 2003 A THESIS SUBMITTED IN PARTIAL FULFILMENT OF T H E REQUIREMENTS OF T H E D E G R E E OF MASTER OF SCIENCE in T H E F A C U L T Y OF G R A D U A T E STUDIES (Genetics) T H E UNIVERSITY OF BRITISH COLUMBIA April 2006 © Brianna Leigh Melnyk, 2006 Abstract Schizophrenia and bipolar disorder are debilitating mental illnesses. Due to their high genetic predisposition, efforts have focused on attempting to find candidate loci. Numerous regions and loci have been suggested and investigated for potential candidate genes, but none have been found to be necessary or sufficient for the development of either disease. D N A copy number changes are often important in genetic disease. For example, changes in D N A copy number are linked to mental retardation (Klein et al., 2004) and cancer (Albertson et al., 2000). Bacterial artificial chromosome (BAC) array comparative genomic hybridization (aCGH) and real time quantitative PCR (RTqPCR) were used to explore copy number variation in 20 first episode psychosis trios (proband, mother and father) with probands affected with psychosis. The genome scan results showed 11 copy number differences (9 amplifications and 2 deletions) at seven loci. Retesting three of these seven loci with RTqPCR showed 18 amplifications and three deletions. The retested locus showing the most variation in copy number was the lipoprotein A gene. Recendy, protein levels of Lp(a) were shown to be significantly increased in patients with schizophrenia, bipolar disorder and major depression (Emanuele et al, 2006). Comparison of the aCGH and RTqPCR results revealed that of the six trios with aCGH-detected aberrations wiriiin RTqPCR-tested loci, three were confirmed in the same samples and in the same direction. The results from this study contribute to the understanding of copy number variation in the human genome using trio sets as samples, and provide insight into different methods for copy number analysis. ii TABLE OF CONTENTS ABSTRACT ii T A B L E OF CONTENTS iii LIST OF TABLES v LIST OF FIGURES vi LIST OF ABBREVIATIONS vii ACKNOWLEDGEMENTS viii DEDICATION ix 1.0 INTRODUCTION 1 1.1 SCHIZOPHRENIA AND BIPOLAR DISORDER 1 1.1.1 Symptoms and Diagnosis 1 1.1.2 Treatment 1 1.1.3 Heritability 2 1.1.4 Linkage Analysis 3 1.1.5 Cytogenetic Analysis 5 1.2 DNA COPY NUMBER AND GENETIC DISEASE 7 1.2.1 Array Comparative Genomic Hybridization 8 1.2.2 Human Copy Number Polymorphisms 10 1.2.3 Tissue Specific Differences 12 1.3 OBJECTIVES AND PURPOSE 12 2.0 METHODS AND MATERIALS 13 2.1 SUBJECT SET 13 2.2 SUBJECT SAMPLES 13 2.2.1 Msel Digestion, Precipitation and Resuspension 13 2.2.2 Quantification of Digested DNA 14 2.2.3 Qualification of Digested DNA 14 2.3 MICROARRAY COMPARATIVE GENOMIC HYBRIDIZATION 15 2.3.1 Labeling 15 2.3.2 Hybridization ; 16 2.3.3 Washing 17 2.3.4 Scanning 18 2.3.5 Analysis 18 2.3.6 Data Handling 19 2.3.7 SMRT Array CGH 19 2.4 REAL TIME QUANTITATIVE PCR 20 2.4.1 Probe and Primer Design 20 2.4.2 PGT and G6PD Control Probes 21 2.4.3 Sample Dilutions 21 2.4.4 Master Mix 21 2.4.5 Plate Preparation 22 2.4.6 Assay Run 22 2.4.7 Analysis 22 2.5 STATISTICAL ANALYSIS 23 2.5.1 Reference Hybridizations 23 3.0 RESULTS 24 iii 3.1 HUMARRAY 2.0 24 3.1.1 Qualification of Digested DNA 24 3.1.2 Sample Hybridizations 25 3.1.3 Aberrant Clones 25 3.2 CHROMOSOME 13 ABERRATION 28 3.2.1 HumArray2.0 28 3.2.2 SMRT Array Validation 30 3.2.3 Reference Hybridization 32 3.3 REAL TIME QUANTITATIVE PCR 34 3.3.1 Clones Chosen for Probe Design 34 3.3.2 Determination of Copy Number Change 35 3.3.3 Aberrant Copy Number 37 3.3.4 Replication 42 3.4 COMPARISON OF ACGH AND RTQPCR 43 3.5 INHERITANCE AND DNA COPY NUMBER ABERRATIONS 50 4.0 DISCUSSION 51 6.0 CONCLUSIONS 57 7.0 REFERENCES 58 APPENDIX A. PROBAND DETAILS 64 APPENDIX B. MYSQL DATABASE 65 APPENDIX C. QUANTITATIVE PCR 67 APPENDIX D. STATISTICAL ANALYSIS 70 iv LIST OF TABLES T A B L E 1.1. L I N K A G E REGIONS ASSOCIATED WITH BPD OR SCZ 3 T A B L E 1.2. RISK G E N E S FOR BPD A N D SCZ 4 T A B L E 2.1. T H E R M A L PROFILE FOR RTQPCR ASSAYS 22 T A B L E 3.1. A B E R R A N T LOCI IDENTIFIED USING TRIO A R R A Y D A T A A N D Q U E R Y B l 26 T A B L E 3.2. LOG 2 RATIOS FOR E A C H OF T H E 16 A B E R R A N T LOCI D E T E C T E D B Y A C G H 27 T A B L E 3.3. G E N E S L O C A T E D WITHIN H I G H DENSITY A R R A Y ABERRATIONS 32 T A B L E 3.4. L O G 2 R A T I O R A N K I N G FOR LOCI 35 T A B L E 3.5. REGIONS C H O S E N FOR R E A L TIME Q U A N T I T A T I V E PCR V A L I D A T I O N 35 T A B L E 3.6. TYPES OF ABERRATIONS IDENTIFIED IN E A C H G E N E B Y RTQPCR 36 T A B L E A l . DETAILS OF P R O B A N D SAMPLES 64 T A B L E B l . DESCRIPTION OF TRIOS T A B L E IN M Y S Q L D A T A B A S E 65 T A B L E B2. DESCRIPTION OF TRIOS_HD T A B L E IN MYSQL D A T A B A S E 65 T A B L E C l . PRIMER A N D PROBE SEQUENCES 68 T A B L E C2. C A L C U L A T I O N OF PRKCZ A N D G6PD COPY N U M B E R FOR TRIO 187 69 T A B L E D I . COEFFICIENT OF V A R I A T I O N (V) FOR T H R E E R E F E R E N C E HYBRIDIZATIONS 70 V LIST OF FIGURES FIGURE 1.1. T H E A R R A Y C O M P A R A T I V E G E N O M I C H Y B R I D I Z A T I O N P R O C E D U R E 9 FIGURE 1.2. SCANS OF A H U M A R R A Y 2.0 SUBARRAY 10 FIGURE 2.1. TRIO L A B E L I N G S C H E M E 16 FIGURE 3.1. A G A R O S E G E L OF DIGESTED D N A 24 FIGURE 3.2. P E D I G R E E FOR TRIO 456 29 FIGURE 3.3. MIA G R A P H OF H I G H DENSITY A R R A Y 31 FIGURE 3.4. MIA G R A P H OF R E F E R E N C E HYBRIDIZATION 33 F IGURE 3.5. G6PD RATIOS FOR F A T H E R SAMPLES 36 FIGURE 3.6. G6PD COPY N U M B E R RATIOS 37 FIGURE 3.7. PRKCZ COPY N U M B E R RATIOS 38 FIGURE 3.8. LPA C O P Y N U M B E R 39 FIGURE 3.9. ZFP37 C O P Y N U M B E R RATIOS 40 F IGURE 3.10. SYT7 COPY N U M B E R RATIO IN TRIO 456 41 FIGURE 3.11. REPLICATION OF LPA C O P Y N U M B E R RATIO IN FOUR TRIOS 42 FIGURE 3.12. TRIO 257 45 F IGURE 3.13. TRIO 297 46 F IGURE 3.14. TRIO 309 47 F IGURE 3.15. TRIO 341 48 F IGURE 3.16. TRIO 261 49 F IGURE B l . R E G I O N OF C H R O M O S O M E 1 (RP11-82D16, PRKCZ) FOR RTQPCR ANALYSIS 67 vi LIST OF ABBREVIATIONS aCGH A R R A Y C O M P A R A T I V E G E N O M I C H Y B R I D I Z A T I O N ARJP A U T O S O M A L RECESSIVE J U V E N I L E PARKINSONISM B A C B A C T E R I A L ARTIFICIAL C H R O M O S O M E bp BASE PAIR BPD BIPOLAR DISORDER BSA B O V I N E SERUM A L B U M I N COMT CATECHOL-0-METHYLTRANSFERASE CSV C O M M A - S E P A R A T E D V A L U E S C, T H R E S H O L D C Y C L E Cy3 dCTP C Y A N I N E 3 D E O X Y - C Y T I D I N E - T R I P H O S P H A T E Cy5 dCTP C Y A N I N E 5 D E O X Y - C Y T I D I N E - T R I P H O S P H A T E DAO D-AMINO ACID OXIDASE DISC1 DISRUPTED IN SCHIZOPHRENIA 1 DISC2 DISRUPTED IN SCHIZOPHRENIA 2 D N A D E O X Y R I B O N U C L E I C A C I D DTNBP1 DYSTROBRE VIN BINDING PROTEIN 1 E t O H E T H A N O L F A M 6-CARBOXY FLUORESCEIN FCGRJB Fc FRAGMENT OF IgG FISH F L U O R E S C E N C E IN SITU HYBRIDIZATION G6PD GLUCOSE-6-PHOSPHATE DEHYDROGENASE G72 D AMINO ACID OXIDASE ACTIVATOR GRK3 G PROTEIN RECEPTOR KINASE 3 ISHDSF IRISH STUDY OF H I G H DENSITY SCHIZOPHRENIA FAMILES kb K I L O B A S E EPA LIPOPROTEIN A Mb • M E G A B A S E MIA MICRO A R R A Y I M A G E ANALYSIS NaOAc SODIUM A C E T A T E NRG1 NEUREGUUN1 PCR P O L Y M E R A S E C H A I N R E A C T I O N P D P A R K I N S O N DISEASE PGT HUMAN PROSTAGLANDIN TRANSPORTER PMT PHOTOMULTIPLIER T U B E PRKCZ PROTEIN KINASE C ZETA PRODH PROLINE DEHYDROGENASE RGS4 REGULATOR OF G-PROTEIN SIGNALING 4 RTqPCR R E A L TIME Q U A N T I T A T I V E P O L Y M E R A S E C H A I N R E A C T I O N R O M A R E P R E S E N T A T I O N A L O L I G O N U C L E O T I D E MICROARRAY ANALYSIS RSF-1 REMODELING AND SPACLNG FACTOR 1 SCZ SCHIZOPHRENIA SDS SODIUM D O D E C Y L SULFATE SKY SPECTRAL K A R Y O T Y P I N G SMRT SUB-MEGABASE RESOLUTION TILING SNP SINGLE N U C L E O T I D E P O L Y M O R P H I S M SSC SODIUM C H L O R I D E / S O D I U M CITRATE STS S E Q U E N C E T A G G E D SITE SYT7 SYNAPTOTAGMIN VII T A E TRIS A C E T A T E E T H Y L E N E D I A M I N E TETRAACETIC ACID T E TRIS E T H Y L E N E D I A M I N E TETRAACETIC ACID VCFS V E L O - C A R D I O F A C I A L S Y N D R O M E ZFP37 ZINC FINGER PROTEIN 37 HOMOLOG vii ACKNOWLEDGEMENTS I am grateful to my supervisor, Robert Holt (BC Cancer Agency Michael Smith Genome Sciences Centre, Dept of Psychiatry UBC) , for his guidance and patience. The Brain Research Group (BCCA Michael Smith GSC) for technical assistance in the lab and with the computer: ~ Gary Wilson ~ Perseus Missirlis ~ V ik Chopra ~ Carri-Lyn Mead For constructive suggestions and discussion during committee meetings: ~ William Honer, Dept of Psychiatry U B C ~ Weihong Song, Dept of Psychiatry U B C ~ Marco Marra, B C C A Michael Smith GSC Dr. Honer was also essential as a collaborator for this project. His participation in the Early Psychosis Identification and Intervention Program made it possible for me to use the trio samples. Thanks also to the dedicated team involved in the Program. Stephane Flibotte (BCCA Michael Smith GSC) for the design of M I A . The Sequencing Group (BCCA Michael Smith GSC) for help with sample labeling, B A C end sequencing, D N A prep and primer ordering. The Mapping Group (BCCA Michael Smith GSC) for help with the B A C re-array and L M P C R . Even though the main products of my work with the Sequencing and Mapping groups were not used for the final thesis project, they were instrumental in helping me during the initial attempts and answering subsequent questions. Donna Albertson, Randy Davis and Greg Hamilton (University of California at San Francisco Cancer Centre) for printing the HumArray 2.0 and help with array trouble-shooting. Spencer Watson and the Wan Lam lab (BC Cancer Research Centre) for completing the high density array hybridization. A n d last but not least, thank you to my family and friends who listened to endless chatter about those array tfiingies and digesting D N A . Y o u may not believe that a B .Gym and a half B.A.Sc could help an aspiring M.Sc, but my father and sister are appreciated for a myriad of tilings, mcludingykr/ write anything and get yourself a newt. A special thank you to my mother, who consistendy repeated the gende reminder that this experience was not the most difficult tiling I have lived through. Internal repetition of that reminder kept me going when nothing else helped. She also kept wondering why I was eating the D N A , but that is a story for another time. viii DEDICATION This piece of my life is dedicated to my aunt, Darrell Susan Drexel 9 January 1948 - 27 May 2002 1.0 INTRODUCTION 1.1 SCHIZOPHRENIA AND BIPOLAR DISORDER /. /. / Symptoms and Diagnosis Schizophrenia (SCZ) and bipolar disorder (BPD) are severe mental illnesses each of which affects approximately 1% of the population (reviewed in Walker et al., 2004 ). These diseases do not have any consistent genetic or neuropathological markers, so diagnosis is based on the presence of positive and negative symptoms (SCZ) or manic, depressive and mixed episodes (BPD) as outlined in the DSMIV-TR (2000). SCZ is divided into five subtypes based on the predominant symptom, while a diagnosis of BPD is derived from the most recent episode. The symptoms of SCZ include hallucinations and delusions (psychosis), disorganized speech and behaviour, and negative symptoms (affective flattening, alogia, avolition). BPD is characterized by a disorder in mood and episodes of mood disorder can be manic, depressive, hypomanic or mixed. Patients with BPD may also experience symptoms of psychosis. 1.1.2 Treatment Treatment of patients with psychosis is usually through administration of antipsychotic medications. In general, use of antipsychotic drugs reduces psychotic symptoms, but can also result in multiple side-effects. The classical antipsychotic medications show a high affinity for D 2 receptors; the drugs bind these receptors tightiy and dissociate slowly (reviewed in Miyamoto et al., 2005 ). In contrast, the second generation (atypical) antipsychotics have multiple sites of action (including dopamine, serotonin, histamine and glutamate receptors) and show faster dissociation rates from the D 2 receptors (reviewed in Miyamoto et al., 2005 ). Both types of drugs are effective against positive symptoms (hallucinations and delusions), but the atypical medications are better for the treatment of negative symptoms (reviewed in Miyamoto 1 et al, 2005 ). Fewer extra-pyramidal symptoms (parkinsonism, dystonia, akathesia, tardive dyskinesia) are caused by the atypical drugs, but they can result in weight gain, diabetes or cardiovascular problems (reviewed in Baldessarini and Tarazi, 2001 ). For these reasons, a diagnosis of SCZ or BPD with psychosis is usually followed by treatment with atypical antipsychotic medication (risperidone, olanzapine or quetiapine). Even though some patients do not respond to drug treatment, or experience a worsening of symptoms, pharmacotherapy remains the most efficient way to treat SCZ and BPD (reviewed in Baldessarini and Tarazi, 2001 ). 1.1.3 Heritability Although environmental factors do contribute to disease risk, SCZ and BPD are highly heritable. It is estimated that the heritability of SCZ is between 82-85% (Cardno et al., 1999), and the heritability of BPD is 85% (McGuffin et al., 2003). This means that 82-85% of the phenotypic variation in the disease is caused by genetic variation (King and Stansfield, 1997). However, even with this evidence for a strong genetic component, there is no single mutation that has been found to cause any case of disease. Nor has research into other potential biological causes (e.g. changes in brain structure, function or cognition) yielded definitive answers (Heinrichs, 2001). In the literature to date, several chromosomal locations have been implicated as risk regions for SCZ and BPD. Most of the candidate chromosomal regions have been found through linkage studies with some clues provided by cytogenetic approaches. Follow-up studies attempt to identify mutations in individual genes that confer risk of disease development. 2 1.1.4 Linkage Analysis Linkage analysis uses genotype data from large families with many cases of a disease of interest to find co-segregation between genetic markers (single nucleotide polymorphisms [SNPs], microsatellites, etc.) and the disease. Currendy, linkage studies have identified at least 9 regions associated with SCZ (reviewed in Sklar, 2002; Owen et al., 2004 ) and 8 associated with BPD (reviewed in Sklar, 2002 ) (summarized in Table 1.1). However, reports from linkage studies are controversial because the findings have not been consistentiy confirmed (reviewed in Sklar, 2002 ). For example, a study with Celtic- and German-Canadian families found evidence of SCZ linkage to chromosome lq21-22 (Brzustowicz et al., 2000). However, another group reported no significant linkage to chromosome lq after genotyping 16 microsatellite markers in multiple populations (Levinson et al., 2002). T A B L E 1.1. L I N K A G E REGIONS ASSOCIATED WITH BPD OR SCZ (adapted from Sklar, 2002; Owen et al., 2004 ). Chromosomal Band Disease lq21-22, 6p22-24, 6q21-22, 8p21, 10pll-15, 13q32, 22qll-13 SCZ 4pl5-16,12q23,13q32,18ql2,18q22, 21q22, 22qll-12 BPD Regions identified through linkage reports are often investigated for candidate genes. To determine potential candidate genes within a region of interest, smaller areas are studied using fine mapping and the disease risk of the genes are investigated using haplotype association. The alleles of specific markers (within or close to the gene of interest) and haplotypes constructed from the alleles, are analyzed for their distributions in patient and control samples. Even though there is high heritability associated with SCZ and BPD, no individual gene has been found to be responsible for disease. However, some potential candidates for increasing disease risk have been identified (Table 1.2). 3 T A B L E 1.2. RISK GENES FOR BPD A N D SCZ (adapted from Harrison and Weinberger, 2005 ). Gene Band References Disease Neuregulin 1 (NRG1) 8pl2 Stefansson et al, 2002 SCZ Dystrobrevin binding protein 1 (DTNBP1) 6p22.3 Straub et al., 2002 SCZ Catechol-o-methyltransferase (COMT) 22qll.21 Shifman et al, 2002 SCZ D-amino acid oxidase (DAO) 12q24.11 Chumakov et al., 2002 SCZ D-amino acid oxidase activator (G72) 13q33.2 Chumakov et al., 2002 SCZ G-protein receptor kinase 3 (GRK3) 22ql2.1 Barrett et al., 2003 BPD Regulator of G-protein signaling 4 (RGS4) lq21 Chowdari et al, 2002 SCZ Disrupted in schizophrenia 1 (DISCI) lq42.2 Hennah et al, 2003 SCZ For example, interest in neuregulin 1 (NRG1) as a risk gene for SCZ was generated by one of multiple linkage scans highlighting chromosome 8p (Stefansson et al., 2002). Subsequent fine-mapping in this study identified NRG1 as a possible susceptibility gene. The authors found evidence of association between a NRG 1 haplotype and SCZ in an Icelandic population where the core haplotype overlapping NRG1 was found at a higher frequency in SCZ patients when compared to controls. Association of this risk haplotype was evaluated in an independent population and a portion of the risk haplotype identified in the Icelandic patient group was also found at a higher frequency in Scottish patient population (Stefansson et al., 2003). Stefansson et al. (2002) also investigated heterozygous NRG1 mutant mice and found that the behavioural phenotype was consistent with other SCZ mouse models. For example, the NRG1 mutant mice were hyperactive and had impaired pre-pulse inhibition. In addition, clozapine treatment reduced the hyperactivity of mutant mice but did not change the activity of normal mice. The results from these papers show how linkage analysis and fine-mapping can be used to suggest risk loci for psychiatric disease. 4 1.1.5 Cytogenetic Analysis Cytogenetic reports related to SCZ and BPD are generally anecdotal and based on isolated cases because patients with psychiatric disorders are not usually referred for cytogenetic testing (reviewed in Maclntyre et al., 2003 ). Cytogenetic aberrations implicated in mental illness include translocations (reciprocal and unbalanced), fragile sites, insertions, inversions and mosaicism. A small number of cytogenetic abnormalities identified have been supported by further evidence of association to disease. For example, researchers discovered that a balanced translocation in a large Scottish family disrupts two genes (DISC1 and DISCZ) on chromosome 1 and segregates with SCZ and affective disorders in this family (Millar et al., 2000; Blackwood et al, 2001). Subsequendy, using SNP markers and haplotype analysis, DISC1 was found to be associated with schizophrenia (Hennah et al., 2003). A seminal cytogenetic finding in SCZ and BPD is related to velo-cardio-facial syndrome (VCFS). This syndrome is caused by a 3 Mb deletion of chromosome 22ql.l. Symptoms of VCFS include craniofacial abnormalities, cardiovascular defects, learning disabilities and behavioural disorders (reviewed in Shprintzen et al., 2005 ). In addition to physical abnormalities, patients with VCFS develop psychiatric disorders. The first report was published in the early 1990's (Shprintzen et al, 1992). Another group of researchers assessed a cohort of 50 adults with VCFS and found an increased rate of schizophrenia (24%) and psychosis (30%) when compared to the general population rate (Murphy et al., 1999). The phenotype of schizophrenia in patients with VCFS is not different from SCZ in patients without VCFS (Bassett et al., 2003). The high degree of risk for people with VCFS is only surpassed by the risk for people with a monozygotic twin or two parents with SCZ or BPD (reviewed in Bray and Owen, 2001 ). 5 Because of the high rate of psychosis in patients with VCFS, efforts have been aimed at identifying genes within the 3 Mb deletion that could be disease risk candidates. Within the approximate boundaries of the microdeletion (chr22:16,865,871-20,930,922), as viewed on the University of California at Santa Cruz (UCSC) Genome Browser (Karolchik et al., 2003), there are approximately 30 genes. Catechol-o-methyltransferase (COMT) and proline dehydrogenase (PRODH) have been investigated as potential risk genes for psychosis. Association between two haplotypes within PRODH and schizophrenia was found in a Chinese population (Li et al., 2004). In addition, missense mutations within PRODH influenced the functional activity of the gene product P O X (Bender et al., 2005). The authors reported that some of the mutations resulting in decreased P O X activity are polymorphisms associated with schizophrenia. The COMT gene product metabolizes catecholamines, including dopamine (Axelrod and Tomchick, 1958). A few papers have shown an association between COMT and SCZ using genetic marker and haplotype analysis. In a study of a population of Ashkenazi Jews, researchers reported significant association between SCZ and a particular COMT haplotype (Shifman et al., 2002). Another group attempted to replicate these findings in the Irish study of high-density schizophrenia families (ISHDSF) (Chen et al., 2004). The authors investigated three of the SNPs examined by Shifman et al. (2002), but found no association of any SNP with SCZ in the ISHDSF. The linkage disequilibrium values for the Irish families showed a similar trend fo that of the Ashkenazi Jews, but were lower. In addition, Chen et al. (2004) did not find strong association between the haplotype identified by Shifman et al. (2002) and SCZ. The differences between the studies suggest that population history may influence the genes that are risk factors. In addition to genetic marker analysis, researchers have examined the effects of COMT genotype on cognitive function. Several studies using cognitive testing revealed better performance of 6 psychosis patients (Nolan et al., 2004; Rosa et al., 2004) and 22qll deletion patients (Bearden et al., 2004) with a methionine at amino acid 158 of the COMT gene product. The increase in risk for the development of psychosis in patients with VCFS suggests that changes in gene copy number are important. Evidence exists that COMT and PRODH are important for the development of SCZ and psychosis, but it remains to be seen whether other genes that show copy number changes in patients are risk factors for disease. 1.2 DNA COPY NUMBER AND GENETIC DISEASE Linkage and cytogenetic analyses are powerful techniques to identify disease genes in which copy number aberrations segregate with disease. Examples of disease genes found through these techniques are a-synuckin and parkin. The a-synuclein gene was first pinpointed after a linkage study found a connection between Parkinson disease (PD) and chromosome 4q21-23 (Polymeropoulos et al., 1996). A copy number increase of the gene was found in independent families with PD (Singleton et al., 2003; Farrer et al, 2004). For the parkin gene, linkage studies with autosomal recessive juvenile parkinsonism (ARJP) highlighted chromosome 6q25.2-25.7 (Matsumine et al., 1997). Fine mapping refined the linkage region to the parkin gene (Saito et al., 1998) and this locus was also found to be deleted in ARJP patients (Kitada et al , 1998). Another example of how copy number influences disease susceptibility is the Fcfragment oflgG (FCGR3B) gene and lupus nephritis in humans. Findings in rats indicated that reduced copy number of Fcgr3 resulted in macrophage overactivity and glomerulonephritis susceptibility. This finding stimulated the authors to investigate families showing mendelian errors for FCGR3B polymorphisms (Airman et al., 2006). The authors found that reduced copy number of FCGR3B was a risk factor for lupus nephritis. This study and the PD studies above, show that copy number of a single gene can influence a complex disease. 7 1.2.1 Array Comparative Genomic Hybridisation Array comparative genomic hybridization (aCGH) is a cytogenetic method used to detect D N A copy number changes (deletions and duplications); this technique is based on chromosomal C G H (Kallioniemi et al., 1992). Previously, chromosome banding and fluorescence in situ hybridization (FISH) were used to determine copy number changes in the genome, but these microscope techniques are limited by low resolution (5-20 Mb) and restricted application. For example, whole chromosomes are needed for both procedures and the target for FISH must be known prior to investigation. Instead of using metaphase whole chromosome spreads, aCGH employs the use of D N A clones printed on slides. An example of this technology is the HumArray 2.0. This array contains 2460 bacterial artificial chromosome (BAC) clones printed in triplicate on a glass slide and represents approximately 15% of the genome (Snijders et al., 2001). Each spot on the HumArray 2.0 is a polymerase chain reaction (PCR) representation of a BAC clone. Instead of using full-length BAC clones (~175kb), which would be difficult to print onto the array because of the viscous nature of the spotting solution, ligation-mediated PCR (LMPCR) is used. This technique cuts each BAC clone into fragments and amplifies each piece. A mixture of the amplified fragments from each BAC clone is printed onto a slide. The chromosomal location of each BAC is known through sequence tagged site (STS) markers (Snijders et al, 2001). To determine copy number changes in samples, genomic D N A from two sources (patient or unaffected, and reference) is labeled with fluorescent nucleotides. Usually, D N A from a reference sample is labeled with Cyanine-5 deoxycytidine triphosphate (Cy5-dCTP; red) and the patient or unaffected control sample is labeled with Cyanine-3 deoxycytidine triphosphate (Cy3-dCTP; green). Equal amounts of labeled D N A are mixed together and incubated with human Cot-1 D N A to block repetitive D N A sequences (Figure 1:1). The incubated mixture is hybridized to the microarray and the ratio of green to red fluorescence of each spot is measured. Since equal amounts of D N A are used, the expected ratio in the absence of a copy number change is 1:1. A significant deviation from this ratio represents a D N A copy number aberration. As seen in Figure 1.2, the red and green spots outlined in white represent sex chromosome copy number differences within family 163. both scans show a copy number decrease of a Y chromosome clone in the mother. D N A 1 + Cy3-dCTP D N A probe 1 D N A 2 soon Q B H O " i i " DP + Cy5-dCTP D N A probe 2 -1 D N A precipitate resuspend denature V •* block hybridize FIGURE 1.1. T H E A R R A Y COMPARATIVE GENOMIC HYBRIDIZATION PROCEDURE. D N A from two sources is labeled with fluorescent nucleotides (Cy.3-dCTP and Cy5-dCTP). The labeled D N A is mixed with Cot-1, denatured and blocked. The mixture is hybridized to the array. 9 a b ' 0 0 » 6 i O Q « © ( >o© 0 1 ' O O >0t > o o o o I O O O O • O O O I i e o o < i Q O . O I l O O O O i i O O O O i l O O O O i i O O O O i l O O O O i >OG' O* • 0 0 . 0 0 SO O O O J O ' . O O O 5 0 * 0 0 0 © • O O O ) O O ^ n l O O t t ' ' ; O I O O » u O >o:o o ) Q - iO - o - 0 0 0 - o >oooo • • O O O . 0 0 0 0 0 , 0 0 0 0 0 i O O G O O 0 0 0 0 0 0 o O O O C O Q O Q G C S O # 0 0 0 0 0 0 O O O O C # 0 0 0 0 0 0 0 0 0 0 Q O O O O 0 0 0 0 0 0 0 0 0 0 0 ©ooooo ©ooooo ©ooooo ©ooooo 0 0 0 0 0 0 ooooo o o j o o o 0 0 * 0 0 0 o u ° o o o i O © « 0 0 l O O O O O ( O O O O O > 0 0 o I ; 0 0 O >o 0 0 0 i O 0 0 »o 0 0 I O I O O O t . 0 0 0 0 • ooooo i t o o e o ) 0 , 0 0 0 0 oooo 0 0 0 0 o 0 0 0 0 0 0 0 0 0 0 l i O O O O ( © O O O O 0 0 0 0 0 0 «*o 0 0 0 0 0 0 . 0 0 : 0 0 0 0 0 0 0 0 0 0 . . , 0 0 0 0 0 0 O O ' O O O o o o o „ o O O . ^ u Q O 0 0 0 0 0 0 0 0 o©> O O O .GO) 0 0 0 0 oooo o©ooc 0 0 © O G O O 0 \ O i o O O O * O O O U v 0 0 :o 0 0 o O O G 0 0 0 0 so o -^rj • O . G G O ' 0 0 0 0 : 0 0 0 0 0 ^ 0 0 0 0 0 o g u O O 0 0 © • © 0 0 0 t i o t o o © • © • G C ooooooo ocoooto o«o®o o©o®o o«o*o 0 0 0 f ° O O O ' " ' 0 0 O O P 1 G G FIGURE 1.2. SCANS OF A H U M A R R A Y 2.0 SUBARRAY. (a) The family 163 father/mother hybridization. Red spots show a copy number decrease of a chromosome Y clone in the mother (Cy3) as compared to the father (Cy5). (b) The family 163 proband/mother hybridization. Green spots show a Y chromosome clone copy number decrease in the mother (Cy5) as compared to the proband (Cy3). The black spaces on the array are regions without spotted D N A because the plates used to print the spots were not completely full. 1.2.2 Human Copy Number Polymorphisms In recent years, D N A copy number analysis has become a hot topic. Interest ranges from the differences between humans and other primates to normal C N polymorphisms in humans. Using the HurnArray 2.0 (Snijders et al., 2001), researchers found 63 sites in the human genome that showed C N differences when compared to other primates (gorilla, pygmy chimpanzee, chimpanzee and orangutan) (Locke et al., 2003). Most variant sites were not common to all primate groups. For example, 30 variant sites were specific to orangutans. Of the 63 sites found, fourteen were investigated further and 7/7 duplications and 2/7 deletions were confirmed copy number changes. In addition, six of the 9 confirmed sites are proximal to human genes. A subsequent study of gorilla, chimpanzee and human samples found 63 10 chromosomal segments with D N A copy number differences using full genome coverage high density aCGH (Wilson et al , 2006b). Two of the CGH-detected duplicated genes were tested and both were validated as copy number amplifications in human D N A using real time quantitative PCR (RTqPCR). Recendy, two studies have been published that describe D N A copy number variation in the human population. The first reported a total of 76 unique copy number polymorphism sites in the genomes of 20 individuals (Sebat et al, 2004). Using representational oligonucleotide microarray analysis (ROMA, a technique similar to aCGH) the authors observed a total of 221 differences at the 76 sites. Fluorescence in situ hybridization (FISH) was used to validate the findings; nine of 12 sites tested were confirmed (two additional sites were confirmed using an alternate method). Seventy genes showing copy number variation were found within the 76 sites. The second study used aCGH with 55 individuals and found 255 clones with copy number differences (Iafrate et al., 2004). Of the identified clones, 14 were near human disease loci. The results from these two studies showed that human genome variation is more common than originally believed. However, the concordance between the two reports was low. Only 11 loci were found in common and there are some limitations of these methods (Carter, 2004). This could be explained because in these two studies neither ROMA nor aCGH have a high resolution compared to arrays that have almost complete coverage of the human genome (e.g. SMRT array (Ishkanian et al., 2004) or higher density ROMA array). The array used for C G H had one clone every 1 Mb (Iafrate et al., 2004), while the ROMA array had one probe every 35 kb (Sebat et al , 2004). These results formed the groundwork of a database for normal copy number variation in humans (http://projects.tcag.ca/variation). The database is designed to show copy number variants within or overlapping a user-defined genomic region. For example, a query of a locus 11 that I have found to have copy number variation, the lipoprotein A (LPA) gene (NM_005577), shows an overlapping segmental duplication cluster of 14,270 bp (DC2038). 1.2.3 Tissue Specific Differences Tumours are excellent examples of cell populations that show changes in D N A copy number relative to normal somatic tissues. A recent publication on ovarian cancer showed that borderline tumours and serous adenocarcinomas had more aneuploid cells than surface epithelium or inclusion cysts (Korner et al., 2005). The results also showed an elevated level of whole chromosome changes in tumours, but did not report on single gene amplifications or deletions. Another publication showed that amplification of remodeling and spacing factor 1 (Rsf-1) in ovarian tumours led to shorter survival times in patients (Shih le et al., 2005). Given the expansive evidence of D N A copy number variation present in tumours, there is the possibility that variation between non-cancerous tissues exists. However, this phenomenon has not been investigated in normal tissues. 1.3 OBJECTIVES A N D PURPOSE My objectives for this project included: (1) complete array comparative genomic hybridization with 20 trios in which the proband suffers from psychosis; (2) identify putative inherited and spontaneous copy number aberrations within the trio; (3) design real time quantitative PCR primers and probes for putative aberrations; (4) validate the differences using RTqPCR. The purpose of this study was to identify candidate genes for psychosis that could be used as therapeutic targets or for the design of diagnostic tools. 12 2.0 METHODS AND MATERIALS 2.1 SUBJECT SET The subjects for this project consisted of sets of trios. A trio is comprised of a youth (proband) aged 14-35 who has experienced a first psychotic episode (with less than 12 weeks exposure to antipsychotic medication) and his/her biological parents. Probands from the South Fraser region (Surrey, White Rock, Delta, Langley) were ascertained through referrals to the Early Psychosis Identification and Intervention (EPII) Program at Peace Arch Hospital (White Rock, British Columbia, Canada). The majority of diagnoses of probands included schizophrenia, schizoaffective disorder and affective disorders (bipolar and major depression) with psychosis. A detailed family history of psychiatric illness had not been completed for these trios. Refer to Appendix A (Table A l ) for details about the proband used in this project. 2.2 SUBJECT SAMPLES Blood samples from all three family members were sent to the BC Cancer Agency Genome Sciences Centre (BCCA GSC). Genomic D N A was extracted from lymphocytes for subsequent experiments (G. Wilson). In addition, some D N A samples arrived pre-extracted from the Kennedy lab in Toronto, Ontario, Canada. These samples were also originally from the EPII program at Peace Arch Hospital. When there was sufficient extracted D N A from subjects, it was digested with Msel enzyme prior to aCGH. This initial digestion improves hybridization and reduces the scatter of values around the 1:1 ratio by creating uniform D N A fragment sizes. 2.2.1 Msel Digestion, Precipitation and Kesuspension Genomic D N A from subjects (1 ug), 1 uL Msel enzyme (lOU/uL, New England Biolabs), 1.2 uL bovine serum albumin (BSA, 100X, NEB) and 1.2 uL 10X N E B Buffer 2 were combined in 13 1.5 mL eppendorf tubes with a total reaction volume of 40 uL, or 96-well plates (Greiner) with a total reaction volume of 12 uL, and incubated at 37°C overnight. After 10 minutes at 70°C, 1 uL glycogen (20 mg/mL), 4 uL sodium acetate (NaOAc, 3M, pH 7, Sigma; 1.2 uL for 96-well plate) and 100 uL 95% ethanol (EtOH; 30 uL for a 96-well plate) were added. Eppendorf tubes were stored at -20°C for 10 minutes followed by centrifugation (15 minutes, 16100 X g). Plates were stored at -20°C for 30 minutes followed by centrifugation (45 minutes, 4°C, 2840 X g). The pellets were decanted, washed with 900 uL 80% EtOH (200 uL for 96-well plate) and allowed to air dry. Pellets in eppendorf tubes were resuspended in 12 uL of 10:1 T E (10 mM Tris-HCl, ImM ethylenediamine tetraacetic acid, pH 8) and stored at 4°C overnight. For resuspension of the pellets in plates, 15 uL of T E was added to each well and the plate was incubated for 20 minutes at 37°C. After incubation, the plate was placed on the IKA-Vibrax plate agitator (Janke & Kunkel) for 5 minutes at 750 rpm. A quick spin (1 minute, 4°C, 805 X g) was followed by storage at 4°C until the D N A was qualified and quantified. 2.2.2 Quantification of Digested DNA Dilutions (in TE) were made for each digested sample (1:100 and 1:1000) and combined with an equal amount of 1:200 pico green (10 uL) in a 384-well black skirted MJR plate. Dilutions (in TE) of calf thymus D N A were used to make the standard curve (0.7 ng/uL, 0.4, 0.2, 0.1, 0). Fluorescence was measured using the VICTOR 3 V 1420 Multilabel Counter (Perkin-Elmer), and analysis was completed using Microsoft Excel. 2.2.3 Qualification of Digested DNA A 0.7% agarose gel in I X T A E (40 mM Tris acetate, 2 mM ethylenediamine tetraacetic acid) was loaded with 1 uL of sample (with 0.5 uL loading buffer and 3.5 uL TE). The samples were run 14 for 1.5 hours at 100 V. The gel was stained with SYBR green for 30 minutes (25 uL in 250mL I X TAE) and then scanned using the Fluorlmager 595 (Molecular Dynamics). 2.3 MICRO ARRAY COMPARATIVE GENOMIC HYBRIDIZATION 2.3.1 Labeling Labeled D N A fragments were prepared using the Invitrogen Bioprime labeling system. Two individual sample DNAs (400 ng each) were each combined with 10 uL of 2.5X random hexamer primers and d H 2 0 in separate tubes (for a total reaction volume of 20.5 uL). The D N A was denatured at 100°C for 10 minutes, then 2.5 uL of dNTP mix (2 mM dATP, 2 mM dGTP, 2 mM dTTP, 1.2 mM dCTP) was added. Cy3-dCTP (1 nmol) was added to one sample of D N A and Cy5-dCTP (1 nmol) was added to the other sample of D N A . Klenow fragment (1 uL of 40 U/uL) was added to each reaction and they were placed in a water bath in an air incubator overnight (~18 hours, 37°C). The reactions were pooled and the unincorporated nucleotides were removed using Amersham ProbeQuant Sephadex G-50 columns. To ensure blockage of repetitive D N A sequences before hybridization to the array, 140 uL of 500 ng/uL Cot-1 D N A (Invitrogen) was added to the eluate from the columns; 65 uL of NaOAc (3M, pH 5.2) and 921 uL of 95% EtOH were added and the reactions were placed on ice (10 minutes) to facilitate precipitation, and then centrifuged (30 minutes, 4°C, 18000 X g). The supernatants were decanted, pellets air-dried and the walls of the tube were dried with tissue paper. The pellets were resuspended in a mixture of 19.2 uL DIGEasy hybridization solution (Roche), 2.4 uL sheared salmon sperm D N A (10 mg/mL, Invitrogen) and 2.4 uL 100X BSA (NEB). The D N A was denatured in a dark water bath (10 minutes, 85°C), and repetitive sequences were blocked by the Cot-1 D N A present in the reaction during re-annealing in the incubator water bath (60-90 minutes, 45°C). 15 For the trios, an example labeling scheme is shown in Figure 2.1. This method of labeling ensures that each trio member is labeled with both dyes, but reduces the number of hybridizations needed for dye flip validation. Three arrays were completed for each trio, and each sample was labeled with each dye. For example, one array may have been the mother labeled with Cy3 (black arrow) and the father labeled with Cy5 (grey arrow). The second array would be a hybridization between the father-Cy3 and proband-Cy5. The last array is between the proband-Cy3 and the mother-Cy5. However, I did the hybridization experiments blind to sample identification. Therefore, the labeling scheme may have been different for each trio. < > FIGURE 2.1. TRIO L A B E L I N G SCHEME. Each trio member is hybridized against the other two, instead of against a reference D N A . O = mother, • = father, A = proband (unknown sex). A = unaffected, A = affected. 2.3.2 Hybridisation To ensure a consistent temperature during application of the hybridization sample to the array, a working surface and the hybridization cassette were warmed in the incubator to 45°C. Each slide was exposed to 260,000 uj of ultraviolet radiation prior to hybridization to link the D N A to the slide. Lifter slips (Erie Scientific) were cleaned with d H 2 0 and 80% EtOH. The 16 hybridization samples were removed from the incubator and placed in a dry block at 45°C. The working surface and hybridization cassette were removed from the incubator; and 22 uL of 2X sodium chloride/sodium citrate (SSC) was added to each reservoir of the hybridization cassette to ensure a humid environment for the slide. The slide was placed in the cassette and the lifter slips were placed over the arrays. The hybridization sample was applied to a side of the lifter slip without lifter rails (one reaction pair per array). A small amount of extra 2X SSC was added to the reservoirs and the hybridization cassette was assembled. The entire cassette was immersed in the water bath in the air incubator (48-72 hours, 45°C). 2.3.3 Washing The hybridization cassette was removed from the water bath, dried and disassembled quickly. The lifter slips were washed off with a solution pre-warmed to 45°C (80% DIGEasy hybridization solution, 2X SSC, pH 7.0). The slide was then immersed in a Copelin jar with the same solution for 15 minutes at 45°C. The slide was transferred to a new Copelin jar (0.1X SSC, 0.1% sodium dodecyl sulfate [SDS], pH 7.0, room temperature). Fresh solution was added each time to complete three separate 5 minute washes. The Copelin jar was covered in foil during the washes to minimize exposure of the arrays to light. After the diird wash, the slide was transferred to a new Copelin jar (0.1X SSC, room temperature). Fresh solution was added each time to complete four separate 30 second washes. The final wash was 5 seconds in a Copelin jar with 18 M£2 H 2 0 . The slide was then placed in a 50 mL conical tube and spun for 7 minutes at 350 X g. 17 2.3.4 Scanning Each slide has two complete arrays, and each array is composed of sixteen 22 spot X 21 spot subarrays. Using a microarray scanner (ScanArray Express, Perkin-Elmer), each array was scanned multiple times at 10 um and 5 um resolution. Typically, initial settings for the Cy3 and Cy5 photo-multiplier tube (PMT) gains were 68% and 62%, respectively. These settings were adjusted depending on the brightness and colour of the scan images. A tan or yellow composite image (combination of Cy3 and Cy5 images) indicates a balance between the two fluorophores. If the composite image was red, the difference between the PMT values was increased; if the composite image was green, the difference between the PMT values was decreased. 2.3.5 Analysis The Cy3 and Cy5 array images were analyzed using Microarray Image Analysis (MIA), a program designed at the BCCA GSC. For an in depth description of MIA, see Wilson et al. (2006b). Briefly, the program was designed to find the 16 subarrays of each array and then the individual spots within each subarray (addressing). This was accomplished by analyzing Fourier transformations of spot spectra and using granulometry. Tiles are placed on the array to match the spot size and the inter-spot distance was calculated by the addressing analysis. The Seeded Region Growing algorithm was used to identify the pixels that contribute to each spot (segmentation). Each pixel within the tile was labeled as a spot, background or artifact pixel. Then, each pixel intensity was calculated. An average intensity for the spot was calculated from all "spot" pixels. The log2ratio for each spot was calculated as: . . Cv5 intensity log,ratio — log, • „ . . 6 2 5 2 Cy3 intensity 18 The data were combined in a comma-separated values (CSV) output file and used for the scan selection step. MIA chooses the CSV file from the best scan of each array (determined empirically based on the standard deviation of each array) and uses this for breakpoint analysis. In breakpoint analysis, each CSV output file is analyzed for regions of the genome with multiple consecutive clones that are significandy above or below the 1:1 D N A copy number ratio. The CSV output file from the best scan was also chosen for population of the data table. 2.3.6 Data Handling The MIA CSV output files were stored in a table (Appendix B, Table Bl) within a relational database (MySQL). Queries of the data were designed to identify clones with a log2ratio that is 3.0 or more standard deviations away from the mean log2ratio of all clones on the array. Examining the output, I identified putative (a) spontaneous (i.e. found in the proband, but not the parents), and (b) inherited (i.e. found in the proband and one parent) aberrations. In addition, the data were inspected by eye for aberrations involving single clones or multiple consecutive clones. 2.3.7 SMRTArray CGH Spencer Watson (Array C G H Laboratory, BC Cancer Research Centre) completed the sub-megabase resolution tiling (SMRT) array hybridization using D N A from the trio 456 proband and a male reference (Novagen). A full description of the array (version 1) and hybridization methods is in Ishkanian et al. (2004). Briefly, the single slide array (version 2) contains more than 26,000 overlapping BAC clones spotted in duplicate. With this number of clones, the coverage of the human genome is 1.44 fold and the theoretical resolution is 80 kb (Ishkanian et al., 2004; Krzywinski et al., 2004). Array resolution is determined by the size of the query genome divided by the number of single copy clones on the array. Selection and validation of 19 the spotted BAC clones was accomplished through Hz'fldlll fingerprint mapping (Krzywinski et al , 2004). 2.4 REAL TIME QUANTITATIVE PCR 2.4.1 Probe and Primer Design Based on a high ranking (see Results section for a description of ranking procedure) and gene content, several putative aberrations were chosen for validation by real time quantitative PCR. The clone name was queried in the UCSC Genome Browser (Kent et al., 2002) with the repeat masker track on. The repeat masker track identifies regions of D N A containing short interspersed nuclear elements, long interspersed nuclear elements, micro-satellites, transfer-RNA, and other repeat family sequences using the Repbase collection of repetitive sequences from the Genetic Information Research Institute (Jurka et al., 2005). If the Browser found only fragments of the clone (200-500 bp), a region of ~200,000 bp around the fragment was searched for genes. Clone fragments are located on the reference genome based on end sequence matches of the clone. These short matches are from only a single end read, and because I did not know which end of the clone the sequence was from, I searched the 200 kb genomic region around the hit. Short stretches of D N A within the gene, but without repetitive D N A were assessed for primer/probe design. Regions of approximately 500 bp without repetitive D N A were (1) assessed for per cent identity to other genomic regions using the BLAST-like alignment tool (Blat) on the UCSC Genome Browser (Kent, 2002), (2) assessed visually to avoid long stretches of mono-nucleotides, and (3) divided into three 100 bp sub-regions for final primer/probe selection (according to instructions from Applied Biosystems). Each sub-region was assessed using Primer3 (Rozen and Skaletsky, 2000). Figure C l is an example of a region queried for RTqPCR suitability. Once a 500 bp region was chosen and analyzed, the sequence 20 was sent to Applied Biosystems Assays-by-Design service for RTqPCR primer/probe design and synthesis. ABI chooses a 100 bp sub-region for the design of each primer/probe set; the solution sent back from ABI is a mixture of the primers and 6-carboxy fluorescein (FAM) labeled probe. 2.4.2 PGT and G6PD Control Probes Primer/probe sets for PGT and G6PD were used as controls. The prostaglandin transporter gene. (PGT or SLC02A1) is located on chromosome 3, and is present as two copies in each person (Lu and Schuster, 1998). However, the glucose-6-phosphate dehydrogenase gene. (G6PD) is a chromosome X gene (Mason et al., 1990) and therefore present in only one copy in males. Using these two genes as controls for RTqPCR, I compared the values obtained with my designed probes to these loci of known copy number. 2.4.3 Sample Dilutions Each of the 60 sample DNAs, as well as control male and female D N A , were diluted to 20ng/uL stocks (in TE). These dilutions (7.5 uL) were then used to make the Ing/uL stock (in 142.5 uL TE) for RTqPCR. The control male and female samples used in this experiment are mixtures of D N A from multiple individuals of the same gender and they are commercially available from Novagen. 2.4.4 Master Mix The master mix for each primer/probe set was prepared fresh for each experiment. The mix contained 240 uL TaqMan Universal PCR Master Mix (2X, Applied Biosystems), 19.2 uL primer/probe (to a final concentration of 0.7 uM for the primers and 0.2 uM for the probe), and 100.8 uL dH 2 0 . In addition, mixes for the PGT and G6PD loci were prepared. Each of these mixes contained 240 uL TaqMan Universal PCR Master Mix (2X), 4.8 uL of 20 uM F A M probe, 21 6.72 uL each of 50 uM forward and reverse primers, and 101.76 uL dH 2 0 . The Universal Master Mix contains: AmpliTaq Gold D N A Polymerase, AmpErase U N G (prevents re-amplification of PCR products containing deoxyuridine), dNTPs with dUTP, and optimized buffer components. Table CI lists the probe and primer sequences for regions tested. 2.4.5 Plate Preparation Fifteen uL of master mix was added to the wells of a 384-well optical PCR plate (ABr). Then, 5 uL of sample or control D N A (lng/uL), or H 2 0 (no template control [NTC]) was added (2 wells per sample, 3 wells per control and 3 wells per NTC for each probe). The plate was sealed with a transparent film and centrifuged for 2 minutes at 805 X g. 2.4.6 Assay Wun Using the Applied Biosystems Prism 7900HT Sequence Detection System (SDS), the thermal profile (shown in Table 2.1) was used for the RTqPCR assays. Each well threshold cycle (C,) was calculated using the ABI software SDS 2.2, and exported into Microsoft Excel for analysis. The C t is equivalent to the PCR cycle at which the sample first begins to show fluorescence from the reporter dye above background levels. T A B L E 2.1. T H E R M A L PROFILE FOR RTQPCR ASSAYS. Primer/probe sets were designed based on the Stage 3 annealing temperature of 60°C. Stage 1 Stage 2 Stage 3 (40 repeats) Temperature (°C) 50 95 95 60 Time (min) 2:00 10:00 0:15 1:00 2.4.7 Analysis Analysis of the RTqPCR data was completed using Microsoft Excel. The reference male C t values were averaged for each probe. The values calculated for the 4 unique probes and the 22 G6PD probe were subtracted from the PGT probe value for each sample. Then, each of these values was subtracted from the male reference value for each probe and converted to copy number (Table C2). This is a standard assay design for gene dosage analysis using RTqPCR, and a standard method of handling RTqPCR data (McCarroll et al., 2006; Wilson et al., 2006a; Wilson et al., 2006b). These subtractions set the C t value for each sample relative to the C t value in a male reference sample. For example, the ratio for G6PD will be twice as high in females as in males because females have two copies. However, other loci with 2 copies in males and females will show a ratio of one relative to the male reference D N A . The final copy number values were averaged for each sample. 2.5 STATISTICAL ANALYSIS 2.5.1 Reference Hybridisations The coefficient of variation (V) comparison was calculated for the reference hybridizations using the Z test (Table DI) (Zar, 1999). 23 3.0 RESULTS 3.1 HUMARRAY 2.0 3.1.1 Qualification of Digested DNA Samples with at least 1 ug of D N A were digested with Msel enzyme. Figure 3.1 is a picture of a representative agarose gel. The digested samples show the same smear pattern as the digested male reference D N A . ° ^ I I =§>! .~ Q3 C O ) Q CH ZD cn IS 10 11 12 13 14 15 12 kb 2kb 1.65 kb 1 kb FIGURE 3.1. A G A R O S E G E L OF DIGESTED D N A . The digested D N A was from three trios (lanes 4-11) and reference male D N A (lanes 13-15). 24 3.1.2 Sample Hybridisations A total of 20 trios (proband, mother and father; 60 arrays) were assessed for D N A copy number changes using low density aCGH and the labeling procedure described in Figure 2.1. 3.1.3 Aberrant Clones For each of the 63 arrays completed, Query B l (Appendix B) was used to find individual aberrant loci from the MySQL data table (Table Bl). Only loci that were aberrant in 2 of 3 arrays per trio were considered candidate aberrations. This is because a true aberration should be detected twice when an individual is compared to each of the other two trio members. Using these criteria I found 7 aberrant loci in 8 trios, and 2 aberrant loci from chromosome 13 in one trio (Table 3.1). These aberrations were found based on the following cutoffs in Query B l : the locus log2ratio was 3 or more standard deviations away from the mean log2ratio of the array (away > 3), the standard deviation of the locus triplicate was 0.2 or less (stdev < 0.2), and the intensity of the triplicate was greater than 10 units on a 16 bit scale (int > 10). I found 11 copy number changes in the seven loci, including 2 amplifications and 9 deletions. The two loci from chromosome 13 were part of a multi-clone aberration cluster. This will be examined further in the next section. For each locus, the inter-array variability was calculated (Query B2). The standard deviation of the 63 independent log2ratio values (20 trios and 3 reference hybridizations) for each aberrant locus was used to determine which loci had the least noisy between-array data. The intra-array variability was also calculated (Query B3) to determine which arrays had the least noisy data. A summary of the log2ratios for each aberrant locus, as well as the inter-array and intra-array variabilities are shown in T A B L E 3.2. 25 T A B L E 3.1. A B E R R A N T LOCI IDENTIFIED USING TRIO A R R A Y D A T A A N D Q U E R Y B l . Loci were identified as aberrant if they were present in 2 out of 3 arrays per trio. Locus Banda Genesb Trio Putative Aberration RP11-122N11 8p23.1 SPAG11 201 Father amplification RP11-82D16 lp36.33 PRKCZ, SKI 231 Proband amplification RP11-1P3 21q22.2 PCP4, DSCAM 257 Mother deletion RP11-88C10 19pll.32 CLUL1, CETN1, EN0SF1, YES1, TYMS 257 Mother deletion RP11-43B19 6q25.3-26 LPA 257 Father deletion RP11-43B19 6q25.3-26 LPA 297 Proband deletion RP11-43B19 6q25.3-26 LPA 309 Mother deletion RP11-43B19 6q25.3-26 LPA 341 Mother deletion RP11-95J4 9q32 ZFP37, SLC21A2 261 Mother deletion RP11-88L18 5pl5.1 none 261 Proband deletion RP11-234M13 13q21.2 none 456 Proband RP11-205J24 13q21.2 none 456 Proband "From UCSC Genome Browser bFrom RefSeq track on UCSC Genome Browser 26 T A B L E 3.2. L O G 2 R A T I O S F O R E A C H O F T H E 16 A B E R R A N T L O C I D E T E C T E D B Y A C G H . Locus Trio Intia_log 2 l b L 0 g 2 _ 2 a Intra_log22b L o g 2 _ 3 * Intra_log23b Inter_varc RP11-122N11 201 -0.4223 0.137 -0.0428 0.197 0.2955 0.144 0.2 RP11-82D16 231 -0.0165 0.233 0.4661 0.181 -0.1982 0.099 0.206 RP11-43B19 257 0.5391 0.144 0.1816 0.109 -0.5127 0.151 0.263 RP11-1P3 257 -0.3613 0.144 0.389 0.109 0.1553 0.151 0.175 RP11-88C10 257 -0.3693 0.144 0.3951 0.109 0.1101 0.151 0.191 RP11-95J4 261 -0.2596 0.14 0.4249 0.153 -0.0716 0.192 0.152 RP11-88L18 261 0.2456 0.14 0.1744 0.153 -0.4656 0.192 0.251 RP11-43B19 297 0.2732 0.127 0.1406 0.201 -0.4919 0.164 0.263 RP11-43B19 309 -0.586 0.221 0.3255 0.125 0.1172 0.112 0.263 RP11-43B19 341 -0.4839 0.148 0.9738 0.148 -0.3144 0.159 0.263 RP11-234M13 456 -0.2936 0.134 -0.2889 0.181 -0.2792 0.111 0.136 RP11-205J24 456 -0.2836 0.134 -0.2074 0.181 -0.3326 0.111 0.222 llogz_ratio from hybridization, bintra-array variability for hybridization, cinter-array variability for locus 3.2 CHROMOSOME 13 ABERRATION 3.2.1 HumArrqy2.0 The chromosome 13 multi-clone aberration was visually obvious in MIA graphical output and identified using Query Bl. Trio 456 showed a proband-specific (spontaneous) aberration of chromosome 13 (Figure 3.2). The aberration was between and including clones RP11-205J24 and RP11-234M13 in a region of approximately 20 Mb. Using MIA breakpoint analysis, all of chromosome 13 was identified as aberrant. 28 FIGURE 3.2. P E D I G R E E FOR TRIO 456. The aberration on chromosome 13 is circled in black on two graphs. Females are represented by circles, males by squares. Affected individuals are shaded. Cy-3 labeled D N A is indicated by a grey arrow and Cy-5 labeled D N A indicated by a black arrow. Log2ratio is log2(Cy5 intensity/Cy3 intensity). 29 3.2.2 SMRTArray Validation Validation of the chromosome 13 amplification was attempted by hybridizing the proband 456 sample against male reference DNA (Novagen) on the high density sub-megabase resolution tiling (SMRT) array. The array results did not validate a chromosome 13 aberration in the proband suggesting the presence of an artifact on the HumArray 2.0 (Figure 3.3) which will be addressed in the next section. However, the results do show putative aberrations on other chromosomes that I missed using the HumArray 2.0 potentially due to the lack of clone coverage for these regions. Using Query B4 with Table B2,1 identified 3 potential multi-clone aberrations in the proband of trio 456. The first aberration is located on chromosome 8, between 86.2 Mb to 86.5 Mb where seven clones are implicated in this aberration. The second aberration is on chromosome 11 between 61.0 Mb and 61.3 Mb. Within the chromosome 8 aberration, there are six genes. The final aberration is on chromosome 16 between 32.5 Mb and 35.0 Mb where six clones are aberrant. None of the genes in the chromosome 8 region are involved in brain development, but the sodium channel associated protein (LRRCC1) may be involved in brain function (Table 3.3). The chromosome 11 aberration includes synaptotagmin VII (SYT7), which is involved in synaptic exocytosis and neurotransmitter release (Rao et al., 2004). The chromosome 16 aberration contained only predicted and provisional genes when viewed with the RefSeq track on the UCSC Genome Browser (Karolchik et al., 2003). I also identified a single clone on chromosome 11 with a log2ratio of -2.9. The genes (SLC1A2, CD44) located within this deletion of chromosome 11 are listed in Table 3.3. 30 FIGURE 3.3. MIA G R A P H OF SMRT A R R A Y DATA. Most clones (24336/24550 = 99.2% of autosomal clones) show no copy number difference between the trio 456 proband and male reference DNA. The X and Y chromosome clones are on the far right of the graph and verify that known copy number differences are detectable on this array platform. 31 T A B L E 3.3. GENES L O C A T E D WITHIN SMRT A R R A Y ABERRATIONS FOR PROBAND FROM TRIO 456. Gene Full Name Chromosome Region RefSeq ID LRRCC1 sodium channel associated protein 2 8 86206716 86245072 N M . .033402.2 E2F5 E2F transcription factor 5 8 86276877 86314002 N M . .001951.2 CA13 carbonic anhydrase XIII 8 86345259 86383554 N M . .198584.1 CA1 carbonic anhydrase I 8 86427709 86477594 N M . .001738.1 CA3 carbonic anhydrase III 8 86537710 86548526 N M . .005181.2 CA2 carbonic anhydrase II 8 86563498 86580973 N M . .000067.1 SLC1A2 solute carrier family 1 member 2 11 35229329 -35397372 N M . .004171.2 CD44 CD44 antigen isoform 5 precursor 11 35116993 •35210524 N M . .001001392.1 SYT7 synaptotagmin VII 11 61039362 61104874 N M . .004200.2 FEN1 flap structure-specific endonuclease 1 11 61316726 •61321284 N M . .004111.1 FADS1 fatty acid desaturase 1 11 61323675 61340886 N M . .013402.3 FADS2 fatty acid desaturase 2 11 61352289 61391401 N M . .004265.2 3.2.3 Reference Hybridisation Because the chromosome 13 aberration was not detected by the higher resolution SMRT array, it is a putative artifact. To further explore this probability, three self hybridizations (male reference D N A versus itself) were performed on the HumArray 2.0. One of the three reference hybridizations again showed a multi-clone chromosome 13 aberration (Figure 3.4). The aberration spans clones RP11-234M13 through RP11-94F7, which matches the trio 456 proband aberration found with the HumArray 2.0 and confirms the presence of a chromosome 13 artifact. The coefficient of variation (V; also called relative variability) was calculated for each of the reference hybridizations (Table DI). A statistical comparison between the three coefficients of variation showed that V for the reference hybridization with the chromosome 13.aberration is significandy different from the other two. This suggests that the reproducibility of the array results is affected by the artifact. The reason why chromosome 13 hybridization results are 32 unreliable is not clear. Due to the sporadic nature of this artifact, loci on chromosome 13 have been excluded from subsequent analysis. l.Sr-l .Oh 0.5 O-Oh • < 2.0 sigmi. • > 2.0 sigmi. * > 4.0 sigmi. (6 K CD O 0.5 -1.01 -1 .5 -2.Q[ log(3/2) Hlog(l/S) PositionID FIGURE 3.4. MIA G R A P H OF R E F E R E N C E HYBRIDIZATION. This graph is the output of a male vs. male reference hybridization. The aberrant clones circled in black are from chromosome 13. 33 3.3 REAL TIME QUANTITATIVE PCR 3.3.1 Clones Chosen for Probe Design Genomic regions for RTqPCR analysis were chosen from the aCGH-detected aberrations (TABLE 3.2). Specifically, the absolute values for the three log2ratios of an aberrant locus (one from each of three arrays per trio) were used to determine an overall log2ratio sum. For example, in Table 3.4 three loci with the absolute values for the three corresponding log2ratios have been shown (abs_log2X). The difference between each of the two highest ratios and the lowest ratio (diff_l and diff_2) were summed and used to determine the log2ratio "ranking" of the locus. A high ranking takes into account that (1) there should be a large difference between the highest and lowest ratios, and/or (2) the lowest ratio is close to zero. Three loci were chosen for analysis based on the rank and gene content (Table 3.5). Each locus was investigated for gene content and one gene per locus was chosen for primer/probe design. The choice of gene was made based on potential function in the brain. The initial ~500bp region for protein kinase C Seta (PRKCZ) incorporated the second to last intron (chrl:2,144,215-2,144,770). Research with rats indicated that the PRKCZ gene product interacts with a potassium channel in brain via another protein, ZIP1 (Gong et al, 1999). The lipoprotein A (LPA) region encompassed all of the second exon and part of the second intron (chr6:161,037,320-161,037,872). A recent study found an increased level of Lp(a) protein in patients with SCZ, major depression and BPD when compared to healthy controls, and suggests that this protein may contribute to cardiovascular risk in psychiatric patients (Emanuele et al., 2006). Finally, the region for sjncfinger protein 37 homolog (ZFP37) was from the last intron (chr9:l 12,886,269-112,886,819). Investigation of ZFP37 in mice suggests that this gene encodes for a protein that participates in the structural integrity of neuronal nuclei (Payen et al., 1998). 34 T A B L E 3.4. LOG2RATIO R A N K I N G FOR LOCI. Locus abs_log2l abs_ log22 abs_ log23 diff_l diff_2 Rank RP11-43B19 0.4839 0.9738 0.3144 0.1695 0.6594 0.8289 RP11-82D16 0.0165 0.4661 0.1982 0.4496 0.1817 0.6313 RP11-95J4 0.2596 0.4249 0.0716 0.188 0.3533 0.5413 abs = absolute value Rank - sum of diff_l and diff_2 T A B L E 3.5. REGIONS CHOSEN FOR R E A L TIME QUANTITATIVE PCR V A L I D A T I O N . Locus Genes3 Full Nameb Potential Brain Function RP11-43B19 LPA lipoprotein A Cardiovascular risk in psychiatric patients RP11-82D16 PRKCZ, SKI protein kinase C %eta Targets potassium channels in brain RP11-95J4 ZFP37,SLC31A2 %incfinger protein 37 homolog Structural protein in rat neuronal nuclei aDNA from the genes in boldface text was used for RTqPCR primer/probe design. bFull name of chosen gene. 3.3.2 Determination of Copy Number Change I considered two methods for detemuning copy number changes in the RTqPCR experiments: the normal range method (NRM), and the standard deviation method (SDM). Using the N R M the range of ratios acquired for fathers using the X chromosome G6PD probe (0.73-1.33) was used as the normal range of variation in my assays for a gene with one copy in the genome. In the SDM, the standard deviation of all the copy number ratios for each gene was used to determine whether an individual sample for a particular gene is aberrant. For example, the average copy number ratio (1.093) and the standard deviation (0.167) for the PRKCZ locus would be used to determine whether an individual sample copy number ratio was aberrant. The copy number of the individual sample would need to be the mean ± 2SD to be identified as aberrant. However, the genes tested by RTqPCR showed a high degree of variation around the normal copy number ratio of 1. These could be real aberrations, but the SDM would not identify them because the real differences had inflated the SD. For this reason I used the normal range method 35 Based on the N R M , ratios for the other genes were categorized as amplifications, deletions or normal if they fell within the ranges of >1.33, <0.73 or 0.73-1.33, respectively. Figure 3.5 is a graph of the G6PD ratios for each father showing the ranges. Male proband ratios for G6PD were all contained witliin the range of 0.73-1.33. Using this range, a number of aberrations were identified in the trio samples (Table 3.6). C 0 N ( D r - O T - 0 ) N T - S 0 ) T - T - L n 0 0 ^ - < D C D C M T -c o o o o o c M c o r o m c D Q O ^ ^ r o O i - ^ i n c D O T - T - T - C \ I C N C N C N C N C \ I C N J C O C O 0 0 r O ^ f ' ^ - ' ^ ' * T f C D Trio FIGURE 3.5. G6PD RATIOS FOR FATHER SAMPLES. Each bar represents the G6PD copy number for a father sample. Error bars represent the standard deviation of the two replicates done for each sample. T A B L E 3.6. TYPES OF ABERRATIONS IDENTIFIED IN E A C H G E N E BY RTQPCR. Numbers include all samples tested. Aberration PRKCZ LPA ZFP37 Amplifications 4 9 5 Deletions 0 3 0 36 3.3.3 Aberrant Copy Number All samples were typed correcdy for gender with the G6PD probe. These results are consistent with the know gender of the subject (Figure 3.6). One sample, typed as female on the sample key, presented as male (proband trio 261, ^ ) . This discrepancy was identified using both aCGH and RTqPCR and is likely due to a clerical error. r 0 N ( D T - o ^ - 0 ) N T - N 0 ) T - T - i n 0 0 ^ - C D ( O C M T -C D 0 0 Q O 0 v i r 0 C 0 l O C D 0 ) O T - ^ 0 ) O i - ^ m ( D O Trio FIGURE 3.6. G6PD COPY N U M B E R RATIOS. Error bars represent the standard deviation of the two replicates done for each sample. 37 By RTqPCR, three of 20 trios show a copy number increase at the PRKCZ locus (Figure 3.7). Trio 163 has an affected mother, while trio 257 has an affected father. Trio 239 has an affected proband and mother. The amplification "allele" from the mother was inherited by the proband. The trio (231) that showed the aCGH aberration did not show an RTqPCR-detected aberration. 163 239 257 Trio FIGURE 3.7. PRKCZ COPY N U M B E R RATIOS. Samples with copy number aberrations for PRKCZ are labeled with 4r. Error bars represent the standard deviation of the two replicates done for each sample. 38 Nine of 20 trios were found by RTqPCR to have copy number changes in the LPA locus (Figure 3.8). Of the affected probands, 2 had copy number decreases (297, 414) and 3 showed amplifications (257, 309, 395). The 2 mother samples (257, 395) showed ampUfications. One father sample (601) showed a deletion while four father samples (201, 261, 309, 341) had amplifications. From these data, it was evident that two probands (257, 395) inherited amplifications from their mother, one proband (309) inherited an amplification from his father and two probands (297, 414) may have spontaneous deletions. FIGURE 3.8. LPA COPY NUMBER. Samples with copy number aberrations are labeled with ^ . Error bars represent the standard deviation of the two or three (trios 257, 297, 309 and 341) replicates done for each sample. The copy number ratios for trios 257, 297, 309 and 341 are average values from the LPA replication experiments (see FIGURE 3.11). 39 Five of 20 trios showed copy number changes in ZFP37 (Figure 3.9). Al l aberrations were amplifications. One proband (311), one mother (201) and three fathers (257, 261, 341) have an amplification. According to these data, the proband amplification was a spontaneous change. 201 257 261 311 341 Trio FIGURE 3.9. ZFP37 COPY N U M B E R RATIOS. Samples with copy number aberrations for ZFP37 are labeled with At. Error bars represent the standard deviation of the two replicates done for each sample. 40 A probe for the synaptotagmin VII (SYT7) gene (designed by G. Wilson as described in Methods), was used with trio 456 (primer and probe sequences are in Table Cl) . This trio showed a possible amplification on chromosome 11 in the proband sample using high density aCGH. However, the SYT7 RTqPCR data showed no aberration in any of the trio 456 samples (Figure 3.10). 1.2 1 S °-8 CD "I 0.6 C L O O 0.4 0.2 0 Father — : T 1 1 I I Mother Sample Proband FIGURE 3.10. SYT7 COPY N U M B E R RATIO IN TRIO 456. Error bars represent the standard deviation of the three replicates done for each sample. 41 3.3.4 Replication The four trios that showed an aCGH aberration in clone RP11-43B19, the LPA locus, were tested a second time by RTqPCR for replication purposes (i.e. to confirm that the RTqPCR finding validated the aCGH results). The replication results show strong concordance with the initial RTqPCR results for LPA. Figure 3.11 shows a comparison between the first and second experiment for the four trios with the LPA probe. Only four samples did not show the same copy number between both experiments (257 mother, 257 proband, 297 mother and 309 father). The average copy number ratio between the two experiments was used for analysis of LPA. I LPA Exp 1 I LPA Exp 2 CD -CZ 03 LL. u o CM CO o m CM T3 CZ co 1 nd L i CO nd CO .CZ ca -CZ -*—1 CO - Q TO o - Q 2 LL 2 O Q _ r^ - Q _ rx CT> CM CD CD m CD CM o CM CM CO CO o CD O CO CD "ca LL. CD CD CO CO O ^r c o CO o -51-CO CO -+—« CO co Sample FIGURE 3.11. REPLICATION OF LPA COPY N U M B E R RATIO IN FOUR TRIOS. Error bars represent the standard deviation of the two (LPA Exp 1) or three (LPA Exp 2) replicates done for each sample. The horizontal black lines indicate the thresholds for aberrant copy number. Ratios between the lines are normal copy number. 42 3.4 COMPARISON OF A C G H A N D RTQPCR The evaluation of aCGH and RTqPCR data must take into account the way in which each method measures copy number. The ratio from aCGH represents a competition between two differentially labeled DNAs such that in trios, the aCGH-defined copy number of each individual is relative to the other people in the family and the actual or absolute copy number may be ambiguous. In the absence of other information, copy number aberrations can be inferred by parsimony. In contrast to aCGH, the values produced from RTqPCR analysis are a quantitative measurement of the copy number in each sample relative to a reference D N A . The RTqPCR-defined copy number is a ratio when compared to a reference D N A , but the values within a trio are absolute with respect to each other. In some cases, results from RTqPCR may confirm the most parsimonious interpretation of an aCGH result, but in other cases the RTqPCR may confirm the less parsimonious interpretation. The following is an interpretation of aCGH copy number at each locus tested by RTqPCR. PRKCZ (clone RP11-82D16) No aberrations were found by RTqPCR in trio 231, so this may be a false positive aCGH finding. Other considerations will be presented in the Discussion section. LPA (clone RP11-43B19) Trio 257 shows the father/proband hybridization with reduced signal and the mother/proband hybridization with increased signal (Figure 3.12). The putative aberrations(s) could be a deletion in the father or amplifications in the mother and proband. The most parsimonious explanation based on the aCGH data alone is a deletion in the father. However, the RTqPCR data indicates 4 3 that there are two separate amplifications, one in the mother and one in the proband, rather than a deletion in the father (Figure 3.12). For trio 297, aCGH showed a decreased ratio in the proband/father hybridization and an increased ratio in the proband/mother hybridization. This result could indicate a proband deletion or amplifications in the mother and father samples. However, the RTqPCR-defined copy number was consistent with a single copy of this locus in the proband. Thus, taken together, the aCGH and RTqPCR data are consistent with a proband deletion (Figure 3.13). In trio 309, aCGH detected a decrease in the mother compared to the proband, and a decrease in the mother when compared to the father. However, this could also be interpreted as amplifications in the father and proband. Subsequendy, the RTqPCR results show amplifications in the proband and father samples (Figure 3.14). The aCGH results for trio 341 showed a decrease in the mother, compared to the proband and a decrease in the mother as compared to the father. As in trio 309, these results could be interpreted as amplifications in the proband and father. The RTqPCR results showed an amplification in the father sample. Given that the proband sample does not contain an RTqPCR-detected amplification, the results for this trio are inconclusive (Figure 3.15). ZFP37 (clone RP11-95J4) Using aCGH, the trio 261 mother showed a decrease in copy number when compared to the father, and a decrease when compared to the proband. This result could be interpreted as amplifications in the proband and father. However, the RTqPCR results showed amplification in the father sample. Taken together, the aCGH and RTqPCR results are inconclusive (Figure 3.16). 44 a 0.6 0.4 0.2 -0.2 -0.4 -0.6 J 0.6 0.4 0.2 0 -0.4 -0.6 RP11-43B19 133000 140000 145000 150000 155OQ0' 160000 165000 Base Position (kb) * 1.5 9 "S 13SJ000 140000 145000 150000 15500\ 160000 165000 £- -0 .2 o o 0.5 LPA RTqPCR Proband RP11-43B19 Mother Sample Father Base Position (kb) 0.6 -i 0.4 0.2 0 ,-0.2 -0.4 -0.6 RP11-43B19 133000 140000 145000 150000 155000 160000 165000 Base Position (kb) FIGURE 3.12. TRIO 257. The locus (RP11-43B19) which contains LPA is labeled on the aCGH graphs. Error bars represent the standard deviation for the triplicate spot (aCGH) or duplicate sample (RTqPCR). The log2ratios for RP11-82D16 that were identified as aberrant are labeled with arrows, (a) aCGH results from the proband-mother hybridization (there is no data from this array for the left-most clone), (b) aCGH results from the father-proband hybridization, (c) aCGH results from the mother-father hybridization, (d) RTqPCR results for trio 257 with the probe for LPA. The aCGH and RTqPCR results are consistent with amplifications in the proband and mother samples. 45 133000 Base Position (kb) LPA RTqPCR RP11-43B19 * 1.5 o O 0.5 Proband Mother Sample Father Base Position (kb) RP11-43B19 fc= 133000 140000 145000 150000 155000 160000 165000 Base Position (kb) FIGURE 3.13. TRIO 297. The locus (RP11-43B19) which contains LPA is labeled on the aCGH graphs. Error bars represent the standard deviation for the triplicate spot (aCGH) or duplicate sample (RTqPCR). The log2ratios for RP11-82D16 that were identified as aberrant are labeled with arrows, (a) aCGH results from the proband-father hybridization, (b) aCGH results from the mother-proband hybridization, (c) aCGH results from the father-mother hybridization, (d) RTqPCR results for trio 297 with the probe for LPA. The aCGH and RTqPCR results are consistent with a deletion in the proband. 46 a 0.4 -0.6 J 1 Base Position (kb) b (j L P A RTqPCR -0.4 -0.6 J Base Position (kb) FIGURE 3.14. TRIO 309. The locus (RP11-43B19) which contains LPA is labeled on the aCGH graphs. Error bars represent the standard deviation for the triplicate spot (aCGH) or duplicate sample (RTqPCR). The log2ratios for RP11-82D16 that were identified as aberrant are labeled with arrows, (a) aCGH results from the proband-father hybridization, (b) aCGH results from the mother-proband hybridization, (c) aCGH results from the father-mother hybridization, (d) RTqPCR results for trio 309 with the probe for LPA. The aCGH and RTqPCR results are consistent with amplifications in the father and proband samples. 47 FIGURE 3.15. TRIO 341. The locus (RP11-43B19) which contains LPA is labeled on the aCGH graphs. Error bars represent the standard deviation for the triplicate spot (aCGH) or duplicate sample (RTqPCR). The log2ratios for RP11-82D16 that were identified as aberrant are labeled with arrows, (a) aCGH results from the mother-proband hybridization, (b) aCGH results from the father-mother hybridization, (c) aCGH results from the proband-father hybridization, (d) RTqPCR results for trio 341 with the probe for LPA. Taken together, the aCGH and RTqPCR results are inconclusive. 48 Base Position (kb) 0.6 0.4 0.2 0 1 •0.2 -0.4 -0.6 -0.8 RP11-95J4 Base Position (kb) 1 1.5 — I I I I ' j— § 1111600 111800 112000 112200 112400 112600 112800 113000 113200 z 1 0.5 ZFP37 qPCR r# i t Proband Mother Sample Father Base Position (kb) FIGURE 3.16. TRIO 261. The locus (RP11-95J4) which contains ZFP37 is labeled on the aCGH graphs. Error bars represent the standard deviation for the triplicate spot (aCGH) or duplicate sample (RTqPCR). The log2ratios for RP11-95J4 that were identified as aberrant are labeled with arrows, (a) aCGH results from the mother-proband hybridization, (b) aCGH results from the father-mother hybridization, (c) aCGH results from the proband-father hybridization, (d) RTqPCR results for trio 261 with the probe for ZFP37. Taken together, the aCGH and RTqPCR results are inconclusive. 49 3.5 INHERITANCE AND DNA COPY NUMBER ABERRATIONS Based on the three conclusive results between the aCGH and RTqPCR data, each person in a trio was typed for the "alleles" they carried. I used this to determine whether a proband aberration was inherited from the parents or the result of a spontaneous event. Trio 257 showed amplifications in the proband and mother samples by aCGH and RTqPCR (Figure 3.12). The alleles in the father would be two normals (N), while the alleles carried by the proband and mother would be one N and one amplified (A). These results indicated an amplification in the proband inherited from the mother. The trio 297 aCGH and RTqPCR results showed a deletion in the proband sample (Figure 3.13). Both parents carry two N alleles, so the deleted (D) allele in the proband is from a spontaneous event. The aCGH and RTqPCR results from trio 309 (Figure 3.14) showed the proband and father carrying one N and one A allele each, while the mother has two N alleles. This indicates an amplification in the proband inherited from the father. The transmission/disequilibrium test (TDT) (reviewed in Schaid, 1998 ) was considered. This test determines whether there is unequal transmission of alleles from heterozygous parents to an affected offspring (reviewed in Schaid, 1998 ). There were only 2 trios (257 and 309) that had heterozygous parents and showed consistent detection of the aberration using aCGH and RTqPCR. Therefore, the TDT would not have the power needed to identify association between an aberration and psychosis.. In addition, heterozygosity of the parent can be ambiguous is there is more than one extra copy of the gene. For example, if there were two extra copies, of the gene it is unclear whether those two extra copies are on the same chromosome or not (i.e. the same allele). The TDT is based on y2 statistics (reviewed in Schaid, 50 1998 ) and the sample size necessary for this type of testing (at a — 0.05, df — 2 and a medium effect size) is N = 107 (Cohen, 1992). 4.0 DISCUSSION The purpose of this project was to find candidate genes for psychosis that could be used as therapeutic targets or in the development of diagnostic tools. I used array comparative genomic hybridization for the initial genome scan and found 11 copy number differences at seven loci. I tested three of the seven aberrant loci using real time quantitative PCR. RTqPCR was used to verify the presence of an aberration and resolve the ambiguity of aCGH results. Al l 20 trios were tested with the three RTqPCR probes. Eighteen amplifications (mcluding all loci tested) and three deletions (only in LPA) were found using RTqPCR. Of the six trios that showed copy number differences by aCGH (within the RTqPCR-tested loci), three showed copy number changes consistent with the results of the RTqPCR assays and the other three were inconclusive. The most intriguing result from this study is the variation seen in the LPA gene. Recendy, the Lp(a) protein has been found at significandy increased plasma levels in patients with SCZ, major depression and BPD when compared to healthy control individuals (Emanuele et al., 2006). Although Emanuele et al. (2006) suggest a link between cardiovascular disease and SCZ, the association could be due to any number of factors. While the present study does not show a significant association between the LPA locus and psychosis, it is interesting that this locus, already implicated in psychiatric disease, is the most variable region of the genome in this trio set. This type of study represents the potential for development of a diagnostic test for psychiatric disorders. A larger case-control sample size to replicate the plasma protein findings is imperative. To investigate the association of copy number variation in LPA with psychiatric 51 disease, a larger number of trios and the transmission/disequilibrium test (TDT) could be used. To detect association (with 80% power) of a disease with an aberrant copy number, the study would have to include 107 families (for a gene of medium effect and a = 0.05, df = 2) (Cohen, 1992). A case-control design could also be used. This type of experiment would have more power because all samples could be included (i.e. homozygous subjects would not be excluded). A disadvantage of this study would be population stratification. Matching the ethnicity of cases and controls would ameliorate this problem. In addition to assessing individuals for LPA copy number, investigating the levels of mRNA and protein could uncover a possible correlation with aberrant copy number. The results from the family 456 proband SMRT array hybridization (Figure 3.3) and the HumArray 2.0 reference hybridization (Figure 3.4) confirm that the potential chromosome 13 aberration detected in family 456 by the HumArray 2.0 is an array artifact (Figure 3.2). However, this artifact does not routinely appear on the HumArray 2.0. Of the 63 arrays completed, only 3 arrays showed the chromosome 13 artifact. The artifact encompasses all of chromosome 13 when viewed by MIA graphical output, and MIA breakpoint analysis identified the whole chromosome as aberrant. Results from these arrays were excluded from further analysis. The artifact could be caused by (1) properties of the slide, or (2) properties of the spotted D N A . The spotted D N A is the most likely cause of the false positive signal because the only regions affected on the slide contain D N A from chromosome 13, and the clones are not segregated on the array by genomic position. To verify this it would be possible to re-generate the spotting solution for all chromosome 13 clones and a number of control loci from other chromosomes. Al l of this D N A , including the original spotting D N A from the HumArray could be printed on the slides and tested for artifacts. If the new chromosome 13 D N A did not show the same artifact pattern, then it would be clear that the old D N A was a problem. 52 However, this experiment is probably unnecessary because the chromosome 13 artifact happens only rarely and is recognizable when it does occur. The results from the SMRT array suggest using a higher density array as a way of exploring copy number variation in the trios. Any regions of genomic D N A not represented by the HumArray 2.0 could be assessed for copy number changes using the SMRT array. In addition, using a larger sample set of trios could identify more aberrations. One aspect to consider when investigating inherited and spontaneous aberrations is the type of tissue used. If spontaneous aberrations occur later in development, it is possible they will be restricted to specific tissues. SCZ and BPD are brain-specific disorders, so there is a possibility that important disease-specific changes in D N A copy number may be restricted to brain tissue. Post-mortem brain D N A used with aCGH (Wilson et al., 2006a) allows identification of chromosomal aberrations in the brain. However, without D N A from other tissues or the parents, we cannot chscriminate between inherited and spontaneous aberrations. The same holds true when using lymphocyte D N A only, as in the present study. These samples allow discrimination between inherited (present in the proband and a parent) and spontaneous (present in proband sample only) chromosomal aberrations in lymphocytes, but do not allow identification of brain-specific aberrations. A comparison between lymphocyte (or other tissues) and brain D N A will identify the differences in copy number between these tissues. If the copy number between tissues is significandy different for more loci perhaps the reason is based on gene function. In certain tissues, particular genes may be under increased selective pressure to remain at a normal copy number. However, a relaxation of this pressure may lead to an increase-in copy number changes. This could also lead to formation of multiple cell populations, within a tissue, that differ in copy number. 53 Six trios were analyzed for consistency between aberrations detected by aCGH and tested by RTqPCR. Three trios showed consistency when the copy number changes were compared. For example, trio 257 showed an aCGH-detected amplification in the mother and proband samples (Figure 3.12). The RTqPCR results showed that the mother and proband samples have increased copy number of the LPA gene (Figure 3.8 and Figure 3.12). Taken together, the aCGH and RTqPCR results are consistent with a copy number increase in the mother and proband samples. Overall, the results suggest that aCGH and RTqPCR have a decent concordance rate. This suggests that the copy number changes are not artifacts. A possible explanation for the aCGH-detected copy number changes not consistent with RTqPCR could be related to the differences in detection between the two methods. Array comparative genomic hybridization and real time quantitative PCR are two very different methods for assessing D N A copy number changes. The main difference is the size of the genomic region each method assesses; aCGH investigates the genome using, on average, 150 kb regions, while RTqPCR analyzes 100 bp sequences. Therefore, RTqPCR has an increased likelihood of finding aberrations at a single small locus than aCGH at a single large locus. For example, the signal from aCGH for a single clone is averaged over 150,000 bp. A small section of that region with aberrant copy number will never be deemed significant. On the other hand, RTqPCR could identify the difference in that small region. Both aCGH and RTqPCR as performed here, are unable to resolve mixed cell populations. The fact that D N A from mixtures of cells has been analyzed limit the interpretation of these results. Many of the ratios observed by RTqPCR do not represent whole copy number changes. For example, the ratio may be between 2 and 3 copies. It is unlikely that inaccurate measurements are the cause, given the reproducibility of the RTqPCR results (Figure 3.11). Instead, this could be explained by the D N A . Since the results from the LPA replication 5 4 experiment do not suggest inaccurate measurements, perhaps, the samples with a ratio between 2 and 3 copies have lymphocytes that are comprised of cells with 2 copies of the gene of interest and cells with 3 copies of the gene. The division in unlikely to be this clean, but it demonstrates the possibility of multiple cell populations. Another example of populations of cells that differ in copy number is cancer. A study of ovarian cancer found that serous tumours contain a higher proportion of aneuploid cells than inclusion cysts and surface epithelium (Korner et al, 2005). The authors propose that aneuploid cells in the cysts and epithelium may be the precursors of ovarian tumours. These results underscore the importance of understanding the D N A copy number composition of normal tissue, and how it can lead to disease. Using spectral karyotyping (SKY), fluorescence in situ hybridization (FISH) and flow cytometry for D N A content, it is possible to estimate the number of different populations present. A potential problem with these techniques is that they can only differentiate between cells with differing amounts of D N A or an aberrant number of large loci. Cells differing by changes in single or multiple genes may not be identified. In addition, the proportions estimated for lymphocyte populations may not be an accurate estimation for brain cell populations. However, the experiments using SKY, FISH and flow cytometry are still valid to understand the types of change within a single cell type. A study investigating whole chromosome copy number changes in mice found a significandy higher rate of aneuploidy in embryonic neuroblasts when compared to adult lymphocytes (Rehen et al, 2001). The researchers found 33% aneuploid neuroblasts and only 3% aneuploid adult lymphocytes. In addition, they found that adult mouse neurons showed lower rates of sex chromosome aneuploidy, suggesting that aneuploid cells in the brain are selected against. Given that we do not have human embryonic neuroblasts to examine, we can only speculate as to the rate of aneuploidy in human brain. However, if the findings in mice can be extrapolated to humans, this may be important in the context of human 55 psychiatric disease. Perhaps certain aneuploid cells in the human embryonic brain are not lost during development, but contribute to disease development or risk. Using lymphocyte D N A , we cannot identify these cells. Even using post-mortem brain tissue may not uncover the aneuploid populations. Comparing the copy number profiles of different parts of the brain, especially those important in SCZ and BPD, may prove useful for finding pathogenic changes. The design and development of future studies may include other methods of D N A copy number detection. A higher density array for C G H would enable better detection of aberrations. With the HumArray 2.0, any aberrations in the genomic D N A not represented by clones on the array would be missed, and finding multi-clone copy number changes is unlikely. In addition, the approximate breakpoints of aberrations could be mapped by using a higher density array. Other methods of copy number detection include the GeneChip Mapping Arrays from Affymetrix, which are designed for genome-wide linkage and association (Klein et al., 2005), and copy number studies (Zhou et al, 2004). Representational oligonucleotide microarray analysis (ROMA) is another oligonucleotide probe-based method (Lucito et al., 2003). The Affymetrix GeneChip differs from aCGH and ROMA in that individual arrays must be hybridized for each sample and reference DNA. This means that the GeneChip does not represent a direct evaluation of competition between two labeled samples of D N A . Both ROMA and the GeneChip contain repeat-free oligonucleotides as probes, and therefore do not require the use of Cot-1 D N A for blocking repetitive sequences. Cot-1 D N A is expensive and can limit the number of arrays done with C G H . ROMA and the GeneChip have higher resolutions than the HumArray. ROMA has an upper limit to resolution because of the limited number of BgAI fragments in the human genome, and higher resolution arrays for C G H are available (Ishkanian et al, 2004). However, BAC arrays for C G H will not achieve the resolution of oligonucleotide arrays because of the large probe size. 56 6.0 CONCLUSIONS In the present study, I investigated D N A copy number changes in trio sets (proband, mother, father) in which the probands have been diagnosed with psychosis. This was an exploratory study using array C G H with 1.4 Mb resolution, I completed low density hybridizations for 20 trio sets. To confirm changes identified by the arrays, I used RTqPCR. The results show a good concordance between methods. Although the two methods were not in 100% agreement, the practice of using them in combination to find aberrations remains valid. aCGH (especially in a high density format) is a satisfactory method for pinpointing regions of the genome that vary between members of a family, or between control and references samples. RTqPCR, if used after aCGH, can further refine the characteristics of a locus. Taken together, the two methods work well to identify and validate copy number changes. An intriguing result was found by these methods. The most abundant aberration in these trios was in the LPA gene, previously shown to be associated with psychiatric disorders. Further evaluation of D N A copy number at this locus could, if findings are positive, lead to a diagnostic test. Finally, this study was important for determining the correlation between two techniques used to determine copy number and provides more insight into human copy number variation. 57 7.0 REFERENCES (2000) Diagnostic and Statistical Manual of Mental Disorders: DSM IV-TR. Washington: American Psychiatric Association. 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Trio Identification Gender Age Ethnicity 163 Male 22 Caucasian 187 Male 23 Caucasian 196 Male 26 Caucasian 201 Female 20 Caucasian 220 Female 21 Caucasian 231 Male 23 Caucasian 239 Male 19 Caucasian 257 Female 18 European Caucasian 261 Female 24 Caucasian 297 Male 20 Caucasian 309 Male 21 Caucasian 311 Female 18 N / A 341 Male 18 Caucasian 395 Male 19 Asian 408 Male 20 N / A 414 Female 21 N / A 446 Male 20 European Caucasian 456 Female N / A N / A 462 Male 21 N / A 601 Female N / A N / A 64 APPENDIX B. MYSQL DATABASE. T A B L E B l . DESCRIPTION OF TRIOS T A B L E IN MYSQL DATABASE. Field Type NuU Key Default Extra row__id int(ll) PRI N U L L auto_increment clone_id varchar(25) YES N U L L trio_id varchar(5) YES N U L L cy3_dna varchar(5) YES N U L L cy5_dna varchar(5) YES N U L L slide tinyint(4) YES N U L L array tinyint(4) YES N U L L log2_ratio decimal(7,4) YES N U L L num_reps int(ll) YES N U L L log2_int decimal(7,4) YES N U L L log2_stdev decimal(7,4) YES N U L L log2_uncert decimal (7,4) YES N U L L away decimal(7,4) YES N U L L T A B L E B2. DESCRIPTION OF TRIOS_HD T A B L E IN MYSQL DATABASE. Field Type Null Key Default row_id int PRI N U L L clone_name varchar(25) YES N U L L trio_id varchar(5) YES N U L L test_dna varchar(5) YES N U L L ref_dna varchar(5) YES N U L L position int YES N U L L chromosome int YES N U L L start_pos int YES N U L L stop_pos int YES N U L L num_replicates int YES N U L L log2_intensity decimal(7,4) YES N U L L log2_ratio decimal(7,4) YES N U L L log2_stdev decimal(7,4) YES N U L L log2_uncertainty decimal(7,4) YES N U L L away decimal(7,4) YES N U L L 65 Q U E R Y B l . CRITERIA FOR FINDING A B E R R A N T CLONES F R O M H U M A R R A Y 2.0 DATA. SELECT c.clone_name, c.chromosome, exposition, t.trio_id, t.cy3_dna, t.c y5_dna, t.away, t.log2_ratio F R O M trios t, clone c W H E R E away > 3 A N D log2_stdev < 0.2 A N D log2_int > 10 A N D chromosome < 23 A N D t.clone_id = c.clone_name; Q U E R Y B2. CRITERIA FOR C A L C U L A T I N G INTER-ARRAY VARIABILITY. SELECT clone_id, std(log2_ratio) F R O M trios W H E R E clone_id = 'RP11-122N11' or clone_id = 'RP4-693L23' or clone_id = 'RP11-82D16' or clone_id = 'RP11-60B6' or cloneJd = 'RP11-1P3' or clone_id = 'RP11-88C10' or clone_id = •RP11-43B19' or clone_id = 'RP11-95J4' or clone_id = 'RP11-88L18' or clone_id = 'RP11-122P17' or clone_id = 'RP11-31N23' or clone_id = 'RP11-11C17' or clone_id = 'RP11-182E4' or clone_id = 'RP11-205J24' or clone_id = 'RP11-234M13' or clone_id = 'RP11-189K9' GROUP BY clone_id; Q U E R Y B3. CRITERIA FOR C A L C U L A T I N G INTRA-ARRAY VARIABILITY. SELECT trio_id, slide, array, Cy3_dna, Cy5_dna, std(log2_ratio) F R O M trios GROUP B Y trio_id, slide, array ORDER B Y trio_id, slide, array; Q U E R Y B4. CRITERIA FOR FINDING A B E R R A N T CLONES F R O M TRIO 456 H I G H DENSITY A R R A Y DATA. SELECT clone_name, position, trio_id, test_dna, ref_dna, log2_ratio, away, chromosome, start_pos, stop_pos F R O M trios_hd W H E R E away > 3 A N D log2_stdev < 0.2 A N D log2_intensity > 10 A N D chromosome < 23; 6 6 APPENDIX C. QUANTITATIVE PCR. >chrl:2144215-2144770 C A G A T C C C C A G A C G A C T C A G A T G C A C G G A C A C C C A G A T G A C A T GGpJjggg GTGGTTTGGGCACCAGGAGCCTGGGAGTCCCATGCTG'CCC .CCJAGGGCACr ACCTCCTGGGCCCAGCCCTGCATCCGGTGGCAGGGCTCACCGTCATCACC CCAACAGTGCAGGGTGGTCTCAGGGACCTCCTCTCATCATTGCCRAGaac t g g c t c c a g g a t g t t t c c a t g t g g c c g g c t a g t a t g g c c a a a g t g g a c c c t g g c g t g c t g t c c c c t t g g a c g c c t c c a g g c c c t g c c c a g c a c g t g g G G C TCGTCCATTCTGTGCCTGACCATGCTCTGCCATGCGGGGCCTAGCCCAGI | | ^ G | A G C C C T G C T G C T T C T C C C C A C C C C A P C ; I ^ | G C C A C C T C C A C C A A G CCACCAGCATCCTGCCTGGCCCTACGGACAGCAGGGTCGTCCTGTGTCCA A A A G C C FIGURE C l . R E G I O N OF CHROMOSOME 1 (RP11-82D16, PRKCZ) FOR RTQPCR ANALYSIS. Underlined regions are 4 mono-nucleotide stretches, highlighted^regions are >4 mono-nucleotide stretches and boldface regions are 100% identical to another genomic segment. — S B . SUB-REGION 2. sub-region 3. 67 T A B L E CI. PRIMER A N D PROBE SEQUENCES. A L L SEQUENCES A R E WRITTEN AS 5'-»3'. Locus Probe (6FAM N N N N N M G B NFQ) Forward Primer Reverse Primer PRKCZ C T G G A G C C A G T T C T T G G G G A C C T C C T C T C A T C A T T G C C G G C C A C A T G G A A A CATC LPA T C A G G T G G G A G T A C T G C C T T C T G C G T C T G A G C A T T G C G T G G C A G C T C C T T A T T G T T A T A C G A ZFP37 T C T C C A T G G G C A C A G T T G GCTCCTGCAGCCTATACTATATTACC G T T G G A C A T C T T G G T T T G A G T C A G A SYT7 C A G T A C C T C C A C A A C C C G A C C C 1'1'1'1'CTCAACCCACAGA C T G T G G C T G G A G C T G C T A PGT CCATCCATGTCCTCATCTC A T C C C C A A A G C A C C T G G T T T A G A G G C C A A G A T A G T C C T G G T A A G6PD C C G T G A G G C C T G G C G T A G G G C T T C T C C A G C T C A A T C T G G C C T C C C A A G C C A T A C T A T G T C T A B L E C2. C A L C U L A T I O N OF PRKCZ A N D G6PD COPY NUMBER FOR TRIO 187. Sample ™ £ C Z PGTO ™ PGT-PRKCZ PGT-G6PD ddCPRKCZ ddC,G6PD I^WRKCZ 2^PD ™ « Z G J ™ 27.21 27.76 28.36 0.55 -0.6 -0.34 -0.45 1.27 1.37 187_F 1.31 0.05 1.27 0.14 27.12 27.76 28.58 0.64 -0.83 -0.43 -0.22 1.34 1.17 27.03 27.57 27.41 0.54 0.16 -0.33 -1.21 1.25 2.31 187_M 1.17 0.12 2.33 0.03 27.18 27.52 27.33 0.33 0.19 -0.12 -1.24 1.09 2.36 27.33 27.52 28.54 0.19 -1.03 0.02 -0.02 0.98 1.01 187_P 0.96 0.04 1.03 0.03 27.28 27.39 28.37 0.11 -0.98 0.11 -0.07 0.93 1.05 Male 27.27 27.48 28.53 0.21 -1.05 0 0 1 1 1 1 27.55 27.94 27.86 0.39 0.07 -0.18 -1.12 1.13 2.17 Female 27.76 27.84 27.97 0.07 -0.14 0.14 -0.91 0.91 1.88 0.99 0.12 2.01 0.15 27.74 27.85 27.91 0.11 -0.06 0.1 -0.98 0.93 1.98 A P P E N D I X D . S T A T I S T I C A L ANALYSIS T A B L E DI . COEFFICIENT OF VARIATION (V) FOR T H R E E R E F E R E N C E HYBRIDIZATIONS. Hybridization Standard Deviation (s) Mean (X) Sample Size (n) Coefficient of Variation (V) Array 1 0.141 0.0857 2464 1.645 Array 2 0.114 0.0725 2464 1.572 **Array 3 0.102 0.0706 2464 1.445 **reference hybridization showing chromosome 13 aberration 1 Xx 0.0857 vx-v2 1.645-1.572 '1,2 V, r v  2 . -1 n 2 - \ j 1.609 1.609 - + -2464-1 2464-1 = 1.391 (0.5 + 1.609) y 2 .. -1 )^ +( 2^ - l )F 2 _ (2464-lXl.645)+(2464-lXl-572) ^ " ( « , - l ) + ( « 2 - l ) (2464-l)+(2464-1) 0^.05(2) — 1-96 Because Z 1 2 = 1.609 < Z 0 0 5 ( 2 ) , the null hypothesis (HD: the coefficients of variation of array 1 and array 2 are the same) cannot be rejected. Because Z 1 3 = 3.949 > Z 0 0 5 ( 2 ) , the null hypothesis (HD: the coefficients of variation of array 1 and array 3 are the same) can be rejected. Because Z 2 3 = 2.560 > Z 0 0 5 ( 2 ) , the null hypothesis(HD: the coefficients of variation of array 2 and array 3 are the same) can be rejected. 70 


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