European Journal of Cardiovascular Medicine

Congenital heart disease (CHD) is one of the most frequently occurring diseases globally; about 9/1000 babies are born with congenital heart disease. In India, nearly two hundred thousand children are born with congenital heart disease per year. According to the rare disease and disorder research, resource, and repository for South Asia, 4/1000 children are born with any type of CHD (1). Among the CHD, ventricular septal defect (VSD, 34%), atrial septal defect (ASD, 13%), and patent ductus arteriosus (PDA, 10%) are the most common throughout the globe. The prevalence of pulmonary stenosis (PS, 8%), tetralogy of Fallot (TOF, 5%), coarctation (Clark, 5%), transposition of the great arteries (TGA, 5%), aortic stenosis (AoS, 4%) varies globally. Significantly higher proportions of PS, TOF, and coarse were observed among Asians; while TGA was highest in Africa (2). Epidemiological studies reveal that 20%-30% of CHD is caused by genetic or environmental insults.  Gross chromosomal anomalies/aneuploidy among CHD varies between 20% to 30% of CHD cases. Single-gene disorders are observed in 3% to 5%, and pathogenic copy number variation (CNVs) in 3% to 25% in syndromic CHD and 3% to 10% among isolated CHD. About 2% to 8% of genetic alterations in CHD could be due to de novo variations. Environmental causes are identified in 2% of CHD cases. The proportion of CHD cases that could not be explained by the molecular defects mentioned above could be due to oligogenic or a combination of genetic and environmental factors. It has been observed that the cause (s) of about 60% of CHD is unknown (3) (4).  Genetic defects as single gene mutations (4,5), and chromosomal anomalies like deletion, amplification as CNVs and structural variants (4,6–8) that contribute to the development of CHD have been identified. Mutations in a large number of genes in a small number of families have been identified. Chromosomal imbalances as detected by CNV using array-CGH have been observed in CHD (7, 9–12). Such abnormalities were observed in various types of CHD like TOF (7–9, 11, 12), ASD (12–14) (15), VSD (9, 12–15). Deletion 22q11.2 is common in TOF and also observed in ASD, VSD (16). Deletion of 22q11.2 disrupts transcription factor TBX1 gene.

It is important to diagnose the congenital anomalies in heart at early age for proper management of the condition. Karyotype is the most used technique to identify chromosomal abnormalities in many congenital defects. But karyotype provides data at the level of mega base with overlooking of comparatively small deletions. To overcome this problem now array CGH is widely used to detect chromosomal aberrations (16). Advantage of array CGH is that it can generate 1-10000 fold detailed data in contrast to any other karyotype (18). Even though molecular abnormalities involving point mutations, small and large deletion have been identified in many patients with TOF, these genetic changes reported cannot explain all TOFs. It is possible that there exist additional changes resulting in TOFs. Molecular nature of the defects of the TOF patients reported by us in an earlier study (19) is also not known. In the present study, we performed array CGH to identify and characterize the chromosomal aberrations, either deletions or amplifications present in blood and heart tissue samples of TOF patients. We have analysed DNA extracted from blood and tissue samples separately from 14 clinically confirmed TOF cases. We have validated some of the findings using RT-PCR in an independent set of samples. Overall, our aim is to identify signature molecular regions altered in TOF from comparative analysis of blood and tissue, which can be further validated in a larger cohort of patients using DNA extracted from blood. Such signatures can be used for screening or designing panels for screening TOF patients in future.

Study population and sample collection

The study was approved by the Ethics Committee of the Institute of Post Graduate Medical Education & Research and SSKM Hospital, Kolkata. Informed consent was taken either from individuals or one of the parents for pediatric cases.  For array-CGH analysis, we recruited 14 TOF patients. We excluded TOF patients with Down syndrome (trisomy 21), Patau syndrome (trisomy 13) or Edwards’s syndrome (trisomy 18) and monosomy Turner syndrome. For 4 unrelated patients, blood samples as well as tissue samples were collected who underwent corrective surgery. These samples were considered as “paired sample”. Five tissue samples and five blood samples were also collected from independent ten TOF patients. DNA from an individual without any heart defects or any other known ailment was included in array CGH as a control. For validation real time PCR was performed on same set of DNA samples. In addition to that, DNA from one tissue sample and six blood samples from independent TOF patients’ cohort was used. DNA isolated from blood of one healthy individual was used as control for aCGH and additional four controls were used in PCR validation.

DNA isolation

QIAgen DNA midi kit was used for DNA isolation from blood. Tissue samples were crushed in liquid nitrogen and put into lysis buffer and DNA was isolated by QIAgen blood and tissue DNAesy kit. Concentrations and purity of DNA was checked by spectrophotometer (Nanodrop).

Array CGH

Identification of chromosomal aberrations was done using Agilent SurePrint G3 Human CGH+SNP Microarray. The 4x180k chip contains ~120000 CGH probes and ~60000 SNP probe. The experiment was done at the facility of Agilent (New Delhi, India). Genomic DNA and reference control DNA (1g) were fragmented at 95⁰C for 10mins. Fragmented reference DNA was tagged with Cy3 and test DNA (sample DNA) was tagged with Cy5 tag and added to the chip. Hybridization reaction was performed at 65⁰C at 20rpm for 24hrs. After hybridization, the signals were available as image file. Agilent Cytogenomics software was used to analyze data. Microarray slides images in form of tif files (image files with microarray slides image) were uploaded and the data was analyzed through default setting program. The default method was CGH+SNP v2 method and as reference Agilent Euro male (for male) and Agilent Euro female (for female) was included in the assay. On analysis, it provided a list of chromosomal aberrations, type of the aberration, size of the deletion or amplification and gene annotations (Fig1 & Table1). Array CGH data was normalized by log(ratio)=0 indicating no deletion or amplification. It implies that if the value is greater than 0 it is amplification and less than 0 means deletion (Fig 1).

Validation by PCR and qPCR:

To validate chromosomal aberrations identified in array CGH, we have selected six deleted regions and three amplified regions (present in multiple individuals). Primer BLAST was used to design the PCR primers flanking the deleted regions common in all individuals. RT-PCR primers were also designed, flanking the deleted regions. Regions and sequence of the deleted or amplified regions were extracted from UCSC genome browser (hg19 genome assembly).

Identification of common deleted regions exclusive in TOF patients identified from array CGH data

In the analyzed data, aberrations are classified as amplification, gain, deletion and loss based on value of mean log ratio of intensity. In cytogenomics output table (example shown in Table 1), sixth column contains log (ratio) value and it is colour coded for amplification (blue) and deletion (red). Amplification is classified as amplification (log (ratio) > 1) and gain (log (ratio) < 1) and deletion is also classified as deletion (log (ratio) >-1) and loss (log (ratio) < -1). For each sample deletion regions (Table S1 & S2) and amplification (Table S3 & S4) were separated and clustered into two different tables. As we mentioned earlier, we had two group of samples – paired and unpaired, paired samples were selected as the first set to find the common altered cytoband regions in blood and tissue. First, we focused on the deleted regions that include both deletion (log(ratio)> -1) and loss(log(ratio)< -1). We have classified all data into four groups for analysis i.e.  1) all deleted cytoband regions of four paired blood samples (Table S1 sheet 1); 2) all deleted cytoband regions of four paired tissue samples (Table S1 sheet 2); 3) all deleted cytoband regions of five unpaired blood samples (Table S2 sheet 1) and 4) all deleted cytoband regions of five unpaired tissue samples (Table S2 sheet 2). By using venny 2.1 (https://bioinfogp.cnb.csic.es/tools/venny/), paired blood and tissue data was compared to find out altered cytoband regions common in both and the output provided a list of common cytoband regions deleted (Fig 2, Table 2). Then the list of cytobands obtained from unpaired blood (five) and tissue (five) samples was separately compared with the common cytoband region (i.e. data in Table 2) and obtained data is described in Table no 3. Common regions from both blood and tissue were further compared with the control samples in order to retain the unique region deleted in patients. After comparing with controls, 16 regions were found exclusively deleted among cases (Table 4). The shortlisted 16 regions were not present in all samples but present in at least one sample. We have calculated frequency of every region separately in paired and unpaired samples (Table 5).

Identification of overlapping regions in common deleted regions

The span of deleted regions is not identical in every individual. We attempted to find out the region lost in every individual at the same deleted locus.  Bedtool intersect tool (https://bedtools.readthedocs.io/en/latest/) was used for this purpose. All the deletions were pooled together to make a master query file, as well as separate *.bed files were made for every single individual. By comparing query file with other 18 bed files for cases, we obtained 12 overlapping regions (table 6). Next, we calculated the size of the deletions, which are shown in table 6. The deleted regions were examined through UCSC genome browser for information on genes located in that genomic region. The deletions are large upto 112 kb and span through many genes. Many regions like 8p23.1 (in total 13 sample), 5q35.1 (in total 4 samples), 22q11.2 (in total 5 samples) etc. which are already known to be linked to TOF were also found to be deleted in our data.  Primers were designed for each of the regions to verify the deletion by presence or absence of the PCR products.

We have extensively searched databases such as DECIPHER and ClinVAR to explore available data on these regions and their association with disease pathology. In DECIPHER, we analyzed information from the gnomAD database for structural variants and patient phenotypes associated with copy-number variants matching those genes listed in Table 6. Our analysis revealed that many loci that are deleted in our data set are also reported to be deleted in control datasets. However, the frequency is very low in the global population, and zero for the East Asian population. Regarding patient-phenotype association data, six regions reported a phenotype of any heart disease, and two regions were associated with Tetralogy of Fallot (TOF). Additionally, as per DECIPHER, three genes TBX1, NKX2-5, FRK (table 6) were earlier reported to link with heart disease and TOF. These findings strengthen our confidence in finding and confirming the importance of the loci detected.

Identification of common amplified regions in TOF patients identified from array CGH data

Paired samples were selected as the first set to find the common cytoband regions. We focused into amplified regions which includes both amplification (log(ration)> 1) and gain (log(ration)< 1). Following, similar screening process mentioned for deletion we sorted our results into four different groups, i.e.  1) all amplified cytoband regions of four paired blood samples (Table S3 sheet 1); 2) all amplified cytoband regions of four paired tissue samples (Table S3 sheet 2); 3) all amplified cytoband regions of five unpaired blood samples (Table S4 sheet 1) and 4) all amplified cytoband regions of five unpaired tissue samples (Table S4 sheet 2). Venny 2.1 was used to find amplified regions common in many individuals as the previously processed for deleted regions. Paired blood and tissue data was compared to find out common cytoband regions. The output was collection of common cytoband regions amplified (Table 2). Next this list was compared to amplified regions obtained from unpaired blood (five) and tissue (five) samples (Table3). Thus, common regions obtained from both blood and tissue were taken further and compared with the control samples. On comparing with control, 5 cytoband regions were found exclusively amplified among cases (Table 4). These common regions were not characteristics of all samples but present in at least one sample. We have calculated frequency of every region separately in paired and unpaired samples (Table 5). 

Identification of overlapping regions in common amplified regions

In case of deletions, we have observed that the span of the deleted regions was not identical in every individual. Similarly, we found that the spans of amplified regions are also not same in every case. Further we attempted to find out constant regions as we have done in case of deleted regions. Bedtool intersect tool (https://bedtools.readthedocs.io/en/latest/) was used to find out the overlapping regions. All the amplifications were pooled together to make a master query file, as well as separate *.bed files were made for every single individual. By comparing query file with other 18 bed files for cases, we got 5 overlapping regions (Table 6). The sizes of the overlapping regions were calculated. Genomic information of these regions was extracted using UCSC genome browser (Table 6).  We selected three regions for further validation studies. Similar to the analysis of deleted regions, we followed the same process for the amplified regions too. In DECIPHER, we analyzed information from the gnomAD database for structural variants and patient phenotypes associated with copy-number variants matching those genes listed in Table 6. Our analysis revealed that many genes present in the amplified regions are also present in control datasets. However, the allele frequency is very low in the global population, and zero for the East Asian population. Regarding patient-phenotype association data, four regions reported phenotype of any heart disease, and one region was associated with Tetralogy of Fallot (TOF). Additionally, the gene MSR1 as obtained from DECIPHER, is already known to link to heart disease and TOF were reported (table 6). These findings strengthen our confidence in analysis of the data obtained from patients.

Validation by PCR and qPCR:

Analysis of array CGH data identified regions exclusively deleted and amplified in TOF samples. We selected six deleted and three amplified regions present across multiple samples for further validation.  Validation was done by PCR (primers flanking deleted region) for different cycles as well as RT-PCR. We have included samples used in array as well as samples not included in array for validation with inclusion of controls harbouring no such deletions in the same region. On PCR amplification, presence of desired band suggests either no deletion or heterozygous condition (Supplementary Fig1&2) where one allele is deleted keeping the other normal.

For one locus on chr 4, PCR was repeated for different cycles (15 cycles, 20 cycles, 25 cycles, 30 cycles and 35 cycles). It was observed that in low cycle number (for chr4) in deleted samples band intensity is lower than the samples with no deletion on chromosome4, but with comparable intensity of bands for GAPDH in every sample (Supplementary fig3). This is indicative of deletion of one allele which is reflected by lower intensity of bands in earlier cycles of PCR. Similar process was repeated with other chromosomal regions (chr8 (ZFPM2), chr5 (NKX2-5) and chr22) with inclusion of one TOF case with no deletion in these regions mentioned above (data not shown). We could validate the deleted region on chr8 (ZFPM2), but we could not do the same for regions on chromosomes 22 and 5. For chromosome 22 and chr5 (NKX2-5) no difference in intensity was visible between deleted and non-deleted samples (Supplementary fig3). In addition, we did realtime PCR for validation. RT-PCR was done for six regions chr4_del, chr5 (NKX2-5)_del, chr8(ZFPM2)_del, chr22_del, chr14_del and chr6_del where deletions were reported in array CGH data. Fold change was calculated considering GAPDH as control gene. We could confirm deletion of a region on chr4 in 8/11 samples (72% concordant with aCGH). Similarly for regions on Chr5 in 2/2 samples (100% concordant), chr8 (ZFPM2) in 4/4 individuals (100% concordant), chr22 in 4/4 individuals (100% concordant), chr14 in 2/2 individuals (100% concordant) and chr6 in 5/5 individuals (100% concordant with aCGH). Thus, we were able to validate deletion in samples which had undergone array CGH in contrast control samples as measured by RT-PCR. Additionally, we validated deletion of regions on chr 4 in 3/6, Chr 5 in 7/7 samples, chr 8 in 7/7 samples, Chr 22 in 7/7, chr 14 in 7/7 and chr6 in 7/7 sample (which were not used in array CGH experiment).

1. Similarly, qPCR primer sets were designed for validating overlapping amplified regions on chr4, chr8 & chr22. Here we also have followed similar strategy to identify samples for validation i.e. TOF with and without amplifications in those regions. Besides we also included additional TOF samples and control as used for verification of deleted regions. For amplified regions on chr4 4/4 individuals (100% concordant with aCGH), chr22 in 1/6 individuals (16% concordant with aCGH) and chr8_amp 0/6 individuals (0% concordant with aCGH) were validated by RT-PCR in contrast to control samples. Additionally, we validated amplification of chr 4 region in 7/7, chr 22 region in 2/7 and chr 8 region in 0/7 samples (which were not included in array CGH experiment).

Genomic information of the deleted and amplified regions

The genomic loci surrounding the deleted or amplified regions were analyzed using the UCSC genome browser. Within the deleted regions, several genes were identified, including GATA4, NKX2-5, ZFPM2, TBX1, UGT2B17, PCDH9, ZDHHC11, FRK, ZNF74, KLHL36, and GSE1. While some of these genes, such as GATA4, NKX2-5, and TBX1, are known to harbor point mutations associated with Tetralogy of Fallot (TOF), many others have not been previously implicated in heart diseases.

To investigate their potential roles in heart development and function, we examined their expression in heart tissue using the GTEx database. Surprisingly, several of these genes, including UGT2B17, GATA4, PCDH9, ZDHHC11, NKX2-5, FRK, ZFPM2, KLHL36, GSE1, TBX1, and ZNF74, were found to be expressed in the heart. Additionally, we observed genes such as MYH7, MYH6, CEBPE, and NLRP, known for their involvement in congenital heart defects, located upstream or downstream of the deleted regions.

In addition to the overlapping amplified/deleted regions, we also investigated the regions flanking the common regions either deleted or amplified. These regions contained 112 genes exclusively present in the deleted regions of patients, 51 of which were found to be expressed in the heart, including two long noncoding RNAs, as identified through the GTEx database (Table S5).

Further analysis using databases such as ClinVar and DECIPHER provided additional insights. In DECIPHER, gnomAD structural variants and patient phenotypes associated with copy-number variants were matched with the aberrant regions identified in our array comparative genomic hybridization (aCGH) data (Table S6). ClinVar database analysis revealed associations between TOF or other heart diseases and genes such as NKX2-5, ZFPM2, TBX1, and MSR1 (Table S7). These findings collectively suggest potential roles for the identified genes in heart morphogenesis and function. We also examined the nonoverlapping regions (for both deleted and amplified regions) and found presence of many genes implicated in heart morphogenesis or defects. The data is summarized in table S8. Not only in the mRNA level but some of these genes are validated at the protein level and different stages of life.

TOF is one of the most frequent congenital heart diseases with four prominent features. With diagnosis and intervention at early stage it can be cured. Point mutations and small insertion/deletion in multiple genes are causal for TOF. Besides large deletion or insertions in any regions of genome harboring genes involved in heart development or function can lead to malformations. These deleted/amplified regions can be used as molecular marker for the disease.

In this study we have identified and characterized some of these large insertion/deletions. Analysis of genomic DNA using array CGH provides information on chromosomal aberrations. We have a cohort of 15 (14+1) individuals whose genomic DNA was analyzed using array CGH. Our results identified characteristics chromosomal aberrations in the genome which are further validated by RT-PCR. From array data we have found 15 regions deleted and 5 regions amplified exclusively in TOF patients (Table 5). Further validation by RT-PCR confirms a deleted region on chr4, Chr 5, Chr 7and chr22 to be concordant with array CGH data. Deleted regions onChr22 harbor TBX1 gene. TBX1 gene is found to be deleted in many developmental disorders like DiGeorge syndrome, Conotruncal Heart Malformations, Chromosome 22q11.2 Deletion Syndrome Distal, Velocardiofacial Syndrome along with TOF. TBX1 is a transcription factor which regulates many genes in the development process like formation of cardiac outflow tract of cardiac myocardium. OnPathCards, Heart development super pathway analysis, suggests interaction network of 46 genes inclusive of TBX1. TBX1 has multiple interacting partners like Foxa2, Pitx2, Fgf8, Fgf10(20).

NKX2-5 mutations are found in >4% TOF patients and these mutations alter highly conserved NK2 domain(21). GATA proteins activity is regulated by some other transcriptional factors and transcriptional captivators or repressors. ZFPM2 mainly regulates GATA4 gene activity. Antonio Pizzutiet al., 2003 (22) found that change of S657G in ZFPM2 protein cannot regulate GATA4. Previous reports have identified point mutations in NKX2-5, ZFPM2, GATA4 genes.  The larger deleted regions obtained in our analysis also harbor these genes. RT-PCR also validated, deletion in regions harboring NKX2-5 and ZFPM2 which showed 100% concordance with array CGH data.

Our study also identified many regions which are not previously reported. Deleted region on Chr4 (69433306-69483277) is such one and the most frequent deletions found in our patient cohort. The deleted region harbor UGT2B17 gene. UGT2B17 is a member of uridinediphosphoglucuronosyltransferase protein family and the enzyme produced from this gene helps to transfer glucouronic acid. It is mainly reported in metabolic disease and a part of drug metabolism pathways. Other regions include Chr5 (710494-801979): harboring two genes ZDHHC11, ZDHHC11B; chr6 (115169659-116296480) FRK, chr7 (38323925-38345585) with three genes TRGC2, TARP, TCRGV; chr13 (67103903-67113409) PCDH9 gene, chr16 (84409311-84567551) ATP2C2, TLDC1, MEAK7. Defects in many of the genes mentioned above are involved in other developmental disorders but not reported in any CHDs.

Our results reiterate the fact that array-CGH can provide solution in detection of chromosomal aberrations for etiological diagnosis of CHD patients harbouring additional features. However, at the present time, the interpretation of a detected imbalance is not always straightforward, given the presence of high level of copy number variations in the human genome. Traditionally, the causality of a chromosomal aberration can be evaluated using several arguments (after exclusion of known polymorphisms) including (1) a gene in the deleted or duplicated region is known to cause CHDs, (2) deletion or duplication can alter dosage effect leading to another dominant monogenic disorder, (2) a patient with a similar chromosomal imbalance and a similar phenotype has previously been described, (3) de novo occurrence of chromosomal aberrations, and (4) the size of the imbalanced region. Our study validates our own findings from array CGH analysis as well as other samples not included in array CGH. High concordance is obtained between array and RT PCR results for deleted regions across many chromosomes. However due to consideration of lesser number of amplified regions only one region (Chr 4) could be validated. Validated regions can be further tested in large number of samples and considered as biomarkers for the disease detectable from blood.

Acknowledgement: The work described was funded by Department of Health & Family Welfare, Govt of India to S. Dutta and NPB. BP acknowledges support from NIBMG intramural grant.

Conflict of interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Contribution of authors: ADG: performed experiments and analysis, wrote the manuscript, SDutta: performed all clinical evaluation and recruitment of study participants, SG, SDas, BK: participated in sample and data collection, processing,

experiments, SC: participated in analysis, NPB, SDutta, BP conceptualized the project, planned experiments, supervised, wrote

manuscript. All the authors reviewed the manuscript.

Legends to Figure

Figure 1: (a) Representation of array CGH data for all chromosomes. (b) On the right an amplified view of chromosome 1 is shown as an example.  The log (ratio) is shown at the bottom, with 0 means no change, >0 is amplification shown in blue colour and < 0 means deletion shown in red colour. Each point is a probe representing the genomic region.

Figure 2:  Overview of Venny2.1 analysis to identify exclusive deleted/amplified regions in TOF cases. (This study encompasses both blood and tissue samples. We've examined shared regions of alteration in both. Ultimately, we seek a non-invasive method to identify markers, exclusively accessible through blood samples).

Supplementary figure 1: Analysis of PCR products (30 cycles) for validation of six deleted (overlapping) region within paired samples. Bands are visible for individuals both with or without deletion obtained from array CGH data in paired samples suggesting deletion of one copy. a) For chr8(ZFPM2) bands was observed at 400bp region [Samples in lane: 1- B7, 2-T7, PC- Positive control for PCR], for chr22 bands were observed at 500bp regions [Samples in lane: 3- B7, 4-T7, PC- Positive control for PCR] and chr6 bands were observed at 1kb region [Samples in lane: 5- B7, 6-T7, PC- Positive control for PCR]; b) for chr5 bands were observed at 600 bp region [Samples in  lane: 1- 1B, 2-1T, 3-2B, 4-2T, 5-3B, 6-3T, 7-7B, 8-7T, PC- Positive control for PCR]; c) for chr14 bands were observed at 500bp region [Samples in lane: 1- 1B, 2-1T, 3-3B, 4-3T, 5-7B, 6-7T, PC- Positive control for PCR]; d) for chr4 bands were observed at 700bp region [Samples in lane: 1- 1B, 2-2T, 3-3B, 4-3T, 5-7B, 6-7T, 7-1T, 8-2B PC- Positive control for PCR]. In all cases NTC is the negative control for PCR. ’B’ denotes DNA isolated from blood and’ T’ denotes DNA isolated from tissue.

Supplementary Figure 2: Analysis of PCR products (30 cycles) of all six deleted overlapping region primers within unpaired samples. Bands were visible for both samples type (deletion and non-deletion) also in unpaired samples.  a) For chr6 band was observed at 1kb region [Samples in lane: 1-B8, 2-B21, 3-B23, PC- Positive control] and for chr22 [Samples in lane: 4-B8, 5-B21, 6-B23, PC- Positive control] and chr8 [Samples in lane: 7-B8, 8-B21, 9-B23, PC- Positive control] bands were observed at 500bp region  ; b) For chr4  bands were observed at 700bp region [Samples in lane: 1-B5, 2-B8, 3-B10, 4-4T, 5-6T, 6-11T, 7-12T, PC- Positive control], chr5 [Samples in lane: 8-4T, 9-12T, PC- Positive control]  and ch5(NKX2-5) [Samples in lane: 10-B8, PC- Positive control]  bands were observed on 500bp regions. in all cases NTC is the negative control for PCR.’B’ denotes DNA isolated from blood and’ T’ denotes DNA isolated from tissue.

Supplementary Figure 3: a) Analysis of PCR products of deleted region on chromosome 4 done for different cycles as indicated. DNA from a TOF case (lane 1,3,5,7 and control (lane 2,4,6,8) were amplified for different cycles (15,20,25,30 cycles respectively) spanning the deleted region.  In each case we see that intensity of band in TOF cases is less compared to that of the control. 1Kb DNA ladder is used for size determination. NTC denotes non template control. b) DNA from two same individuals mentioned above (TOF case lane 1,3,5,7,9, control lane 2,4,6,8,10) were amplified for GAPDH gene done for different cycles (15,20,25,30, 35). [lane 9 & 10 depicts PCR product done for GAPDH gene for 35 cycles. We do not have amplified product for 35 cycles for deleted region on Chromosome 4. Hence PCR bands in lanes 9& 10 were not considered for analysis]. 1Kb DNA ladder is used for size determination. NTC denotes non-template control.

Legend to supplementary table

Supplementary table 1: summary of deletion and loss obtained from Array CGH in paired tissue and blood samples

Supplementary table 6

Table 6: List of overlapping regions within the common cytoband regions, genes present in those regions and the size of those regions

Conclusion: The findings aim to uncover signature molecular regions altered in TOF, with validation through RT-PCR from blood. The study provides valuable insights for future TOF screening and diagnostic panels, contributing to improved patient care and management.

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