Balkan Journal of Medical Genetics

ANALYSIS OF MICROSATELLITE POLYMORPHISMS IN SOUTH INDIAN PATIENTS WITH NON SYNDROMIC CLEFT LIP AND PALATE
Xavier DL1,* Arif YA1, Murali RV1, Kishore Kumar S1, Vipin Kumar S2, Tamang R2, Thangaraj K2, Bhaskar LVKS3
*Corresponding Author: Dr. Dhayananth L. Xavier, Department of Orthodontics, Sree Balaji Dental College, Pallikaranai, Chennai, India; Tel.: +91-44-22461883; E-mail: drxavy@gmail.com
page: 49

MATERIALS AND METHODS

Subjects. In the present study, 173 South Indian subjects (Dravidian speakers) were recruited from Sree Balaji Dental College and Hospital, Chennai, Tamil Nadu, India. Of these, 83 had NSCLP (45 males, 38 females, aged 1-2 years). Cleft status of the NSCLP group was determined by clinical examination as well as through their medical records. All the subjects in the case group are isolated NSCLPs. The cleft phenotype was divided into two sub-phenotypes such as cleft lip with or without cleft palate (74 CLP) and cleft palate only (nine CPO). The control group comprised 90 unrelated south Indian children (48 males and 42 females, aged 2-3 years) without clefts or family history of clefting or other major health problems. Children with mental retardation, serious medical problems or other congenital malformations were excluded. About 5 mL of intravenous blood was collected from all the participants. All subjects had provided informed consent prior to the sample collection. A procedure for protection of human subjects in this study is also approved by the Institutional Ethical Review Committee of Sree Balaji Dental College, Chennai, India. Genotyping. Genomic DNA was extracted from blood using the standard protocol described elsewhere [6]. Five microsatellite markers within five different genes (DLX3, MSX1, RARA, BCL3 and EDN1) were amplified using the primer sets labeled at the 5’ ends (forward primer) with 6-FAM/HEX fluorescent dye (BioServe Biotechnologies India Pvt Ltd, Hyderabad, Andhra Pradesh, India; Table 1). As the forward primer is labeled with fluorescent dye, the polymerase chain reaction (PCR) product so generated will also have the fluorescence. To resolve the products, 1 mL of PCR product was mixed with 10 mL of 50.0% HiDye™ formamide and 0.1 mL LIZ (size standard; Applied Biosystems, Foster City, CA, USA). The sample plates were kept and run on the ABI PRISM™ 3730 DNA Analyzer (Applied Biosystems). In the sequencer, the fragments were separated by length from longest to shortest. The fluorescence of the PCR product when illuminated by a laser beam was read by an automatic scanner that provided the size of the allele and the data were processed by GENE MAPPER v3.0 software (Applied Biosystems). Statistical Analyses. As the number of CPO samples in the group was less, we considered all clefts as a single group. Power and sample size calculation program software (version 2.1.31) (http:// biostat.mc.vanderbilt.edu/ twiki/bin/view/Main/ PowerSampleSize) was used to evaluate the null hypothesis in the uncorrected c2 statistic model. Allele frequencies of microsatellite markers were estimated as simple proportions in patients and controls. Concordance with Hardy-Weinberg expectations was assessed through Genepop, a web based software (http:// genepop.curtin.edu.au/). The markers were tested for association with NSCLPs by conducting a case-control association analysis. The CLUMP v1.9 program (http://www.smd. qmul.ac.uk/statgen/dcurtis. software.html) was used to test each marker for association with clefts [7]. The CLUMP v1.9 program, uses the Monte Carlo method, was designed to overcome the problems of sparse contingency tables as found in a c2 analysis of multiallelic markers such as microsatellites. Significance was assessed for each marker by performing 10,000 simulations to generate tables with the same marginal totals as the original data. Empirical p values were obtained by counting the number of times the c2 value of the real data was achieved by the simulated tables.

Number 27 VOL. 27 (2), 2024	Number 27 VOL. 27 (1), 2024
Number 26 Number 26 VOL. 26(2), 2023 All in one	Number 26 VOL. 26(2), 2023
Number 26 VOL. 26, 2023 Supplement	Number 26 VOL. 26(1), 2023
Number 25 VOL. 25(2), 2022	Number 25 VOL. 25 (1), 2022
Number 24 VOL. 24(2), 2021	Number 24 VOL. 24(1), 2021
Number 23 VOL. 23(2), 2020	Number 22 VOL. 22(2), 2019
Number 22 VOL. 22(1), 2019	Number 22 VOL. 22, 2019 Supplement
Number 21 VOL. 21(2), 2018	Number 21 VOL. 21 (1), 2018
Number 21 VOL. 21, 2018 Supplement	Number 20 VOL. 20 (2), 2017
Number 20 VOL. 20 (1), 2017	Number 19 VOL. 19 (2), 2016
Number 19 VOL. 19 (1), 2016	Number 18 VOL. 18 (2), 2015
Number 18 VOL. 18 (1), 2015	Number 17 VOL. 17 (2), 2014
Number 17 VOL. 17 (1), 2014	Number 16 VOL. 16 (2), 2013
Number 16 VOL. 16 (1), 2013	Number 15 VOL. 15 (2), 2012
Number 15 VOL. 15, 2012 Supplement	Number 15 Vol. 15 (1), 2012
Number 14 14 - Vol. 14 (2), 2011	Number 14 The 9th Balkan Congress of Medical Genetics
Number 14 14 - Vol. 14 (1), 2011	Number 13 Vol. 13 (2), 2010
Number 13 Vol.13 (1), 2010	Number 12 Vol.12 (2), 2009
Number 12 Vol.12 (1), 2009	Number 11 Vol.11 (2),2008
Number 11 Vol.11 (1),2008	Number 10 Vol.10 (2), 2007
Number 10 10 (1),2007	Number 9 1&2, 2006
Number 9 3&4, 2006	Number 8 1&2, 2005
Number 8 3&4, 2004	Number 7 1&2, 2004
Number 6 3&4, 2003	Number 6 1&2, 2003
Number 5 3&4, 2002	Number 5 1&2, 2002
Number 4 Vol.3 (4), 2000	Number 4 Vol.2 (4), 1999
Number 4 Vol.1 (4), 1998	Number 4 3&4, 2001
Number 4 1&2, 2001	Number 3 Vol.3 (3), 2000
Number 3 Vol.2 (3), 1999	Number 3 Vol.1 (3), 1998
Number 2 Vol.3(2), 2000	Number 2 Vol.1 (2), 1998
Number 2 Vol.2 (2), 1999	Number 1 Vol.3 (1), 2000
Number 1 Vol.2 (1), 1999	Number 1 Vol.1 (1), 1998

About the journal ::: Editorial ::: Subscription ::: Information for authors ::: Contact