NGS meta data analysis for identification of SNP and INDEL patterns in human airway transcriptome: A preliminary indicator for lung cancer.

High-throughput sequencing of RNA (RNA-Seq) was developed primarily to analyze global gene expression in different tissues. It is also an efficient way to discover coding SNPs and when multiple individuals with different genetic backgrounds were used, RNA-Seq is very effective for the identification of SNPs. The objective of this study was to perform SNP and INDEL discoveries in human airway transcriptome of healthy never smokers, healthy current smokers, smokers without lung cancer and smokers with lung cancer. By preliminary comparative analysis of these four data sets, it is expected to get SNP and INDEL patterns responsible for lung cancer. A total of 85,028 SNPs and 5738 INDELs in healthy never smokers, 32,671 SNPs and 1561 INDELs in healthy current smokers, 50,205 SNPs and 3008 INDELs in smokers without lung cancer and 51,299 SNPs and 3138 INDELs in smokers with lung cancer were identified. The analysis of the SNPs and INDELs in genes that were reported earlier as differentially expressed was also performed. It has been found that a smoking person has SNPs at position 62,186,542 and 62,190,293 in SCGB1A1 gene and 180,017,251, 180,017,252, and 180,017,597 in SCGB3A1 gene and INDELs at position 35,871,168 in NFKBIA gene and 180,017,797 in SCGB3A1 gene. The SNPs identified in this study provides a resource for genetic studies in smokers and shall contribute to the development of a personalized medicine. This study is only a preliminary kind and more vigorous data analysis and wet lab validation are required.