Dataset Information

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

ABSTRACT: 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.

SUBMITTER: B S

PROVIDER: S-EPMC4745382 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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

B Sathya S Dharshini Akila Parvathy AP Kumar Gopal Ramesh GR

Applied & translational genomics 20141224

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 ...[more]

PMID: 26937342

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Project description:BACKGROUND:Next-Generation Sequencing (NGS) technology has exceptionally increased the ability to sequence DNA in a massively parallel and cost-effective manner. Nevertheless, NGS data analysis requires bioinformatics skills and computational resources well beyond the possibilities of many "wet biology" laboratories. Moreover, most of projects only require few sequencing cycles and standard tools or workflows to carry out suitable analyses for the identification and annotation of genes, transcripts and splice variants found in the biological samples under investigation. These projects can take benefits from the availability of easy to use systems to automatically analyse sequences and to mine data without the preventive need of strong bioinformatics background and hardware infrastructure. RESULTS:To address this issue we developed an automatic system targeted to the analysis of NGS data obtained from large-scale transcriptome studies. This system, we named NGS-Trex (NGS Transcriptome profile explorer) is available through a simple web interface http://www.ngs-trex.org and allows the user to upload raw sequences and easily obtain an accurate characterization of the transcriptome profile after the setting of few parameters required to tune the analysis procedure. The system is also able to assess differential expression at both gene and transcript level (i.e. splicing isoforms) by comparing the expression profile of different samples.By using simple query forms the user can obtain list of genes, transcripts, splice sites ranked and filtered according to several criteria. Data can be viewed as tables, text files or through a simple genome browser which helps the visual inspection of the data. CONCLUSIONS:NGS-Trex is a simple tool for RNA-Seq data analysis mainly targeted to "wet biology" researchers with limited bioinformatics skills. It offers simple data mining tools to explore transcriptome profiles of samples investigated taking advantage of NGS technologies.

Project description:BACKGROUND:Leaf mold, one of the major diseases of tomato caused by Cladosporium fulvum (C. fulvum), can dramatically reduce the yield and cause multimillion dollar losses annually worldwide. Mapping the resistance genes (R genes) of C. fulvum and devising MAS based strategies for breeding new cultivars is an effective approach to improve the resistance in tomato. Up to now, many C. fulvum genes or QTLs have been mapped using different genetic materials, but few studies focused on Cf-10 gene positioning. RESULTS:In this study, we investigated the genetic rules for Cf-10 and used a novel combinatorial strategy to rapidly map the Cf-10 gene. Initially, the performance of F1, F2 and BC1F1 individuals after infection, demonstrated that the resistance against C. fulvum was controlled by a single dominant gene. Two pools of resistant and susceptible individuals from F2 population were investigated, using mapping by sequencing approach and Cf-10 was found to be localized to 3.35?Mb and 3.74?Mb on chromosome 1, employing SNP/InDel index methods, respectively. After accounting for overlapping regions, these two algorithms yielded a total length of 3.29?Mb, narrowing down the target region. We further developed five serviceable KASP markers for this region based on sequencing data and conducted local QTL mapping using individuals from the F2 population, except for mapping by sequencing as mentioned above. Finally Cf-10 gene was mapped spanning a region of 790?kb, where only one gene (Solyc01g007130.3) was annotated as probable receptor protein kinase TMK1 with a LRR motif, a common R gene characteristic. The RT-qPCR analysis further confirmed the localization and the relative expression of Solyc01g007130.3 in Ontario 792 and was found to be significantly higher than that in Moneymaker at 9 dpi and 12 dpi, respectively. CONCLUSION:This study proposed a novel combinatorial strategy by combining SNP-index, InDel-index analyses and local QTL mapping using KASP genotyping approach to rapidly map genes responsible for specific traits and provided a robust base for cloning the Cf-10 gene. Furthermore, these analyses suggest that Solyc01g007130.3 is a potential candidate to be regarded as Cf-10 gene.

Dataset Information

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

Publications

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

Similar Datasets

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