Dataset Information

Determination of RET Sequence Variation in an MEN2 Unaffected Cohort Using Multiple-Sample Pooling and Next-Generation Sequencing.

ABSTRACT: Multisample, nonindexed pooling combined with next-generation sequencing (NGS) was used to discover RET proto-oncogene sequence variation within a cohort known to be unaffected by multiple endocrine neoplasia type 2 (MEN2). DNA samples (113 Caucasians, 23 persons of other ethnicities) were amplified for RET intron 9 to intron 16 and then divided into 5 pools of <30 samples each before library prep and NGS. Two controls were included in this study, a single sample and a pool of 50 samples that had been previously sequenced by the same NGS methods. All 59 variants previously detected in the 50-pool control were present. Of the 61 variants detected in the unaffected cohort, 20 variants were novel changes. Several variants were validated by high-resolution melting analysis and Sanger sequencing, and their allelic frequencies correlated well with those determined by NGS. The results from this unaffected cohort will be added to the RET MEN2 database.

SUBMITTER: Margraf RL

PROVIDER: S-EPMC3321559 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Publications

Determination of RET Sequence Variation in an MEN2 Unaffected Cohort Using Multiple-Sample Pooling and Next-Generation Sequencing.

Margraf R L RL Durtschi J D JD Stephens J E JE Perez M M Voelkerding K V KV

Journal of thyroid research 20120401

Multisample, nonindexed pooling combined with next-generation sequencing (NGS) was used to discover RET proto-oncogene sequence variation within a cohort known to be unaffected by multiple endocrine neoplasia type 2 (MEN2). DNA samples (113 Caucasians, 23 persons of other ethnicities) were amplified for RET intron 9 to intron 16 and then divided into 5 pools of <30 samples each before library prep and NGS. Two controls were included in this study, a single sample and a pool of 50 samples that ha ...[more]

PMID: 22545224

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Project description:The impact of natural killer (NK) cell alloreactivity on hematopoietic stem cell transplantation (HSCT) outcome is still debated due to the complexity of graft parameters, HLA class I environment, the nature of killer cell immunoglobulin-like receptor (KIR)/KIR ligand genetic combinations studied, and KIR+ NK cell repertoire size. KIR genes are known to be polymorphic in terms of gene content, copy number variation, and number of alleles. These allelic polymorphisms may impact both the phenotype and function of KIR+ NK cells. We, therefore, speculate that polymorphisms may alter donor KIR+ NK cell phenotype/function thus modulating post-HSCT KIR+ NK cell alloreactivity. To investigate KIR allele polymorphisms of all KIR genes, we developed a next-generation sequencing (NGS) technology on a MiSeq platform. To ensure the reliability and specificity of our method, genomic DNA from well-characterized cell lines were used; high-resolution KIR typing results obtained were then compared to those previously reported. Two different bioinformatic pipelines were used allowing the attribution of sequencing reads to specific KIR genes and the assignment of KIR alleles for each KIR gene. Our results demonstrated successful long-range KIR gene amplifications of all reference samples using intergenic KIR primers. The alignment of reads to the human genome reference (hg19) using BiRD pipeline or visualization of data using Profiler software demonstrated that all KIR genes were completely sequenced with a sufficient read depth (mean 317× for all loci) and a high percentage of mapping (mean 93% for all loci). Comparison of high-resolution KIR typing obtained to those published data using exome capture resulted in a reported concordance rate of 95% for centromeric and telomeric KIR genes. Overall, our results suggest that NGS can be used to investigate the broad KIR allelic polymorphism. Hence, these data improve our knowledge, not only on KIR+ NK cell alloreactivity in HSCT but also on the role of KIR+ NK cell populations in control of viral infections and diseases.

Dataset Information

Determination of RET Sequence Variation in an MEN2 Unaffected Cohort Using Multiple-Sample Pooling and Next-Generation Sequencing.

Publications

Determination of RET Sequence Variation in an MEN2 Unaffected Cohort Using Multiple-Sample Pooling and Next-Generation Sequencing.

Similar Datasets

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