Dataset Information

Read count-based method for high-throughput allelic genotyping of transposable elements and structural variants.

ABSTRACT:

Background

Like other structural variants, transposable element insertions can be highly polymorphic across individuals. Their functional impact, however, remains poorly understood. Current genome-wide approaches for genotyping insertion-site polymorphisms based on targeted or whole-genome sequencing remain very expensive and can lack accuracy, hence new large-scale genotyping methods are needed.

Results

We describe a high-throughput method for genotyping transposable element insertions and other types of structural variants that can be assayed by breakpoint PCR. The method relies on next-generation sequencing of multiplex, site-specific PCR amplification products and read count-based genotype calls. We show that this method is flexible, efficient (it does not require rounds of optimization), cost-effective and highly accurate.

Conclusions

This method can benefit a wide range of applications from the routine genotyping of animal and plant populations to the functional study of structural variants in humans.

SUBMITTER: Kuhn A

PROVIDER: S-EPMC4494700 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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Publications

Read count-based method for high-throughput allelic genotyping of transposable elements and structural variants.

Kuhn Alexandre A Ong Yao Min YM Quake Stephen R SR Burkholder William F WF

BMC genomics 20150708

<h4>Background</h4>Like other structural variants, transposable element insertions can be highly polymorphic across individuals. Their functional impact, however, remains poorly understood. Current genome-wide approaches for genotyping insertion-site polymorphisms based on targeted or whole-genome sequencing remain very expensive and can lack accuracy, hence new large-scale genotyping methods are needed.<h4>Results</h4>We describe a high-throughput method for genotyping transposable element inse ...[more]

PMID: 26153459

Similar Datasets

Project description:BackgroundTransposable elements (TEs), which constitute nearly half of the human genome, have long been regarded as genomic "dark matter". However, their reactivation in tumor cells, resulting in the production of TE-chimeric transcripts (TCTs), has emerged as a potential driver of cancer progression. The complexity and full extent of these transcripts remain elusive, largely due to the limitations of short-read next-generation sequencing technologies. These methods have struggled to comprehensively capture the diversity and structure of TCTs, particularly those involving short interspersed nuclear elements (SINEs) or closely co-transcribed TEs.MethodsLeveraging full-length cDNA sequencing technology based on nanopore sequencing platform, we developed a customized pipeline for identifying and quantifying TCTs in 19 lung adenocarcinoma (LUAD) cell lines. The short-read RNA-seq dataset from a LUAD corhort (~ 200 tumor samples) was employed to validate the identified TCTs and explore their association with tumor progression. To assess the functional roles of a specific TCTs, cell migration and cell proliferation assays were performed.ResultsWe uncovered 208 unique TCT candidates in the LUAD cell lines. Our approach allowed for the identification of cryptic promoters and terminators within non-transposing TEs. Notably, we identified a chimeric transcript involving MIR_HKDC1, which appears to play a significant role in the progression of LUAD. Furthermore, the expression of these TCTs were associated with poor clinical outcomes in a cohort of LUAD patients, suggesting their potential as novel biomarkers for both LUAD progression and prognosis.ConclusionsOur study underscores the application of long-read sequencing to unravel the complex landscape of TCTs in LUAD. We provide a comprehensive characterization of TCTs in LUAD, exploring their potential regulatory roles in cancer progression. These findings contribute to a deeper understanding of the genomic intricacies underlying cancer, and offer new directions for the development of targeted therapies and personalized treatment strategies for LUAD. This research highlights the potential of TCTs as both biomarkers and therapeutic targets in the oncogenesis, offering new insights into the interplay between transposable elements and gene regulation in cancer.

Dataset Information

Read count-based method for high-throughput allelic genotyping of transposable elements and structural variants.

Background

Results

Conclusions

Publications

Read count-based method for high-throughput allelic genotyping of transposable elements and structural variants.

Similar Datasets

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