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Identification of polymorphic SVA retrotransposons using a mobile element scanning method for SVA (ME-Scan-SVA)

BACKGROUND: Mobile element insertions are a major source of human genomic variation. SVA (SINE-R/VNTR/Alu) is the youngest retrotransposon family in the human genome and a number of diseases are known to be caused by SVA insertions. However, inter-individual genomic variations generated by SVA inser...

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Detalles Bibliográficos
Autores principales: Ha, Hongseok, Loh, Jui Wan, Xing, Jinchuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4967303/
https://www.ncbi.nlm.nih.gov/pubmed/27478512
http://dx.doi.org/10.1186/s13100-016-0072-x
Descripción
Sumario:BACKGROUND: Mobile element insertions are a major source of human genomic variation. SVA (SINE-R/VNTR/Alu) is the youngest retrotransposon family in the human genome and a number of diseases are known to be caused by SVA insertions. However, inter-individual genomic variations generated by SVA insertions and their impacts have not been studied extensively due to the difficulty in identifying polymorphic SVA insertions. RESULTS: To systematically identify SVA insertions at the population level and assess their genomic impact, we developed a mobile element scanning (ME-Scan) protocol we called ME-Scan-SVA. Using a nested SVA-specific PCR enrichment method, ME-Scan-SVA selectively amplify the 5′ end of SVA elements and their flanking genomic regions. To demonstrate the utility of the protocol, we constructed and sequenced a ME-Scan-SVA library of 21 individuals and analyzed the data using a new analysis pipeline designed for the protocol. Overall, the method achieved high SVA-specificity and over >90 % of the sequenced reads are from SVA insertions. The method also had high sensitivity (>90 %) for fixed SVA insertions that contain the SVA-specific primer-binding sites in the reference genome. Using candidate locus selection criteria that are expected to have a 90 % sensitivity, we identified 151 and 29 novel polymorphic SVA candidates under relaxed and stringent cutoffs, respectively (average 12 and 2 per individual). For six polymorphic SVAs that we were able to validate by PCR, the average individual genotype accuracy is 92 %, demonstrating a high accuracy of the computational genotype calling pipeline. CONCLUSIONS: The new approach allows identifying novel SVA insertions using high-throughput sequencing. It is cost-effective and can be applied in large-scale population study. It also can be applied for detecting potential active SVA elements, and somatic SVA retrotransposition events in different tissues or developmental stages. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13100-016-0072-x) contains supplementary material, which is available to authorized users.