Logo image
Characterisation of retrotransposon insertion polymorphisms in whole genome sequencing data from individuals with amyotrophic lateral sclerosis
Journal article   Open access   Peer reviewed

Characterisation of retrotransposon insertion polymorphisms in whole genome sequencing data from individuals with amyotrophic lateral sclerosis

A.L. Savage, A. Iacoangeli, G.G. Schumann, A. Rubio-Roldan, J.L. Garcia-Perez, A. Al Khleifat, S. Kõks, V.J. Bubb, A. Al-Chalabi and J.P. Quinn
Gene, Vol.843, Art. 146799
2022
pdf
retrotransposon.pdfDownloadView
Published (Version of Record) Open Access
url
Free to Read *No subscription requiredView

Abstract

The genetics of an individual is a crucial factor in understanding the risk of developing the neurodegenerative disease amyotrophic lateral sclerosis (ALS). There is still a large proportion of the heritability of ALS, particularly in sporadic cases, to be understood. Among others, active transposable elements drive inter-individual variability, and in humans long interspersed element 1 (LINE1, L1), Alu and SINE-VNTR-Alu (SVA) retrotransposons are a source of polymorphic insertions in the population. We undertook a pilot study to characterise the landscape of non-reference retrotransposon insertion polymorphisms (non-ref RIPs) in 15 control and 15 ALS individuals’ whole genomes from Project MinE, an international project to identify potential genetic causes of ALS. The combination of two bioinformatics tools (mobile element locator tool (MELT) and TEBreak) identified on average 1250 Alu, 232 L1 and 77 SVA non-ref RIPs per genome across the 30 analysed. Further PCR validation of individual polymorphic retrotransposon insertions showed a similar level of accuracy for MELT and TEBreak. Our preliminary study did not identify a specific RIP or a significant difference in the total number of non-ref RIPs in ALS compared to control genomes. The use of multiple bioinformatic tools improved the accuracy of non-ref RIP detection and our study highlights the potential importance of studying these elements further in ALS.

Details

UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

Source: InCites

Metrics

23 File views/ downloads
63 Record Views

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Collaboration types
Domestic collaboration
International collaboration
Citation topics
1 Clinical & Life Sciences
1.54 Molecular & Cell Biology - Genetics
1.54.1122 Transposable Elements
Web Of Science research areas
Genetics & Heredity
ESI research areas
Molecular Biology & Genetics
Logo image