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Assessment of genetic variation for the LINE-1 retrotransposon from next generation sequence data
- Source :
- BMC Bioinformatics, Vol 11, Iss Suppl 9, p S12 (2010), BMC Bioinformatics
- Publisher :
- Springer Nature
-
Abstract
- Background In humans, copies of the Long Interspersed Nuclear Element 1 (LINE-1) retrotransposon comprise 21% of the reference genome, and have been shown to modulate expression and produce novel splice isoforms of transcripts from genes that span or neighbor the LINE-1 insertion site. Results In this work, newly released pilot data from the 1000 Genomes Project is analyzed to detect previously unreported full length insertions of the retrotransposon LINE-1. By direct analysis of the sequence data, we have identified 22 previously unreported LINE-1 insertion sites within the sequence data reported for a mother/father/daughter trio. Conclusions It is demonstrated here that next generation sequencing data, as well as emerging high quality datasets from individual genome projects allow us to assess the amount of heterogeneity with respect to the LINE-1 retrotransposon amongst humans, and provide us with a wealth of testable hypotheses as to the impact that this diversity may have on the health of individuals and populations.
- Subjects :
- Molecular Sequence Data
Retrotransposon
Biology
lcsh:Computer applications to medicine. Medical informatics
Genome
Biochemistry
03 medical and health sciences
0302 clinical medicine
Structural Biology
Phylogenetics
Databases, Genetic
Genetic variation
Humans
Gene
lcsh:QH301-705.5
Molecular Biology
Phylogeny
030304 developmental biology
Genetics
0303 health sciences
Base Sequence
Applied Mathematics
Genetic Variation
Computer Science Applications
Long interspersed nuclear element
Proceedings
Long Interspersed Nucleotide Elements
lcsh:Biology (General)
lcsh:R858-859.7
DNA microarray
030217 neurology & neurosurgery
Reference genome
Subjects
Details
- Language :
- English
- ISSN :
- 14712105
- Volume :
- 11
- Issue :
- Suppl 9
- Database :
- OpenAIRE
- Journal :
- BMC Bioinformatics
- Accession number :
- edsair.doi.dedup.....522fad70017c6261d0d4d45fb281ebb0
- Full Text :
- https://doi.org/10.1186/1471-2105-11-s9-s12