ArticleBMC bioinformatics2019
Impact of polymorphic transposable elements on transcription in lymphoblastoid cell lines from public data.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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Who cites it
10 citing papers in PubMed, 16 citations in OpenAlex.
- An eQTL-based approach reveals candidate regulators of LINE-1 RNA levels in lymphoblastoid cells.PLoS genetics · 2024Article
- Investigating mobile element variations by statistical genetics.Human genome variation · 2024Review
- Regulation of expression quantitative trait loci by SVA retrotransposons within the major histocompatibility complex.Experimental biology and medicine (Maywood, N.J.) · 2023Article
- An eQTL-based Approach Reveals Candidate Regulators of LINE-1 RNA Levels in Lymphoblastoid Cells.bioRxiv : the preprint server for biology · 2023Article
- Exploratory analysis of L1 retrotransposons expression in autism.Molecular autism · 2023Article
- Transposable Elements in Pluripotent Stem Cells and Human Disease.Frontiers in genetics · 2022Review
- Role of Transposable Elements in Gene Regulation in the Human Genome.Life (Basel, Switzerland) · 2021Review
- Haplotype Shuffling and Dimorphic Transposable Elements in the Human Extended Major Histocompatibility Complex Class II Region.Frontiers in genetics · 2021Article
- Haplotypic Associations and Differentiation of MHC Class II Polymorphic Alu Insertions at Five Loci With HLA-DRB1 Alleles in 12 Minority Ethnic Populations in China.Frontiers in genetics · 2021Article
- Polymorphic mobile element insertions contribute to gene expression and alternative splicing in human tissues.Genome biology · 2020Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundTransposable elements (TEs) are DNA sequences able to mobilize themselves and to increase their copy-number in the host genome. In the past, they have been considered mainly selfish DNA without evident functions. Nevertheless, currently they are believed to have been extensively involved in the evolution of primate genomes, especially from a regulatory perspective. Due to their recent activity they are also one of the primary sources of structural variants (SVs) in the human genome. By taking advantage of sequencing technologies and bioinformatics tools, recent surveys uncovered specific TE structural variants (TEVs) that gave rise to polymorphisms in human populations. When combined with RNA-seq data this information provides the opportunity to study the potential impact of TEs on gene expression in human.
resultsIn this work, we assessed the effects of the presence of specific TEs in cis on the expression of flanking genes by producing associations between polymorphic TEs and flanking gene expression levels in human lymphoblastoid cell lines. By using public data from the 1000 Genome Project and the Geuvadis consortium, we exploited an expression quantitative trait loci (eQTL) approach integrated with additional bioinformatics data mining analyses. We uncovered human loci enriched for common, less common and rare TEVs and identified 323 significant TEV-cis-eQTL associations. SINE-R/VNTR/Alus (SVAs) resulted the TE class with the strongest effects on gene expression. We also unveiled differential functional enrichments on genes associated to TEVs, genes associated to TEV-cis-eQTLs and genes associated to the genomic regions mostly enriched in TEV-cis-eQTLs highlighting, at multiple levels, the impact of TEVs on the host genome. Finally, we also identified polymorphic TEs putatively embedded in transcriptional units, proposing a novel mechanism in which TEVs may mediate individual-specific traits.
conclusionWe contributed to unveiling the effect of polymorphic TEs on transcription in lymphoblastoid cell lines.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.