Transposable elements are associated with the variable response to influenza infection

Chen, X; Pacis, Alain; Aracena, Katherine A.; Gona, Saideep; Kwan, Tony; Groza, Cristian; Lin, Yen-Lung; Sindeaux, Renata H.M.; Yotova, Vania; Pramatarova, Albéna; Maguire, Simon; Pastinen, Tomi; Barreiro, Luis B.; Bourque, Guillaume

doi:10.1016/j.xgen.2023.100292

Cited by 6 publications

(8 citation statements)

References 63 publications

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“…A similar trend is observed with TE biomarkers like MER48, and MER54A, suggesting these TEs are accessible in uninfected monocytes but transcriptionally dormant. This leads us to propose that such TEs may be primed to a “poised” state that might correlate to monocyte function [50]. Notably, several of these TEs, previously identified as “poised”, featured prominently among the upregulated TEs.…”

Section: Resultsmentioning

confidence: 99%

MATES: A Deep Learning-Based Model for Locus-specific Quantification of Transposable Elements in Single Cell

Wang,

Zheng,

Zhang

et al. 2024

Preprint

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Transposable elements (TEs) are crucial for genetic diversity and gene regulation. Current single-cell quantification methods often align multi-mapping reads to either `best-mapped' or `random-mapped' locations and categorize them at sub-family levels, overlooking the biological necessity for accurate, locus-specific TE quantification. Moreover, these existing methods are primarily designed for and focused on transcriptomics data, which restricts their adaptability to single-cell data of other modalities. To address these challenges, here we introduce MATES, a novel deep-learning approach that accurately allocates multi-mapping reads to specific loci of TEs, utilizing context from adjacent read alignments flanking the TE locus. When applied to diverse single-cell omics datasets, MATES shows improved performance over existing methods, enhancing the accuracy of TE quantification and aiding in the identification of marker TEs for identified cell populations. This development enables exploring single-cell heterogeneity and gene regulation through the lens of TEs, offering a transformative tool for the single-cell genomics community.

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Section: Resultsmentioning

confidence: 99%

MATES: A Deep Learning-Based Model for Locus-specific Quantification of Transposable Elements in Single Cell

Wang,

Zheng,

Zhang

et al. 2024

Preprint

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“…We downloaded the ATAC-seq peaks from the NCBI Gene Expression Omnibus (GEO) database (GSE115046) (Inoue et al 2019). After that, we used the same approach as we previously described to evaluate the enrichment level relative to the random genomic background per TE subfamily (Chen et al 2023). Briefly, we first shuffled the peak regions 1000 times relative to the distribution of peaks.…”

Section: Methodsmentioning

confidence: 99%

“…The additional ATAC-seq and H3K27ac peak files were downloaded from the same sources. Fold change per subfamily between ESCs and NPCs was computed as we described previously (Chen et al 2023). We then kept subfamilies with a minimum of two-fold enrichment of chromatin accessibility in ESCs compared to NPCs.…”

Section: Methodsmentioning

confidence: 99%

“…Simian-specific LTR subfamilies were detected as the LTR subfamilies with a minimum of 100 instances (≥ 200 bp) and a maximum of 20% instances that were shared with the lemur genome. Evolutionary ages were computed based on the divergence rates as we previously described (Chen et al 2023). Briefly, the divergence rates were first divided by the substitution rate for the human genome (2.2×10 -9 ) and then averaged across instances from each subfamily as the evolutionary age.…”

Section: Ltr Orthology and Sequence Divergence Analysismentioning

confidence: 99%

“…The computed reads per million (RPM) distribution of accessible MER11B instances were first aligned to each subfamily consensus sequence using the downloaded ".align" file as we previously described (Chen et al 2023). We determined the consensus accessible regions based on the aggregated RPM distribution along the consensus sequences.…”

Section: Detection Of Sequence Frames Along the Ltr Consensus Sequencesmentioning

confidence: 99%

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Cryptic endogenous retrovirus subfamilies in the primate lineage

Chen,

Zhang,

Yan

et al. 2023

Preprint

Self Cite

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Many endogenous retroviruses (ERVs) in the human genome are primate-specific and have contributed novel cis-regulatory elements and transcripts. However, current approaches for classifying and annotating ERVs and their long terminal repeats (LTRs) have limited resolution and are inaccurate. Here, we developed a new annotation based on phylogenetic analysis and cross-species conservation. Focusing on the evolutionary young MER11A/B/C subfamilies, we revealed the presence of 4 ‘phyletic groups’, that better explained the epigenetic heterogeneity observed within these subfamilies, suggesting a new annotation for 412 (19.8%) of the MER11 instances. Furthermore, we functionally validated the regulatory potential of these four phyletic groups using a massively parallel reporter assay (MPRA), which also identified motifs associated with their differential activities. Combining MPRA with phyletic groups across primates revealed an apes-specific gain of SOX related motifs through a single-nucleotide deletion. Lastly, by applying our approach across 53 primate-specific LTR subfamilies, we determined the presence of 75 phyletic groups and found that 3,807 (30.0%) instances from 26 LTR subfamilies could be categorized into a novel phyletic group, many of which with a distinct epigenetic profile. Thus, with our refined annotation of primate-specific LTRs, it will be possible to better understand the evolution in primate genomes and potentially identify new roles for ERV/LTRs in their hosts.

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TDP-43 chronic deficiency leads to dysregulation of transposable elements and gene expression by affecting R-loop and 5hmC crosstalk

Hou,

Li,

Xiang

et al. 2024

Cell Reports

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Transposable elements are associated with the variable response to influenza infection

Cited by 6 publications

References 63 publications

MATES: A Deep Learning-Based Model for Locus-specific Quantification of Transposable Elements in Single Cell

MATES: A Deep Learning-Based Model for Locus-specific Quantification of Transposable Elements in Single Cell

Cryptic endogenous retrovirus subfamilies in the primate lineage

TDP-43 chronic deficiency leads to dysregulation of transposable elements and gene expression by affecting R-loop and 5hmC crosstalk

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