Browse
Submit Data
Databases
API
Help

Dataset Information

22 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

HiTea: a computational pipeline to identify non-reference transposable element insertions in Hi-C data.

ABSTRACT: Hi-C is a common technique for assessing 3D chromatin conformation. Recent studies have shown that long-range interaction information in Hi-C data can be used to generate chromosome-length genome assemblies and identify large-scale structural variations. Here, we demonstrate the use of Hi-C data in detecting mobile transposable element (TE) insertions genome-wide. Our pipeline Hi-C-based TE analyzer (HiTea) capitalizes on clipped Hi-C reads and is aided by a high proportion of discordant read pairs in Hi-C data to detect insertions of three major families of active human TEs. Despite the uneven genome coverage in Hi-C data, HiTea is competitive with the existing callers based on whole-genome sequencing (WGS) data and can supplement the WGS-based characterization of the TE-insertion landscape. We employ the pipeline to identify TE-insertions from human cell-line Hi-C samples.

Availability and implementation

HiTea is available at https://github.com/parklab/HiTea and as a Docker image.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Jain D

PROVIDER: S-EPMC8599941 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

McClintock: An Integrated Pipeline for Detecting Transposable Element Insertions in Whole-Genome Shotgun Sequencing Data.

Project description:Transposable element (TE) insertions are among the most challenging types of variants to detect in genomic data because of their repetitive nature and complex mechanisms of replication . Nevertheless, the recent availability of large resequencing data sets has spurred the development of many new methods to detect TE insertions in whole-genome shotgun sequences. Here we report an integrated bioinformatics pipeline for the detection of TE insertions in whole-genome shotgun data, called McClintock (https://github.com/bergmanlab/mcclintock), which automatically runs and standardizes output for multiple TE detection methods. We demonstrate the utility of McClintock by evaluating six TE detection methods using simulated and real genome data from the model microbial eukaryote, Saccharomyces cerevisiae We find substantial variation among McClintock component methods in their ability to detect nonreference TEs in the yeast genome, but show that nonreference TEs at nearly all biologically realistic locations can be detected in simulated data by combining multiple methods that use split-read and read-pair evidence. In general, our results reveal that split-read methods detect fewer nonreference TE insertions than read-pair methods, but generally have much higher positional accuracy. Analysis of a large sample of real yeast genomes reveals that most McClintock component methods can recover known aspects of TE biology in yeast such as the transpositional activity status of families, target preferences, and target site duplication structure, albeit with varying levels of accuracy. Our work provides a general framework for integrating and analyzing results from multiple TE detection methods, as well as useful guidance for researchers studying TEs in yeast resequencing data.

| S-EPMC5555480 | biostudies-literature

SnapHiC: a computational pipeline to identify chromatin loops from single-cell Hi-C data.

Project description:Single-cell Hi-C (scHi-C) analysis has been increasingly used to map chromatin architecture in diverse tissue contexts, but computational tools to define chromatin loops at high resolution from scHi-C data are still lacking. Here, we describe Single-Nucleus Analysis Pipeline for Hi-C (SnapHiC), a method that can identify chromatin loops at high resolution and accuracy from scHi-C data. Using scHi-C data from 742 mouse embryonic stem cells, we benchmark SnapHiC against a number of computational tools developed for mapping chromatin loops and interactions from bulk Hi-C. We further demonstrate its use by analyzing single-nucleus methyl-3C-seq data from 2,869 human prefrontal cortical cells, which uncovers cell type-specific chromatin loops and predicts putative target genes for noncoding sequence variants associated with neuropsychiatric disorders. Our results indicate that SnapHiC could facilitate the analysis of cell type-specific chromatin architecture and gene regulatory programs in complex tissues.

| S-EPMC8440170 | biostudies-literature

Identification and Genotyping of Transposable Element Insertions From Genome Sequencing Data.

Project description:Transposable element (TE) mobilization is a significant source of genomic variation and has been associated with various human diseases. The exponential growth of population-scale whole-genome sequencing and rapid innovations in long-read sequencing technologies provide unprecedented opportunities to study TE insertions and their functional impact in human health and disease. Identifying TE insertions, however, is challenging due to the repetitive nature of the TE sequences. Here, we review computational approaches to detecting and genotyping TE insertions using short- and long-read sequencing and discuss the strengths and weaknesses of different approaches. © 2020 Wiley Periodicals LLC.

| S-EPMC8906366 | biostudies-literature

Transposable Element Insertions in Long Intergenic Non-Coding RNA Genes.

Project description:Transposable elements (TEs) are abundant in mammalian genomes and appear to have contributed to the evolution of their hosts by providing novel regulatory or coding sequences. We analyzed different regions of long intergenic non-coding RNA (lincRNA) genes in human and mouse genomes to systematically assess the potential contribution of TEs to the evolution of the structure and regulation of expression of lincRNA genes. Introns of lincRNA genes contain the highest percentage of TE-derived sequences (TES), followed by exons and then promoter regions although the density of TEs is not significantly different between exons and promoters. Higher frequencies of ancient TEs in promoters and exons compared to introns implies that many lincRNA genes emerged before the split of primates and rodents. The content of TES in lincRNA genes is substantially higher than that in protein-coding genes, especially in exons and promoter regions. A significant positive correlation was detected between the content of TEs and evolutionary rate of lincRNAs indicating that inserted TEs are preferentially fixed in fast-evolving lincRNA genes. These results are consistent with the repeat insertion domains of LncRNAs hypothesis under which TEs have substantially contributed to the origin, evolution, and, in particular, fast functional diversification, of lincRNA genes.

| S-EPMC4460805 | biostudies-other

Transposable element insertions in 1000 Swedish individuals.

Project description:The majority of rare diseases are genetic, and regardless of advanced high-throughput genomics-based investigations, 60% of patients remain undiagnosed. A major factor limiting our ability to identify disease-causing alterations is a poor understanding of the morbid and normal human genome. A major genomic contributor of which function and distribution remain largely unstudied are the transposable elements (TE), which constitute 50% of our genome. Here we aim to resolve this knowledge gap and increase the diagnostic yield of rare disease patients investigated with clinical genome sequencing. To this end we characterized TE insertions in 1000 Swedish individuals from the SweGen dataset and 2504 individuals from the 1000 Genomes Project (1KGP), creating seven population-specific TE insertion databases. Of note, 66% of TE insertions in SweGen were present at >1% in the 1KGP databases, proving that most insertions are common across populations. Focusing on the rare TE insertions, we show that even though ~0.7% of those insertions affect protein coding genes, they rarely affect known disease casing genes (<0.1%). Finally, we applied a TE insertion identification workflow on two clinical cases where disease causing TE insertions were suspected and could verify the presence of pathogenic TE insertions in both. Altogether we demonstrate the importance of TE insertion detection and highlight possible clinical implications in rare disease diagnostics.

| S-EPMC10381067 | biostudies-literature

SnapHiC-D: a computational pipeline to identify differential chromatin contacts from single cell Hi-C data

Project description:Single cell Hi-C (scHi-C) has been used to map genome organization in complex tissues. However, computational tools to detect dynamic chromatin contacts from scHi-C datasets in development and through disease pathogenesis are still lacking. Here, we present SnapHiC-D, a computational pipeline to identify differential chromatin contacts (DCCs) between two scHi-C datasets. Compared to methods designed for bulk Hi-C data, SnapHiC-D detects DCCs with high sensitivity and accuracy. We used SnapHiC-D to identify cell-type-specific chromatin contacts at 10 kilobase resolution in mouse hippocampal and human prefrontal cortical tissues, and demonstrated that DCCs detected in the cortical and hippocampal cell types are generally correlated with cell-type-specific gene expression patterns and epigenomic features. SnapHiC-D is freely available at https://github.com/HuMingLab/SnapHiC-D.

2023-08-24 | GSE210585 | GEO

Contribution of unfixed transposable element insertions to human regulatory variation.

Project description:Thousands of unfixed transposable element (TE) insertions segregate in the human population, but little is known about their impact on genome function. Recently, a few studies associated unfixed TE insertions to mRNA levels of adjacent genes, but the biological significance of these associations, their replicability across cell types and the mechanisms by which they may regulate genes remain largely unknown. Here, we performed a TE-expression QTL analysis of 444 lymphoblastoid cell lines (LCL) and 289 induced pluripotent stem cells using a newly developed set of genotypes for 2743 polymorphic TE insertions. We identified 211 and 176 TE-eQTL acting in cis in each respective cell type. Approximately 18% were shared across cell types with strongly correlated effects. Furthermore, analysis of chromatin accessibility QTL in a subset of the LCL suggests that unfixed TEs often modulate the activity of enhancers and other distal regulatory DNA elements, which tend to lose accessibility when a TE inserts within them. We also document a case of an unfixed TE likely influencing gene expression at the post-transcriptional level. Our study points to broad and diverse cis-regulatory effects of unfixed TEs in the human population and underscores their plausible contribution to phenotypic variation. This article is part of a discussion meeting issue 'Crossroads between transposons and gene regulation'.

| S-EPMC7061991 | biostudies-literature

Comprehensive identification of transposable element insertions using multiple sequencing technologies.

Project description:Transposable elements (TEs) help shape the structure and function of the human genome. When inserted into some locations, TEs may disrupt gene regulation and cause diseases. Here, we present xTea (x-Transposable element analyzer), a tool for identifying TE insertions in whole-genome sequencing data. Whereas existing methods are mostly designed for short-read data, xTea can be applied to both short-read and long-read data. Our analysis shows that xTea outperforms other short read-based methods for both germline and somatic TE insertion discovery. With long-read data, we created a catalogue of polymorphic insertions with full assembly and annotation of insertional sequences for various types of retroelements, including pseudogenes and endogenous retroviruses. Notably, we find that individual genomes have an average of nine groups of full-length L1s in centromeres, suggesting that centromeres and other highly repetitive regions such as telomeres are a significant yet unexplored source of active L1s. xTea is available at https://github.com/parklab/xTea .

| S-EPMC8219666 | biostudies-literature

Chicdiff: a computational pipeline for detecting differential chromosomal interactions in Capture Hi-C data.

Project description:SummaryCapture Hi-C is a powerful approach for detecting chromosomal interactions involving, at least on one end, DNA regions of interest, such as gene promoters. We present Chicdiff, an R package for robust detection of differential interactions in Capture Hi-C data. Chicdiff enhances a state-of-the-art differential testing approach for count data with bespoke normalization and multiple testing procedures that account for specific statistical properties of Capture Hi-C. We validate Chicdiff on published Promoter Capture Hi-C data in human Monocytes and CD4+ T cells, identifying multitudes of cell type-specific interactions, and confirming the overall positive association between promoter interactions and gene expression.Availability and implementationChicdiff is implemented as an R package that is publicly available at https://github.com/RegulatoryGenomicsGroup/chicdiff.Supplementary informationSupplementary data are available at Bioinformatics online.

| S-EPMC6853696 | biostudies-literature

An age-of-allele test of neutrality for transposable element insertions.

Project description:How natural selection acts to limit the proliferation of transposable elements (TEs) in genomes has been of interest to evolutionary biologists for many years. To describe TE dynamics in populations, previous studies have used models of transposition-selection equilibrium that assume a constant rate of transposition. However, since TE invasions are known to happen in bursts through time, this assumption may not be reasonable. Here we propose a test of neutrality for TE insertions that does not rely on the assumption of a constant transposition rate. We consider the case of TE insertions that have been ascertained from a single haploid reference genome sequence. By conditioning on the age of an individual TE insertion allele (inferred by the number of unique substitutions that have occurred within the particular TE sequence since insertion), we determine the probability distribution of the insertion allele frequency in a population sample under neutrality. Taking models of varying population size into account, we then evaluate predictions of our model against allele frequency data from 190 retrotransposon insertions sampled from North American and African populations of Drosophila melanogaster. Using this nonequilibrium neutral model, we are able to explain ? 80% of the variance in TE insertion allele frequencies based on age alone. Controlling for both nonequilibrium dynamics of transposition and host demography, we provide evidence for negative selection acting against most TEs as well as for positive selection acting on a small subset of TEs. Our work establishes a new framework for the analysis of the evolutionary forces governing large insertion mutations like TEs, gene duplications, or other copy number variants.

| S-EPMC3914624 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data