Mobile Element Insertions Research Articles

Characterizing mobile element insertions in 5675 genomes.

Mobile element insertions (MEIs) are a major class of structural variants (SVs) and have been linked to many human genetic disorders, including hemophilia, neurofibromatosis, and various cancers. However, human MEI resources from large-scale genome sequencing are still lacking compared to those for SNPs and SVs. Here, we report a comprehensive map of 36 699 non-reference MEIs constructed from 5675 genomes, comprising 2998 Chinese samples (∼26.2×, NyuWa) and 2677 samples from the 1000 Genomes Project (∼7.4×, 1KGP). We discovered that LINE-1 insertions were highly enriched in centromere regions, implying the role of chromosome context in retroelement insertion. After functional annotation, we estimated that MEIs are responsible for about 9.3% of all protein-truncating events per genome. Finally, we built a companion database named HMEID for public use. This resource represents the latest and largest genomewide study on MEIs and will have broad utility for exploration of human MEI findings.

Mutagenesis of human genomes by endogenous mobile elements on a population scale.

Several large-scale Illumina whole-genome sequencing (WGS) and whole-exome sequencing (WES) projects have emerged recently that have provided exceptional opportunities to discover mobile element insertions (MEIs) and study the impact of these MEIs on human genomes. However, these projects also have presented major challenges with respect to the scalability and computational costs associated with performing MEI discovery on tens or even hundreds of thousands of samples. To meet these challenges, we have developed a more efficient and scalable version of our mobile element locator tool (MELT) called CloudMELT. We then used MELT and CloudMELT to perform MEI discovery in 57,919 human genomes and exomes, leading to the discovery of 104,350 nonredundant MEIs. We leveraged this collection (1) to examine potentially active L1 source elements that drive the mobilization of new Alu, L1, and SVA MEIs in humans; (2) to examine the population distributions and subfamilies of these MEIs; and (3) to examine the mutagenesis of GENCODE genes, ENCODE-annotated features, and disease genes by these MEIs. Our study provides new insights on the L1 source elements that drive MEI mutagenesis and brings forth a better understanding of how this mutagenesis impacts human genomes.

The Dynamism of Transposon Methylation for Plant Development and Stress Adaptation.

Plant development processes are regulated by epigenetic alterations that shape nuclear structure, gene expression, and phenotypic plasticity; these alterations can provide the plant with protection from environmental stresses. During plant growth and development, these processes play a significant role in regulating gene expression to remodel chromatin structure. These epigenetic alterations are mainly regulated by transposable elements (TEs) whose abundance in plant genomes results in their interaction with genomes. Thus, TEs are the main source of epigenetic changes and form a substantial part of the plant genome. Furthermore, TEs can be activated under stress conditions, and activated elements cause mutagenic effects and substantial genetic variability. This introduces novel gene functions and structural variation in the insertion sites and primarily contributes to epigenetic modifications. Altogether, these modifications indirectly or directly provide the ability to withstand environmental stresses. In recent years, many studies have shown that TE methylation plays a major role in the evolution of the plant genome through epigenetic process that regulate gene imprinting, thereby upholding genome stability. The induced genetic rearrangements and insertions of mobile genetic elements in regions of active euchromatin contribute to genome alteration, leading to genomic stress. These TE-mediated epigenetic modifications lead to phenotypic diversity, genetic variation, and environmental stress tolerance. Thus, TE methylation is essential for plant evolution and stress adaptation, and TEs hold a relevant military position in the plant genome. High-throughput techniques have greatly advanced the understanding of TE-mediated gene expression and its associations with genome methylation and suggest that controlled mobilization of TEs could be used for crop breeding. However, development application in this area has been limited, and an integrated view of TE function and subsequent processes is lacking. In this review, we explore the enormous diversity and likely functions of the TE repertoire in adaptive evolution and discuss some recent examples of how TEs impact gene expression in plant development and stress adaptation.

Structural variants are a major source of gene expression differences in humans and often affect multiple nearby genes.

Structural variants (SVs) are an important source of human genome diversity, but their functional effects are poorly understood. We mapped 61,668 SVs in 613 individuals from the GTEx project and measured their effects on gene expression. We estimate that common SVs are causal at 2.66% of eQTLs, a 10.5-fold enrichment relative to their abundance in the genome. Duplications and deletions were the most impactful variant types, whereas the contribution of mobile element insertions was small (0.12% of eQTLs, 1.9-fold enriched). Multitissue analysis of eQTLs revealed that gene-altering SVs show more constitutive effects than other variant types, with 62.09% of coding SV-eQTLs active in all tissues with eQTL activity compared with 23.08% of coding SNV- and indel-eQTLs. Noncoding SVs, SNVs and indels show broadly similar patterns. We also identified 539 rare SVs associated with nearby gene expression outliers. Of these, 62.34% are noncoding SVs that affect gene expression but have modest enrichment at regulatory elements, showing that rare noncoding SVs are a major source of gene expression differences but remain difficult to predict from current annotations. Both common and rare SVs often affect the expression of multiple genes: SV-eQTLs affect an average of 1.82 nearby genes, whereas SNV- and indel-eQTLs affect an average of 1.09 genes, and 21.34% of rare expression-altering SVs show effects on two to nine different genes. We also observe significant effects on rare gene expression changes extending 1 Mb from the SV. This provides a mechanism by which individual SVs may have strong or pleiotropic effects on phenotypic variation.

In Silico identification of a common mobile element insertion in exon 4 of RP1

Mobile element insertions (MEIs) typically exceed the read lengths of short-read sequencing technologies and are therefore frequently missed. Recently, a founder Alu insertion in exon 4 of RP1 has been detected in Japanese patients with macular dystrophy by PCR and gel electrophoresis. We aimed to develop a grep search program for the detection of the Alu insertion in exon 4 of RP1 using unprocessed short reads. Among 494 unrelated Korean patients with inherited eye diseases, 273 patients with specific retinal phenotypes who were previously genotyped by targeted panel or whole exome sequencing were selected. Five probands had a single heterozygous truncating RP1 variant, and one of their unaffected parents also carry this variant. To find a hidden genetic variant, whole genome sequencing was performed in two patients, and it revealed AluY c.4052_4053ins328/p.(Tyr1352Alafs*9) insertion in RP1 exon 4. This AluY insertion was additionally identified in other 3 families, which was confirmed by PCR and gel electrophoresis. We developed simplified grep search program to detect this AluY insertion in RP1 exon 4. The simple grep search revealed a median variant allele frequency of 0.282 (interquartile range, 0.232–0.383), with no false-positive results using 120 control samples. The MEI in RP1 exon 4 was a common founder mutation in Korean, occurring in 1.8% of our cohort. The RP1-Alu grep program efficiently detected the AluY insertion, without the preprocessing of raw data or complex installation processes.

Mobile element insertions and associated structural variants in longitudinal breast cancer samples

While mobile elements are largely inactive in healthy somatic tissues, increased activity has been found in cancer tissues, with significant variation among different cancer types. In addition to insertion events, mobile elements have also been found to mediate many structural variation events in the genome. Here, to better understand the timing and impact of mobile element insertions and associated structural variants in cancer, we examined their activity in longitudinal samples of four metastatic breast cancer patients. We identified 11 mobile element insertions or associated structural variants and found that the majority of these occurred early in tumor progression. Most of the variants impact intergenic regions; however, we identified a translocation interrupting MAP2K4 involving Alu elements and a deletion in YTHDF2 involving mobile elements that likely inactivate reported tumor suppressor genes. The high variant allele fraction of the translocation, the loss of the other copy of MAP2K4, the recurrent loss-of-function mutations found in this gene in other cancers, and the important function of MAP2K4 indicate that this translocation is potentially a driver mutation. Overall, using a unique longitudinal dataset, we find that most variants are likely passenger mutations in the four patients we examined, but some variants impact tumor progression.

Cas9 targeted enrichment of mobile elements using nanopore sequencing

Mobile element insertions (MEIs) are repetitive genomic sequences that contribute to genetic variation and can lead to genetic disorders. Targeted and whole-genome approaches using short-read sequencing have been developed to identify reference and non-reference MEIs; however, the read length hampers detection of these elements in complex genomic regions. Here, we pair Cas9-targeted nanopore sequencing with computational methodologies to capture active MEIs in human genomes. We demonstrate parallel enrichment for distinct classes of MEIs, averaging 44% of reads on-targeted signals and exhibiting a 13.4-54x enrichment over whole-genome approaches. We show an individual flow cell can recover most MEIs (97% L1Hs, 93% AluYb, 51% AluYa, 99% SVA_F, and 65% SVA_E). We identify seventeen non-reference MEIs in GM12878 overlooked by modern, long-read analysis pipelines, primarily in repetitive genomic regions. This work introduces the utility of nanopore sequencing for MEI enrichment and lays the foundation for rapid discovery of elusive, repetitive genetic elements.

Comparison of mitochondrial genomes provides insights into intron dynamics and evolution in Botryosphaeria dothidea and B. kuwatsukai

Botryosphaeria dothidea is one of the most common fungal pathogens on a large number of hosts worldwide. Botryosphaeria dothidea and B. kuwatsukai are also the main causal agents of apple ring rot. In this study, we sequenced, assembled and annotated the circular mitogenomes of 12 diverse B. dothidea isolates (105.7-114.8kb) infecting various plants including apple, and five diverse B. kuwatsukai isolates (118.0-124.6kb) from apple. B. dothidea mitogenomes harboured a set of 29-31 introns and 48-52 ORFs. In contrast, B. kuwatsukai mitogenomes harboured more introns (32-34) and ORFs (51-54). The variation in mitogenome sizes was associated mainly with different numbers of introns and insertions of mobile genetic elements. Interestingly, B. dothidea and B. kuwatsukai displayed distinct intron distribution patterns, with three intron loci showing presence/absence dynamics in each species. Large numbers of introns (57% in B. dothidea and 49% in B. kuwatsukai) were most likely obtained through horizontal transfer from non-Dothideomycetes. The mitochondrial gene phylogeny supported the differentiation of the two species. Overall, this study sheds light into the mitochondrial evolution of the plant pathogens B. dothidea and B. kuwatsukai, and intron distribution patterns could be useful markers for studies on population diversity.

Genome-wide strand asymmetry in massively parallel reporter activity favors genic strands.

Massively parallel reporter assays (MPRAs) are useful tools to characterize regulatory elements in human genomes. An aspect of MPRAs that is not typically the focus of analysis is their intrinsic ability to differentiate activity levels for a given sequence element when placed in both of its possible orientations relative to the reporter construct. Here, we describe pervasive strand asymmetry of MPRA signals in data sets from multiple reporter configurations in both published and newly reported data. These effects are reproducible across different cell types and in different treatments within a cell type and are observed both within and outside of annotated regulatory elements. From elements in gene bodies, MPRA strand asymmetry favors the sense strand, suggesting that function related to endogenous transcription is driving the phenomenon. Similarly, we find that within Alu mobile element insertions, strand asymmetry favors the transcribed strand of the ancestral retrotransposon. The effect is consistent across the multiplicity of Alu elements in human genomes and is more pronounced in less diverged Alu elements. We find sequence features driving MPRA strand asymmetry and show its prediction from sequence alone. We see some evidence for RNA stabilization and transcriptional activation mechanisms and hypothesize that the effect is driven by natural selection favoring efficient transcription. Our results indicate that strand asymmetry is a pervasive and reproducible feature in MPRA data. More importantly, the fact that MPRA asymmetry favors naturally transcribed strands suggests that it stems from preserved biological functions that have a substantial, global impact on gene and genome evolution.

Assessing the utility of long-read nanopore sequencing for rapid and efficient characterization of mobile element insertions

Short-read next generation sequencing (NGS) has become the predominant first-line technique used to diagnose patients with rare genetic conditions. Inherent limitations of short-read technology, notably for the detection and characterization of complex insertion-containing variants, are offset by the ability to concurrently screen many disease genes. “Third-generation” long-read sequencers are increasingly being deployed as an orthogonal adjunct technology, but their full potential for molecular genetic diagnosis has yet to be exploited. Here, we describe three diagnostic cases in which pathogenic mobile element insertions were refractory to characterization by short-read sequencing. To validate the accuracy of the long-read technology, we first used Sanger sequencing to confirm the integration sites and derive curated benchmark sequences of the variant-containing alleles. Long-read nanopore sequencing was then performed on locus-specific amplicons. Pairwise comparison between these data and the previously determined benchmark alleles revealed 100% identity of the variant-containing sequences. We demonstrate a number of technical advantages over existing wet-laboratory approaches, including in silico size selection of a mixed pool of amplification products, and the relative ease with which an automated informatics workflow can be established. Our findings add to a growing body of literature describing the diagnostic utility of long-read sequencing.

CRISPRbuilder-TB: "CRISPR-builder for tuberculosis". Exhaustive reconstruction of the CRISPR locus in mycobacterium tuberculosis complex using SRA.

Mycobacterium tuberculosis complex (MTC) CRISPR locus diversity has long been studied solely investigating the presence/absence of a known set of spacers. Unveiling the genetic mechanisms of its evolution requires a more exhaustive reconstruction in a large amount of representative strains. In this article, we point out and resolve, with a new pipeline, the problem of CRISPR reconstruction based directly on short read sequences in M. tuberculosis. We first show that the process we set up, that we coin as "CRISPRbuilder-TB" (https://github.com/cguyeux/CRISPRbuilder-TB), allows an efficient reconstruction of simulated or real CRISPRs, even when including complex evolutionary steps like the insertions of mobile elements. Compared to more generalist tools, the whole process is much more precise and robust, and requires only minimal manual investigation. Second, we show that more than 1/3 of the currently complete genomes available for this complex in the public databases contain largely erroneous CRISPR loci. Third, we highlight how both the classical experimental in vitro approach and the basic in silico spoligotyping provided by existing analytic tools miss a whole diversity of this locus in MTC, by not capturing duplications, spacer and direct repeats variants, and IS6110 insertion locations. This description is extended in a second article that describes MTC-CRISPR diversity and suggests general rules for its evolution. This work opens perspectives for an in-depth exploration of M. tuberculosis CRISPR loci diversity and of mechanisms involved in its evolution and its functionality, as well as its adaptation to other CRISPR locus-harboring bacterial species.

Intronic Breakpoint Signatures Enhance Detection and Characterization of Clinically Relevant Germline Structural Variants

The relevance of large copy number variants (CNVs) to hereditary disorders has been long recognized, and population sequencing efforts have chronicled many common structural variants (SVs). However, limited data are available on the clinical contribution of rare germline SVs. Here, a detailed characterization of SVs identified using targeted next-generation sequencing was performed. Across 50 genes associated with hereditary cancer and cardiovascular disorders, a minimum of 828 unique SVs were reported, including 584 fully characterized SVs. Almost 40% of CNVs were <5 kb, with one in three deletions impacting a single exon. Additionally, 36 mid-range deletions/duplications (50 to 250 bp), 21 mobile element insertions, 6 inversions, and 27 complex rearrangements were detected. This data set was used to model SV detection in a bioinformatics pipeline solely relying on read depth, which revealed that genome sequencing (30×) allows detection of 71%, a 500× panel only targeting coding regions 53%, and exome sequencing (100×) <20% of characterized SVs. SVs accounted for 14.1% of all unique pathogenic variants, supporting the importance of SVs in hereditary disorders. Robust SV detection requires an ensemble of variant-calling algorithms that utilize sequencing of intronic regions. These algorithms should use distinct data features representative of each class of mutational mechanism, including recombination between two sequences sharing high similarity, covariants inserted betweenCNV breakpoints, and complex rearrangements containing inverted sequences.

Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia.

Retrotransposons can cause somatic genome variation in the human nervous system, which is hypothesized to have relevance to brain development and neuropsychiatric disease. However, the detection of individual somatic mobile element insertion (MEIs) presents a difficult signal-to-noise problem. Using a machine learning method (RetroSom) and deep whole genome sequencing, we analyzed L1 and Alu retrotransposition in sorted neurons and glia from human brains. We characterized two brain-specific L1 insertions in neurons and glia from a donor with schizophrenia. There was anatomical distribution of the L1 insertions in neurons and glia across both hemispheres, indicating retrotransposition occurred during early embryogenesis. Both insertions were within the introns of genes (CNNM2, FRMD4A) within genomic loci associated with neuropsychiatric disorders. Proof-of-principle experiments revealed these L1 insertions significantly reduced gene expression. These results demonstrate RetroSom has broad applications for studies of brain development and may provide insight into the possible pathological effects of somatic retrotransposition.

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

HiTea is available at https://github.com/parklab/HiTea and as a Docker image. Supplementary data are available at Bioinformatics online.

Towards a better understanding of the low recall of insertion variants with short-read based variant callers

BackgroundSince 2009, numerous tools have been developed to detect structural variants using short read technologies. Insertions >50 bp are one of the hardest type to discover and are drastically underrepresented in gold standard variant callsets. The advent of long read technologies has completely changed the situation. In 2019, two independent cross technologies studies have published the most complete variant callsets with sequence resolved insertions in human individuals. Among the reported insertions, only 17 to 28% could be discovered with short-read based tools.ResultsIn this work, we performed an in-depth analysis of these unprecedented insertion callsets in order to investigate the causes of such failures. We have first established a precise classification of insertion variants according to four layers of characterization: the nature and size of the inserted sequence, the genomic context of the insertion site and the breakpoint junction complexity. Because these levels are intertwined, we then used simulations to characterize the impact of each complexity factor on the recall of several structural variant callers. We showed that most reported insertions exhibited characteristics that may interfere with their discovery: 63% were tandem repeat expansions, 38% contained homology larger than 10 bp within their breakpoint junctions and 70% were located in simple repeats. Consequently, the recall of short-read based variant callers was significantly lower for such insertions (6% for tandem repeats vs 56% for mobile element insertions). Simulations showed that the most impacting factor was the insertion type rather than the genomic context, with various difficulties being handled differently among the tested structural variant callers, and they highlighted the lack of sequence resolution for most insertion calls.ConclusionsOur results explain the low recall by pointing out several difficulty factors among the observed insertion features and provide avenues for improving SV caller algorithms and their combinations.

Complex mosaic structural variations in human fetal brains.

Somatic mosaicism, manifesting as single nucleotide variants (SNVs), mobile element insertions, and structural changes in the DNA, is a common phenomenon in human brain cells, with potential functional consequences. Using a clonal approach, we previously detected 200–400 mosaic SNVs per cell in three human fetal brains (15–21 wk postconception). However, structural variation in the human fetal brain has not yet been investigated. Here, we discover and validate four mosaic structural variants (SVs) in the same brains and resolve their precise breakpoints. The SVs were of kilobase scale and complex, consisting of deletion(s) and rearranged genomic fragments, which sometimes originated from different chromosomes. Sequences at the breakpoints of these rearrangements had microhomologies, suggesting their origin from replication errors. One SV was found in two clones, and we timed its origin to ∼14 wk postconception. No large scale mosaic copy number variants (CNVs) were detectable in normal fetal human brains, suggesting that previously reported megabase-scale CNVs in neurons arise at later stages of development. By reanalysis of public single nuclei data from adult brain neurons, we detected an extrachromosomal circular DNA event. Our study reveals the existence of mosaic SVs in the developing human brain, likely arising from cell proliferation during mid-neurogenesis. Although relatively rare compared to SNVs and present in ∼10% of neurons, SVs in developing human brain affect a comparable number of bases in the genome (∼6200 vs. ∼4000 bp), implying that they may have similar functional consequences.

TIP_finder: An HPC Software to Detect Transposable Element Insertion Polymorphisms in Large Genomic Datasets.

Transposable elements (TEs) are non-static genomic units capable of moving indistinctly from one chromosomal location to another. Their insertion polymorphisms may cause beneficial mutations, such as the creation of new gene function, or deleterious in eukaryotes, e.g., different types of cancer in humans. A particular type of TE called LTR-retrotransposons comprises almost 8% of the human genome. Among LTR retrotransposons, human endogenous retroviruses (HERVs) bear structural and functional similarities to retroviruses. Several tools allow the detection of transposon insertion polymorphisms (TIPs) but fail to efficiently analyze large genomes or large datasets. Here, we developed a computational tool, named TIP_finder, able to detect mobile element insertions in very large genomes, through high-performance computing (HPC) and parallel programming, using the inference of discordant read pair analysis. TIP_finder inputs are (i) short pair reads such as those obtained by Illumina, (ii) a chromosome-level reference genome sequence, and (iii) a database of consensus TE sequences. The HPC strategy we propose adds scalability and provides a useful tool to analyze huge genomic datasets in a decent running time. TIP_finder accelerates the detection of transposon insertion polymorphisms (TIPs) by up to 55 times in breast cancer datasets and 46 times in cancer-free datasets compared to the fastest available algorithms. TIP_finder applies a validated strategy to find TIPs, accelerates the process through HPC, and addresses the issues of runtime for large-scale analyses in the post-genomic era.

Promoter methylation, transcription, and retrotransposition of LINE-1 in colorectal adenomas and adenocarcinomas

BackgroundThe methylation of the CpG islands of the LINE-1 promoter is a tight control mechanism on the function of mobile elements. However, simultaneous quantification of promoter methylation and transcription of LINE-1 has not been performed in progressive stages of colorectal cancer. In addition, the insertion of mobile elements in the genome of advanced adenoma stage, a precancerous stage before colorectal carcinoma has not been emphasized. In this study, we quantify promoter methylation and transcripts of LINE-1 in three stages of colorectal non-advanced adenoma, advanced adenoma, and adenocarcinoma. In addition, we analyze the insertion of LINE-1, Alu, and SVA elements in the genome of patient tumors with colorectal advanced adenomas.MethodsLINE-1 hypomethylation status was evaluated by absolute quantitative analysis of methylated alleles (AQAMA) assay. To quantify the level of transcripts for LINE-1, quantitative RT-PCR was performed. To find mobile element insertions, the advanced adenoma tissue samples were subjected to whole genome sequencing and MELT analysis.ResultsWe found that the LINE-1 promoter methylation in advanced adenoma and adenocarcinoma was significantly lower than that in non-advanced adenomas. Accordingly, the copy number of LINE-1 transcripts in advanced adenoma was significantly higher than that in non-advanced adenomas, and in adenocarcinomas was significantly higher than that in the advanced adenomas. Whole-genome sequencing analysis of colorectal advanced adenomas revealed that at this stage polymorphic insertions of LINE-1, Alu, and SVA comprise approximately 16%, 51%, and 74% of total insertions, respectively.ConclusionsOur correlative analysis showing a decreased methylation of LINE-1 promoter accompanied by the higher level of LINE-1 transcription, and polymorphic genomic insertions in advanced adenoma, suggests that the early and advanced polyp stages may host very important pathogenic processes concluding to cancer.

Divergent Evolution of Mutation Rates and Biases in the Long-Term Evolution Experiment with Escherichia coli.

All organisms encode enzymes that replicate, maintain, pack, recombine, and repair their genetic material. For this reason, mutation rates and biases also evolve by mutation, variation, and natural selection. By examining metagenomic time series of the Lenski long-term evolution experiment (LTEE) with Escherichia coli (Good BH, McDonald MJ, Barrick JE, Lenski RE, Desai MM. 2017. The dynamics of molecular evolution over 60,000 generations. Nature 551(7678):45–50.), we find that local mutation rate variation has evolved during the LTEE. Each LTEE population has evolved idiosyncratic differences in their rates of point mutations, indels, and mobile element insertions, due to the fixation of various hypermutator and antimutator alleles. One LTEE population, called Ara+3, shows a strong, symmetric wave pattern in its density of point mutations, radiating from the origin of replication. This pattern is largely missing from the other LTEE populations, most of which evolved missense, indel, or structural mutations in topA, fis, and dusB—loci that all affect DNA topology. The distribution of mutations in those genes over time suggests epistasis and historical contingency in the evolution of DNA topology, which may have in turn affected local mutation rates. Overall, the replicate populations of the LTEE have largely diverged in their mutation rates and biases, even though they have adapted to identical abiotic conditions.

Early-onset breast cancer in a woman with a germline mobile element insertion resulting in BRCA2 disruption: a case report

Mobile element insertions (MEIs) contribute to genomic diversity, but they can be responsible for human disease in some cases. Initial clinical testing (BRCA1, BRCA2 and PALB2) in a 40-year-old female with unilateral breast cancer did not detect any pathogenic variants. Subsequent reanalysis for MEIs detected a novel likely pathogenic insertion of the retrotransposon element (RE) c.7894_7895insSVA in BRCA2. This case highlights the importance of bioinformatic pipeline optimization for the detection of MEIs in genes associated with hereditary cancer, as early detection can significantly impact clinical management.