TypeTE: a tool to genotype mobile element insertions from whole genome resequencing data

Investigating mobile element variations by statistical genetics

The integration of structural variations (SVs) in statistical genetics provides an opportunity to understand the genetic factors influencing complex human traits and disease. Recent advances in long-read technology and variant calling methods for short reads have improved the accurate discovery and genotyping of SVs, enabling their use in expression quantitative trait loci (eQTL) analysis and genome-wide association studies (GWAS). Mobile elements are DNA sequences that insert themselves into various genome locations. Insertional polymorphisms of mobile elements between humans, called mobile element variations (MEVs), contribute to approximately 25% of human SVs. We recently developed a variant caller that can accurately identify and genotype MEVs from biobank-scale short-read whole-genome sequencing (WGS) datasets and integrate them into statistical genetics. The use of MEVs in eQTL analysis and GWAS has a minimal impact on the discovery of genome loci associated with gene expression and disease; most disease-associated haplotypes can be identified by single nucleotide variations (SNVs). On the other hand, it helps make hypotheses about causal variants or effector variants. Focusing on MEVs, we identified multiple MEVs that contribute to differential gene expression and one of them is a potential cause of skin disease, emphasizing the importance of the integration of MEVs in medical genetics. Here, I will provide an overview of MEVs, MEV calling from WGS, and the integration of MEVs in statistical genetics. Finally, I will discuss the unanswered questions about MEVs, such as rare variants.

Genotyping of Transposable Element Insertions Segregating in Human Populations Using Short-Read Realignments

Transposable element (TE) insertions are a major source of structural variation in the human genome. Due to the repetitive nature and biological importance of TEs, many bioinformatic tools have been developed to identify and genotype TE insertion polymorphisms using high-throughput short-reads. In this chapter, we outline recently developed methods to characterize TE insertion polymorphisms in human populations. We also provide detailed protocols to tackle this question primarily using three software: MELT2, ERVcaller, and TypeREF.

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.

The Absence of Retroelement Activity Is Characteristic for Childhood Acute Leukemias and Adult Acute Lymphoblastic Leukemia

Retroelements (RE) have been proposed as important players in cancerogenesis. Different cancer types are characterized by a different level of tumor-specific RE insertions. In previous studies, small cohorts of hematological malignancies, such as acute myeloid leukemia, multiple myeloma, and chronic lymphocytic leukemia have been characterized by a low level of RE insertional activity. Acute lymphoblastic leukemia (ALL) in adults and childhood acute leukemias have not been studied in this context. We performed a search for new RE insertions (Alu and L1) in 44 childhood ALL, 14 childhood acute myeloid leukemia, and 14 adult ALL samples using a highly sensitive NGS-based approach. First, we evaluated the method sensitivity revealing the 1% detection threshold for the proportion of cells with specific RE insertion. Following this result, we did not identify new tumor-specific RE insertions in the tested cohort of acute leukemia samples at the established level of sensitivity. Additionally, we analyzed the transcription levels of active L1 copies and found them increased. Thus, the increased transcription of active L1 copies is not sufficient for overt elevation of L1 retrotranspositional activity in leukemia.

The Simons Genome Diversity Project: A Global Analysis of Mobile Element Diversity

Ongoing retrotransposition of Alu, LINE-1, and SINE–VNTR–Alu elements generates diversity and variation among human populations. Previous analyses investigating the population genetics of mobile element insertions (MEIs) have been limited by population ascertainment bias or by relatively small numbers of populations and low sequencing coverage. Here, we use 296 individuals representing 142 global populations from the Simons Genome Diversity Project (SGDP) to discover and characterize MEI diversity from deeply sequenced whole-genome data. We report 5,742 MEIs not originally reported by the 1000 Genomes Project and show that high sampling diversity leads to a 4- to 7-fold increase in MEI discovery rates over the original 1000 Genomes Project data. As a result of negative selection, nonreference polymorphic MEIs are underrepresented within genes, and MEIs within genes are often found in the transcriptional orientation opposite that of the gene. Globally, 80% of Alu subfamilies predate the expansion of modern humans from Africa. Polymorphic MEIs show heterozygosity gradients that decrease from Africa to Eurasia to the Americas, and the number of MEIs found uniquely in a single individual are also distributed in this general pattern. The maximum fraction of MEI diversity partitioned among the seven major SGDP population groups (F_ST) is 7.4%, similar to, but slightly lower than, previous estimates and likely attributable to the diverse sampling strategy of the SGDP. Finally, we utilize these MEIs to extrapolate the primary Native American shared ancestry component to back to Asia and provide new evidence from genome-wide identical-by-descent genetic markers that add additional support for a southeastern Siberian origin for most Native Americans.

Identification and Genotyping of Transposable Element Insertions From Genome Sequencing Data

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.

Single-Strand Annealing in Cancer

DNA double-strand breaks (DSBs) are among the most serious forms of DNA damage. In humans, DSBs are repaired mainly by non-homologous end joining (NHEJ) and homologous recombination repair (HRR). Single-strand annealing (SSA), another DSB repair system, uses homologous repeats flanking a DSB to join DNA ends and is error-prone, as it removes DNA fragments between repeats along with one repeat. Many DNA deletions observed in cancer cells display homology at breakpoint junctions, suggesting the involvement of SSA. When multiple DSBs occur in different chromosomes, SSA may result in chromosomal translocations, essential in the pathogenesis of many cancers. Inhibition of RAD52 (RAD52 Homolog, DNA Repair Protein), the master regulator of SSA, results in decreased proliferation of BRCA1/2 (BRCA1/2 DNA Repair Associated)-deficient cells, occurring in many hereditary breast and ovarian cancer cases. Therefore, RAD52 may be targeted in synthetic lethality in cancer. SSA may modulate the response to platinum-based anticancer drugs and radiation. SSA may increase the efficacy of the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)/Cas9 (CRISPR associated 9) genome editing and reduce its off-target effect. Several basic problems associated with SSA, including its evolutionary role, interplay with HRR and NHEJ and should be addressed to better understand its role in cancer pathogenesis and therapy.

SeqURE - a new copy-capture based method for sequencing of unknown Retroposition events

Background

Retroelements (REs) occupy a significant part of all eukaryotic genomes including humans. The majority of retroelements in the human genome are inactive and unable to retrotranspose. Dozens of active copies are repressed in most normal tissues by various cellular mechanisms. These copies can become active in normal germline and brain tissues or in cancer, leading to new retroposition events. The consequences of such events and their role in normal cell functioning and carcinogenesis are not yet fully understood. If new insertions occur in a small portion of cells they can be found only with the use of specific methods based on RE enrichment and high-throughput sequencing. The downside of the high sensitivity of such methods is the presence of various artifacts imitating real insertions, which in many cases cannot be validated due to lack of the initial template DNA. For this reason, adequate assessment of rare (< 1%) subclonal cancer specific RE insertions is complicated.

Results

Here we describe a new copy-capture technique which we implemented in a method called SeqURE for Sequencing Unknown of Retroposition Events that allows for efficient and reliable identification of new genomic RE insertions. The method is based on the capture of copies of target molecules (copy-capture), selective amplification and sequencing of genomic regions adjacent to active RE insertions from both sides. Importantly, the template genomic DNA remains intact and can be used for validation experiments. In addition, we applied a novel system for testing method sensitivity and precisely showed the ability of the developed method to reliably detect insertions present in 1 out of 100 cells and a substantial portion of insertions present in 1 out of 1000 cells. Using advantages of the method we showed the absence of somatic Alu insertions in colorectal cancer samples bearing tumor-specific L1HS insertions.

Conclusions

This study presents the first description and implementation of the copy-capture technique and provides the first methodological basis for the quantitative assessment of RE insertions present in a small portion of cells.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13100-020-00228-6.

Identification and characterisation of endogenous Avian Leukosis Virus subgroup E (ALVE) insertions in chicken whole genome sequencing data

Background

Endogenous retroviruses (ERVs) are the remnants of retroviral infections which can elicit prolonged genomic and immunological stress on their host organism. In chickens, endogenous Avian Leukosis Virus subgroup E (ALVE) expression has been associated with reductions in muscle growth rate and egg production, as well as providing the potential for novel recombinant viruses. However, ALVEs can remain in commercial stock due to their incomplete identification and association with desirable traits, such as ALVE21 and slow feathering. The availability of whole genome sequencing (WGS) data facilitates high-throughput identification and characterisation of these retroviral remnants.

Results

We have developed obsERVer, a new bioinformatic ERV identification pipeline which can identify ALVEs in WGS data without further sequencing. With this pipeline, 20 ALVEs were identified across eight elite layer lines from Hy-Line International, including four novel integrations and characterisation of a fast feathered phenotypic revertant that still contained ALVE21. These bioinformatically detected sites were subsequently validated using new high-throughput KASP assays, which showed that obsERVer was highly precise and exhibited a 0% false discovery rate. A further fifty-seven diverse chicken WGS datasets were analysed for their ALVE content, identifying a total of 322 integration sites, over 80% of which were novel. Like exogenous ALV, ALVEs show site preference for proximity to protein-coding genes, but also exhibit signs of selection against deleterious integrations within genes.

Conclusions

obsERVer is a highly precise and broadly applicable pipeline for identifying retroviral integrations in WGS data. ALVE identification in commercial layers has aided development of high-throughput diagnostic assays which will aid ALVE management, with the aim to eventually eradicate ALVEs from high performance lines. Analysis of non-commercial chicken datasets with obsERVer has revealed broad ALVE diversity and facilitates the study of the biological effects of these ERVs in wild and domesticated populations.