RetroSeq: transposable element discovery from next-generation sequencing data

detectEVE: Fast, Sensitive and Precise Detection of Endogenous Viral Elements in Genomic Data

Endogenous viral elements (EVEs) are fragments of viral genomic material embedded within the host genome. Retroviruses contribute to the majority of EVEs because of their genomic integration during their life cycle; however, the latter can also arise from non-retroviral RNA or DNA viruses, then collectively known as non-retroviral (nr) EVEs. Detecting nrEVEs poses challenges because of their sequence and genomic structural diversity, contributing to the scarcity of specific tools designed for nrEVEs detection. Here, we introduce detectEVE, a user-friendly and open-source tool designed for the accurate identification of nrEVEs in genomic assemblies. detectEVE deviates from other nrEVE detection pipelines, which usually classify sequences in a more rigid manner as either virus-associated or not. Instead, we implemented a scaling system assigning confidence scores to hits in protein sequence similarity searches, using bit score distributions and search hints related to various viral characteristics, allowing for higher sensitivity and specificity. Our benchmarking shows that detectEVE is computationally efficient and accurate, as well as considerably faster than existing approaches, because of its resource-efficient parallel execution. Our tool can help to fill current gaps in both host-associated fields and virus-related studies. This includes (i) enhancing genome annotations with metadata for EVE loci, (ii) conducting large-scale paleo-virological studies to explore deep viral evolutionary histories, and (iii) aiding in the identification of actively expressed EVEs in transcriptomic data, reducing the risk of misinterpretations between exogenous viruses and EVEs.

Endogenous retrovirus loci and induced changes in gene expression in Japanese indigenous chickens

When retroviruses infect germ cells and are transmitted to offspring, they become endogenous retroviruses (ERVs), whose insertions may influence the expression of nearby genes. In this study, we aimed to identify the genomic loci of ERVs in commercial broiler (Ross308), Tosa-Jidori, and Yakido chickens, as well as to elucidate their impact on neighboring gene expression. Whole-genome data were obtained using next-generation sequencing, and candidate ERV loci were identified using the RetroSeq software. The Integrative Genomics Viewer tool was used to confirm target site duplications (TSDs) as evidence of ERV insertions. All reads within 200 bp of these TSDs were extracted to create contigs, confirming the presence of ERV sequences in the contigs using BLASTN. Gene expression levels were estimated by focusing on genes located near the 172 identified ERV loci. Among these, 119 loci were detected in broiler chickens, 80 in Tosa-Jidori chickens, and 86 in Yakido chickens, with 28 loci shared among them. Moreover, of these 172 loci, 75 were located within or near genes. Significant differences in gene expression were observed for N-acetylated alpha-linked acidic dipeptidase 2 (NAALAD2) and phosphoribosylaminoimidazolesuccinocarboxamide synthase (PAICS) depending on the presence of ERV insertions. These results suggest that ERV insertions may influence the expression of NAALAD2 and PAICS, providing insights into the genetic diversity and evolutionary background of commercial and indigenous chickens. Understanding the effects of ERV insertions on gene expression can inform future genetic research and poultry breeding programs aimed at improving health and productivity.

Leveraging long-read assemblies and machine learning to enhance short-read transposable element detection and genotyping

Transposable elements (TEs) are parasitic genomic elements that are ubiquitous across the tree of life and play a crucial role in genome evolution. Advances in long-read sequencing have allowed highly accurate TE detection, though at a higher cost than short-read sequencing. Recent studies using long reads have shown that existing short-read TE detection methods perform inadequately when applied to real data. In this study, we use a machine learning approach (called TEforest) to discover and genotype TE insertions and deletions with short-read data by using TEs detected from long-read genome assemblies as training data. Our method first uses a highly sensitive algorithm to discover potential TE insertion or deletion sites in the genome, extracting relevant features from short-read alignments. To discriminate between true and false TE insertions, we train a random forest model with a labeled ground-truth dataset for which we have calculated the same set of short-read features. We conduct a comprehensive benchmark of TEforest and traditional TE detection methods using real data, finding that TEforest identifies more true positives and fewer false positives across datasets with different read lengths and coverages, while also accurately inferring genotypes and the precise breakpoints of insertions. By learning short-read signatures of TEs previously only discoverable using long reads, our approach bridges the gap between large-scale population genetic studies and the accuracy of long-read assemblies. This work provides a user-friendly tool to study the prevalence and phenotypic effects of TE insertions across the genome.

Detecting transposable elements in long-read genomes using sTELLeR

MOTIVATION

Repeat elements, such as transposable elements (TE), are highly repetitive DNA sequences that compose around 50% of the genome. TEs such as Alu, SVA, HERV, and L1 elements can cause disease through disrupting genes, causing frameshift mutations or altering splicing patters. These are elements challenging to characterize using short-read genome sequencing, due to its read length and TEs repetitive nature. Long-read genome sequencing (lrGS) enables bridging of TEs, allowing increased resolution across repetitive DNA sequences. lrGS therefore present an opportunity for improved TE detection and analysis not only from a research perspective but also for future clinical detection. When choosing an lrGS TE caller, parameters such as runtime, CPU hours, sensitivity, precision, and compatibility with inclusion into pipelines are crucial for efficient detection.

RESULTS

We therefore developed sTELLeR, (s) Transposable ELement in Long (e) Read, for accurate, fast, and effective TE detection. Particularly, sTELLeR exhibit higher precision and sensitivity for calling of Alu elements than similar tools. The caller is 5-48× as fast and uses <2% of the CPU hours compared to competitive callers. The caller is haplotype aware and output results in a variant call format (VCF) file, enabling compatibility with other variant callers and downstream analysis.

AVAILABILITY AND IMPLEMENTATION

sTELLeR is a python-based tool and is available at https://github.com/kristinebilgrav/sTELLeR. Altogether, we show that sTELLeR is a fast, sensitive, and precise caller for detection of TE elements, and can easily be implemented into variant calling workflows.

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.

The genomic landscape of Vk*MYC myeloma highlights shared pathways of transformation between mice and humans

Multiple myeloma (MM) is a heterogeneous disease characterized by frequent MYC translocations. Sporadic MYC activation in the germinal center of genetically engineered Vk*MYC mice is sufficient to induce plasma cell tumors in which a variety of secondary mutations are spontaneously acquired and selected over time. Analysis of 119 Vk*MYC myeloma reveals recurrent copy number alterations, structural variations, chromothripsis, driver mutations, apolipoprotein B mRNA-editing enzyme, catalytic polypeptide (APOBEC) mutational activity, and a progressive decrease in immunoglobulin transcription that inversely correlates with proliferation. Moreover, we identify frequent insertional mutagenesis by endogenous retro-elements as a murine specific mechanism to activate NF-kB and IL6 signaling pathways shared with human MM. Despite the increased genomic complexity associated with progression, advanced tumors remain dependent on MYC. In summary, here we credential the Vk*MYC mouse as a unique resource to explore MM genomic evolution and describe a fully annotated collection of diverse and immortalized murine MM tumors.

Contribution of de novo retroelements to birth defects and childhood cancers

Insertion of active retroelements-L1s, Alus, and SVAs-can disrupt proper genome function and lead to various disorders including cancer. However, the role of de novo retroelements (DNRTs) in birth defects and childhood cancers has not been well characterized due to the lack of adequate data and efficient computational tools. Here, we examine whole-genome sequencing data of 3,244 trios from 12 birth defect and childhood cancer cohorts in the Gabriella Miller Kids First Pediatric Research Program. Using an improved version of our tool xTea (x-Transposable element analyzer) that incorporates a deep-learning module, we identified 162 DNRTs, as well as 2 pseudogene insertions. Several variants are likely to be causal, such as a de novo Alu insertion that led to the ablation of a whole exon in the NF1 gene in a proband with brain tumor. We observe a high de novo SVA insertion burden in both high-intolerance loss-of-function genes and exons as well as more frequent de novo Alu insertions of paternal origin. We also identify potential mosaic DNRTs from embryonic stages. Our study reveals the important roles of DNRTs in causing birth defects and predisposition to childhood cancers.

Endogenous retroviral solo-LTRs in human genome

Human endogenous retroviruses (HERVs) are derived from the infection and integration of exogenetic retroviruses. HERVs account for 8% of human genome, and the majority of HERVs are solitary LTRs (solo-LTRs) due to homologous recombination. Multiple findings have showed that solo-LTRs could provide an enormous reservoir of transcriptional regulatory sequences involved in diverse biological processes, especially carcinogenesis and cancer development. The link between solo-LTRs and human diseases still remains poorly understood. This review focuses on the regulatory modules of solo-LTRs, which contribute greatly to the diversification and evolution of human genes. More importantly, although inactivating mutations, insertions and deletions have been identified in solo-LTRs, the inherited regulatory elements of solo-LTRs initiate the expression of chimeric lncRNA transcripts, which have been reported to play crucial roles in human health and disease. These findings provide valuable insights into the evolutionary and functional mechanisms underlying the presence of HERVs in human genome. Taken together, in this review, we will present evidences showing the regulatory and encoding capacity of solo-LTRs as well as the significant impact on various aspects of human biology.

Contrasting segregation patterns among endogenous retroviruses across the koala population

Koalas (Phascolarctos cinereus) have experienced a history of retroviral epidemics leaving their trace as heritable endogenous retroviruses (ERVs) in their genomes. A recently identified ERV lineage, named phaCin-β, shows a pattern of recent, possibly current, activity with high insertional polymorphism in the population. Here, we investigate geographic patterns of three focal ERV lineages of increasing estimated ages, from the koala retrovirus (KoRV) to phaCin-β and to phaCin-β-like, using the whole-genome sequencing of 430 koalas from the Koala Genome Survey. Thousands of ERV loci were found across the population, with contrasting patterns of polymorphism. Northern individuals had thousands of KoRV integrations and hundreds of phaCin-β ERVs. In contrast, southern individuals had higher phaCin-β frequencies, possibly reflecting more recent activity and a founder effect. Overall, our findings suggest high ERV burden in koalas, reflecting historic retrovirus-host interactions. Importantly, the ERV catalogue supplies improved markers for conservation genetics in this endangered species.

The role of transposable elements in human evolution and methods for their functional analysis: current status and future perspectives

Transposable elements (TEs) are mobile DNA sequences that can insert themselves into various locations within the genome, causing mutations that may provide advantages or disadvantages to individuals and species. The insertion of TEs can result in genetic variation that may affect a wide range of human traits including genetic disorders. Understanding the role of TEs in human biology is crucial for both evolutionary and medical research. This review discusses the involvement of TEs in human traits and disease susceptibility, as well as methods for functional analysis of TEs.

Emerging Opportunities to Study Mobile Element Insertions and Their Source Elements in an Expanding Universe of Sequenced Human Genomes

Three mobile element classes, namely Alu, LINE-1 (L1), and SVA elements, remain actively mobile in human genomes and continue to produce new mobile element insertions (MEIs). Historically, MEIs have been discovered and studied using several methods, including: (1) Southern blots, (2) PCR (including PCR display), and (3) the detection of MEI copies from young subfamilies. We are now entering a new phase of MEI discovery where these methods are being replaced by whole genome sequencing and bioinformatics analysis to discover novel MEIs. We expect that the universe of sequenced human genomes will continue to expand rapidly over the next several years, both with short-read and long-read technologies. These resources will provide unprecedented opportunities to discover MEIs and study their impact on human traits and diseases. They also will allow the MEI community to discover and study the source elements that produce these new MEIs, which will facilitate our ability to study source element regulation in various tissue contexts and disease states. This, in turn, will allow us to better understand MEI mutagenesis in humans and the impact of this mutagenesis on human biology.

Online data resource for exploring transposon insertion polymorphisms in public soybean germplasm accessions

Soybean (Glycine max L. Merrill) is one of the most important economical crops. A large number of whole-genome resequencing datasets have been generated and are increasingly expanded for exploring genetic diversity and mining important quantitative trait loci. Most genome-wide association studies have focused on single-nucleotide polymorphisms, short insertions, and deletions. Nevertheless, structure variants mainly caused by transposon element mobilization are not fully considered. To fill this gap, we uniformly processed the publicly available whole-genome resequencing data from 5,521 soybean germplasm accessions and built an online soybean transposon insertion polymorphisms database named Soybean Transposon Insertion Polymorphisms Database (SoyTIPdb) (https://biotec.njau.edu.cn/soytipdb). The collected germplasm accessions derived from more than 45 countries and 160 regions representing the most comprehensive genetic diversity of soybean. SoyTIPdb implements easy-to-use query, analysis, and browse functions to help understand and find meaningful structural variations from TE insertions. In conclusion, SoyTIPdb is a valuable data resource and will help soybean breeders/researchers take advantage of the whole-genome sequencing datasets available in the public depositories.

Homeostasis of flavonoids and triterpenoids most likely modulates starch metabolism for pollen tube penetration in rice

In angiosperms, the timely delivery of sperm cell nuclei by pollen tube (PT) to the ovule is vital for double fertilization. Penetration of PT into maternal stigma tissue is a critical step for sperm cell nuclei delivery, yet little is known about the process. Here, a male-specific and sporophytic mutant xt6, where PTs are able to germinate but unable to penetrate the stigma tissue, is reported in Oryza sativa. Through genetic study, the causative gene was identified as Chalcone synthase (OsCHS1), encoding the first enzyme in flavonoid biosynthesis. Indeed, flavonols were undetected in mutant pollen grains and PTs, indicating that the mutation abolished flavonoid biosynthesis. Nevertheless, the phenotype cannot be rescued by exogenous application of quercetin and kaempferol as reported in maize and petunia, suggesting a different mechanism exists in rice. Further analysis showed that loss of OsCHS1 function disrupted the homeostasis of flavonoid and triterpenoid metabolism and led to the accumulation of triterpenoid, which inhibits significantly α-amylase activity, amyloplast hydrolysis and monosaccharide content in xt6, these ultimately impaired tricarboxylic acid (TCA) cycle, reduced ATP content and lowered the turgor pressure as well. Our findings reveal a new mechanism that OsCHS1 modulates starch hydrolysis and glycometabolism through modulating the metabolic homeostasis of flavonoids and triterpenoids which affects α-amylase activity to maintain PT penetration in rice, which contributes to a better understanding of the function of CHS1 in crop fertility and breeding.

Young SINEs in pig genomes impact gene regulation, genetic diversity, and complex traits

Transposable elements (TEs) are a major source of genetic polymorphisms and play a role in chromatin architecture, gene regulatory networks, and genomic evolution. However, their functional role in pigs and contributions to complex traits are largely unknown. We created a catalog of TEs (n = 3,087,929) in pigs and found that young SINEs were predominantly silenced by histone modifications, DNA methylation, and decreased accessibility. However, some transcripts from active young SINEs showed high tissue-specificity, as confirmed by analyzing 3570 RNA-seq samples. We also detected 211,067 dimorphic SINEs in 374 individuals, including 340 population-specific ones associated with local adaptation. Mapping these dimorphic SINEs to genome-wide associations of 97 complex traits in pigs, we found 54 candidate genes (e.g., ANK2 and VRTN) that might be mediated by TEs. Our findings highlight the important roles of young SINEs and provide a supplement for genotype-to-phenotype associations and modern breeding in pigs.

Aicardi Syndrome Is a Genetically Heterogeneous Disorder

Aicardi Syndrome (AIC) is a rare neurodevelopmental disorder recognized by the classical triad of agenesis of the corpus callosum, chorioretinal lacunae and infantile epileptic spasms syndrome. The diagnostic criteria of AIC were revised in 2005 to include additional phenotypes that are frequently observed in this patient group. AIC has been traditionally considered as X-linked and male lethal because it almost exclusively affects females. Despite numerous genetic and genomic investigations on AIC, a unifying X-linked cause has not been identified. Here, we performed exome and genome sequencing of 10 females with AIC or suspected AIC based on current criteria. We identified a unique de novo variant, each in different genes: KMT2B, SLF1, SMARCB1, SZT2 and WNT8B, in five of these females. Notably, genomic analyses of coding and non-coding single nucleotide variants, short tandem repeats and structural variation highlighted a distinct lack of X-linked candidate genes. We assessed the likely pathogenicity of our candidate autosomal variants using the TOPflash assay for WNT8B and morpholino knockdown in zebrafish (Danio rerio) embryos for other candidates. We show expression of Wnt8b and Slf1 are restricted to clinically relevant cortical tissues during mouse development. Our findings suggest that AIC is genetically heterogeneous with implicated genes converging on molecular pathways central to cortical development.

Transposable element insertions in 1000 Swedish individuals

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.

The Vk*MYC Mouse Model recapitulates human multiple myeloma evolution and genomic diversity

Despite advancements in profiling multiple myeloma (MM) and its precursor conditions, there is limited information on mechanisms underlying disease progression. Clincal efforts designed to deconvolute such mechanisms are challenged by the long lead time between monoclonal gammopathy and its transformation to MM. MM mouse models represent an opportunity to overcome this temporal limitation. Here, we profile the genomic landscape of 118 genetically engineered Vk*MYC MM and reveal that it recapitulates the genomic heterogenenity and life history of human MM. We observed recurrent copy number alterations, structural variations, chromothripsis, driver mutations, APOBEC mutational activity, and a progressive decrease in immunoglobulin transcription that inversely correlates with proliferation. Moreover, we identified frequent insertional mutagenesis by endogenous retro-elements as a murine specific mechanism to activate NF-kB and IL6 signaling pathways shared with human MM. Despite the increased genomic complexity associated with progression, advanced tumors remain dependent on MYC expression, that drives the progression of monoclonal gammopathy to MM.

Reproducible evaluation of transposable element detectors with McClintock 2 guides accurate inference of Ty insertion patterns in yeast

BACKGROUND

Many computational methods have been developed to detect non-reference transposable element (TE) insertions using short-read whole genome sequencing data. The diversity and complexity of such methods often present challenges to new users seeking to reproducibly install, execute, or evaluate multiple TE insertion detectors.

RESULTS

We previously developed the McClintock meta-pipeline to facilitate the installation, execution, and evaluation of six first-generation short-read TE detectors. Here, we report a completely re-implemented version of McClintock written in Python using Snakemake and Conda that improves its installation, error handling, speed, stability, and extensibility. McClintock 2 now includes 12 short-read TE detectors, auxiliary pre-processing and analysis modules, interactive HTML reports, and a simulation framework to reproducibly evaluate the accuracy of component TE detectors. When applied to the model microbial eukaryote Saccharomyces cerevisiae, we find substantial variation in the ability of McClintock 2 components to identify the precise locations of non-reference TE insertions, with RelocaTE2 showing the highest recall and precision in simulated data. We find that RelocaTE2, TEMP, TEMP2 and TEBreak provide consistent estimates of [Formula: see text]50 non-reference TE insertions per strain and that Ty2 has the highest number of non-reference TE insertions in a species-wide panel of [Formula: see text]1000 yeast genomes. Finally, we show that best-in-class predictors for yeast applied to resequencing data have sufficient resolution to reveal a dyad pattern of integration in nucleosome-bound regions upstream of yeast tRNA genes for Ty1, Ty2, and Ty4, allowing us to extend knowledge about fine-scale target preferences revealed previously for experimentally-induced Ty1 insertions to spontaneous insertions for other copia-superfamily retrotransposons in yeast.

CONCLUSION

McClintock ( https://github.com/bergmanlab/mcclintock/ ) provides a user-friendly pipeline for the identification of TEs in short-read WGS data using multiple TE detectors, which should benefit researchers studying TE insertion variation in a wide range of different organisms. Application of the improved McClintock system to simulated and empirical yeast genome data reveals best-in-class methods and novel biological insights for one of the most widely-studied model eukaryotes and provides a paradigm for evaluating and selecting non-reference TE detectors in other species.

Detection of long terminal repeat loci derived from endogenous retrovirus in junglefowl using whole-genome sequencing

Endogenous retroviruses (ERVs) are genetic elements present in the genome that retain traces of past viral infections. Characterization of ERVs can provide crucial insights into avian evolution. This study aimed to identify novel long terminal repeat (LTR) loci derived from ERVs (ERV-LTRs) absent in the reference genome using whole-genome sequencing data of red junglefowl, gray junglefowl, Ceylon junglefowl, and green junglefowl. In total, 835 ERV-LTR loci were identified across the four Gallus species. The numbers of ERV-LTRs loci detected in red junglefowl and its subspecies gray junglefowl, Ceylon junglefowl, and green junglefowl were 362, 216, 193, and 128, respectively. The phylogenetic tree was congruent with previously reported trees, suggesting the potential for inferring relationships among past junglefowl populations from the identified ERV-LTR loci. Of the detected loci, 306 ERV-LTRs were identified near or within the genes, and some were associated with cell adhesion. The detected ERV-LTR sequences were classified as endogenous avian retrovirus family, avian leukosis virus subgroup E, Ovex-1, and murine leukemia virus-related ERVs. In addition, the sequence of the EAV family was divided into four patterns by combining the U3, R, and U5 regions. These findings contribute to a more comprehensive understanding of the characteristics of junglefowl ERVs.

The evolution of two transmissible cancers in Tasmanian devils

Tasmanian devils have spawned two transmissible cancer lineages, named devil facial tumor 1 (DFT1) and devil facial tumor 2 (DFT2). We investigated the genetic diversity and evolution of these clones by analyzing 78 DFT1 and 41 DFT2 genomes relative to a newly assembled, chromosome-level reference. Time-resolved phylogenetic trees reveal that DFT1 first emerged in 1986 (1982 to 1989) and DFT2 in 2011 (2009 to 2012). Subclone analysis documents transmission of heterogeneous cell populations. DFT2 has faster mutation rates than DFT1 across all variant classes, including substitutions, indels, rearrangements, transposable element insertions, and copy number alterations, and we identify a hypermutated DFT1 lineage with defective DNA mismatch repair. Several loci show plausible evidence of positive selection in DFT1 or DFT2, including loss of chromosome Y and inactivation of MGA, but none are common to both cancers. This study reveals the parallel long-term evolution of two transmissible cancers inhabiting a common niche in Tasmanian devils.

Reproducible evaluation of transposable element detectors with McClintock 2 guides accurate inference of Ty insertion patterns in yeast

BACKGROUND

Many computational methods have been developed to detect non-reference transposable element (TE) insertions using short-read whole genome sequencing data. The diversity and complexity of such methods often present challenges to new users seeking to reproducibly install, execute, or evaluate multiple TE insertion detectors.

RESULTS

We previously developed the McClintock meta-pipeline to facilitate the installation, execution, and evaluation of six first-generation short-read TE detectors. Here, we report a completely re-implemented version of McClintock written in Python using Snakemake and Conda that improves its installation, error handling, speed, stability, and extensibility. McClintock 2 now includes 12 short-read TE detectors, auxiliary pre-processing and analysis modules, interactive HTML reports, and a simulation framework to reproducibly evaluate the accuracy of component TE detectors. When applied to the model microbial eukaryote Saccharomyces cerevisiae, we find substantial variation in the ability of McClintock 2 components to identify the precise locations of non-reference TE insertions, with RelocaTE2 showing the highest recall and precision in simulated data. We find that RelocaTE2, TEMP, TEMP2 and TEBreak provide a consistent and biologically meaningful view of non-reference TE insertions in a species-wide panel of ∼1000 yeast genomes, as evaluated by coverage-based abundance estimates and expected patterns of tRNA promoter targeting. Finally, we show that best-in-class predictors for yeast have sufficient resolution to reveal a dyad pattern of integration in nucleosome-bound regions upstream of yeast tRNA genes for Ty1, Ty2, and Ty4, allowing us to extend knowledge about fine-scale target preferences first revealed experimentally for Ty1 to natural insertions and related copia-superfamily retrotransposons in yeast.

CONCLUSION

McClintock (https://github.com/bergmanlab/mcclintock/) provides a user-friendly pipeline for the identification of TEs in short-read WGS data using multiple TE detectors, which should benefit researchers studying TE insertion variation in a wide range of different organisms. Application of the improved McClintock system to simulated and empirical yeast genome data reveals best-in-class methods and novel biological insights for one of the most widely-studied model eukaryotes and provides a paradigm for evaluating and selecting non-reference TE detectors for other species.

An assessment of bioinformatics tools for the detection of human endogenous retroviral insertions in short-read genome sequencing data

There is a growing interest in the study of human endogenous retroviruses (HERVs) given the substantial body of evidence that implicates them in many human diseases. Although their genomic characterization presents numerous technical challenges, next-generation sequencing (NGS) has shown potential to detect HERV insertions and their polymorphisms in humans. Currently, a number of computational tools to detect them in short-read NGS data exist. In order to design optimal analysis pipelines, an independent evaluation of the available tools is required. We evaluated the performance of a set of such tools using a variety of experimental designs and datasets. These included 50 human short-read whole-genome sequencing samples, matching long and short-read sequencing data, and simulated short-read NGS data. Our results highlight a great performance variability of the tools across the datasets and suggest that different tools might be suitable for different study designs. However, specialized tools designed to detect exclusively human endogenous retroviruses consistently outperformed generalist tools that detect a wider range of transposable elements. We suggest that, if sufficient computing resources are available, using multiple HERV detection tools to obtain a consensus set of insertion loci may be ideal. Furthermore, given that the false positive discovery rate of the tools varied between 8% and 55% across tools and datasets, we recommend the wet lab validation of predicted insertions if DNA samples are available.

RetroSnake: A modular pipeline to detect human endogenous retroviruses in genome sequencing data

Human endogenous retroviruses (HERVs) integrated into the human genome as a result of ancient exogenous infections and currently comprise ∼8% of our genome. The members of the most recently acquired HERV family, HERV-Ks, still retain the potential to produce viral molecules and have been linked to a wide range of diseases including cancer and neurodegeneration. Although a range of tools for HERV detection in NGS data exist, most of them lack wet lab validation and they do not cover all steps of the analysis. Here, we describe RetroSnake, an end-to-end, modular, computationally efficient, and customizable pipeline for the discovery of HERVs in short-read NGS data. RetroSnake is based on an extensively wet-lab validated protocol, it covers all steps of the analysis from raw data to the generation of annotated results presented as an interactive html file, and it is easy to use by life scientists without substantial computational training. Availability and implementation: The Pipeline and an extensive documentation are available on GitHub.

Human Retrotransposons and Effective Computational Detection Methods for Next-Generation Sequencing Data

Transposable elements (TEs) are classified into two classes according to their mobilization mechanism. Compared to DNA transposons that move by the "cut and paste" mechanism, retrotransposons mobilize via the "copy and paste" method. They have been an essential research topic because some of the active elements, such as Long interspersed element 1 (LINE-1), Alu, and SVA elements, have contributed to the genetic diversity of primates beyond humans. In addition, they can cause genetic disorders by altering gene expression and generating structural variations (SVs). The development and rapid technological advances in next-generation sequencing (NGS) have led to new perspectives on detecting retrotransposon-mediated SVs, especially insertions. Moreover, various computational methods have been developed based on NGS data to precisely detect the insertions and deletions in the human genome. Therefore, this review discusses details about the recently studied and utilized NGS technologies and the effective computational approaches for discovering retrotransposons through it. The final part covers a diverse range of computational methods for detecting retrotransposon insertions with human NGS data. This review will give researchers insights into understanding the TEs and how to investigate them and find connections with research interests.

svaRetro and svaNUMT: modular packages for annotating retrotransposed transcripts and nuclear integration of mitochondrial DNA in genome sequencing data

Nuclear integration of mitochondrial genomes and retrocopied transcript insertion are biologically important but often-overlooked aspects of structural variant (SV) annotation. While tools for their detection exist, these typically rely on reanalysis of primary data using specialised detectors rather than leveraging calls from general purpose structural variant callers. Such reanalysis potentially leads to additional computational expense and does not take advantage of advances in general purpose structural variant calling. Here, we present svaRetro and svaNUMT; R packages that provide functions for annotating novel genomic events, such as nonreference retrocopied transcripts and nuclear integration of mitochondrial DNA. The packages were developed to work within the Bioconductor framework. We evaluate the performance of these packages to detect events using simulations and public benchmarking datasets, and annotate processed transcripts in a public structural variant database. svaRetro and svaNUMT provide modular, SV-caller agnostic tools for downstream annotation of structural variant calls.

Pattern matching for high precision detection of LINE-1s in human genomes

Background

Long interspersed element 1 (LINE-1 or L1) retrotransposons are mobile elements that constitute 17–20% of the human genome. Strong correlations between abnormal L1 expression and several human diseases have been reported. This has motivated increasing interest in accurate quantification of the number of L1 copies present in any given biologic specimen. A main obstacle toward this aim is that L1s are relatively long DNA segments with regions of high variability, or largely present in the human genome as truncated fragments. These particularities render traditional alignment strategies, such as seed-and-extend inefficient, as the number of segments that are similar to L1s explodes exponentially. This study uses the pattern matching methodology for more accurate identification of L1s. We validate experimentally the superiority of pattern matching for L1 detection over alternative methods and discuss some of its potential applications.

Results

Pattern matching detected full-length L1 copies with high precision, reasonable computational time, and no prior input information. It also detected truncated and significantly altered copies of L1 with relatively high precision. The method was effectively used to annotate L1s in a target genome and to calculate copy number variation with respect to a reference genome. Crucial to the success of implementation was the selection of a small set of k-mer probes from a set of sequences presenting a stable pattern of distribution in the genome. As in seed-and-extend methods, the pattern matching algorithm sowed these k-mer probes, but instead of using heuristic extensions around the seeds, the analysis was based on distribution patterns within the genome. The desired level of precision could be adjusted, with some loss of recall.

Conclusion

Pattern matching is more efficient than seed-and-extend methods for the detection of L1 segments whose characterization depends on a finite set of sequences with common areas of low variability. We propose that pattern matching may help establish correlations between L1 copy number and disease states associated with L1 mobilization and evolution.

Multi-Omic Investigations of a 17-19 Translocation Links MINK1 Disruption to Autism, Epilepsy and Osteoporosis

Balanced structural variants, such as reciprocal translocations, are sometimes hard to detect with sequencing, especially when the breakpoints are located in repetitive or insufficiently mapped regions of the genome. In such cases, long-range information is required to resolve the rearrangement, identify disrupted genes and, in symptomatic carriers, pinpoint the disease-causing mechanisms. Here, we report an individual with autism, epilepsy and osteoporosis and a de novo balanced reciprocal translocation: t(17;19) (p13;p11). The genomic DNA was analyzed by short-, linked- and long-read genome sequencing, as well as optical mapping. Transcriptional consequences were assessed by transcriptome sequencing of patient-specific neuroepithelial stem cells derived from induced pluripotent stem cells (iPSC). The translocation breakpoints were only detected by long-read sequencing, the first on 17p13, located between exon 1 and exon 2 of MINK1 (Misshapen-like kinase 1), and the second in the chromosome 19 centromere. Functional validation in induced neural cells showed that MINK1 expression was reduced by >50% in the patient’s cells compared to healthy control cells. Furthermore, pathway analysis revealed an enrichment of changed neural pathways in the patient’s cells. Altogether, our multi-omics experiments highlight MINK1 as a candidate monogenic disease gene and show the advantages of long-read genome sequencing in capturing centromeric translocations.

Detection of non-reference porcine endogenous retrovirus loci in the Vietnamese native pig genome

The Vietnamese native pig (VnP)-a porcine breed with a small body-has proven suitable as a biomedical animal model. Here, we demonstrate that, compared to other breeds, VnPs have fewer copies of porcine endogenous retroviruses (PERVs), which pose a risk for xenotransplantation of pig organs to humans. More specifically, we sought to characterize non-reference PERVs (nrPERVs) that were previously unidentified in the reference genome. To this end, we used whole-genome sequencing data to identify nrPERV loci with long terminal repeat (LTR) sequences in VnPs. RetroSeq was used to estimate nrPERV loci based on the most current porcine reference genome (Sscrofa11.1). LTRs were detected using de novo sequencing read assembly near the loci containing the target site duplication sequences in the inferred regions. A total of 21 non-reference LTR loci were identified and separated into two subtypes based on phylogenetic analysis. Moreover, PERVs within the detected LTR loci were identified, the presence of which was confirmed using conventional PCR and Sanger sequencing. These novel loci represent previously unknown PERVs as they have not been identified in the porcine reference genome. Thus, our RetroSeq method accurately detects novel PERV loci, and can be applied for development of a useful biomedical model.

Expansion of a retrovirus lineage in the koala genome

Retroviruses have left their legacy in host genomes over millions of years as endogenous retroviruses (ERVs), and their structure, diversity, and prevalence provide insights into the historical dynamics of retrovirus-host interactions. In bioinformatic analyses of koala (Phascolarctos cinereus) whole-genome sequences, we identify a recently expanded ERV lineage (phaCin-β) that is related to the New World squirrel monkey retrovirus. This ERV expansion shares many parallels with the ongoing koala retrovirus (KoRV) invasion of the koala genome, including highly similar and mostly intact sequences, and polymorphic ERV loci in the sampled koala population. The recent phaCin-β ERV colonization of the koala genome appears to predate the current KoRV invasion, but polymorphic ERVs and divergence comparisons between these two lineages predict a currently uncharacterized, possibly still extant, phaCin-β retrovirus. The genomics approach to ERV-guided discovery of novel retroviruses in host species provides a strong incentive to search for phaCin-β retroviruses in the Australasian fauna.

Identification of LINE retrotransposons and long non-coding RNAs expressed in the octopus brain

Background

Transposable elements (TEs) widely contribute to the evolution of genomes allowing genomic innovations, generating germinal and somatic heterogeneity, and giving birth to long non-coding RNAs (lncRNAs). These features have been associated to the evolution, functioning, and complexity of the nervous system at such a level that somatic retrotransposition of long interspersed element (LINE) L1 has been proposed to be associated to human cognition. Among invertebrates, octopuses are fascinating animals whose nervous system reaches a high level of complexity achieving sophisticated cognitive abilities. The sequencing of the genome of the Octopus bimaculoides revealed a striking expansion of TEs which were proposed to have contributed to the evolution of its complex nervous system. We recently found a similar expansion also in the genome of Octopus vulgaris. However, a specific search for the existence and the transcription of full-length transpositionally competent TEs has not been performed in this genus.

Results

Here, we report the identification of LINE elements competent for retrotransposition in Octopus vulgaris and Octopus bimaculoides and show evidence suggesting that they might be transcribed and determine germline and somatic polymorphisms especially in the brain. Transcription and translation measured for one of these elements resulted in specific signals in neurons belonging to areas associated with behavioral plasticity. We also report the transcription of thousands of lncRNAs and the pervasive inclusion of TE fragments in the transcriptomes of both Octopus species, further testifying the crucial activity of TEs in the evolution of the octopus genomes.

Conclusions

The neural transcriptome of the octopus shows the transcription of thousands of putative lncRNAs and of a full-length LINE element belonging to the RTE class. We speculate that a convergent evolutionary process involving retrotransposons activity in the brain has been important for the evolution of sophisticated cognitive abilities in this genus.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01303-5.

Genome-wide clonal variability in European pear "Rocha" using high-throughput sequencing

Pears (Pyrus) are one of the most economically important fruits worldwide. The Pyrus genus is characterized by a high degree of genetic variability between species and interspecific hybrids, and several studies have been performed to assess this variability for both cultivated and wild accessions. These studies have mostly been limited by the resolving power of traditional molecular markers, although in the recent past the availability of reference genome sequences or SNP arrays for pear have enhanced the capability of high-resolution genomics studies. These tools can also be applied to better understand the intra-varietal (or clonal) variability in pear. Here we report the first high resolution genomics analysis of a pear clonal population using whole genome sequencing (WGS). Results showed unique signatures for the accumulation of mutations and transposable element insertions in each clone, which are likely related to their history of propagation and cultivation. The nucleotide diversity remained low in the clonal collection with the exception of few genomic windows, suggesting that balancing selection may be occurring. These windows included mainly genes related to plant fertility. Regions with higher mutational load were partially associated with transcription factors, probably reflecting the distinctive phenotypes in the collection. The annotation of variants also revealed the theoretical disruption of relevant genes in pear. Taken together, the results from this study show that pear clones accumulate mutations differently, and that those mutations can play a role on pear phenotypes, meaning that the study of pear clonal populations can be relevant in genetic studies, mainly when comparing with traditional association studies.

Exploring transposable element-based markers to identify allelic variations underlying agronomic traits in rice

Transposable elements (TEs) are a major force in the production of new alleles during domestication; nevertheless, their use in association studies has been limited because of their complexity. We have developed a TE genotyping pipeline (TEmarker) and applied it to whole-genome genome-wide association study (GWAS) data from 176 Oryza sativa subsp. japonica accessions to identify genetic elements associated with specific agronomic traits. TE markers recovered a large proportion (69%) of single-nucleotide polymorphism (SNP)-based GWAS peaks, and these TE peaks retained ca. 25% of the SNPs. The use of TEs in GWASs may reduce false positives associated with linkage disequilibrium (LD) among SNP markers. A genome scan revealed positive selection on TEs associated with agronomic traits. We found several cases of insertion and deletion variants that potentially resulted from the direct action of TEs, including an allele of LOC_Os11g08410 associated with plant height and panicle length traits. Together, these findings reveal the utility of TE markers for connecting genotype to phenotype and suggest a potential role for TEs in influencing phenotypic variations in rice that impact agronomic traits.

Epistatic selection on a selfish Segregation Distorter supergene - drive, recombination, and genetic load

Meiotic drive supergenes are complexes of alleles at linked loci that together subvert Mendelian segregation resulting in preferential transmission. In males, the most common mechanism of drive involves the disruption of sperm bearing one of a pair of alternative alleles. While at least two loci are important for male drive-the driver and the target-linked modifiers can enhance drive, creating selection pressure to suppress recombination. In this work, we investigate the evolution and genomic consequences of an autosomal, multilocus, male meiotic drive system, Segregation Distorter (SD) in the fruit fly, Drosophila melanogaster. In African populations, the predominant SD chromosome variant, SD-Mal, is characterized by two overlapping, paracentric inversions on chromosome arm 2R and nearly perfect (~100%) transmission. We study the SD-Mal system in detail, exploring its components, chromosomal structure, and evolutionary history. Our findings reveal a recent chromosome-scale selective sweep mediated by strong epistatic selection for haplotypes carrying Sd, the main driving allele, and one or more factors within the double inversion. While most SD-Mal chromosomes are homozygous lethal, SD-Mal haplotypes can recombine with other, complementing haplotypes via crossing over, and with wildtype chromosomes via gene conversion. SD-Mal chromosomes have nevertheless accumulated lethal mutations, excess non-synonymous mutations, and excess transposable element insertions. Therefore, SD-Mal haplotypes evolve as a small, semi-isolated subpopulation with a history of strong selection. These results may explain the evolutionary turnover of SD haplotypes in different populations around the world and have implications for supergene evolution broadly.

Finding and Characterizing Repeats in Plant Genomes

Plant genomes contain a particularly high proportion of repeated structures of various types. This chapter proposes a guided tour of the available software that can help biologists to scan automatically for these repeats in sequence data or check hypothetical models intended to characterize their structures. Since transposable elements (TEs) are a major source of repeats in plants, many methods have been used or developed for this broad class of sequences. They are representative of the range of tools available for other classes of repeats and we have provided two sections on this topic (for the analysis of genomes or directly of sequenced reads), as well as a selection of the main existing software. It may be hard to keep up with the profusion of proposals in this dynamic field and the rest of the chapter is devoted to the foundations of an efficient search for repeats and more complex patterns. We first introduce the key concepts of the art of indexing and mapping or querying sequences. We end the chapter with the more prospective issue of building models of repeat families. We present the Machine Learning approach first, seeking to build predictors automatically for some families of ET, from a set of sequences known to belong to this family. A second approach, the linguistic (or syntactic) approach, allows biologists to describe themselves and check the validity of models of their favorite repeat family.

Current status of structural variation studies in plants

Structural variations (SVs) including gene presence/absence variations and copy number variations are a common feature of genomes in plants and, together with single nucleotide polymorphisms and epigenetic differences, are responsible for the heritable phenotypic diversity observed within and between species. Understanding the contribution of SVs to plant phenotypic variation is important for plant breeders to assist in producing improved varieties. The low resolution of early genetic technologies and inefficient methods have previously limited our understanding of SVs in plants. However, with the rapid expansion in genomic technologies, it is possible to assess SVs with an ever-greater resolution and accuracy. Here, we review the current status of SV studies in plants, examine the roles that SVs play in phenotypic traits, compare current technologies and assess future challenges for SV studies.

Comprehensive identification of transposable element insertions using multiple sequencing technologies

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 .

A benchmark and an algorithm for detecting germline transposon insertions and measuring de novo transposon insertion frequencies

Transposons are genomic parasites, and their new insertions can cause instability and spur the evolution of their host genomes. Rapid accumulation of short-read whole-genome sequencing data provides a great opportunity for studying new transposon insertions and their impacts on the host genome. Although many algorithms are available for detecting transposon insertions, the task remains challenging and existing tools are not designed for identifying de novo insertions. Here, we present a new benchmark fly dataset based on PacBio long-read sequencing and a new method TEMP2 for detecting germline insertions and measuring de novo ‘singleton’ insertion frequencies in eukaryotic genomes. TEMP2 achieves high sensitivity and precision for detecting germline insertions when compared with existing tools using both simulated data in fly and experimental data in fly and human. Furthermore, TEMP2 can accurately assess the frequencies of de novo transposon insertions even with high levels of chimeric reads in simulated datasets; such chimeric reads often occur during the construction of short-read sequencing libraries. By applying TEMP2 to published data on hybrid dysgenic flies inflicted by de-repressed P-elements, we confirmed the continuous new insertions of P-elements in dysgenic offspring before they regain piRNAs for P-element repression. TEMP2 is freely available at Github: https://github.com/weng-lab/TEMP2.

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.

Different types of disease-causing noncoding variants revealed by genomic and gene expression analyses in families with X-linked intellectual disability

The pioneering discovery research of X-linked intellectual disability (XLID) genes has benefitted thousands of individuals worldwide; however, approximately 30% of XLID families still remain unresolved. We postulated that noncoding variants that affect gene regulation or splicing may account for the lack of a genetic diagnosis in some cases. Detecting pathogenic, gene-regulatory variants with the same sensitivity and specificity as structural and coding variants is a major challenge for Mendelian disorders. Here, we describe three pedigrees with suggestive XLID where distinctive phenotypes associated with known genes guided the identification of three different noncoding variants. We used comprehensive structural, single-nucleotide, and repeat expansion analyses of genome sequencing. RNA-Seq from patient-derived cell lines, reverse-transcription polymerase chain reactions, Western blots, and reporter gene assays were used to confirm the functional effect of three fundamentally different classes of pathogenic noncoding variants: a retrotransposon insertion, a novel intronic splice donor, and a canonical splice variant of an untranslated exon. In one family, we excluded a rare coding variant in ARX, a known XLID gene, in favor of a regulatory noncoding variant in OFD1 that correlated with the clinical phenotype. Our results underscore the value of genomic research on unresolved XLID families to aid novel, pathogenic noncoding variant discovery.

A study of transposable element-associated structural variations (TASVs) using a de novo-assembled Korean genome

Advances in next-generation sequencing (NGS) technology have made personal genome sequencing possible, and indeed, many individual human genomes have now been sequenced. Comparisons of these individual genomes have revealed substantial genomic differences between human populations as well as between individuals from closely related ethnic groups. Transposable elements (TEs) are known to be one of the major sources of these variations and act through various mechanisms, including de novo insertion, insertion-mediated deletion, and TE–TE recombination-mediated deletion. In this study, we carried out de novo whole-genome sequencing of one Korean individual (KPGP9) via multiple insert-size libraries. The de novo whole-genome assembly resulted in 31,305 scaffolds with a scaffold N50 size of 13.23 Mb. Furthermore, through computational data analysis and experimental verification, we revealed that 182 TE-associated structural variation (TASV) insertions and 89 TASV deletions contributed 64,232 bp in sequence gain and 82,772 bp in sequence loss, respectively, in the KPGP9 genome relative to the hg19 reference genome. We also verified structural differences associated with TASVs by comparative analysis with TASVs in recent genomes (AK1 and TCGA genomes) and reported their details. Here, we constructed a new Korean de novo whole-genome assembly and provide the first study, to our knowledge, focused on the identification of TASVs in an individual Korean genome. Our findings again highlight the role of TEs as a major driver of structural variations in human individual genomes.

A novel strategy for genome analysis offers insights into the distribution and impact on genome variation of transposable elements, DNA sequences that can replicate and relocate themselves at different chromosomal regions. These sequences, also known as ‘jumping genes’, comprise up to 50% of the genome, but it has proven challenging to map them with existing techniques. Seyoung Mun of Dankook University, Cheonan, South Korea, and coworkers have developed a sequencing and computational analysis strategy that allowed them to accurately map transposable elements across the genome of a Korean individual. These data revealed hundreds of insertion and deletion events relative to an existing reference map of the genome, showing significant alterations in the chromosomal structure. The authors speculate that such widespread transposition events could potentially contribute to individual differences in gene expression and risk of disease.

Detecting Causal Variants in Mendelian Disorders Using Whole-Genome Sequencing

Increasingly affordable sequencing technologies are revolutionizing the field of genomic medicine. It is now feasible to interrogate all major classes of variation in an individual across the entire genome for less than $1000 USD. While the generation of patient sequence information using these technologies has become routine, the analysis and interpretation of this data remains the greatest obstacle to widespread clinical implementation. This chapter summarizes the steps to identify, annotate, and prioritize variant information required for clinical report generation. We discuss methods to detect each variant class and describe strategies to increase the likelihood of detecting causal variant(s) in Mendelian disease. Lastly, we describe a sample workflow for synthesizing large amount of genetic information into concise clinical reports.

Transposable Element Mobilization in Interspecific Yeast Hybrids

Barbara McClintock first hypothesized that interspecific hybridization could provide a “genomic shock” that leads to the mobilization of transposable elements (TEs). This hypothesis is based on the idea that regulation of TE movement is potentially disrupted in hybrids. However, the handful of studies testing this hypothesis have yielded mixed results. Here, we set out to identify if hybridization can increase transposition rate and facilitate colonization of TEs in Saccharomyces cerevisiae × Saccharomyces uvarum interspecific yeast hybrids. Saccharomyces cerevisiae have a small number of active long terminal repeat retrotransposons (Ty elements), whereas their distant relative S. uvarum have lost the Ty elements active in S. cerevisiae. Although the regulation system of Ty elements is known in S. cerevisiae, it is unclear how Ty elements are regulated in other Saccharomyces species, and what mechanisms contributed to the loss of most classes of Ty elements in S. uvarum. Therefore, we first assessed whether TEs could insert in the S. uvarum sub-genome of a S. cerevisiae × S. uvarum hybrid. We induced transposition to occur in these hybrids and developed a sequencing technique to show that Ty elements insert readily and nonrandomly in the S. uvarum genome. We then used an in vivo reporter construct to directly measure transposition rate in hybrids, demonstrating that hybridization itself does not alter rate of mobilization. However, we surprisingly show that species-specific mitochondrial inheritance can change transposition rate by an order of magnitude. Overall, our results provide evidence that hybridization can potentially facilitate the introduction of TEs across species boundaries and alter transposition via mitochondrial transmission, but that this does not lead to unrestrained proliferation of TEs suggested by the genomic shock theory.

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 insertions 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 and FRMD4A) inside genomic loci associated with neuropsychiatric disorders. Proof-of-principle experiments revealed these L1 insertions significantly reduced gene expression. These results demonstrate that RetroSom has broad applications for studies of brain development and may provide insight into the possible pathological effects of somatic retrotransposition.

Spontaneous and Fungicide-Induced Genomic Variation in Sclerotinia sclerotiorum

Stress from exposure to sublethal fungicide doses may cause genomic instability in fungal plant pathogens, which may accelerate the emergence of fungicide resistance or other adaptive traits. In a previous study, five strains of Sclerotinia sclerotiorum were exposed to sublethal doses of four fungicides with different modes of action, and genotyping showed that such exposure induced mutations. The goal of the present study was to characterize genome-wide mutations in response to sublethal fungicide stress in S. sclerotiorum and study the effect of genomic background on the mutational repertoire. The objectives were to determine the effect of sublethal dose exposure and genomic background on mutation frequency/type, distribution of mutations, and fitness costs. Fifty-five S. sclerotiorum genomes were sequenced and aligned to the reference genome. Variants were called and quality filtered to obtain high confidence calls for single nucleotide polymorphisms (SNPs), insertions/deletions (INDELs), copy number variants, and transposable element (TE) insertions. Results suggest that sublethal fungicide exposure significantly increased the frequency of INDELs in two strains from one genomic background (P value ≤ 0.05), while TE insertions were generally repressed for all genomic backgrounds and under all fungicide exposures. The frequency and/or distribution of SNPs, INDELs, and TE insertions varied with genomic background. A propensity for large duplications on chromosome 7 and aneuploidy of this chromosome were observed in the S. sclerotiorum genome. Mutation accumulation did not significantly affect the overall in planta strain aggressiveness (P value > 0.05). Understanding factors that affect pathogen mutation rates can inform disease management strategies that delay resistance evolution.

Analysis of retrotransposon subfamily DNA methylation reveals novel early epigenetic changes in chronic lymphocytic leukemia

Retrotransposons such as LINE-1 and Alu comprise >25% of the human genome. While global hypomethylation of these elements has been widely reported in solid tumours, their epigenetic dysregulation is yet to be characterised in chronic lymphocytic leukemia (CLL), and there has been scant consideration of their evolutionary history that mediates sensitivity to hypomethylation. Here, we developed an approach for locus- and evolutionary subfamily-specific analysis of retrotransposons using the Illumina Infinium Human Methylation 450K microarray platform, which we applied to publicly-available datasets from CLL and other haematological malignancies. We identified 9,797 microarray probes mapping to 117 LINE-1 subfamilies and 13,130 mapping to 37 Alu subfamilies. Of these, 10,782 were differentially methylated (PFDR<0.05) in CLL patients (n=139) compared with healthy individuals (n=14), with enrichment at enhancers (P=0.002). Differential methylation was associated with evolutionary age of LINE-1 (r²=0.31, P=0.003) and Alu (r²=0.74, P=0.002) elements, with greater hypomethylation of older subfamilies (L1M, AluJ). Locus-specific hypomethylation was associated with differential expression of proximal genes, including DCLK2, HK1, ILRUN, TANK, TBCD, TNFRSF1B and TXNRD2, with higher expression of DCLK2 and TNFRSF1B associated with reduced patient survival. Hypomethylation at nine loci was highly frequent in CLL (>90% patients) but not observed in healthy individuals or other leukaemias, and was detectable in blood samples taken prior to CLL diagnosis in 9 of 82 individuals from the Melbourne Collaborative Cohort Study. Our results demonstrate differential methylation of retrotransposons in CLL by their evolutionary heritage that modulates expression of proximal genes.

The effect of hybridization on transposable element accumulation in an undomesticated fungal species

Transposable elements (TEs) are mobile genetic elements that can profoundly impact the evolution of genomes and species. A long-standing hypothesis suggests that hybridization could deregulate TEs and trigger their accumulation, although it received mixed support from studies mostly in plants and animals. Here, we tested this hypothesis in fungi using incipient species of the undomesticated yeast Saccharomyces paradoxus. Population genomic data revealed no signature of higher transposition in natural hybrids. As we could not rule out the elimination of past transposition increase signatures by natural selection, we performed a laboratory evolution experiment on a panel of artificial hybrids to measure TE accumulation in the near absence of selection. Changes in TE copy numbers were not predicted by the level of evolutionary divergence between the parents of a hybrid genotype. Rather, they were highly dependent on the individual hybrid genotypes, showing that strong genotype-specific deterministic factors govern TE accumulation in yeast hybrids.

ERVcaller: identifying polymorphic endogenous retrovirus and other transposable element insertions using whole-genome sequencing data

MOTIVATION

Approximately 8% of the human genome is derived from endogenous retroviruses (ERVs). In recent years, an increasing number of human diseases have been found to be associated with ERVs. However, it remains challenging to accurately detect the full spectrum of polymorphic (unfixed) ERVs using whole-genome sequencing (WGS) data.

RESULTS

We designed a new tool, ERVcaller, to detect and genotype transposable element (TE) insertions, including ERVs, in the human genome. We evaluated ERVcaller using both simulated and real benchmark WGS datasets. Compared to existing tools, ERVcaller consistently obtained both the highest sensitivity and precision for detecting simulated ERV and other TE insertions derived from real polymorphic TE sequences. For the WGS data from the 1000 Genomes Project, ERVcaller detected the largest number of TE insertions per sample based on consensus TE loci. By analyzing the experimentally verified TE insertions, ERVcaller had 94.0% TE detection sensitivity and 96.6% genotyping accuracy. Polymerase chain reaction and Sanger sequencing in a small sample set verified 86.7% of examined insertion statuses and 100% of examined genotypes. In conclusion, ERVcaller is capable of detecting and genotyping TE insertions using WGS data with both high sensitivity and precision. This tool can be applied broadly to other species.

AVAILABILITY AND IMPLEMENTATION

http://www.uvm.edu/genomics/software/ERVcaller.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Estimation of the Genome-Wide Mutation Rate and Spectrum in the Archaeal Species Haloferax volcanii

Organisms adapted to life in extreme habitats (extremophiles) can further our understanding of the mechanisms of genetic stability, particularly replication and repair. Despite the harsh environmental conditions they endure, these extremophiles represent a great deal of the Earth's biodiversity. Here, for the first time in a member of the archaeal domain, we report a genome-wide assay of spontaneous mutations in the halophilic species Haloferax volcanii using a direct and unbiased method: mutation accumulation experiments combined with deep whole-genome sequencing. H. volcanii is a key model organism not only for the study of halophilicity, but also for archaeal biology in general. Our methods measure the genome-wide rate, spectrum, and spatial distribution of spontaneous mutations. The estimated base substitution rate of 3.15 × 10^-10 per site per generation, or 0.0012 per genome per generation, is similar to the value found in mesophilic prokaryotes (optimal growth at ∼20-45°). This study contributes to a comprehensive phylogenetic view of how evolutionary forces and molecular mechanisms shape the rate and molecular spectrum of mutations across the tree of life.

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

Alu retrotransposons account for more than 10% of the human genome, and insertions of these elements create structural variants segregating in human populations. Such polymorphic Alus are powerful markers to understand population structure, and they represent variants that can greatly impact genome function, including gene expression. Accurate genotyping of Alus and other mobile elements has been challenging. Indeed, we found that Alu genotypes previously called for the 1000 Genomes Project are sometimes erroneous, which poses significant problems for phasing these insertions with other variants that comprise the haplotype. To ameliorate this issue, we introduce a new pipeline - TypeTE - which genotypes Alu insertions from whole-genome sequencing data. Starting from a list of polymorphic Alus, TypeTE identifies the hallmarks (poly-A tail and target site duplication) and orientation of Alu insertions using local re-assembly to reconstruct presence and absence alleles. Genotype likelihoods are then computed after re-mapping sequencing reads to the reconstructed alleles. Using a high-quality set of PCR-based genotyping of >200 loci, we show that TypeTE improves genotype accuracy from 83% to 92% in the 1000 Genomes dataset. TypeTE can be readily adapted to other retrotransposon families and brings a valuable toolbox addition for population genomics.

intansv: an R package for integrative analysis of structural variations

Identification of structural variations between individuals is very important for the understanding of phenotype variations and diseases. Despite the existence of dozens of programs for prediction of structural variations, none of them is the golden standard in this field and the results of multiple programs were usually integrated to get more reliable predictions. Annotation and visualization of structural variations are important for the understanding of their functions. However, no program provides these functions currently as far as we are concerned. We report an R package, intansv, which can integrate the predictions of multiple programs as well as annotate and visualize structural variations. The source code and the help manual of intansv is freely available at https://github.com/venyao/intansv and http://www.bioconductor.org/packages/devel/bioc/html/intansv.html.