Host Gene Regulation by Transposable Elements: The New, the Old and the Ugly

Repeat-based phylogenomics shed light on unclear relationships in the monocentric genus Juncus L. (Juncaceae)

The repetitive fraction (repeatome) of eukaryotic genomes is diverse and usually fast evolving, being an important tool for clarify plant systematics. The genus Juncus L. comprises 332 species, karyotypically recognized by having holocentric chromosomes. However, four species were recently described as monocentric, yet our understanding of their genome evolution is largely masked by unclear phylogenetic relationships. Here, we reassess the current Juncus systematics using low-coverage genome skimming data of 33 taxa to construct repeats, nuclear rDNA and plastome-based phylogenetic hypothesis. Furthermore, we characterize the repeatome and chromosomal distribution of Juncus-specific centromeric repeats/CENH3 protein to test the monocentricity reach in the genus. Repeat-base phylogenies revealed topologies congruent with the rDNA tree, but not with the plastome tree. The incongruence between nuclear and plastome chloroplast dataset suggest an ancient hybridization in the divergence of Juncotypus and Tenageia sections 40 Myr ago. The phylogenetic resolution at section level was better fitted with the rDNA/repeat-based approaches, with the recognition of two monophyletic sections (Stygiopsis and Tenageia). We found specific repeatome trends for the main lineages, such as the higher abundances of TEs in the Caespitosi and Iridifolii + Ozophyllum clades. CENH3 immunostaining confirmed the monocentricity of Juncus, which can be a generic synapomorphy for the genus. The heterogeneity of the repeatomes, with high phylogenetic informativeness, identified here may be correlated with their ancient origin (56 Mya) and reveals the potential of comparative genomic analyses for understanding plant systematics and evolution.

Co-option of endogenous retroviruses through genetic escape from TRIM28 repression

Endogenous retroviruses (ERVs) have rewired host gene networks. To explore the origins of co-option, we employed an active murine ERV, IAPEz, and an embryonic stem cell (ESC) to neural progenitor cell (NPC) differentiation model. Transcriptional silencing via TRIM28 maps to a 190 bp sequence encoding the intracisternal A-type particle (IAP) signal peptide, which confers retrotransposition activity. A subset of "escapee" IAPs (∼15%) exhibits significant genetic divergence from this sequence. Canonical repressed IAPs succumb to a previously undocumented demarcation by H3K9me3 and H3K27me3 in NPCs. Escapee IAPs, in contrast, evade repression in both cell types, resulting in their transcriptional derepression, particularly in NPCs. We validate the enhancer function of a 47 bp sequence within the U3 region of the long terminal repeat (LTR) and show that escapee IAPs convey an activating effect on nearby neural genes. In sum, co-opted ERVs stem from genetic escapees that have lost vital sequences required for both TRIM28 restriction and autonomous retrotransposition.

Transposons contribute to the acquisition of cell type-specific cis-elements in the brain

Mammalian brains have evolved in stages over a long history to acquire higher functions. Recently, several transposable element (TE) families have been shown to evolve into cis-regulatory elements of brain-specific genes. However, it is not fully understood how TEs are important for gene regulatory networks. Here, we performed a single-cell level analysis using public data of scATAC-seq to discover TE-derived cis-elements that are important for specific cell types. Our results suggest that DNA elements derived from TEs, MER130 and MamRep434, can function as transcription factor-binding sites based on their internal motifs for Neurod2 and Lhx2, respectively, especially in glutamatergic neuronal progenitors. Furthermore, MER130- and MamRep434-derived cis-elements were amplified in the ancestors of Amniota and Eutheria, respectively. These results suggest that the acquisition of cis-elements with TEs occurred in different stages during evolution and may contribute to the acquisition of different functions or morphologies in the brain.

Confounding factors in profiling of locus-specific human endogenous retrovirus (HERV) transcript signatures in primary T cells using multi-study-derived datasets

BACKGROUND

Human endogenous retroviruses (HERV) are repetitive sequence elements and a substantial part of the human genome. Their role in development has been well documented and there is now mounting evidence that dysregulated HERV expression also contributes to various human diseases. While research on HERV elements has in the past been hampered by their high sequence similarity, advanced sequencing technology and analytical tools have empowered the field. For the first time, we are now able to undertake locus-specific HERV analysis, deciphering expression patterns, regulatory networks and biological functions of these elements. To do so, we inevitable rely on omics datasets available through the public domain. However, technical parameters inevitably differ, making inter-study analysis challenging. We here address the issue of confounding factors for profiling locus-specific HERV transcriptomes using datasets from multiple sources.

METHODS

We collected RNAseq datasets of CD4 and CD8 primary T cells and extracted HERV expression profiles for 3220 elements, resembling most intact, near full-length proviruses. Looking at sequencing parameters and batch effects, we compared HERV signatures across datasets and determined permissive features for HERV expression analysis from multiple-source data.

RESULTS

We could demonstrate that considering sequencing parameters, sequencing-depth is most influential on HERV signature outcome. Sequencing samples deeper broadens the spectrum of expressed HERV elements. Sequencing mode and read length are secondary parameters. Nevertheless, we find that HERV signatures from smaller RNAseq datasets do reliably reveal most abundantly expressed HERV elements. Overall, HERV signatures between samples and studies overlap substantially, indicating a robust HERV transcript signature in CD4 and CD8 T cells. Moreover, we find that measures of batch effect reduction are critical to uncover genic and HERV expression differences between cell types. After doing so, differences in the HERV transcriptome between ontologically closely related CD4 and CD8 T cells became apparent.

CONCLUSION

In our systematic approach to determine sequencing and analysis parameters for detection of locus-specific HERV expression, we provide evidence that analysis of RNAseq datasets from multiple studies can aid confidence of biological findings. When generating de novo HERV expression datasets we recommend increased sequence depth ( > = 100 mio reads) compared to standard genic transcriptome pipelines. Finally, batch effect reduction measures need to be implemented to allow for differential expression analysis.

Systemic Alterations of Cancer Cells and Their Boost by Polyploidization: Unicellular Attractor (UCA) Model

Using meta-analyses, we introduce a unicellular attractor (UCA) model integrating essential features of the ‘atavistic reversal’, ‘cancer attractor’, ‘somatic mutation’, ‘genome chaos’, and ‘tissue organization field’ theories. The ‘atavistic reversal’ theory is taken as a keystone. We propose a possible mechanism of this reversal, its refinement called ‘gradual atavism’, and evidence for the ‘serial atavism’ model. We showed the gradual core-to-periphery evolutionary growth of the human interactome resulting in the higher protein interaction density and global interactome centrality in the UC center. In addition, we revealed that UC genes are more actively expressed even in normal cells. The modeling of random walk along protein interaction trajectories demonstrated that random alterations in cellular networks, caused by genetic and epigenetic changes, can result in a further gradual activation of the UC center. These changes can be induced and accelerated by cellular stress that additionally activates UC genes (especially during cell proliferation), because the genes involved in cellular stress response and cell cycle are mostly of UC origin. The functional enrichment analysis showed that cancer cells demonstrate the hyperactivation of energetics and the suppression of multicellular genes involved in communication with the extracellular environment (especially immune surveillance). Collectively, these events can unleash selfish cell behavior aimed at survival at all means. All these changes are boosted by polyploidization. The UCA model may facilitate an understanding of oncogenesis and promote the development of therapeutic strategies.

Gradistics: An underappreciated dimension in evolutionary space

The growth of complexity is an unsolved and underappreciated problem. We consider possible causes of this growth, hypotheses testing, molecular mechanisms, complexity measures, cases of simplification, and significance for biomedicine. We focus on a general ability of regulation, which is based on the growing information storage and processing capacities, as the main proxy of complexity. Natural selection is indifferent to complexity. However, complexification can be inferred from the same first principle, on which natural selection is founded. Natural selection depends on potentially unlimited reproduction under limited environmental conditions. Because of the demographic pressure, the simple ecological niches become fulfilled and diversified (due to species splitting and divergence). Diversification increases complexity of biocenoses. After the filling and diversification of simple niches, the more complex niches can arise. This is the 'atomic orbitals' (AO) model. Complexity has many shortcomings but it has an advantage. This advantage is ability to regulatory adaptation, including behavioral, formed in the evolution by means of genetic adaptation. Regulatory adaptation is much faster than genetic one because it is based on the information previously accumulated via genetic adaptation and learning. Regulatory adaptation further increases complexity of biocenoses. This is the 'regulatory advantage' (RA) model. The comparison of both models allows testable predictions. We focus on the animal evolution because of the appearance of higher regulatory level (nervous system), which is absent in other lineages, and relevance to humans (including biomedical aspects).

Roles of transposable elements in the regulation of mammalian transcription

Transposable elements (TEs) comprise about half of the mammalian genome. TEs often contain sequences capable of recruiting the host transcription machinery, which they use to express their own products and promote transposition. However, the regulatory sequences carried by TEs may affect host transcription long after the TEs have lost the ability to transpose. Recent advances in genome analysis and engineering have facilitated systematic interrogation of the regulatory activities of TEs. In this Review, we discuss diverse mechanisms by which TEs contribute to transcription regulation. Notably, TEs can donate enhancer and promoter sequences that influence the expression of host genes, modify 3D chromatin architecture and give rise to novel regulatory genes, including non-coding RNAs and transcription factors. We discuss how TEs spur regulatory evolution and facilitate the emergence of genetic novelties in mammalian physiology and development. By virtue of their repetitive and interspersed nature, TEs offer unique opportunities to dissect the effects of mutation and genomic context on the function and evolution of cis-regulatory elements. We argue that TE-centric studies hold the key to unlocking general principles of transcription regulation and evolution.

A retrotransposon storm marks clinical phenoconversion to late-onset Alzheimer's disease

Recent reports have suggested that the reactivation of otherwise transcriptionally silent transposable elements (TEs) might induce brain degeneration, either by dysregulating the expression of genes and pathways implicated in cognitive decline and dementia or through the induction of immune-mediated neuroinflammation resulting in the elimination of neural and glial cells. In the work we present here, we test the hypothesis that differentially expressed TEs in blood could be used as biomarkers of cognitive decline and development of AD. To this aim, we used a sample of aging subjects (age > 70) that developed late-onset Alzheimer’s disease (LOAD) over a relatively short period of time (12–48 months), for which blood was available before and after their phenoconversion, and a group of cognitive stable subjects as controls. We applied our developed and validated customized pipeline that allows the identification, characterization, and quantification of the differentially expressed (DE) TEs before and after the onset of manifest LOAD, through analyses of RNA-Seq data. We compared the level of DE TEs within more than 600,000 TE-mapping RNA transcripts from 25 individuals, whose specimens we obtained before and after their phenotypic conversion (phenoconversion) to LOAD, and discovered that 1790 TE transcripts showed significant expression differences between these two timepoints (logFC ± 1.5, logCMP > 5.3, nominal p value < 0.01). These DE transcripts mapped both over- and under-expressed TE elements. Occurring before the clinical phenoconversion, this TE storm features significant increases in DE transcripts of LINEs, LTRs, and SVAs, while those for SINEs are significantly depleted. These dysregulations end with signs of manifest LOAD. This set of highly DE transcripts generates a TE transcriptional profile that accurately discriminates the before and after phenoconversion states of these subjects. Our findings suggest that a storm of DE TEs occurs before phenoconversion from normal cognition to manifest LOAD in risk individuals compared to controls, and may provide useful blood-based biomarkers for heralding such a clinical transition, also suggesting that TEs can indeed participate in the complex process of neurodegeneration.

Loss of heterochromatin and retrotransposon silencing as determinants in oocyte aging

Mammalian oocyte quality reduces with age. We show that prior to the occurrence of significant aneuploidy (9M in mouse), heterochromatin histone marks are lost, and oocyte maturation is impaired. This loss occurs in both constitutive and facultative heterochromatin marks but not in euchromatic active marks. We show that heterochromatin loss with age also occurs in human prophase I-arrested oocytes. Moreover, heterochromatin loss is accompanied in mouse oocytes by an increase in RNA processing and associated with an elevation in L1 and IAP retrotransposon expression and in DNA damage and DNA repair proteins nuclear localization. Artificial inhibition of the heterochromatin machinery in young oocytes causes an elevation in retrotransposon expression and oocyte maturation defects. Inhibiting retrotransposon reverse-transcriptase through azidothymidine (AZT) treatment in older oocytes partially rescues their maturation defects and activity of the DNA repair machinery. Moreover, activating the heterochromatin machinery via treatment with the SIRT1 activating molecule SRT-1720, or overexpression of Sirt1 or Ezh2 via plasmid electroporation into older oocytes causes an upregulation in constitutive heterochromatin, downregulation of retrotransposon expression, and elevated maturation rates. Collectively, our work demonstrates a significant process in oocyte aging, characterized by the loss of heterochromatin-associated chromatin marks and activation of specific retrotransposons, which cause DNA damage and impair oocyte maturation.

Repeatome-Based Phylogenetics in Pelargonium Section Ciconium (Sweet) Harvey

The repetitive part of the genome (the repeatome) contains a wealth of often overlooked information that can be used to resolve phylogenetic relationships and test evolutionary hypotheses for clades of related plant species such as Pelargonium. We have generated genome skimming data for 18 accessions of Pelargonium section Ciconium and one outgroup. We analyzed repeat abundancy and repeat similarity in order to construct repeat profiles and then used these for phylogenetic analyses. We found that phylogenetic trees based on read similarity were largely congruent with previous work based on morphological and chloroplast sequence data. For example, results agreed in identifying a “Core Ciconium” group which evolved after the split with P. elongatum. We found that this group was characterized by a unique set of repeats, which confirmed currently accepted phylogenetic hypotheses. We also found four species groups within P. sect. Ciconium that reinforce previous plastome-based reconstructions. A second repeat expansion was identified in a subclade which contained species that are considered to have dispersed from Southern Africa into Eastern Africa and the Arabian Peninsula. We speculate that the Core Ciconium repeat set correlates with a possible WGD event leading to this branch.

Growth of Biological Complexity from Prokaryotes to Hominids Reflected in the Human Genome

The growth of complexity in evolution is a most intriguing phenomenon. Using gene phylostratigraphy, we showed this growth (as reflected in regulatory mechanisms) in the human genome, tracing the path from prokaryotes to hominids. Generally, the different regulatory gene families expanded at different times, yet only up to the Euteleostomi (bony vertebrates). The only exception was the expansion of transcription factors (TF) in placentals; however, we argue that this was not related to increase in general complexity. Surprisingly, although TF originated in the Prokaryota while chromatin appeared only in the Eukaryota, the expansion of epigenetic factors predated the expansion of TF. Signaling receptors, tumor suppressors, oncogenes, and aging- and disease-associated genes (indicating vulnerabilities in terms of complex organization and strongly enrichment in regulatory genes) also expanded only up to the Euteleostomi. The complexity-related gene properties (protein size, number of alternative splicing mRNA, length of untranslated mRNA, number of biological processes per gene, number of disordered regions in a protein, and density of TF–TF interactions) rose in multicellular organisms and declined after the Euteleostomi, and possibly earlier. At the same time, the speed of protein sequence evolution sharply increased in the genes that originated after the Euteleostomi. Thus, several lines of evidence indicate that molecular mechanisms of complexity growth were changing with time, and in the phyletic lineage leading to humans, the most salient shift occurred after the basic vertebrate body plan was fixed with bony skeleton. The obtained results can be useful for evolutionary medicine.

Bioinformatics and Machine Learning Approaches to Understand the Regulation of Mobile Genetic Elements

Simple Summary

Transposable elements (TEs) are DNA sequences that are, or were, able to move (transpose) within the genome of a single cell. They were first discovered by Barbara McClintock while working on maize, and they make up a large fraction of the genome. Transpositions can result in mutations and they can alter the genome size. Cells regulate the activity of TEs using a variety of mechanisms, such as chemical modifications of DNA and small RNAs. Machine learning (ML) is an interdisciplinary subject that studies computer algorithms that can improve through experience and by the use of data. ML has been successfully applied to a variety of problems in bioinformatics and has exhibited favorable precision and speed. Here, we provide a systematic and guided review on the ML and bioinformatic methods and tools that are used for the analysis of the regulation of TEs.

Abstract

Transposable elements (TEs, or mobile genetic elements, MGEs) are ubiquitous genetic elements that make up a substantial proportion of the genome of many species. The recent growing interest in understanding the evolution and function of TEs has revealed that TEs play a dual role in genome evolution, development, disease, and drug resistance. Cells regulate TE expression against uncontrolled activity that can lead to developmental defects and disease, using multiple strategies, such as DNA chemical modification, small RNA (sRNA) silencing, chromatin modification, as well as sequence-specific repressors. Advancements in bioinformatics and machine learning approaches are increasingly contributing to the analysis of the regulation mechanisms. A plethora of tools and machine learning approaches have been developed for prediction, annotation, and expression profiling of sRNAs, for methylation analysis of TEs, as well as for genome-wide methylation analysis through bisulfite sequencing data. In this review, we provide a guided overview of the bioinformatic and machine learning state of the art of fields closely associated with TE regulation and function.

Ancient evolution of hepadnaviral paleoviruses and their impact on host genomes

Hepadnaviruses (family Hepadnaviviridae) are reverse-transcribing animal viruses that infect vertebrates. DNA sequences derived from ancient hepadnaviruses have been identified in the germline genome of numerous vertebrate species, and these ‘endogenous hepatitis B viruses’ (eHBVs) reveal aspects of the long-term coevolutionary relationship between hepadnaviruses and their vertebrate hosts. Here, we use a novel, data-oriented approach to recover and analyse the complete repertoire of eHBV elements in published animal genomes. We show that germline incorporation of hepadnaviruses is exclusive to a single vertebrate group (Sauria) and that the eHBVs contained in saurian genomes represent a far greater diversity of hepadnaviruses than previously recognized. Through in-depth characterization of eHBV elements, we establish the existence of four distinct subgroups within the genus Avihepadnavirus and trace their evolution through the Cenozoic Era. Furthermore, we provide a completely new perspective on hepadnavirus evolution by showing that the metahepadnaviruses (genus Metahepadnavirus) originated >300 million years ago in the Paleozoic Era and have historically infected a broad range of vertebrates. We also show that eHBVs have been intra-genomically amplified in some saurian lineages, and that eHBVs located at approximately equivalent genomic loci have been acquired in entirely distinct germline integration events. These findings indicate that selective forces have favoured the accumulation of hepadnaviral sequences at specific loci in the saurian germline. Our investigation provides a range of new insights into the long-term evolutionary history of reverse-transcribing DNA viruses and shows that germline incorporation of hepadnaviruses has played a role in shaping the evolution of saurian genomes.

Chromatin and Epigenetic Rearrangements in Embryonic Stem Cell Fate Transitions

A major event in embryonic development is the rearrangement of epigenetic information as the somatic genome is reprogrammed for a new round of organismal development. Epigenetic data are held in chemical modifications on DNA and histones, and there are dramatic and dynamic changes in these marks during embryogenesis. However, the mechanisms behind this intricate process and how it is regulating and responding to embryonic development remain unclear. As embryos develop from totipotency to pluripotency, they pass through several distinct stages that can be captured permanently or transiently in vitro. Pluripotent naïve cells resemble the early epiblast, primed cells resemble the late epiblast, and blastomere-like cells have been isolated, although fully totipotent cells remain elusive. Experiments using these in vitro model systems have led to insights into chromatin changes in embryonic development, which has informed exploration of pre-implantation embryos. Intriguingly, human and mouse cells rely on different signaling and epigenetic pathways, and it remains a mystery why this variation exists. In this review, we will summarize the chromatin rearrangements in early embryonic development, drawing from genomic data from in vitro cell lines, and human and mouse embryos.

Nsd2 Represses Endogenous Retrovirus MERVL in Embryonic Stem Cells

The facilitates chromatin transcription (FACT) complex is a histone H2A/H2B chaperone, which represses endogenous retroviruses (ERVs) and transcription of ERV-chimeric transcripts. It binds to both transcription start site and gene body region. Here, we investigated the downstream targets of FACT complex to identify the potential regulators of MERVL, which is a key 2-cell marker gene. H3K36me2 profile was positively correlated with that of FACT component Ssrp1. Among H3K36me2 deposition enzymes, Nsd2 was downregulated after the loss of Ssrp1. Furthermore, we demonstrated that Nsd2 repressed the expression of ERVs without affecting the expression of pluripotency genes. The expression of MERVL and 2-cell genes was partially rescued by Nsd2 overexpression. The enrichment of H3K36me2 decreased on MERVL-chimeric gene in ESCs without Ssrp1. Our study discovers that Nsd2 is a repressor of MERVL, and FACT partially represses MERVL expression by regulating the expression of Nsd2 and its downstream H3K36me2.

Recognize Yourself-Innate Sensing of Non-LTR Retrotransposons

Although mobile genetic elements, or transposons, have played an important role in genome evolution, excess activity of mobile elements can have detrimental consequences. Already, the enhanced expression of transposons-derived nucleic acids can trigger autoimmune reactions that may result in severe autoinflammatory disorders. Thus, cells contain several layers of protective measures to restrict transposons and to sense the enhanced activity of these “intragenomic pathogens”. This review focuses on our current understanding of immunogenic patterns derived from the most active elements in humans, the retrotransposons long interspersed element (LINE)-1 and Alu. We describe the role of known pattern recognition receptors in nucleic acid sensing of LINE-1 and Alu and the possible consequences for autoimmune diseases.