TeXP: Deconvolving the effects of pervasive and autonomous transcription of transposable elements

Locus-specific LINE-1 expression in clinical ovarian cancer specimens at the single-cell level

Long interspersed nuclear elements (LINE-1s/L1s) are a group of retrotransposons that can copy themselves within a genome. In humans, it is the most successful transposon in nucleotide content. L1 expression is generally mild in normal human tissues, but the activity has been shown to increase significantly in many cancers. Few studies have examined L1 expression at single-cell resolution, thus it is undetermined whether L1 reactivation occurs solely in malignant cells within tumors. One of the cancer types with frequent L1 activity is high-grade serous ovarian carcinoma (HGSOC). Here, we identified locus-specific L1 expression with 3' single-cell RNA sequencing in pre- and post-chemotherapy HGSOC sample pairs from 11 patients, and in fallopian tube samples from five healthy women. Although L1 expression quantification with the chosen technique was challenging due to the repetitive nature of the element, we found evidence of L1 expression primarily in cancer cells, but also in other cell types, e.g. cancer-associated fibroblasts. The expression levels were similar in samples taken before and after neoadjuvant chemotherapy, indicating that L1 transcriptional activity was unaffected by clinical platinum-taxane treatment. Furthermore, L1 activity was negatively associated with the expression of MYC target genes, a finding that supports earlier literature of MYC being an L1 suppressor.

Vitamin C activates young LINE-1 elements in mouse embryonic stem cells via H3K9me3 demethylation

BACKGROUND

Vitamin C (vitC) enhances the activity of 2-oxoglutarate-dependent dioxygenases, including TET enzymes, which catalyse DNA demethylation, and Jumonji-domain histone demethylases. The epigenetic remodelling promoted by vitC improves the efficiency of induced pluripotent stem cell derivation, and is required to attain a ground-state of pluripotency in embryonic stem cells (ESCs) that closely mimics the inner cell mass of the early blastocyst. However, genome-wide DNA and histone demethylation can lead to upregulation of transposable elements (TEs), and it is not known how vitC addition in culture media affects TE expression in pluripotent stem cells.

RESULTS

Here we show that vitC increases the expression of several TE families, including evolutionarily young LINE-1 (L1) elements, in mouse ESCs. We find that TET activity is dispensable for L1 upregulation, and that instead it occurs largely as a result of H3K9me3 loss mediated by KDM4A/C histone demethylases. Despite increased L1 levels, we did not detect increased somatic insertion rates in vitC-treated cells. Notably, treatment of human ESCs with vitC also increases L1 protein levels, albeit through a distinct, post-transcriptional mechanism.

CONCLUSION

VitC directly modulates the expression of mouse L1s and other TEs through epigenetic mechanisms, with potential for downstream effects related to the multiple emerging roles of L1s in cellular function.

Taming transposable elements in livestock and poultry: a review of their roles and applications

Livestock and poultry play a significant role in human nutrition by converting agricultural by-products into high-quality proteins. To meet the growing demand for safe animal protein, genetic improvement of livestock must be done sustainably while minimizing negative environmental impacts. Transposable elements (TE) are important components of livestock and poultry genomes, contributing to their genetic diversity, chromatin states, gene regulatory networks, and complex traits of economic value. However, compared to other species, research on TE in livestock and poultry is still in its early stages. In this review, we analyze 72 studies published in the past 20 years, summarize the TE composition in livestock and poultry genomes, and focus on their potential roles in functional genomics. We also discuss bioinformatic tools and strategies for integrating multi-omics data with TE, and explore future directions, feasibility, and challenges of TE research in livestock and poultry. In addition, we suggest strategies to apply TE in basic biological research and animal breeding. Our goal is to provide a new perspective on the importance of TE in livestock and poultry genomes.

Low impact of polyploidization on the transcriptome of synthetic allohexaploid wheat

BACKGROUND

Bread wheat is a recent allohexaploid (genomic constitution AABBDD) that emerged through a hybridization between tetraploid Triticum turgidum (AABB) and diploid Aegilops tauschii (DD) less than 10,000 years ago. The hexaploidization can be re-created artificially, producing synthetic wheat that has been used to study immediate genomic responses to polyploidization. The scale of the consequences of polyploidization, and their mechanism of establishment, remain uncertain.

RESULTS

Here we sampled several synthetic wheats from alternative parental genotypes and reciprocal crosses, and examined transcriptomes from two different tissues and successive generations. We did not detect any massive reprogramming in gene expression, with only around 1% of expressed genes showing significant differences compared to their lower-ploidy parents. Most of this differential expression is located on the D subgenome, without consistency in the direction of the expression change. Homoeolog expression bias in synthetic wheat is similar to the pattern observed in the parents. Both differential expression and homoeolog bias are tissue-specific. While up to three families of transposable elements became upregulated in wheat synthetics, their position and distance are not significantly associated with expression changes in proximal genes.

DISCUSSION

While only a few genes change their expression pattern after polyploidization, they can be involved in agronomically important pathways. Alternative parental combinations can lead to opposite changes on the same subset of D-located genes, which is relevant for harnessing new diversity in wheat breeding. Tissue specificity of the polyploidization-triggered expression changes indicates the remodelling of transcriptomes in synthetic wheat is plastic and likely caused by regulome interactions rather than permanent changes. We discuss the pitfalls of transcriptomic comparisons across ploidy levels that can inflate the de-regulation signal.

CONCLUSIONS

Transcriptomic response to polyploidization in synthetic AABBDD wheat is modest and much lower than some previous estimates. Homoeolog expression bias in wheat allohexaploids is mostly attributed to parental legacy, with polyploidy having a mild balancing effect.

LINE-1 retrotransposon expression in cancerous, epithelial and neuronal cells revealed by 5' single-cell RNA-Seq

LINE-1 retrotransposons are sequences capable of copying themselves to new genomic loci via an RNA intermediate. New studies implicate LINE-1 in a range of diseases, especially in the context of aging, but without an accurate understanding of where and when LINE-1 is expressed, a full accounting of its role in health and disease is not possible. We therefore developed a method-5' scL1seq-that makes use of a widely available library preparation method (10x Genomics 5' single cell RNA-seq) to measure LINE-1 expression in tens of thousands of single cells. We recapitulated the known pattern of LINE-1 expression in tumors-present in cancer cells, absent from immune cells-and identified hitherto undescribed LINE-1 expression in human epithelial cells and mouse hippocampal neurons. In both cases, we saw a modest increase with age, supporting recent research connecting LINE-1 to age related diseases.

Quantification of LINE-1 RNA Expression from Bulk RNA-seq Using L1EM

LINE-1 retrotransposons have the potential to cause DNA damage, contribute to genome instability, and induce an interferon response. Thus, accurate measurements of their expression, especially in disease contexts where genome instability and the interferon response are relevant, are of particular importance. Illumina-based bulk RNA sequencing remains the most abundant datatype for measuring gene expression. However, "active" expression from its own internal promoter is only one source of LINE-1 aligning reads in an RNA-seq experiment. With about half a million LINE-1 sequences scattered throughout the genome, many are incorporated into other transcripts that have nothing to do with LINE-1 activity. We call this "passive" co-transcription. Here we will describe how to use L1EM, a computational method that separates active from passive LINE-1 expression at the locus-specific level.

SCIFER: approach for analysis of LINE-1 mRNA expression in single cells at a single locus resolution

BACKGROUND

Endogenous expression of L1 mRNA is the first step in an L1-initiated mutagenesis event. However, the contribution of individual cell types to patterns of organ-specific L1 mRNA expression remains poorly understood, especially at single-locus resolution. We introduce a method to quantify expression of mobile elements at the single-locus resolution in scRNA-Seq datasets called Single Cell Implementation to Find Expressed Retrotransposons (SCIFER). SCIFER aligns scRNA-Seq reads uniquely to the genome and extracts alignments from single cells by cell-specific barcodes. In contrast to the alignment performed using default parameters, this alignment strategy increases accuracy of L1 locus identification by retaining only reads that are uniquely mapped to individual L1 loci. L1 loci expressed in single cells are unambiguously identified using a list of L1 loci manually validated to be expressed in bulk RNA-Seq datasets generated from the same cell line or organ.

RESULTS

Validation of SCIFER using MCF7 cells determined technical parameters needed for optimal detection of L1 expression in single cells. We show that unsupervised analysis of L1 expression in single cells exponentially inflates both the levels of L1 expression and the number of expressed L1 loci. Application of SCIFER to analysis of scRNA-Seq datasets generated from mouse and human testes identified that mouse Round Spermatids and human Spermatogonia, Spermatocytes, and Round Spermatids express the highest levels of L1 mRNA. Our analysis also determined that similar to mice, human testes from unrelated individuals share as much as 80% of expressed L1 loci. Additionally, SCIFER determined that individual mouse cells co-express different L1 sub-families and different families of transposable elements, experimentally validating their co-existence in the same cell.

CONCLUSIONS

SCIFER detects mRNA expression of individual L1 loci in single cells. It is compatible with scRNA-Seq datasets prepared using traditional sequencing methods. Validated using a human cancer cell line, SCIFER analysis of mouse and human testes identified key cell types supporting L1 expression in these species. This will further our understanding of differences and similarities in endogenous L1 mRNA expression patterns in mice and humans.

TEspeX: consensus-specific quantification of transposable element expression preventing biases from exonized fragments

SUMMARY

Transposable elements (TEs) play key roles in crucial biological pathways. Therefore, several tools enabling the quantification of their expression were recently developed. However, many of the existing tools lack the capability to distinguish between the transcription of autonomously expressed TEs and TE fragments embedded in canonical coding/non-coding non-TE transcripts. Consequently, an apparent change in the expression of a given TE may simply reflect the variation in the expression of the transcripts containing TE-derived sequences. To overcome this issue, we have developed TEspeX, a pipeline for the quantification of TE expression at the consensus level. TEspeX uses Illumina RNA-seq short reads to quantify TE expression avoiding counting reads deriving from inactive TE fragments embedded in canonical transcripts.

AVAILABILITY AND IMPLEMENTATION

The tool is implemented in python3, distributed under the GNU General Public License (GPL) and available on Github at https://github.com/fansalon/TEspeX (Zenodo URL: https://doi.org/10.5281/zenodo.6800331).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Meta-Analysis Suggests That Intron Retention Can Affect Quantification of Transposable Elements from RNA-Seq Data

Simple Summary

Transposable elements (TEs) are repetitive sequences comprising more than one third of the human genome with the original ability to change their location within the genome. Owing to their repetitive nature, the quantification of TEs results often challenging. RNA-seq is a useful tool for genome-wide TEs quantification, nevertheless it also presents technical issues, including low reads mappability and erroneous quantification derived from the transcription of TEs fragments embedded in canonical transcripts. Fragments derived from TEs are found within the introns of most genes, which led to the hypothesis that intron retention (IR) can affect the unbiased quantification of TEs expression. Performing meta-analysis of public RNA-seq datasets, here we observe that IR can indeed impact the quantification of TEs by increasing the number of reads mapped on intronic TE copies. Our work highlights a correlation between IR and TEs expression measurement by RNA-seq that should be taken into account to achieve reliable TEs quantification, especially in samples characterized by extensive IR, because differential IR might be confused with differential TEs expression.

Abstract

Transposable elements (TEs), also known as “jumping genes”, are repetitive sequences with the capability of changing their location within the genome. They are key players in many different biological processes in health and disease. Therefore, a reliable quantification of their expression as transcriptional units is crucial to distinguish between their independent expression and the transcription of their sequences as part of canonical transcripts. TEs quantification faces difficulties of different types, the most important one being low reads mappability due to their repetitive nature preventing an unambiguous mapping of reads originating from their sequences. A large fraction of TEs fragments localizes within introns, which led to the hypothesis that intron retention (IR) can be an additional source of bias, potentially affecting accurate TEs quantification. IR occurs when introns, normally removed from the mature transcript by the splicing machinery, are maintained in mature transcripts. IR is a widespread mechanism affecting many different genes with cell type-specific patterns. We hypothesized that, in an RNA-seq experiment, reads derived from retained introns can introduce a bias in the detection of overlapping, independent TEs RNA expression. In this study we performed meta-analysis using public RNA-seq data from lymphoblastoid cell lines and show that IR can impact TEs quantification using established tools with default parameters. Reads mapped on intronic TEs were indeed associated to the expression of TEs and influence their correct quantification as independent transcriptional units. We confirmed these results using additional independent datasets, demonstrating that this bias does not appear in samples where IR is not present and that differential TEs expression does not impact on IR quantification. We concluded that IR causes the over-quantification of intronic TEs and differential IR might be confused with differential TEs expression. Our results should be taken into account for a correct quantification of TEs expression from RNA-seq data, especially in samples in which IR is abundant.

LINE-1 expression in cancer correlates with p53 mutation, copy number alteration, and S phase checkpoint

Retrotransposons are genomic DNA sequences that copy themselves to new genomic locations via RNA intermediates; LINE-1 is the only active and autonomous retrotransposon in the human genome. The mobility of LINE-1 is largely repressed in somatic tissues but is derepressed in many cancers, where LINE-1 retrotransposition is correlated with p53 mutation and copy number alteration (CNA). In cell lines, inducing LINE-1 expression can cause double-strand breaks (DSBs) and replication stress. Reanalyzing multiomic data from breast, ovarian, endometrial, and colon cancers, we confirmed correlations between LINE-1 expression, p53 mutation status, and CNA. We observed a consistent correlation between LINE-1 expression and the abundance of DNA replication complex components, indicating that LINE-1 may also induce replication stress in human tumors. In endometrial cancer, high-quality phosphoproteomic data allowed us to identify the DSB-induced ATM-MRN-SMC S phase checkpoint pathway as the primary DNA damage response (DDR) pathway associated with LINE-1 expression. Induction of LINE-1 expression in an in vitro model led to increased phosphorylation of MRN complex member RAD50, suggesting that LINE-1 directly activates this pathway.

The Dynamism of Transposon Methylation for Plant Development and Stress Adaptation

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

Artificial intelligence to deep learning: machine intelligence approach for drug discovery

Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design and discovery. Further, complex and big data from genomics, proteomics, microarray data, and clinical trials also impose an obstacle in the drug discovery pipeline. Artificial intelligence and machine learning technology play a crucial role in drug discovery and development. In other words, artificial neural networks and deep learning algorithms have modernized the area. Machine learning and deep learning algorithms have been implemented in several drug discovery processes such as peptide synthesis, structure-based virtual screening, ligand-based virtual screening, toxicity prediction, drug monitoring and release, pharmacophore modeling, quantitative structure-activity relationship, drug repositioning, polypharmacology, and physiochemical activity. Evidence from the past strengthens the implementation of artificial intelligence and deep learning in this field. Moreover, novel data mining, curation, and management techniques provided critical support to recently developed modeling algorithms. In summary, artificial intelligence and deep learning advancements provide an excellent opportunity for rational drug design and discovery process, which will eventually impact mankind. The primary concern associated with drug design and development is time consumption and production cost. Further, inefficiency, inaccurate target delivery, and inappropriate dosage are other hurdles that inhibit the process of drug delivery and development. With advancements in technology, computer-aided drug design integrating artificial intelligence algorithms can eliminate the challenges and hurdles of traditional drug design and development. Artificial intelligence is referred to as superset comprising machine learning, whereas machine learning comprises supervised learning, unsupervised learning, and reinforcement learning. Further, deep learning, a subset of machine learning, has been extensively implemented in drug design and development. The artificial neural network, deep neural network, support vector machines, classification and regression, generative adversarial networks, symbolic learning, and meta-learning are examples of the algorithms applied to the drug design and discovery process. Artificial intelligence has been applied to different areas of drug design and development process, such as from peptide synthesis to molecule design, virtual screening to molecular docking, quantitative structure-activity relationship to drug repositioning, protein misfolding to protein-protein interactions, and molecular pathway identification to polypharmacology. Artificial intelligence principles have been applied to the classification of active and inactive, monitoring drug release, pre-clinical and clinical development, primary and secondary drug screening, biomarker development, pharmaceutical manufacturing, bioactivity identification and physiochemical properties, prediction of toxicity, and identification of mode of action.

Vertebrate Lineages Exhibit Diverse Patterns of Transposable Element Regulation and Expression across Tissues

Transposable elements (TEs) comprise a major fraction of vertebrate genomes, yet little is known about their expression and regulation across tissues, and how this varies across major vertebrate lineages. We present the first comparative analysis integrating TE expression and TE regulatory pathway activity in somatic and gametic tissues for a diverse set of 12 vertebrates. We conduct simultaneous gene and TE expression analyses to characterize patterns of TE expression and TE regulation across vertebrates and examine relationships between these features. We find remarkable variation in the expression of genes involved in TE negative regulation across tissues and species, yet consistently high expression in germline tissues, particularly in testes. Most vertebrates show comparably high levels of TE regulatory pathway activity across gonadal tissues except for mammals, where reduced activity of TE regulatory pathways in ovarian tissues may be the result of lower relative germ cell densities. We also find that all vertebrate lineages examined exhibit remarkably high levels of TE-derived transcripts in somatic and gametic tissues, with recently active TE families showing higher expression in gametic tissues. Although most TE-derived transcripts originate from inactive ancient TE families (and are likely incapable of transposition), such high levels of TE-derived RNA in the cytoplasm may have secondary, unappreciated biological relevance.

STK11/LKB1 Loss of Function Is Associated with Global DNA Hypomethylation and S-Adenosyl-Methionine Depletion in Human Lung Adenocarcinoma

STK11 (liver kinase B1, LKB1) is the fourth most frequently mutated gene in lung adenocarcinoma, with loss of function observed in up to 30% of all cases. Our previous work identified a 16-gene signature for LKB1 loss of function through mutational and nonmutational mechanisms. In this study, we applied this genetic signature to The Cancer Genome Atlas (TCGA) lung adenocarcinoma samples and discovered a novel association between LKB1 loss and widespread DNA demethylation. LKB1-deficient tumors showed depletion of S-adenosyl-methionine (SAM-e), which is the primary substrate for DNMT1 activity. Lower methylation following LKB1 loss involved repetitive elements (RE) and altered RE transcription, as well as decreased sensitivity to azacytidine. Demethylated CpGs were enriched for FOXA family consensus binding sites, and nuclear expression, localization, and turnover of FOXA was dependent upon LKB1. Overall, these findings demonstrate that a large number of lung adenocarcinomas exhibit global hypomethylation driven by LKB1 loss, which has implications for both epigenetic therapy and immunotherapy in these cancers. SIGNIFICANCE: Lung adenocarcinomas with LKB1 loss demonstrate global genomic hypomethylation associated with depletion of SAM-e, reduced expression of DNMT1, and increased transcription of repetitive elements.

Transcript assembly improves expression quantification of transposable elements in single-cell RNA-seq data

Transposable elements (TEs) are an integral part of the host transcriptome. TE-containing noncoding RNAs (ncRNAs) show considerable tissue specificity and play important roles during development, including stem cell maintenance and cell differentiation. Recent advances in single-cell RNA-seq (scRNA-seq) revolutionized cell type-specific gene expression analysis. However, effective scRNA-seq quantification tools tailored for TEs are lacking, limiting our ability to dissect TE expression dynamics at single-cell resolution. To address this issue, we established a TE expression quantification pipeline that is compatible with scRNA-seq data generated across multiple technology platforms. We constructed TE-containing ncRNA references using bulk RNA-seq data and showed that quantifying TE expression at the transcript level effectively reduces noise. As proof of principle, we applied this strategy to mouse embryonic stem cells and successfully captured the expression profile of endogenous retroviruses in single cells. We further expanded our analysis to scRNA-seq data from early stages of mouse embryogenesis. Our results illustrated the dynamic TE expression at preimplantation stages and revealed 146 TE-containing ncRNA transcripts with substantial tissue specificity during gastrulation and early organogenesis.

Comparative analysis of morabine grasshopper genomes reveals highly abundant transposable elements and rapidly proliferating satellite DNA repeats

BACKGROUND

Repetitive DNA sequences, including transposable elements (TEs) and tandemly repeated satellite DNA (satDNAs), collectively called the "repeatome", are found in high proportion in organisms across the Tree of Life. Grasshoppers have large genomes, averaging 9 Gb, that contain a high proportion of repetitive DNA, which has hampered progress in assembling reference genomes. Here we combined linked-read genomics with transcriptomics to assemble, characterize, and compare the structure of repetitive DNA sequences in four chromosomal races of the morabine grasshopper Vandiemenella viatica species complex and determine their contribution to genome evolution.

RESULTS

We obtained linked-read genome assemblies of 2.73-3.27 Gb from estimated genome sizes of 4.26-5.07 Gb DNA per haploid genome of the four chromosomal races of V. viatica. These constitute the third largest insect genomes assembled so far. Combining complementary annotation tools and manual curation, we found a large diversity of TEs and satDNAs, constituting 66 to 75% per genome assembly. A comparison of sequence divergence within the TE classes revealed massive accumulation of recent TEs in all four races (314-463 Mb per assembly), indicating that their large genome sizes are likely due to similar rates of TE accumulation. Transcriptome sequencing showed more biased TE expression in reproductive tissues than somatic tissues, implying permissive transcription in gametogenesis. Out of 129 satDNA families, 102 satDNA families were shared among the four chromosomal races, which likely represent a diversity of satDNA families in the ancestor of the V. viatica chromosomal races. Notably, 50 of these shared satDNA families underwent differential proliferation since the recent diversification of the V. viatica species complex.

CONCLUSION

This in-depth annotation of the repeatome in morabine grasshoppers provided new insights into the genome evolution of Orthoptera. Our TEs analysis revealed a massive recent accumulation of TEs equivalent to the size of entire Drosophila genomes, which likely explains the large genome sizes in grasshoppers. Despite an overall high similarity of the TE and satDNA diversity between races, the patterns of TE expression and satDNA proliferation suggest rapid evolution of grasshopper genomes on recent timescales.

Measuring and interpreting transposable element expression

Transposable elements (TEs) are insertional mutagens that contribute greatly to the plasticity of eukaryotic genomes, influencing the evolution and adaptation of species as well as physiology or disease in individuals. Measuring TE expression helps to understand not only when and where TE mobilization can occur but also how this process alters gene expression, chromatin accessibility or cellular signalling pathways. Although genome-wide gene expression assays such as RNA sequencing include transposon-derived transcripts, most computational analytical tools discard or misinterpret TE-derived reads. Emerging approaches are improving the identification of expressed TE loci and helping to discriminate TE transcripts that permit TE mobilization from chimeric gene-TE transcripts or pervasive transcription. Here we review the main challenges associated with the detection of TE expression, including mappability, insertional and internal sequence polymorphisms, and the diversity of the TE transcriptional landscape, as well as the different experimental and computational strategies to solve them.

Transposable elements, circular RNAs and mitochondrial transcription in age-related genomic regulation

Our understanding of the molecular regulation of aging and age-related diseases is still in its infancy, requiring in-depth characterization of the molecular landscape shaping these complex phenotypes. Emerging classes of molecules with promise as aging modulators include transposable elements, circRNAs and the mitochondrial transcriptome. Analytical complexity means that these molecules are often overlooked, even though they exhibit strong associations with aging and, in some cases, may directly contribute to its progress. Here, we review the links between these novel factors and age-related phenotypes, and we suggest tools that can be easily incorporated into existing pipelines to better understand the aging process.

The Sophisticated Transcriptional Response Governed by Transposable Elements in Human Health and Disease

Transposable elements (TEs), which cover ~45% of the human genome, although firstly considered as “selfish” DNA, are nowadays recognized as driving forces in eukaryotic genome evolution. This capability resides in generating a plethora of sophisticated RNA regulatory networks that influence the cell type specific transcriptome in health and disease. Indeed, TEs are transcribed and their RNAs mediate multi-layered transcriptional regulatory functions in cellular identity establishment, but also in the regulation of cellular plasticity and adaptability to environmental cues, as occurs in the immune response. Moreover, TEs transcriptional deregulation also evolved to promote pathogenesis, as in autoimmune and inflammatory diseases and cancers. Importantly, many of these findings have been achieved through the employment of Next Generation Sequencing (NGS) technologies and bioinformatic tools that are in continuous improvement to overcome the limitations of analyzing TEs sequences. However, they are highly homologous, and their annotation is still ambiguous. Here, we will review some of the most recent findings, questions and improvements to study at high resolution this intriguing portion of the human genome in health and diseases, opening the scenario to novel therapeutic opportunities.

Mobile genomics: tools and techniques for tackling transposons

Next-generation sequencing approaches have fundamentally changed the types of questions that can be asked about gene function and regulation. With the goal of approaching truly genome-wide quantifications of all the interaction partners and downstream effects of particular genes, these quantitative assays have allowed for an unprecedented level of detail in exploring biological interactions. However, many challenges remain in our ability to accurately describe and quantify the interactions that take place in those hard to reach and extremely repetitive regions of our genome comprised mostly of transposable elements (TEs). Tools dedicated to TE-derived sequences have lagged behind, making the inclusion of these sequences in genome-wide analyses difficult. Recent improvements, both computational and experimental, allow for the better inclusion of TE sequences in genomic assays and a renewed appreciation for the importance of TE biology. This review will discuss the recent improvements that have been made in the computational analysis of TE-derived sequences as well as the areas where such analysis still proves difficult. This article is part of a discussion meeting issue 'Crossroads between transposons and gene regulation'.

A potential new mechanism for pregnancy loss: considering the role of LINE-1 retrotransposons in early spontaneous miscarriage

LINE1 retrotransposons are mobile DNA elements that copy and paste themselves into new sites in the genome. To ensure their evolutionary success, heritable new LINE-1 insertions accumulate in cells that can transmit genetic information to the next generation (i.e., germ cells and embryonic stem cells). It is our hypothesis that LINE1 retrotransposons, insertional mutagens that affect expression of genes, may be causal agents of early miscarriage in humans. The cell has evolved various defenses restricting retrotransposition-caused mutation, but these are occasionally relaxed in certain somatic cell types, including those of the early embryo. We predict that reduced suppression of L1s in germ cells or early-stage embryos may lead to excessive genome mutation by retrotransposon insertion, or to the induction of an inflammatory response or apoptosis due to increased expression of L1-derived nucleic acids and proteins, and so disrupt gene function important for embryogenesis. If correct, a novel threat to normal human development is revealed, and reverse transcriptase therapy could be one future strategy for controlling this cause of embryonic damage in patients with recurrent miscarriages.