© 2020. Published by The Company of Biologists Ltd | Development (2020) 147, dev175786. doi:10.1242/dev.175786 REVIEW Transposable elements, circular RNAs and mitochondrial transcription in age-related genomic regulation Juan I. Bravo1,2,Séverine Nozownik1,3, Prakroothi S. Danthi1 and Bérénice A. Benayoun1,4,5,6,* ABSTRACT the birth of an organism, which is the most intuitive definition of Our understanding of the molecular regulation of aging and age- aging); (2) replicative aging [the number of times a cell can divide related diseases is still in its infancy, requiring in-depth (Mortimer and Johnston, 1959)]; (3) cellular senescence [the characterization of the molecular landscape shaping these complex endpoint of replicative aging, corresponding to irreversible cell ‘ ’ phenotypes. Emerging classes of molecules with promise as aging cycle arrest once a cell population reaches its Hayflick limit modulators include transposable elements, circRNAs and the (Hayflick and Moorhead, 1961)], the burden of which on multi- mitochondrial transcriptome. Analytical complexity means that cellular animals increases with age (Dimri et al., 1995) and which these molecules are often overlooked, even though they exhibit may underlie aspects of organismal aging and age-related diseases strong associations with aging and, in some cases, may directly (Baker et al., 2016; Bussian et al., 2018); and (4) premature aging contribute to its progress. Here, we review the links between these syndromes [e.g. Hutchinson-Gilford progeria syndrome (Burtner novel factors and age-related phenotypes, and we suggest tools that and Kennedy, 2010)]. Moreover, aging is characterized by several ‘ ’ can be easily incorporated into existing pipelines to better understand hallmarks , including genomic instability, cellular senescence, the aging process. altered intercellular communication/pervasive inflammation, loss of protein homeostasis, mitochondrial dysfunction, deregulated KEY WORDS: Aging, CircRNAs, Mitochondria, Transposable nutrient sensing, stem cell exhaustion, telomere attrition and elements epigenetic alterations (Kennedy et al., 2014; López-Otín et al., 2013). Importantly, a central hypothesis in the geroscience field is Introduction that aging itself is a major risk factor for a number of chronic ‘age- The field of geroscience seeks to understand and characterize the related’ diseases, such as Alzheimer’s disease (AD) and other mechanisms that contribute to aging and that may directly or dementias, cancer, etc. (Franceschi et al., 2018a). Finally, many indirectly drive aging-associated pathologies (Kennedy et al., features of the aging process can be fine-tuned, even within a 2014). Over the past few decades, a number of evolutionarily species, based on environmental cues, inter-individual genetic conserved pathways that modulate lifespan in yeast, nematodes, variations and even sex (Fischer et al., 2016). flies and mammals have been identified, such as the insulin Accumulating evidence across experimental models of aging signaling, mTOR and sirtuin pathways (Bareja et al., 2019; Bishop suggests that complex underlying molecular factors are important et al., 2010; Pan and Finkel, 2017). during aging, many of which are still poorly understood. Changes in One of the major limitations the field has encountered is that the traditional gene expression features such as general transcription relative magnitudes of lifespan changes that genetic and levels (Lai et al., 2019), epigenetic regulation (Booth and Brunet, pharmaceutical interventions exhibit do not linearly translate 2016; Pal and Tyler, 2016; Sen et al., 2016) and alternative splicing between organisms. For example, dietary restriction can increase (Bhadra et al., 2020) are reviewed elsewhere. In this Review, we lifespan in worms two- to threefold, but this intervention may only focus on three emerging factors of interest: transposable elements, increase mouse lifespan between 30 and 50%, and its long-term circular RNAs (circRNAs) and the mitochondrial transcriptome. effects on humans are not well characterized (Fontana et al., 2010). The analysis of the first two factors can be readily incorporated into Thus far, there is no known intervention that can bridge the gap existing data analysis pipelines and may provide important insights between the average human lifespan (∼79 years in the USA) and the into the aging process. We provide an introduction to these maximal, recorded human lifespan (∼122 years). This suggests that emerging factors, highlight known relationships and current gaps in there may be complex underlying molecular factors important knowledge with respect to aging and, when available, indicate during the aging process that are still poorly understood. tools that are available for their analysis. In the future, a more Experimental studies of the aging process can be carried out at systematic incorporation of these factors into aging studies will help several levels in the laboratory: (1) chronological aging (time since provide a more comprehensive view of the changes that occur, suggest novel molecular mechanisms underlying aspects of aging, and provide new therapeutic targets for pro-longevity 1Leonard Davis School of Gerontology, University of Southern California, Los interventions. Angeles, CA 90089, USA. 2Graduate Program in the Biology of Aging, University of Southern California, Los Angeles, CA 90089, USA. 3Magisterè européen de Génétique, UniversitéParis Diderot-Paris 7, Paris 75014, France. 4Neuroscience Transposable elements as drivers of aging and aging-related Graduate Program, University of Southern California, Los Angeles, CA 90089, USA. pathologies 5USC Norris Comprehensive Cancer Center, Epigenetics and Gene Regulation, ‘ Los Angeles, CA 90089, USA. 6USC Stem Cell Initiative, Los Angeles, CA 90089, Transposable elements (TEs; informally referred to as jumping USA. genes’) are mobile genetic elements within host genomes that may impact several aspects of the aging process. Transposons constitute *Author for correspondence ([email protected]) a significant fraction of eukaryotic genomes, ranging anywhere J.I.B., 0000-0002-9429-0488; B.A.B., 0000-0002-7401-4777 from ∼3% in yeast (Saccharomyces cerevisiae)to∼80% in the frog DEVELOPMENT 1 REVIEW Development (2020) 147, dev175786. doi:10.1242/dev.175786 cancer (Di Ruocco et al., 2018; Iskow et al., 2010; De Luca et al., Box 1. Emerging tools to quantify genomic regulation 2015; Rodićet al., 2014), AD (Guo et al., 2018; Sun et al., 2018) of TEs and TDP-43-mediated ailments (e.g. amyotrophic lateral sclerosis, From a data analysis perspective, the inherent repetitive nature of TEs frontotemporal lobar degeneration, etc.) (Krug et al., 2017; Li makes many analyses complicated and computationally intensive, et al., 2012; Prudencio et al., 2017). Broadly, this re-activation notably because short-read NGS technologies are limited in their has a number of implications for gene expression. Transposition- ability to distinguish different instances of the same element (Treangen competent TEs may drive mutation and, if inserted into genes, and Salzberg, 2012). Thus, sequencing reads from TEs are most frequently ignored and discarded in genomic analyses (e.g. RNA-seq, drive production of non-functional gene products (Kidwell and ChIP-seq and ATAC-seq), and only the expression profiles of annotated Lisch, 1997). TEs may also alter expression of nearby genes. genes are considered (Slotkin, 2018). This analytical pragmatism means Indeed, TEs harbor regulatory elements that can alter gene that researchers often have an incomplete representation of genome expression in cis, although an additional possibility is that they regulation associated with their manipulation or intervention of interest. may sequester transcriptional machinery away from nearby To attempt to address this deficit, a growing number of pipelines are genes (Elbarbary et al., 2016; Jordan et al., 2003). Ultimately, being developed to discover, classify and quantify TEs from high- throughput sequencing experiments (Table 1; reviewed by Goerner- whether altered TE activity is a mere by-product or an actual Potvin and Bourque, 2018; O’Neill et al., 2020). As these tools are still driver of aging and age-related diseases remains mostly unclear. relatively young and are based on different algorithmic assumptions, it To fully understand the contributions of TE mis-regulation to will be important to benchmark them in order to understand which ones the aging process, the field will need to determine which are most useful in the study of aging genomic-regulation networks. hallmarks are modulated by TE deregulation and characterize Ultimately, systematically incorporating TE analyses in bioinformatic any underlying mechanisms (Box 1; discussed below). We pipelines, especially in the contexts of aging research, will help us gain a more comprehensive view of transcriptional landscapes, which may indicate a selection of bioinformatic tools that can easily be implicate TEs in previously unconnected phenotypes or disease states. integrated in existing analytical pipelines to interrogate TE regulation (Table 1). In the human genome, the two most abundant families of TEs are RNA mediated: the long interspersed element 1 (LINE-1 or L1) and Rana esculenta (Biémont and Vieira, 2006). Of greater relevance, Alu elements, which account for ∼16-17% and ∼9-11% of the the proportion of TEs has been reported to be ∼38% in the mouse genome, respectively (Lander et al., 2001; Venter et al.,