Retro-miRs: Novel and functional miRNAs originating from mRNA retrotransposition

doi:10.21203/rs.3.rs-2679750/v1

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Retro-miRs: Novel and functional miRNAs originating from mRNA retrotransposition

https://doi.org/10.21203/rs.3.rs-2679750/v1

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published 08 Sep, 2023

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Background. Reverse-transcribed gene copies (retrocopies) have emerged as major sources of evolutionary novelty. MicroRNAs (miRNAs) are small and highly conserved RNA molecules that serve as key post-transcriptional regulators of gene expression. The origin and subsequent evolution of miRNAs have been addressed but not fully elucidated.

Results.In this study, we performed a comprehensive investigation of miRNA origination through retroduplicated mRNA sequences (retro-miRs). We identified 17 retro-miRs that emerged from the mRNA retrocopies. Four of these retro-miRs had de novo origins within retrocopied sequences, while 13 retro-miRNAs were located within exon regions and duplicated along with their host mRNAs. We found that retro-miRs were primate-specific, including five retro-miRs conserved among all primates and two human-specific retro-miRs. All retro-miRs were expressed, with predicted and experimentally validated target genes except miR-10527. Notably, the target genes of retro-miRs are involved in key biological processes such as metabolic processes, cell signaling, and regulation of neurotransmitters in the central nervous system. Additionally, we found that these retro-miRs play a potential oncogenic role in cancer by targeting key cancer genes and are overexpressed in several cancer types, including liver hepatocellular carcinoma and stomach adenocarcinoma.

Conclusions. Our findings demonstrated that mRNA retrotransposition is a key mechanism for the generation of novel miRNAs (retro-miRs) in primates. These retro-miRs are expressed, conserved, have target genes with important cellular functions, and play important roles in cancer.

miRNAs

retrocopies

gene origination

gene expression

cancer

MicroRNAs (miRNAs) are small non-protein-coding RNAs (approximately 22 bp) with a key function of regulating gene expression at the post-transcriptional level [1]. Advances in our understanding of miRNA biology have revealed hundreds of miRNA genes that are widespread throughout the animal kingdom [2]. The biogenesis of miRNAs involves several coordinated processing steps resulting in the incorporation of mature miRNAs into the RNA-induced silencing complex (RISC) [3]. miRNAs act in gene regulation mechanisms by targeting the 3’ untranslated region (UTR) of protein-coding genes leading to translational repression or mRNA degradation [4]. Additionally, miRNAs have been shown to act as gene regulators very early on in the evolution of animals and have complex evolutionary patterns that differ from those of other genetic sequences [5].

Remarkably, it has been shown that the genome incorporation of novel miRNAs is a pivotal and instrumental step in the evolution of organismal complexity [5]. It is clear that the expression of miRNAs modulates the transcript variability of their target coding genes, fine-tuning the protein molecules produced by the coding gene, and therefore, conferring robustness to cellular pathways and gene networks. Consequently, the robustness of gene expression may have contributed to a decrease in phenotypic variation, maintaining an invariant phenotype despite endogenous and exogenous perturbations. This increased the heritability of species-specific traits [6].

For the emergence of new miRNA sequences, it is a fundamental prerequisite that the novel miRNA gene is transcribed from a genomic locus prone to produce an RNA fold recognizable by the miRNA processing machinery [7]. Essentially, there are two distinct molecular mechanisms capable of generating a novel miRNA: i) duplication of a pre-existing miRNA, followed by sub-or neofunctionalization [8], and ii) de novo origination of miRNAs [9]. While the former is majorly mediated by a local or full genome duplication [10], the latter (de novo) miRNA origination has a bias to occur in transcribed regions, frequently from introns [11, 12]) or is mediated by transposable elements [13] in the duplication of non-coding RNAs [14–16].

One overlooked source of novel miRNAs is the copies of processed mRNA, which are also known as retrocopies. Retrocopies are mRNA copies (of protein-coding genes) that have been reverse-transcribed to cDNA sequences and re-inserted into the genome in a process known as retrotransposition [17]. Until recently, retrocopies have been referred to as processed pseudogenes, but an increasing body of evidence suggests that a large fraction of retrocopies is functional [18–20]. Retrocopies are a major source of genetic novelty because they create novel genes [21], regulatory regions [22] and other noncoding genes, including miRNAs [15]. Specifically, this previous work [15] showed that two miRNAs (hsa-miR-220 and hsa-miR-492) lie within retrocopies of protein-coding genes and suggest that these retroduplicates are good "miRNA incubators''. Surprisingly, almost two decades later, no further investigations have been conducted on this issue.

In this study, we comprehensively investigated the contribution of retrocopies as a source of novel miRNAs (retrocopy-derived miRNAs (retro-miRs)) in the human genome. To accomplish this, we used an extensive range of databases concerning genomic annotations, sequence conservation, expression in healthy and cancerous tissues, information about miRNA target genes, and a complete set of bioinformatics tools. In summary, we identified 17 primate-specific retro-miRNAs and investigated their conservation, expression, gene targets, and putative functions in cancer.

Finding miRNAs originated by mRNA retrotransposition events

To identify miRNAs originating from mRNA retrocopies (retro-miRs), we developed a set of local pipelines and surveyed several databases (Fig. 1A). Briefly, we constructed and used a set of computational algorithms to assess and integrate information from three databases: miRBase, the reference database for information on several miRNAs [23]; miRIAD, a database containing annotation and further data on intragenic miRNAs and their host genes [24, 25]; and RCPedia, a database of retrocopies present in humans and other species [26]). Further information about the investigated genes (retrocopies and miRNAs), such as their conservation, expression, miRNA targets, and functional information, was retrieved from other databases (e.g., TargetScan [27], miRTarBase [28], FANTOM phase 5, and The Cancer Genome Atlas (TCGA) and locally processed (Fig. 1A). Further details are available in the Methodology section.

Using this strategy, we identified 17 retro-miRs in retrocopied sequences. These miRNAs were grouped into three distinct classes: retroposed (R-retro-miRs), exon junction (EJ)-retro-miRs, and novel retro-miRs (N-retro-miRs) (Fig. 1B). Six R-retro-miRs (35.3%; miR-4444-2, miR-1244-2, miR-1244-3, miR-1244-4, miR-1244-5, and miR-1244-6) are retroduplications of exonic miRNAs already present in their parental gene sequences (Fig. 1B, Supplementary Figure S1). These include four R-retro-miRs that are fully identical to their parental miRNAs and two others that have variations in their precursor stem, including one retro-miR with variations in the mature region (outer seed region). We found seven EJ-retro-miRs (41.2%; miR-492, miR-622, miR-4426, miR-4426-1, miR-3654, miR-3654-1, and miR-10527), which were also in the exonic region of their parental genes but spanned two exons (Fig. 1B, Supplementary Figure S2). Interestingly, none of these miRNAs have been annotated in the parental gene region, likely because they are split by an intronic sequence. The last retro-miR class, N-retro-miR, comprised four miRNAs (23.5%; miR-4788, miR-7161, miR-4468, and miR-572) that had a de novo origin in the retrocopied sequences because of the occurrence of mutations during evolution (Fig. 1B, Supplementary Figure S3). Upon checking the equivalent region in the parental gene, no evidence of a stem loop, that is, a putative miRNA, was found (Supplementary Figure S4).

Next, we investigated the characteristics of retrocopies containing retro-miRs. First, we found that the six R-retro-miRs present in both retrocopy and parental genes originated from six distinct retroduplication events but only from two parental genes: PTMA (five retrocopies with retro-miRs) and HNRNPA3 (one retrocopy) (Supplementary Table S1). Interestingly, these genes were highly retroduplicated in the human genome. PTMA presented 13 retrocopies and HNRNPA3 presented 17 retrocopies (Supplementary Table S2). In contrast, five distinct parental genes originated from the seven retrocopies with seven EJ-retro-miRs, and four distinct parental genes originated from four retrocopies, each with an N-retro-miR (Supplementary Table S1 and S2).

These results led us to investigate the events of chromosomal duplication of genes containing exonic miRNAs, in addition to the retro-miRs we identified. Briefly, we found that among the 19,768 protein-coding genes, 144 contained exonic miRNAs, of which 17 were duplicated by retrotransposition and 24 by DNA-mediated duplication. Interestingly, only two DNA-based duplications contained miRNAs in their duplicates (Supplementary Table S3). Taken together, these results suggest that retroduplication is a common pathway for the origin of novel miRNAs.

Characteristics and conservation of retro-miR events

To trace the evolutionary origin of each retrocopy and its retro-miRs, we used a homology-based approach (see Methods) to determine their conservation (Fig. 2A). First, this analysis revealed that all these retrocopies and their miRNAs originated in the primate lineage (Supplementary Table S4) and, in agreement with the literature on retrocopies, are primate-specific [19]. By correlating the ages of retro-miRs with their classes, we observed that the oldest events (conserved in all primates) were enriched in de novo N-retro-miRs. EJ-retro-miRs were spread across all ages, and R-retro-miRs were only present in great apes and up (Fig. 2A).

These results prompted us to investigate whether retrocopies containing retro-miRs evolved under functional constraints (purifying or positive selection) or under neutral conditions. To assess this, we used retrocopy-predicted coding regions to quantify the ratio of the number of nonsynonymous substitutions per nonsynonymous site to the number of synonymous substitutions per synonymous site (dN/dS). We found three retrocopies under neutral selection (dN/dS ~ 1, retrocopies containing retro-miR-4444-2, retro-miR-1244-2, and retro-miR-3654-1) and 12 retrocopies with a dN/dS ratio different from 1 (potentially under functional constraints) (Fig. 2D). However, only for three of these retrocopies, we confirmed a dN/dS value significantly different than 1 (p-value < = 0.05, likelihood ratio test), with two retrocopies under purifying selection (retrocopies containing retro-miR-1244-6 and retro-miR-7161) and one retrocopy (containing retro-mir-1244-5) under positive selection (Fig. 2D, Supplementary Table S5).

Taken together, these results indicate that retro-miRs originated during primate evolution in distinct waves. Additionally, considering the recent insertion of these retrocopies and retro-miRs into the evolutionary history of humans, we observed a tendency to purify evolutionary pressure on them.

Expression of retro-miRs in normal tissues.

After dissecting the genomic features of retro-miRs, we attempted to identify their transcription and target genes, which are fundamental features of functional miRNAs. We examined evidence of retro-miR transcription using short RNA sequencing (RNA-seq) [29] and CAGE data [30]. All retro-miRNAs (except retro-miR-10527) were expressed in normal samples (404 individuals, 32 tissues) and/or cell lines (48 cell lines) (Fig. 3A). Notably, we observed distinct expression patterns of retro-miRs in different tissues and cell lines. Interestingly, a novel retro-miR (mir-4788) was highly expressed (the highest median expression among all retro-miRs) in normal samples. Conversely, in stem cells, miR-4788 showed the lowest (median) expression.

Next, to further support the true expression of these loci containing retro-miRs, we evaluated the presence of a transcription start site (TSS) (up to 4 Kbp) upstream of their 5' end using CAGE sequencing. The results confirmed TSSs for 82% (14/17) of the retro-miRs (Fig. 3B). In agreement with the RNA-seq data, retro-miRs with a defined TSS had, in general, higher expression and were more broadly expressed in different tissues than retro-miRs without a TSS (Fig. 3B).

Next, we compared the expression of retro-miRs with that of all the other annotated miRNAs (Supplementary Table S6). Figure 3C shows that retro-miRs were in the middle of the first quartile in terms of expression levels and number of tissues expressed. Together, we observed that all retro-miRs had similar expression levels, which is expected for genes (miRNAs) that have recently evolved. Additionally, N-retro-miRs were among the miRNAs expressed in fewer tissues, a pattern that is expected for novel genes (miRNAs).

In a further investigation, we sought to identify the set of genes targeted by retro-miRs, a sine qua non feature of functional miRNAs [27]. Notably, we identified target genes for all retro-miRs using TargetScan (7mer-m8 and 8mer) and TargetScan (8mer), and experimentally validated the targets (Fig. 4A; Supplementary Table S7). Only one retro-miR (miR-10527) had no experimentally validated targets, which is in accordance with our previous results (Fig. 3), where we reported no expression of miR-10527. Next, to evaluate the global functions of these retro-miR targets, we performed a Gene Ontology investigation of their biological processes. We found that these target genes function in key cellular processes, including the regulation of transcription, DNA replication, cell proliferation and differentiation, and DNA binding (Fig. 4B; p-value < 0.05; fold enrichment > 1.5). Next, we separately examined each set of targets for all retro-miRs (Supplementary Figure S5) and identified two sets of target genes. The two novel retro-miRs (miR-4788 and miR-572) had gene targets enriched in neural biological processes, particularly those involved in the regulation of neurotransmitters and synapses (Fig. 4C, Supplementary Figure S5). In addition, miR-4788 is conserved from humans to marmosets, and miR-572 is conserved from humans to gorillas. This finding may be implicated in the phenomenon of species-specific trait heritability of miRNAs.

We also assessed whether the targets of the retro-miRs were enriched in specific Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Remarkably, we found enrichment of several cancer-specific pathways, including breast, colorectal, gastric, pancreatic, prostate, and lung cancers (Fig. 4D), in addition to more general cancer-related pathways, such as P53, ErbB, and MAPK signaling, as well as resistance to platinum drugs and EGFR tyrosine kinase inhibitors (Supplementary Table S8). In this analysis, several known cancer genes, including BRAF, KRAS, EGFR, and TP53 emerged as targets of retro-miRs.

Taken together, the expression and gene target investigation revealed that retro-miRs (except miR-10527) have reliable expression and validated gene targets, which are the two fundamental characteristics of functional miRNAs. We also observed that retro-miRs target genes involved in fundamental cell processes (e.g., cell growth, regulation of transcription, and post-transcriptional regulation) and that two novel retro-miRs (miR-572 and miR-4788) regulate genes related to neuronal functions. Additionally, we observed that these retro-miRNAs targeted key cancer genes, suggesting that they play oncogenic roles in cancer tissues.

Retro-miRs are highly or majorly transcribed in cancer tissues

Our previous results (Fig. 4D) prompted us to study the expression of these retro-miRs in cancer tissues. Using short RNA-seq data available in TCGA [31], we expressed mature retro-miRs in 10 solid tumors. Their normal counterpart tissues were used as controls due to the relatively limited number of normal samples. Overall, this investigation revealed that retro-miRs have distinct and high expression levels in cancer (Fig. 5). Specifically, miR-10527-5p, miR-3654, miR-4444, miR-4788, and miR-1244 were highly expressed in cancer tissues but were also expressed in several normal tissues (Fig. 5). Interestingly, miR-10527-5p was highly expressed in tumors, although it was not expressed in normal samples or cell lines (Fig. 3). Remarkably, five retro-miRs emerged as putative tumor biomarkers because they presented a very low (or absent) expression in normal samples and consistent expression in cancer. Notably, two retro-miRs (miR-622 and miR-492) were exclusively expressed in seven cancer types each: BRCA (miR-622), COAD (miR-622 and miR-492), LUAD (miR-622), PAAD (miR-622 and miR-492), PRAD (miR-622 and miR-492), STAD (miR-492), and THCA (miR-492) (Fig. 5). Two mature miRNAs from the same precursor (miR-7161), miR-7161-3p and miR-7161-5p, were also exclusively expressed in six cancer types: BRCA (miR-7161-3p and miR-7161-5p), COAD (miR-7161-3p), LUAD (miR-7161-3p), LIHC (miR-7161-5p), PAAD (miR-7161-3p and miR-7161-5p), and PRAD (miR-7161-3p). Finally, miR-4426 was found to be expressed exclusively in BRCA, COAD, KIRC, and PAAD.

Taken together, these results indicate that retro-miRs are highly expressed in cancer, with some retro-miRs presenting a cancer-specific expression pattern and thus, their potential as tumor biomarkers should be further studied.

Overall Survival based on groups of retro-miRs in TCGA samples

Having confirmed the high and distinct expression of retro-miRs in cancer, we sought to determine whether these miRNAs have prognostic value in the overall survival of patients with cancer. To assess this, we used Reboot [32], an algorithm that identifies gene signatures (including those of miRNAs) associated with cancer patient prognosis. Using this strategy in approximately 8000 samples from 10 cancer types presenting with overall survival (OS) data, we found two signatures with prognostic value: a signature with two retro-miRs (Fig. 6A-B) in liver hepatocellular carcinoma (LICH) and another with three retro-miRs with prognostic value in STAD (Fig. 6C-D). In detail, Fig. 6A shows the overall survival curve of two sets of patients with LICH: patients with higher expression of miR-4444 and miR-3654 presented significantly (p-value < 0.0002) lower overall survival (e.g., overall survival of ~ 1650 days for 50% of patients) than patients with lower miR-4444 and miR-3654 expression (e.g., survival of ~ 2600 days (60% more) for 50% of patients). In patients with STAD, three retro-miRs (miR-622, miR-4788, and miR-4444) with high expression were associated with worse overall survival. Patients with a higher expression of these retro-miRs had a lower overall survival (~ 850 days for 50% of patients) than patients with a lower expression of these retro-miRs (~ 1300 days for 50% of patients). Thus, these data also show the prognostic value of these retro-miRs in LIHC and STAD and add a greater layer of functionality (which needs to be further explored) to these retrocopy-derived miRNAs.

MiRNAs are crucial regulators of gene expression and are instrumental elements in species evolution. Understanding the mechanisms underlying miRNA origination and their functions is essential for understanding the evolution of increasingly complex organisms and disease development, including cancer. Retrocopies, gene copies generated by the retroduplication of an mRNA molecule [18], are widespread in human and primate genomes and play a crucial role in shaping the genomic landscape and driving evolutionary innovation [17, 19]. In this study, we investigated retro-miRs, a class of miRNAs that emerge from the retroduplication of protein-coding genes (mRNAs). We explored retro-miR origination, conservation, expression, gene targets, and putative roles in cancer, including their potential to serve as tumor biomarkers and their association with overall cancer survival (prognostics).

MiRNAs are widespread in the animal kingdom [33]. The current miRBase release (22.1) presents 253 annotated (precursor) miRNAs in Caenorhabditis elegans, 882 miRNAs in chickens, 1,234 miRNAs in mice, and 1,917 miRNAs in humans. Interestingly, some miRNAs are widely conserved (e.g., mir-100, conserved in eumetazoans), but mammals, especially primates, present a high number of miRNAs that are associated with the emergence of novel phenotypes in the evolution of these species [5]. Briefly, miRNAs act primarily by buffering (reducing the variance in) the expression levels of their target genes. Finally, miRNAs ensure a stable gene expression mode against endogenous and exogenous factors, maintaining invariant (novel) phenotypes [5, 6]. A prerequisite for the origin of a novel mRNA is a transcribed genomic locus capable of producing an RNA fold that is recognizable by the miRNA processing machinery [1]. DNA duplication of pre-existing miRNAs, followed by their sub-functionalization or neofunctionalization, is a major source of novel miRNA genes [8]. However, miRNA origination from scratch (especially from intronic regions), duplication of non-coding RNAs (small nucleolar RNAs (snoRNAs) and transfer RNAs (tRNAs)), and retroduplicated elements (transposable elements) have also been reported [34]. Interestingly, Devor [15] demonstrated that two primate-specific miRNAs originated from retroduplicated genes (processed pseudogenes or retrocopies) and suggested that retrocopies are good miRNA incubators [15]. Conversely, even with the advent of genomics and bioinformatics, new investigations of miRNAs originating from retrocopies have not been conducted. This study fills this gap in the literature by identifying 17 novel miRNAs that originate from the retroduplication of protein-coding genes. Interestingly, these novel miRNAs are primate-specific, with three being shared only between humans and chimpanzees, and two are human-specific retro-miRs (Fig. 2). Surprisingly, some of these miRNAs (hsa-mir-572 and hsa-mir-622) have been studied for years but have never been found to originate from mRNA retroduplication. For example, the (retro-)miR-572 originated in RNPS1 retrocopy, RNPS1P1.

To function, an miRNA gene must be transcribed, folded, processed, and have gene targets [1]. Using RNA sequencing data (and TSS definition) from tissues and cell lines, we confirmed that all retro-miRs (except miR-10527) were transcribed (Fig. 3). Curiously, miR-10527 shows expression in both cancer and normal tissues (Fig. 5). As expected for a set of genes (miRNAs) presenting distinct functions and under the control of different promoter regions, the expression profile of retro-miRs ranged from retro-miRs expressed in a few samples and tissues to others being highly expressed in more tissues (Fig. 3). In the second step, we identified retro-miR gene targets. Notably, all retro-miRs had predicted and experimentally validated gene targets, except for miR-10527, which lacked a validated target. Gene Ontology analysis of the biological processes associated with retro-miR targets revealed genes involved in fundamental cellular processes and functions, including cell differentiation and signaling, DNA replication, gene expression regulation, and neurotransmitter transport (Fig. 4). Remarkably, two novel retro-miRs, miR-572 and miR-4788, have gene targets that are primarily involved in brain functions, such as nervous system development, regulation of neurotransmitter levels, neurotransmitter transport, and synapses. Therefore, because miRNAs provide robustness to their target gene regulatory networks, helping to maintain novel traits [5], these novel and primate-specific retro-miRs are promising candidates for further exploration in the context of key genes (miRNAs) to explain the evolution of the brain in humans and other primates.

Additionally, we found that retro-miRs target important cancer-related genes (Fig. 4D), prompting us to investigate their expression in cancer. First, we confirmed that retro-miRNAs were highly expressed in several cancer types (Fig. 5). Three retro-miRs (miR-572, miR-622, and miR-492) have been extensively studied in cancer. Studies have shown that miR-572 can act as both a tumor suppressor and oncogene, depending on the tissue and tumor type. Consistent with our findings (Fig. 5), miR-572 has been shown to have low expression levels (potentially acting as a tumor suppressor) in breast [35] and colorectal tumors [36]. On the other hand, the oncogenic role of miR-572 has been confirmed in lung tumors [37], hepatocellular carcinoma [38], and kidney cancer [39], which is also consistent with our results (Fig. 5). However, the importance of retro-miRs in other tumors (Fig. 5) remains underexplored. For miR-622, the literature also reports that this retro-miR can act as both a tumor suppressor and an onco-miR in several cancers, such as breast cancer, glioma, colorectal cancer, hepatocellular carcinoma (HCC), lung cancer, gastric cancer (GC), melanoma, ovarian carcinoma, prostate cancer, and pancreatic cancer [40], which is in agreement with our results (Fig. 5). Similar to the other two retro-miRs, the literature reports that miR-492 acts as both a tumor suppressor and an oncogene. Consistent with our expression data, this retro-miR is upregulated in metastatic hepatoblastoma [41], lung cancer [42], and stomach cancer [43]. However, for other retro-miRs (Fig. 5), few or no investigations have been performed on tumor tissues.

Finally, we also found that the expression (signature) of two sets of retro-miRs was associated with the overall survival in two cancer types: LIHC and STAD (Fig. 6). These results require further investigation.

In conclusion, we conducted a comprehensive study of miRNAs derived from retroduplicated protein-coding genes in the human genome. Our findings demonstrated that these retro-miRs are expressed in a conserved environment, have regulatory targets in fundamental cellular processes, including those in the nervous system, and exhibited differential expression and functional roles in various cancer types. Overall, our study sheds light on the role of mRNA retrotransposition in generating genetic novelties, such as miRNAs, and highlights the potential for future investigations into the function of retrocopies in humans and other organisms.

Identification of retro-miRs derived from retrocopies

To identify the retro-miRs, we followed these steps: i) we used mirBase (http://www.mirbase.org/) as an annotation source for miRNA characteristics, such as their genomic position and gene name; ii) our dataset of retrocopied genes was obtained from the RCPedia database [26], which contains information on retrocopies (e.g., genomic location, sequences, expression, and conservation) and their parental genes. To convert the retrocopies' genomic coordinates from hg19 to hg38 we used the LiftOver online tool (https://genome.ucsc.edu/cgi-bin/hgLiftOver). Subsequently, we selected miRNAs from miRBase whose genomic coordinates overlapped with those of the retrocopies using BedTools v2.26.0 (with default parameters and a minimum overlap of 5 bp) [44]. We manually removed the data of those miRNAs that originated from the insertion of a mobile element into the retrocopies. To assess the colocalization (exonic, intronic, and intergenic) of miRNAs and protein-coding genes, we used the miRIAD database [24, 25]. Additionally, we selected annotated exonic miRNAs of coding genes whose retrocopies and retro-miRs were already identified. We aligned the mature miRNA sequences from these candidates against the respective retrocopies of the coding genes using Clustal Omega available at EMBL (https://www.ebi.ac.uk/Tools/msa/clustalo/). To evaluate the formation of secondary structures, we used RNAFold version 2.4.17 [45]. When a secondary structure was formed, the candidates were considered retro-miRs.

DNA-mediated duplication

To identify duplicated genes, we used transcripts annotated in GENCODE v32. We used tblastn 2.7.1+ [46] with default parameters to align the amino acid sequences of all transcripts against their nucleotide sequences. We considered that a gene has a DNA-mediated duplication if it has at least one alignment besides its own nucleotide transcript with a score that is divided by the score of its original nucleotide transcript and is greater than or equal to 0.7. Additionally, we searched for miRNAs in these duplicated genes and duplications of these miRNAs in the duplicated genes using the miRNA genomic coordinates provided by miRBase.

Classification of retro-miRs

To classify retro-miRs into R-retro-miRs, EJ-retro-miRs, and N-retro-miRs, we aligned the sequences of retro-miRs against the reference genome (GRCh38) using the BLAT tool (https://genome.ucsc.edu). For each retro-miR, we investigated the alignment pattern with the parental retrocopy gene. Based on this, three major patterns emerged: (I) retro-miRs, which are exact copies of the exonic miRNA of the parental sequence (R-retro-miRs); (II) retro-miRs originating from the exon-exon junction (EJ-retro-miRs); and (III) retro-miRs originating from mutations (> 1 bp) in relation to the parental gene in the mature sequence (N-retro-miRs).

Conservation of retro-miRs among primates

The conservation of retro-miRs among primate genomes was determined using MultiZAling, which is available in the Genome Browser (https://genome.ucsc.edu/index.html). We compared the sequences of miRNAs annotated in humans with those of the genomes of chimpanzee (Pan_tro 3.0), gorilla (GSMRT3), orangutan (WUGSC 2.0.2), rhesus (BCM Mmul_8.0.1), and marmoset (WUGSC 3.2). We considered a retro-miR to be conserved if its sequence identity with homologous sequences in these genomes was greater than 80%.

dN/dS Analysis

To calculate the dN/dS values, we extracted the nucleotide sequences of the retrocopies from the reference genome (GRCH38) and used ORFfinder [47] to extract the longest predicted amino acid (aa) sequence. For human retrocopies (HNRNPA3P6 and RPS27AP5), we used BLAT [48] to align the predicted aa sequence against the human genome (version GRCh38/hg38) and retrieved the best match of the parental gene nucleotide sequence (paralog). For retrocopies with a primate ortholog (RPS27AP16, PTMAP2, PTMAP9, PTMAP4, RP11-371A22.1, RNPS1P1, PTMAP8, RP11-529H20.3, EEF1GP5, KRT18P27, TATDN2P2, HMGB3P13, RCC2P3, KRT19P2, and PABPC1P4), we aligned the predicted human aa sequence against the genome of chimpanzees (panTro6) with BLAT and retrieved the best match on the retrocopy ortholog. For both the paralogs and orthologs, we used ORFfinder to find the longest predicted aa sequence equivalent to the aa sequence of the human retrocopy. ClustalW [49] was used to align the aa sequence of the retrocopy and its corresponding paralog or ortholog. PAL2NAL (codeml; CodonFreq = 2, model = 0, Nsites = 0, fix_omega = 0, omega = 0.4) [50] was used to calculate the synonymous (dS) and non-synonymous (dN) substitution rates. The p-values of dN/dS were determined by comparison to a model assuming neutral evolution (fix_omega = 1, omega = 1 for paralogs, and omega = 0.5 for orthologs) with a likelihood-ratio test [LRT], p-value < 0.05, chi-sq. distribution. blastn [47] was used to calculate the identity between nucleotide sequence equivalents of the coding sequence (CDS).

Retro-miR expression and TSS definition in normal and cancer tissues

Expression of these retro-miRs in normal tissues was analyzed using preprocessed data from the FANTOM Phase 5 database [29, 30]. The extracted data were related to the expression of retro-miRNAs, as per miRNA-seq of samples from different cell types (Table 1S). We screened for a TSS on the expected transcription orientation (based on the miRNA direction) up to a distance of 4000 base pairs of the 5' end of the retro-miR. We also used preprocessed miRNA expression (short RNA-seq methodology) data from TCGA and the microRNA Tissue Expression Database (miTED). We selected TCGA data as the main data for further investigations and selected miTED expression data for miRNAs that were not initially expressed in TCGA data. In both datasets, we normalized the data using transcripts per million (TPM). Expression was quantified only for the mature retro-miR sequences.

Investigating the prognostic value of retro-miRs in 10 cancer types

To investigate the prognostic value of retro-miRs in cancer, short RNA-seq and patient's survival information were extracted from TCGA for the following tumor types: breast cancer (BRCA), colon adenocarcinoma (COAD), kidney renal clear cell carcinoma (KIRC), liver hepatocellular carcinoma (LIHC), lung squamous cell carcinoma (LUSC), lung adenocarcinoma (LUAD), pancreatic adenocarcinoma (PAAD), prostate adenocarcinoma (PRAD), stomach adenocarcinoma (STAD), and thyroid carcinoma (THCA). Only retro-miRNAs (TPM > 0) were considered for the analysis. The association between the retro-miR expression signature (combined expression of two or more retro-miRs) and overall patient survival was assessed using Reboot (dos Santos et al., 2021) with default parameters.

Finding retro-miR target genes

To find out the target genes of retro-miRs, we ran TargetScan 7.0 with the set of 3′ UTR sequences of protein-coding genes provided by the Targetscan [27]. We selected only transcripts that had 8mer-1a or 7mer-m8 site types, or if these genes were represented in miRTarBase [28]. Enrichment analyses of target genes in Gene Ontology (Biological Processes) and KEGG pathways were performed using ShinyGO v0.77 (http://bioinformatics.sdstate.edu/go/). Redundant Gene Ontology terms were removed using REVIGO (http://revigo.irb.hr/). Only Gene Ontology processes and KEGG pathways with fold enrichment > 1.5 and false discovery rate (FDR) < 0.05 were considered significant.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This work was supported by grant #2018/15579-8, São Paulo Research Foundation (FAPESP) to PAFG; grants: #2020/02413-4 (to RLVM), #2018/13613-4 (to HBC), #2017/19541-2 (to GDAG), São Paulo Research Foundation (FAPESP). Partially supported by funds from Serrapilheira Foundation, CNPq and Hospital Sírio-Libanês to PAFG.

Authors' contributions

R.L.M. and P.A.F.G. conceived the study. R.L.M., H.B.C., and G.D.A.G. performed the analyses. G.G., M.D.V., and L.C.H. contributed to the analyses. R.L.M., H.B.C., G.D.A.G., G.G., M.D.V., L.C.H., and P.A.F.G. discussed the results. P.A.F.G. coordinated the study and prepared the manuscript, with inputs from all authors. All authors reviewed and approved the final manuscript.

Acknowledgements

We would like to thank all members of the Galante lab for their helpful discussions and feedback on the manuscript.

Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004;116:281–97.
Grimson A, Srivastava M, Fahey B, Woodcroft BJ, Chiang HR, King N, et al. Early origins and evolution of microRNAs and Piwi-interacting RNAs in animals. Nature. 2008;455:1193–7.
Axtell MJ, Westholm JO, Lai EC. Vive la différence: biogenesis and evolution of microRNAs in plants and animals. Genome Biol. 2011;12:221.
Bartel DP. MicroRNAs: target recognition and regulatory functions. Cell. 2009;136:215–33.
Berezikov E. Evolution of microRNA diversity and regulation in animals. Nat Rev Genet. 2011;12:846–60.
Peterson KJ, Dietrich MR, McPeek MA. MicroRNAs and metazoan macroevolution: insights into canalization, complexity, and the Cambrian explosion. Bioessays. 2009;31:736–47.
Chen K, Rajewsky N. The evolution of gene regulation by transcription factors and microRNAs. Nat Rev Genet. 2007;8:93–103.
Ruby JG, Stark A, Johnston WK, Kellis M, Bartel DP, Lai EC. Evolution, biogenesis, expression, and target predictions of a substantially expanded set of Drosophila microRNAs. Genome Res. 2007;17:1850–64.
Liu N, Okamura K, Tyler DM, Phillips MD, Chung W-J, Lai EC. The evolution and functional diversification of animal microRNA genes. Cell Res. 2008;18:985–96.
Hertel J, Lindemeyer M, Missal K, Fried C, Tanzer A, Flamm C, et al. The expansion of the metazoan microRNA repertoire. BMC Genomics. 2006;7:25.
França GS, Vibranovski MD, Galante PAF. Host gene constraints and genomic context impact the expression and evolution of human microRNAs. Nat Commun. 2016;7:11438.
França GS, Hinske LC, Galante PAF, Vibranovski MD. Unveiling the Impact of the Genomic Architecture on the Evolution of Vertebrate microRNAs. Front Genet. 2017;8:34.
Piriyapongsa J, Mariño-Ramírez L, Jordan IK. Origin and evolution of human microRNAs from transposable elements. Genetics. 2007;176:1323–37.
Scott MS, Avolio F, Ono M, Lamond AI, Barton GJ. Human miRNA precursors with box H/ACA snoRNA features. PLoS Comput Biol. 2009;5:e1000507.
Devor EJ. Primate microRNAs miR-220 and miR-492 lie within processed pseudogenes. J Hered. 2006;97:186–90.
Ender C, Krek A, Friedländer MR, Beitzinger M, Weinmann L, Chen W, et al. A human snoRNA with microRNA-like functions. Mol Cell. 2008;32:519–28.
Casola C, Betrán E. The Genomic Impact of Gene Retrocopies: What Have We Learned from Comparative Genomics, Population Genomics, and Transcriptomic Analyses? Genome Biol Evol. 2017;9:1351–73.
Kaessmann H, Vinckenbosch N, Long M. RNA-based gene duplication: mechanistic and evolutionary insights. Nat Rev Genet. 2009;10:19–31.
Navarro FCP, Galante PAF. A Genome-Wide Landscape of Retrocopies in Primate Genomes. Genome Biol Evol. 2015;7:2265–75.
Bim LV, Navarro FCP, Valente FOF, Lima-Junior JV, Delcelo R, Dias-da-Silva MR, et al. Retroposed copies of RET gene: a somatically acquired event in medullary thyroid carcinoma. BMC Med Genomics. 2019;12:104.
Carelli FN, Hayakawa T, Go Y, Imai H, Warnefors M, Kaessmann H. The life history of retrocopies illuminates the evolution of new mammalian genes. Genome Res. 2016;26:301–14.
Parker HG, VonHoldt BM, Quignon P, Margulies EH, Shao S, Mosher DS, et al. An expressed fgf4 retrogene is associated with breed-defining chondrodysplasia in domestic dogs. Science. 2009;325:995–8.
Kozomara A, Griffiths-Jones S. miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res. 2014;42:D68–73.
Hinske LC, França GS, Torres HAM, Ohara DT, Lopes-Ramos CM, Heyn J, et al. miRIAD-integrating microRNA inter- and intragenic data. Database [Internet]. 2014;2014. Available from: http://dx.doi.org/10.1093/database/bau099
Hinske LC, Dos Santos FRC, Ohara DT, Ohno-Machado L, Kreth S, Galante PAF. MiRIAD update: using alternative polyadenylation, protein interaction network analysis and additional species to enhance exploration of the role of intragenic miRNAs and their host genes. Database [Internet]. 2017;2017. Available from: http://dx.doi.org/10.1093/database/bax053
Navarro FCP, Galante PAF. RCPedia: a database of retrocopied genes. Bioinformatics. 2013;29:1235–7.
Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 2005;120:15–20.
Chou C-H, Shrestha S, Yang C-D, Chang N-W, Lin Y-L, Liao K-W, et al. miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions. Nucleic Acids Res. 2018;46:D296–302.
de Rie D, Abugessaisa I, Alam T, Arner E, Arner P, Ashoor H, et al. An integrated expression atlas of miRNAs and their promoters in human and mouse. Nat Biotechnol. 2017;35:872–8.
Lizio M, Abugessaisa I, Noguchi S, Kondo A, Hasegawa A, Hon CC, et al. Update of the FANTOM web resource: expansion to provide additional transcriptome atlases. Nucleic Acids Res. 2019;47:D752–8.
Cancer Genome Atlas Research Network, Weinstein JN, Collisson EA, Mills GB, Shaw KRM, Ozenberger BA, et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet. 2013;45:1113–20.
Dos Santos FRC, Guardia GDA, Dos Santos FF, Ohara DT, Galante PAF. Reboot: a straightforward approach to identify genes and splicing isoforms associated with cancer patient prognosis. NAR Cancer. 2021;3:zcab024.
Pasquinelli AE, Reinhart BJ, Slack F, Martindale MQ, Kuroda MI, Maller B, et al. Conservation of the sequence and temporal expression of let-7 heterochronic regulatory RNA [Internet]. Nature. 2000. p. 86–9. Available from: http://dx.doi.org/10.1038/35040556
Campo-Paysaa F, Sémon M, Cameron RA, Peterson KJ, Schubert M. microRNA complements in deuterostomes: origin and evolution of microRNAs. Evol Dev. 2011;13:15–27.
Gasparini P, Lovat F, Fassan M, Casadei L, Cascione L, Jacob NK, et al. Protective role of miR-155 in breast cancer through RAD51 targeting impairs homologous recombination after irradiation. Proc Natl Acad Sci U S A. 2014;111:4536–41.
Bobowicz M, Skrzypski M, Czapiewski P, Marczyk M, Maciejewska A, Jankowski M, et al. Prognostic value of 5-microRNA based signature in T2-T3N0 colon cancer. Clin Exp Metastasis. 2016;33:765–73.
Sun B, Zhao J, Shao Z-Y. MiR-572 promotes the development of non-small cell lung cancer by targeting KLF2. Eur Rev Med Pharmacol Sci. 2022;26:3083–90.
Song C, Li D, Liu H, Sun H, Liu Z, Zhang L, et al. The competing endogenous circular RNA ADAMTS14 suppressed hepatocellular carcinoma progression through regulating microRNA-572/regulator of calcineurin 1. J Cell Physiol. 2019;234:2460–70.
Zhang C, Lv G-Q, Cui L-F, Guo C-C, Liu Q-E. MicroRNA-572 targets CDH1 to promote metastasis of Wilms’ tumor. Eur Rev Med Pharmacol Sci. 2019;23:3709–17.
Lu J, Xie Z, Xiao Z, Zhu D. The expression and function of miR-622 in a variety of tumors. Biomed Pharmacother. 2022;146:112544.
von Frowein J, Hauck SM, Kappler R, Pagel P, Fleischmann KK, Magg T, et al. MiR-492 regulates metastatic properties of hepatoblastoma via CD44. Liver Int. 2018;38:1280–91.
Zou W, Wang Y, Song Q, Li Q, Ren J, Liu X, et al. Ultrasound-targeted microbubble destruction mediated miR-492 inhibitor suppresses the tumorigenesis in non-small cell lung cancer. Ann Med. 2021;53:2246–55.
Dinesh H, Jayaraman M. Role of microRNAs in the progression and metastasis of gastric cancer. J Appl Biol Biotechnol. Open Science Publishers LLP; 2022;1–8.
Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26:841–2.
Lorenz R, Bernhart SH, Höner Zu Siederdissen C, Tafer H, Flamm C, Stadler PF, et al. ViennaRNA Package 2.0. Algorithms Mol Biol. 2011;6:26.
Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997;25:3389–402.
Wheeler DL, Church DM, Federhen S, Lash AE, Madden TL, Pontius JU, et al. Database resources of the National Center for Biotechnology. Nucleic Acids Res. 2003;31:28–33.
Kent WJ. BLAT--the BLAST-like alignment tool. Genome Res. 2002;12:656–64.
McWilliam H, Li W, Uludag M, Squizzato S, Park YM, Buso N, et al. Analysis Tool Web Services from the EMBL-EBI. Nucleic Acids Res. 2013;41:W597–600.
Yang Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol. 2007;24:1586–91.

No competing interests reported.

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published 08 Sep, 2023

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Retro-miRs: Novel and functional miRNAs originating from mRNA retrotransposition

Status:

Journal Publication

Version 1

Abstract

Figures

Background

Results

Finding miRNAs originated by mRNA retrotransposition events

Characteristics and conservation of retro-miR events

Retro-miRs are highly or majorly transcribed in cancer tissues

Overall Survival based on groups of retro-miRs in TCGA samples

Discussion

Conclusions

Materials And Methods

Identification of retro-miRs derived from retrocopies

DNA-mediated duplication

Classification of retro-miRs

Conservation of retro-miRs among primates

dN/dS Analysis

Retro-miR expression and TSS definition in normal and cancer tissues

Investigating the prognostic value of retro-miRs in 10 cancer types

Finding retro-miR target genes

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1