- Research article
- Open Access
Retrotransposon-centered analysis of piRNA targeting shows a shift from active to passive retrotransposon transcription in developing mouse testes
© Mourier; licensee BioMed Central Ltd. 2011
- Received: 15 April 2011
- Accepted: 1 September 2011
- Published: 1 September 2011
Piwi-associated RNAs (piRNAs) bind transcripts from retrotransposable elements (RTE) in mouse germline cells and seemingly act as guides for genomic methylation, thereby repressing the activity of RTEs. It is currently unknown if and how Piwi proteins distinguish RTE transcripts from other cellular RNAs. During germline development, the main target of piRNAs switch between different types of RTEs. Using the piRNA targeting of RTEs as an indicator of RTE activity, and considering the entire population of genomic RTE loci along with their age and location, this study aims at further elucidating the dynamics of RTE activity during mouse germline development.
Due to the inherent sequence redundancy between RTE loci, assigning piRNA targeting to specific loci is problematic. This limits the analysis, although certain features of piRNA targeting of RTE loci are apparent. As expected, young RTEs display a much higher level of piRNA targeting than old RTEs. Further, irrespective of age, RTE loci near protein-coding coding genes are targeted to a greater extent than RTE loci far from genes. During development, a shift in piRNA targeting is observed, with a clear increase in the relative piRNA targeting of RTEs residing within boundaries of protein-coding gene transcripts.
Reanalyzing published piRNA sequences and taking into account the features of individual RTE loci provide novel insight into the activity of RTEs during development. The obtained results are consistent with some degree of proportionality between what transcripts become substrates for Piwi protein complexes and the level by which the transcripts are present in the cell. A transition from active transcription of RTEs to passive co-transcription of RTE sequences residing within protein-coding transcripts appears to take place in postnatal development. Hence, the previously reported increase in piRNA targeting of SINEs in postnatal testis development does not necessitate widespread active transcription of SINEs, but may simply be explained by the prevalence of SINEs residing in introns.
Retrotransposable elements (RTE) constitute a significant proportion of mammalian genomes. The RTEs proliferate through an RNA stage that is subsequently reverse transcribed back to genomic DNA . The high level of divergence in RTE insertions between closely related organisms [2–5] and the link between RTE insertions and diseases [6–8] witness the ongoing activity of RTEs in mammalian genomes. Several genomic mechanisms are devised to minimize the proliferation of RTEs acting both at pre- and post-transcriptional levels [9–11].
Mouse retrotransposable elements
Around 40 percent of the mouse genome consists of RTE sequence, slightly lower than observed for the human genome, although this presumably is a result of the higher substitution rate in mouse, limiting the identification of old RTE sequence [12, 13]. RTEs are divided according to the presence or absence of long terminal repeats (LTR). Mammalian LTR elements consist mainly of endogenous retroviruses (ERV) that at some point during evolution have been inserted in the germline and fixed. Although the amount of sequence occupied by LTR elements is comparable between human and mouse, the level of de novo mutations caused by LTR element activity is extensively higher in mouse than in human [8, 14]. The most abundant ERV class in the mouse genome (~5.5%) is the Class III ERVs, which in the RepeatMasker  annotation - upon which this study is based - is broadly divided in two groups, the ERVL and MaLR elements. The latter is a non-autonomous transposon, meaning that the elements do not encode the enzymatic machinery required for its own transposition. The Class II ERVs (~4% of the genome), annotated as ERVK in RepeatMasker, is believed to be younger than Class III ERVs  and consists of a broad range of clades, including the IAP elements (Intracisternal A-type Particles). Class I ERVs (ERV1 in RepeatMasker) cover less than 1% of the mouse genome. Through ectopic recombination between the flanking LTR sequences, solitary LTR sequences may be formed. In RepeatMasker, terminal LTR sequences and the internal sequences (residing between the terminal LTRs in a complete LTR retrotransposon) are annotated independently. Although the terminal and internal sequences may in many cases be determined to form a single LTR retrotransposon, for simplicity, the two annotations (termed 'LTRter' and 'LTRint', respectively) are analysed independently in this study.
Non-LTR retrotransposons are divided into LINEs (Long INterspersed Elements) that are autonomous, and SINEs (Short INterspersed Elements) that are non-autonomous. LINEs occupy roughly 20% of the mouse genome. The majority of mouse LINE elements belong to the L1 superfamily, which contains sub-families that are still active [17–19]. Despite the comparable levels of genome occupied by LINE sequences in human and mouse [12, 13], there are more than 15 times as many full-length L1 elements with intact open reading frames in the mouse genome . Almost 1.5 million SINE elements are present in the mouse genome, making up approximately 8% of the total genome size. Unlike the human genome where a single SINE, the Alus, is dominating , the mouse genome harbours two successful superfamilies of SINEs, Alu and B2 that are present in equal numbers . The evolutionary histories of the mouse SINEs are truly different; Alus are derived from a 7SL RNA, whereas B2s evolved from a tRNA sequence [21, 22].
Piwi proteins and small RNAs
Piwi-associated RNAs (piRNAs) are small (24-30 nucleotides long) RNAs that bind Piwi proteins of the Argonaute family [23, 24]. The mouse genome encodes 3 Piwi proteins, MILI, MIWI and MIWI2 that all binds piRNAs in the male germline [25, 26]. Initially, piRNAs from adult mouse testis were found to contain less RTE sequence than would be expected from the genomic content of RTEs, suggesting that piRNAs were not specifically targeting RTEs [27, 28]. However, a later study on piRNAs from an earlier (pre-pachytene) stage showed a high content of RTE sequence in piRNAs . Further evidence for the involvement of mouse piRNAs in controlling RTE activity came with the finding that knockout of Mili and Miwi2 resulted in reduced piRNA levels and increased RTE transcription [29, 30]. Knockout mice further showed decreased DNA methylation levels at RTE loci [31, 32]. As the temporal expression of Piwi proteins in developing mouse testis coincides with the resetting of genomic methylation , it is hypothesised that piRNAs act as guides for the methylation machinery [29, 31, 32].
By analysing the piRNAs bound to MIWI2 and MILI, Aravin and colleagues  suggested the following scenario: In prenatal development (16.5 days postcoitum, dpc), transcripts from full-length active RTEs are the main substrates for piRNAs that primarily associate with MILI (and to a lesser extent to MIWI2). Available transcripts containing antisense RTE sequence bind this complex and antisense RTE piRNAs are formed which in turn associate primarily with MIWI2 (and MILI, respectively). Both complexes may bind complementary RTE transcripts, entering the so-called ping-pong amplification cycle of piRNAs, in which Piwi-bound piRNAs pair with complementary transcripts that are subsequently cut into new piRNAs having a 10 nucleotide overlap with the template piRNAs [31, 34]. In prenatal development, piRNAs are primarily targeting L1 and IAP RTEs, for which activity has been reported at this stage [35, 36]. In postnatal development (10 days postpartum, dpp) MIWI2 is no longer detectable, whereas MILI is present throughout germline development [31, 37, 38]. The overall level of piRNA targeting of RTE sequences drops at 10 dpp, but interestingly, a relative increase in the piRNAs targeting B1 SINEs (members of the Alu superfamily) was observed .
This raises two fundamental questions. Firstly, do Piwi proteins discriminate between transcripts and how is RTE sequences then distinguished from other transcripts? The finding of piRNAs targeting supported a scenario with limited discrimination . Secondly, what lies behind the apparent shift in RTEs being targeted by piRNAs during development in male mouse germline? By analysing to extent to which genomic RTE loci are targeted by piRNAs in developing mouse testes, the present study aims at assessing the transcriptional dynamics of RTE during development, and consider the relationship between RTE activity and piRNA generation further.
The data for such analysis should meet a range of criteria. Although numerous mouse RNA libraries are available, only a small subset is derived from wild-type developing mouse testes . Further, as the prevalent transcription of RTEs will results in a large population of fragmented transcripts of sizes similar to piRNAs, analysis should be restricted to libraries of RNAs associated with Piwi proteins. This limits the available data to libraries from the above-mentioned study by Aravin and colleagues .
Results and Discussion
Theoretical piRNA coverage of individual RTE loci
Piwi-RNA sequence read libraries
Percent of mapped reads covering:
Raw reads (× 1000)
Mapped reads (× 1000)
Higher piRNA coverage of younger elements
Gene expression levels and piRNA coverage
For some RTE types, the relative number of young and old loci differ between the vicinities of highly expressed genes and lowly expressed genes, (Additional File 1, Figure S2), suggesting that the higher levels of piRNA coverage of RTE near highly expressed genes could simply be explained by the age of the RTE sequences. However, when repeating the analysis without the youngest RTE sequences, essentially similar results and significance levels are found (Additional File 1, Table S3).
Interestingly, when assessing the piRNA coverage of RTE sequence near transcription start sites (TSS), peaks are observed immediately upstream of TSS on the reverse strand, and for piRNAs not targeting RTEs, also immediately downstream of TSS on the forward strand (Additional File 1, Figure S3). Such a pattern resembles that of the recently discovered short transcripts generated around TSS (the TSS-associated RNAs) [45, 46] suggesting that these piRNAs may in fact be TSS-associated RNAs. It is uncertain if this represents experimental contamination of non-piRNAs or if these TSS-associated RNAs provide the transcripts that a processed into piRNAs, although the presence of RNA reads smaller than the usual 24-30 nucleotides - especially among early MILI piRNAs - hints that a contribution from the former scenario cannot be ruled out (Additional File 1, Figure S4). Assuming all RNAs mapping within 1000 base pairs of an annotated TSS are TSS-associated RNAs and removing these from the analysis does not change any of the presented conclusions (data not shown).
piRNA coverage and distance to genes
Strand bias in piRNA coverage of genic RTEs
As reported previously, RTE families are targeted very differently by piRNAs in developing mouse testes. By focusing on the total population of RTE loci, the present reanalysis of published data reveal further differences in piRNA targeting between individual members of RTE families. The available data for this analysis is arguably limited and the presented data relies on a single set of experiments. Although deep-sequencing techniques ideally should provide sequences from all available transcripts in a neutral fashion, biases may be introduced experimentally, especially during construction of libraries . Furthermore, considerable biological differences in RTE sequences have been reported between mouse strains [49, 50]. Nevertheless, the vast majority of RTE sequences will be shared among all extant mice, and the results presented here are all of a global genomic character with no predictions for individual loci, suggesting a fair generality of the findings.
Transcriptional activity is correlated between genomic regions residing near each other [51–53], and the observation that piRNA targeting of RTEs is higher around highly expressed genes, may simply reflect that transcription of RTEs is more permissible near highly expressed genes. A correlation between transcription levels of LTR sequences and their neighbouring genes has previously been reported in fission yeast . This further supports the notion that RTE transcripts are not specifically recognized as RTEs by the Piwi proteins, but are largely triggering the piRNA response in a manner proportional to their presence. It should be stressed that the reported preference by MILI for sense RTE sequences and the corresponding preference by MIWI2 for antisense sequences  suggest some level of discrimination of transcripts.
In postnatal testis development, piRNA targeting is shifted towards loci residing in introns of protein-coding genes. If, as assumed, active transcription of RTE loci is repressed at this stage, one would expect a higher proportion of RTE sequences in the total transcriptome to be derived from co-transcription of intronic RTE loci. This observation could at least in part explain the previously observed increase in piRNAs targeting SINE elements in postnatal stages , as SINE elements are the most abundant RTEs in introns (Additional File 1, Figure S5). Therefore, the increased piRNA response directed at SINE sequences does not necessitate transcription of active SINE elements in postnatal development. In fact, as SINE elements are non-autonomous, presumably using the enzymatic machinery provided by LINE elements [55, 56], there should be no basis for SINE proliferation in postnatal development if the prenatal silencing of LINE persists. Yet, SINE transcription may take place without subsequent transposition, and the known functional effects of mammalian SINE transcription [57–59] and the recently reported SINE RNA toxicity  suggest both active SINE transcription in later development, and the possible need for regulation.
On an evolutionary time scale, RTE activity has contributed hugely to the evolution of mammalian genomes [61–64], and when attempting to understand the diversity of present eukaryotic life it is essential to include the history and activity of RTEs. However, RTEs are not just silent passengers that occasionally spring into action, but have to be dealt with within each individual's life history. In this respect, the indirect approach of analysing small RNAs generated to repress RTE activity in the germline may produce further valuable knowledge on the activity of RTEs during development.
Data and Annotations
Small RNA libraries accession numbers GSM319953 (MILI late), GSM319956 (MILI early) and GSM319957 (MIWI2 early) were retrieved through DeepBase (http://deepbase.sysu.edu.cn/)  and mapped to the mouse genome (mm9 assembly) using bowtie . Prior to mapping, reads were filtered and sequences with ambiguous base calls and low-complexity sequences were removed. The latter was done measuring the linguistic complexity  of the sequences in 16 bp windows, and excluding reads with an average complexity of less than 0.75. Preliminary tests showed that this would remove highly repetitive reads with very large numbers of genomic mappings (not shown). For each library, this procedure filtered out between 0.14 and 0.17% of all raw reads. RepeatMasker and known gene annotations were downloaded from the UCSC Genome Browser [15, 40, 67]. A set of non-overlapping TSS was selected by grouping all known genes according to their assignment to ENSEMBL genes . For each ENSEMBL gene, the most abundant genomic start point was selected. If more than one point was found to have the highest abundance, the one furthest upstream of these was chosen. Gene expression levels were assessed from the 'testis' signal intensities in the Mouse GNF1M Gene Atlas from BioGPS (http://biogps.gnf.org/) .
Mapping and coverage
For each RTE loci the number of reads mapped within the locus were recorded. Reads were assigned a score of 1/(number of genomic mappings of read), so that only uniquely mapping reads scored 1. The read score were then divided by the size of the RTE loci (in kilo-base pairs). Finally, scores were divided by the total number (in millions) of mapped reads from the library in question.
To test for difference between RTE loci from different genomic regions (data presented in Figure 5), all RTE families were first split in 3 groups based on age where after members in each group were divided according to their genomic context (genic, proximal, distal). Hence, for each RTE family, nine sets of loci were formed, and the average piRNA coverage for each set was recorded. To test for difference between two groups (for example, between old LINE loci being genic or distal), pairs of average values were collected for the 90 LINE families (Additional File 1, Table S1) and tested using a Wilcoxon Signed-Rank Test. Bonferroni corrections (n = 108 in Figure 5) were calculated as: pcorrected = 1-(1-p)n. All statistical analyses were carried out using R .
This work was supported by a grant from the Lundbeck Foundation. I am indebted to JianHua Yang for invaluable advice on small RNAs, for preparing and providing RNA reads from DeepBase, and for critical reading of the manuscript.
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