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Genomic and Epigenetic Complexity of the FOXF1 Locus in 16q24.1: Implications for Development and Disease
research-article
Author(s):
Avinash V. Dharmadhikari
1
,
2 ,
Przemyslaw Szafranski
1 ,
Vladimir V. Kalinichenko
3 ,
Pawel Stankiewicz
1
,
2
,
*
Publication date (Electronic):
April 2015
Journal:
Current Genomics
Publisher:
Bentham Science Publishers
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Abstract
The FOXF1 (Forkhead box F1) gene, located on chromosome 16q24.1 encodes a member of the FOX family of transcription factors characterized by a distinct forkhead DNA binding domain. FOXF1 plays an important role in epithelium-mesenchyme signaling, as a downstream target of Sonic hedgehog pathway. Heterozygous point mutations and genomic deletions involving FOXF1 have been reported in newborns with a lethal lung developmental disorder, Alveolar Capillary Dysplasia with Misalignment of Pulmonary Veins (ACDMPV). In addition, genomic deletions upstream to FOXF1 identified in ACDMPV patients have revealed that FOXF1 expression is tightly regulated by distal tissue-specific enhancers. Interestingly, FOXF1 has been found to be incompletely paternally imprinted in human lungs; characterized genomic deletions arose de novo exclusively on maternal chromosome 16, with most of them being Alu-Alu mediated. Regulation of FOXF1 expression likely utilizes a combination of chromosomal looping, differential methylation of an upstream CpG island overlapping GLI transcription factor binding sites, and the function of lung-specific long non-coding RNAs (lncRNAs). FOXF1 knock-out mouse models demonstrated its critical role in mesoderm differentiation and in the development of pulmonary vasculature. Additionally, epigenetic inactivation of FOXF1 has been reported in breast and colorectal cancers, whereas overexpression of FOXF1 has been associated with a number of other human cancers, e.g. medulloblastoma and rhabdomyosarcoma. Constitutional duplications of FOXF1 have recently been reported in congenital intestinal malformations. Thus, understanding the genomic and epigenetic complexity at the FOXF1 locus will improve diagnosis, prognosis, and treatment of ACDMPV and other human disorders associated with FOXF1 alterations.
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Transposable Elements Are Major Contributors to the Origin, Diversification, and Regulation of Vertebrate Long Noncoding RNAs
Aurélie Kapusta, Zev Kronenberg, Vincent J Lynch … (2013)
Introduction There is a growing appreciation that the functional repertoire of metazoan genomes includes much more than protein-coding sequences [1]–[3]. Recent functional genomic studies have revealed, in particular, the widespread occurrence, bewildering diversity, and functional significance of noncoding RNA [4]. In addition to small regulatory RNAs, such as tRNAs or microRNAs, the genome encodes a myriad of long noncoding RNAs (lncRNAs) that are greater than 200 nt in length [for review: 5]–[7]. The most recent, though still conservative, catalogues predict between 5,000 and 10,000 discrete lncRNA loci in the human genome [8]–[10]. The majority of lncRNAs in these manually curated reference sets are intergenic units often referred to as large intergenic noncoding RNAs (lincRNAs) because they do not overlap with known protein-coding genes. Comparable numbers of lncRNA loci are expected to occur in the mouse and other vertebrate genomes [9], [11]–[16] and hundreds of loci with similar properties have also been identified in model invertebrates such as Drosophila melanogaster [17] and Caenorhabidtis elegans [18], as well as in the model plant Arabidopsis thaliana [19]. Although once dismissed as transcriptional ‘noise’, there is mounting evidence that many lncRNAs are important functional molecules engaged in diverse regulatory activities. First, the majority of functionally characterized lncRNAs exhibit precise spatiotemporal patterns of expression and, often, discrete cellular localization [9], [11]–[13], [20]–[25]. Second, the structure, biogenesis and processing of lncRNAs are very similar to that of protein-coding genes and indicate that most lncRNAs are produced from independent transcription units. For example, lncRNAs are typically transcribed by RNA polymerase II, under the control of diverse combinations of transcription factors that actively bind to promoters and enhancers, with canonical chromatin modifications [10]–[12], [26], [27]. LncRNA transcripts are also alternatively spliced, polyadenylated, and subject to other post-transcriptional modifications [10], [12], [28]. Third, lncRNA exons generally display a clear signal of purifying selection, implying structural and/or functional sequence constraint, albeit less stringent than on protein-coding exons [10], [12], [29]–[33]. Moreover, some lncRNA genes are evolutionarily ancient. A small but increasing number of loci orthologous to human lncRNAs have been identified in the mouse, and the origins of some human lncRNAs can be traced to the common ancestor of mammals, amniotes, or even vertebrates [9], [10], [14], [16], [34], [35]. Finally, a growing body of genetic and biochemical work on individual lncRNAs, as well as more systematic approaches to explore lncRNA function and their association with disease, point to crucial regulatory activities, notably in cell differentiation and embryonic development [for review: 7], [23], [36]–[44]. While the precise molecular functions of lncRNAs are still poorly understood, even less is known about their origin and evolution. Four non-mutually exclusive hypotheses have been proposed for the emergence of lncRNAs [6], [14]: (i) transformation of a protein-coding genes; (ii) duplication of another lncRNA; (iii) de novo origin from sequences previously untranscribed or devoid of exonic sequences; (iv) emergence from transposable element (TE) sequences. Individual examples illustrating each of these mechanisms have been described. For example, Xist, a lncRNA controlling mammalian X inactivation, originated in the eutherian ancestor from a mixture of exons derived from a decayed protein-coding gene [45] together with a variety of transposable elements (TEs) progressively accumulated and ‘exonized’ at this locus [46]. However, with the exception of a few emblematic and intensively studied lncRNAs such as Xist, the origins of most lncRNAs remain elusive. In one of the most systematic efforts to trace the origins of lncRNAs, Ulitsky et al. [14] found that a minority (∼15%) of zebrafish lncRNAs showed significant sequence similarity to another lncRNAs or protein-coding genes in the zebrafish genome. Likewise, Derrien et al. [10] reported that human lncRNAs rarely have extensive sequence similarity to each other outside of shared repetitive elements. Collectively these observations suggest that, in contrast to protein-coding genes, novel lncRNA genes do not commonly arise by duplication, but rather may emerge de novo from previously non-exonic sequences and/or from TEs. TEs occupy a substantial fraction of vertebrate genomes (e.g. at least half of the human genome [47], [48]) and are increasingly recognized as important players in the origin of functional novelties [for review: 49]–[52]. Several instances of TEs co-opted for cellular function on a genome-wide scale have been documented, notably as a source of cis-elements regulating adjacent host genes, such as promoters [53], [54], transcription factor binding sites [55]–[57], enhancers [58], [59] or insulators [60], [61]. TEs can also be ‘exonized’ into novel coding and non-coding exons [for review: 49], [62], [63]. As a source of non-coding exons, TEs have been shown to contribute substantially to untranslated regions [64]–[67] and to alternatively spliced exons of protein-coding genes [66]–[70], as well as to microRNA genes [71], [72]. In this study we provide evidence for the widespread involvement of TEs in the assembly, diversification, regulation, and potential function of lncRNAs. Results Datasets We focus on three vertebrate species -human, mouse and zebrafish- for which extensive lncRNA datasets are available (Table 1). Each set has been ‘manually’ curated based on a combination of bioinformatics and high-throughput genomics experiments, such as deep sequencing of polyadenylated RNAs (RNA-seq), chromatin state maps and cap-analysis of gene expression (CAGE) or paired-end ditags to determine transcript termini. For human, we primarily analyzed the most recent Gencode catalog of lncRNAs (v13) produced from 15 cell lines as part of the ENCODE project [10], [73], [74]. We replicated most analyses on another large set of lncRNAs assembled by Cabili et al. [9] from 24 human tissues and cell types. Importantly, the Gencode and “Cabili” sets differ slightly in the way they were curated and they are only partially overlapping [10]. Indeed we found that 64.9% of the Gencode v13 genes have no overlap with genes in the Cabili set, and conversely 47.3% of the Cabili genes have no overlap with the Gencode v13 set. While the Cabili set only contains “intergenic” (l i ncRNA) units (no overlap with known protein-coding genes), the Gencode catalog includes also “genic” lncRNAs, i.e. those overlapping or nested within protein-coding genes [10], Figure S1. Thus, these two sets may be viewed as complementary rather than redundant, acting as “biological replicates” for our study. For mouse, we primarily studied lincRNAs from Ensembl (release 70) and replicated some analyses on lincRNAs from adult liver tissue compiled by Kutter et al [16]. For zebrafish, we merged the sets of developmentally expressed lncRNAs from Pauli et al. [24] and lincRNAs from Ulitsky et al. [14] (see Methods for more details). 10.1371/journal.pgen.1003470.t001 Table 1 Number of genes and transcripts in studied datasets. Datasets Genes# Transcripts Human, Gencode v7 [10] 9,277 14,880 Human, Gencode v13 12,393 19,835 Human, lincRNAs, Cabili et al. (2011) [9] 8,263 14,353 Mouse, lincRNAs, Ensembl release 70 1,671 2,167 Mouse, lincRNAs, Kutter et al. (2012) [16] 293 293 Zebrafish [14], [24] 1,402 1,780 # For zebrafish gene annotation, see Methods. Other numbers are from the datasets themselves. A substantial fraction of vertebrate lncRNAs contain exonized TE sequences We inferred the TE content of lncRNAs by calculating the fraction of lncRNA transcripts with exons overlapping at least 10-bp of DNA annotated as TE by RepeatMasker (see Methods). We found that 75% of human (Gencode v13) lncRNA transcripts contain an exon of at least partial TE origin, which is considerably much higher than any other type of RNAs such as small ncRNAs (tRNAs, sno/miRNAs), pseudogenes, coding exons (less than 1%), as well as UTRs, the non-coding parts of mRNAs (Figure 1A). The median length of TE-derived fragments in human lncRNAs is 112 nucleotides and the average is 150 nucleotides. While the majority of human lncRNA transcripts are comprised of a relatively small percentage of TE-derived sequences, 3,789 out of 19,835 transcripts examined (∼19%) are composed of ≥50% of TE-derived sequences (Figure 1B). Similarly, 68.23% and 66.5% of mouse and zebrafish lncRNA transcripts, respectively, contain exonic sequences of at least partial TE origin (Figure 1A). 10.1371/journal.pgen.1003470.g001 Figure 1 TE occurrence in lncRNAs. See text, Methods and Table 1 for more details about lncRNA datasets. A. Percentage of transcripts with at least one exon overlapping with a TEs fragment (at least 10 bp). In red, lncRNAs (human = Gencode v13; mouse = both sets). Rest corresponds to human Refseq 57: in green, small non-coding RNAs (tRNAs and sno/miRNAs); in blue, protein-coding genes (pc genes) separated in exon types (coding and non-coding = UTRs); in black, pseudo = pseudogenes. B. Distribution of percentage of human lncRNA transcripts (Gencode v13) derived from TEs (more than 0% to more than 95%). The number of transcripts with more than 80% and more than 50% TE-derived DNA exons are indicated. Distribution is also shown for the subset of 36 studied lncRNAs presented in Table 2 and Table S2. To measure the total coverage of TE-derived sequences in lncRNA exons in each species, we intersected TE annotations from RepeatMasker (with a minimum overlap of 10 bp, see Methods) with the genomic coordinates of all lncRNA exons, and for comparison, with UTRs and coding exons of RefSeq protein-coding genes. The results show that, in all three species TE coverage is considerably higher for lncRNA exons than for protein-coding exons, but still lower than in the whole genome (Figure 2). The fraction of lncRNA exon sequence covered by TEs is also at least twice higher than in their UTRs. 10.1371/journal.pgen.1003470.g002 Figure 2 Coverage of different TE classes in genome, lncRNA, and protein-coding exons in human, mouse, and zebrafish. For genomes, total length (100%) corresponds to total length of assembly without gaps (human: 2,897 Mb. Mouse: 2,620 Mb. Zebrafish: 1,401 Mb). For lncRNAs, total length of genomic projection of all of exons are considered (human, Genc. = Gencode v13: 14.2 Mb. Human, Cabili set: 8.5 Mb. Mouse, Ens70 = Ensembl 70: 2.8 Mb. Mouse, Kutter: 0.15 Mb. Zebrafish: 2.3 Mb). For protein coding genes (pc genes), total length of CDS exons, 5′ and 3′UTR respectively are as follow: human, 30.9 Mb, 5.2 Mb, 24.6 Mb. Mouse: 30.5 Mb, 4.0 Mb, 21.6 Mb. Zebrafish: 19.1 Mb, 33.6 Mb, 12.5 Mb. Only pc genes from Refseq annotations with CDS and UTR features are considered (see Methods). Percentage of coverage of all TEs is indicated above bars. We noticed that the Cabili set [9], which consists exclusively of intergenic units (lincRNAs) shows greater TE coverage (35.1%; Figure 2) than the Gencode v13 set (28.9%; Figure 2), suggesting that intergenic lncRNAs may have a higher TE content than ‘genic’ lncRNAs (i.e. those overlapping protein-coding genes). Consistent with this idea, the TE coverage of intergenic lncRNAs in the Gencode v13 set is 31.8%, while genic lncRNAs are comprised of 25.9% of TE-derived sequences (Table S1). Thus, human lincRNA transcripts tend to be richer in TE sequences than genic lncRNAs. We wondered whether this trend could merely reflect a higher TE density in intergenic regions in general. It does not appear to be the case because the TE coverage of introns and surrounding sequences of Gencode intergenic lncRNAs is similar to that of protein-coding genes or genic lncRNAs (Table S1). These observations suggest that TEs are more prevalent in intergenic lncRNAs than in genic lncRNAs. A survey of individual human lncRNAs previously characterized in the literature recapitulates the omnipresence and high prevalence of TE sequences we detect in the ab initio lncRNA catalogs (Figure 1B, Table 2 and for an expanded version, Table S2). The presence of exonized TEs has been reported for some of these lncRNAs, such as XIST [46], UCA1 [75], HULC [76], PCAT-14 [77] and SLC7A2-IT1A/B [78]. But for the majority, there has been no previous mention of embedded TEs, even though some of these mature lncRNA transcripts are almost entirely composed of TE sequences. For example, the first three exons (out of four, i.e. ∼86% of the sequence) of the mature transcript of BANCR, which is involved in melanoma cell migration [79], are derived from a MER41 long terminal repeat/endogenous retrovirus (LTR/ERV) element (Figure 3A). The mature transcript of lincRNA-RoR, which has been shown to modulate the reprogramming of human induced pluripotent stem cells [41], is made from an assemblage of 6 different TEs together accounting for 2,057 nt (79.7%) of its length (Figure 3B) [see also ref. 7]. Importantly, the structures of BANCR and lincRNA-RoR transcripts have been validated by a combination of RACE and RT-PCR experiments and their function investigated by siRNA knockdowns and rescue experiments [41], [79]. These transcripts were independently retrieved and their structure accurately predicted in the Cabili and Gencode v13 sets, respectively. In mouse, Fendrr lincRNA, which has a very restricted pattern of expression in lateral mesoderm [80], initiates within a MTEa (ERVL-MaLR) and 4 different TEs account for 808 nt (33.7%) of its length (data not shown). In summary, our analyses point to an extensive contribution of TEs to the content of mature lncRNA transcripts, including many of those with established regulatory functions. 10.1371/journal.pgen.1003470.g003 Figure 3 Examples of lncRNAs with embedded TEs. Genomic DNA is represented as a grey line, transcripts are represented by a black line, with arrows showing sense of transcription and in grey boxes the exons of the mature transcript. TEs as colored boxes (orange-red: DNA TEs. Yellow: SINEs. Pink-purple: LTR/ERVs. Green: LINEs). Only TEs overlapping with lncRNA exons are represented. See also Table S2 for details of TEs in these lncRNAs. A. BANCR [79]. B. lnc-RoR [41]. Apes = gibbon, gorilla, orangutan, bonobo, chimpanzee, human. C. lnc-ES3 [43]. 10.1371/journal.pgen.1003470.t002 Table 2 TE content of known lncRNAs in human. Gene/ID# Range of % of TE based DNA of mature transcripts when applies TSS in TE: class (number of transcripts) polyA in TE: class (number of transcripts) number of transcripts: with TE/total PCAT14 99.6–99.96 LTR (2) LTR (2) 2/2 BANCR 86.4 LTR (1) - 1/1 Lnc-RoR 79.7 LTR (1) LINE (1) 1/1 PTCSC3 60.6 - LTR (1) 1/1 BACE1-AS 56.4 SINE (1) - 1/1 UCA1 51.8 LTR (1) - 1/1 HULC 45.7 LTR (1) - 1/1 LINC00458 (LncRNA-ES3) 45.3–57 LTR (3) - 3/3 ncRNA-7 (LINC00651) 41.1 lincRNA-p21 40.9 - SINE (1) 1/1 NEAT1 38.1 - - 1/2 PCAT1 37.1–81.7 - DNA (1) 2/2 AK023948 29.7 - - 1/1 KCNQ1OT1 29.5 - - 1/1 Tie-1AS 24.4–96.3 LINE (2) - 3/3 PTENP1 21 - LINE (1) 1/1 linc-CCDC90A-1 (LncRNA-ES1) 13.8 - LTR (1) 1/1 OIP5-AS1 (Cyrano) 12.5–64.7 - LTR (1); SINE (3); LINE (1) 10/10 SLC7A2-IT1 11.6–18.6 - LINE (2) 2/2 HOTAIRM1 9 - - 1/5 BIRC6 (megamind) 8.9 LINE (1) - 1/1 HAR1 7.2 - DNA (1) 1/1 BDNFOS (BDNF-AS) 6.4–71.1 - - 9/11 MEG3 5.6–47.1 SINE (2); LINE (1) SINE (6) 23/28 GAS5 5.3–40.9 - SINE (3) 23/29 Xist 5.3–17.4 - - 2/8 MALAT1/NEAT2 4.1–7.7 - - 2/3 ANRIL (CDKN2B-AS1, p15AS1, Mycn) 4–41.1 SINE (1) SINE (7); DNA (1) 16/17 TUG1 1.9–40.6 - LTR (1) 6/7 # Known lncRNAs with no detectable exonized TE are not shown, but include: HOTAIR, Zeb2AS1, TERC, PANDA, H19, LncRNA-ES2 and UNCA-RC. See Table S2 for an expanded version of this table and references. TE sequences in lncRNAs evolve under modest yet greater functional constraint than their non–TE sequences We next sought to evaluate the functional potential of TEs embedded in lncRNA transcripts. Several studies have reported that lncRNA exons show a signature of evolutionary constraint based on interspecies conservation [10], [12], [29], [30] as well as reduced nucleotide diversity in the human population [31]–[33] compared to randomly sampled regions of the genome or surrounding non-exonic sequences. Nonetheless, the level of constraint acting on lncRNA exons assessed through these analyses was much weaker than on protein-coding exons, presumably reflecting greater malleability of lncRNAs. To compare the level of selective constraint acting on TE-derived sequences to non-TE derived sequences in human lncRNAs (Gencode v13) and to various other types of genomic regions, we aggregated conservation scores per nucleotide calculated by phyloP across an alignment of 10 primate genomes (see Methods). As expected, we found that both TE and non-TE sequences in lncRNA exons were much less conserved than coding exons or UTRs of protein-coding transcripts (Figure 4A). Strikingly though, we found that TE sequences within lncRNA exons were significantly more conserved than either a size-matched random set of genomic regions or a neutral set of TE sequences residing in lncRNA introns (permutation test, p 0.5.). TEs promote the lineage-specific diversification of lncRNAs Because transposition represents a major source of lineage-specific DNA, we wanted to evaluate its contribution to the evolution of the vertebrate lncRNA repertoire. Our examination of TE-derived sequences in studied human lncRNAs reveals that many of these elements are restricted to primates (36.3% for Gencode v13, Figure S4), suggesting that TEs play an important role in the diversification and possibly the birth of primate-specific lncRNAs. Few of the human lncRNAs functionally characterized have identifiable orthologs in non-primate species, but Xist and cyrano provide solid examples of functional lncRNAs with ancient evolutionary origins. Xist is involved in X-chromosome inactivation and originated in the common ancestor of eutherian mammals [45], [46]. Previous in silico reconstruction of the Xist locus in the eutherian ancestor suggested that several TEs were already present at the dawn of the Xist gene and likely contributed to the assembly of the first functional Xist transcript [46]. Other TEs embedded in Xist exons are lineage-specific and therefore must have contributed to the diversification of the transcript during eutherian evolution. For example, a primate-specific FLAM_C element makes up nearly half (114 nt) of the first Xist exon in human (Table S2). cyrano is one of a small subset of zebrafish lncRNAs sharing significant sequence similarity and synteny with apparent orthologs in mouse and human [14]. Most of the sequence similarity between species is limited to a central region of the last exon (see PhastCons plot in Figure 9). In zebrafish embryos, cyrano is expressed in the nervous system and notochord and morpholino-mediated knockdowns followed by rescue experiments indicate that this lncRNA plays a role in neurodevelopment, a function possibly conserved in mammals [14]. We find that the conserved exonic region of cyrano is flanked by lineage-specific TEs embedded in this orthologous exon in each of the three species examined (Table 2, Figure 9). These examples illustrate how TEs can be incorporated long after the birth of lncRNAs to diversify their sequence in a lineage-specific fashion. 10.1371/journal.pgen.1003470.g009 Figure 9 Lineage-specific TE insertions in cyrano. Symbols and graphics are as in Figure 3. The structure of cyrano (lnc-oip5) [14] is based on coordinates of Gencode v13 transcript OIP5-AS1-001. Vertebrate PhastCons: peaks of sequence conservation across 46 vertebrate genomes displayed in the UCSC genome browser. Among functionally characterized human lncRNAs, we uncovered numerous instances where the TSS resides in primate-specific TEs (Table S2). In most of those cases, the TE provides the only identified TSS for that lncRNA locus, suggesting a pivotal role for these TEs in the biogenesis and most likely the birth of these lncRNAs during primate evolution. These include six of the eight known lncRNAs containing the largest TE amounts listed in Table 2, which all have their TSS located within the LTR of an ERV element. Intriguingly, these instances include two different lncRNAs that are highly expressed in human embryonic stem cells (ESCs) and have been experimentally shown to be implicated in the maintenance of ESC pluripotency: lncRNA-RoR [41] and lncRNA-ES3 [43]. The transcripts cloned for lncRNA-RoR and lncRNA-ES3 both initiate within LTR7/HERVH elements (Figure 3B and 3C). Furthermore, we found that these same LTR7 elements have donated the DNA binding sites for the ‘master’ transcriptional regulators of pluripotency NANOG, OCT4, and SOX2 mapped previously to the proximal promoter of lncRNA-RoR [41] (Figure 3B). Ng et al. [39] mapped two binding sites for NANOG in the promoter region of lncRNA-ES3 that we find to reside within the LTR7 driving this locus (Figure 3C). The contribution of LTR7 to the regulation of these lncRNAs in ESCs is consistent with two recent studies showing that TEs, and LTR/ERV elements in particular, play an extensive role in the primate-specific wiring of the core transcriptional network of human ESCs [57], [84]. In fact, Kunarso et al. [57] identified LTR7/HERVH as one of the most over-represented TE families seeding OCT4 and NANOG binding sites throughout the human genome. Our results indicate that this ERV family also contributed to the recruitment of primate-specific lncRNAs into the pluripotency network of human ESCs [see also ref. 7]. Some TEs confer lncRNAs the potential to form secondary structures Since lncRNAs act at the RNA level, we hypothesized that TEs may participate in the folding of lncRNAs into secondary structures, which could be important for their function. One prediction of this hypothesis is that lncRNAs with high TE content may fold into more stable structure than those with low TE content. To test this, we selected from the Gencode v13 set the top 100 lncRNAs with highest TE content and the top 100 lncRNAs with lowest TE content (see Methods) and compared the minimum free energy (MFE) of predicted secondary structures computed by the program randfold [85] for each of these individual lncRNAs. For each input sequence, randfold attributes a p-value to a predicted MFE by comparing it with a MFE obtained for the same sequence randomly reshuffled 99 times (See ref. [85] and Methods). The average p-value for high TE content lncRNAs was significantly lower than the one of low TE content lncRNAs (p = 0.0022, Wilcox rank sum test) (Figure 10A). The average length of the lncRNAs in the two datasets was also substantially different (913 nt and 1,913 nt for high and low TE content respectively), but there was no correlation between RNA length and p-value for the 200 lncRNAs examined (data not shown), ruling out a possible bias introduced by lncRNA length. Together these results indicate that TEs generally stabilize lncRNA structure in human, which supports the hypothesis that some of the TEs embedded in lncRNA exons contribute to the folding of lncRNAs into secondary structures. 10.1371/journal.pgen.1003470.g010 Figure 10 TE contribution to predicted lncRNA secondary structures. A. High and low TE content groups of 100 lncRNA were extracted from Gencode v13 set (TE content from 96.74% to 100% and from 0.49% to 2.27% respectively; see Table S7). P-values were calculated by Randfold and provide an indication of predicted secondary structure stability. The boxplot depicts the maximum, upper quantile, median, lower quantile and minimum value in a standard way. The mean of these 2 groups are significantly different by Wilcox rank sum test (p = 0.0022). B. Predicted secondary structures (RNAfold [115]) and compensatory mutations for two zebrafish lncRNAs containing ANGEL (DNA TEs) elements. In structures, TE derived regions are marked by solid line and base pairing probability by color spectrum (from 0 in violet to 1 in red). Zoom-in windows show part of stem with compensatory mutations: nucleotide substitution are boxed and the corresponding nucleotide found in ANGEL consensus are shown under/above actual RNA sequence. Sites of compensatory mutations are marked by asterisks and written p-values are adjusted by Bonferroni methods. To explore further this hypothesis, we studied a family of DNA transposons in zebrafish, called Angel, which occur in high copy numbers and are known to have the potential to form a stable stem-loop structure at the RNA level due to their long inverted repeats [86]. We reasoned that the incorporation of Angel elements in lncRNAs might in some case have conferred a functional benefit by increasing RNA stability. We identified 71 zebrafish lncRNAs containing exonized Angel elements. As expected, RNA folding programs predict that these lncRNAs have the potential to form a long stem-loop structure by intramolecular pairing of the Angel inverted repeats (see examples in Figure 10B). Furthermore, by comparing the sequence of these elements to that of their ancestral (consensus) progenitor, we identified two instances of Angel elements in lncRNAs where base substitutions in one of the arms of the predicted stem-loop structure were accompanied by compensatory substitutions on the other arm allowing the maintenance of base-pairing within the stem-loop structure (Figure 10B). To rule out the possibility that these substitutions occurred not at these loci, but prior to transposon insertion in a progenitor element that would have amplified or duplicated, we used BLAT [87] to search the zebrafish Zv9 genome assembly for paralogous Angel elements that might be sharing the same substitutions. In each case, we found that the compensatory substitutions we identified were unique to the Angel copies residing within the examined lncRNAs (data not shown), suggesting that these mutations occurred after transposon insertion. The probability that these compensatory substitutions would have occurred by chance alone in these two Angel elements is 0.001 and 0.036 after Bonferroni correction, respectively (see Methods). Furthermore, 12 of the 16 concerted mutations were from A/T to C/G base pairs, which is consistent with the idea that they increased the stability of the stem-loop structure. These data suggest that these Angel elements indeed fold into the predicted secondary structures in vivo and have been maintained over time by natural selection, plausibly for the proper function of the lncRNAs. To seek another, independent line of evidence for the involvement of TEs in forming secondary structures potentially important for lncRNA function, we next looked for sites of adenosine-to-inosine (A-to-I) editing in lncRNAs. This form of RNA editing is catalyzed by the ADAR family of adenosine deaminases that act on double-stranded RNA templates [88]. In humans, it has been reported that A-to-I RNA editing occurs predominantly within Alu elements embedded in the 3′ UTR of protein-coding transcripts [89]–[91]. This bias has been explained by the relatively high frequency of Alu elements in transcribed regions of the human genome, which often occur in inverted pairs and thereby can form long RNA duplexes providing templates for ADARs [92]. We used DARNED, a database of RNA editing sites in humans [93], to identify 2,941 A-to-I editing sites in mature lncRNA transcripts. As observed previously for mRNAs, most (82%) of the edited sites in lncRNAs occur within Alu elements, although we also found evidence of A-to-I editing within a wide range of TE types embedded in lncRNAs (Table 3 and Table S6). This may be explained by the fact that non-Alu TE sequences are much more frequent in lncRNAs than in mRNAs, even when UTRs are considered separately (Figure 2 and Figure S1). Indeed, we found that the density of edited sites within Alu, non-Alu TE, or non-TE sequences fall within the same order of magnitude in lncRNAs and UTRs (Table 3). In several cases individually examined, we found that editing sites in TE sequences map preferentially within regions of the lncRNA predicted to form stem-loop structures by virtue of the inclusion of two inverted copies of the same TE family in the lncRNA (see two examples in Figure 11). The finding that TE sequences, and in particular Alu elements, embedded in lncRNAs are frequent templates for A-to-I editing confirms that TEs are commonly engaged in intra- or inter-molecular base pairing interactions to form stable dsRNA structures. 10.1371/journal.pgen.1003470.g011 Figure 11 Long stem in two human lincRNAs (Cabili set) formed by inverted TEs. Two examples of heavily edited human lincRNA transcripts with editing sites located in TEs. RNA structures are predicted by RNAfold [115]. Nucleotide color in structures indicates base pairing probability (from 0 to 1). Inverted TE pairs are marked by solid lines, the arrow illustrating TE strand. The stem pair of TCONS_00017795 is composed by inverted Alu elements, while the structure of TCONS_0001109 is formed by 2 LTRs (MLT2B3). 10.1371/journal.pgen.1003470.t003 Table 3 Editing sites in exons. Total editing sites lincRNA 5′UTR 3′UTR Alu 1521 29 5297 other TE 162 0 121 nonTE 187 87 688 Editing sites per 100 kbp# lincRNA 5′UTR 3′UTR Alu 298 59 472 other TE 6.19 0 6.84 nonTE 3.23 1.75 3.17 # Editing sites density in Alu and non-Alu sequences are similar among non-coding transcript. The density of Alu in different sequences are about 10-3, while in other TE elements and non TE sequences the density is about 10-5. Discussion Recent high-throughput efforts to characterize the transcriptome of multicellular eukaryotes have uncovered thousands of lncRNA genes [5]–[7], [17]–[19]. While current lncRNA catalogs, such as those we used, are still far from exhaustive and almost certainly contain false positives, they indicate that the abundance and complexity of lncRNAs in mammalian genomes may rival or exceed that of protein-coding genes [9], [10], [13], [16]. The precise functions of the vast majority of lncRNAs remain to be determined, but evidence from genetic, genomic, and biochemical experiments, as well as analyses of sequence constraint, suggest that many lncRNAs perform important functions, most notably in the control of protein-coding gene expression during development and differentiation [for review: 5], [6], [7]. Despite the functional importance of some known lncRNAs, the basic mechanisms of lncRNA evolution have been largely unexplored. The few studies that have examined the evolutionary dynamics of lncRNAs paint a picture of evolutionary volatility, where large cohorts of lncRNAs seem to appear, disappear, or rapidly diversify, pointing to a potentially important role of lncRNAs in lineage-specific regulatory innovation [6], [10], [16]. Here we present a systematic assessment of TE contribution to the makeup, evolutionary origins, and regulation of vertebrate lncRNAs. While this paper was in its final stage of preparation, a study by Kelley and Rinn [94] analyzed in some detail the contribution of TEs to human and mouse multi-exonic intergenic lncRNAs. The two studies complement each other in that we analyzed different lncRNA sets, but arrive at the same general conclusion that TEs are important players in the composition and diversification of lncRNAs, highlighting a new way mobile elements have influenced genome evolution and shaped a likely crucial layer of genomic regulation. TEs are ubiquitous in vertebrate lncRNAs, but the type and amount of TE vary among species While TEs are seldom found in protein-coding transcripts (even in their UTRs, see Figure 1 and Figure 2), they are ubiquitous in lncRNAs of all three vertebrates examined (Figure 1A), accounting for a large fraction of total lncRNA sequence (Figure 2). Thus, high TE prevalence is probably a common characteristic of vertebrate lncRNA repertoires that distinguish them from mRNAs and smaller ncRNAs, such as tRNAs or microRNAs, which are typically TE-depleted (Figure 1A). We found that all major TE classes are found in lncRNAs in each of the three vertebrate species surveyed, and their relative abundance mirrors that of the entire genome (Figure 2). Nonetheless, in each species we identified TE families that were statistically enriched (up to 32 fold) in lncRNA exons relative to their coverage or density in the whole genome (Figure 7 and Figure S3). Interestingly, these over-represented families belong to different TE classes in the species examined, for example, LTR/ERV in human and mouse and DNA transposons in zebrafish (compare colors per species in Figure 7 and Figure S3). The predominance of DNA transposons in zebrafish is expected based on the prevalence of DNA transposons in this genome (see Figure 2, Figure 7 and Figure S1). However our results show that LTR/ERVs contribute disproportionally to lncRNAs in human and mouse, which is in agreement with the recent results reported by Kelley and Rinn [94]. Interestingly, human lncRNAs are mostly enriched for the ERV I subclass (alpharetroviruses), compared to mouse where ERV 2, ERV 3 or ERV K TEs are enriched (Figure 7 and Figure S3). ERV 1 subclass of elements is less abundant in the mouse genome [95] and strongly repressed in mouse ESCs [96], [97]. Therefore, it is not surprising that this type of retroviral elements do not contribute more to mouse lincRNAs. While LTR/ERV elements are also generally silenced in most human tissues, a subset of families is known to escape silencing and to become transcriptionally active in some tissues, cell types, or at certain developmental stages [54], [98]–[100]. These properties may derive from the intrinsic capacity of retroviruses to hijack host transcriptional activators in order to promote their own expression in a cell-type or developmentally restricted fashion [51], [52], [55]. For example, hundreds of ERV I elements recruit the pluripotency factors OCT4 and NANOG in human ESCs, but rarely do so in mouse ESCs [57]. This mechanism can readily explain why lncRNA-RoR and lncRNA-ES3 and hundreds of other lncRNAs associated with ERV I elements (such as LTR7/HERVH) are highly transcribed in human ESCs (Figure 3, Table 2) [see also ref. 94]. This trend is also globally apparent through the enrichment of LTR elements (including LTR7/HERVH) in 286 human lncRNAs upregulated in ES cells [annotations from Table S1, 10] (data not shown). In sum, the interspecific variations we observe in the coverage and type of TEs in lncRNAs likely reflect a variety of factors; both methodological, such as the breadth of cell types and tissues examined, and biological such as the abundance and intrinsic properties of certain TEs residing in the genome. “lncRNA first” versus “TE first”: Divergence or emergence? Two scenarios can explain the prevalence of TEs in lncRNAs. The first is that TE insertion in pre-existing lncRNAs has relatively little deleterious effect on lncRNA function allowing TEs to accumulate over time as waves of transposition break in the genome. We call this scenario the ‘lncRNA first’ model because it implies that the origin of the lncRNA predates the incorporation of TE(s) in their exons. In the second and not mutually exclusive scenario, the ‘TE first’ model, lncRNAs are assembled from TEs that inserted before the birth of the lncRNAs. Several observations and examples outlined below indicate that both models contribute to the pervasive occurence of TEs in lncRNAs. The “lncRNA first” scenario is supported by a comparison of the few lncRNAs known to be of relatively ancient origin, exemplified by Xist or cyrano, which have assimilated lineage-specific TE insertions sequentially during evolution (see Figure 9 and Table S2). Typically, these exonized TEs correspond to the most variable regions of the transcript sequence flanking more deeply conserved core sequences (see [14] and Figure 9). On a broader scale, we observe that TEs predominantly contribute to the last exon of lncRNAs (56.5% of TE amount, see Figure S5). The biased incorporation of TEs to the 3′ region of transcripts is also apparent for mRNAs, where exonized TEs are more abundant in 3′ UTRs (Figure 1, Figure 2 and Figure S5), as reported previously [65]–[67]. These data suggest that TE-derived sequences are preferentially acquired at the 3′ end of pre-existing transcripts, either because this region is more permissive to TE insertion and/or because TEs are somehow predisposed for this type of exonization events, for example owing to the presence of cryptic acceptor splice sites facilitating their capture [70], [101], [102]. In any case, this 3′ bias is consistent with the ‘lncRNA first’ model whereby TEs are secondarily acquired by existing lncRNAs. On the other hand, several observations support the ‘TE first’ model. First, we identified thousands of lncRNA transcripts that are mostly or entirely composed of TEs (Figure 1B). It is difficult to conceive that these lncRNAs would have emerged from ancestral non-TE regions later replaced or obliterated by secondary TE insertions. More likely, these lncRNAs were born from material providing by pre-existing TE insertions. In support to this idea, we identified 4,404 human Gencode v13 lncRNA transcripts with TE-derived TSS, with 1,777 of these (40.4%) derived from primate-specific TE families (Table S4). In addition, we found 2,213 human lncRNA transcripts whose first exons are entirely derived from TEs, and 965 of these (43.6%) are derived from primate-specific TE families (Table S4). These values are very similar when only genes with a unique TSS are considered and we retrieved comparable numbers in the Cabili set (Table S4). Since these TEs provide the only TSS assigned for these transcripts, we propose that these lncRNAs were born from the transcriptional activity brought upon TE insertion in the genome. Interestingly, 36.8% (857/2,331) of the TE-derived unique TSS map within LTR/ERV elements, while this type of elements account for only 8% of all TEs in the human genome (see Figure 2). Thus, it appears that the tissue-specific transcriptional activity of LTR/ERV elements [52], [54], [100] represents a major force driving the birth of lncRNAs. These data also imply that a substantial fraction of human lncRNAs are of recent origin, because ∼40% of TEs driving human lncRNAs are primate-specific and some are even restricted to hominoids (e.g. Figure 3A and 3B, Table S2). In summary, our data suggest that, in some instances, TE insertion events have been a source of diversification of ancestral lncRNAs, while in others TE insertions have triggered the emergence of brand new lncRNAs during evolution. In order to better quantify the relative importance of either process to lncRNA evolution, it will be necessary to infer systematically the age of lncRNAs using a comparative RNA-seq approach [16]. TE–mediated regulation of lncRNA genes It has been extensively documented that mammalian TEs represent an abundant source of cis-regulatory sequences driving or modulating the expression of adjacent protein-coding genes [reviewed in 49], [56]. Our study provides evidence that TEs located in the vicinity of lncRNAs may also frequently contribute to the transcriptional regulation of these genes. As discussed above, LTR/ERV elements appear to make a disproportionate contribution to lncRNA regulation relative to other TE types and in some cases they may be solely responsible for the cell-type specificity of lncRNA expression. This is exemplified by lncRNA-RoR whose transcription in hESCs is driven by a LTR7/HERVH element occupied by the pluripotency factors OCT4, NANOG and SOX2 (Figure 3C and [41], [94]). Thus, much like LTR/ERV elements have been implicated in the wiring of protein-coding genes into specific regulatory networks [55], [57], [59], [84], they have also recruited lncRNAs serving important developmental function, notably in the pluripotency network [41], [43], [94]. Possible functions of TEs embedded in lncRNAs Perhaps the most pressing question to address in the future is to what extent TEs may contribute to the function of lncRNA and how? Our analysis shows that TEs embedded in lncRNAs frequently supply sequences and signals essential for the transcription (e.g. TSS) and processing (e.g. splice, polyA sites) of the lncRNAs (Figure 5). However it does not prove that TE sequences per se are indispensable for lncRNA function, if such function even exists. Many studies have used various approaches and statistics to show that lncRNA exons, as a whole, display weak but significant signals of purifying selection suggesting that at least a fraction of lncRNA sequences is subject to functional constraint detectable at the primary DNA level [10], [12], [29]–[33]. Our analysis confirms the existence of a signal of purifying selection acting on human lncRNA exons, but more importantly we observe that this signal is higher in TE-derived than in non-TE derived lncRNA sequences (Figure 4A) suggesting that a subset of TE sequences in lncRNAs are structurally or functionally constrained. TE-derived sequences could serve as the functional elements of lncRNAs in numerous ways. For example, TE sequences might provide interaction interfaces with proteins involved in post-transcriptional or transcriptional regulation, such as the chromatin modifiers often found in complex with lncRNAs [37], [103]. Their inclusion may also provide opportunities for base-pairing interaction with single-stranded DNA or RNA containing similar repeats in inverted orientation. Such duplexes might act as a platform to recruit protein effector complexes to genomic or RNA targets. For example, Alu elements embedded within several human lncRNAs form a group called 1/2sbs-RNAs that base-pair with complementary Alu elements located in the 3′-UTR of several protein-coding transcripts to form duplexes creating a binding site for the Staufen1-mediated RNA decay machinery, which in turn promote post-transcriptional repression of the targeted mRNAs [104]. Given the abundance of Alu and other high copy number TEs in lncRNAs, such trans-regulatory effects may be widespread and affecting a large number of mRNAs containing complementary TEs in their UTRs. It was also shown recently that a B2 SINE embedded in a mouse lncRNA antisense to Uchl1 is required for post-transcriptional up-regulation of UCHL1 protein synthesis, an activity that can be transferred to an artificial antisense green fluorescent protein transcript containing the B2 SINE element [105]. We identified 361 mouse lncRNAs containing B2 SINEs (16.7%; see Tables S5 and S9), raising the possibility that these elements confer similar post-transcriptional regulatory activity to other lncRNAs. Finally, another recent study identified a point mutation associated with a lethal form of infantile encephalopathy within a primate-specific LINE-1 retrotransposon transcribed as part of a lncRNA in the human brain [78]. The precise function of the LINE-1 element in this lncRNA is unknown, but knockdown of the lncRNA resulted in increased neuronal apoptosis, an effect consistent with the encephalopathy phenotype. Interestingly, the point mutation detected in affected individuals was predicted to destabilize a secondary structure in the corresponding lncRNA, suggesting that the LINE-1 element may contribute to lncRNA folding that is important for its function in the brain. Similarly, we identified several instances in zebrafish and in human where TEs embedded in lncRNAs are predicted to be involved in the formation of stem-loop structures that have been maintained in evolution through compensatory mutations and therefore are likely to be functionally significant. We also found that these structures often lead to RNA editing of lncRNAs, which to our knowledge is a novel observation that may be relevant to the function of some lncRNAs [88], [92]. We also show that human lncRNAs fold into more stable structure than those with low TE content, suggesting that these individual examples of TEs apparently co-opted for the cellular function of lncRNAs likely represent only the tip of a large iceberg. Future work is bound to unravel a variety of mechanisms through which TEs embedded in lncRNAs have become involved in regulating the expression of vertebrate genomes. Conclusions There is growing evidence that vertebrate genomes contain a large number of long non-coding RNA genes (lncRNAs) that play important gene regulation roles, however, remarkably little is known about the origins of these genes. Our study reveals that TEs, through their capacity to move and spread in genomes in a lineage-specific fashion, as well as their ability to introduce regulatory sequences upon chromosomal insertion, represent a considerable force shaping the lncRNA repertoire of human, mouse and zebrafish. These results suggest that the apparent paucity of ancient lncRNA genes may be explained in part by rapid turnover mediated by lineage-specific TEs and imply that the regulatory networks in which lncRNA genes act may be rapidly diverging between species. Methods lncRNA datasets The datasets used in this study are as follow: human, Gencode release 13 (from ftp://ftp.sanger.ac.uk/pub/gencode) and Cabili et al. (2011) [9]. Mouse, Ensembl release 70 (ftp://ftp.ensembl.org/pub/release-70/gtf/mus_musculus/) and Kutter et al (2012) [16], both sets filtered to keep only intergenic lncRNAs. Coordinates from Kutter et al. were converted from mm9 to mm10 using the liftover tool from UCSC (http://genome.ucsc.edu/cgi-bin/hgLiftOver?hgsid=325693955). Zebrafish sets are from Pauli et al. (2012) [24] and Ulitsky et al. (2011) [14]. To limit redundancy, in case of overlap of exons between transcripts of the two sets, only transcripts from Pauli et al. (2012) were kept. Additional descriptors of the datasets are provided in Table 1. TE annotation TE annotations used in this study are obtained from the outputs of the RepeatMasker (RM) software [106] produced for the following genome assemblies: human, hg19 assembly, RM v.330, repbase libraries 20120124, from RM website (http://www.repeatmasker.org/species/homSap.html). Mouse, mm10 assembly, RM v.330, repbase libraries 20110920, from UCSC website (http://hgdownload.soe.ucsc.edu/goldenPath/mm10/bigZips/). Zebrafish, danRer7: RM v.329, repbase libraries RB20090604, from UCSC website (http://hgdownload.cse.ucsc.edu/goldenPath/danRer7/bigZips/). These RM outputs were filtered to remove non-TE elements (Low Complexity, Satellites, Simple Repeats and ncRNA). For mouse, MutSatRep1, CYRA11_Mm and YREP_Mm are also removed. To minimize multiple counting of single TE copies artificially fragmented in the RepeatMasker outputs we merged consecutive pieces of the same TE separated by less than 10 nt. Counts of TEs in transcripts The TE content of lncRNA transcripts (datasets described above) and human RefSeq 57 ncRNAs (22,486 in total), pseudogenes (13,430), CDS and UTRs (20,848 protein coding genes) was determined by intersecting these sets with each species' TE annotations (described above) using the ‘Table Browser’ at the UCSC Genome Bioinformatics Site (http://genome.ucsc.edu/index.html) [107]. Only overlaps of minimum 10 bp were kept. Coverage of TEs in exons and surrounding sequences Protein-coding gene (pc genes) models were filtered to retain only those with 5′ and 3′ UTRs, from following releases: human, Refseq 49 (hg19, gtf file from UCSC genome browser); mouse, Refseq 57 (mm10, gtf file from UCSC genome browser); zebrafish, Ensembl 68 (danRer7). All nucleotide amounts correspond to genomic amount. Introns and upstream or downstream intergenic regions were processed through Galaxy [108]–[110] to remove all RefSeq genes exons (CDS and UTRS: Refseq 51 for human and zebrafish, Refseq 57 for mouse) as well as lncRNA exons of the datasets considered. Intergenic sequences (upstream or downstream, up to 10 or 1 kb) correspond to the longest fragment between TSS or polyA and another feature (RefSeq entries as well as lncRNA exons of the dataset considered). These sets (exons, introns, intergenic sequences) were then joined in Galaxy with filtered RepeatMasker outputs described above keeping only fragments with at least 10 nt of overlap, to calculate TE coverage of exons. See Tables S7, S8, S9, S10, S11 for transcripts TE content data. Conservation PhyloP By comparing their PhyloP scores across an alignment of 10 primate genomes, the conservation of human (Gencode v13) TE-derived lncRNA exonic segments was compared to non-TE derived lncRNA segments, RefSeq 57 5′- and 3′-UTRs, protein-coding exons and a set of random genomic fragments size-matched to the TE-derived lncRNA segments. We also generated a set of TE-derived lncRNA intronic segments, non overlapping with splicing sites and corresponding to inactive chromatin to obtain a most neutral set to compare with exonic TE-derived lncRNA segments [32] (all annotated chromatin marks from 9 cell lines were subtracted: GM12878, H1-hESC, HMEC, HSMM, HUVEC, HepG2, K562, NHEK, NHLF; ENCODE version Jan. 2011). Precompiled PhyloP scores were obtained from the ‘phyloP46wayPrimates’, ‘phyloP46wayPlacental’, and ‘phyloP46wayAll’ tracks available from the UCSC Genome Bioinformatics Site (http://genome.ucsc.edu/index.html) [107] and intersected with gene annotations using bedtools (http://code.google.com/p/bedtools/) [111]. Boxplots were made in R (http://www.r-project.org). Statistical test used: permutation test with 1000 permutations were performed in R. TE contribution to functional features: Exon counts TEs were not assigned a strand allowing them to overlap genomic features on either strand. TEs found in a genomic feature were classified based on their position in the feature, as schematized in Figure 5A. Both lncRNA and protein-coding genes were filtered before both the random and non-random analyses. In case of multiple splice forms a random mRNA was kept. Additionally protein coding genes that did not have both a 5′ UTR and 3′ UTR were excluded from the analysis. Sets of protein-coding genes are as follows: human, Refseq release 49, mouse, Refseq release 46, zebrafish, Ensembl release 68. For the random sets, all TEs were shuffled within chromosomes (excluding gaps) while preventing TE overlap. This process was repeated 5,000 times for each set, using a custom perl script (see http://www.yandell-lab.org/publications/index.html). The standard error for the random sets across all categories (Figure 5A) always plateaued before 1,000 replicates (data not shown). The probability of observing the non-random counts was calculated using the random sets. The p-value represents number of times a lower category count was observed in the random set out of 5,000 replicates. With the exception of ‘exonized’, ‘TSS’ and ‘polyA’ categories in mouse (p-values = 1, 0.001 and 0.298 respectively) and ‘exonized’ category in zebrafish (p-value = 0.001), the p-values were systematically 1 or the 25 most over represented are shown. A. Human, set from Gencode v13. B. Human, set of Cabili et al. (lincRNAs). C. Mouse, lincRNAs from Ensembl. D. Zebrafish. (TIF) Click here for additional data file. Figure S4 Amount of lineage specific and ancient TEs in human lncRNAs and protein-coding genes genomic environment. G: genome. See Methods “Coverage of TEs in exons and surrounding sequences” for details on sets. Ancient TEs correspond to TEs shared between placental mammals (Eutherians). Gencode v13 set for lncRNA. (TIF) Click here for additional data file. Figure S5 Relative amount of TEs depending on exon type. TE contribution means that 100% is the total coverage of a given class of TEs. For example, ∼20% (19.5) of TE amount is in first exon for lncRNAs, whereas for pc genes it is 6.4% (“All” TEs). lncRNAs are Gencode v13 set. A. Coverage. B. Counts. (TIF) Click here for additional data file. Table S1 TE coverage and TE counts in genic and intergenic human lncRNAs and surrounding regions. (XLSX) Click here for additional data file. Table S2 Detailed TE content of known lncRNAs presented in Table 2. (XLSX) Click here for additional data file. Table S3 Numbers of exons overlapping with TEs (data corresponding to Figure 5). (XLSX) Click here for additional data file. Table S4 Counts of functional features provided by ancient or primate TEs in human. (XLSX) Click here for additional data file. Table S5 Editing sites in Cabili lincRNA set. (XLSX) Click here for additional data file. Table S6 361 mouse lincRNAs with B2 SINEs elements (ENSEMBL release70). (XLSX) Click here for additional data file. Table S7 Details of TE content of human Gencode v13 lncRNAs. (XLSX) Click here for additional data file. Table S8 Details of TE content of human lincRNAs from Cabili et al. (2011). (XLSX) Click here for additional data file. Table S9 Details of TE content of mouse lincRNAs from ENSEMBL release 70. (XLSX) Click here for additional data file. Table S10 Details of TE content of mouse lincRNAs from Kutter et al. (2012). (XLSX) Click here for additional data file. Table S11 Details of TE content of zebrafish lincRNAs. (XLSX) Click here for additional data file.
- Record: found
- Abstract: found
- Article: not found
A Microhomology-Mediated Break-Induced Replication Model for the Origin of Human Copy Number Variation
P Hastings, Grzegorz Ira, James R. Lupski (2009)
Chromosome structural changes with nonrecurrent endpoints associated with genomic disorders offer windows into the mechanism of origin of copy number variation (CNV). A recent report of nonrecurrent duplications associated with Pelizaeus-Merzbacher disease identified three distinctive characteristics. First, the majority of events can be seen to be complex, showing discontinuous duplications mixed with deletions, inverted duplications, and triplications. Second, junctions at endpoints show microhomology of 2–5 base pairs (bp). Third, endpoints occur near pre-existing low copy repeats (LCRs). Using these observations and evidence from DNA repair in other organisms, we derive a model of microhomology-mediated break-induced replication (MMBIR) for the origin of CNV and, ultimately, of LCRs. We propose that breakage of replication forks in stressed cells that are deficient in homologous recombination induces an aberrant repair process with features of break-induced replication (BIR). Under these circumstances, single-strand 3′ tails from broken replication forks will anneal with microhomology on any single-stranded DNA nearby, priming low-processivity polymerization with multiple template switches generating complex rearrangements, and eventual re-establishment of processive replication.
- Record: found
- Abstract: found
- Article: not found
The evolution of Fox genes and their role in development and disease.
Sridhar Hannenhalli, Klaus Kaestner (2009)
The forkhead box (Fox) family of transcription factors, which originated in unicellular eukaryotes, has expanded over time through multiple duplication events, and sometimes through gene loss, to over 40 members in mammals. Fox genes have evolved to acquire a specialized function in many key biological processes. Mutations in Fox genes have a profound effect on human disease, causing phenotypes as varied as cancer, glaucoma and language disorders. We summarize the salient features of the evolution of the Fox gene family and highlight the diverse contribution of various Fox subfamilies to developmental processes, from organogenesis to speech acquisition.
Author and article information
Journal
Journal ID (nlm-ta): Curr Genomics
Journal ID (iso-abbrev): Curr. Genomics
Journal ID (publisher-id): CG
Title:
Current Genomics
Publisher:
Bentham Science Publishers
ISSN
(Print):
1389-2029
ISSN
(Electronic):
1875-5488
Publication date
(Print):
April
2015
Publication date
(Electronic):
April
2015
Volume: 16
Issue: 2
Pages: 107-116
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Author notes
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] Address correspondence to this author at the Dept. of Molecular & Human
Genetics, Baylor College of Medicine, One Baylor Plaza, Rm. R809,
Houston, TX 77030, USA; Tel: (713) 798-5370; Fax: (713) 798-7418;
E-mail:
pawels@
123456bcm.edu
Article
Publisher ID: CG-16-107DOI: 10.2174/1389202916666150122223252
PMC ID: 4467301
PubMed ID: 26085809
SO-VID: 1481f9c1-70c9-4a33-bff9-227dd7c8c901
Copyright © © 2015 Bentham Science Publishers
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This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
History
Date
received
: 19
November
2014
Date
revision received
: 9
January
2015
Date
accepted
: 21
January
2015
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ScienceOpen disciplines: Genetics
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ScienceOpen disciplines: Genetics