Mol. Cells 2017; 40(4): 262-270
Published online March 21, 2017
https://doi.org/10.14348/molcells.2017.2295
© The Korean Society for Molecular and Cellular Biology
Correspondence to : *Correspondence: khs307@pusan.ac.kr
MicroRNAs (miRNAs) are single-stranded, small RNAs (21?23 nucleotides) that function in gene silencing and translational inhibition via the RNA interference mechanism. Most miRNAs originate from host genomic regions, such as intergenic regions, introns, exons, and transposable elements (TEs). Here, we focused on the palindromic structure of medium reiteration frequencies (MERs), which are similar to precursor miRNAs. Five MER consensus sequences (MER5A1, MER53, MER81, MER91C, and MER117) were matched with paralogous transcripts predicted to be precursor miRNAs in the horse genome (equCab2) and located in either intergenic regions or introns. The MER5A1, MER53, and MER91C sequences obtained from RepeatMasker were matched with the eca-miR-544b, eca-miR-1302, and eca-miR-652 precursor sequences derived from Ensembl transcript database, respectively. Each precursor form was anticipated to yield two mature forms, and we confirmed miRNA expression in six different tissues (cerebrum, cerebellum, lung, spleen, adrenal gland, and duodenum) of one thorough-bred horse. MER5A1-derived miRNAs generally showed significantly higher expression in the lung than in other tissues. MER91C-derived miRNA-5p also showed significantly higher expression in the duodenum than in other tissues (cerebellum, lung, spleen, and adrenal gland). The MER117-overlapped expressed sequence tag generated polycistronic miRNAs, which showed higher expression in the duodenum than other tissues. These data indicate that horse MER transposons encode miR-NAs that are expressed in several tissues and are thought to have biological functions.
Keywords medium reiteration frequency transposon, MicroRNA, palindromic structure, thoroughbred horse
MicroRNAs (miRNAs) are non-coding small RNAs (21–23 nucleotides) that play a key role in inhibiting target genes by binding their 3′ UTRs, which are complementary to the miR-NAs’ seed regions (Bartel, 2009; Chen and Rajewsky, 2007; Shukla et al., 2011). These sequences are known to influence various biological processes in numerous animals and plants (Bartel, 2009). miRNAs undergo a series of changes from the transcript stage to maturity. First, primary miRNAs are transcribed by polymerase II in the nucleus (Lee et al., 2004). Next, they are cleaved into precursor miRNAs (70 nucleotides), with a double-stranded hairpin structure, by Drosha. Finally, precursor miRNAs are exported into the cytoplasm and converted to mature miRNAs by Dicer (Lund and Dahlberg, 2006). In a genome, miRNA-encoding genes are located in various characterized regions such as intergenic regions, exons, introns, and transposable elements (TEs) (Piriyapongsa et al., 2007). TEs contribute to miRNA sequences in various ways. For example, two adjacent TEs, as well as genomic sequences and one TE, yield one precursor miRNA. Palindrome sequences containing TEs such as miniature inverted repeat transposable elements (MITE) and medium reiteration frequency (MER) generate one precursor form and two mature miRNAs (Ahn et al., 2013; Yuan et al., 2010). Two mature miRNAs are derived from one precursor miRNA and present asymmetric expression or selective expression patterns (Hutvagner, 2005; Ruike et al., 2008).
MERs are non-autonomous mammalian DNA transposons (Jurka et al., 1996). A total of 240,000 copies of MERs are present in humans, accounting for 2.4% of the human genome (Lander et al., 2001). Most of these sequences were fossilized, such as long terminal repeats (LTRs) or endogenous retroviruses (ERVs) (Coffin, 2004; Smit, 1993), although some cause diseases in host organisms (Balada et al., 2010; Lamprecht et al., 2010). The genomes of primates, rodentia, and lagomorpha contain MER repeats inserted before the
The reference genome sequence for horse was determined in 2007, and the horse genetic map has been available since 2009 (Wade et al., 2009). The horse genome contains numerous genetic traits linked to racing ability, such as single-nucleotide polymorphisms (SNPs), specific transcripts, and copy number variation (CNV) (Doan et al., 2012; Hill et al., 2010; Petersen et al., 2013). Based on the horse reference genome sequence, a total of 1397 horse miRNAs have been identified in the miRBase database (Kozomara and Griffiths-Jones, 2014). Subsequently, the functional study and characterization of horse miRNAs could be available (Kim et al., 2014; Zhou et al., 2009). However, horse miR-NAs have not been as relatively well studied as other genetic traits, such as SNPs or CNV (Doan et al., 2012; Gim et al., 2015; Hill et al., 2010).
Many identified expressed sequence tags (ESTs) are available in databases, and ESTs can encode miRNAs and miRNA clusters (Smalheiser, 2003). The miRNA cluster transcripts are formed from ESTs, which show polycistronic expression patterns containing multiple, distinct loops separated by Drosha and Dicer. Forty-eight percent of all human mature miRNAs are derived from primary miRNAs of polycistronic transcripts (Altuvia et al., 2005). A well-known miRNA cluster, previously known as
MER consensus sequences that form palindromic sequences were downloaded from the Repbase database version 21.05 of the Genetic Information Research Institute (
MER consensus sequences forming palindromic sequences were predicted by RNAfold (
The animal protocol and sample extraction method in this study were reviewed by the Pusan National University-Institutional Animal Care and Use Committee (PNU-IACUC) for the ethical procedures and scientific care (approval number PNU-2013-0411). Small RNA from 100 mg of different tissues from one thoroughbred horse, sacrificed for biological research, was extracted from the cerebrum, cerebellum, lung, spleen, adrenal gland, and duodenum, using Hybrid-R™ miRNA (GeneAll Biotechnology Co., Ltd., Korea) according to the manufacturer’s protocol. Hybrid-R™ kit is available to simultaneously isolate large RNA and small RNA, and to separate total RNA and small RNA by using small RNA specific binding column tube. In order to exclude short RNA sequences from degreaded longer transcripts, a portion (2–3μl) of total RNA was loaded onto an agarose gel, then only detected 28S and 18S samples were used.
Next, the turbo DNA-free™ kit (Ambion, USA) was used according to the manufacturer’s protocol to remove DNA contamination from the small RNAs. A portion (2–3 μl) of isolated small RNA was loaded onto an agarose gel, and only samples in which small-RNA (< 200 nt) was detected were used in subsequent experiments. We measured the small RNA concentrations, which ranged between 130–180 ng/μl in the samples. Each small RNA sample was quantitated to 500 ng using a NanoDrop® ND-1000 UV–vis Spectrophotometer (NanoDrop Technologies, USA). After quantifying small RNA, adenine was added to the small RNA transcripts at their 3′ ends, using poly (A) tailing kits (Ambion). Samples were incubated in E-PAP buffer at 37°C for 30 min for the poly (A) tailing reactions. After the reactions, we performed reverse transcription reactions using Moloney murine leukemia virus reverse transcriptase with an RNase inhibitor (Promega, USA) at an annealing temperature of 42°C. To select target miRNAs in the reverse transcription reactions, we used an oligo-dT adaptor (5′-CTGTGAATGCTG CGACTACGAT-18dTs-3′) according to the methods of previous study (Fu et al., 2006). The miRNA sequence is used as forward primer, and adaptor sequences excluded poly T in the 3′ terminal is used as reverse primer (
RT-PCR was conducted in a thermocycler (Eppendorf, Germany) and SYBR green quantitative RT-PCR was conducted using a Roter Gene Q (Qiagen, Germany). Each reaction was performed in a final volume of 20 μl containing 1 μl of cDNA sample as a template, 10 μl of Quantitect® SYBR® Green PCR MasterMix (Qiagen), 7 μl of nuclease-free water, and 1μl each of sense primer and antisense primer (each 10 pmol). RT-PCR of genes was performed at 94°C for 5 min, 35 cycles of 94°C for 30 s, 55°C for 30 s, and 72°C for 30 s, and a final elongation at 72°C for 7 min. Next, quantitative RT-PCR of genes was performed at 94°C for 15 min, 55 cycles of 94°C for 10 s, 55°C for 15 s, and 72°C for 15 s using the primers shown in
Some of consensus sequences of MER have palindromic structures, which are similar to those of precursor miRNAs. A total of 238 MER elements were screened from the Repbase database, and 24 MER elements were identified to have palindromic structures. In the 24 MER elements, only five MER-derived mature miRNAs were confirmed as RT-PCR (
To confirm that the mature miRNAs were derived from MER transposons, all mature miRNAs were extracted from the tissues of one thoroughbred horse. Adenine and adaptor sequences were added to the 3′ end of each mature miRNA (see “Materials and Methods”). Next, RT-PCR was performed to identify the expression of 24 MER transposon-derived miRNA, and only five miRNAs were detected. Then, we performed qRT-PCR of five miRNAs in the six tissues of one horse (Cerebrum, Cerebellum, Lung, Spleen, Adrenal gland, Duodenum), and MER-derived miRNA showed tissue-specific expression patterns. As shown in Fig. 2, two mature miRNAs derived from one primary miRNA showed similar expression patterns. The MER5A1-derived ENSECAT000000 29718 transcript yielded two miRNAs showing lung-dominant expression patterns than other tissues (Fig. 2A). The MER53-derived ENSECAT00000027640 transcript yielded two miRNAs showing different expression patterns between the -5p and -3p forms. The -5p miRNA showed higher expression value in the cerebrum and duodenum than in other tissues, but no significant expression patterns were detected (Fig. 2B, left). The -3p miRNA showed dominant expression patterns in the duodenum, compared to cerebrum, cerebellum, lung, and adrenal gland (Fig. 2B, right). The MER81-derived ENSECAT00000029221 transcript yielded two miRNAs, that were no significant expression patterns (Fig. 2C). The MER91C-derived ENSECAT00000027964 transcript yielded two miRNAs, which showed different expression patterns. The -5p miRNA was enriched in the duodenum than other tissues (Fig. 2D, left), whereas the -3p miRNA was enriched in the cerebrum than cerebellum, lung, and duodenum (Fig. 2D, right).
We confirmed that the MER117 sequence overlapped with horse EST of BM734541.1, the transcript of which was predicted to contain many palindromic structures. The BM734541.1 transcript was predicted to generate five precursor forms of polycistronic miRNAs. As shown in Fig. 3, the expression patterns of five different mature forms of the BM734541.1 were confirmed. We detected these mature forms in six different tissues, indicating that total mature forms except EST-2-derived mature form have significantly low expression patterns in the cerebellum than adrenal gland (Figs. 3A, 3C–3E). Interestingly, EST-1-derived mature form was dominantly expressed in other tissues than cerebellum, except cerebrum (Fig. 3A). Only adrenal gland had higher expression pattern than cerebellum in the EST-4-derived mature form (Fig. 3D). The location of mature miR-NAs in the BM734541.1 transcript is indicated for each corresponding region in Fig. 3F.
MER-sequences are non-autonomous DNA transposons distributed throughout the host genome in a fossilized state. According to pre-RepeatMasking data, the horse genome possesses 3.61% DNA transposons containing MER-sequences (Smit et al., 2004). MER sequences can form palindromic stem-loop structures, which are similar to miR-NA precursor sequences. This suggests a mode for miRNA sequence formation (Ahn et al., 2013; Gim et al., 2014). To date, miRNAs that are derived from repetitive elements have been identified in the genomes of various species (Nozawa et al., 2010; Yuan et al., 2011). In this study, we identified 13 MER-derived miRNAs and confirmed their expression in six tissues of one thoroughbred horse.
During miRNA maturation, two mature miRNAs are processed from one precursor miRNA. According to previous studies, the two mature miRNAs are expressed via asymmetric selection of each miRNA strand by the processing of precursor miRNA (Hutvagner, 2005; Ruike et al., 2008). In this study, we also observed that two miRNAs presented different expression patterns. In the MER5A1-derived miRNAs, similar expression patterns were observed for the two miR-NAs from one precursor miRNA (Fig. 2A), whereas the MER53- and MER91C-derived miRNAs showed slightly different expression patterns (Figs. 2C and 2D). MER5A1-derived miRNAs showed dominant expression in the lung; thus, it may be a good target for future studies on exercise, cardiopulmonary fitness, or any lung-related process (Fig. 2A). As a part of brain, cerebrum and cerebellum are related to central nervous system (CNS). However, they expression patterns have different in MER81 and MER91C-derived miRNAs (Figs. 2C and 2D). Cerebrum is most important region of the CNS, and controls all voluntary operation in the body. Thus, these different expression patterns could be related to the cerebrum-specific roles in the CNS. Moreover, these results could provide a clue for cognitive function of the horse (Lein et al., 2007). Spleen is related to immune response, and adrenal gland produces a variety of hormones. In our data, spleen and adrenal gland have lower expressed patterns. Therefore, these two organs provide the important points in the immune and internal secretion pathways in the organisms (Nishimura and Naito, 2005). Most chemical digestion takes place in duodenum, therefore MER53-derived ENSECAT00000027640-3p miRNA, MER91C-derived ENSEC AT00000027964-5p miRNA and BM734541.1-derived miR-NAs could be crucial roles in digestion (Fang et al., 2006). Our six tissue expression patterns could be involved in exercise, cognition, and the physiological pathway.
MER5A1-derived miRNA precursor sequences were well-matched with eca-miR-544b (Table 2); therefore, they may be good targets for future studies on exercise and cardio-pulmonary fitness. miR-544b has, to date, been identified in only three species (human, cow, and horse), and additional studies are required to determine the species- or tissue-specific roles of miR-544b. MER53 has been predicted to encode miR-1302 (Yuan et al., 2010). MER53-derived miR-NAs did not show consistent expression patterns among their families. The miR-1302 subfamily derived from MER53 showed tissue-specific expression and identified in human, chimpanzee, orangutan (Kozomara and Griffiths-Jones, 2014). Therefore, it may be interesting to analyze their functions and evolutionary mechanisms in various animals in further studies. MER81-derived miRNAs have no significantly expressed patterns in all tissues to the other miRNAs. Three of four MER81-derived precursor sequences were not matched with previously identified precursor sequences. Although only one sequence matched with eca-miR-8990, its E-value was not significant. According to the latest version of miRBase (version 21.0), a total of 1397 horse miR-NAs have been identified. However, when compared to the total of 4523 human miRNAs, the number of horse miRNAs is small (Kozomara and Griffiths-Jones, 2014). This means that additional miRNAs may be identified in the horse genome; our data identified some of these miRNAs. Two MER91C-derived precursor miRNAs and four mature miR-NAs were identified, and their expression in human cell lines has been validated (Ahn et al., 2013). MER91C-derived precursor sequences were matched to eca-miR-652 in the horse (Table 2) and to hsa-miR-652 in humans (Ahn et al., 2013). Many studies have identified TE-derived miRNAs (Borchert et al., 2011; Piriyapongsa et al., 2007; Smalheiser and Torvik, 2005). Specifically, palindromic structures of TEs show the potential to generate miRNA precursor forms; thus, MITE- and MER-derived miRNAs are well-known (Ahn et al., 2013; Gim et al., 2014; Piriyapongsa and Jordan, 2008; Piriyapongsa et al., 2007; Yuan et al., 2010). However, few studies have examined the functions of TE-derived miRNAs. We determined the expression patterns in several tissues in a horse, and additional studies are needed to evaluate the functions of these miRNAs.
We also predicted the miRNA cluster, identified as BM734541.1, in the horse EST
As an invader of host genomes, TE sequences have undergone rapid evolution compared to other genomic sequences (Park et al., 2015). As a class II TE, DNA transposons, including MER repeats, underwent arrangement and were then conserved in the host genome (Pace and Feschotte, 2007). MER-derived miRNAs, detected in humans and horses, may be present in other mammals, including rodentia and lagomorpha. MER5A1-derived miRNAs were matched with miR-544b, which was previously identified in humans, horses, and cows. MER53-matched miR-1302 and MER91C-derived miR-652 were identified in four and fourteen species, respectively (Kozomara and Griffiths-Jones, 2014). Similarly, many cases of TE-derived miRNAs have been linked to phylogeny-specific miRNAs (Piriyapongsa et al., 2007). For instance, MITE-derived miR-548 was principally identified in primates (Liang et al., 2012).
We predict that additional miRNAs, as well as ESTs, derived from palindrome sequence TEs will be identified. In the host, these miRNAs were reported to have various roles. In a human study, the SNP in miR-1302-binding sites impaired spermatogenesis (Zhang et al., 2011), and miR-652 expression was related to heart disease. miR-548 is involved in the host antiviral response by targeting interferon λ1, and thus may be related to the immune system (Li et al., 2013). Based on these results, further studies are required to determine the functions of these miRNAs in horse and other mammalian species.
Owing to the development of next-generation sequencing technology, more precise genome sequencing data and transcript data is expected to be available. This study provides insights into novel functional transcripts. Future studies are required to understand how TE-derived miRNAs manipulate biological functions.
MER5A1 was identified in Eutheria. MER53, MER81, MER91C, and MER117 were identified in human.
(A) MER5A1-derived transcript ENSECAT00000029718 5p (left) and 3p (right) miRNA. (B) MER53-derived transcript ENSECAT00000027640 5p (left) and 3p (right) miRNA. (C) MER81-derived transcript ENSECAT00000029221 5p (left) and 3p (right) miRNA. (D) MER91C-derived transcript ENSECAT00000027964 5p (left) and 3p (right) miRNA. Each samples was examined in triplicate (Bar: mean; Whisker: standard deviation). Paired Student’s
(A–E) Five mature miRNAs from horse EST. (F) Secondary structure prediction of BM734541.1, indicated are each mature sequence. Each samples was examined in triplicate (Bar: mean; Whisker: standard deviation). Paired Student’s
Palindromic MER consensus sequences in horse genome
Repeat name | Repeat length (bp) | Structure | Number of paralogs in horse genome (equCab2) |
---|---|---|---|
MER5A1 | 160 | Palindrome | 196 |
MER53 | 189 | Palindrome | 202 |
MER81 | 114 | Palindrome | 161 |
MER91C | 140 | Palindrome | 168 |
MER117 | 197 | Palindrome | 160 |
Comparison between miRBase database sequences and palindromic MER-derived transcripts.
Matched precursor sequences and E-values were the results of the miRBase BLAST seaching.
Repeat name | Transcript assession no. | Position | Strand | Transcript length (bp) | Matched precursor sequence | E-value | Genomic region (Gene or transcript accession no.) |
---|---|---|---|---|---|---|---|
MER5A1 | ENSECAT00000029344.1 | chr14:89,097,198-89,097,294 | + | 97 | eca-miR-544b | 9.00E-15 | Intergenic |
ENSECAT00000029411.1 | chr21:31,003,689-31,003,780 | − | 92 | eca-miR-544b | 6.00E-06 | Intron (ADAMTS12) | |
ENSECAT00000029517.1 | chrX:10,032,472-10,032,568 | + | 97 | eca-miR-544b | 5.00E-14 | Intergenic | |
ENSECAT00000029551.1 | chr15:74,838,110-74,838,184 | + | 93 | eca-miR-544b | 1.00E-14 | Intergenic | |
ENSECAT00000029718.1 | chr11:53,066,395-53,066,487 | − | 93 | eca-miR-544b | 4.00E-08 | Intron (MYH1, MYH2, MYH4, MYH6, MYH7, MYH7B, MYH8, MYH13) | |
ENSECAT00000029813.1 | chrX:19,077,964-19,078,058 | − | 95 | eca-miR-544b | 3.00E-09 | Intron (POLA) | |
MER53 | ENSECAT00000027451.1 | chr16:58,884,211-58,884,360 | − | 150 | eca-miR-1302c-5 | 1.00E-15 | Intron (JL635408) |
ENSECAT00000027640.1 | chr14:29,187,011-29,187,112 | + | 102 | eca-miR-1302-1 | 6.00E-08 | Intron (HTR4, GU289397, AY647163) | |
MER81 | ENSECAT00000029217.1 | chr10:36,160,777-36,160,851 | + | 75 | Not detected | Intron (IBTK), UTR (JL626932) | |
ENSECAT00000029221.1 | chrX:50,972,151-50,972,233 | − | 83 | Not detected | Intergenic | ||
ENSECAT00000029305.1 | chr21:8,851,113-8,851,188 | + | 76 | Not detected | Intron (JL635478, JL639598, JL624325) | ||
ENSECAT00000029634.1 | chr2:37,821,443-37,821,510 | + | 68 | eca-miR-8990 | Not significant | Intergenic | |
MER91C | ENSECAT00000027964.1 | chrX:86,921,316-86,921,413 | + | 98 | eca-miR-652 | 2.00E-34 | Intergenic |
MER117 | BM734541.1 | chr23:7,068,821-7,073,667 | − | 655 | Not detected | Intron (JL633484, JL641603) |
Mol. Cells 2017; 40(4): 262-270
Published online April 30, 2017 https://doi.org/10.14348/molcells.2017.2295
Copyright © The Korean Society for Molecular and Cellular Biology.
Jeong-An Gim1,2,3, and Heui-Soo Kim1,2,*
1Department of Biological Sciences, College of Natural Sciences, Pusan National University, Busan 46241, Korea, 2Genetic Engineering Institute, Pusan National University, Busan 46241, Korea, 3The Genomics Institute, Life Sciences Department, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea
Correspondence to:*Correspondence: khs307@pusan.ac.kr
MicroRNAs (miRNAs) are single-stranded, small RNAs (21?23 nucleotides) that function in gene silencing and translational inhibition via the RNA interference mechanism. Most miRNAs originate from host genomic regions, such as intergenic regions, introns, exons, and transposable elements (TEs). Here, we focused on the palindromic structure of medium reiteration frequencies (MERs), which are similar to precursor miRNAs. Five MER consensus sequences (MER5A1, MER53, MER81, MER91C, and MER117) were matched with paralogous transcripts predicted to be precursor miRNAs in the horse genome (equCab2) and located in either intergenic regions or introns. The MER5A1, MER53, and MER91C sequences obtained from RepeatMasker were matched with the eca-miR-544b, eca-miR-1302, and eca-miR-652 precursor sequences derived from Ensembl transcript database, respectively. Each precursor form was anticipated to yield two mature forms, and we confirmed miRNA expression in six different tissues (cerebrum, cerebellum, lung, spleen, adrenal gland, and duodenum) of one thorough-bred horse. MER5A1-derived miRNAs generally showed significantly higher expression in the lung than in other tissues. MER91C-derived miRNA-5p also showed significantly higher expression in the duodenum than in other tissues (cerebellum, lung, spleen, and adrenal gland). The MER117-overlapped expressed sequence tag generated polycistronic miRNAs, which showed higher expression in the duodenum than other tissues. These data indicate that horse MER transposons encode miR-NAs that are expressed in several tissues and are thought to have biological functions.
Keywords: medium reiteration frequency transposon, MicroRNA, palindromic structure, thoroughbred horse
MicroRNAs (miRNAs) are non-coding small RNAs (21–23 nucleotides) that play a key role in inhibiting target genes by binding their 3′ UTRs, which are complementary to the miR-NAs’ seed regions (Bartel, 2009; Chen and Rajewsky, 2007; Shukla et al., 2011). These sequences are known to influence various biological processes in numerous animals and plants (Bartel, 2009). miRNAs undergo a series of changes from the transcript stage to maturity. First, primary miRNAs are transcribed by polymerase II in the nucleus (Lee et al., 2004). Next, they are cleaved into precursor miRNAs (70 nucleotides), with a double-stranded hairpin structure, by Drosha. Finally, precursor miRNAs are exported into the cytoplasm and converted to mature miRNAs by Dicer (Lund and Dahlberg, 2006). In a genome, miRNA-encoding genes are located in various characterized regions such as intergenic regions, exons, introns, and transposable elements (TEs) (Piriyapongsa et al., 2007). TEs contribute to miRNA sequences in various ways. For example, two adjacent TEs, as well as genomic sequences and one TE, yield one precursor miRNA. Palindrome sequences containing TEs such as miniature inverted repeat transposable elements (MITE) and medium reiteration frequency (MER) generate one precursor form and two mature miRNAs (Ahn et al., 2013; Yuan et al., 2010). Two mature miRNAs are derived from one precursor miRNA and present asymmetric expression or selective expression patterns (Hutvagner, 2005; Ruike et al., 2008).
MERs are non-autonomous mammalian DNA transposons (Jurka et al., 1996). A total of 240,000 copies of MERs are present in humans, accounting for 2.4% of the human genome (Lander et al., 2001). Most of these sequences were fossilized, such as long terminal repeats (LTRs) or endogenous retroviruses (ERVs) (Coffin, 2004; Smit, 1993), although some cause diseases in host organisms (Balada et al., 2010; Lamprecht et al., 2010). The genomes of primates, rodentia, and lagomorpha contain MER repeats inserted before the
The reference genome sequence for horse was determined in 2007, and the horse genetic map has been available since 2009 (Wade et al., 2009). The horse genome contains numerous genetic traits linked to racing ability, such as single-nucleotide polymorphisms (SNPs), specific transcripts, and copy number variation (CNV) (Doan et al., 2012; Hill et al., 2010; Petersen et al., 2013). Based on the horse reference genome sequence, a total of 1397 horse miRNAs have been identified in the miRBase database (Kozomara and Griffiths-Jones, 2014). Subsequently, the functional study and characterization of horse miRNAs could be available (Kim et al., 2014; Zhou et al., 2009). However, horse miR-NAs have not been as relatively well studied as other genetic traits, such as SNPs or CNV (Doan et al., 2012; Gim et al., 2015; Hill et al., 2010).
Many identified expressed sequence tags (ESTs) are available in databases, and ESTs can encode miRNAs and miRNA clusters (Smalheiser, 2003). The miRNA cluster transcripts are formed from ESTs, which show polycistronic expression patterns containing multiple, distinct loops separated by Drosha and Dicer. Forty-eight percent of all human mature miRNAs are derived from primary miRNAs of polycistronic transcripts (Altuvia et al., 2005). A well-known miRNA cluster, previously known as
MER consensus sequences that form palindromic sequences were downloaded from the Repbase database version 21.05 of the Genetic Information Research Institute (
MER consensus sequences forming palindromic sequences were predicted by RNAfold (
The animal protocol and sample extraction method in this study were reviewed by the Pusan National University-Institutional Animal Care and Use Committee (PNU-IACUC) for the ethical procedures and scientific care (approval number PNU-2013-0411). Small RNA from 100 mg of different tissues from one thoroughbred horse, sacrificed for biological research, was extracted from the cerebrum, cerebellum, lung, spleen, adrenal gland, and duodenum, using Hybrid-R™ miRNA (GeneAll Biotechnology Co., Ltd., Korea) according to the manufacturer’s protocol. Hybrid-R™ kit is available to simultaneously isolate large RNA and small RNA, and to separate total RNA and small RNA by using small RNA specific binding column tube. In order to exclude short RNA sequences from degreaded longer transcripts, a portion (2–3μl) of total RNA was loaded onto an agarose gel, then only detected 28S and 18S samples were used.
Next, the turbo DNA-free™ kit (Ambion, USA) was used according to the manufacturer’s protocol to remove DNA contamination from the small RNAs. A portion (2–3 μl) of isolated small RNA was loaded onto an agarose gel, and only samples in which small-RNA (< 200 nt) was detected were used in subsequent experiments. We measured the small RNA concentrations, which ranged between 130–180 ng/μl in the samples. Each small RNA sample was quantitated to 500 ng using a NanoDrop® ND-1000 UV–vis Spectrophotometer (NanoDrop Technologies, USA). After quantifying small RNA, adenine was added to the small RNA transcripts at their 3′ ends, using poly (A) tailing kits (Ambion). Samples were incubated in E-PAP buffer at 37°C for 30 min for the poly (A) tailing reactions. After the reactions, we performed reverse transcription reactions using Moloney murine leukemia virus reverse transcriptase with an RNase inhibitor (Promega, USA) at an annealing temperature of 42°C. To select target miRNAs in the reverse transcription reactions, we used an oligo-dT adaptor (5′-CTGTGAATGCTG CGACTACGAT-18dTs-3′) according to the methods of previous study (Fu et al., 2006). The miRNA sequence is used as forward primer, and adaptor sequences excluded poly T in the 3′ terminal is used as reverse primer (
RT-PCR was conducted in a thermocycler (Eppendorf, Germany) and SYBR green quantitative RT-PCR was conducted using a Roter Gene Q (Qiagen, Germany). Each reaction was performed in a final volume of 20 μl containing 1 μl of cDNA sample as a template, 10 μl of Quantitect® SYBR® Green PCR MasterMix (Qiagen), 7 μl of nuclease-free water, and 1μl each of sense primer and antisense primer (each 10 pmol). RT-PCR of genes was performed at 94°C for 5 min, 35 cycles of 94°C for 30 s, 55°C for 30 s, and 72°C for 30 s, and a final elongation at 72°C for 7 min. Next, quantitative RT-PCR of genes was performed at 94°C for 15 min, 55 cycles of 94°C for 10 s, 55°C for 15 s, and 72°C for 15 s using the primers shown in
Some of consensus sequences of MER have palindromic structures, which are similar to those of precursor miRNAs. A total of 238 MER elements were screened from the Repbase database, and 24 MER elements were identified to have palindromic structures. In the 24 MER elements, only five MER-derived mature miRNAs were confirmed as RT-PCR (
To confirm that the mature miRNAs were derived from MER transposons, all mature miRNAs were extracted from the tissues of one thoroughbred horse. Adenine and adaptor sequences were added to the 3′ end of each mature miRNA (see “Materials and Methods”). Next, RT-PCR was performed to identify the expression of 24 MER transposon-derived miRNA, and only five miRNAs were detected. Then, we performed qRT-PCR of five miRNAs in the six tissues of one horse (Cerebrum, Cerebellum, Lung, Spleen, Adrenal gland, Duodenum), and MER-derived miRNA showed tissue-specific expression patterns. As shown in Fig. 2, two mature miRNAs derived from one primary miRNA showed similar expression patterns. The MER5A1-derived ENSECAT000000 29718 transcript yielded two miRNAs showing lung-dominant expression patterns than other tissues (Fig. 2A). The MER53-derived ENSECAT00000027640 transcript yielded two miRNAs showing different expression patterns between the -5p and -3p forms. The -5p miRNA showed higher expression value in the cerebrum and duodenum than in other tissues, but no significant expression patterns were detected (Fig. 2B, left). The -3p miRNA showed dominant expression patterns in the duodenum, compared to cerebrum, cerebellum, lung, and adrenal gland (Fig. 2B, right). The MER81-derived ENSECAT00000029221 transcript yielded two miRNAs, that were no significant expression patterns (Fig. 2C). The MER91C-derived ENSECAT00000027964 transcript yielded two miRNAs, which showed different expression patterns. The -5p miRNA was enriched in the duodenum than other tissues (Fig. 2D, left), whereas the -3p miRNA was enriched in the cerebrum than cerebellum, lung, and duodenum (Fig. 2D, right).
We confirmed that the MER117 sequence overlapped with horse EST of BM734541.1, the transcript of which was predicted to contain many palindromic structures. The BM734541.1 transcript was predicted to generate five precursor forms of polycistronic miRNAs. As shown in Fig. 3, the expression patterns of five different mature forms of the BM734541.1 were confirmed. We detected these mature forms in six different tissues, indicating that total mature forms except EST-2-derived mature form have significantly low expression patterns in the cerebellum than adrenal gland (Figs. 3A, 3C–3E). Interestingly, EST-1-derived mature form was dominantly expressed in other tissues than cerebellum, except cerebrum (Fig. 3A). Only adrenal gland had higher expression pattern than cerebellum in the EST-4-derived mature form (Fig. 3D). The location of mature miR-NAs in the BM734541.1 transcript is indicated for each corresponding region in Fig. 3F.
MER-sequences are non-autonomous DNA transposons distributed throughout the host genome in a fossilized state. According to pre-RepeatMasking data, the horse genome possesses 3.61% DNA transposons containing MER-sequences (Smit et al., 2004). MER sequences can form palindromic stem-loop structures, which are similar to miR-NA precursor sequences. This suggests a mode for miRNA sequence formation (Ahn et al., 2013; Gim et al., 2014). To date, miRNAs that are derived from repetitive elements have been identified in the genomes of various species (Nozawa et al., 2010; Yuan et al., 2011). In this study, we identified 13 MER-derived miRNAs and confirmed their expression in six tissues of one thoroughbred horse.
During miRNA maturation, two mature miRNAs are processed from one precursor miRNA. According to previous studies, the two mature miRNAs are expressed via asymmetric selection of each miRNA strand by the processing of precursor miRNA (Hutvagner, 2005; Ruike et al., 2008). In this study, we also observed that two miRNAs presented different expression patterns. In the MER5A1-derived miRNAs, similar expression patterns were observed for the two miR-NAs from one precursor miRNA (Fig. 2A), whereas the MER53- and MER91C-derived miRNAs showed slightly different expression patterns (Figs. 2C and 2D). MER5A1-derived miRNAs showed dominant expression in the lung; thus, it may be a good target for future studies on exercise, cardiopulmonary fitness, or any lung-related process (Fig. 2A). As a part of brain, cerebrum and cerebellum are related to central nervous system (CNS). However, they expression patterns have different in MER81 and MER91C-derived miRNAs (Figs. 2C and 2D). Cerebrum is most important region of the CNS, and controls all voluntary operation in the body. Thus, these different expression patterns could be related to the cerebrum-specific roles in the CNS. Moreover, these results could provide a clue for cognitive function of the horse (Lein et al., 2007). Spleen is related to immune response, and adrenal gland produces a variety of hormones. In our data, spleen and adrenal gland have lower expressed patterns. Therefore, these two organs provide the important points in the immune and internal secretion pathways in the organisms (Nishimura and Naito, 2005). Most chemical digestion takes place in duodenum, therefore MER53-derived ENSECAT00000027640-3p miRNA, MER91C-derived ENSEC AT00000027964-5p miRNA and BM734541.1-derived miR-NAs could be crucial roles in digestion (Fang et al., 2006). Our six tissue expression patterns could be involved in exercise, cognition, and the physiological pathway.
MER5A1-derived miRNA precursor sequences were well-matched with eca-miR-544b (Table 2); therefore, they may be good targets for future studies on exercise and cardio-pulmonary fitness. miR-544b has, to date, been identified in only three species (human, cow, and horse), and additional studies are required to determine the species- or tissue-specific roles of miR-544b. MER53 has been predicted to encode miR-1302 (Yuan et al., 2010). MER53-derived miR-NAs did not show consistent expression patterns among their families. The miR-1302 subfamily derived from MER53 showed tissue-specific expression and identified in human, chimpanzee, orangutan (Kozomara and Griffiths-Jones, 2014). Therefore, it may be interesting to analyze their functions and evolutionary mechanisms in various animals in further studies. MER81-derived miRNAs have no significantly expressed patterns in all tissues to the other miRNAs. Three of four MER81-derived precursor sequences were not matched with previously identified precursor sequences. Although only one sequence matched with eca-miR-8990, its E-value was not significant. According to the latest version of miRBase (version 21.0), a total of 1397 horse miR-NAs have been identified. However, when compared to the total of 4523 human miRNAs, the number of horse miRNAs is small (Kozomara and Griffiths-Jones, 2014). This means that additional miRNAs may be identified in the horse genome; our data identified some of these miRNAs. Two MER91C-derived precursor miRNAs and four mature miR-NAs were identified, and their expression in human cell lines has been validated (Ahn et al., 2013). MER91C-derived precursor sequences were matched to eca-miR-652 in the horse (Table 2) and to hsa-miR-652 in humans (Ahn et al., 2013). Many studies have identified TE-derived miRNAs (Borchert et al., 2011; Piriyapongsa et al., 2007; Smalheiser and Torvik, 2005). Specifically, palindromic structures of TEs show the potential to generate miRNA precursor forms; thus, MITE- and MER-derived miRNAs are well-known (Ahn et al., 2013; Gim et al., 2014; Piriyapongsa and Jordan, 2008; Piriyapongsa et al., 2007; Yuan et al., 2010). However, few studies have examined the functions of TE-derived miRNAs. We determined the expression patterns in several tissues in a horse, and additional studies are needed to evaluate the functions of these miRNAs.
We also predicted the miRNA cluster, identified as BM734541.1, in the horse EST
As an invader of host genomes, TE sequences have undergone rapid evolution compared to other genomic sequences (Park et al., 2015). As a class II TE, DNA transposons, including MER repeats, underwent arrangement and were then conserved in the host genome (Pace and Feschotte, 2007). MER-derived miRNAs, detected in humans and horses, may be present in other mammals, including rodentia and lagomorpha. MER5A1-derived miRNAs were matched with miR-544b, which was previously identified in humans, horses, and cows. MER53-matched miR-1302 and MER91C-derived miR-652 were identified in four and fourteen species, respectively (Kozomara and Griffiths-Jones, 2014). Similarly, many cases of TE-derived miRNAs have been linked to phylogeny-specific miRNAs (Piriyapongsa et al., 2007). For instance, MITE-derived miR-548 was principally identified in primates (Liang et al., 2012).
We predict that additional miRNAs, as well as ESTs, derived from palindrome sequence TEs will be identified. In the host, these miRNAs were reported to have various roles. In a human study, the SNP in miR-1302-binding sites impaired spermatogenesis (Zhang et al., 2011), and miR-652 expression was related to heart disease. miR-548 is involved in the host antiviral response by targeting interferon λ1, and thus may be related to the immune system (Li et al., 2013). Based on these results, further studies are required to determine the functions of these miRNAs in horse and other mammalian species.
Owing to the development of next-generation sequencing technology, more precise genome sequencing data and transcript data is expected to be available. This study provides insights into novel functional transcripts. Future studies are required to understand how TE-derived miRNAs manipulate biological functions.
MER5A1 was identified in Eutheria. MER53, MER81, MER91C, and MER117 were identified in human.
(A) MER5A1-derived transcript ENSECAT00000029718 5p (left) and 3p (right) miRNA. (B) MER53-derived transcript ENSECAT00000027640 5p (left) and 3p (right) miRNA. (C) MER81-derived transcript ENSECAT00000029221 5p (left) and 3p (right) miRNA. (D) MER91C-derived transcript ENSECAT00000027964 5p (left) and 3p (right) miRNA. Each samples was examined in triplicate (Bar: mean; Whisker: standard deviation). Paired Student’s
(A–E) Five mature miRNAs from horse EST. (F) Secondary structure prediction of BM734541.1, indicated are each mature sequence. Each samples was examined in triplicate (Bar: mean; Whisker: standard deviation). Paired Student’s
. Palindromic MER consensus sequences in horse genome.
Repeat name | Repeat length (bp) | Structure | Number of paralogs in horse genome (equCab2) |
---|---|---|---|
MER5A1 | 160 | Palindrome | 196 |
MER53 | 189 | Palindrome | 202 |
MER81 | 114 | Palindrome | 161 |
MER91C | 140 | Palindrome | 168 |
MER117 | 197 | Palindrome | 160 |
. Comparison between miRBase database sequences and palindromic MER-derived transcripts..
Matched precursor sequences and E-values were the results of the miRBase BLAST seaching..
Repeat name | Transcript assession no. | Position | Strand | Transcript length (bp) | Matched precursor sequence | E-value | Genomic region (Gene or transcript accession no.) |
---|---|---|---|---|---|---|---|
MER5A1 | ENSECAT00000029344.1 | chr14:89,097,198-89,097,294 | + | 97 | eca-miR-544b | 9.00E-15 | Intergenic |
ENSECAT00000029411.1 | chr21:31,003,689-31,003,780 | − | 92 | eca-miR-544b | 6.00E-06 | Intron (ADAMTS12) | |
ENSECAT00000029517.1 | chrX:10,032,472-10,032,568 | + | 97 | eca-miR-544b | 5.00E-14 | Intergenic | |
ENSECAT00000029551.1 | chr15:74,838,110-74,838,184 | + | 93 | eca-miR-544b | 1.00E-14 | Intergenic | |
ENSECAT00000029718.1 | chr11:53,066,395-53,066,487 | − | 93 | eca-miR-544b | 4.00E-08 | Intron (MYH1, MYH2, MYH4, MYH6, MYH7, MYH7B, MYH8, MYH13) | |
ENSECAT00000029813.1 | chrX:19,077,964-19,078,058 | − | 95 | eca-miR-544b | 3.00E-09 | Intron (POLA) | |
MER53 | ENSECAT00000027451.1 | chr16:58,884,211-58,884,360 | − | 150 | eca-miR-1302c-5 | 1.00E-15 | Intron (JL635408) |
ENSECAT00000027640.1 | chr14:29,187,011-29,187,112 | + | 102 | eca-miR-1302-1 | 6.00E-08 | Intron (HTR4, GU289397, AY647163) | |
MER81 | ENSECAT00000029217.1 | chr10:36,160,777-36,160,851 | + | 75 | Not detected | Intron (IBTK), UTR (JL626932) | |
ENSECAT00000029221.1 | chrX:50,972,151-50,972,233 | − | 83 | Not detected | Intergenic | ||
ENSECAT00000029305.1 | chr21:8,851,113-8,851,188 | + | 76 | Not detected | Intron (JL635478, JL639598, JL624325) | ||
ENSECAT00000029634.1 | chr2:37,821,443-37,821,510 | + | 68 | eca-miR-8990 | Not significant | Intergenic | |
MER91C | ENSECAT00000027964.1 | chrX:86,921,316-86,921,413 | + | 98 | eca-miR-652 | 2.00E-34 | Intergenic |
MER117 | BM734541.1 | chr23:7,068,821-7,073,667 | − | 655 | Not detected | Intron (JL633484, JL641603) |
Jeong-An Gim, and Heui-Soo Kim
Mol. Cells 2017; 40(10): 796-804 https://doi.org/10.14348/molcells.2017.0141Rui Cao, Wang Jun Wu, Xiao Long Zhou, Peng Xiao, Yi Wang, and Hong Lin Liu
Mol. Cells 2015; 38(4): 304-311 https://doi.org/10.14348/molcells.2015.2122Jeong-An Gim, Chang Pyo Hong, Dae-Soo Kim, Jae-Woo Moon, Yuri Choi, Jungwoo Eo, Yun-Jeong Kwon, Ja-Rang Lee, Yi-Deun Jung, Jin-Han Bae, Bong-Hwan Choi, Junsu Ko, Sanghoon Song, Kung Ahn, Hong-Seok Ha, Young Mok Yang, Hak-Kyo Lee, Kyung-Do Park, Kyoung-Tag Do, Kyudong Han, Joo Mi Yi, Hee-Jae Cha, Selvam Ayarpadikannan, Byung-Wook Cho, Jong Bhak, and Heui-Soo Kim
Mol. Cells 2015; 38(3): 210-220 https://doi.org/10.14348/molcells.2015.2138
MER5A1 was identified in Eutheria. MER53, MER81, MER91C, and MER117 were identified in human.
|@|~(^,^)~|@|Quantitative expression patterns of MER-derived transcript miRNAs.(A) MER5A1-derived transcript ENSECAT00000029718 5p (left) and 3p (right) miRNA. (B) MER53-derived transcript ENSECAT00000027640 5p (left) and 3p (right) miRNA. (C) MER81-derived transcript ENSECAT00000029221 5p (left) and 3p (right) miRNA. (D) MER91C-derived transcript ENSECAT00000027964 5p (left) and 3p (right) miRNA. Each samples was examined in triplicate (Bar: mean; Whisker: standard deviation). Paired Student’s
(A–E) Five mature miRNAs from horse EST. (F) Secondary structure prediction of BM734541.1, indicated are each mature sequence. Each samples was examined in triplicate (Bar: mean; Whisker: standard deviation). Paired Student’s