Characterization of an extensive rainbow trout miRNA transcriptome by next generation sequencing
- Amelie Juanchich1Email author,
- Philippe Bardou2,
- Olivier Rué3,
- Jean-Charles Gabillard1,
- Christine Gaspin3,
- Julien Bobe†1 and
- Yann Guiguen†1
© Juanchich et al. 2016
Received: 8 October 2015
Accepted: 19 February 2016
Published: 1 March 2016
MicroRNAs (miRNAs) have emerged as important post-transcriptional regulators of gene expression in a wide variety of physiological processes. They can control both temporal and spatial gene expression and are believed to regulate 30 to 70 % of the genes. Data are however limited for fish species, with only 9 out of the 30,000 fish species present in miRBase. The aim of the current study was to discover and characterize rainbow trout (Oncorhynchus mykiss) miRNAs in a large number of tissues using next-generation sequencing in order to provide an extensive repertoire of rainbow trout miRNAs.
A total of 38 different samples corresponding to 16 different tissues or organs were individually sequenced and analyzed independently in order to identify a large number of miRNAs with high confidence. This led to the identification of 2946 miRNA loci in the rainbow trout genome, including 445 already known miRNAs. Differential expression analysis was performed in order to identify miRNAs exhibiting specific or preferential expression among the 16 analyzed tissues. In most cases, miRNAs exhibit a specific pattern of expression in only a few tissues. The expression data from sRNA sequencing were confirmed by RT-qPCR. In addition, novel miRNAs are described in rainbow trout that had not been previously reported in other species.
This study represents the first characterization of rainbow trout miRNA transcriptome from a wide variety of tissue and sets an extensive repertoire of rainbow trout miRNAs. It provides a starting point for future studies aimed at understanding the roles of miRNAs in major physiological process such as growth, reproduction or adaptation to stress. These rainbow trout miRNAs repertoire provide a novel resource to advance genomic research in salmonid species.
KeywordsmicroRNA Rainbow trout Repertoire Tissue expression Gene regulation
MicroRNAs (miRNAs) have emerged as important post-transcriptional regulators of gene expression in a wide variety of physiological processes. miRNAs are short endogenous non-coding RNA (ncRNA) present in a wide variety of organisms, including plants, animals, unicellular organisms, and viruses . Mature miRNAs derive from primary transcripts (approximately 1000 bp long) forming hairpins that are cleaved into miRNA precursor (pre-miRNA). One strand of the resulting miRNA duplex is loaded into a miRISC Complex (microRNA Induced Silencing Complex) by Argonaute proteins. Most mature miRNAs are 20–24 nt long while pre-miRNA are 60–80 nt in length. Mainly, the miRISC complex can bind to the 3′UTR of its target mRNA and subsequently lead to degradation or repression of translation [1, 2]. Several examples of non-canonical binding (CDS or 5′UTR) have been reported lately for miRNAs proven to be functional . The role of miRNAs has been studied in several physiological and physiopathological processes. They are involved in key animal developmental processes, such as maternal transcript clearance  or axial patterning . Moreover, miRNAs are also involved in disease and 163 pathologies reported in miR2Disease database have been associated with misregulation of 349 miRNA genes or dysfunction of miRNA/mRNA target interaction . In addition, miRNAs can be associated with economical traits. In sheep, a mutation in myostatin 3′-UTR creates a new target site for miRNA and affects muscularity . miRNAs are often expressed in a tissue-enriched manner . They can control both temporal and spatial gene expression and are believed to regulate 30 to 70 % of the protein-coding genes .
Before the development of high-throughput sequencing the number of miRNAs discovered by cloning and Sanger sequencing was dramatically underestimated and limited to approximately 100 per species. With the advent of large-scale genomic analyses, even miRNAs with low abundance have been successfully discovered in various species. To date, at least 35,823 mature miRNAs sequence have been discovered, corresponding to a total of 28,645 hairpins sequences in 223 species (miRBase 21, June 2014) [9–11]. Mammals and insects are the most studied species with regards to miRNA discovery but the most recent release (miRBase 21) contains several entries for several fish species such as Atlantic salmon (371 precursors, 498 matures), zebrafish (346 precursors, 350 matures), medaka (168 precursors, 146 matures), common carp (134 precursors, 146 matures), fugu (131 precursors, 108 matures), tetraodon (132 precursors, 109 matures), Atlantic halibut (40 precursors, 37 matures), olive flounder (20 precursors, 38 matures), and channel catfish (281 precursors, 205 matures). All above miRNAs have been discovered by next-generation sequencing. This database is however limited for salmonid species despite the reports of several miRNAs in several tissues of Atlantic salmon [12, 13] or rainbow trout [14, 15] and in rainbow trout eggs . Salmonids are economically and environmentally important species for both wild fisheries and worldwide aquaculture production. Genomic resources for rainbow trout and Atlantic salmon are advanced but our knowledge of salmonid miRNAs repertoire remains incomplete.
The aim of the current study was to discover and characterize rainbow trout (Oncorhynchus mykiss) miRNAs in a large number of tissues using next-generation sequencing in order to provide an extensive repertoire of rainbow trout miRNAs. A total of 38 different samples corresponding to 16 different tissues were individually sequenced and analyzed independently in order to identify a large number of miRNAs with high confidence. Differential expression analysis was performed in order to identify miRNAs exhibiting specific or preferential expression among the 16 tissues analyzed. The dataset was also used to discover novel miRNAs that had not been previously reported in other species. This miRNA characterization is a first step to better understand the role of miRNAs in gene regulation in rainbow trout.
Results and discussion
Overview of small RNA sequencing
Identification of conserved rainbow trout miRNAs
Many miRNAs have been conserved during evolution and the sequence identity is extremely high even among evolutionary distant species [25–27]. In the present study, we identified rainbow trout miRNAs based on their sequence similarity with other species and used miRBase database (version 21.0) and Rfam database as reference datasets. A total of 445 conserved putative precursors were discovered at unique genome locations that correspond to 123 mature conserved miRNAs. The annotation of miRNAs showed that we have identified 111 evolutionary conserved miRNA families in our dataset (Additional file 2). Several isoforms in sequence and size were found for each miRNA family. This number of identified miRNAs is consistent (i.e in the same range) with miRNA repertoires characterized in other fish species such as salmon [12, 13], zebrafish , and medaka . Some miRNAs are present at a unique locus but most of them are present at different positions in the genome (Additional file 2). The large presence of the same miRNA at multiple genomic locations is directly linked to the last round of whole genome duplication (Ss4R) that occurred in salmonids species. First, teleost WGD gave rise to several duplicated miRNA genes located in multiple genomic loci as reported for several teleost fish species. The fourth salmonid-specific event (Ss4R) further bolstered this condition in the genome of salmonid species. As previously shown , almost all miRNA loci are retained in duplicated copies in the rainbow trout genome.
Tissue distribution of rainbow trout miRNAs
Relative abundance of miRNA in the dataset was characterized (Fig. 4). In the global dataset, two miRNAs, miR-21 and miR-146, represent almost half of the reads with 33 and 15 % of the total number of reads in the complete dataset, respectively. Gene expression datasets from several tissues usually exhibit a different pattern: each gene has a small contribution to the total but none of them are overrepresented like it is the case for miRNAs. miR-21 is a well studied miRNA that is involved in different types of cancer [30, 31] and also in the development of heart disease . miR-146 is thought to be a mediator of inflammation and is upregulated by inflammatory factors such as interleukins and tumor necrosis factor-alpha . Eight miRNAs (miR-21, miR-146, miR-30, miR-3596, let-7, miR-101, miR-1 and miR-192) account for more than 1 % each and collectively represent 70 % of the total number of reads. When looking at the miRNA distribution within the different organs (Additional file 4), we found the same miRNAs to be on the top of each list (miR-21, miR-146, miR-143) but also some over-represented miRNA are specific to one organ. For instance, miR-202 accounts for respectively 20 and 10 % of the total reads in testis and ovary, miR-1 accounts for 42 % in muscles and 12 % in heart. A similar distribution was reported in rainbow trout unfertilized eggs , with slight differences. let-7 was the most expressed miRNA and accounts for 24 % of the total, followed by miR-21 (18 % of the total). In the present study, we confirm that a small subset of miRNAs is highly expressed and accounts for approximately 70 % of total miRNA counts. This pattern has been observed in salmon fry, but the top expressed miRNAs are not the same. Ssa-miR-181 and ssa-miR-10 account for more than 72 % of the total miRNAs in salmon alevin . The two different studies in salmon do not include as many organs as we have in the present study, so that might be the reason why the top expressed miRNAs are different. In salmon, by looking at a subset of tissue or alevin, they are probably looking at miRNA enrichment in those organs or developmental stages.
Identification of novel rainbow trout miRNAs
Conservation of identified rainbow trout miRNAs
In conclusion, this study represents the first characterization of rainbow trout miRNA transcriptome from a wide variety of organs/tissues and describes an extensive repertoire of rainbow trout miRNAs. We identified 2946 miRNA loci in the rainbow trout genome including already known miRNAs (445) and putative novel miRNAs (2501 including 94 with high confidence). We also show that differential expression analysis in different tissues is possible using RNA sequencing strategy by confirming the expression data by RT-qPCR with high percentage of correlation. This study provides a starting point for future studies aimed at understanding the roles of miRNAs in major physiological process such as growth, reproduction, nutrition, and adaptation. This rainbow trout miRNAs repertoire provides a novel resource to advance genomic research in salmonids species.
Animals and sample collection
Investigations were conducted according to the guiding principles for the use and care of laboratory animals and in compliance with French and European regulations on animal welfare. Protocols were approved by the Rennes ethical committee for animal research (CREEA). Fish were euthanized using a lethal dose of 2-phenoxyethanol (10 mg/ml of water). All 38 samples (Additional file 1) were immediately frozen in liquid nitrogen and subsequently stored at -80 °C until RNA extraction. Samples from adult fish (heart, stomach, kidney, intestine, pituitary, brain, gills, spleen and skin) were all sampled from the same fish (adult female – 2 years old) in quadruplicates (one for sRNA-seq and the 3 others for RT-qPCR). All others samples were sampled from different fishes, under different experimental or physiological conditions (Additional file 1). Gonies were sampled as previously described in .
Optimized RNA extraction protocols were used for each tissue as previously described . All samples (except myocytes and myoblastes) were separately homogenized in Tri-reagent (Sigma, St-Louis, USA) at a ratio of 100 mg of tissue per ml of reagent and total RNA was extracted according to manufacturer’s instructions. RNA from myocytes and myoblasts was extracted using the NucleoSpin miRNA kit (Isolation of small and large RNA, Macherey Nagel, Germany) and according to the manufacturer’s instructions. Both long and small RNAs were kept in the same fraction and further referenced as total RNA. Ovarian tissues (ovary and oocytes) were homogenized in Tri-reagent (Sigma, St-Louis, USA) at a ratio of 100 mg of tissue per ml of reagent and total RNA was extracted according to manufacturer’s instructions. Because of high egg yolk content of vitellogenic ovaries and oocytes, all RNA samples were subsequently re-purified using a NucleoSpin miRNA kit (Isolation of small and large RNA, Macherey Nagel, Germany) in order to obtain genomic-grade RNA quality. Both long and small RNAs were kept in the same fraction and further referenced as total RNA. For all samples, RNA integrity was checked using RNA 6000 Nano chip (Agilent).
Small RNA library and sequencing (Illumina technology)
Small RNA libraries were prepared according to Small RNA v1.5 sample preparation guide (Illumina, January 2010). Briefly, 5 μg of total RNA is used for the small library preparation. Adapters are added at each ends of the small by ligation. First, the ligation is made at the 3′end and then a second ligation is made at the 5′end. v1.5 small RNA 3′ adapter is specifically modified to target miRNAs and other small RNAs that have a 3′ hydroxyl group resulting from enzymatic cleavage by Dicer or other processing enzymes. Small RNAs with both adapters are reverse-transcribed and amplified by PCR. Amplified small RNA libraries are gel purified on a polyacrylamide gel (miRNAs are 89 nt to 96 nt long with both adapters). DNA quality and integrity were checked using DNA-1000 chip (Agilent).
The small library is then hybridized on the flow cell and the libraries’ clustering was performed with the C-Boot cluster machine. The sequencing was done using a HiSeq-1000 sequencer (Illumina).
Cleaning and redundancy removal
The reads of length 36 nt contain part of the adapter in their 3′ end. We used CutAdapt  to remove the part of the adapter occurring at the 3′ end of reads and keep only relevant sequences for further analysis. The trimming was realized on all datasets with options -a ATCTCGTATGCCGTCTTCTGCTTG to remove the Illumina 3′ adapter. Resulting reads in the range 16 to 28 were obtained by setting parameters -m 16 and -M 28. This allowed us to keep reads in an enlarged expected range of miRNA size. Sequences containing ‘N’ and those of low complexity (less than 3 different nucleotides) were removed. Redundancy was then removed by pooling together all datasets and keeping only unique sequences. Finally sequences for which the number of occurrence was lower than 1000 were removed from the datasets. For each unique sequence, its occurrences were summed up and conserved for the dataset of all pooled libraries and for each independent library dataset.
Identification and annotation of miRNA loci
Analysis of unique sequences led to the identification of several known and novel small ncRNA families, including ribosomal RNA (rRNA), small nucleolar RNA (snoRNA), transfer RNA (tRNA) and many others. Unique cleaned sequences were aligned with Bowtie2 against the available rainbow trout scaffolded sequences . At most 15 hits of exact match were reported for each unique sequence. Loci were built by considering regions on the same strand separated by at most 70 nt. Loci were submitted to the miRNA prediction procedure that considers the expected pre-miRNA stem-loop structure, the size of the pre-miRNA sequence, the size of pre-miRNA loops (bulges, internal loops, stem loop), the size of the most represented sequence (20–24 nt) and its alignment against the stem of the pre-miRNA and the pre-miRNA expected expression profile. A score is assigned to each predicted pre-miRNA locus considering previous characteristics. Each predicted pre-miRNA locus is then submitted to the annotation procedure by aligning it against known ncRNA databases with Blast +  allowing mismatches. We selected SILVA , GtRNAdb , miRBase  and Rfam  to annotate sequences matching respectively known SSU and LSU rRNA, tRNA, miRNA and ncRNA from other families (Additional file 3). All predicted loci were mapped (Bowtie2 , no mismatch) against a repeat elements database  to remove transposons sequences from the putative predicted miRNA loci.
Conservation analysis was performed by blasting the identified rainbow trout miRNAs dataset against 8 fish genomes: Atlantic salmon (ICSASG_v1), Atlantic cod (gadMor1), zebrafish (Zv9), medaka (HdrR), seabass, stickleback (BROAD S1), tetraodon (TETRADON 8.0) and fugu (FUGU 4.0). Number of hits and eventual mismatches on the genome were recorded (Additional file 2).
miRNA reverse transcription and qPCR analysis
Reverse transcription and QPCR were performed as previously described with minor modifications . Briefly, total RNA (500 ng) was reverse transcribed using NCode™ VILO™ miRNA cDNA synthesis kit (Invitrogen, Cergy Pontoise, France) according to the manufacturer’s instructions. Real-time PCR was performed using a Step One Plus thermocycler (Applied Biosystems, Foster City, USA). Reverse transcription products were diluted to 1/100 and 4 μl were used for each real-time PCR reaction. Duplicates were run for each RT product. Real-time PCR was performed using a real-time PCR kit provided with a SYBR Green fluorophore (Fast SYBR Green Master Mix kit, Applied Biosystems) according to the manufacturer’s instructions with 100 nM of each primer (Additional file 7) for miRNAs. After a 30-s incubation step at 95 °C, amplification was performed using the following cycle: 95 °C, 3 s; 60 °C, 30 s; 40 times. The relative abundance of target cDNA within sample set was calculated from a serially diluted cDNA pool using the Step One Plus software. After amplification, a fusion curve was obtained in order to ensure that a single PCR product had been generated using the following protocol: 1 s holding followed by a 0.5 °C increase, from 60 to 95 °C. QPCR signal was normalized using 18S expression which is stable when comparing different tissues.
Analysis of tissue distribution
A hierarchical clustering was performed to characterize the miRNAs tissue distribution. The analysis was restricted to 16 different and independent tissues in order to characterize any differences between tissues and not between physiological conditions. The aim of the study was to characterize the rainbow trout miRNA repertoire but not to study any differences between several physiological conditions. We sequenced a large number of samples in order to get the most complete repertoire. The 16 chosen tissues are in bold in Additional file 1.
Availability of supporting data
All the sequencing data are deposited in SRA under the Bioproject accession number PRJNA227065 (http://www.ncbi.nlm.nih.gov/sra/?term=PRJNA227065). A website located at “ngspipelines.toulouse.inra.fr:9064” allows to explore all predicted miRNA providing complete information including functional and structural annotation, locus view and expression visualization by library (Additional file 8).
complementary DesoxyriboNucleic acid
real-time quantitative polymerase chain reaction
The authors are grateful to the experimental facility staff of the INRA LPGP laboratory for fish rearing and to Thaovi Nguyen for excellent technical assistance. The authors thank the MGX sequencing platform and especially Laurent Journot, Hugues Parrinello and Grégory Baronian for the sRNA-sequencing. The project was founded by INRA (AIP Bioressources 2010 « microTrout » and PHASE division grant « microFish »). OR was supported by France Génomique National infrastructure, funded as part of “Investissement d’avenir” program managed by Agence Nationale pour la Recherche (contrat ANR-10-INBS-09).
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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