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Novick RP Plasmid incompatibility. Microbiol Rev — Ruther U Construction and properties of a new cloning vehicle, allowing direct screening for recombinant plasmids. Mol Gen Genet — Sherratt DJ Bacterial plasmids. Cell — Studier FW Protein production by auto-induction in high density shaking cultures. Protein Expr Purif — J Mol Biol — Methods Enzymol — Eur J Biochem — Int J Med Microbiol — Vieira J, Messing J The pUC plasmids, an M13mp7-derived system for insertion mutagenesis and sequencing with synthetic universal primers.

Science — Download references. You can also search for this author in PubMed Google Scholar. Correspondence to Douglas A. Reprints and Permissions. Julin, D. Plasmid Cloning Vectors. In: Wells, R. Springer, New York, NY. Published : 30 January Print ISBN : Online ISBN : Anyone you share the following link with will be able to read this content:. Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative.

Skip to main content. Search SpringerLink Search. Conceived and designed the experiments: SC GL. Animal maintenance and tissue dissection: AG FN. Despite the economic and medical importance of the pig, knowledge about its genome organization, gene expression regulation, and molecular mechanisms involved in physiological processes is far from that achieved for mouse and rat, the two most used model organisms in biomedical research.

We applied a novel computational approach to predict species-specific and conserved miRNAs in the pig genome, which were then subjected to experimental validation. We established the subtle variability in expression of isomiRs and miRNA-miRNA star couples supporting a biological function for these molecules.

Finally, miRNA and mRNA expression profiles produced from the same sample of 20 different tissue of the animal were combined, using a correlation threshold to filter miRNA-target predictions, to identify tissue-specific regulatory networks. Our data represent a significant progress in the current understanding of miRNAome in pig. The identification of miRNAs, their target mRNAs, and the construction of regulatory circuits will provide new insights into the complex biological networks in several tissues of this important animal model.

Basic research and knowledge of human development, physiology, and pathology are closely tied by the use of suitable model organisms. Even if mouse and rat are the two mammals most used as human model organisms, many of their physiological parameters such as size, feeding, and respiratory rate are actually different from man. Furthermore, rodent genomes are evolving at a faster rate than the human genome [1].

The pig, despite a more expensive farming and a longer gestation period days vs 20 days for the mouse , is a model organism that can overcome these problems thanks to several similarities with humans. In particular, the size of organs and various anatomical features, as well as physiology and organ development, are very similar in the two species allowing the use of the pig as model to study different important issues such for example pathologies affecting the cardiovascular [2] , [3] , gastrointestinal [4] , and neuronal [5] systems, eyes [6] or muscles [7] or problems related with organ transplantation [8] , [9].

Indeed, the pig has become the most important species for the production of xenografts to overcome the growing gap between request and availability of human organs suitable for transplantation [8] , [10] , [11]. Moreover, many varieties of pigs play a relevant role in the economy of human feeding, opening issues on food safety where it is used to study host-pathogen interaction [12].

Despite this well-documented importance, the knowledge about the genome organization, gene expression regulation, and molecular mechanisms underlying the physio-pathological processes of the pig are still far from the knowledge we have achieved for the mouse and rat. Detailed information on the porcine genome, together with emerging transgenic technologies, will enhance our possibilities to create specific and useful pig models.

Recently, the atlas of DNA methylomes in porcine adipose and muscle tissues was published [14] and a great effort was made to associate the genome sequence knowledge to studies faced at gene expression analysis. Many of these studies were focused on swine immune system [15] — [19] , while a genome wide expression analysis in different tissues has been described [20]. In this scenario, the knowledge of miRNA expression, tissue specificity, and regulation acquire a fundamental role in the study of the transcriptome plasticity of the pig.

Recently, many studies have been directed to pig tissue-specific miRNA repertoires using deep-sequencing approaches. McDaneld [22] and Zhou [23] identified genes expressed in porcine skeletal muscle and predicted the miRNAs that may target these genes. Liu and colleagues discriminated between oxidative and glycolytic skeletal muscles identifying miRNAs that play essential roles in the phenotypic variations observed in different muscle fiber types [24].

MiRNA expressed in the kidney of different porcine breeds were analyzed, leading to the identification of breed-specific miRNAs, which could be potentially associated to specific phenotypes [28]. Moreover, miRNAs expressed by teeth have been studied as tools for investigating the molecular mechanism of tooth development [29] and those expressed by the pig intestine tracts [30] could be useful to study human pathologies of this organ due to the similarity among the two species.

Also in the pig brain the miRNA repertoire was studied, leading to the identification of miRNAs that are specifically activated during brain development [31]. MiRNAs expressed during embryonic life in testis, ovary and spermatic cells of the pig were discussed in recent papers providing a valuable resource for investigators interested in the regulation of embryonic development in pigs and other animals [32] — [36].

Pituitary gland is important for homeostasis through specific hormone secretion: Hongyi and colleagues showed that cells of this gland produce a lot of miRNA involved in both development and physiology of this organ [37]. Li and colleagues demonstrated, in a comparison of muscle and adipose tissues of the pig, that a complex regulatory network may underlie the subcutaneous fat development due to the great diversity of miRNA composition and expression levels found in the two tissues [38].

To obtain better insight into the biological function of this class of small RNA molecules, the identification of all miRNAs expressed from the pig genome is essential to monitor their activity and function in different tissues and to fully identify their potential mRNA targets [39] — [42].

The study presented in this paper was aimed at contributing to a complete view of the pig miRNome and to improve knowledge of miRNA function in different pig tissues. First, we systematically analyzed the pig genome to identify putative pre-miRNA structures.

In second instance, we experimentally identified true positive pre-miRNAs, i. This work is expanding the information on miRNA-tissue knowledge as it was reported up to now by Chen's [39] and Xie's [40] papers, who analyzed three or ten individual porcine tissues. The bioinformatic predictions of miRNA targets is a research field of a great expansion with a growing number of tools becoming available [45].

However, the rate of false positive results obtained with these tools is still very high, so we reasoned that the correlation between expression of miRNA and predicted targets, in their common physiological context, would be a useful strategy to support their connection and thus the functional relevance of predicted pairing.

The identification of putative pre-miRNAs was made following two complementary approaches. The first approach was meant at identifying conserved miRNA through the comparison of the pig genome sequence with the collection of miRNAs identified in other species. The second approach was a de novo identification based on the prediction of the putative pre-miRNAs structures in the porcine genome.

We found that A small percentage of conserved miRNAs show similarities to invertebrate sequences Saccoglossus kowalevskii 2. The percentage of pre-miRNAs putatively conserved in Sus scrofa was correlated with the phylogenetic distance between pig and other species. Lower percentage of miRNAs with homology to pig genome are seen in invertebrates e. Saccoglossus kowalevskii 2. The de-novo identification of miRNAs was based on the recognition in the whole pig genome of hairpins that are compatible with the canonical pri-miRNA secondary structure.

This analysis resulted in 10,, distinct candidate pri-miRNAs that, filtered with the triplet SVM algorithm probability score higher than 0. A series of microarrays, based on the RAKE approach, was used to experimentally identify mature miRNAs predicted by bioinformatic approaches conserved and de-novo computationally identified pre-miRNA [43] , [44].

This experiments has two important consequences: first it leads to the identification of true positive pre-miRNA among all predictions and second it makes possible the identification of the mature miRNA sequences originated from pre-miRNAs. In fact, computational analyses are unable to predict the correct boundaries of the mature miRNAs. However, RAKE technology is able to identify only one of the ends of the mature sequences from each microarray experiment see methods. Microarray probes were organized in tiling paths of 44 probes complementary to every predicted pre-miRNA.

These two platforms were used to screen 6, predicted pre-miRNAs conserved and de-novo predictions and the known miRNA sequences collected from miRBase and the literature [26] , [27] , [48] — [50] , using a pool of small RNAs prepared from 20 different tissues of the pig Protocol S1. We identified 1, responsive probes i.

Only perfectly hybridized probes allow the incorporation of biotinylated dATP, producing a fluorescent signal due to the successive incubation of microarrays with Cy3-strepatvidin VI. Electropherogram for the sample G. Peaks are evident for lower and upper markers, for the amplified miRNA 50 bp , and for the ladder 25 bp.

The table indicates the concentration and size of the peaks identified in the electropherogram. The letters and names over the gel lines correspond to the primers listed in the table SM2 of Protocol S1. Only high confidence miRNA sequences were considered for further analyses to describe gene regulative network in different pig tissues. Of the 23 positive miRNAs, 10 belong to the high confidence set, 2 to the medium and 11 to the low confidence set demonstrating that also medium and low confidence sets contain real miRNA Protocol S1.

We considered five different miRNAs. Since the pig is an important animal model for pre-clinical studies, especially for cardiovascular diseases [52] , four miRNAs highly expressed in the heart and one presenting a pronounced expression in the liver were chosen. Their expression was evaluated by qRT-PCR in five different tissues: liver, spleen, atrium, skeletal muscle, and white blood cells Figure 3.

Bringing forward results about the integration of miRNA and mRNA expression it is interesting to notice that putative target genes of the four miRNAs highly expressed in the heart are enriched in the ubiquitin protein ligase binding capacity. This result is interesting since inhibition of the cardiac proteasome, here evidenced as potentially regulated through miRNAs, has been shown to be cardio protective under some circumstances [53].

The Y-axis represents miRNA quantity related to the average quantity in the considered tissues. Next, we analyzed the expression pattern of the discovered miRNAs across 14 different tissues of the pig. This genome-wide study allowed the separation of tissues according to miRNA signatures. They cluster according to the structure, anatomical location, and physiological functions of tested organs, suggesting that the function of a miRNA could be inferred by the biology of tissue in which it is uniquely or mainly expressed.

MicroRNA expression profiles divide pig tissues in three large clusters Figure 4 A : a tissues with contractile properties like heart atrium and ventricle, stomach, tongue, and skeletal muscle, b circulating cells white blood cells , and c all other examined tissues liver, skin, adipose tissue, lung, lymph node, spleen, and kidney. Gene expression pattern of the stomach is linked to contractile tissues, showing that the smooth muscle component is predominant over the epithelial tissue of the stomach wall, while the skeletal muscle shows an expression pattern more comparable to that of the tongue.

The profile of white blood cell samples formed an out-group in the clustering tree, reflecting the specific features of these cells. The third cluster is composed of a group of tissues, such as lymph node, spleen, and adipose tissue. The similarity between spleen and lymph node samples reflects their important role for the immune system. MiRNA analysis of human normal tissues showed that these tissues have a very similar expression profiles also in man [56]. Clustering tree of pig tissue samples according to miRNA expression data.

The color of the arms describes the statistical support for the nodes, based on data resampling, as quantified in the node support legend. Each experiment was performed in duplicate, with replicas indicated with numbers 1 and 2 in the sample name. Clustering tree of pig tissue samples according to mRNA expression data. Heat map of miRNA specifically expressed in heart atrium and ventricle. Arrows indicate most up-regulated miRNA. Heat map of the miRNAs specifically expressed in white blood cells.

Grey squares indicate expression below the limit of detection. Many miRNAs are expressed across several tissues, but large sets of miRNAs were found to have, instead, a tissue-specific expression. Five different clusters of miRNAs appear to be restricted to white blood cells, myocardium, skeletal muscle, adipose tissue and liver respectively. Hereafter we discuss the miRNA clusters specific for white blood cells WBC and myocardium because of the importance of these two tissues in cardiocirculatory system [57].

Despite structural and functional similarities with human myocardium and the wide use of pig heart valves in cardiovascular surgery [58] , [59] , there are few genome-wide experimental identifications of miRNAs in the pig heart [60]. Our analysis identified a cluster of miRNAs preferentially expressed in atrium and ventricle with some overlap with those expressed in the stomach Figure 4 C.

Many components of this cluster are pig-specific miRNAs, and the most up-regulated is mirb, which appears to have an important role in heart function because it was found under-expressed in the ischemic reperfused myocardium in the rat model [61]. This family is expressed as polycistronic units, revealing a common regulatory mechanism [62] , that is confirmed by the similarity of their expression profiles Figure 4 D. This family is prevalently involved in different lymphomas [63] and its downregulation is associated with disease progression and poor prognosis of these tumors [64].

Expression was monitored by microarray RAKE on 14 different pig tissues for tissue symbols see description in the caption of figure 4. The color intensity scale reported on top of the heat maps is proportional to the concentration of miRNAs and varies from black low concentration to bright yellow 14 pM concentrated.

Gray squares indicate concentration under detection limit. MicroRNA identifications are composed of features letters and numbers divided by underscores as explained below. The first feature is the miRNA name and could be P standing for predicted and referring to the de-novo identification , the Ensembl, or the Ver. The second feature indicates the chromosome number where the pre-miRNA is located.

The third and fourth features indicate the start and stop nucleotide positions of pre-miRNAs in the pig genome. The sixth feature 3p or 5p distinguishes the two arms of pre-miRNA hairpins. V and L. Tissue-specific expression studies of microRNA provide clues for the regulatory mechanisms that regulate their expression but the comprehension of their function is facilitated by the discovery and association with their correct mRNA targets.

To this aim, a new microarray platform was developed to obtain the profiles of all large RNA transcripts in pig tissues to be integrated with miRNA profiles. For each transcript with a duplicated probe, we selected the probe that was more responsive and specific on the basis of intensity of fluorescence in the hybridization test, as suggested by Kronick [65].

The definitive pig whole-genome microarray here used for gene expression analysis is composed of i 17, replicated probes and unique probes specific for Ensembl transcripts, ii 11, replicated probes specific for UniGene clusters of length comprised between and 1, nt, and iii 28, unique probes specific for the remaining UniGene clusters. As a result, With this design procedure, we were not able to produce specific probes for UniGene clusters and 1, Ensembl transcripts.

To overcome the still poor gene annotation of the pig genome, we tried to increase the number of annotated features on the microarray by mining description and protein annotations to associate to our probes. Basically, for those whom HUGO symbol was not present we mined the description available from Unigene database and retrieved if present additional gene or protein IDs.

A major limitation in the network analysis of genetic circuits is the unavailability of mRNA and miRNA profiles from the same sample. The present study overcomes this limitation and provides fully compatible datasets for developing new algorithms, other than those published [66] , to detect modulation of target mRNA expression by miRNAs.

Our objective was to identify miRNA and mRNA expression patterns that may contribute to maintain tissue functionality and specificity. All networks evidence a bipartite structure and dash line indicates bipartition point. The most complex network we identified was that related to tissues involved in inflammatory responses. It can be deconstructed in at least 18 functional modules. Module 1 is made by nodes and edges Figure 7 A and, according to gene ontology analysis, it describes cell homeostasis through autophagy process.

The subject of the second permissive module Figure 7 B , 73 nodes and edges can be described as the transcription regulation in inflammatory cells. An interesting gene of this module is PLBD1 that codify for a phospholipase B precursor purified from normal granulocytes [70]. The expression of this gene appears to be connected in the module with 8 different miRNAs whose expression level is anti-correlated.

The third module 48 nodes and 68 edges contains different inflammatory pathways like those related to Toll-like receptor, NF-kB signaling and apoptosis Figure 7 C. Module 1 describes cell homeostasis through autophagy process.

Module 2 can be described as the transcription regulation in inflammatory cells. An interesting gene of this module is PLBD1 arrow that codify for a phospholipase B precursor purified from normal granulocytes. The expression of this gene appears to be modulated in the module by 8 different miRNAs whose expression level is anti-correlated with that of the gene.

Module 3 that contains different inflammatory pathways like those related to Toll-like receptor, NF-kB signaling and apoptosis. We generally noted that miRNAs highly expressed in well-differentiated tissues, where the protein turnover is relatively slow, control processes associated with regeneration and proliferation. For example, positive regulation of apoptosis and developmental pathways are biological functions enriched enrichment score 2. Other significantly enriched categories are those describing the positive regulation of T cell activation, regulation of cell cycle and striated muscle cell differentiation enrichment score are 1.

Another example of this relationship is given by the network related to heart. Regeneration ability is not maintained for this organ in the adult life [71] , and in fact our results show that miRNAs highly expressed in heart are those related to and thus inhibiting ubiquitin-dependent catabolic processes and proteolysis enrichment score 4. Conversely, up-regulated transcripts of the heart connected to downregulated miRNAs in the permissive network are involved prevalently in the maintenance of protein folding, cell vitality and mitochondrion respiration Chaperon function, enrichment score 8.

In skeletal muscle, the permissive network is enriched with transcripts coding for proteins involved in muscle contraction and in sarcomeric Z-disc structure Table P in Table S9 and shows a high anti-correlation with a group of miRNAs. Moreover, some important genes of the heart, such as the Ras-related associated with diabetes RRAD , which may play an important role in cardiac antiarrhythmia [72] , the ubiquinol-cytochrome c reductase core protein I UQCRC1 , which is involved in cardiomyopathies, and the solute carrier family 25 mitochondrial carrier; phosphate carrier , member 3 SLC25A3 , whose deficiency is associated with hypertrophic cardiomyopathy [73] are inversely correlated with the expression of different miRNAs.

The comparison of permissive networks for skeletal muscle and heart evidences that the heart specific network is characterized by genes involved in the formation of adherent junctions. In conclusion, trough the integration of the interaction maps from the BioGRID database [74] and transcripts inferred as miRNA targets we produced networks that summarize the molecular interactions controlling the steady states of pig tissue in normal conditions.

According to the guidelines for miRNA annotation [75] , a putative miRNA sequence should be supported by data demonstrating its evolutionary conservation and by evidence of expression in order to be recognized as a genuine miRNA. The collection of miRNAs presented here is supported by stringent bioinformatic criteria. Interestingly, the number of conserved miRNAs is related to the phylogenic distance between S. This indicates that miRNA functional role is maintained across phylogenetically close species, while species-specific miRNAs with their peculiar function may be lost during evolution.

We also adopted stringent criteria to experimentally validate the predicted miRNAs. RAKE and deep sequencing experiments allowed the identification of hairpins high confidence that maturate functional miRNAs. Interestingly, with this approach we showed that different pre-miRNAs, in addition to those defined as highly confident, allow miRNA maturation.

This demonstrates the stringency of the criteria adopted to produce our regulatory networks, where only fully validated miRNAs were considered and the interactions did not needed to be weighted down for false positive miRNAs. MiRNA microarrays allow for massive parallel and relative measurement of all known miRNAs, but they cannot be used for absolute quantification. In fact, the short length of miRNAs makes difficult the proper selection of complementary probes that result in a high dynamic range of melting temperatures.

Here we developed a new method that integrates the hybridization of miRNAs to a specific microarray with an enzymatic elongation reaction that can take place only after the establishment of a perfect match between miRNA and probe. Moreover, we introduced oligonucleotide spikes in the hybridization and enzymatic reaction, allowing the relative quantification of miRNAs and avoiding biases related to sequence, labeling, or hybridization.

An alternative method for the absolute quantization of miRNAs was recently proposed [76]. The performance of our method is independent from sequence differences because the labeling reaction that generates the signal for the positive hybridization of a miRNA molecule to a perfectly matching probe is due to the incorporation, by the Klenow enzyme, of labeled adenosines biotin-dATP and not to an enzymatic process performed before the hybridization.

The correlation between qRT-PCR and microarray expression was good demonstrating that profiles across different tissues through our microarray technique, based on a titration curve quantization, is reliable in measuring different miRNA expression across samples.

In fact, four highly expressed heart-specific miRNAs were chosen for these validations. The association of putative mRNA targets to these heart miRNAs shows that they are enriched for transcripts codifying ubiquitin protein ligases, enzymes that are active in protein catabolism mediated by the proteasome. The inhibition of cardiac proteasome is cardioprotective [53] , [77] and, as stated by May and colleagues [77] , proteasome inhibition, and also the miRNAs involved in this process that we evidenced, could provide new therapeutic strategies to prevent cardiac fibrosis and progression of heart failure.

The RAKE method allowed us to analyze the expression signatures of 14 different pig tissues. They cluster according to anatomical proximity and functional similarity. Moreover, miRNA clusters are preferentially expressed in a tissue-specific manner suggesting a role for these miRNAs in the maintenance of specific molecular processes in the considered tissue Figure 4. Some of the identified clusters are discussed below.

Recently, pig and human pathologies have been linked by the discovery that the H1N1 strain of influenza virus is able to infect humans with potential pandemic effects [78]. Therefore, it would be important to understand the immune system of these mammals and the molecular mechanisms that lead to viral infection.

Moreover, the identification of miRNAs prevalently expressed in WBCs could be useful in the identification of immunological mechanisms that are important for the butchering industries. The over-expression of mir, 18, 19a, and 20 was demonstrated in tumors of the lung [79] and a second study reported the up-regulation of the miR cluster in B-cell lymphomas [62]. We found, on the contrary, that mir, 18, and 20a are not expressed in normal lung Figure 4 D.

Taken together, these data support the importance of these miRNAs for the function of the immune system. The study of these miRNAs could be a good basis for the identification and analysis of potential immuno-modulatory effectors in immuno-mediated diseases like multiple sclerosis, where a down-regulation of miR and miRa associated with T-cell activation was demonstrated [80] , or like inflammatory myopathies.

A possible important advancement in this topic will be the identification of interactions between the miRNAs of these paralogue families and their targets. The proximity between myocardial and smooth muscles can be explained by their common properties. Smooth muscle forms the major contractile elements of the viscera, especially those of the respiratory and digestive tracts, the blood vessels, and the stomach wall. Cardiac muscle has many properties in common with smooth muscle. For example, it is innervated by the autonomous system and contract spontaneously.

Presumably, cardiac muscle evolved as a specialized type from the general smooth muscle of the circulatory vessels [81]. This could explain the similarity of miRNA profiles of atrium and ventricle. The presence of the tongue-specific miRNAs in the same contractile cluster Figure 4 A can be explained by the fact that this organ is mainly composed of striated muscles 16 different.

Here we integrated mRNA and miRNA signatures obtained from the same tissue sample, establishing tissue-specific circuits and discussing their possible integration and regulation. A new microarray platform was developed, containing the best probes that are able to detect the whole pig transcriptome. Recently, a new microarray platform was published based on 52, expressed sequences comprising miRNAs in miRBase ver.

We think that our platform is more suitable for expression studies in the pig. A growing number of studies have assigned to miRNAs a fundamental role in the regulation of a variety of cell processes, and many of those identified in this study are well-positioned to regulate gene expression in different pig tissues as they presented a negative correlation with the expression of their predicted targets.

Several observations showed that miRNAs are essential for the normal development of mammals. Here, we suggest that they are also important in the maintenance of normal tissue function. For example, we found that genes involved positive regulation of apoptosis and developmental pathways are targeted by miRNAs in the skeletal muscle Table M in Table S9. We reason that in adult skeletal muscle there is no need for constant expression of important transcription factors and proteins involved in chromatin regulation that are expressed during muscle development.

In the heart, where the regenerative process is limited because heart muscle cells are terminally differentiated, the importance of cell structure maintenance is fundamental. From our analyses it appears that heart muscle cells control the protein degradation pathway trough ubiquitinization by upregulating miRNAs targeting mRNAs for ubiquitinating enzymes and activating chaperons to control protein folding Table N in Table S9.

Inhibition of the cardiac proteasome has been shown to be cardioprotective under some circumstances, indicating the clinical potential for understanding its function [53]. Among miRNAs preferentially expressed in the heart Figure 4 mira, mir, and mir are particularly important.

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