Evaluation of the capability of the PCV2 genome to encode miRNAs : lack of viral miRNA expression in an experimental infection

Porcine circovirus type 2 (PCV2) is a ssDNA virus causing PCV2-systemic disease (PCV2-SD), one of the most important diseases in swine. MicroRNAs (miRNAs) are a new class of small non-coding RNAs that regulate gene expression post-transcriptionally. Viral miRNAs have recently been described and the number of viral miRNAs has been increasing in the past few years. In this study, small RNA libraries were constructed from two tissues of subclinically PCV2 infected pigs to explore if PCV2 can encode viral miRNAs. The deep sequencing data revealed that PCV2 does not express miRNAs in an in vivo subclinical infection

Endometrial gene expression profile of pregnant sows with extreme phenotypes for reproductive efficiency

Prolificacy can directly impact porcine profitability, but large genetic variation and low heritability have been found regarding litter size among porcine breeds. To identify key differences in gene expression associated to swine reproductive efficiency, we performed a transcriptome analysis of sows' endometrium from an Iberian x Meishan F2 population at day 30-32 of gestation, classified according to their estimated breeding value (EBV) as high (H, EBV > 0) and low (L, EBV < 0) prolificacy phenotypes. For each sample, mRNA and small RNA libraries were RNA-sequenced, identifying 141 genes and 10 miRNAs differentially expressed between H and L groups. We selected four miRNAs based on their role in reproduction, and five genes displaying the highest differences and a positive mapping into known reproductive QTLs for RT-qPCR validation on the whole extreme population. Significant differences were validated for genes: PTGS2 (p = 0.03; H/L ratio = 3.50), PTHLH (p = 0.03; H/L ratio = 3.69), MMP8 (p = 0.01; H/L ratio = 4.41) and SCNN1G (p = 0.04; H/L ratio = 3.42). Although selected miRNAs showed similar expression levels between H and L groups, significant correlation was found between the expression level of ssc-miR-133a (p < 0.01) and ssc-miR-92a (p < 0.01) and validated genes. These results provide a better understanding of the genetic architecture of prolificacy-related traits and embryo implantation failure in pigs

The role of viral and host microRNAs in the Aujeszky's disease virus during the infection process

Porcine production is a primary market in the world economy. Controlling swine diseases in the farm is essential in order to achieve the sector necessities. Aujeszky's disease is a viral condition affecting pigs and is endemic in many countries of the world, causing important economic losses in the swine industry. microRNAs (miRNAs) are non-coding RNAs which modulates gene expression in animals, plants and viruses. With the aim of understanding miRNA roles during the Aujeszky's disease virus [ADV] (also known as suid herpesvirus type 1 [SuHV-1]) infection, the expression profiles of host and viral miRNAs were determined through deep sequencing in SuHV-1 infected porcine cell line (PK-15) and in an animal experimental SuHV-1 infection with virulent (NIA-3) and attenuated (Begonia) strains. In the in vivo approach miR-206, miR-133a, miR-133b and miR-378 presented differential expression between virus strains infection. In the in vitro approach, most miRNAs were down-regulated in infected groups. miR-92a and miR-92b-3p were up-regulated in Begonia infected samples. Functional analysis of all this over expressed miRNAs during the infection revealed their association in pathways related to viral infection processes and immune response. Furthermore, 8 viral miRNAs were detected by stem loop RT-qPCR in both in vitro and in vivo approaches, presenting a gene regulatory network affecting 59 viral genes. Most described viral miRNAs were related to Large Latency Transcript (LLT) and to viral transcription activators EP0 and IE180, and also to regulatory genes regarding their important roles in the host-pathogen interaction during viral infection

Identification of microRNAs in PCV2 subclinically infected pigs by high throughput sequencing

Porcine circovirus type 2 (PCV2) is the essential etiological infectious agent of PCV2-systemic disease and has been associated with other swine diseases, all of them collectively known as porcine circovirus diseases. MicroRNAs (miRNAs) are a new class of small non-coding RNAs that regulate gene expression post-transcriptionally. miRNAs play an increasing role in many biological processes. The study of miRNA-mediated host-pathogen interactions has emerged in the last decade due to the important role that miRNAs play in antiviral defense. The objective of this study was to identify the miRNA expression pattern in PCV2 subclinically infected and non-infected pigs. For this purpose an experimental PCV2 infection was carried out and small-RNA libraries were constructed from tonsil and mediastinal lymph node (MLN) of infected and non-infected pigs. High throughput sequencing determined differences in miRNA expression in MLN between infected and non-infected while, in tonsil, a very conserved pattern was observed. In MLN, miRNA 126-3p, miRNA 126-5p, let-7d-3p, mir-129a and mir-let-7b-3p were up-regulated whereas mir-193a-5p, mir-574-5p and mir-34a down-regulated. Prediction of functional analysis showed that these miRNAs can be involved in pathways related to immune system and in processes related to the pathogenesis of PCV2, although functional assays are needed to support these predictions. This is the first study on miRNA gene expression in pigs infected with PCV2 using a high throughput sequencing approach in which several host miRNAs were differentially expressed in response to PCV2 infection

Genetic and molecular basis of reproductive efficiency in swine

En els darrers anys, la caracterització del transcriptoma s'ha convertit en un tema candent a la recerca genòmica, ja sigui en humans o en animals. En aquests últims, els avanços en transcriptòmica tenen com a principal objectiu entendre millor els caràcters amb major impacte econòmic. Una de les espècies més importants en la producció ramadera és la porcina. Els caràcters reproductius com la prolificitat poden afectar directament la seva rendibilitat, però la gran variabilitat genètica existent entre races porcines i la baixa heretabilitat d'aquest caràcter han fet de la seva selecció tot un repte. Això posa de manifest la importància d'estudiar les interaccions gèniques i els mecanismes de regulació que afecten el tamany final de la camada en aquesta espècie. En aquesta tesi, oferim una visió global del transcriptoma de l'endometri de dues races porcines que difereixen significativament en els seus nivells de prolificitat, donant una llista de més d'un centenar de gens diferencialment expressats la funció dels quals està associada amb etapes crítiques per a la supervivència embrionària durant la gestació. Aquestes diferències d'expressió han estat validades per 12 gens que constitueixen una llista de nous candidats a exercir un paper clau en l'arquitectura genètica de caràcters relacionats amb l'eficiència reproductiva en el porc. Donat que les microRNAs (miRNAs) són coneguts reguladors post-transcripcionals de l’expressió génica, vam pensar que les diferències observades en el nivell d'expressió d'aquests gens podia respondre a un patró d'expressió de microRNAs diferent. Per validar aquesta hipòtesi, es va analitzar el perfil d'expressió de miRNAs en l'endometri de truges gestants amb nivells de prolificidad divergents, identificant 10 miRNAs madurs diferencialment expressats. Tot i que després de la seva quantificació relativa els nivells d'aquests microRNAs van resultar ser similars, es van trobar correlacions significatives entre l'expressió dels miRNAs ssc-miR-92a i ssc-miR-133a i els gens candidats MMP8, PTGS2, PTHLH i SCNN1G. A més, es va dur a terme la caracterització funcional de nou miRNAs altament implicats en reproducció identificant un total de 13 polimorfismes (SNPs) a les seves seqüències precursores. Per determinar l'efecte d'aquestes variants en l'eficiència reproductiva de les truges, es va realitzar un estudi d'associació que va revelar que el genotip per a les variants identificades a la seqüència de ssc-mir-27a, ssc-mir-29b-2 i ssc-mir-106 era determinant tant per als nivells d'expressió del miRNA madur com per als valors d’EBV. Aquests resultats suggerien que les variants genètiques a la seqüència de miRNAs precursors juguen un paper clau en els caràcteres relacionades amb la reproducció porcina. Finalment, es va dur a terme la validació funcional de la regulació dels gens ADM, HTRA3, PTHLH i VEGFA per part dels seus microRNAs diana ssc-miR-181d-5p, ssc-miR-101-3p, ssc-miR-144 i ssc-miR-195-5p respectivament, que ens va permetre establir una relació directa entre aquestes interaccions i una disminució en els seus nivells d'expressió.In recent years, transcriptome characterization has seen a remarkable rise, becoming a hot topic in genomic research either in human or animal genetics. In this last, advances in transcriptomics have addressed the goal to better understand those traits with higher economic impact. One of the most important species in livestock production are pigs. Reproductive traits such as prolificacy can directly impact porcine profitability, but large genetic variation and low heritability have been found regarding litter size among porcine breeds. This highlights the importance to perform expression profiling experiments in porcine breeds with extreme prolificacy phenotypes, to better understand those gene interactions and regulatory mechanisms affecting litter size in pigs. In this thesis, we provide a global view of the endometrial transcriptome of two porcine breeds that differ significantly in their prolificacy levels, giving a list of more than one hundred differentially expressed genes associated with critical steps of embryonic survival during sow’s gestation. These expression differences have been validated for 12 genes providing a list of new candidate genes that may play key role on the genetic architecture of prolificacy-related traits in pigs. We hypothesized that the observed differences in the expression level of these genes between Iberian x Meishan F2 sows with divergent prolificacy phenotypes might respond to a different expression pattern of microRNAs (miRNAs), known to function as post-transcriptional down-regulators of gene expression. To validate this hypothesis, we explored the endometrial miRNA expression profile by RNA-seq identifying 10 differentially expressed miRNAs. Expression levels appear to be similar after relative quantification, despite significant correlations were found between the expression of ssc-miR-92a and ssc-miR-133a and candidate genes MMP8, PTGS2, PTHLH and SCNN1G. We functionally characterized nine reproduction-related miRNAs identifying a total of 13 SNPs in their precursor sequences. To determine the effect of these variants in the reproductive efficiency of the pregnant sows, we performed an association study that revealed that the genotype for the variants in ssc-mir-27a, ssc-mir-29b-2 and ssc-mir-106a was determinant for the mature miRNA expression levels and the EBVs. Finally, a functional validation of the miRNA-mediated regulation of ADM, HTRA3, PTHLH and VEGFA upon they target miRNAs ssc-miR-181d-5p, ssc-miR-101-3p, ssc-miR-144 and ssc-miR-195-5p respectively, allowed us to find a direct relationship between these interactions and decreased levels of gene expression

Determination of reference microRNAs for relative quantification in porcine tissues.

Relative quantification is the strategy of choice for processing RT-qPCR data in microRNAs (miRNAs) expression studies. Normalisation of relative quantification data is performed by using reference genes. In livestock species, such as pigs, the determination of reference miRNAs and the optimal number of them has not been widely studied. In this study, the stability of ten miRNAs (Ssc-let-7a, Ssc-miR-103, Ssc-miR-17-3p, Hsa-miR-25, Hsa-miR-93, Ssc-miR-106a, Ssc-miR-191, Ssc-miR-16, Ssc-miR-26a and Ssc-miR-17-5p) was investigated by RT-qPCR in different tissues (skeletal muscle, kidney, liver, ovary and uterus) and in different pig breeds (Iberian, Landrace, Large White, Meishan and Vietnamese) as variation factors. Stability values were calculated with geNorm and NormFinder algorithms obtaining high correlation between them (r(2) = 0.99). The analyses showed that tissue is an important variability factor in miRNAs expression stability whereas breed is not a determinant factor. All ten miRNAs analysed had good stability values and, therefore, can be used as reference miRNAs. When all tissues were considered, miR-93 was the most stable miRNA. Dividing data set by tissues, let-7a was the most stable in skeletal muscle and ovary, miR-17-5p in kidney, miR-26a in liver and miR-103 in uterus. Moreover, the optimal number of reference miRNAs to be used for proper normalisation data was determined. It is suggested the use of five reference miRNAs (miR-93, miR-25, miR-106a, miR-17-5p and miR-26a) in multi-tissue experimental designs and the use of three reference miRNAs as the optimal number in single tissues studies (let-7a, miR-17-5p and miR-25 in skeletal muscle; miR-17-5p, miR-93 and miR-26a in kidney, miR-26a, miR-103 and let-7a in liver, let-7a, miR-25 and miR-106a in ovary and miR-103, let-7a and miR-93 in uterus). Overall, this study provides valuable information about the porcine reference miRNAs that can be used in order to perform a proper normalisation when relative quantification by RT-qPCR studies is undertaken

Endometrial gene expression profile of pregnant sows with extreme phenotypes for reproductive efficiency

Prolificacy can directly impact porcine profitability, but large genetic variation and low heritability have been found regarding litter size among porcine breeds. To identify key differences in gene expression associated to swine reproductive efficiency, we performed a transcriptome analysis of sows’ endometrium from an Iberian x Meishan F2 population at day 30–32 of gestation, classified according to their estimated breeding value (EBV) as high (H, EBV > 0) and low (L, EBV < 0) prolificacy phenotypes. For each sample, mRNA and small RNA libraries were RNA-sequenced, identifying 141 genes and 10 miRNAs differentially expressed between H and L groups. We selected four miRNAs based on their role in reproduction and five genes displaying the highest differences and a positive mapping into known reproductive QTLs for RT-qPCR validation on the whole extreme population. Significant differences were validated for genes: PTGS2 (p = 0.03; H/L ratio = 3.50), PTHLH (p = 0.03; H/L ratio = 3.69), MMP8 (p = 0.01; H/L ratio = 4.41) and SCNN1G (p = 0.04; H/L ratio = 3.42). Although selected miRNAs showed similar expression levels between H and L groups, significant correlation was found between the expression level of ssc-miR-133a (p < 0.01) and ssc-miR-92a (p < 0.01) and validated genes. These results provide a better understanding of the genetic architecture of prolificacy-related traits and embryo implantation failure in pigs.This research was funded by the projects AGL2004–08368-C03, AGL2010-22358-C02-01 and by the Consolider-Ingenio 2010 Programme (CSD2007-00036) all from the Spanish Ministry of Economy and Competitiveness. The authors are also indebted to INRA (France) and the CIA El Dehesón del Encinar (Spain) for providing the purebred Meishan sows and Iberian boars, respectively. Funding: This research was funded by the Science and Innovation Ministry of the Spanish Government (projects AGL2010-22358-C02-01 and AGL2004–08368-C03) and also by the Consolider-Ingenio 2010 Programme (CSD2007-00036). SC is a recipient of an FPI PhD fellowship from the Science and Innovation Ministry of the Spanish Government.Peer reviewe

Correlation between M-value (geNorm¹) and stability value (NormFinder²) in the general data set.

<p>¹: <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044413#pone.0044413-Vandesompele1" target="_blank">[17]</a>, ²: <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044413#pone.0044413-Andersen1" target="_blank">[33]</a> A very good correlation between the two approximations confirms the robustness and the credibility of our results.</p

Stability values of each reference miRNA from geNorm¹ and NormFinder² algorithms.

<p>¹: <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044413#pone.0044413-Vandesompele1" target="_blank">[17]</a>, ²: <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044413#pone.0044413-Andersen1" target="_blank">[33]</a>. Continuous lines: M-value from geNorm software; dashed lines: stability value from NormFinder software. Black lines: general study, blue lines: kidney, red lines: ovary, green lines: uterus, orange lines: skeletal muscle, purple lines: liver.</p