Although many genes have been identified using high throughput technologies in endometriosis (ES), only a small number of individual genes have been analyzed functionally. This is due to the complexity of the disease that has different stages and is affected by various genetic and environmental factors. Many genes are upregulated or downregulated at each stage of the disease, thus making it difficult to identify key genes. In addition, little is known about the differences between the different stages of the disease. We assumed that the study of the identified genes in ES at a system-level can help to better understand the molecular mechanism of the disease at different stages of the development. We used publicly available microarray data containing archived endometrial samples from women with minimal/mild endometriosis (MMES), mild/severe endometriosis (MSES) and without endometriosis. Using weighted gene co-expression analysis (WGCNA), functional modules were derived from normal endometrium (NEM) as the reference sample. Subsequently, we tested whether the topology or connectivity pattern of the modules was preserved in MMES and/or MSES. Common and specific hub genes were identified in non-preserved modules. Accordingly, hub genes were detected in the non-preserved modules at each stage. We identified sixteen co-expression modules. Of the 16 modules, nine were non-preserved in both MMES and MSES whereas five were preserved in NEM, MMES, and MSES. Importantly, two non-preserved modules were found in either MMES or MSES, highlighting differences between the two stages of the disease. Analyzing the hub genes in the non-preserved modules showed that they mostly lost or gained their centrality in NEM after developing the disease into MMES and MSES. The same scenario was observed, when the severeness of the disease switched from MMES to MSES. Interestingly, the expression analysis of the new selected gene candidates including CC2D2A, AEBP1, HOXB6, IER3, and STX18 as well as IGF-1, CYP11A1 and MMP-2 could validate such shifts between different stages. The overrepresented gene ontology (GO) terms were enriched in specific modules, such as genetic disposition, estrogen dependence, progesterone resistance and inflammation, which are known as endometriosis hallmarks. Some modules uncovered novel co-expressed gene clusters that were not previously discovered.
RNA editing increases the diversity of the transcriptome and proteome. Adenosine-to-inosine (A-to-I) editing is the predominant type of RNA editing in mammals and it is catalyzed by the adenosine deaminases acting on RNA (ADARs) family. Here, we used a largescale computational analysis of transcriptomic data from brain, heart, colon, lung, spleen, kidney, testes, skeletal muscle and liver, from three adult animals in order to identify RNA editing sites in bovine. We developed a computational pipeline and used a rigorous strategy to identify novel editing sites from RNA-Seq data in the absence of corresponding DNA sequence information. Our methods take into account sequencing errors, mapping bias, as well as biological replication to reduce the probability of obtaining a false-positive result. We conducted a detailed characterization of sequence and structural features related to novel candidate sites and found 1,600 novel canonical A-to-I editing sites in the nine bovine tissues analyzed. Results show that these sites 1) occur frequently in clusters and short interspersed nuclear elements (SINE) repeats, 2) have a preference for guanines depletion/enrichment in the flanking 5′/3′ nucleotide, 3) occur less often in coding sequences than other regions of the genome, and 4) have low evolutionary conservation. Further, we found that a positive correlation exists between expression of ADAR family members and tissue-specific RNA editing. Most of the genes with predicted A-to-I editing in each tissue were significantly enriched in biological terms relevant to the function of the corresponding tissue. Lastly, the results highlight the importance of the RNA editome in nervous system regulation. The present study extends the list of RNA editing sites in bovine and provides pipelines that may be used to investigate the editome in other organisms.
Fat-tail content of sheep breeds is varied and the molecular mechanisms regulating fat-tail development have not been well characterized. Aiming at better identifying the important candidate genes and their functional pathways contributing to fat deposition in the tail, a comparative transcriptome analysis was performed between fat- (Lori-Bakhtiari) and thin-tailed (Zel) Iranian sheep breeds using RNA-seq. The experiment was conducted on six male lambs (three lambs per each breed) at seven months of age. Four different combinations of aligners and statistical methods including Hisat2 + edgeR, Hisat2 + DESeq2, STAR + edgeR and STAR + DESeq2 were used to identify the differentially expressed genes (DEGs). The DEGs were selected for functional enrichment analysis and protein-protein interaction (PPI) network construction. Module analysis was also conducted to mine the functional sub-networks from the PPI network. In total, 264 genes including 80 up- and 184 down-regulated genes were identified as DEGs. The RNA-Seq results were validated by Q-RT-PCR. Functional analysis of DEGs and the module analysis of PPI network demonstrated that in addition to pathways affecting lipid metabolism, a series of enriched functional terms related to “response to interleukin”, “MAPK signaling pathways”, “Wnt signaling pathway”, “ECM-receptor interaction”, “regulation of actin cytoskeleton”, and “response to cAMP” might contribute to the deposition of fat in tails of sheep. Overall results using RNA-Seq analysis characterized important candidate genes involved in the fatty acid metabolism and regulation of fat deposition, suggesting novel insights into molecular aspects of fat-tail metabolism in sheep. Selected DEGs should be further investigated as potential markers associated with the fat-tail development in sheep breeds.
Emerging evidence suggests that long non-coding RNAs (lncRNAs) participate in the regulation of a diverse range of biological processes. However, most studies have been focused on a few established model organisms and little is known about lncRNAs in fat-tail development in sheep. Here, the first profile of lncRNA in sheep fat-tail along with their possible roles in fat deposition were investigated, based on a comparative transcriptome analysis between fat-tailed (Lori-Bakhtiari) and thin-tailed (Zel) Iranian sheep breeds. Among all identified lncRNAs candidates, 358 and 66 transcripts were considered novel intergenic (lincRNAs) and novel intronic (ilncRNAs) corresponding to 302 and 58 gene loci, respectively. Our results indicated that a low percentage of the novel lncRNAs were conserved. Also, synteny analysis identified 168 novel lincRNAs with the same syntenic region in human, bovine and chicken. Only seven lncRNAs were identified as differentially expressed genes between fat and thin tailed breeds. Q-RT-PCR results were consistent with the RNA-Seq data and validated the findings. Target prediction analysis revealed that the novel lncRNAs may act in cis or trans and regulate the expression of genes that are involved in the lipid metabolism. A gene regulatory network including lncRNA-mRNA interactions were constructed and three significant modules were found, with genes relevant to lipid metabolism, insulin and calcium signaling pathway. Moreover, integrated analysis with AnimalQTLdb database further suggested six lincRNAs and one ilncRNAs as candidates of sheep fat-tail development. Our results highlighted the putative contributions of lncRNAs in regulating expression of genes associated with fat-tail development in sheep.
The use of assisted reproductive technologies (ART) can induce a congenital overgrowth condition in humans and ruminants, namely Beckwith-Wiedemann syndrome (BWS) and large offspring syndrome (LOS), respectively. Shared phenotypes and epigenotypes have been found between BWS and LOS. We have observed global misregulation of transcripts in bovine foetuses with LOS. microRNAs (miRNAs) are important post-transcriptional gene expression regulators. We hypothesize that there is miRNA misregulation in LOS and that this misregulation is shared with BWS. In this study, small RNA sequencing was conducted to investigate miRNA expression profiles in bovine and human samples. We detected 407 abundant known miRNAs and predicted 196 putative miRNAs from the bovine sequencing results and identified 505 abundant miRNAs in human tongue. Differentially expressed miRNAs (DE-miRNAs) were identified between control and LOS groups in all tissues analysed as well as between BWS and control human samples. DE-miRNAs were detected from several miRNA clusters including DLK1-DIO3 genomic imprinted cluster in LOS and BWS. DNA hypermethylation was associated with downregulation of miRNAs in the DLK1-DIO3. mRNA targets of the DE-miRNAs were predicted and signalling pathways associated with control of organ size (including the Hippo signalling pathway), cell proliferation, apoptosis, cell survival, cell cycle, and cell adhesion were found to be enriched with these genes. Yes associated protein 1 (YAP1) is the core effector of the Hippo signalling pathway, and increased level of active (non-phosphorylated) YAP1 protein was detected in skeletal muscle of LOS foetuses. Overall, our data provide evidence of miRNA misregulation in LOS and BWS.
Genetic basis of fat deposition in sheep tail have not been completely elucidated yet. Understanding the genetic mechanisms controlling fat-tail size can improve breeding strategies to modulate fat deposition. RnA sequencing has made it possible to discover genetic variants that may underlie various phenotypic differences. Hence, to identify genetic variants that are important for describing different fat-tail phenotypes in sheep, RNA sequencing was used for single nucleotide polymorphism (SNP) calling in two Iranian sheep breeds (Lori-Bakhtiari, fat-tailed; n = 4, vs Zel, thin-tailed; n = 4). Using a stringent pipeline, a total of 112,344 known SNPs were genotyped, of which 30,550 and 42,906 SNPs were shared by at least two Lori-Bakhtiari and Zel, respectively. Comparing these SNPs showed 2,774 (including 209 missense and 25 deleterious SNPs) and 10,470 (including 1,054 missense and 116 deleterious SNPs) breed-specific SNPs in Lori-Bakhtiari and Zel sheep, respectively. Potential breed-specific SNPs were detected by considering those located in QTL regions associated with fatness or reported as important candidates in previous similar studies. Of the breed-specific SNPs, 724 and 2,905 were located in the QTL regions. Functional enrichment analysis of the affected genes revealed several enriched gene ontologies and KeGG pathways related to fat metabolism. Based on the results, several affected genes were proposed to be strongly linked with fat deposition such as DGAT2,
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