Academic literature on the topic 'MiRNA reference gene selection'
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Journal articles on the topic "MiRNA reference gene selection"
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Lyu, Shiheng, Ying Yu, Shirong Xu, Weiwei Cai, Guixin Chen, Jianjun Chen, Dongming Pan, and Wenqin She. "Identification of Appropriate Reference Genes for Normalizing miRNA Expression in Citrus Infected by Xanthomonas citri subsp. citri." Genes 11, no. 1 (December 23, 2019): 17. http://dx.doi.org/10.3390/genes11010017.
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MicroRNAs (miRNAs) are short noncoding RNA molecules that regulate gene expression at the posttranscriptional level. Reverse transcription-quantitative PCR (RT-qPCR) is one of the most common methods used for quantification of miRNA expression, and the levels of expression are normalized by comparing with reference genes. Thus, the selection of reference genes is critically important for accurate quantification. The present study was intended to identify appropriate miRNA reference genes for normalizing the level of miRNA expression in Citrus sinensis L. Osbeck and Citrus reticulata Blanco infected by Xanthomonas citri subsp. citri, which caused citrus canker disease. Five algorithms (Delta Ct, geNorm, NormFinder, BestKeeper and RefFinder) were used for screening reference genes, and two quantification approaches, poly(A) extension RT-qPCR and stem-loop RT-qPCR, were used to determine the most appropriate method for detecting expression patterns of miRNA. An overall comprehensive ranking output derived from the multi-algorithms showed that poly(A)-tailed miR162-3p/miR472 were the best reference gene combination for miRNA RT-qPCR normalization in citrus canker research. Candidate reference gene expression profiles determined by poly(A) RT-qPCR were more consistent in the two citrus species. To the best of our knowledge, this is the first systematic comparison of two miRNA quantification methods for evaluating reference genes. These results highlight the importance of rigorously assessing candidate reference genes and clarify some contradictory results in miRNA research on citrus.
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Korma, Workneh, Adane Mihret, Azeb Tarekegn, Yunhee Chang, Dasom Hwang, Tesfaye Sisay Tessema, and Hyeyoung Lee. "Identification of Circulating miR-22-3p and miR-93-5p as Stable Endogenous Control in Tuberculosis Study." Diagnostics 10, no. 11 (October 23, 2020): 868. http://dx.doi.org/10.3390/diagnostics10110868.
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The diagnosis and prognosis of tuberculosis remains challenging and necessitates the development of a new test that can accurately diagnose and monitor treatment responses. In this regard, miRNA is becoming a potential diagnostic and prognostic biomarker which differentiates treatment respondents from non-respondents for various non-infectious and infectious diseases, including tuberculosis. The concentration of miRNAs varies based on cell type, disease, and site of infection, implicating that selection of an optimal reference gene is crucial, and determines the quantification of transcript level and biological interpretation of the data. Thus, the study evaluated the stability and expression level of five candidate miRNAs (let-7i-5p, let-7a-5p, miRNA-16-5p, miRNA-22-3p and miRNA-93-5p), including U6 Small Nuclear RNA (RNU6B) to normalize circulating miRNAs in the plasma of 68 participants (26 healthy controls, 23 latent, and 19 pulmonary tuberculosis infected) recruited from four health centers and three hospitals in Addis Ababa, Ethiopia. The expression levels of miRNAs isolated from plasma of culture confirmed newly diagnosed pulmonary tuberculosis patients were compared with latently infected and non-infected healthy controls. The qPCR data were analyzed using four independent statistical tools: Best Keeper, Genorm, Normfinder and comparative delta-Ct methods, and the data showed that miRNA-22-3p and miRNA-93-5p were suitable plasma reference miRNAs in a tuberculosis study.
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Buonpane, Christie, Guillermo Ares, Beshoy Benyamen, Carrie Yuan, and Catherine J. Hunter. "Identification of suitable reference microRNA for qPCR analysis in pediatric inflammatory bowel disease." Physiological Genomics 51, no. 5 (May 1, 2019): 169–75. http://dx.doi.org/10.1152/physiolgenomics.00126.2018.
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Pediatric inflammatory bowel disease (IBD) accounts for 10–15% of IBD and is associated with considerable morbidity for patients. Dysregulated microRNAs (miRNA, miR), small noncoding RNA molecules that modulate gene expression, have been the target of research in IBD diagnosis, surveillance, and therapy. Proper selection of reference genes, which are a prerequisite for accurate measurement of miRNA expression, is currently lacking. We hypothesize that appropriate normalization requires unique reference genes for different tissue and disease types. Through the study of 28 pediatric intestinal samples, we sought to create a protocol for selection of suitable endogenous reference genes. Candidate reference genes (miR-16, 193a, 27a, 103a, 191) were analyzed by RT-quantitative (q)PCR. Criteria used for designation of suitable reference genes were as follows: 1) ubiquitous: present in all tissue samples with quantification cycle value 15–35; 2) uniform expression: no differential expression between control and disease samples ( P > 0.05); 3) stability: stability value <0.5 by NormFinder. Our results suggest the use of miR-27a/191 for Crohn’s disease small bowel, none of the five candidate genes for Crohn’s disease colon, and miR-16/27a for ulcerative colitis. Additionally, target miR-874 had differential expression when normalized with different reference genes. Our results demonstrate that reference gene choice for qPCR analysis has a significant effect on study results and that proper data normalization is imperative.
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Yin, Zhimin, Fuliang Xie, Krystyna Michalak, Baohong Zhang, and Ewa Zimnoch-Guzowska. "Reference gene selection for miRNA and mRNA normalization in potato in response to potato virus Y." Molecular and Cellular Probes 55 (February 2021): 101691. http://dx.doi.org/10.1016/j.mcp.2020.101691.
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Ghanbari, Sogol, Adel Salimi, Saeid Rahmani, Nahid Nafissi, Ali Sharifi-Zarchi, and Seyed Javad Mowla. "miR-361-5p as a promising qRT-PCR internal control for tumor and normal breast tissues." PLOS ONE 16, no. 6 (June 8, 2021): e0253009. http://dx.doi.org/10.1371/journal.pone.0253009.
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Background One of the most widely used evaluation methods in miRNA experiments is qRT-PCR. However, selecting suitable internal controls (IC) is crucial for qRT-PCR experiments. Currently, there is no consensus on the ICs for miRNA qRT-PCR experiments in breast cancer. To this end, we tried to identify the most stable (the least expression alteration) and promising miRNAs in normal and tumor breast tissues by employing TCGA miRNA-Seq data and then experimentally validated them on fresh clinical samples. Methods A multi-component scoring system was used which takes into account multiple expression stability criteria as well as correlation with clinical characteristics. Furthermore, we extended the scoring system for more than two biological sub-groups. TCGA BRCA samples were analyzed based on two grouping criteria: Tumor & Normal samples and Tumor subtypes. The top 10 most stable miRNAs were further investigated by differential expression and survival analysis. Then, we examined the expression level of the top scored miRNA (hsa-miR-361-5p) along with two commonly used ICs hsa-miR-16-5p and U48 on 34 pairs of Primary breast tumor and their adjacent normal tissues using qRT-PCR. Results According to our multi-component scoring system, hsa-miR-361-5p had the highest stability score in both grouping criteria and hsa-miR-16-5p showed significantly lower scores. Based on our qRT-PCR assay, while U48 was the most abundant IC, hsa-miR-361-5p had lower standard deviation and also was the only IC capable of detecting a significant up-regulation of hsa-miR-21-5p in breast tumor tissue. Conclusions miRNA-Seq data is a great source to discover stable ICs. Our results demonstrated that hsa-miR-361-5p is a highly stable miRNA in tumor and non-tumor breast tissue and we recommend it as a suitable reference gene for miRNA expression studies in breast cancer. Additionally, although hsa-miR-16-5p is a commonly used IC, it’s not a suitable one for breast cancer studies.
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Sippl, Christoph, Louisa Schoeneberger, Fritz Teping, Walter Schulz-Schaeffer, Steffi Urbschat, Ralf Ketter, and Joachim Oertel. "Impact of MiRNA-181a2 on the Clinical Course of IDH1 Wild Type Glioblastoma." Processes 9, no. 5 (April 21, 2021): 728. http://dx.doi.org/10.3390/pr9050728.
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Background: Recently, miRNA-181a2 could be identified as a major regulator of IDH1 expression in fat tissue. The IDH1 gene, its mutation and expression have a major impact on overall survival in patients with glioblastoma. The presented study aimed to investigate the effect of miRNA-181a2 on IDH1 expression in glioblastoma and on the prognosis of patients suffering from, for example, a tumor. Methods: A total of 74 glioblastoma specimens were analyzed for the expression of miRNA-181a2, acquired as fold change, using qRT-PCR. IDH1 protein expression was estimated via mRNA quantification. Eight post mortal, non-glioma related brain tissue specimens served as the control group. The results were correlated with relevant demographic and clinical aspects of the cohort. A TCGA dataset was used as an independent reference. Results: MiRNA-181a2 was significantly downregulated in tumor samples compared to the control group (p < 0.001). In the glioblastoma cohort, 63/74 (85.1%) showed an IDH1 wild type, while 11/74 (14.9%) patients harbored an IDH 1 mutation. In patients with IDH1 wild type glioblastoma, low miRNA-181a2 expression correlated with a prolonged overall survival (p = 0.019), also verifiable in an independent TCGA dataset. This correlation could not be identified for patients with an IDH1 mutation. MiRNA-181a2 expression tended to correlate inversely with IDH1 protein expression (p = 0.06). Gross total resection of the tumor was an independent marker for a prolonged survival (p = 0.03). Conclusion: MiRNA-181a2 seems to be a promising prognostic marker of selective glioblastoma patients with IDH1 wild type characteristics. This effect may be mediated via direct regulation of IDH1 expression.
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Ocłoń, Ewa, and Anna Hrabia. "Selection of the Most Stable Endogenous Control Genes for Microrna Quantitation in Chicken Ovarian Follicles." Annals of Animal Science 20, no. 1 (January 1, 2020): 109–23. http://dx.doi.org/10.2478/aoas-2019-0070.
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AbstractMicroRNAs (miRNAs or miRs) belong to a class of small non-coding RNAs of 19 to 24 nucleotides long that act as negative gene regulators at the post-transcriptional level. Quantitative PCR (q-PCR) is a commonly used technique in the profiling of miRs, and identification of reliable endogenous controls is crucial for proper data normalisation. To date, no study has been performed on reference miRs for the normalisation of miR expression in chicken ovarian tissues. Therefore, the aim of the present study was to experimentally identify the most stable reference mirs for normalisation of miR q-PCR expression data in the chicken ovary. Relying on high-throughput sequencing, five putative reference miR (let-7a-3p, miR-140a-3p, miR-22-5p, miR-33-5p, miR-99a-3p) were identified and subsequently analysed in a total of 66 tissue samples. The stability of candidate endogenous controls validated by the most widely used algorithms, geNorm, NormFinder, and BestKeeper, showed that let-7a-3p, miR-140a-3p, and miR-22-5p are the most appropriate choice of reference genes. Application of different normalisation approaches to the relative quantitation of randomly chosen miR-1552-5p in chicken ovarian follicles indicated the impact of the selected reference genes on miR expression. Further, the results revealed a downregulation of miR-1552-5p. In summary, the three identified endogenous reference miRs are suitable for profiling the miR expression in ovarian tissues of laying hens. Our findings provide valuable information for future miR expression studies in the avian ovary.
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Kim, Jin-Hyun, Joo-Seok Park, Chae-Young Lee, Min-Gyun Jeong, Jiu Liang Xu, Yongsoo Choi, Ho-Won Jung, and Hong-Kyu Choi. "Dissecting seed pigmentation-associated genomic loci and genes by employing dual approaches of reference-based and k-mer-based GWAS with 438 Glycine accessions." PLOS ONE 15, no. 12 (December 1, 2020): e0243085. http://dx.doi.org/10.1371/journal.pone.0243085.
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The soybean is agro-economically the most important among all cultivated legume crops, and its seed color is considered one of the most attractive factors in the selection-by-breeders. Thus, genome-wide identification of genes and loci associated with seed colors is critical for the precision breeding of crop soybeans. To dissect seed pigmentation-associated genomic loci and genes, we employed dual approaches by combining reference-based genome-wide association study (rbGWAS) and k-mer-based reference-free GWAS (rfGWAS) with 438 Glycine accessions. The dual analytical strategy allowed us to identify four major genomic loci (designated as SP1-SP4 in this study) associated with the seed colors of soybeans. The k-mer analysis enabled us to find an important recombination event that occurred between subtilisin and I-cluster B in the soybean genome, which could describe a special structural feature of ii allele within the I locus (SP3). Importantly, mapping analyses of both mRNAs and small RNAs allowed us to reveal that the subtilisin-CHS1/CHS3 chimeric transcripts generate and act as an initiator towards ‘mirtron (i.e., intron-harboring miRNA precursor)’-triggered silencing of chalcone synthase (CHS) genes. Consequently, the results led us to propose a working model of ‘mirtron-triggered gene silencing (MTGS)’ to elucidate a long-standing puzzle in the genome-wide CHS gene silencing mechanism. In summary, our study reports four major genomic loci, lists of key genes and genome-wide variations that are associated with seed pigmentation in soybeans. In addition, we propose that the MTGS mechanism plays a crucial role in the genome-wide silencing of CHS genes, thereby suggesting a clue to currently predominant soybean cultivars with the yellow seed coat. Finally, this study will provide a broad insight into the interactions and correlations among seed color-associated genes and loci within the context of anthocyanin biosynthetic pathways.
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Klinge, Carolyn M., Belinda J. Petri, and Kellianne M. Piell. "Epitranscriptomic Reader HNRNPA2B1 Confers Endocrine Resistance to Breast Cancer Cells." Journal of the Endocrine Society 5, Supplement_1 (May 1, 2021): A807—A808. http://dx.doi.org/10.1210/jendso/bvab048.1643.
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Abstract Despite new combination therapies improving survival of breast cancer patients with estrogen receptor α (ER+) tumors, the molecular mechanisms for endocrine-resistant metastatic disease remain unresolved. HNRNPA2B1 (Heterogeneous Nuclear Ribonucleoprotein A2/B1), an RNA binding protein that functions as reader of the N(6)-methyladenosine (m6A) mark in transcribed RNA, is upregualted in tamoxifen- and fulvestrant-resistant, estrogen receptor (ERα)+ LCC9 and LY2 cells derived from MCF-7 endocrine-sensitive luminal A breast cancer cells (1). The miRNA-seq transcriptome of MCF-7 cells transiently overexpressing HNRNPA2B1 (A2B1) identified gene ontology (GO) pathways including “cellular response to steroid hormone signaling and estradiol” and “positive regulation of protein ser/thr kinase activity”. Modest (~ 4.5-fold) stable HNRNPA2B1 overexpression in MCF-7 cells (MCF-7-A2B1) results in ablation of growth inhibition by 4-hydroxytamoxifen (4-OHT) and fulvestrant. This was not due to loss or decrease of ERα; in fact, ERα was increased. Conversely, transient knockdown of HNRNPA2B1 in LCC9 and LY2 cells sensitized the cells to growth inhibition by 4-OHT and fulvestrant while reducing ERα. MCF-7-A2B1 cells showed increased migration, invasion, clonogenicity, soft agar colony size, and markers of epithelial-to-mesenchymal transition. Like LCC9 cells, MCF-7-A2B1 cells showed activation of AKT and MAPK and high androgen receptor (AR). Treatment of MCF-7-A2B1 cells with either PI3K inhibitor Wortmannin or MEK inhibitor PD98059 inhibited soft agar colony formation and reduced colony size. Knockdown of HNRNPA2B1 in MCF-7-A2B1 reduces clonogenicity, but had no effect on the clonogenicity of either LCC9 or LY2 cells. These data suggest a role for HNRNPA2B1 in promoting the initiation of acquired endocrine-resistance by activating ser/thr kinase growth factor signaling pathways. Selective inhibition of HNRNPA2B1 may be a target to prevent acquistion of endocrine therapy resistance, but not treat established metastatic disease. Reference: (1) Klinge CM, Piell KM, Tooley CS, Rouchka EC. HNRNPA2/B1 is upregulated in endocrine-resistant LCC9 breast cancer cells and alters the miRNA transcriptome when overexpressed in MCF-7 cells. Scientific reports 2019; 9:9430
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Milani, Gloria, Tobia Lana, Silvia Bresolin, Francesca Paderi, Chiara Frasson, Giuseppe Basso, and Geertruy Kronnie. "Microvesicles Transcripts As Hallmark and Vector From Leukemic Parental Cells." Blood 120, no. 21 (November 16, 2012): 1459. http://dx.doi.org/10.1182/blood.v120.21.1459.1459.
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Abstract Abstract 1459 Microvesicles (MVs) are nano-sized lipid bodies (100–1000 nm in diameter) that are released by cells, both in vitro and in vivo. MVs are secreted in the extracellular space and as carriers of proteins, mRNA and miRNA represent vectors from donor to target cells involved in intercellular communication. MVs modulate the functional state of receiving cells through fusion with the target cell. In leukemia MVs were suggested to modulate the hematopoietic niche. In this study, we investigated the transcriptome of MVs released from leukemic cell lines. In particular, we analyzed K562, a BCR-ABL positive human erythromyeloblastoid leukemia cell line, and we collected RNA both from cells and MVs released in culture. Since many different methods have been described for microvesicles isolation and description of MV populations are often ambiguous, an accurate protocol has been developed in order to select a defined MVs population. In detail, for MVs isolation cell culture medium was centrifuged at 2500g for 15 minutes. These centrifugations allowed to delete cells and bigger bodies. Then supernatant was filtered by means of a 1.2um filter, in order to keep only vesicles of defined physical measure and to eliminate residual bigger vesicles, such as apoptotic bodies (>1000nm). The filtration allowed an accurate selection of a well defined MVs population. The filtered medium was then centrifuged at 18000g for 1h at 4°C. MVs were resuspended in Trizol for RNA isolation. Also RNA of cells, from which MVs have been released, was extracted using the Trizol method, according to manufacturer instructions. Cell line RNA quality was assessed using the Agilent 2100 Bioanalyzer (Agilent Technologies) and quantified by means of NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies Inc.). To check MVs RNA integrity we determined the ratio of 5' amplicons to 3' amplicons of housekeeping transcripts by Real Time PCR. We screened the presence of several housekeeping transcripts in MVs and selected GAPDH as reference. The GAPDH 5':3' amplicon ratio should equal 1 to ensure MVs RNA quality. Afterwards, reverse transcription–polymerase chain reaction (RT-PCR) amplification was performed. cDNA was synthesized from 1mg of total RNA. We analyzed the gene expression profile of K562 cell line and MVs, released from these cells, using GeneChip Human Genome U133 Plus 2.0 arrays (Affymetrix). Gene expression data have been compared between cells and MVs. Ninety-one percent of probe sets showed a similar expression (fold-change lower than 1.5) between cell line and MVs. Thirteen percent of these probes were recognized as present call probe sets in both cell line and MVs. Analysis of probe sets using DAVID Functional Annotation Bioinformatics Microarray Analysis revealed a conservation of MVs gene transcripts involved in pathways of cell function such as RNA processing, protein translation, aminoacid metabolism and cell respiration. Remarkably, in MVs we observed a high presence of gene transcripts coding for protein belonging to the Chronic Myeloid Leukemia pathway that are expressed downstream of the BCR-ABL tyrosin kinase fusion protein. The maintenance of this pathway in MVs highlights the intrinsic peculiarity of BCR-ABL positive K562 cells apparently also conserved in MVs mRNA outfit representing a hallmark of the parental cell from which they have been released. Furthermore, 3.8% of the probe sets resulted to be up-regulated in MVs compare to the cell line (fold-change higher than 1.5). In MVs, we observed a higher expression of genes belonging to cell communication pathways, adhesion and migration processes, membrane and ionic channels signals. In conclusion, we isolated MVs released by K562 leukemic cells using an accurate selection of the MV population based on physical measures and for the first time a whole transcriptome gene expression analysis has been performed comparing K562 cells and MVs. Moreover, we identified an enrichment of transcripts coding for proteins involved in several essential pathways in the MVs supporting the hypothesis of a functional selection from the parental cell transcriptome and underlining the relevant role of MVs as vehicles of messages to target cells. Disclosures: No relevant conflicts of interest to declare.
Dissertations / Theses on the topic "MiRNA reference gene selection"
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Yu, Tian. "COMPUTATIONAL IDENTIFICATION AND MOLECULAR VERIFICATION OF MIRNA IN EASTERN SUBTERRANEAN TERMITES (RETICULITERMES FLAVIPES)." UKnowledge, 2014. http://uknowledge.uky.edu/entomology_etds/12.
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Reticulitermes flavipes is one of the most common termite species in the world, and has been an intriguing research model due to its ecological and biological and economic significance. The fundamental biological question addressed by this study is to elucidate the role of miRNAs in termite development and how miRNA can influence labor division. miRNAs are short non-coding RNAs that have an important role in gene regulation at post-transcriptional level, and can potentially be involved in the regulation of caste polyphenism. Using a computational approach, I identified 167 conserved and 33 novel miRNAs in the dataset. miR-iab-4 and 19 other miRNAs showed highly differential expression between worker and soldier, and their possible roles in termite biology are discussed. To reliably quantify miRNA expression in experiments, I tested the stability of 10 miRNAs as reference gene using quantitative real-time PCR. miR-8_3, bantam and miR-276a-3p are the most stable miRNAs in different castes, pre-soldier formation, and different tissues, respectively. Lastly, the predicted miRNA expression is verified by the qRT-PCR for 8 miRNAs. Overall, this study shows that miRNA plays a role in mediating the work-soldier transition in R. flavipes.
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Schulze, Felix, Deeksha Malhan, Khassawna Thaqif El, Christian Heiss, Anja Seckinger, Dirk Hose, and Angela Rösen-Wolff. "A tissue-based approach to selection of reference genes for quantitative real-time PCR in a sheep osteoporosis model." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-232280.
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BACKGROUND:
In order to better understand the multifactorial nature of osteoporosis, animal models are utilized and compared to healthy controls. Female sheep are well established as a model for osteoporosis induced by ovariectomy, calcium and vitamin D low diet, application of steroids, or a combination of these treatments. Transcriptional studies can be performed by applying quantitative real time PCR (RT-qPCR). RT-qPCR estimates mRNA-levels of target genes in relation to reference genes. A chosen set of reference genes should not show variation under experimental conditions. Currently, no standard reference genes are accepted for all tissue types and experimental conditions. Studies examining reference genes for sheep are rare and only one study described stable reference in mandibular bone. However, this type of bone differs from trabecular bone where most osteoporotic fractures occur. The present study aimed at identifying a set of reference genes for relative quantification of transcriptional activity of ovine spine bone and ovine in vitro differentiated mesenchymal stromal cells (MSC) for reliable comparability.
METHODS:
Twelve candidate reference genes belonging to different functional classes were selected and their expression was measured from cultured ovMSCs (n = 18) and ovine bone samples (n = 16), respectively. RefFinder was used to rank the candidate genes.
RESULTS:
We identified B2M, GAPDH, RPL19 and YWHAZ as the best combination of reference genes for normalization of RT-qPCR results for transcriptional analyses of these ovine samples.
CONCLUSION:
This study demonstrates the importance of applying a set of reference genes for RT-qPCR analysis in sheep. Based on our data we recommend using four identified reference genes for relative quantification of gene expression studies in ovine bone or for in vitro experiments with osteogenically differentiated ovine MSCs.
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Schulze, Felix, Deeksha Malhan, Khassawna Thaqif El, Christian Heiss, Anja Seckinger, Dirk Hose, and Angela Rösen-Wolff. "A tissue-based approach to selection of reference genes for quantitative real-time PCR in a sheep osteoporosis model." BioMed Central, 2017. https://tud.qucosa.de/id/qucosa%3A30735.
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BACKGROUND:
In order to better understand the multifactorial nature of osteoporosis, animal models are utilized and compared to healthy controls. Female sheep are well established as a model for osteoporosis induced by ovariectomy, calcium and vitamin D low diet, application of steroids, or a combination of these treatments. Transcriptional studies can be performed by applying quantitative real time PCR (RT-qPCR). RT-qPCR estimates mRNA-levels of target genes in relation to reference genes. A chosen set of reference genes should not show variation under experimental conditions. Currently, no standard reference genes are accepted for all tissue types and experimental conditions. Studies examining reference genes for sheep are rare and only one study described stable reference in mandibular bone. However, this type of bone differs from trabecular bone where most osteoporotic fractures occur. The present study aimed at identifying a set of reference genes for relative quantification of transcriptional activity of ovine spine bone and ovine in vitro differentiated mesenchymal stromal cells (MSC) for reliable comparability.
METHODS:
Twelve candidate reference genes belonging to different functional classes were selected and their expression was measured from cultured ovMSCs (n = 18) and ovine bone samples (n = 16), respectively. RefFinder was used to rank the candidate genes.
RESULTS:
We identified B2M, GAPDH, RPL19 and YWHAZ as the best combination of reference genes for normalization of RT-qPCR results for transcriptional analyses of these ovine samples.
CONCLUSION:
This study demonstrates the importance of applying a set of reference genes for RT-qPCR analysis in sheep. Based on our data we recommend using four identified reference genes for relative quantification of gene expression studies in ovine bone or for in vitro experiments with osteogenically differentiated ovine MSCs.
Books on the topic "MiRNA reference gene selection"
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Walsh, Bruce, and Michael Lynch. Evolution and Selection of Quantitative Traits. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.001.0001.
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Quantitative traits—be they morphological or physiological characters, aspects of behavior, or genome-level features such as the amount of RNA or protein expression for a specific gene—usually show considerable variation within and among populations. Quantitative genetics, also referred to as the genetics of complex traits, is the study of such characters and is based on mathematical models of evolution in which many genes influence the trait and in which non-genetic factors may also be important. Evolution and Selection of Quantitative Traits presents a holistic treatment of the subject, showing the interplay between theory and data with extensive discussions on statistical issues relating to the estimation of the biologically relevant parameters for these models. Quantitative genetics is viewed as the bridge between complex mathematical models of trait evolution and real-world data, and the authors have clearly framed their treatment as such. This is the second volume in a planned trilogy that summarizes the modern field of quantitative genetics, informed by empirical observations from wide-ranging fields (agriculture, evolution, ecology, and human biology) as well as population genetics, statistical theory, mathematical modeling, genetics, and genomics. Whilst volume 1 (1998) dealt with the genetics of such traits, the main focus of volume 2 is on their evolution, with a special emphasis on detecting selection (ranging from the use of genomic and historical data through to ecological field data) and examining its consequences. This extensive work of reference is suitable for graduate level students as well as professional researchers (both empiricists and theoreticians) in the fields of evolutionary biology, genetics, and genomics. It will also be of particular relevance and use to plant and animal breeders, human geneticists, and statisticians.
Book chapters on the topic "MiRNA reference gene selection"
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Wang, Meng, and Navreet K. Bhullar. "Selection of Suitable Reference Genes for qRT-PCR Gene Expression Studies in Rice." In Methods in Molecular Biology, 293–312. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1068-8_20.
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Saxena, Shipra, Sneha Yogindran, Manmohan Arya, Yogita Sharma, and Chandra Pal Singh. "RNAi-Mediated Control of Lepidopteran Pests of Important Crop Plants." In Moths and Caterpillars. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.96429.
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Insects as pests destroy annually an estimated 18–20% of the crop production worldwide. Caterpillars, the larval stage of moths, are the major pests of agricultural products owing to their voracious feeding habits. In the past few decades, the potent methods of insect control, such as insecticides and Bt toxins, have been constrained as a result of health hazards, environmental issues, and development of resistance, after their prolonged application. Thus, there is need to find alternative options to improve plant protection strategies. Recently, RNA interference (RNAi), the post-transcriptional gene-silencing mechanism, has emerged as one of such a novel, sustainable, and environment friendly approaches for insect management and crop protection. RNAi technology relies on selection of a vital insect pest target gene and its expression as a double stranded RNA or stem-loop RNA molecule, which is recognized by the host RNAi machinery and processed into small interfering RNAs (siRNAs) or microRNAs (miRNAs). The siRNA/miRNA along with the RNA-induced silencing complex (RISC) binds to the complimentary mRNA and induce gene silencing at post-transcriptional level. With effective target-gene selection and transgenic plants expressing these precursor RNA molecules, insect pests of various crops have been efficiently managed. In this chapter, we discuss the basic mechanism of RNAi and its application in controlling lepidopteran pests of important crop plants.
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Dash, Sujata, and Bichitrananda Patra. "Feature Selection Algorithms for Classification and Clustering in Bioinformatics." In Global Trends in Intelligent Computing Research and Development, 111–30. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4936-1.ch005.
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This chapter discusses some important issues such as pre-processing of gene expression data, curse of dimensionality, feature extraction/selection, and measuring or estimating classifier performance. Although these concepts are relatively well understood among the technical people such as statisticians, electrical engineers, and computer scientists, they are relatively new to biologists and bioinformaticians. As such, it was observed that there are still some misconceptions about the use of classification methods. For instance, in most classifier design strategies, the gene or feature selection is an integral part of the classifier, and as such, it must be a part of the cross-validation process that is used to estimate the classifier prediction performance. Simon (2003) discussed several studies that appeared in prestigious journals where this important issue is overlooked, and optimistically biased prediction performances were reported. Furthermore, the authors have also discuss important properties such as generalizability or sensitivity to overtraining, built-in feature selection, ability to report prediction strength, and transparency of different approaches to provide a quick and concise reference. The classifier design and clustering methods are relatively well established; however, the complexity of the problems rooted in the microarray technology hinders the applicability of the classification methods as diagnostic and prognostic predictors or class-discovery tools in medicine.
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"Final Remarks for the Research With Advanced Machine Learning Methods in Colon Cancer Analysis." In Machine Learning in Cancer Research With Applications in Colon Cancer and Big Data Analysis, 151–54. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7316-7.ch007.
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Generally, classification accuracy is very important to gene processing and selection and cancer classification. It is needed to achieve better cancer treatments and improve medical drug assignments. However, the time complexity analysis will enhance the application's significance. To answer the research questions in Chapter 1, several case studies have been implemented (see Chapters 4 and 5), each was essential to sustain the methodologies discussed in Chapter 3. The study used a colon-cancer dataset comprising 2000 genes. The best search algorithm, GA, showed high performance with a good efficient time complexity. However, both DTs and SVMs showed the best classification contribution with reference to performance accuracy and time efficiency. However, it is difficult to apply a completely fair comparative study because existing algorithms and methods were tested by different authors to reflect the effectiveness and powerful of their own methods.
Conference papers on the topic "MiRNA reference gene selection"
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Ibrahim, Rania, Noha A. Yousri, Mohamed A. Ismail, and Nagwa M. El-Makky. "Multi-level gene/MiRNA feature selection using deep belief nets and active learning." In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2014. http://dx.doi.org/10.1109/embc.2014.6944490.
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Kornev, A. A., V. V. Vysochinskaya, N. A. Knyazev, A. K. Emel'yanov, and A. A. Bogdanov. "Transfection of human peripheral blood T-lymphocytes with synthetic small interfering RNAs: selection of an effective technique." In Global science. Development and novelty. L-Journal, 2020. http://dx.doi.org/10.18411/gsdn-25-12-2020-04.
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It has been shown that the state of the human immune system and its activity determines the development, course and prognosis of many oncological diseases. To date, various immunotherapeutic approaches have been developed, of which the most promising is adoptive cell therapy (ACT). An increase in the effectiveness of this type of therapy could be achieved by using synthetic small interfering RNAs (siRNAs) to suppress the expression of key immune checkpoint (ICI) genes (PD1, CTL4) in T-lymphocytes, which are involved in cellular immunosuppression. However, there is a problem of selecting an effective method for delivering such siRNAs to T-lymphocytes. In the present study, we developed a synthetic siRNA specific to the mRNA sequence of the PD1 gene and evaluated the efficiency of its delivery to activated human T-lymphocytes using chemically modified siRNA, histone H1, – 18 – Global science. Development and novelty and the liposomal agent HiperFect. Ex vivo activated T-lymphocytes from healthy donors were used. The efficiency of siRNA transfection into cells and its confirmation was assessed using flow cytofluorometry and confocal microscopy. As a result of the study, a high (51%) efficiency of transfection into these cells using chemically modified "self-delivering" siRNA was shown. For other methods of delivery of miRNA to T-lymphocytes, low efficiency is shown. Thus, our data suggest that of the three approaches used in this work for miRNAs delivery to activated T-lymphocytes, the most effective is the use of “self-delivering” chemically modified cholesterol miRNA.
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Venables, Anne, and Grace Tan. "A 'Hands on' Strategy for Teaching Genetic Algorithms to Undergraduates." In InSITE 2007: Informing Science + IT Education Conference. Informing Science Institute, 2007. http://dx.doi.org/10.28945/3132.
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Genetic algorithms (GAs) are a problem solving strategy that uses stochastic search. Since their introduction (Holland, 1975), GAs have proven to be particularly useful for solving problems that are ‘intractable’ using classical methods. The language of genetic algorithms (GAs) is heavily laced with biological metaphors from evolutionary literature, such as population, chromosome, crossover, cloning, mutation, genes and generations. For beginners studying genetic algorithms, there is quite an overhead in gaining comfort with these terms and an understanding of their parallel meanings in the unfamiliar computing milieu of an evolutionary algorithm. This paper describes a ‘hands on’ strategy to introduce and teach genetic algorithms to undergraduate computing students. By borrowing an analogical model from senior biology classes, poppet beads are used to represent individuals in a population (Harrison, 2001). Described are several introductory exercises that transport students from an illustration of natural selection in Biston betula moths, onto the representation and solution of differing mathematical and computing problems. Through student manipulation and interactions with poppet beads, the exercises cover terms such as population, generation, chromosome, gene, mutation and crossover in both their biological and computing contexts. Importantly, the tasks underline the two key design issues of genetic algorithms: the choice of an appropriate chromosome representation, and a suitable fitness function for each specific instance. Finally, students are introduced to the notion of schema upon which genetic algorithms operate. The constructivist model of learning advocates the use of such contextual problems to create an environment where students become active participants in their own learning (Ben-Ari, 1998; Greening, 2000; Kolb, 1984). Initial student feedback about these “hands on” exercises has been enthusiastic. As well, several students have made reference to the lessons learnt as the basis for GA coding in subsequent open-ended assignments. It seems that once the hurdle of becoming familiar with GA terminology has been surmounted, students find genetic algorithms to be particularly intriguing for their uncanny ability to solve incredibly complex problems quickly and proficiently (Moore, 2001).