Procjena gama-aktina, beta-aktina, gliceraldehid-3-fosfat dehidrogenaze i 18S kao referentnih gena za qRT-PCR uporabom uzoraka krvi u istraživanju mliječnih žlijezda kujica

Mammary tumours are the most frequent group of neoplasia in female dogs. Tumorigenesis is associated with gene expression changes in a wide variety of genes. For this reason, real-time quantitative PCR (qRT-PCR) is used in routine diagnostic procedures in clinical practice due to its the specificity, sensitivity, simplicity, and high performance. qRT-PCR is also widely used to measure the expression of target genes compared to reference genes in several tissues. We collected blood samples from healthy female dogs and females with canine mammary cancer in Manizales, Colombia between June 2018 and January 2019, and mRNA was isolated from each sample for cDNA synthesis. qRT-PCR-based expression assays were performed using primers designed for gamma-actin, beta-actin, GAPDH, and 18S genes. We calculated the amplification efficiency, specificity, and stability using geNorm, NormFinder, BestKeeper, and the ΔCt comparative method. We obtained linear regressions to verify constant gene expression and conducted an ANOVA to detect expression differences regarding Ct values and healthy vs. ill conditions. We found stability for primers 18S-1, GAPDH-1, GAPDH-NM, and Gamma-actin-1 (in increasing order). Furthermore, these genes showed constant expression levels in patients (R2>0.80). We report novel primers for gamma-actin and GAPDH, which proved to be efficient endogenous control genes for qRT-PCR applications in blood tissue. These primers are useful for gene expression research in canine mammary cancer.Tumori mliječnih žlijezda najčešća su skupina neoplazija u kujica. Tumorogeneza je povezana s promjenama u ekspresiji gena u širokom rasponu gena. Iz tog razloga se rabi kvantitativna lančana reakcija polimerazom u stvarnom vremenu (qRT-PCR) u rutinskim dijagnostičkim postupcima u kliničkoj praksi, uslijed specifičnosti, osjetljivosti, jednostavnosti i visoke učinkovitosti ove tehnike. qRT-PCR se široko rabi i za mjerenje ekspresije ciljanih gena u usporedbi s referentnim genima u više vrsta tkiva. Prikupili smo uzorke krvi zdravih kujica i kujica s tumorom mliječnih žlijezda u Manizalesu, Kolumbiji, od lipnja 2018. do siječnja 2019. godine. Izolirali smo mRNK iz svakog uzorka za cDNK sintezu. Pokusi ekspresije na bazi qRT-PCR obavljeni su uporabom primera dizajniranih za gama-aktin, beta-aktin, gliceraldehid- 3-fosfat dehidrogenazu (GAPDH) i 18S gene. Izračunali smo pojačanu učinkovitost, specifičnost i stabilnost uporabom geNorm, NormFinder, BestKeeper i ΔCt komparativne metode. Dobili smo linearne regresije za potvrđivanje stalne ekspresije gena i proveli smo analizu varijance (ANOVA) za detekciju razlika u ekspresiji s obzirom na Ct vrijednosti te zdrava u usporedbi s bolesnim stanjima. Otkrili smo i stabilnost za primere 18S-1, GAPDH-1, GAPDH-NM i Gamma-actin-1 (rastućim redoslijedom). Nadalje, ovi geni su pokazali konstantne razine ekspresije u pacijenata (R2>0,80). Izvještavamo o novim primerima za gama-aktin i GAPDH, koji su se pokazali učinkovitim endogenim kontrolnim genima za qRT-PCR primjene u krvnom tkivu. Ti primeri su korisni za istraživanje ekspresije gena u tumora psećih mliječnih žlijezda

Identification of Novel Endogenous Controls for qPCR Normalization in SK-BR-3 Breast Cancer Cell Line

Funding Information: Funding: The present study was funded by Riga Stradin,š University (RSU) Project Nb.5-1/252/2020. Funding Information: The present study was funded by Riga Stradin, ? University (RSU) Project Nb.5-1/252/2020. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Normalization of gene expression using internal controls or reference genes (RGs) has been the method of choice for standardizing the technical variations in reverse transcription quantitative polymerase chain reactions (RT-qPCR). Conventionally, ACTB and GAPDH have been used as reference genes despite evidence from literature discouraging their use. Hence, in the present study we identified and investigated novel reference genes in SK-BR-3, an HER2-enriched breast cancer cell line. Transcriptomic data of 82 HER2-E breast cancer samples from TCGA database were analyzed to identify twelve novel genes with stable expression. Additionally, thirteen RGs from the literature were analyzed. The expression variations of the candidate genes were studied over five successive passages (p) in two parallel cultures S1 and S2 and in acute and chronic hypoxia using various algorithms. Finally, the most stable RGs were selected and validated for normalization of the expression of three genes of interest (GOIs) in normoxia and hypoxia. Our results indicate that HSP90AB1, DAD1, PFN1 and PUM1 can be used in any combination of three (triplets) for optimizing intra- and inter-assay gene expression differences in the SK-BR-3 cell line. Additionally, we discourage the use of conventional RGs (ACTB, GAPDH, RPL13A, RNA18S and RNA28S) as internal controls for RT-qPCR in SK-BR-3 cell line.publishersversionPeer reviewe

LRP10, PGK1 and RPLP0: best reference genes in periprostatic adipose tissue under obesity and prostate cancer conditions

Obesity (OB) is a metabolic disorder characterized by adipose tissue dysfunction that has emerged as a health problem of epidemic proportions in recent decades. OB is associated with multiple comorbidities, including some types of cancers. Specifically, prostate cancer (PCa) has been postulated as one of the tumors that could have a causal relationship with OB. Particularly, a specialized adipose tissue (AT) depot known as periprostatic adipose tissue (PPAT) has gained increasing attention over the last few years as it could be a key player in the pathophysiological interaction between PCa and OB. However, to date, no studies have defined the most appropriate internal reference genes (IRGs) to be used in gene expression studies in this AT depot. In this work, two independent cohorts of PPAT samples (n = 20/n = 48) were used to assess the validity of a battery of 15 literature-selected IRGs using two widely used techniques (reverse transcription quantitative PCR [RT-qPCR] and microfluidic-based qPCR array). For this purpose, ΔCt method, GeNorm (v3.5), BestKeeper (v1.0), NormFinder (v.20.0), and RefFinder software were employed to assess the overall trends of our analyses. LRP10, PGK1, and RPLP0 were identified as the best IRGs to be used for gene expression studies in human PPATs, specifically when considering PCa and OB conditions

Selecting suitable reference genes for qPCR normalization : A comprehensive analysis in MCF-7 breast cancer cell line

Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: MCF-7 breast cancer cell line is undoubtedly amongst the most extensively studied patient-derived research models, providing pivotal results that have over the decades translated to constantly improving patient care. Many research groups, have previously identified suitable reference genes for qPCR normalization in MCF-7 cell line. However, over the course of identification of suitable reference genes, a comparative analysis comprising these genes together in a single study has not been reported. Furthermore, the expression dynamics of these reference genes within sub-clones cultured over multiple passages (p) has attracted limited attention from research groups. Therefore, we investigated the expression dynamics of 12 previously suggested reference genes within two sub-clones (culture A1 and A2) cultured identically over multiple passages. Additionally, the effect of nutrient stress on reference gene expression was examined to postulate an evidence-based recommendation of the least variable reference genes that could be employed in future gene expression studies. Results: The analysis revealed the presence of differential reference gene expression within the sub-clones of MCF-7. In culture A1, GAPDH-CCSER2 were identified as the least variable reference genes while for culture A2, GAPDH-RNA28S were identified. However, upon validation using genes of interest, both these pairs were found to be unsuitable control pairs. Normalization of AURKA and KRT19 with triplet pair GAPDH-CCSER2-PCBP1 yielded successful results. The triplet also proved its capability to handle variations arising from nutrient stress. Conclusions: The variance in expression behavior amongst sub-clones highlights the potential need for exercising caution while selecting reference genes for MCF-7. GAPDH-CCSER2-PCBP1 triplet offers a reliable alternative to otherwise traditionally used internal controls for optimizing intra- and inter-assay gene expression differences. Furthermore, we suggest avoiding the use of ACTB, GAPDH and PGK1 as single internal controls.publishersversionPeer reviewe

S100A4 mRNA-protein relationship uncovered by measurement noise reduction

Intrinsic biological fluctuation and/or measurement error can obscure the association of gene expression patterns between RNA and protein levels. Appropriate normalization of reverse-transcription quantitative PCR (RT-qPCR) data can reduce technical noise in transcript measurement, thus uncovering such relationships. The accuracy of gene expression measurement is often challenged in the context of cancer due to the genetic instability and “splicing weakness” involved. Here, we sequenced the poly(A) cancer transcriptome of canine osteosarcoma using mRNA-Seq. Expressed sequences were resolved at the level of two consecutive exons to enable the design of exon-border spanning RT-qPCR assays and ranked for stability based on the coefficient of variation (CV). Using the same template type for RT-qPCR validation, i.e. poly(A) RNA, avoided skewing of stability assessment by circular RNAs (circRNAs) and/or rRNA deregulation. The strength of the relationship between mRNA expression of the tumour marker S100A4 and its proportion score of quantitative immunohistochemistry (qIHC) was introduced as an experimental readout to fine-tune the normalization choice. Together with the essential logit transformation of qIHC scores, this approach reduced the noise of measurement as demonstrated by uncovering a highly significant, strong association between mRNA and protein expressions of S100A4 (Spearman’s coefficient ρ = 0.72 (p = 0.006)).publishedVersio

How to perform RT-qPCR accurately in plant species?: a case study on flower colour gene expression in an azalea (Rhododendron simsii hybrids) mapping population

Background: Flower colour variation is one of the most crucial selection criteria in the breeding of a flowering pot plant, as is also the case for azalea (Rhododendron simsii hybrids). Flavonoid biosynthesis was studied intensively in several species. In azalea, flower colour can be described by means of a 3-gene model. However, this model does not clarify pink-coloration. The last decade gene expression studies have been implemented widely for studying flower colour. However, the methods used were often only semi-quantitative or quantification was not done according to the MIQE-guidelines. We aimed to develop an accurate protocol for RT-qPCR and to validate the protocol to study flower colour in an azalea mapping population. Results: An accurate RT-qPCR protocol had to be established. RNA quality was evaluated in a combined approach by means of different techniques e.g. SPUD-assay and Experion-analysis. We demonstrated the importance of testing noRT-samples for all genes under study to detect contaminating DNA. In spite of the limited sequence information available, we prepared a set of 11 reference genes which was validated in flower petals; a combination of three reference genes was most optimal. Finally we also used plasmids for the construction of standard curves. This allowed us to calculate gene-specific PCR efficiencies for every gene to assure an accurate quantification. The validity of the protocol was demonstrated by means of the study of six genes of the flavonoid biosynthesis pathway. No correlations were found between flower colour and the individual expression profiles. However, the combination of early pathway genes (CHS, F3H, F3'H and FLS) is clearly related to co-pigmentation with flavonols. The late pathway genes DFR and ANS are to a minor extent involved in differentiating between coloured and white flowers. Concerning pink coloration, we could demonstrate that the lower intensity in this type of flowers is correlated to the expression of F3'H. Conclusions: Currently in plant research, validated and qualitative RT-qPCR protocols are still rare. The protocol in this study can be implemented on all plant species to assure accurate quantification of gene expression. We have been able to correlate flower colour to the combined regulation of structural genes, both in the early and late branch of the pathway. This allowed us to differentiate between flower colours in a broader genetic background as was done so far in flower colour studies. These data will now be used for eQTL mapping to comprehend even more the regulation of this pathway

Sample size calculations and normalization methods for RNA-seq data.

High-throughput RNA sequencing (RNA-seq) has become the preferred choice for transcriptomics and gene expression studies. With the rapid growth of RNA-seq applications, sample size calculation methods for RNA-seq experiment design and data normalization methods for DEG analysis are important issues to be explored and discussed. The underlying theme of this dissertation is to develop novel sample size calculation methods in RNA-seq experiment design using test statistics. I have also proposed two novel normalization methods for analysis of RNA-seq data. In chapter one, I present the test statistical methods including Wald’s test, log-transformed Wald’s test and likelihood ratio test statistics for RNA-seq data with a negative binomial distribution. Following the test statistics, I present the five sample calculation methods based on a one-sided test. A comparison of my five methods and an existing method was performed by calculating the sample sizes and the simulated power in different scenarios. Due to the limitations of these methods, in chapter two, I have further derived two explicit sample size calculation methods based on a generalized linear model with a negative binomial distribution in RNA-seq data. These two sample size methods based on a two-sided Wald’s test are presented under a wide range of settings including the imbalanced design and unequal read depth, which is applicable in many situations. In chapter 3, I have a literature review of the existing normalization methods and describe the challenge of choosing an optimal normalization method due to multiple factors contributing to read count variability that effect overall the sensitivity and specificity. Then, I present two proposed normalization methods. I evaluate the performance of the commonly used methods (DESeq, TMM-edgeR, FPKM-CuffDiff, TC, Med, UQ and FQ) and two new methods I propose: Med-pgQ2 and UQ-pgQ2. The results from MAQC2 data shows that my proposed Med-pgQ2 and UQ-pgQ2 methods may be better choices for the differential gene analysis of RNA-seq data by improving specificity while maintaining a good detection power given a nominal FDR level. Finally, in chapter 4, I focus on data analysis in RNA-seq data using three normalization methods and two test statistic method with the aid of DESeq2 and edgeR packages. Through within-group analysis of these real RNA-seq data, I have found my normalization method, UQ-pgQ2, performs best with a lower false positive rate while maintaining a good detection power. Thus, in my work, I have derived the explicit sample size calculation methods, which is a very useful tool for researchers to quickly estimate the sample sizes in an experiment design. Furthermore, my two normalization methods can improve the performance for differential gene analysis of RNA-seq data by controlling false positives for high read count genes

Investigation of Griffithsin's Interactions with Human Cells Confirms Its Outstanding Safety and Efficacy Profile as a Microbicide Candidate

Many natural product-derived lectins such as the red algal lectin griffithsin (GRFT) have potent in vitro activity against viruses that display dense clusters of oligomannose N-linked glycans (NLG) on their surface envelope glycoproteins. However, since oligomannose NLG are also found on some host proteins it is possible that treatment with antiviral lectins may trigger undesirable side effects. For other antiviral lectins such as concanavalin A, banana lectin and cyanovirin-N (CV-N), interactions between the lectin and as yet undescribed cellular moieties have been reported to induce undesirable side effects including secretion of inflammatory cytokines and activation of host T-cells. We show that GRFT, unlike CV-N, binds the surface of human epithelial and peripheral blood mononuclear cells (PBMC) through an exclusively oligosaccharide-dependent interaction. In contrast to several other antiviral lectins however, GRFT treatment induces only minimal changes in secretion of inflammatory cytokines and chemokines by epithelial cells or human PBMC, has no measureable effect on cell viability and does not significantly upregulate markers of T-cell activation. In addition, GRFT appears to retain antiviral activity once bound to the surface of PBMC. Finally, RNA microarray studies show that, while CV-N and ConA regulate expression of a multitude of cellular genes, GRFT treatment effects only minimal alterations in the gene expression profile of a human ectocervical cell line. These studies indicate that GRFT has an outstanding safety profile with little evidence of induced toxicity, T-cell activation or deleterious immunological consequence, unique attributes for a natural product-derived lectin