Identification and Validation of Reference Genes for qPCR Detection of Serum microRNAs in Colorectal Adenocarcinoma Patients

Serum microRNAs (miRNAs) have become a highlighted research hotspot, especially for their great potential as a novel promising non-invasive biomarker in cancer diagnosis. The most frequently used approach for serum miRNAs detection is quantitative real time polymerase chain reaction (qPCR). In order to obtain reliable qPCR data of miRNAs expression, the use of reference genes as endogenous control is undoubtly necessary. However, no systematic evaluation and validation of reference genes for normalizing qPCR analysis of serum miRNAs has been reported in colorectal adenocarcinoma. We firstly profiled pooled serum of colorectal adenocarcinoma, colorectal adenoma and healthy controls and selected a list of 13 miRNAs as candidate reference genes. U6 snRNA (U6) and above-mentioned 13 miRNAs were included in further confirmation by qPCR. As a result, 5 miRNAs (miR-151a-3p, miR-4446-3p, miR-221-3p, miR-93-5p and miR-3184-3p) were not detected in all samples and 2 miRNAs (miR-197-3p and miR-26a-5p) were relatively low with median Cq more than 35, and were excluded from further stability analysis. Then variable stability of other 6 miRNAs (miR-103b, miR-484, miR-16-5p, miR-3615, miR-18a-3p and miR-191-5p) and U6 were evaluated using two algorithms: geNorm and NormFinder which both identified miR-191-5p as the most stably expressed reference gene and selected miR-191-5p and U6 as the most stable pair of reference genes. After validating in an independent large cohorts and selecting miR-92a-3p as target miRNA to evaluate the effect of reference gene, we propose that combination of miR-191-5p and U6 could be used as reference genes for serum microRNAs qPCR data in colorectal adenocarcinoma, colorectal adenoma and healthy controls.     

Comparative Validation of Conventional and RNA-Seq Data-Derived Reference Genes for qPCR Expression Studies of Colletotrichum kahawae

Colletotrichum kahawae is an emergent fungal pathogen causing severe epidemics of Coffee Berry Disease on Arabica coffee crops in Africa. Currently, the molecular mechanisms underlying the Coffea arabica—C. kahawae interaction are still poorly understood, as well as the differences in pathogen aggressiveness, which makes the development of functional studies for this pathosystem a crucial step. Quantitative real time PCR (qPCR) has been one of the most promising approaches to perform gene expression analyses. However, proper data normalization with suitable reference genes is an absolute requirement. In this study, a set of 8 candidate reference genes were selected based on two different approaches (literature and Illumina RNA-seq datasets) to assess the best normalization factor for qPCR expression analysis of C. kahawae samples. The gene expression stability of candidate reference genes was evaluated for four isolates of C. kahawae bearing different aggressiveness patterns (Ang29, Ang67, Zim12 and Que2), at different stages of fungal development and key time points of the plant-fungus interaction process. Gene expression stability was assessed using the pairwise method incorporated in geNorm and the model-based method used by NormFinder software. For C. arabica—C. kahawae interaction samples, the best normalization factor included the combination of PP1, Act and ck34620 genes, while for C. kahawae samples the combination of PP1, Act and ck20430 revealed to be the most appropriate choice. These results suggest that RNA-seq analyses can provide alternative sources of reference genes in addition to classical reference genes. The analysis of expression profiles of bifunctional catalase-peroxidase (cat2) and trihydroxynaphthalene reductase (thr1) genes further enabled the validation of the selected reference genes. This study provides, for the first time, the tools required to conduct accurate qPCR studies in C. kahawae considering its aggressiveness pattern, developmental stage and host interaction.     

Validation of Candidate Reference Genes for the Accurate Normalization of Real-Time Quantitative RT-PCR Data in Rice During Seed Development

Rice seed, a natural storage organ for starch and protein, is also an ideal bioreactor for the production of valuable proteins. Increasingly, studies focused on rice have tried to determine the functions of its genes and also to improve its yield and quality. Real-time RT-PCR is the best available choice at present for gene expression analysis due to its accuracy, sensitivity, and reproducibility. The right choice of reference genes for normalization, however, is a critical precondition for reliable results. In this study, the expression stabilities of nine commonly used housekeeping genes in rice were carefully assessed using the software geNorm. Our results showed that eIF-4a and ACT1 were the most suitable reference genes among almost all the tested samples from two rice varieties, including different temporal and spatial-specific tissues, especially in seeds at different developmental stages. In contrast, 18S and 25S rRNAs, two common reference genes, were found to have the least stable expression. Moreover, it is necessary to use multiple suitable reference genes together for normalization to get a more reliable result in temporal and spatial expression analysis during rice seed development. The validated reference genes were further relied when used to quantify the expression of several genes of interest during rice seed development.     

Over Expression of Minichromosome Maintenance Genes is Clinically Correlated to Cervical Carcinogenesis

Minichromosome Maintenance (MCM) proteins play important roles in cell cycle progression by mediating DNA replication initiation and elongation. Among 10 MCM homologues MCM 2–7 form a hexamer and assemble to the pre-replication complex acting as replication licensing factors. Binding and function of MCM2-7 to pre-replication complex is regulated by MCM10 mediated binding of RECQL4 with MCM2-7. The purpose of this study is to explore the role of MCMs in cervical cancer and their correlation with the clinical parameters of cervical cancer. We have investigated sixty primary cervical cancer tissue samples, eight cervical cancer cell lines and thirty hysterectomised normal cervical tissue. The expression profiling of MCMs was done using semi-quantitative RT-PCR, immunoblotting and immunohistochemistry. MCM2, 4, 5, 6, 7, 10 and RECQL4 are significantly over-expressed in cervical cancer. Among these, MCM4, 6 and 10 show increased frequency of over expression along with advancement of tumor stages. MCM4, 5 and 6 also show differential expression in different types of lesion, while MCM2 and MCM10 are over expressed in cervical cancer irrespective of clinico-pathological parameters. Our data indicates the role of MCM4, MCM5, MCM6, MCM10 and RECQL4 in the progression of cervical cancer.     

Toward Enhanced MIQE Compliance: Reference Residual Normalization of qPCR Gene Expression Data

Normalization of fluorescence-based quantitative real-time PCR (qPCR) data varies across quantitative gene expression studies, despite its integral role in accurate data quantification and interpretation. Identification of suitable reference genes plays an essential role in accurate qPCR normalization, as it ensures that uncorrected gene expression data reflect normalized data. The reference residual normalization (RRN) method presented here is a modified approach to conventional 2^−ΔΔCtqPCR normalization that increases mathematical transparency and incorporates statistical assessment of reference gene stability. RRN improves mathematical transparency through the use of sample-specific reference residuals (RR_i) that are generated from the mean C_t of one or more reference gene(s) that are unaffected by treatment. To determine stability of putative reference genes, RRN uses ANOVA to assess the effect of treatment on expression and subsequent equivalence-threshold testing to establish the minimum permitted resolution. Step-by-step instructions and comprehensive examples that demonstrate the influence of reference gene stability on target gene normalization and interpretation are provided. Through mathematical transparency and statistical rigor, RRN promotes compliance with Minimum Information for Quantitative Experiments and, in so doing, provides increased confidence in qPCR data analysis and interpretation.     

Identification of Novel Reference Genes Using Multiplatform Expression Data and Their Validation for Quantitative Gene Expression Analysis

Normalization of mRNA levels using endogenous reference genes (ERGs) is critical for an accurate comparison of gene expression between different samples. Despite the popularity of traditional ERGs (tERGs) such as GAPDH and ACTB, their expression variability in different tissues or disease status has been reported. Here, we first selected candidate housekeeping genes (HKGs) using human gene expression data from different platforms including EST, SAGE, and microarray, and 13 novel ERGs (nERGs) (ARL8B, CTBP1, CUL1, DIMT1L, FBXW2, GPBP1, LUC7L2, OAZ1, PAPOLA, SPG21, TRIM27, UBQLN1, ZNF207) were further identified from these HKGs. The mean coefficient variation (CV) values of nERGs were significantly lower than those of tERGs and the expression level of most nERGs was relatively lower than high expressing tERGs in all dataset. The higher expression stability and lower expression levels of most nERGs were validated in 108 human samples including formalin-fixed paraffin-embedded (FFPE) tissues, frozen tissues and cell lines, through quantitative real-time RT-PCR (qRT-PCR). Furthermore, the optimal number of nERGs required for accurate normalization was as few as two, while four genes were required when using tERGs in FFPE tissues. Most nERGs identified in this study should be better reference genes than tERGs, based on their higher expression stability and fewer numbers needed for normalization when multiple ERGs are required.     

Validation of Reference Genes for Accurate Normalization of Gene Expression in Lilium davidii var. unicolor for Real Time Quantitative PCR

Lilium is an important commercial market flower bulb. qRT-PCR is an extremely important technique to track gene expression levels. The requirement of suitable reference genes for normalization has become increasingly significant and exigent. The expression of internal control genes in living organisms varies considerably under different experimental conditions. For economically important Lilium, only a limited number of reference genes applied in qRT-PCR have been reported to date. In this study, the expression stability of 12 candidate genes including α-TUB, β-TUB, ACT, eIF, GAPDH, UBQ, UBC, 18S, 60S, AP4, FP, and RH2, in a diverse set of 29 samples representing different developmental processes, three stress treatments (cold, heat, and salt) and different organs, has been evaluated. For different organs, the combination of ACT, GAPDH, and UBQ is appropriate whereas ACT together with AP4, or ACT along with GAPDH is suitable for normalization of leaves and scales at different developmental stages, respectively. In leaves, scales and roots under stress treatments, FP, ACT and AP4, respectively showed the most stable expression. This study provides a guide for the selection of a reference gene under different experimental conditions, and will benefit future research on more accurate gene expression studies in a wide variety of Lilium genotypes.     

黄梁木实时荧光定量PCR分析中内参基因的选择

为筛选黄梁木(Neolamarckia cadamba)实时定量PCR最佳内参基因, 该研究以黄梁木的根、芽、叶、花、果、皮及形成层为材料, 利用RT-qPCR技术对ACT、CAC、CYP和EF1α等21个管家基因家族43个候选内参基因进行表达量分析, 并利用geNorm、NormFinder和BestKeeper软件进行内参基因稳定性分析。geNorm的分析结果显示, UPL基因的稳定性最高(M=0.443), UBQ基因的稳定性最低(M=2.859); NormFinder的分析结果显示, UPL基因的稳定性最高(E=0.223), UBQ基因的稳定性最低(M=4.759); BestKeeper分析显示, UPL基因的标准偏差(SD=0.513)最低。研究结果表明, UPL基因作为内参基因稳定性最高, UBQ基因的稳定性最低。因此可以选择UPL基因作为黄梁木不同组织中RT-qPCR定量分析的内参基因。     

A Panel of Stably Expressed Reference Genes for Real-Time qPCR Gene Expression Studies of Mallards (Anas platyrhynchos)

Determining which reference genes have the highest stability, and are therefore appropriate for normalising data, is a crucial step in the design of real-time quantitative PCR (qPCR) gene expression studies. This is particularly warranted in non-model and ecologically important species for which appropriate reference genes are lacking, such as the mallard—a key reservoir of many diseases with relevance for human and livestock health. Previous studies assessing gene expression changes as a consequence of infection in mallards have nearly universally used β-actin and/or GAPDH as reference genes without confirming their suitability as normalisers. The use of reference genes at random, without regard for stability of expression across treatment groups, can result in erroneous interpretation of data. Here, eleven putative reference genes for use in gene expression studies of the mallard were evaluated, across six different tissues, using a low pathogenic avian influenza A virus infection model. Tissue type influenced the selection of reference genes, whereby different genes were stable in blood, spleen, lung, gastrointestinal tract and colon. β-actin and GAPDH generally displayed low stability and are therefore inappropriate reference genes in many cases. The use of different algorithms (GeNorm and NormFinder) affected stability rankings, but for both algorithms it was possible to find a combination of two stable reference genes with which to normalise qPCR data in mallards. These results highlight the importance of validating the choice of normalising reference genes before conducting gene expression studies in ducks. The fact that nearly all previous studies of the influence of pathogen infection on mallard gene expression have used a single, non-validated reference gene is problematic. The toolkit of putative reference genes provided here offers a solid foundation for future studies of gene expression in mallards and other waterfowl.     

Type 2 Diabetes Monocyte MicroRNA and mRNA Expression: Dyslipidemia Associates with Increased Differentiation-Related Genes but Not Inflammatory Activation

There is increasing evidence that inflammatory macrophages in adipose tissue are involved in insulin resistance of type 2 diabetes (T2D). Due to a relative paucity of data on circulating monocytes in T2D, it is unclear whether the inflammatory changes of adipose tissue macrophages are reflected in these easily accessible cells.

Objective

To study the expression pattern of microRNAs and mRNAs related to inflammation in T2D monocytes.

Design

A microRNA finding study on monocytes of T2D patients and controls using array profiling was followed by a quantitative Real Time PCR (qPCR) study on monocytes of an Ecuadorian validation cohort testing the top over/under-expressed microRNAs. In addition, monocytes of the validation cohort were tested for 24 inflammation-related mRNAs and 2 microRNAs previously found deregulated in (auto)-inflammatory monocytes.

Results

In the finding study, 142 significantly differentially expressed microRNAs were identified, 15 having the strongest power to discriminate T2D patients from controls (sensitivity 66%, specificity 90%). However, differences in expression of these microRNAs between patients and controls were small. On the basis of >1.4 or <0.6-fold change expression 5 microRNAs were selected for further validation. One microRNA (miR-34c-5p) was validated as significantly over-expressed in T2D monocytes. In addition, we found over expression of 3 mRNAs (CD9, DHRS3 and PTPN7) in the validation cohort. These mRNAs are important for cell morphology, adhesion, shape change, and cell differentiation. Classical inflammatory genes (e.g. TNFAIP3) were only over-expressed in monocytes of patients with normal serum lipids. Remarkably, in dyslipidemia, there was a reduction in the expression of inflammatory genes (e.g. ATF3, DUSP2 and PTGS2).

Conclusions

The expression profile of microRNAs/mRNAs in monocytes of T2D patients indicates an altered adhesion, differentiation, and shape change potential. Monocyte inflammatory activation was only found in patients with normal serum lipids. Abnormal lipid values coincided with a reduced monocyte inflammatory state.     

With Reference to Reference Genes: A Systematic Review of Endogenous Controls in Gene Expression Studies

The choice of reference genes that are stably expressed amongst treatment groups is a crucial step in real-time quantitative PCR gene expression studies. Recent guidelines have specified that a minimum of two validated reference genes should be used for normalisation. However, a quantitative review of the literature showed that the average number of reference genes used across all studies was 1.2. Thus, the vast majority of studies continue to use a single gene, with β-actin (ACTB) and/or glyceraldehyde 3-phosphate dehydrogenase (GAPDH) being commonly selected in studies of vertebrate gene expression. Few studies (15%) tested a panel of potential reference genes for stability of expression before using them to normalise data. Amongst studies specifically testing reference gene stability, few found ACTB or GAPDH to be optimal, whereby these genes were significantly less likely to be chosen when larger panels of potential reference genes were screened. Fewer reference genes were tested for stability in non-model organisms, presumably owing to a dearth of available primers in less well characterised species. Furthermore, the experimental conditions under which real-time quantitative PCR analyses were conducted had a large influence on the choice of reference genes, whereby different studies of rat brain tissue showed different reference genes to be the most stable. These results highlight the importance of validating the choice of normalising reference genes before conducting gene expression studies.