Reference Gene Validation for RT-qPCR, a Note on Different Available Software Packages

Background: An appropriate normalization strategy is crucial for data analysis from real time reverse transcription polymerase chain reactions (RT-qPCR). It is widely supported to identify and validate stable reference genes, since no single biological gene is stably expressed between cell types or within cells under different conditions. Different algorithms exist to validate optimal reference genes for normalization. Applying human cells, we here compare the three main methods to the online available RefFinder tool that integrates these algorithms along with R-based software packages which include the NormFinder and GeNorm algorithms. Results: 14 candidate reference genes were assessed by RT-qPCR in two sample sets, i.e. a set of samples of human testicular tissue containing carcinoma in situ (CIS), and a set of samples from the human adult Sertoli cell line (FS1) either cultured alone or in co-culture with the seminoma like cell line (TCam-2) or with equine bone marrow derived mesenchymal stem cells (eBM-MSC). Expression stabilities of the reference genes were evaluated using geNorm, NormFinder, and BestKeeper. Similar results were obtained by the three approaches for the most and least stably expressed genes. The R-based packages NormqPCR, SLqPCR and the NormFinder for R script gave identical gene rankings. Interestingly, different outputs were obtained between the original software packages and the RefFinder tool, which is based on raw Cq values for input. When the raw data were reanalysed assuming 100% efficiency for all genes, then the outputs of the original software packages were similar to the RefFinder software, indicating that RefFinder outputs may be biased because PCR efficiencies are not taken into account. Conclusions: This report shows that assay efficiency is an important parameter for reference gene validation. New software tools that incorporate these algorithms should be carefully validated prior to use

Altered Expression of ZO-1 and ZO-2 in Sertoli Cells and Loss of Blood-Testis Barrier Integrity in Testicular Carcinoma In Situ

Carcinoma in situ (CIS) is the noninvasive precursor of most human testicular germ cell tumors. In normal seminiferous epithelium, specialized tight junctions between Sertoli cells constitute the major component of the blood-testis barrier. Sertoli cells associated with CIS exhibit impaired maturation status, but their functional significance remains unknown. The aim was to determine whether the blood-testis barrier is morphologically and/or functionally altered. We investigated the expression and distribution pattern of the tight junction proteins zonula occludens (ZO) 1 and 2 in normal seminiferous tubules compared to tubules showing CIS. In normal tubules, ZO-1 and ZO-2 immunostaining was observed at the blood-testis barrier region of adjacent Sertoli cells. Within CIS tubules, ZO-1 and ZO-2 immunoreactivity was reduced at the blood-testis barrier region, but spread to stain the Sertoli cell cytoplasm. Western blot analysis confirmed ZO-1 and ZO-2, and their respective mRNA were shown by RT-PCR. Additionally, we assessed the functional integrity of the blood-testis barrier by lanthanum tracer study. Lanthanum permeated tight junctions in CIS tubules, indicating disruption of the blood-testis barrier. In conclusion, Sertoli cells associated with CIS show an altered distribution of ZO-1 and ZO-2 and lose their blood-testis barrier function

On the origin of germ cell neoplasia in situ: Dedifferentiation of human adult Sertoli cells in cross talk with seminoma cells in vitro

Germ cell neoplasia in situ (GCNIS) is the noninvasive precursor of testicular germ cell tumors type II, the most common cancer in young men, which originates from embryonic germ cells blocked in their maturation. GCNIS is associated with impaired Sertoli cells (SCs) that express fetal keratin 18 (KRT18) and the pluripotency factor SRY-Box transcription factor 2 (SOX2). According to the current theory concerning the origin of GCNIS, these SCs are prepubertal cells arrested in their maturation due to (epi)genetic anomalies and/or environmental antiandrogens. Thus, they are unable to support the development of germ cells, which leads to their maturational block and further progresses into GCNIS. Alternatively, these SCs are hypothesized to be adult cells dedifferentiating secondarily under the influence of GCNIS. To examine whether tumor cells can dedifferentiate SCs, we established a coculture model of adult human SCs (FS1) and a seminoma cell line similar to GCNIS (TCam-2). After 2 wk of coculture, FS1 cells showed progressive expression of KRT18 and SOX2, mimicking the in vivo changes. TCam-2 cells showed SOX2 expression and upregulation of further pluripotency- and reprogramming-associated genes, suggesting a seminoma to embryonal carcinoma transition. Thus, our FS1/TCam-2 coculture model is a valuable tool for investigating interactions between SCs and seminoma cells. Our immunohistochemical and ultrastructural studies of human testicular biopsies with varying degrees of GCNIS compared to biopsies from fetuses, patients with androgen insensitivity syndrome, and patients showing normal spermatogenesis further suggest that GCNIS-associated SCs represent adult cells undergoing progressive dedifferentiation

Primers used in the study (Ta: annealing temperature).

<p>All samples were run in triplicate and each run included three no template controls. Standard dilution curves were generated to determine PCR efficiency using cDNA of normal testicular tissue. RT-qPCR was performed in 20 μl final volume containing 1 μl cDNA, 0.6 μl of primers each (10 μM), and 10 μl iQ SYBR Green Supermix (Bio-Rad, Hercules, CA). RT-qPCR was performed on a CFX 96 Real-Time system (Bio-Rad) with a two-step method. The hot start enzyme was activated (95°C for 3 min), and cDNA was amplified for 40 cycles consisting of denaturation at 95°C for 10 s and annealing/extension at 59°C for 30 s. Afterwards a melt curve assay was performed (59°C of 1 min and then the temperature was increased until 94°C by an increment of 0.5°C every 5 s) to detect the formation of non-specifically amplified products.</p><p>Primers used in the study (Ta: annealing temperature).</p

NormFinder outputs with efficiency corrected data (blue bars) and without efficiency corrected data (red bars) for the two datasets, i.e. FS1 (A) and CIS (B).

<p>NormFinder outputs with efficiency corrected data (blue bars) and without efficiency corrected data (red bars) for the two datasets, i.e. FS1 (A) and CIS (B).</p

BestKeeper outputs of reference genes ranked by the correlation coefficients (A&C) or by their standard deviation (B&D) for the two datasets, i.e. FS1 (A&B) and CIS (C&D).

<p>BestKeeper outputs of reference genes ranked by the correlation coefficients (A&C) or by their standard deviation (B&D) for the two datasets, i.e. FS1 (A&B) and CIS (C&D).</p

geNorm outputs with efficiency corrected data (A&C) and without efficiency corrected data (B&D) for the two datasets, i.e. FS1 (A&B) and CIS (C&D).

<p>geNorm outputs with efficiency corrected data (A&C) and without efficiency corrected data (B&D) for the two datasets, i.e. FS1 (A&B) and CIS (C&D).</p