Computational protocol: Identification of Suitable Reference Genes for Gene Expression Studies in Tendons from Patients with Rotator Cuff Tear

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Protocol publication

[…] We categorized the tissue samples into the following 12 groups: 1) CC samples (N = 28); 2) PC samples (N = 28); 3) AC samples (N = 28); 4) CC and PC samples (N = 56); 5) CC and AC samples (N = 56); 6) all tissue samples from cases (N = 84); 7) CCC samples (N = 8); 8) ACC samples (N = 8); 9) all tissue samples from controls (N = 16); 10) CC and CCC samples (N = 36); 11) AC and ACC samples (N = 36) and 12) all tissue samples (N = 100). Typically, gene expression studies compare transcript levels between case (i.e., the injured tissue) and control samples. We considered three types of possible controls: PC, AC [] and CCC [,,] samples; therefore we created the groups #4, #5 and #10, respectively. However, some researchers have been investigated a possible association between gene expression and clinical variables [,] and also have been reported the presence of molecular alterations of subscapular tendon samples of patients with supraspinatus tears [,]; therefore we chose to present the analysis of suitable reference gene in each type of tendon. In addition, the group composed by all tissue samples from controls (group #9), as well as was the group composed by macroscopically non-injured subscapular tendons (group #11), were created since the understanding of gene expression regulation in non-injured tendons is still necessary.For comparisons of candidate reference gene stability we used NormFinder (, geNorm (∼jvdesomp/genorm/∼jvdesomp/genorm/), BestKeeper1 ( and DataAssist ( software programs according to the recommendations of the software guides.NormFinder accounts for both intra- and inter-group variations when evaluating the stability of each single reference gene []. The stability values and standard errors are calculated according to the transcription variation of the reference genes. Stably expressed genes, which have low variation in expression levels, present low stability values. NormFinder analysis also calculated the stability value for two reference genes.geNorm calculates the expression stability value (M) for each gene based on the average pairwise expression ratio between a particular gene and all other reference genes. geNorm sequentially eliminates the gene that shows the highest variation relative to all the other genes based on paired expression values in all the studied samples. The most stably expressed gene yields the lowest M value, and then the two most stable reference genes are determined by stepwise exclusion of the least stable gene []. Because of the elimination process, geNorm cannot identify a single suitable reference gene, and ends up by suggesting a pair of genes that shows high correlation and should be suitable for normalization of qPCR studies.Bestkeeper was used to rank the 6 reference genes based on the standard deviation (SD) and coefficient of variance (CV) expressed as a percentage of the cycle threshold (Ct) level []. The more stable reference gene presents the lowest CV and SD. Bestkeeper also uses a statistical algorithm wherein the Pearson correlation coefficient for each candidate reference gene pair is calculated along with the probability of correlation significance of the pair.Lastly, DataAssist software provided a metric to measure reference gene stability based on the geNorm algorithm. In contrast to the other programs, DataAssist uses RQ to calculate the stability value of individual candidate reference genes. The lower score represents the more stable the control.GenEx software ( was used to determine the optimal number of reference genes by calculating the accumulated standard deviation (Acc.SD). If larger number of reference genes is used, random variation among the genes’ expression partially cancel reducing the SD. A minimum in the Acc.SD plot indicate the number of reference genes that give the lowest SD. […]

Pipeline specifications

Software tools NormFinder, geNorm, BestKeeper
Databases MedGen
Application qPCR
Organisms Homo sapiens
Diseases Liver Diseases, Tendinopathy