High expression stability of microtubule affinity regulating kinase 3 (MARK3) makes it a reliable reference gene

Chia, Ching-Yee; Lim, Claudia W X; Leong, Wan-Ting; Ling, Maurice Ht

doi:10.1002/iub.295

Cited by 11 publications

(21 citation statements)

References 25 publications

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“…For example, several studies had analyzed published microarray datasets for reference genes [63,64] and other biologically significant features [65]. Moreover, most of the 30 microarrays originated from studies that were representative of the type of experimental studies which we expect our predictor to be useful in.…”

Section: Resultsmentioning

confidence: 99%

A predictor for predicting Escherichia colitranscriptome and the effects of gene perturbations

Ling

Poh

2014

BMC Bioinformatics

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BackgroundA means to predict the effects of gene over-expression, knockouts, and environmental stimuli in silico is useful for system biologists to develop and test hypotheses. Several studies had predicted the expression of all Escherichia coli genes from sequences and reported a correlation of 0.301 between predicted and actual expression. However, these do not allow biologists to study the effects of gene perturbations on the native transcriptome.ResultsWe developed a predictor to predict transcriptome-scale gene expression from a small number (n = 59) of known gene expressions using gene co-expression network, which can be used to predict the effects of over-expressions and knockdowns on E. coli transcriptome. In terms of transcriptome prediction, our results show that the correlation between predicted and actual expression value is 0.467, which is similar to the microarray intra-array variation (p-value = 0.348), suggesting that intra-array variation accounts for a substantial portion of the transcriptome prediction error. In terms of predicting the effects of gene perturbation(s), our results suggest that the expression of 83% of the genes affected by perturbation can be predicted within 40% of error and the correlation between predicted and actual expression values among the affected genes to be 0.698. With the ability to predict the effects of gene perturbations, we demonstrated that our predictor has the potential to estimate the effects of varying gene expression level on the native transcriptome.ConclusionWe present a potential means to predict an entire transcriptome and a tool to estimate the effects of gene perturbations for E. coli, which will aid biologists in hypothesis development. This study forms the baseline for future work in using gene co-expression network for gene expression prediction.

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Section: Resultsmentioning

confidence: 99%

A predictor for predicting Escherichia colitranscriptome and the effects of gene perturbations

Ling

Poh

2014

BMC Bioinformatics

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“…The advantage of COV is its capability to analyse as large number of samples as required [23] as the number of calculations increases proportionally to the sample size, resulting in linear complexity. NormFinder uses residual analysis between sample subgroup variation and the overall variation of the expression dataset to evaluate the variation contributed by each gene in the entire dataset [20].…”

Section: Resultsmentioning

confidence: 99%

“…However, microarrays, which usually contain thousands of probes, present a good source of data for identifying reference genes [22]. A recent study had successfully identified MARK3 as a suitable reference gene in mouse liver using microarray analysis [23]. …”

Section: Introductionmentioning

confidence: 99%

Glucan Biosynthesis Protein G Is a Suitable Reference Gene in Escherichia coli K-12

et al. 2011

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The expressions of reference genes used in gene expression studies are assumed to be stable under most circumstances. However, a number of studies had demonstrated that such genes were found to vary under experimental conditions. In addition, genes that are stably expressed in an organ may not be stably expressed in other organs or other organisms, suggesting the need to identify reference genes for each organ and organism. This study aims at identifying stably expressed genes in Escherichia coli. Microarray datasets from E. coli substrain MG1655 and 1 dataset from W3110 were analysed. Coefficient of variance (COV) of was calculated and 10% of the lowest COV from 4631 genes common in the 3 MG1655 sets were analysed using NormFinder. Glucan biosynthesis protein G (mdoG), which is involved in cell wall synthesis, displayed the lowest weighted COV and weighted NormFinder Stability Index for the MG1655 datasets, while also showing to be the most stable in the dataset for substrain W3110, suggesting that mdoG is a suitable reference gene for E. coli K-12. Gene ontology over-representation analysis on the 39 genes suggested an over-representation of cell division, carbohydrate metabolism, and protein synthesis which supports the short generation time of E. coli.

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“…The expression stability was evaluated based on the assumption that a lower CV value means lower variations of POI expression levels within each group. CV values equal to or less than 10% were used for selecting stable genes in a previous study,6 the same criterion was adopted in this study.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of Protein Expression in Housekeeping Genes across Multiple Tissues in Rats

Kim

Min

et al. 2014

Korean J Pathol

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BackgroundHousekeeping genes, which show constant protein expression patterns between different tissue types, are very important in molecular biological studies as an internal control for protein research.MethodsThe protein expression profiles of seven housekeeping genes (HPRT1, PPIA, GYS1, TBP, YWHAZ, GAPDH and ACTB) in various rat tissues (cerebrum, cerebellum, cardiac ventricle and atrium, psoas muscle, femoral muscle, liver, spleen, kidney, and aorta) were analyzed by Western blot and compared by coefficient of variation (CV).ResultsHPRT1 was stably expressed (CV≤10%) in six tissues (cerebrum, cerebellum, ventricle, femoral muscle, spleen, and kidney), PPIA was stably expressed in five tissues (cerebrum, cerebellum, ventricle, spleen and kidney), YWHAZ was stably expressed in three tissues (cerebrum, cerebellum, and kidney), and GAPDH was stably expressed in four tissues (cerebrum, ventricle, psoas muscle, and kidney). In comparison, GYS1, TBP, and ACTB were found to have CV values over 10% in all tissues. Of the seven genes examined, four (HPRT1, PPIA, YWHAZ, and GAPDH) were found to be stably expressed across multiple organs, with low CV values (≤10%).ConclusionsThese results will provide fundamental information regarding internal controls for protein expression studies and can be used for analysis of postmortem protein degradation patterns in forensic medicine.

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High expression stability of microtubule affinity regulating kinase 3 (MARK3) makes it a reliable reference gene

Cited by 11 publications

References 25 publications

A predictor for predicting Escherichia colitranscriptome and the effects of gene perturbations

A predictor for predicting Escherichia colitranscriptome and the effects of gene perturbations

Glucan Biosynthesis Protein G Is a Suitable Reference Gene in Escherichia coli K-12

Evaluation of Protein Expression in Housekeeping Genes across Multiple Tissues in Rats

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