Accurate Quantification Of Gene Expression Research Articles

Development of reference genes for RT-qPCR analysis of gene expression in Pleurotus pulmonarius for biotechnological applications

Jatropha curcas is an oilseed crop with biorefinery applications. Whilst cake generated following oil extraction offers potential as a protein source for animal feed, inactivation of toxic phorbol esters present in the material is necessary. Pleurotus pulmonarius is a detoxifying agent for jatropha cake with additional potential as animal feed, edible mushroom and for enzyme production. For the characterization of fungal genes involved in phorbol ester degradation, together with other industrial applications, reverse transcription-quantitative PCR (RT-qPCR) is a tool that enables accurate quantification of gene expression. For this, reliable analysis requires reference genes for normalization of mRNA levels validated under conditions employed for target genes. The stability of potential reference genes β-TUB, ACTIN, GAPDH, PHOS, EF1α, TRPHO, LAC, MNP3, MYP and VP were evaluated following growth of P. pulmonarius on toxic, non-toxic jatropha cake and a combined treatment, respectively. NormFinder and geNorm algorithms for expression stability analysis identified PHOS, EF1α and MNP3 as appropriate for normalizing gene expression. Reference gene combinations contrasting in ranking were compared following normalization of relative expression of the CHU_2040 gene, encoding an esterase enzyme potentially involved in phorbol ester degradation. The reference genes for P. pulmonarius will facilitate the elucidation of mechanisms involved in detoxification of phorbol esters as well as analysis of target genes for application in biorefinery models.

Direct lysis of 3D cell cultures for RT-qPCR gene expression quantification

In vitro cell culture experiments are widely used to study cellular behavior in most biological research fields. Except for suspension cells, most human cell types are cultured as adherent monolayers on a plastic surface. While technically convenient, monolayer cultures can suffer from limitations in terms of physiological relevance, as their resemblance to complex in vivo tissue structures is limited. To address these limitations, three-dimensional (3D) cell culture systems have gained increased interest as they mimic key structural and functional properties of their in vivo tissue counterparts. Nevertheless, protocols established on monolayer cell cultures may require adjustments if they are to be applied to 3D cell cultures. As gene expression quantification is an essential part of many in vitro experiments, we evaluated and optimized a direct cell lysis, reverse transcription and qPCR protocol applicable for 3D cell cultures. The newly developed protocol wherein gene expression is determined directly from crude cell lysates showed improved cell lysis compared to the standard protocol, accurate gene expression quantification, hereby avoiding time-consuming cell harvesting and RNA extraction.

Selection and Validation of Reference Genes for Normalization of RT-qPCR Analysis in Developing or Abiotic-Stressed Tissues of Loquat (Eriobotrya japonica)

Loquat (Eriobotrya japonica Lindl.) is a subtropical evergreen fruit tree that produces fruits with abundant nutrients and medicinal components. Confirming suitable reference genes for a set of loquat samples before qRT-PCR experiments is essential for the accurate quantification of gene expression. In this study, eight candidate reference genes were selected from our previously published RNA-seq data, and primers for each candidate reference gene were designed and evaluated. The Cq values of the candidate reference genes were calculated by RT-qPCR in 31 different loquat samples, including 12 subgroups of developing or abiotic-stressed tissues. Different combinations of stable reference genes were screened according to a comprehensive rank, which was synthesized from the results of four algorithms, including the geNorm, NormFinder, BestKeeper and ΔCt methods. The screened reference genes were verified by normalizing EjLGA1 in each subgroup. The obtained suitable combinations of reference genes for accurate normalization were GAPDH, EF1α and ACT for floral development; GAPDH, UBCE and ACT for fruit setting; EF1α, GAPDH and eIF2B for fruit ripening; ACT, EF1α and UBCE for leaves under heat stress; eIF2B, UBCE and EF1α for leaves under freezing stress; EF1α, TUA and UBCE for leaves under salt stress; ACT, EF1α and eIF2B for immature pulp under freezing stress; ACT, UBCE and eIF2B for immature seeds under freezing stress; EF1α, eIF2B and UBCE for both immature pulp and seeds under freezing stress; UBCE, TUB and TUA for red-fleshed fruits under cold-storage stress; eIF2B, RPS3 and TUB for white-fleshed fruits under cold-storage stress; and eIF2B, UBCE and RPS3 for both red- and white-fleshed fruits under cold-storage stress. This study obtained different combinations of stable reference genes for accurate normalization in twelve subgroups of developing or abiotic-stressed tissues in loquat. To our knowledge, this is the first report to obtain stable reference genes for normalizing gene expression of abiotic-stressed tissues in E. japonica. The use of the three most stable reference genes could increase the reliability of future quantification experiments.

Selection and Validation of Suitable Reference Genes for Gene Expression Studies in Callerya speciosa (Champ. ex Benth.) Schot under Different Experimental Conditions

The accuracy of reverse transcription quantitative real-time PCR (RT-qPCR) strongly depends on the stability of reference gene. It is essential to select a suitable reference gene in order to obtain reliable RT-qPCR results when gene expression profiles were evaluated. Callerya speciosa, a traditional Chinese medicine, has a long cultivation history in south China. However, suitable reference genes in C. speciosa have not yet been investigated for accurate gene expression quantification under different experimental conditions. In this study, eight candidate reference genes, including GAPDH (glyceraldehyde-3-phosphate dehydrogenase), 60S (60S ribosomal protein L34), ACTIN (actin), TUA2 (tubulin alpha chain), TUB1 (tubulin beta-1 chain), TIF5 (eukaryotic translation initiation factor 5A), UBQ (polyubiquitin), and EF2 (elongation factor 2), were selected from the transcriptome databases, and their expression stability under six different experimental conditions (developmental stages, tissues, MeJA treatment, GA3 treatment, CPPU treatment, and PP333 treatment) was evaluated using ΔCT, geNorm, NormFinder, BestKeeper, and RefFinder programs. The results showed that GAPDH was the optimal reference gene for all different experimental conditions, whereas ACTIN showed the best stability under most of the hormone treatments. TUA2 and EF2 were the two least suitable ones as reference genes in C. speciosa. The expression pattern of CsMYB36, a gene associated with the regulation of isoflavonoid biosynthesis in C. speciosa, verified the accuracy of our experimental results. These results provided a theoretical basis for subsequent research on the regulation of functional gene expression in C. speciosa and other Callerya species in the future.

Identification and Validation of Reference Genes for Expression Analysis Using qRT-PCR in Cimex hemipterus (Hemiptera: Cimicidae).

The tropical bed bug, Cimex hemipterus (F.) (Hemiptera: Cimicidae) is an important public-health pest that feeds on the blood of humans and some other animals. To explore the function of the target genes of C. hemipterus, it is essential to select suitable reference genes for the accurate quantification of gene expression. Here, we selected 10 frequently used reference genes in insects and evaluated their stability in C. hemipterus under various biotic (developmental stage, sex, and tissue) and abiotic (gas stimulation and temperature) conditions through RefFinder (which integrates four computational programs: geNorm, NormFinder, BestKeeper, and ∆Ct). Results indicate that the optimal combination of reference genes for each experimental condition was as follows: RPL8 and EF1α for the developmental stage (eggs, early instar nymphs, late instar nymphs, and adults), RPL8 and RPS16 for adult sex, RPL8 and RPL11 for adult tissue (head, thorax, abdomen, and legs), RPL8 and β-tubulin for gas stimulation (air and carbon dioxide), and RPL8 and NADH for temperature (0, 5, 17, 30, and 37 °C). Finally, the expression pattern of the HSP70 and GR21 genes were analyzed, and the results highlight the importance of appropriate reference-gene selection. Our results provide a comprehensive list of optimal reference genes from C. hemipterus for the first time, which will contribute to accurately analyzing the expression of target genes.

Identification of suitable reference genes for normalization of quantitative real-time PCR-based gene expression in chicken (Gallus gallus).

The recent availability of genome information greatly facilitates the fundamental research on chicken. In different organs, gene expression patterns can provide clues to understanding the biological functions. For rapid and accurate quantification of gene expression, quantitative real-time PCR (qPCR) has become one of the most widely used methods. However, the success of qPCR data normalization depends on the use of a suitable reference gene and a single reference gene is not universally suitable for all the experiments. Therefore, reference gene validation is a crucial step for different organ tissues of chicken where suitable reference genes for qPCR analysis in varieties of tissues have not been investigated exhaustively so far. In this study, we have selected 30 Gallus gallus candidate reference genes from NCBI, amplified and studied their expression profiles by qPCR in different organ tissues (breast muscle, thigh muscle, heart, liver, spleen, gizzard, and bursa) of chicken. The result showed that, for breast muscle HSP10 and RPL23, thigh muscle RPL14 and RPL13, liver ALB and HSP70, spleen ALB and GAPDH, heart CYCS and TUBA8B, gizzard RPL5 and 18S rRNA, and bursa EEF1A1 and PGK2 are most stable genes respectively. The results also showed that for different organ tissues, individual or a combination of reference genes should be selected for data normalization. In this study, we have identified and validated 30 reference genes in seven different organ tissues to provide accurate transcript normalization and quantification, which can be useful for gene expression studies in other avian species.

RiboCleaner: a pipeline to identify and quantify rRNA read contamination from RNA-seq data in plants.

Analysis of gene expression data can be crucial for elucidating biological relationships within living organisms. However, accurate quantification of gene expression relies directly upon the accuracy of the reference genome or transcriptome to which the expression data are mapped. Errors in gene annotation can lead to errors in the quantification of gene expression. One source of gene annotation error in eukaryotes arises from incorrect predictions of messenger RNA gene models within ribosomal DNA (rDNA) regions. Here, we provide examples of how the presence of false gene models in rDNA regions can result in a handful of genes appearing to contribute to >50% of the total transcripts per million values of entire RNA-seq datasets. To this end, we have created riboCleaner, a bioinformatics pipeline designed to identify misannotated gene models in rDNA regions and quantify rRNA-derived reads in RNA-seq data. We also show the applicability of riboCleaner in several plant genome assemblies. We have implemented riboCleaner as a containerized Snakemake workflow. The workflow, instructions for building the container and other documentation are available at https://github.com/basf. The data underlying this article are available in GitHub at https://github.com/basf/riboCleaner. For convenience, a prebuilt Docker image containing riboCleaner is available at https://hub.docker.com/u/basfcontainers. Supplementary data are available at Bioinformatics online.

RNA-Seq Experiment and Data Analysis.

With the ability to obtain several millions of reads per sample, high-throughput RNA sequencing (RNA-Seq) enables investigation of any transcriptome at a fine resolution. Not just the messenger RNA (mRNA), but a wide variety of different RNA populations (e.g., total RNA, microRNA, long ncRNA, pre-mRNA) can also be investigated using RNA-Seq. While facilitating accurate quantification of gene expression, RNA-Seq offers the opportunity to estimate abundance of isoforms and find novel transcripts and allele-specific transcripts. In this chapter, we describe a protocol to construct an RNA-Seq library for sequencing on Illumina NGS platforms and a computational pipeline to perform RNA-Seq data analysis. The protocols described in this chapter can be applied to the analysis of differential gene expression in control versus 17β-estradiol treatment of in vivo or in vitro systems.

Genetic diseases in the omics era

Accurate quantification of gene expression at RNA and protein levels has provided invaluable insight into the mechanisms of biological processes in health and disease. The so-called “-omics” technologies (transcriptomics, proteomics, but also epigenomics, etc.) enabled researchers to detect expression changes specifically associated with given biological states and, more recently, to establish their dynamics at a single-cell resolution in stem cell-based models. In this issue of Molecular Therapy, Djeddi et al.

Systematic Identification of Housekeeping Genes Possibly Used as References in Caenorhabditis elegans by Large-Scale Data Integration.

For accurate gene expression quantification, normalization of gene expression data against reliable reference genes is required. It is known that the expression levels of commonly used reference genes vary considerably under different experimental conditions, and therefore, their use for data normalization is limited. In this study, an unbiased identification of reference genes in Caenorhabditis elegans was performed based on 145 microarray datasets (2296 gene array samples) covering different developmental stages, different tissues, drug treatments, lifestyle, and various stresses. As a result, thirteen housekeeping genes (rps-23, rps-26, rps-27, rps-16, rps-2, rps-4, rps-17, rpl-24.1, rpl-27, rpl-33, rpl-36, rpl-35, and rpl-15) with enhanced stability were comprehensively identified by using six popular normalization algorithms and RankAggreg method. Functional enrichment analysis revealed that these genes were significantly overrepresented in GO terms or KEGG pathways related to ribosomes. Validation analysis using recently published datasets revealed that the expressions of newly identified candidate reference genes were more stable than the commonly used reference genes. Based on the results, we recommended using rpl-33 and rps-26 as the optimal reference genes for microarray and rps-2 and rps-4 for RNA-sequencing data validation. More importantly, the most stable rps-23 should be a promising reference gene for both data types. This study, for the first time, successfully displays a large-scale microarray data driven genome-wide identification of stable reference genes for normalizing gene expression data and provides a potential guideline on the selection of universal internal reference genes in C. elegans, for quantitative gene expression analysis.

Identification and Validation of Reference Genes in the Adzuki Bean (Vigna angularis) Under Iron Deficiency Using Quantitative Real-Time PCR

Adzuki bean (Vigna angularis var. angularis), an important food legume, is grown in more than 30 countries, especially in East Asia. Almost 25% of the world population is affected by iron deficiency. Iron is very important on adzuki bean yield and quality. The identification of suitable reference genes in adzuki bean is important for exploring gene expression and the molecular mechanisms of gene, yet few reference genes have been reported for adzuki bean. This research systematically evaluated the stability of 11 candidate reference genes (ACT, ACT1, CYP, CYP2, SKIP16, ELF1B, HDC, Lectin, TUA, PEPKR1, and 18SrRNA) using the geNorm, NormFinder, BestKeeper, and RefFinder protocols under iron-deficient stress. The best combined number of reference genes for all samples was two. ELF1B/Lectin was best for qRT-PCR analysis of roots and combined analysis of roots, stems, and leaves under iron deficiency, ELF1B/CYP was optimum for leaves, and SKIP16/PEPKR1 was optimum for stems. The identification of these reference genes will enable accurate quantification of gene expression under iron deficiency and enhance our comprehension of reference genes in adzuki bean.

3\u2019Pool-seq: an optimized cost-efficient and scalable method of whole-transcriptome gene expression profiling

BackgroundThe advent of Next Generation Sequencing has allowed transcriptomes to be profiled with unprecedented accuracy, but the high costs of full-length mRNA sequencing have posed a limit on the accessibility and scalability of the technology. To address this, we developed 3’Pool-seq: a simple, cost-effective, and scalable RNA-seq method that focuses sequencing to the 3′-end of mRNA. We drew from aspects of SMART-seq, Drop-seq, and TruSeq to implement an easy workflow, and optimized parameters such as input RNA concentrations, tagmentation conditions, and read depth specifically for bulk-RNA.ResultsThorough optimization resulted in a protocol that takes less than 12 h to perform, does not require custom sequencing primers or instrumentation, and cuts over 90% of the costs associated with TruSeq, while still achieving accurate gene expression quantification (Pearson’s correlation coefficient with ERCC theoretical concentration r = 0.96) and differential gene detection (ROC analysis of 3’Pool-seq compared to TruSeq AUC = 0.921). The 3’Pool-seq dual indexing scheme was further adapted for a 96-well plate format, and ERCC spike-ins were used to correct for potential row or column pooling effects. Transcriptional profiling of troglitazone and pioglitazone treatments at multiple doses and time points in HepG2 cells was then used to show how 3’Pool-seq could distinguish the two molecules based on their molecular signatures.Conclusions3’Pool-seq can accurately detect gene expression at a level that is on par with TruSeq, at one tenth of the total cost. Furthermore, its unprecedented TruSeq/Nextera hybrid indexing scheme and streamlined workflow can be applied in several different formats, including 96-well plates, which allows users to thoroughly evaluate biological systems under several conditions and timepoints. Care must be taken regarding experimental design and plate layout such that potential pooling effects can be accounted for and corrected. Lastly, further studies using multiple sets of ERCC spike-ins may be used to simulate differential gene expression in a system with known ground-state values.

Evaluation of Suitable Reference Genes for Normalization of RT-qPCR in Echiura (Urechis unicinctus) during Developmental Process

Reverse transcription quantitative PCR (RT-qPCR) is commonly used for gene expression analysis. Appropriate reference genes enable the accurate quantification of gene expression. In this study, expressional stability of seven candidate reference genes in embryos and larvae of the Echiura Urechis unicinctus were evaluated using four programs, geNorm, NormFinder, BestKeeper, and ∆Ct method. The expressional stability was ATPase > eIF3 > EF-1-α > TUB > IDH > VDAC > ABL based on the comprehensive analysis, and the combination of ATPase, eIF3, and EF-1-α was predicted to be the most optimum choice for accurate gene quantification during the developmental process. Furthermore, we verified the competence of the candidate reference genes/combinations through evaluating the expression levels of TGF-β receptor 1 (TGFβR1) and SMAD4, and inspiringly found using either ATPase or eIF3 alone generated exactly similar results with that of using reference gene combinations. Therefore, we suggested that under certain circumstances, ATPase or eIF3 could be independently used as an alternative to quantify target gene expression in U. unicinctus during developmental process. This study provides important information for gene expression and function researches in Echiura or Annelida species.

Evaluation of suitable reference genes for normalization of quantitative reverse transcription PCR analyses in Clavibacter michiganensis.

Clavibacter michiganensis, the causal agent of bacterial canker of tomato, is a Gram‐positive bacterium and a model for studying plant diseases. The real‐time quantitative reverse transcription PCR (real‐time qRT‐PCR) assay is widely used to quantify gene expression in plant pathogenic bacteria. However, accurate quantification of gene expression requires stably expressed reference genes that are consistently expressed during the experimental conditions of interest. The use of inappropriate reference genes leads to a misinterpretation of gene expression data and false conclusions. In current study, we empirically assessed the expression stability of six housekeeping genes (gyrB, rpoB, tufA, bipA, gapA, and pbpA) of C. michiganensis under five experimental conditions using two algorithms, geNorm and NormFinder. C. michiganensis expressed gyrB, bipA, and gapA stably when growing in nutrient‐rich broth (TBY broth and modified M9 broth). We concluded that pbpA, tufA, and gyrB were suitable reference genes in C. michiganensis—tomato interaction studies. We also recommended bipA and rpoB to be used to study bacterial gene expression under nutrient‐poor conditions. Finally, gyrB, pbpA, and rpoB can be used to normalize the quantification of C. michiganensis gene expression while the bacterium is in the viable but nonculturable (VBNC) state. This study identified the most suitable reference genes depending on the experimental conditions for calibrating real‐time qRT‐PCR analyses of C. michiganensis and will be useful in studies that seek to understand the molecular interactions between C. michiganensis and tomato.

Validation of Reference Genes for Gene Expression Normalization in RAW264.7 Cells under Different Conditions.

RAW264.7 is a macrophage strain derived from mice tumour and shows a significant ability in antigen uptake. Real-time quantitative PCR (RT-qPCR) is one of the most commonly used methods in gene studies and requires suitable reference genes to normalize and quantitate the expression of gene of interest with sensitivity and specificity. However, suitable reference genes in RAW264.7 cells have not yet been identified for accurate gene expression quantification. In the current study, we evaluated expression levels of ten candidate reference genes in RAW264.7 cells under different conditions. RT-qPCR results indicated significant differences in the expression levels among the ten reference genes. Statistical analyses were carried out using geNorm, NormFinder, and BestKeeper software to further investigate the stability of the reference genes. Integrating the results from the three analytical methods, cytochrome c-1 and hydroxymethylbilane synthase were found to be the most stable and therefore more suitable reference genes, while ribosomal protein L4 and cyclophilin A were the least stable. This study emphasises the importance of identifying and selecting the most stable reference genes for normalization and provides a basis for future gene expression studies using RAW264.7 cells.

Selection of Reference Genes for Real-time Quantitative PCR Normalization in the Process of Gaeumannomyces graminis var. tritici Infecting Wheat.

Gaeumannomyces graminis var. tritici is a soil borne pathogenic fungus associated with wheat roots. The accurate quantification of gene expression during the process of infection might be helpful to understand the pathogenic molecular mechanism. However, this method requires suitable reference genes for transcript normalization. In this study, nine candidate reference genes were chosen, and the specificity of the primers were investigated by melting curves of PCR products. The expression stability of these nine candidates was determined with three programs-geNorm, Norm Finder, and Best Keeper. TUBβ was identified as the most stable reference gene. Furthermore, the exopolygalacturonase gene (ExoPG) was selected to verify the reliability of TUBβ expression. The expression profile of ExoPG assessed using TUBβ agreed with the results of digital gene expression analysis by RNA-Seq. This study is the first systematic exploration of the optimal reference genes in the infection process of Gaeumannomyces graminis var. tritici.

Targeted expression profiling by RNA-Seq improves detection of cellular dynamics during pregnancy and identifies a role for T cells in term parturition

Development of maternal blood transcriptomic markers to monitor placental function and risk of obstetrical complications throughout pregnancy requires accurate quantification of gene expression. Herein, we benchmark three state-of-the-art expression profiling techniques to assess in maternal circulation the expression of cell type-specific gene sets previously discovered by single-cell genomics studies of the placenta. We compared Affymetrix Human Transcriptome Arrays, Illumina RNA-Seq, and sequencing-based targeted expression profiling (DriverMapTM) to assess transcriptomic changes with gestational age and labor status at term, and tested 86 candidate genes by qRT-PCR. DriverMap identified twice as many significant genes (q < 0.1) than RNA-Seq and five times more than microarrays. The gap in the number of significant genes remained when testing only protein-coding genes detected by all platforms. qRT-PCR validation statistics (PPV and AUC) were high and similar among platforms, yet dynamic ranges were higher for sequencing based platforms than microarrays. DriverMap provided the strongest evidence for the association of B-cell and T-cell gene signatures with gestational age, while the T-cell expression was increased with spontaneous labor at term according to all three platforms. We concluded that sequencing-based techniques are more suitable to quantify whole-blood gene expression compared to microarrays, as they have an expanded dynamic range and identify more true positives. Targeted expression profiling achieved higher coverage of protein-coding genes with fewer total sequenced reads, and it is especially suited to track cell type-specific signatures discovered in the placenta. The T-cell gene expression signature was increased in women who underwent spontaneous labor at term, mimicking immunological processes at the maternal-fetal interface and placenta.

Reference genes for accurate normalization of gene expression in wood-decomposing fungi

Wood-decomposing fungi efficiently decompose plant lignocellulose, and there is increasing interest in characterizing and perhaps harnessing the fungal gene regulation strategies that enable wood decomposition. Proper interpretation of these fungal mechanisms relies on accurate quantification of gene expression, demanding reliable internal control genes (ICGs) as references. Commonly used ICGs such as actin, however, fluctuate among wood-decomposing fungi under defined conditions. In this study, by mining RNA-seq data in silico and validating ICGs in vitro using qRT-PCR, we targeted more reliable ICGs for studying transcriptional responses in wood-decomposing fungi, particularly responses to changing environments (e.g., carbon sources, decomposition stages) in various culture conditions. Using the model brown rot fungus Postia placenta in a first-pass study, our mining efforts yielded 15 constitutively-expressed genes robust in variable carbon sources (e.g., no carbon, glucose, cellobiose, aspen) and cultivation stages (e.g., 15 h, 72 h) in submerged cultures. Of these, we found 7 genes as most suitable ICGs. Expression stabilities of these newly selected ICGs were better than commonly used ICGs, analyzed by NormFinder algorithm and qRT-PCR. In a second-pass, multi-species study in solid wood, our RNA-seq mining efforts revealed hundreds of highly constitutively expressed genes among four wood-decomposing fungi with varying nutritional modes (brown rot, white rot), including a shared core set of ICGs numbering 11 genes. Together, the newly selected ICGs highlighted here will increase reliability when studying gene regulatory mechanisms of wood-decomposing fungi.

AltHapAlignR: improved accuracy of RNA-seq analyses through the use of alternative haplotypes.

MotivationReliance on mapping to a single reference haplotype currently limits accurate estimation of allele or haplotype-specific expression using RNA-sequencing, notably in highly polymorphic regions such as the major histocompatibility complex.ResultsWe present AltHapAlignR, a method incorporating alternate reference haplotypes to generate gene- and haplotype-level estimates of transcript abundance for any genomic region where such information is available. We validate using simulated and experimental data to quantify input allelic ratios for major histocompatibility complex haplotypes, demonstrating significantly improved correlation with ground truth estimates of gene counts compared to standard single reference mapping. We apply AltHapAlignR to RNA-seq data from 462 individuals, showing how significant underestimation of expression of the majority of classical human leukocyte antigen genes using conventional mapping can be corrected using AltHapAlignR to allow more accurate quantification of gene expression for individual alleles and haplotypes.Availability and implementationSource code freely available at https://github.com/jknightlab/AltHapAlignR.Supplementary information Supplementary data are available at Bioinformatics online.

Identifying suitable reference genes for developing and injured mouse CNS tissues.

Accurate quantification of gene expression is fundamental for understanding the molecular, genetic and functional bases of tissue development and diseases. Quantitative real-time PCR (qPCR) is now the most widely used method of quantifying gene expression due to its simplicity, specificity, sensitivity, and wide quantification range. The use of appropriate reference genes to ensure accurate normalization is crucial for the correct quantification of gene expression from the early development, maturation, aging to injury processes in the central nervous system (CNS). In this study, we have determined the expression profiles of 12 candidate housekeeping genes (ACTB, CYC1, HMBS, GAPDH, HPRT1, RPL13A, YWHAZ, PPIA, RPLP0, TFRC, GUS, and 18S rRNA) in developing mouse brain and spinal cord. Throughout development, there was a significant degree of fluctuations in their expression levels, indicating the importance and complexity of finding appropriate reference genes. Three software including BestKeeper, geNorm and NormFinder were used to evaluate the stability of potential reference genes. GUS was the most stable gene and GUS/YWHAZ were the most stable reference gene pair across different developmental stages in different CNS regions, whereas HPRT1 and GAPDH were the most variable genes and thus inappropriate to use as reference genes. Therefore, our results identified GUS and YWHAZ as the best combination of two reference genes for expression data normalization in CNS developmental studies. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 39-50, 2018.