Do housekeeping genes exist?

Protocol Development for CRISPR/Cas9 Knockout of the Anti-inflammatory Protein TNIP1 in HaCaT Keratinocytes

Gene editing in cultured cells, including the intent of sequence disruption to achieve a functional knockout of the targeted gene, has been greatly facilitated with the advent of Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/CRISPR-associated protein 9 (CRISPR/Cas9) technology. Primary cell strains and immortalized cell lines from diverse tissue types have been successfully targeted both for basic research examining the effects of loss of the correlating protein and for modeling select loss-of-function disorders. Such accomplishments have extended to cutaneous cells, especially epidermal keratinocytes given their key structural and functional role in barrier formation and surveillance of and response to surface events such as triggering and processing inflammatory responses. Here we describe disruption of the Tumor Necrosis factor-induced protein 3-Interacting Protein 1 (TNIP1) gene in human HaCaT keratinocytes to generate an ongoing loss of expression as a parallel system to transient knockdown we had previously achieved with siRNA transfection. The TNIP1 protein restricts cytoplasmic progression of inflammatory signals. We cover our CRISPR/Cas9 vector choice, enrichment of transfected cells via positive selection for puromycin resistance, their subsequent cloning, and gene disruption and expression analysis. We also emphasize prior keratinocyte-CRISPR/Cas9 literature as a springboard for other investigators and to illustrate the widespread relevance of such editing to the diverse, yet highly consequentially different, genes expressed in keratinocytes.

Housekeeping protein-coding genes interrogated with tissue and individual variations

Housekeeping protein-coding genes are stably expressed genes in cells and tissues that are thought to be engaged in fundamental cellular biological functions. They are often utilized as normalization references in molecular biology research and are especially important in integrated bioinformatic investigations. Prior studies have examined human housekeeping protein-coding genes by analyzing various gene expression datasets. The inclusion of different tissue types significantly impacted the discovery of housekeeping genes. In this report, we investigated particularly individual human subject expression differences in protein-coding genes across different tissue types. We used GTEx V8 gene expression datasets obtained from more than 16,000 human normal tissue samples. Furthermore, the Gini index is utilized to investigate the expression variations of protein-coding genes between tissue and individual donor subjects. Housekeeping protein-coding genes found using Gini index profiles may vary depending on the tissue subtypes investigated, particularly given the diverse sample size collections across the GTEx tissue subtypes. We subsequently selected major tissues and identified subsets of housekeeping genes with stable expression levels among human donors within those tissues. In this work, we provide alternative sets of housekeeping protein-coding genes that show more consistent expression patterns in human subjects across major solid organs. Weblink: https://hpsv.ibms.sinica.edu.tw .

InterOpt: Improved gene expression quantification in qPCR experiments using weighted aggregation of reference genes

qPCR is still the gold standard for gene expression quantification. However, its accuracy is highly dependent on the normalization procedure. The conventional method involves using the geometric mean of multiple study-specific reference genes (RGs) expression for cross-sample normalization. While research on selecting stably expressed RGs is extensive, scant literature exists regarding the optimal approach for aggregating multiple RGs into a unified RG. In this paper, we introduce a family of scale-invariant functions as an alternative to the geometric mean aggregation. Our candidate method (weighted geometric mean minimizing standard deviation) demonstrated significantly better results compared to other proposed methods. We provide theoretical and experimental support for this finding using real data from solid tumors and liquid biopsies. Moreover, the closed form and regression-based solution enable efficient computation and straightforward adoption on various platforms. All the proposed methods have been implemented within an easy-to-use R package with graphics processing unit (GPU) acceleration.

The role of intracellular calcium-store-mediated calcium signals in in vivo sensor and effector functions of microglia

Under physiological conditions microglia, the immune sentinels of the brain, constantly monitor their microenvironment. In the case of danger, damage or cell/tissue dyshomeostasis, they react with changes in process motility, polarization, directed process movement, morphology and gene expression profile; release pro- and anti-inflammatory mediators; proliferate; and clean brain parenchyma by means of phagocytosis. Based on recent transcriptomic and in vivo Ca2+ imaging data, we argue that the local cell/tissue dyshomeostasis is sensed by microglia via intracellular Ca2+ signals, many of which are mediated by Ca2+ release from the intracellular Ca2+ stores. These signals encode the strength, duration and spatiotemporal pattern of the stimulus and, at the same time, relay this information further to trigger the respective Ca2+ -dependent effector pathways. We also point to the fact that microglial Ca2+ signalling is sexually dimorphic and undergoes profound changes across the organism's lifespan. Interestingly, the first changes in microglial Ca2+ signalling are visible already in 9- to 11-month-old mice, roughly corresponding to 40-year-old humans.

YWHAZ and TBP are potential reference gene candidates for qPCR analysis of response to radiation therapy in colorectal cancer

The expression profiles of conventional reference genes (RGs), including ACTB and GAPDH, used in quantitative real-time PCR (qPCR), vary depending on tissue types and environmental conditions. We searched for suitable RGs for qPCR to determine the response to radiotherapy in colorectal cancer (CRC) cell lines, organoids, and patient-derived tissues. Ten CRC cell lines (Caco-2, COLO 205, DLD-1, HCT116, HCT-15, HT-29, RKO, SW1116, SW480, and SW620) and organoids were selected and irradiated with 2, 10 or 21 grays (Gy) based on the previous related studies conducted over the last decade. The expression stability of 14 housekeeping genes (HKGs; ACTB, B2M, G6PD, GAPDH, GUSB, HMBS, HPRT1, IPO8, PGK1, PPIA, TBP, TFRC, UBC, and YWHAZ) after irradiation was evaluated using RefFinder using raw quantification cycle (Cq) values obtained from samples before and after irradiation. The expression stability of HKGs were also evaluated for paired fresh frozen tissues or formalin-fixed, paraffin-embedded samples obtained from CRC patients before and after chemoradiotherapy. The expression of YWHAZ and TBP encoding 14-3-3-zeta protein and TATA-binding protein were more stable than the other 12 HKGs in CRC cell lines, organoids, and patient-derived tissues after irradiation. The findings suggest that YWHAZ and TBP are potential RG candidates for normalizing qPCR results in CRC radiotherapy experiments.

Gene regulatory network inference using mixed-norms regularized multivariate model with covariance selection

Despite extensive research efforts, reconstruction of gene regulatory networks (GRNs) from transcriptomics data remains a pressing challenge in systems biology. While non-linear approaches for reconstruction of GRNs show improved performance over simpler alternatives, we do not yet have understanding if joint modelling of multiple target genes may improve performance, even under linearity assumptions. To address this problem, we propose two novel approaches that cast the GRN reconstruction problem as a blend between regularized multivariate regression and graphical models that combine the L2,1-norm with classical regularization techniques. We used data and networks from the DREAM5 challenge to show that the proposed models provide consistently good performance in comparison to contenders whose performance varies with data sets from simulation and experiments from model unicellular organisms Escherichia coli and Saccharomyces cerevisiae. Since the models' formulation facilitates the prediction of master regulators, we also used the resulting findings to identify master regulators over all data sets as well as their plasticity across different environments. Our results demonstrate that the identified master regulators are in line with experimental evidence from the model bacterium E. coli. Together, our study demonstrates that simultaneous modelling of several target genes results in improved inference of GRNs and can be used as an alternative in different applications.

Deciphering the sex bias in housekeeping gene expression in adipose tissue: a comprehensive meta-analysis of transcriptomic studies

BACKGROUND

As the housekeeping genes (HKG) generally involved in maintaining essential cell functions are typically assumed to exhibit constant expression levels across cell types, they are commonly employed as internal controls in gene expression studies. Nevertheless, HKG may vary gene expression profile according to different variables introducing systematic errors into experimental results. Sex bias can indeed affect expression display, however, up to date, sex has not been typically considered as a biological variable.

METHODS

In this study, we evaluate the expression profiles of six classical housekeeping genes (four metabolic: GAPDH, HPRT, PPIA, and UBC, and two ribosomal: 18S and RPL19) to determine expression stability in adipose tissues (AT) of Homo sapiens and Mus musculus and check sex bias and their overall suitability as internal controls. We also assess the expression stability of all genes included in distinct whole-transcriptome microarrays available from the Gene Expression Omnibus database to identify sex-unbiased housekeeping genes (suHKG) suitable for use as internal controls. We perform a novel computational strategy based on meta-analysis techniques to identify any sexual dimorphisms in mRNA expression stability in AT and to properly validate potential candidates.

RESULTS

Just above half of the considered studies informed properly about the sex of the human samples, however, not enough female mouse samples were found to be included in this analysis. We found differences in the HKG expression stability in humans between female and male samples, with females presenting greater instability. We propose a suHKG signature including experimentally validated classical HKG like PPIA and RPL19 and novel potential markers for human AT and discarding others like the extensively used 18S gene due to a sex-based variability display in adipose tissue. Orthologs have also been assayed and proposed for mouse WAT suHKG signature. All results generated during this study are readily available by accessing an open web resource ( https://bioinfo.cipf.es/metafun-HKG ) for consultation and reuse in further studies.

CONCLUSIONS

This sex-based research proves that certain classical housekeeping genes fail to function adequately as controls when analyzing human adipose tissue considering sex as a variable. We confirm RPL19 and PPIA suitability as sex-unbiased human and mouse housekeeping genes derived from sex-specific expression profiles, and propose new ones such as RPS8 and UBB.

Identification and validation of stable reference genes for quantitative real time PCR in different minipig tissues at developmental stages

Background

Quantitative real time PCR (qPCR) is a powerful tool to evaluate mRNA expression level. However, reliable qPCR results require normalization with validated reference gene(s). In this study, we investigated stable reference genes in seven tissues according to four developmental stages in minipigs. Six candidate reference genes and one target gene (ACE2) were selected and qPCR was performed. BestKeeper, geNorm, NormFinder, and delta Ct method through the RefFinder web-based tool were used to evaluate the stability of candidate reference genes. To verify the selected stable genes, relative expression of ACE2 was calculated and compared with each other.

Results

As a result, HPRT1 and 18S genes had lower SD value, while HMBS and GAPDH genes had higher SD value in all samples. Using statistical algorithms, HPRT1 was the most stable gene, followed by 18S, β-actin, B2M, GAPDH, and HMBS. In intestine, all candidate reference genes exhibited similar patterns of ACE2 gene expression over time, whereas in liver, lung, and kidney, gene expression pattern normalized with stable reference genes differed from those normalized with less stable genes. When normalized with the most stable genes, the expression levels of ACE2 in minipigs highly increased in intestine and kidney at PND28, which is consistent with the ACE2 expression pattern in humans.

Conclusions

We suggest that HPRT1 and 18S are good choices for analyzing all these samples across the seven tissues and four developmental stages. However, this study can be a reference literature for gene expression experiments using minipig because reference gene should be validated and chosen according to experimental conditions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08830-z.

Crosstalk of hepatocyte nuclear factor 4a and glucocorticoid receptor in the regulation of lipid metabolism in mice fed a high-fat-high-sugar diet

BACKGROUND

Hepatocyte nuclear factor 4α (HNF4α) and glucocorticoid receptor (GR), master regulators of liver metabolism, are down-regulated in fatty liver diseases. The present study aimed to elucidate the role of down-regulation of HNF4α and GR in fatty liver and hyperlipidemia.

METHODS

Adult mice with liver-specific heterozygote (HET) and knockout (KO) of HNF4α or GR were fed a high-fat-high-sugar diet (HFHS) for 15 days. Alterations in hepatic and circulating lipids were determined with analytical kits, and changes in hepatic mRNA and protein expression in these mice were quantified by real-time PCR and Western blotting. Serum and hepatic levels of bile acids were quantified by LC-MS/MS. The roles of HNF4α and GR in regulating hepatic gene expression were determined using luciferase reporter assays.

RESULTS

Compared to HFHS-fed wildtype mice, HNF4α HET mice had down-regulation of lipid catabolic genes, induction of lipogenic genes, and increased hepatic and blood levels of lipids, whereas HNF4α KO mice had fatty liver but mild hypolipidemia, down-regulation of lipid-efflux genes, and induction of genes for uptake, synthesis, and storage of lipids. Serum levels of chenodeoxycholic acid and deoxycholic acid tended to be decreased in the HNF4α HET mice but dramatically increased in the HNF4α KO mice, which was associated with marked down-regulation of cytochrome P450 7a1, the rate-limiting enzyme for bile acid synthesis. Hepatic mRNA and protein expression of sterol-regulatory-element-binding protein-1 (SREBP-1), a master lipogenic regulator, was induced in HFHS-fed HNF4α HET mice. In reporter assays, HNF4α cooperated with the corepressor small heterodimer partner to potently inhibit the transactivation of mouse and human SREBP-1C promoter by liver X receptor. Hepatic nuclear GR proteins tended to be decreased in the HNF4α KO mice. HFHS-fed mice with liver-specific KO of GR had increased hepatic lipids and induction of SREBP-1C and PPARγ, which was associated with a marked decrease in hepatic levels of HNF4α proteins in these mice. In reporter assays, GR and HNF4α synergistically/additively induced lipid catabolic genes.

CONCLUSIONS

induction of lipid catabolic genes and suppression of lipogenic genes by HNF4α and GR may mediate the early resistance to HFHS-induced fatty liver and hyperlipidemia.

Comprehensive analysis of ubiquitously expressed genes in human, from a data-driven perspective

Comprehensive characterization of spatial and temporal gene expression patterns in humans is critical for uncovering the regulatory codes of the human genome and understanding the molecular mechanism of human disease. The ubiquitously expressed genes (UEGs) refer to those genes expressed across a majority, if not all, phenotypic and physiological conditions of an organism. It is known that many human genes are broadly expressed across tissues. However, most previous UEG studies have only focused on providing a list of UEGs without capturing their global expression patterns, thus limiting the potential use of UEG information. In this article, we proposed a novel data-driven framework to leverage the extensive collection of ∼40,000 human transcriptomes to derive a list of UEGs and their corresponding global expression patterns, which offers a valuable resource to further characterize human transcriptome. Our results suggest that about half (12,234; 49.01%) of the human genes are expressed in at least 80% of human transcriptomes, and the median size of the human transcriptome is 16,342 (65.44%). Through gene clustering, we identified a set of UEGs, named LoVarUEGs, that have stable expression across human transcriptomes and can be used as internal reference genes for expression measurement. To further demonstrate the usefulness of this resource, we evaluated the global expression patterns for 16 previously predicted disallowed genes in islets beta cells and found that seven of these genes showed relatively more varied expression patterns, suggesting that the repression of these genes may not be unique to islets beta cells.

Conservation and architecture of housekeeping genes in the model marine diatom Thalassiosira pseudonana

Housekeeping genes (HKGs) are constitutively expressed with low variation across tissues/conditions. They are thought to be highly conserved and fundamental to cellular maintenance, with distinctive genomic features. Here, we identify 1505 HKGs in the unicellular marine diatom Thalassiosira pseudonana based on an RNA-seq analysis of 232 samples taken under 12 experimental conditions over 0-72 h. We identify promising internal reference genes (IRGs) for T. pseudonana from the most stably expressed HKGs. A comparative analysis indicates < 18% of HKGs in T. pseudonana have orthologs in other eukaryotes, including other diatom species. Contrary to work on human tissues, T. pseudonana HKGs are longer than non-HKGs, due to elongated introns. More ancient HKGs tend to be shorter than more recent HKGs, and expression levels of HKGs decrease more rapidly with gene length relative to non-HKGs. Our results indicate that HKGs are highly variable across the tree of life and thus unlikely to be universally fundamental for cellular maintenance. We hypothesize that the distinct genomic features of HKGs of T. pseudonana may be a consequence of selection pressures associated with high expression and low variance across conditions.

Mouse Organ-Specific Proteins and Functions

Organ-specific proteins (OSPs) possess great medical potential both in clinics and in biomedical research. Applications of them—such as alanine transaminase, aspartate transaminase, and troponins—in clinics have raised certain concerns of their organ specificity. The dynamics and diversity of protein expression in heterogeneous human populations are well known, yet their effects on OSPs are less addressed. Here, we used mice as a model and implemented a breadth study to examine the panorgan proteome for potential variations in organ specificity in different genetic backgrounds. Using reasonable resources, we generated panorgan proteomes of four in-bred mouse strains. The results revealed a large diversity that was more profound among OSPs than among proteomes overall. We defined a robustness score to quantify such variation and derived three sets of OSPs with different stringencies. In the meantime, we found that the enriched biological functions of OSPs are also organ-specific and are sensitive and useful to assess the quality of OSPs. We hope our breadth study can open doors to explore the molecular diversity and dynamics of organ specificity at the protein level.

miR-361-5p as a promising qRT-PCR internal control for tumor and normal breast tissues

BACKGROUND

One of the most widely used evaluation methods in miRNA experiments is qRT-PCR. However, selecting suitable internal controls (IC) is crucial for qRT-PCR experiments. Currently, there is no consensus on the ICs for miRNA qRT-PCR experiments in breast cancer. To this end, we tried to identify the most stable (the least expression alteration) and promising miRNAs in normal and tumor breast tissues by employing TCGA miRNA-Seq data and then experimentally validated them on fresh clinical samples.

METHODS

A multi-component scoring system was used which takes into account multiple expression stability criteria as well as correlation with clinical characteristics. Furthermore, we extended the scoring system for more than two biological sub-groups. TCGA BRCA samples were analyzed based on two grouping criteria: Tumor & Normal samples and Tumor subtypes. The top 10 most stable miRNAs were further investigated by differential expression and survival analysis. Then, we examined the expression level of the top scored miRNA (hsa-miR-361-5p) along with two commonly used ICs hsa-miR-16-5p and U48 on 34 pairs of Primary breast tumor and their adjacent normal tissues using qRT-PCR.

RESULTS

According to our multi-component scoring system, hsa-miR-361-5p had the highest stability score in both grouping criteria and hsa-miR-16-5p showed significantly lower scores. Based on our qRT-PCR assay, while U48 was the most abundant IC, hsa-miR-361-5p had lower standard deviation and also was the only IC capable of detecting a significant up-regulation of hsa-miR-21-5p in breast tumor tissue.

CONCLUSIONS

miRNA-Seq data is a great source to discover stable ICs. Our results demonstrated that hsa-miR-361-5p is a highly stable miRNA in tumor and non-tumor breast tissue and we recommend it as a suitable reference gene for miRNA expression studies in breast cancer. Additionally, although hsa-miR-16-5p is a commonly used IC, it's not a suitable one for breast cancer studies.

HRT Atlas v1.0 database: redefining human and mouse housekeeping genes and candidate reference transcripts by mining massive RNA-seq datasets

Housekeeping (HK) genes are constitutively expressed genes that are required for the maintenance of basic cellular functions. Despite their importance in the calibration of gene expression, as well as the understanding of many genomic and evolutionary features, important discrepancies have been observed in studies that previously identified these genes. Here, we present Housekeeping and Reference Transcript Atlas (HRT Atlas v1.0, www.housekeeping.unicamp.br) a web-based database which addresses some of the previously observed limitations in the identification of these genes, and offers a more accurate database of human and mouse HK genes and transcripts. The database was generated by mining massive human and mouse RNA-seq data sets, including 11 281 and 507 high-quality RNA-seq samples from 52 human non-disease tissues/cells and 14 healthy tissues/cells of C57BL/6 wild type mouse, respectively. User can visualize the expression and download lists of 2158 human HK transcripts from 2176 HK genes and 3024 mouse HK transcripts from 3277 mouse HK genes. HRT Atlas also offers the most stable and suitable tissue selective candidate reference transcripts for normalization of qPCR experiments. Specific primers and predicted modifiers of gene expression for some of these HK transcripts are also proposed. HRT Atlas has also been integrated with a regulatory elements resource from Epiregio server.

Selection of reference genes for quantitative PCR: identifying reference genes for airway epithelial cells exposed to Pseudomonas aeruginosa

Most quantitative PCR (qPCR) experiments report differential expression relative to the expression of one or more reference genes. Therefore, when experimental conditions alter reference gene expression, qPCR results may be compromised. Little is known about the magnitude of this problem in practice. We found that reference gene responses are common and hard to predict and that their stability should be demonstrated in each experiment. Our reanalysis of 15 airway epithelia microarray data sets retrieved from the National Center for Biotechnology Information (NCBI) identified no common reference gene that was reliable in all 15 studies. Reanalysis of published RNA sequencing (RNA-seq) data in which human bronchial epithelial cells (HBEC) were exposed to Pseudomonas aeruginosa revealed that minor experimental details, including bacterial strain, may alter reference gene responses. Direct measurement of 32 TaqMan reference genes in primary cultures of HBEC exposed to P. aeruginosa (strain PA14) demonstrated that choosing an unstable reference gene could make it impossible to observe statistically significant changes in IL8 gene expression. We found that reference gene instability is a general phenomenon and not limited to studies of airway epithelial cells. In a diverse compendium of 986 human microarray experiments retrieved from the NCBI, reference genes were differentially expressed in 42% of studies. Experimentally induced changes in reference gene expression ranged from 21% to 212%. These results highlight the importance of identifying adequate reference genes for each experimental system and documenting their response to treatment in each experiment. This will enhance experimental rigor and reproducibility in qPCR studies.

Novel reference genes in colorectal cancer identify a distinct subset of high stage tumors and their associated histologically normal colonic tissues

Background

Reference genes are often interchangeably called housekeeping genes due to 1) the essential cellular functions their proteins provide and 2) their constitutive expression across a range of normal and pathophysiological conditions. However, given the proliferative drive of malignant cells, many reference genes such as beta-actin (ACTB) and glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) which play critical roles in cell membrane organization and glycolysis, may be dysregulated in tumors versus their corresponding normal controls

Methods

Because Next Generation Sequencing (NGS) technology has several advantages over hybridization-based technologies, such as independent detection and quantitation of transcription levels, greater sensitivity, and increased dynamic range, we evaluated colorectal cancers (CRC) and their histologically normal tissue counterparts by NGS to evaluate the expression of 21 “classical” reference genes used as normalization standards for PCR based methods. Seventy-nine paired tissue samples of CRC and their patient matched healthy colonic tissues were subjected to NGS analysis of their mRNAs.

Results

We affirmed that 17 out of 21 classical reference genes had upregulated expression in tumors compared to normal colonic epithelial tissue and dramatically so in some cases. Indeed, tumors were distinguished from normal controls in both unsupervised hierarchical clustering analyses (HCA) and principal component analyses (PCA). We then identified 42 novel potential reference genes with minimal coefficients of variation (CV) across 79 CRC tumor pairs. Though largely consistently expressed across tumors and normal control tissues, a subset of high stage tumors (HSTs) as well as some normal tissue samples (HSNs) located adjacent to these HSTs demonstrated dysregulated expression, thus identifying a subset of tumors with a potentially distinct and aggressive biological profile.

Conclusion

While classical CRC reference genes were found to be differentially expressed between tumors and normal controls, novel reference genes, identified via NGS, were more consistently expressed across malignant and normal colonic tissues. Nonetheless, a subset of HST had profound dysregulation of such genes as did many of the histologically normal tissues adjacent to such HSTs, indicating that the HSTs so distinguished may have unique biological properties and that their histologically normal tissues likely harbor a small population of microscopically undetected but metabolically active tumors.

Electronic supplementary material

The online version of this article (10.1186/s12881-019-0867-y) contains supplementary material, which is available to authorized users.

AKIRIN1: A Potential New Reference Gene in Human Natural Killer Cells and Granulocytes in Sepsis

Timely and reliable distinction of sepsis from non-infectious systemic inflammatory response syndrome (SIRS) supports adequate antimicrobial therapy and saves lives but is clinically challenging. Blood transcriptional profiling promises to deliver insights into the pathomechanisms of SIRS and sepsis and to accelerate the discovery of urgently sought sepsis biomarkers. However, suitable reference genes for normalizing gene expression in these disease conditions are lacking. In addition, variability in blood leukocyte subtype composition complicates gene profile interpretation. Here, we aimed to identify potential reference genes in natural killer (NK) cells and granulocytes from patients with SIRS and sepsis on intensive care unit (ICU) admission. Discovery by a two-step probabilistic selection from microarray data followed by validation through branched DNA assays in independent patients revealed several candidate reference genes in NK cells including AKIRIN1, PPP6R3, TAX1BP1, and ADRBK1. Initially, no candidate genes could be validated in patient granulocytes. However, we determined highly similar AKIRIN1 expression also in SIRS and sepsis granulocytes and no change by in vitro LPS challenge in granulocytes from healthy donors. Inspection of external neutrophil transcriptome datasets further support unchanged AKIRIN1 expression in human systemic inflammation. As a potential new reference gene in NK cells and granulocytes in infectious and inflammatory diseases, AKIRIN1 may improve our pathomechanistic understanding of SIRS and sepsis and help identifying new sepsis biomarkers.

Effects of tendon injury on uninjured regional tendons in the distal limb: An in-vivo study using an ovine tendinopathy model

Following injury to a tendon little is known about potential for pathology to develop in other regional tendons from overloading or altered function. The aim of this study was to investigate the gene expression and histopathological changes that occur 1) within the deep digital flexor tendon (DDFT) after injury to the superficial digital flexor tendon (SDFT) and 2) within the flexor tendons (SDFT and DDFT) after injury to the extensor tendons. Merino wethers [Ovis aries] (n = 18) were divided into three equal groups and underwent either partial transection of the SDFT, complete transection of the extensor tendons or were left as non-operated controls. Tendons were harvested and sampled regionally for gene expression (real time PCR) and histologic analysis eight weeks after surgery. Transection of the SDFT resulted in increased expression of collagen III, versican, biglycan, lumican and MMP1 (P<0.026 for all genes) within the DDFT. There was no effect of transecting the extensor tendons on the expression of any gene tested in either the SDFT or the DDFT. The DDFT had elevated histopathology scores induced by transection of the SDFT, eight weeks previously. There were minimal histological differences in either the SDFT or DDFT after transection of the extensor tendons. Transection of the SDFT results in a mild, subclinical tendinopathy within the DDFT with potential implications on treatment and rehabilitation of SDFT injuries. Injury to the extensor tendons has minimal measured effect on the SDFT or DDFT.

Identification of stable senescence-associated reference genes

Cellular senescence is a state of permanent cell cycle arrest activated in response to damaging stimuli. Many hallmarks associated with senescent cells are measured by quantitative real-time PCR (qPCR). As the selection of stable reference genes for interpretation of qPCR data is often overlooked, we performed a systematic review to understand normalization strategies entailed in experiments involving senescent cells. We found that, in violation of the Minimum Information for publication of qPCR Experiments (MIQE) guidelines, most reports used only one reference gene to normalize qPCR data, and that stability of the reference genes was either not tested or not reported. To identify new and more stable reference genes in senescent fibroblasts, we analyzed the Shapiro-Wilk normality test and the coefficient of variation per gene using in public RNAseq datasets. We then compared the new reference gene candidates with commonly used ones by using both RNAseq and qPCR data. Finally, we defined the best reference genes to be used universally or in a strain-dependent manner. This study intends to raise awareness of the instability of classical reference genes in senescent cells and to serve as a first attempt to define guidelines for the selection of more reliable normalization methods.

Data Analysis in Single-Cell Transcriptome Sequencing

Single-cell transcriptome sequencing, often referred to as single-cell RNA sequencing (scRNA-seq), is used to measure gene expression at the single-cell level and provides a higher resolution of cellular differences than bulk RNA-seq. With more detailed and accurate information, scRNA-seq will greatly promote the understanding of cell functions, disease progression, and treatment response. Although the scRNA-seq experimental protocols have been improved very quickly, many challenges in the scRNA-seq data analysis still need to be overcome. In this chapter, we focus on the introduction and discussion of the research status in the field of scRNA-seq data normalization and cluster analysis, which are the two most important challenges in the scRNA-seq data analysis. Particularly, we present a protocol to discover and validate cancer stem cells (CSCs) using scRNA-seq. Suggestions have also been made to help researchers rationally design their scRNA-seq experiments and data analysis in their future studies.

Systematic identification of human housekeeping genes possibly useful as references in gene expression studies

The ideal reference, or control, gene for the study of gene expression in a given organism should be expressed at a medium-high level for easy detection, should be expressed at a constant/stable level throughout different cell types and within the same cell type undergoing different treatments, and should maintain these features through as many different tissues of the organism. From a biological point of view, these theoretical requirements of an ideal reference gene appear to be best suited to housekeeping (HK) genes. Recent advancements in the quality and completeness of human expression microarray data and in their statistical analysis may provide new clues toward the quantitative standardization of human gene expression studies in biology and medicine, both cross- and within-tissue. The systematic approach used by the present study is based on the Transcriptome Mapper tool and exploits the automated reassignment of probes to corresponding genes, intra- and inter-sample normalization, elaboration and representation of gene expression values in linear form within an indexed and searchable database with a graphical interface recording quantitative levels of expression, expression variability and cross-tissue width of expression for more than 31,000 transcripts. The present study conducted a meta-analysis of a pool of 646 expression profile data sets from 54 different human tissues and identified actin γ 1 as the HK gene that best fits the combination of all the traditional criteria to be used as a reference gene for general use; two ribosomal protein genes, RPS18 and RPS27, and one aquaporin gene, POM121 transmembrane nucleporin C, were also identified. The present study provided a list of tissue- and organ-specific genes that may be most suited for the following individual tissues/organs: Adipose tissue, bone marrow, brain, heart, kidney, liver, lung, ovary, skeletal muscle and testis; and also provides in these cases a representative, quantitative portrait of the relative, typical gene-expression profile in the form of searchable database tables.

Identification of reliable reference genes for qRT-PCR studies of the developing mouse mammary gland

Cell growth and differentiation are often driven by subtle changes in gene expression. Many challenges still exist in detecting these changes, particularly in the context of a complex, developing tissue. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) allows relatively high-throughput evaluation of multiple genes and developmental time points. Proper quantification of gene expression levels by qRT-PCR requires normalization to one or more reference genes. Traditionally, these genes have been selected based on their presumed “housekeeping” function, with the implicit assumption that they are stably expressed over the entire experimental set. However, this is rarely tested empirically. Here we describe the identification of novel reference genes for the mouse mammary gland based on their stable expression in published microarray datasets. We compared eight novel candidate reference genes (Arpc3, Clock, Ctbp1, Phf7, Prdx1, Sugp2, Taf11 and Usp7) to eight traditional ones (18S, Actb, Gapdh, Hmbs, Hprt, Rpl13a, Sdha and Tbp) and analysed all genes for stable expression in the mouse mammary gland from pre-puberty to adulthood using four different algorithms (GeNorm, DeltaCt, BestKeeper and NormFinder). Prdx1, Phf7 and Ctbp1 were validated as novel and reliable, tissue-specific reference genes that outperform traditional reference genes in qRT-PCR studies of postnatal mammary gland development.

Selective forces and mutational biases drive stop codon usage in the human genome: a comparison with sense codon usage

BACKGROUND

The three stop codons UAA, UAG, and UGA signal the termination of mRNA translation. As a result of a mechanism that is not adequately understood, they are normally used with unequal frequencies.

RESULTS

In this work, we showed that selective forces and mutational biases drive stop codon usage in the human genome. We found that, in respect to sense codons, stop codon usage was affected by stronger selective forces but was less influenced by neutral mutational biases. UGA is the most frequent termination codon in human genome. However, UAA was the preferred stop codon in genes with high breadth of expression, high level of expression, AT-rich coding sequences, housekeeping functions, and in gene ontology categories with the largest deviation from expected stop codon usage. Selective forces associated with the breadth and the level of expression favoured AT-rich sequences in the mRNA region including the stop site and its proximal 3'-UTR, but acted with scarce effects on sense codons, generating two regions, upstream and downstream of the stop codon, with strongly different base composition. By favouring low levels of GC-content, selection promoted labile local secondary structures at the stop site and its proximal 3'-UTR. The compositional and structural context favoured by selection was surprisingly emphasized in the class of ribosomal proteins and was consistent with sequence elements that increase the efficiency of translational termination. Stop codons were also heterogeneously distributed among chromosomes by a mechanism that was strongly correlated with the GC-content of coding sequences.

CONCLUSIONS

In human genome, the nucleotide composition and the thermodynamic stability of stop codon site and its proximal 3'-UTR are correlated with the GC-content of coding sequences and with the breadth and the level of gene expression. In highly expressed genes stop codon usage is compositionally and structurally consistent with highly efficient translation termination signals.

The analyses of human inherited disease and tissue-specific proteins in the interaction network

OBJECTIVES

With the announcement of human proteome and interaction data, it becomes possible to comprehensively investigate the tissue-expression and network properties of inherited disease proteins. In this study, our goal was to develop methods to map the disease and expression data and analyze the disorder-tissue associations.

METHODS

In this paper, we manually classified the human disease proteins into 22 disorder classes and systematically analyzed the properties of disease proteins in different disorder classes. Then, we investigated the similarity of different disorder classes by computing the overlap of different disorder proteins and networks. We proposed two novel measures, Enrichment Ratio and P-value for comparative analysis of disease proteins across tissues and revealed the associations between disorder classes and tissues/cells.

RESULTS

Compared with non-disease proteins, disease proteins tend to express in more tissues, have higher expression levels and interact with more other proteins in the network. The overlap percentages of networks are much higher than those of proteins, implying that different disorder classes usually influence each other by means of their interacting neighbors. The metabolic, muscular and hematologic proteins are related with most tissues/cells, and cancer proteins are closely associated with the disorders in immune cells.

CONCLUSION

This paper provided novel methods to investigate proteome-wide disease proteins and their interacting networks in order to understand different disease's associations.

Detection bias in microarray and sequencing transcriptomic analysis identified by housekeeping genes

This work includes the original data used to discover the gene ontology bias in transcriptomic analysis conducted by microarray and high throughput sequencing (Zhang et al., 2015) [1]. In the analysis, housekeeping genes were used to examine the differential detection ability by microarray and sequencing because these genes are probably the most reliably detected. The genes included here were compiled from 15 human housekeeping gene studies. The provided tables here comprise of detailed chromosomal location, detection breadth, normalized expression level, exon count, total exon length, and total intron length of each concerned gene and their related transcripts. We hope this information can help researchers better understand the differences in gene ontology-bias we discussed (Zhang et al., 2015) [1] and can encourage further improvement on these two technology platforms.

Verification of suitable and reliable reference genes for quantitative real-time PCR during adipogenic differentiation in porcine intramuscular stromal-vascular cells

Intramuscular fat (IMF) is an important trait influencing meat quality, and intramuscular stromal-vascular cell (MSVC) differentiation is a key factor affecting IMF deposition. Quantitative real-time PCR (qPCR) is often used to screen the differentially expressed genes during differentiation of MSVCs, where proper reference genes are essential. In this study, we assessed 31 of previously reported reference genes for their expression suitability in porcine MSVCs derived form longissimus dorsi with qPCR. The expression stability of these genes was evaluated using NormFinder, geNorm and BestKeeper algorithms. NormFinder and geNorm uncovered ACTB, ALDOA and RPS18 as the most three stable genes. BestKeeper identified RPL13A, SSU72 and DAK as the most three stable genes. GAPDH was found to be the least stable gene by all of the three software packages, indicating it is not an appropriate reference gene in qPCR assay. These results might be helpful for further studies in pigs that explore the molecular mechanism underlying IMF deposition.