scholarly journals Systematic selection of reference genes for normalization of circulating RNA transcripts in pregnant women based on RNA-seq data

2017 ◽  
Author(s):  
Stephen S. C. Chim ◽  
Karen K. W. Wong ◽  
Claire Y. L. Chung ◽  
Stephanie K. W. Lam ◽  
Jamie S. L. Kwok ◽  
...  

AbstractRNA transcripts circulating in peripheral blood represent an important source of non-invasive biomarkers. To accurately quantify the levels of a circulating transcript, one needs to normalize the data with internal control reference genes, which are detected at relatively constant levels across different blood samples. A few stably-expressed reference gene candidates have to be selected from transcriptome data before validation of their stable expression by reverse-transcription quantitative polymerase chain reaction. However, there is a lack of transcriptome, let alone whole-transcriptome, data from maternal blood. To overcome this shortfall, we performed RNA-seq on blood samples from women presented with preterm labor. Of 11215 exons detected in the maternal blood whole-transcriptome, we systematically identified a panel of 395 genes comprising exons that were detected at acoefficient of variation(CV) ranging from 7.75%-17.7%. Their levels were considerably less variable than anyGAPDHexon (minimumCV, 27.3%). Upon validation, selected genes from this panel remained as more stably expressed thanGAPDHin maternal blood. This panel is over-represented with genes involved with actin cytoskeleton, macromolecular complex and the integrin signaling pathway. This groundwork provides a starting point for systematically selecting reference gene candidates for normalizing the levels of circulating RNA transcripts in maternal blood.


2017 ◽  
Vol 18 (8) ◽  
pp. 1709 ◽  
Author(s):  
Stephen Chim ◽  
Karen Wong ◽  
Claire Chung ◽  
Stephanie Lam ◽  
Jamie Kwok ◽  
...  


2021 ◽  
Author(s):  
Lichun Zhang ◽  
Xiaoqian Yang ◽  
Yiyi Yin ◽  
Jinxing Wang ◽  
Yanwei Wang

Abstract Quantitative real time polymerase chain reaction (qRT-PCR) is a common method to analyze gene expression. Due to differences in RNA quantity, quality, and reverse transcription efficiency between qRT-PCR samples, reference genes are used as internal standards to normalize gene expression. However, few universal genes especially miRNAs have been identified as reference so far. Therefore, it is essential to identify reference genes that can be used across various experimental conditions, stress treatments, or tissues. In this study, 14 microRNAs (miRNAs) and 5.8S rRNA were assessed for expression stability in poplar trees infected with canker pathogen. Using three reference gene analysis programs, we found that miR156g and miR156a exhibited stable expression throughout the infection process. miR156g and miR156a were then tested as internal standards to measure the expression of miR1447 and miR171c, and the results were compared to small RNA sequencing (RNA-seq) data. We found that when miR156a was used as the reference gene, the expression of miR1447 and miR171c were consistent with the small RNA-seq expression profiles. Therefore, miR156a was the most stable miRNAs examined in this study, and could be used as a reference gene in poplar under canker pathogen stress, which should enable comprehensive comparisons of miRNAs expression and avoid the bias caused by different lenth between detected miRNAs and traditional referece genes. The present study has expanded the miRNA reference genes available for gene expression studies in trees under biotic stress.



2019 ◽  
Author(s):  
Donald G. Gilbert

AbstractMethods of transcript assembly and reduction filters are compared for recovery of reference gene sets of human, pig and plant, including longest coding sequence with EvidentialGene, longest transcript with CD-HIT, and most RNA-seq with TransRate. EvidentialGene methods are the most accurate in recovering reference genes, and maintain accuracy for alternate transcripts and paralogs. In comparison, filtering large over-assemblies by longest RNA measures, and most RNA-seq expression measures, discards a large portion of accurate models, especially alternates and paralogs. Accuracy of protein calculations is compared, with errors found in popular methods, as is accuracy of transcript assemblers. Gene reconstruction accuracy depends upon the underlying measurements, where protein criteria, including homology among species, have the strength of evolutionary biology that other criteria lack. EvidentialGene provides a gene reconstruction algorithm that is consistent with genome biology.



Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 3768-3768 ◽  
Author(s):  
Grazia Fazio ◽  
Marco Severgnini ◽  
Ingrid Cifola ◽  
Silvia Bungaro ◽  
Andrea Biondi ◽  
...  

Abstract Introduction. Acute Lymphoblastic Leukemia (ALL) is the most frequent type of childhood leukemia. It is a multi-step process, characterized by the expansion of a pre-leukemic clone, accumulating cooperative genetic events required for the full transformation and clinical manifestation. Recently, the technological advances in genome-wide profiling techniques have allowed a better understanding of its molecular basis and heterogeneity. However, incidence and cure rates greatly differ among children, reflecting diverse responses to drug treatment and distinguishing risk groups. This defines the need for molecular investigations to better understand leukemia biology and improve risk prediction. Aim. We applied a whole-transcriptome sequencing approach (RNA-seq) to characterize low- (LR) versus high-risk (HR) patients, to identify new genetic lesions associated to different early response to therapy. Methods. Total RNA was extracted from primary leukemic blast samples of 10 pediatric ALL patients (4LR and 6 HR, according to minimal residual disease monitoring), included in the Italian AIEOP-BFM ALL2000 protocol. Genome-wide DNA profiling was performed by Affymetrix Cyto2.7M Arrays, RNA-seq was carried out by Illumina GAIIx platform, and validations were performed using independent approaches, such as RT-PCR and FISH. Fusion events were detected using FusionMap software, followed by a custom computational pipeline for the reduction of false positives and the identification of the most likely fusion candidates. Potential interest for leukemia was explored by testing the occurrence of these candidate fusions and con-joined genes in other RNA-seq datasets from different tumors and normal blood samples (i.e.: 15 melanomas, 2 melanocytes, 45 CEU individuals from 1K Genomes Project, plus 25 AML and 12 ALL). Results. We sequenced the transcriptome of 10 childhood ALL cases, not carrying other clinical or genetic risk factors. We performed a comprehensive whole-transcriptome analysis, comprising identification of fusion transcripts, alternative splicing and SNPs. Priority was given to fusion transcripts, which could originate from intra- or inter-chromosomal rearrangements, since they might represent potential prognostic markers or therapeutic targets for personalized treatments. We identified 127 fusion candidates. Strikingly, 123 out of 127 events were identified as intra-chromosomal, 119 of which were involving two contiguous genes or with overlapping loci (the so-called “con-joined genes”). Among the four intra-chromosomal events, the NUP214-ABL1 fusion, previously found in T-ALL and responsive to kinase inhibitors, was here identified and validated in one HR B-ALL patient, thus opening new perspectives for targeted treatment options. Finally, among the four inter-chromosomal events, the novel PAX5-POM121C fusion was identified and validated in one LR patient. Both intra- and inter-chromosomal fusions resulted private or low-frequent events, not recurrent in other tumor types, nor in normal blood samples. Among the con-joined genes, we identified a subset of 22 events not present in melanoma nor in normal blood samples, but common to the external AML and ALL datasets. Conclusion. RNA-seq represents one of the most comprehensive approaches to identify genetic alterations carried by leukemia clones. Our analyses identified novel fusion genes, originated by either inter- or intra-chromosomal rearrangements, as well as a considerable number of con-joined genes. Further evaluations will address SNPs, mutations, gene expression changes and splice variants that could be related to a different risk of relapse, and the feasibility of the screening of these candidates on a larger population of consecutive clinical cases. Disclosures No relevant conflicts of interest to declare.



BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Kristin Hieronymus ◽  
Benjamin Dorschner ◽  
Felix Schulze ◽  
Neeta L. Vora ◽  
Joel S. Parker ◽  
...  

Abstract Background Preterm birth is the leading cause of neonatal morbidity and mortality, but research efforts in neonatology are complicated due to the unavailability of large volume blood samples. Whole blood assays can be used to overcome this problem by performing both functional and gene expression studies using small amounts of blood. Gene expression studies using RT-qPCR estimate mRNA-levels of target genes normalized to reference genes. The goal of this study was to identify and validate stable reference genes applicable to cord blood samples obtained from developing neonates of different gestational age groups as well as to adult peripheral blood samples. Eight reference gene candidates (ACTB, B2M, GAPDH, GUSB, HPRT, PPIB, RPLP0, RPL13) were analyzed using the three published software algorithms Bestkeeper, GeNorm and NormFinder. Results A normalization factor consisting of ACTB and PPIB allows for comparative expression analyses of neonatal samples from different gestational age groups. Normalization factors consisting of GAPDH and PPIB or ACTB and GAPDH are suitable when samples from preterm and full-term neonates and adults are compared. However, all candidate reference genes except RPLP0 exhibited significant intergroup gene expression variance and a higher gene expression towards an older age which resulted in a small but statistically significant systematic bias. Systematic analysis of RNA-seq data revealed new reference gene candidates with potentially superior stability. Conclusions The current study identified suitable normalization factors and proposed the use of the additional single gene RPLP0 to avoid systematic bias. This combination will enable comparative analyses not only between neonates of different gestational ages, but also between neonates and adults, as it facilitates more detailed investigations of developmental gene expression changes. The use of software algorithms did not prevent unintended systematic bias. This generally highlights the need for careful validation of such results to prevent false interpretation of potential age-dependent changes in gene expression. To identify the most stable reference genes in the future, RNA-seq based global approaches are recommended.



2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Velma Herwanto ◽  
Benjamin Tang ◽  
Ya Wang ◽  
Maryam Shojaei ◽  
Marek Nalos ◽  
...  

Abstract Objectives Hospitalized patients who presented within the last 24 h with a bacterial infection were recruited. Participants were assigned into sepsis and uncomplicated infection groups. In addition, healthy volunteers were recruited as controls. RNA was prepared from whole blood, depleted from beta-globin mRNA and sequenced. This dataset represents a highly valuable resource to better understand the biology of sepsis and to identify biomarkers for severe sepsis in humans. Data description The data presented here consists of raw and processed transcriptome data obtained by next generation RNA sequencing from 105 peripheral blood samples from patients with uncomplicated infections, patients who developed sepsis, septic shock patients, and healthy controls. It is provided as raw sequenced reads and as normalized log2 transformed relative expression levels. This data will allow performing detailed analyses of gene expression changes between uncomplicated infections and sepsis patients, such as identification of differentially expressed genes, co-regulated modules as well as pathway activation studies.



2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Fei Xiong ◽  
Xiangyun Cheng ◽  
Chao Zhang ◽  
Roland Manfred Klar ◽  
Tao He

Abstract Background Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) remains one of the best-established techniques to assess gene expression patterns. However, appropriate reference gene(s) selection remains a critical and challenging subject in which inappropriate reference gene selction can distort results leading to false interpretations. To date, mixed opinions still exist in how to choose the most optimal reference gene sets in accodrance to the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guideline. Therefore, the purpose of this study was to investigate which schemes were the most feasible for the identification of reference genes in a bone and cartilage bioengineering experimental setting. In this study, rat bone mesenchymal stem cells (rBMSCs), skeletal muscle tissue and adipose tissue were utilized, undergoing either chondrogenic or osteogenic induction, to investigate the optimal reference gene set identification scheme that would subsequently ensure stable and accurate interpretation of gene expression in bone and cartilage bioengineering. Results The stability and pairwise variance of eight candidate reference genes were analyzed using geNorm. The V0.15- vs. Vmin-based normalization scheme in rBMSCs had no significant effect on the eventual normalization of target genes. In terms of the muscle tissue, the results of the correlation of NF values between the V0.15 and Vmin schemes and the variance of target genes expression levels generated by these two schemes showed that different schemes do indeed have a significant effect on the eventual normalization of target genes. Three selection schemes were adopted in terms of the adipose tissue, including the three optimal reference genes (Opt3), V0.20 and Vmin schemes, and the analysis of NF values with eventual normalization of target genes showed that the different selection schemes also have a significant effect on the eventual normalization of target genes. Conclusions Based on these results, the proposed cut-off value of Vn/n + 1 under 0.15, according to the geNorm algorithm, should be considered with caution. For cell only experiments, at least rBMSCs, a Vn/n + 1 under 0.15 is sufficient in RT-qPCR studies. However, when using certain tissue types such as skeletal muscle and adipose tissue the minimum Vn/n + 1 should be used instead as this provides a far superior mode of generating accurate gene expression results. We thus recommended that when the stability and variation of a candidate reference genes in a specific study is unclear the minimum Vn/n + 1 should always be used as this ensures the best and most accurate gene expression value is achieved during RT-qPCR assays.



Author(s):  
Guohong Zeng ◽  
Jin Li ◽  
Yuxiu Ma ◽  
Qian Pu ◽  
Tian Xiao ◽  
...  

AbstractSaponins are kinds of antifungal compounds produced by Panax notoginseng to resist invasion by pathogens. Ilyonectria mors-panacis G3B was the dominant pathogen inducing root rot of P. notoginseng, and the abilities to detoxify saponins were the key to infect P. notoginseng successfully. To research the molecular mechanisms of detoxifying saponins in I. mors-panacis G3B, we used high-throughput RNA-Seq to identify 557 and 1519 differential expression genes (DEGs) in I. mors-panacis G3B with saponins treatments for 4H (Hours) and 12H (Hours) compared with no saponins treatments, respectively. Among these DEGs, we found 93 genes which were simultaneously highly expressed in I. mors-panacis G3B with saponins treatments for 4H and 12H, they mainly belong to genes encoding transporters, glycoside hydrolases, oxidation–reduction enzymes, transcription factors and so on. In addition, there were 21 putative PHI (Pathogen–Host Interaction) genes out of those 93 up-regulated genes. In this report, we analyzed virulence-associated genes in I. mors-panacis G3B which may be related to detoxifying saponins to infect P. notoginseng successfully. They provided an excellent starting point for in-depth study on pathogenicity of I. mors-panacis G3B and developed appropriate root rot disease management strategies in the future.



2021 ◽  
Vol 141 (5) ◽  
pp. S32
Author(s):  
L. Youssefian ◽  
A. Saeidian ◽  
P. Fortina ◽  
A. South ◽  
J. Uitto ◽  
...  


2019 ◽  
Vol 66 (1) ◽  
pp. 229-238 ◽  
Author(s):  
Tracie Profaizer ◽  
Patricia Slev

Abstract BACKGROUND T-cell receptor excision circles (TREC) and κ-deleting recombination receptor excision circles (KREC) concentrations can be used to assess and diagnose immune deficiencies, monitor thymic and bone marrow immune reconstitution, or follow responses to drug therapy. We developed an assay to quantify TREC, KREC, and a reference gene in a single reaction using droplet digital PCR (ddPCR). METHODS PCR was optimized for 3 targets: TREC, KREC, and ribonuclease P/MRP subunit p30 (RPP30) as the reference gene. Multiplexing was accomplished by varying the target's fluorophore and concentration. Correlation with clinical results was evaluated using 47 samples from healthy donors, 59 samples with T-cell and B-cell markers within the reference interval from the flow cytometry laboratory, 20 cord blood samples, and 34 samples submitted for exome sequencing for severe combined immunodeficiency disease (SCID). RESULTS The limit of the blank was 4 positive droplets, limit of detection 9 positive droplets, and limit of quantification 25 positive droplets, or 2.0 copies/μL. TREC and KREC copies/μL were as expected in the healthy donors and cord blood samples and concordant with the healthy flow cytometry results. Of the samples from the SCID Panel, 56.5% had a TREC count <20 copies/μL and 17.7% had a KREC count <20 copies/μL, suggestive of low T- and B-cell numbers, respectively. CONCLUSIONS Our multiplex ddPCR assay is an analytically sensitive and specific method for the absolute quantification of TREC and KREC. To the best of our knowledge, this paper is the first to describe the simultaneous quantification of TREC, KREC, and a reference gene by use of ddPCR.



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