25 research outputs found
Toward reliable biomarker signatures in the age of liquid biopsies - how to standardize the small RNA-Seq workflow
Small RNA-Seq has emerged as a powerful tool in transcriptomics, gene expression profiling and biomarker discovery. Sequencing cell-free nucleic acids, particularly microRNA (miRNA), from liquid biopsies additionally provides exciting possibilities for molecular diagnostics, and might help establish disease-specific biomarker signatures. The complexity of the small RNA-Seq workflow, however, bears challenges and biases that researchers need to be aware of in order to generate high-quality data. Rigorous standardization and extensive validation are required to guarantee reliability, reproducibility and comparability of research findings. Hypotheses based on flawed experimental conditions can be inconsistent and even misleading. Comparable to the well-established MIQE guidelines for qPCR experiments, this work aims at establishing guidelines for experimental design and pre-analytical sample processing, standardization of library preparation and sequencing reactions, as well as facilitating data analysis. We highlight bottlenecks in small RNA-Seq experiments, point out the importance of stringent quality control and validation, and provide a primer for differential expression analysis and biomarker discovery. Following our recommendations will en-courage better sequencing practice, increase experimental transparency and lead to more reproducible small RNA-Seq results. This will ultimately enhance the validity of biomarker signatures, and allow reliable and robust clinical predictions
The Dynamics of microRNA Transcriptome in Bovine Corpus Luteum during Its Formation, Function, and Regression
The formation, function, and subsequent regression of the ovarian corpus luteum (CL) are dynamic processes that enable ovary cyclical activity. Studies in whole ovary tissue have found microRNAs (miRNAs) to by critical for ovary function. However, relatively little is known about the role of miRNAs in the bovine CL. Utilizing small RNA next-generation sequencing we profiled miRNA transcriptome in bovine CL during the entire physiological estrous cycle, by sampling the CL on days: d 1-2, d 3-4, and d 5-7 (early CL, eCL), d 8-12 (mid CL, mCL), d 13-16 (late CL, lCL), and d > 18 (regressed CL, rCL). We characterized patterns of miRNAs abundance and identified 42 miRNAs that were consistent significantly different expressed (DE) in the eCL relative to their expression at each of the analyzed stages (mCL, lCL, and rCL). Out of these, bta-miR-210-3p, -2898, -96, -7-5p, -183-5p, -182, and -202 showed drastic up-regulation with a fold-change of >= 2.0 and adjusted P < 0.01 in the eCL, while bta-miR-146a was downregulated at lCL and rCL vs. the eCL. Another 24, 11, and 21 miRNAs were significantly DE only between individual comparisons, eCL vs. the mCL, lCL, and rCL, respectively. Irrespective of cycle stage two miRNAs, bta-miR-21-5p and bta-miR-143 were identified as the most abundant miRNAs species and show opposing expression abundance. Whilst bta-miR-21-5p peaked in number of reads in the eCL and was significantly downregulated in the mCL and lCL, bta-miR-143 reached its peak in the rCL and is significantly downregulated in the eCL. MiRNAs with significant DE in at least one cycle stage (CL class) were further grouped into eight distinct clusters by the self-organizing tree algorithm (SOTA). Half of the clusters contain miRNAs with low-expression, whilst the other half contain miRNAs with high-expression levels during eCL. Prediction analysis for significantly DE miRNAs resulted in target genes involved with CL formation, functionalization and CL regression. This study is the most comprehensive profiling of miRNA transcriptome in bovine CL covering the entire estrous cycle and provides a compact database for further functional validation and biomarker identification relevant for CL viability and fertility
New surveillance concepts in food safety in meat producing animals: the advantage of high throughput ‘omics’ technologies — A review
The misuse of anabolic hormones or illegal drugs is a ubiquitous problem in animal husbandry and in food safety. The ban on growth promotants in food producing animals in the European Union is well controlled. However, application regimens that are difficult to detect persist, including newly designed anabolic drugs and complex hormone cocktails. Therefore identification of molecular endogenous biomarkers which are based on the physiological response after the illicit treatment has become a focus of detection methods. The analysis of the ‘transcriptome’ has been shown to have promise to discover the misuse of anabolic drugs, by indirect detection of their pharmacological action in organs or selected tissues. Various studies have measured gene expression changes after illegal drug or hormone application. So-called transcriptomic biomarkers were quantified at the mRNA and/or microRNA level by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) technology or by more modern ‘omics’ and high throughput technologies including RNA-sequencing (RNA-Seq). With the addition of advanced bioinformatical approaches such as hierarchical clustering analysis or dynamic principal components analysis, a valid ‘biomarker signature’ can be established to discriminate between treated and untreated individuals. It has been shown in numerous animal and cell culture studies, that identification of treated animals is possible via our transcriptional biomarker approach. The high throughput sequencing approach is also capable of discovering new biomarker candidates and, in combination with quantitative RT-qPCR, validation and confirmation of biomarkers has been possible. These results from animal production and food safety studies demonstrate that analysis of the transcriptome has high potential as a new screening method using transcriptional ‘biomarker signatures’ based on the physiological response triggered by illegal substances
Article DOI: 10.2478/v10133-010-0074-7 Be COMPARISON OF TWO AVAILABLE PLATFORMS FOR DETERMINATION OF RNA QUALITY
The integrity of RNA is a very critical aspect regarding downstream RNA based quantitative analysis like RT-qPCR. Lowquality RNA can compromise the results of such experiments. Today automated lab-on-chip capillary electrophoresis allows rapid RNA quality and quantity determination, e.g. 2100 Bioanalyzer (Agilent Technologies) and the Experion (Bio-Rad). Both platforms determine RNA quality using a numerical system which represents the integrity of RNA. The Bioanalyzer offers the RIN algorithm (RNA Integrity Number) on the Bioanalyzer 2100 and Bio-Rad developed a new Experion software version that offers an algorithm for calculating the RNA Quality Index (RQI). The aim of this study was to compare both systems regarding sensitivity, reproducibility, linearity and the influence of individual tissue extractions and different chip runs on RNA quality and quantity determination. Overall it was confirmed that both algorithms are very comparable and beneficial for the determination of RNA quality for downstream applications. The Experion showed slightly better results regarding reproducibility and absolute sensitivity, whereas the 2100 Bioanalyzer showed a higher linearity
Chapter 5 mRNA and microRNA Purity and Integrity: The Key to Success in Expression Profi ling
Abstract RNA quality control is a crucial step in guaranteeing integer nondegraded RNA and receiving meaningful results in gene expression profi ling experiments, using micro-array, RT-qPCR (Reverse-Transcription quantitative PCR), or Next-Generation-Sequencing by RNA-Seq or small-RNA Seq. Therefore, assessment of RNA integrity and purity is very essential prior to gene expression analysis of sample RNA to ensure the accuracy of any downstream applications. RNA samples should be nondegraded or fragmented and free of protein, genomic DNA, nucleases, and enzymatic inhibitors. Herein we describe the current state-of-the-art RNA quality assessment by combining UV/Vis spectrophotometry and microfl uidic capillary electrophoresis
The potential of circulating extracellular small RNAs (smexRNA) in veterinary diagnostics—Identifying biomarker signatures by multivariate data analysis
Worldwide growth and performance-enhancing substances are used in cattle husbandry to increase productivity. In certain countries however e.g., in the EU, these practices are forbidden to prevent the consumers from potential health risks of substance residues in food. To maximize economic profit, ‘black sheep‘ among farmers might circumvent the detection methods used in routine controls, which highlights the need for an innovative and reliable detection method. Transcriptomics is a promising new approach in the discovery of veterinary medicine biomarkers and also a missing puzzle piece, as up to date, metabolomics and proteomics are paramount. Due to increased stability and easy sampling, circulating extracellular small RNAs (smexRNAs) in bovine plasma were small RNA-sequenced and their potential to serve as biomarker candidates was evaluated using multivariate data analysis tools.
After running the data evaluation pipeline, the proportion of miRNAs (microRNAs) and piRNAs (PIWI-interacting small non-coding RNAs) on the total sequenced reads was calculated. Additionally, top 10 signatures were compared which revealed that the readcount data sets were highly affected by the most abundant miRNA and piRNA profiles. To evaluate the discriminative power of multivariate data analyses to identify animals after veterinary drug application on the basis of smexRNAs, OPLS-DA was performed. In summary, the quality of miRNA models using all mapped reads for both treatment groups (animals treated with steroid hormones or the β-agonist clenbuterol) is predominant to those generated with combined data sets or piRNAs alone. Using multivariate projection methodologies like OPLS-DA have proven the best potential to generate discriminative miRNA models, supported by small RNA-Seq data. Based on the presented comparative OPLS-DA, miRNAs are the favorable smexRNA biomarker candidates in the research field of veterinary drug abuse
Toward reliable biomarker signatures in the age of liquid biopsies - how to standardize the small RNA-Seq workflow
Small RNA-Seq has emerged as a powerful tool in transcriptomics, gene expression profiling and biomarker discovery. Sequencing cell-free nucleic acids, particularly microRNA (miRNA), from liquid biopsies additionally provides exciting possibilities for molecular diagnostics, and might help establish disease-specific biomarker signatures. The complexity of the small RNA-Seq workflow, however, bears challenges and biases that researchers need to be aware of in order to generate high-quality data. Rigorous standardization and extensive validation are required to guarantee reliability, reproducibility and comparability of research findings. Hypotheses based on flawed experimental conditions can be inconsistent and even misleading. Comparable to the well-established MIQE guidelines for qPCR experiments, this work aims at establishing guidelines for experimental design and pre-analytical sample processing, standardization of library preparation and sequencing reactions, as well as facilitating data analysis. We highlight bottlenecks in small RNA-Seq experiments, point out the importance of stringent quality control and validation, and provide a primer for differential expression analysis and biomarker discovery. Following our recommendations will en-courage better sequencing practice, increase experimental transparency and lead to more reproducible small RNA-Seq results. This will ultimately enhance the validity of biomarker signatures, and allow reliable and robust clinical predictions
Development of mRNA patterns for screening of anabolic steroids in
bovine and primate tissue
The Dynamics of microRNA Transcriptome in Bovine Corpus Luteum during Its Formation, Function, and Regression
The formation, function, and subsequent regression of the ovarian corpus luteum (CL) are dynamic processes that enable ovary cyclical activity. Studies in whole ovary tissue have found microRNAs (miRNAs) to by critical for ovary function. However, relatively little is known about the role of miRNAs in the bovine CL. Utilizing small RNA next-generation sequencing we profiled miRNA transcriptome in bovine CL during the entire physiological estrous cycle, by sampling the CL on days: d 1–2, d 3–4, and d 5–7 (early CL, eCL), d 8–12 (mid CL, mCL), d 13–16 (late CL, lCL), and d > 18 (regressed CL, rCL). We characterized patterns of miRNAs abundance and identified 42 miRNAs that were consistent significantly different expressed (DE) in the eCL relative to their expression at each of the analyzed stages (mCL, lCL, and rCL). Out of these, bta-miR-210-3p, −2898, −96, −7-5p, −183-5p, −182, and −202 showed drastic up-regulation with a fold-change of ≥2.0 and adjusted P < 0.01 in the eCL, while bta-miR-146a was downregulated at lCL and rCL vs. the eCL. Another 24, 11, and 21 miRNAs were significantly DE only between individual comparisons, eCL vs. the mCL, lCL, and rCL, respectively. Irrespective of cycle stage two miRNAs, bta-miR-21-5p and bta-miR-143 were identified as the most abundant miRNAs species and show opposing expression abundance. Whilst bta-miR-21-5p peaked in number of reads in the eCL and was significantly downregulated in the mCL and lCL, bta-miR-143 reached its peak in the rCL and is significantly downregulated in the eCL. MiRNAs with significant DE in at least one cycle stage (CL class) were further grouped into eight distinct clusters by the self-organizing tree algorithm (SOTA). Half of the clusters contain miRNAs with low-expression, whilst the other half contain miRNAs with high-expression levels during eCL. Prediction analysis for significantly DE miRNAs resulted in target genes involved with CL formation, functionalization and CL regression. This study is the most comprehensive profiling of miRNA transcriptome in bovine CL covering the entire estrous cycle and provides a compact database for further functional validation and biomarker identification relevant for CL viability and fertility
DOI 10.1007/s10529-009-0130-2
Validation of extraction methods for total RNA and miRNA from bovine blood prior to quantitative gene expression analyse