Next Generation Sequencing Facilitates Differential Expression Analysis of miRNA Expression In the Whole Blood Samples Obtained From Prostate Cancer Patients vs. Controls
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE97901 | GEO | 2017/04/18
SECONDARY ACCESSION(S): PRJNA383159
REPOSITORIES: GEO
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Project description:IntroductionAs tick-borne diseases rise to become the second most prevalent arthropod-transmitted disease globally, the increasing investigations focus on ticks correspondingly. Factors contributed to this increase include anthropogenic influences, changes in vertebrate faunal composition, social-recreational shifts, and climatic variation. Employing the 16S gene sequence method in next-generation sequencing (NGS) allows comprehensive pathogen identification in samples, facilitating the development of refined approaches to tick research omnidirectionally.MethodsIn our survey, we compared the microbial richness and biological diversity of ticks in Wuwei City, Gansu province, differentiating between questing ticks found in grass and parasitic ticks collected from sheep based on 16S NGS method.ResultsThe results show Rickettsia, Coxiella, and Francisella were detected in all 50 Dermacentor nuttalli samples, suggesting that the co-infection may be linked to specific symbiotic bacteria in ticks. Our findings reveal significant differences in the composition and diversity of microorganisms, with the Friedmanniella and Bordetella genera existing more prevalent in parasitic ticks than in questing ticks (p < 0.05). Additionally, the network analysis demonstrates that the interactions among bacterial genera can be either promotive or inhibitive in ticks exhibiting different lifestyles with the correlation index |r| > 0.6. For instance, Francisella restrains the development of 10 other bacteria in parasitic ticks, whereas Phyllobacterium and Arthrobacter enhance colonization across all tick species.DiscussionBy leveraging NGS techniques, our study reveals a high degree of species and phylogenetic diversity within the tick microbiome. It further highlights the potential to investigate the interplay between bacterial genera in both parasitic and questing ticks residing in identical habitat environments.
| S-EPMC10773790 | biostudies-literature
Project description:Neurodegenerative diseases encompass a wide variety of pathological conditions caused by a loss of neurons in the central nervous system (CNS) and are severely debilitating. Exosome contains bio-signatures of great diagnostic and therapeutic value. There is proof that exosomal proteins can be biomarkers for Alzheimer's disease (AD) and Parkinson's disease (PD). MicroRNAs in exosome has potential to be an important source of biomarkers for neurodegenerative diseases. Here, we report exosomal microRNA performance of human plasma in neurodegenerative diseases by small RNA sequencing. A wide range of altered exo-miRNA expression levels were detected in both AD and PD patients. Down-regulated miRNAs in AD samples were enriched in ECM-receptor interaction pathway and both up-/down-regulated miRNAs in PD samples were enriched in fatty acid biosynthesis pathway. Compared to the control, 8 miRNAs were found to be significantly elevated/declined in AD and PD samples, of which 4 miRNAs were newly identified. Additionally, two exosome isolating methods were compared and the reproducibility of plasma exo-miRNA expression was confirmed, suggesting the feasibility of large-scale clinical application of this method. This study revealed exo-miRNA expression levels in neurodegenerative diseases, proposed new biomarkers and their potential functional pathway for AD and PD, confirmed the reproductivity of exo-miRNA profiles by using a different exosome isolating method, and compared the results with plasma miRNA expression. Therefore, this study also provides a precedent for identifying exosomal biomarkers of neurodegenerative diseases in plasma by high-throughput sequencing and it could extend the therapeutic repertoire of exosomal biomarkers.
| S-EPMC7227778 | biostudies-literature
Project description:Next-generation sequencing technologies enable the rapid cost-effective production of sequence data. To evaluate the performance of these sequencing technologies, investigation of the quality of sequence reads obtained from these methods is important. In this study, we analyzed the quality of sequence reads and SNP detection performance using three commercially available next-generation sequencers, i.e., Roche Genome Sequencer FLX System (FLX), Illumina Genome Analyzer (GA), and Applied Biosystems SOLiD system (SOLiD). A common genomic DNA sample obtained from Escherichia coli strain DH1 was applied to these sequencers. The obtained sequence reads were aligned to the complete genome sequence of E. coli DH1, to evaluate the accuracy and sequence bias of these sequence methods. We found that the fraction of "junk" data, which could not be aligned to the reference genome, was largest in the data set of SOLiD, in which about half of reads could not be aligned. Among data sets after alignment to the reference, sequence accuracy was poorest in GA data sets, suggesting relatively low fidelity of the elongation reaction in the GA method. Furthermore, by aligning the sequence reads to the E. coli strain W3110, we screened sequence differences between two E. coli strains using data sets of three different next-generation platforms. The results revealed that the detected sequence differences were similar among these three methods, while the sequence coverage required for the detection was significantly small in the FLX data set. These results provided valuable information on the quality of short sequence reads and the performance of SNP detection in three next-generation sequencing platforms.
| S-EPMC3096631 | biostudies-literature
Project description: Not available
| S-EPMC11022476 | biostudies-literature
Project description:We established a protocol of the SuperSAGE technology combined with next-generation sequencing, coined "High-Throughput (HT-) SuperSAGE". SuperSAGE is a method of digital gene expression profiling that allows isolation of 26-bp tag fragments from expressed transcripts. In the present protocol, index (barcode) sequences are employed to discriminate tags from different samples. Such barcodes allow researchers to analyze digital tags from transcriptomes of many samples in a single sequencing run by simply pooling the libraries. Here, we demonstrated that HT-SuperSAGE provided highly sensitive, reproducible and accurate digital gene expression data. By increasing throughput for analysis in HT-SuperSAGE, various applications are foreseen and several examples are provided in the present study, including analyses of laser-microdissected cells, biological replicates and tag extraction using different anchoring enzymes.
| S-EPMC2917361 | biostudies-literature
Project description:Due to its cost effectiveness, next-generation sequencing of pools of individuals (Pool-Seq) is becoming a popular strategy for characterizing variation in population samples. Because Pool-Seq provides genome-wide SNP frequency data, it is possible to use them for demographic inference and/or the identification of selective sweeps. Here, we introduce a statistical method that is designed to detect selective sweeps from pooled data by accounting for statistical challenges associated with Pool-Seq, namely sequencing errors and random sampling among chromosomes. This allows for an efficient use of the information: all base calls are included in the analysis, but the higher credibility of regions with higher coverage and base calls with better quality scores is accounted for. Computer simulations show that our method efficiently detects sweeps even at very low coverage (0.5× per chromosome). Indeed, the power of detecting sweeps is similar to what we could expect from sequences of individual chromosomes. Since the inference of selective sweeps is based on the allele frequency spectrum (AFS), we also provide a method to accurately estimate the AFS provided that the quality scores for the sequence reads are reliable. Applying our approach to Pool-Seq data from Drosophila melanogaster, we identify several selective sweep signatures on chromosome X that include some previously well-characterized sweeps like the wapl region.
| S-EPMC3424412 | biostudies-literature
Project description:Sequencing large number of individuals, which is often needed for population genetics studies, is still economically challenging despite falling costs of Next Generation Sequencing (NGS). Pool-seq is an alternative cost- and time-effective option in which DNA from several individuals is pooled for sequencing. However, pooling of DNA creates new problems and challenges for accurate variant call and allele frequency (AF) estimation. In particular, sequencing errors confound with the alleles present at low frequency in the pools possibly giving rise to false positive variants. We sequenced 996 individuals in 83 pools (12 individuals/pool) in a targeted re-sequencing experiment. We show that Pool-seq AFs are robust and reliable by comparing them with public variant databases and in-house SNP-genotyping data of individual subjects of pools. Furthermore, we propose a simple filtering guideline for the removal of spurious variants based on the Kolmogorov-Smirnov statistical test. We experimentally validated our filters by comparing Pool-seq to individual sequencing data showing that the filters remove most of the false variants while retaining majority of true variants. The proposed guideline is fairly generic in nature and could be easily applied in other Pool-seq experiments.
| S-EPMC5037392 | biostudies-literature
Project description:Histopathological samples are a treasure-trove of DNA for clinical research. However, the quality of DNA can vary depending on the source or extraction method applied. Thus a standardized and cost-effective workflow for the qualification of DNA preparations is essential to guarantee interlaboratory reproducible results. The qualification process consists of the quantification of double strand DNA (dsDNA) and the assessment of its suitability for downstream applications, such as high-throughput next-generation sequencing. We tested the two most frequently used instrumentations to define their role in this process: NanoDrop, based on UV spectroscopy, and Qubit 2.0, which uses fluorochromes specifically binding dsDNA. Quantitative PCR (qPCR) was used as the reference technique as it simultaneously assesses DNA concentration and suitability for PCR amplification. We used 17 genomic DNAs from 6 fresh-frozen (FF) tissues, 6 formalin-fixed paraffin-embedded (FFPE) tissues, 3 cell lines, and 2 commercial preparations. Intra- and inter-operator variability was negligible, and intra-methodology variability was minimal, while consistent inter-methodology divergences were observed. In fact, NanoDrop measured DNA concentrations higher than Qubit and its consistency with dsDNA quantification by qPCR was limited to high molecular weight DNA from FF samples and cell lines, where total DNA and dsDNA quantity virtually coincide. In partially degraded DNA from FFPE samples, only Qubit proved highly reproducible and consistent with qPCR measurements. Multiplex PCR amplifying 191 regions of 46 cancer-related genes was designated the downstream application, using 40 ng dsDNA from FFPE samples calculated by Qubit. All but one sample produced amplicon libraries suitable for next-generation sequencing. NanoDrop UV-spectrum verified contamination of the unsuccessful sample. In conclusion, as qPCR has high costs and is labor intensive, an alternative effective standard workflow for qualification of DNA preparations should include the sequential combination of NanoDrop and Qubit to assess the purity and quantity of dsDNA, respectively.
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Project description:Current prostate cancer risk calculators are limited in impact because only a probability of having prostate cancer is provided. We developed the next generation of prostate cancer risk calculator that incorporates life expectancy in order to better evaluate prostate cancer risk in context to a patient's age and comorbidity.We combined two cohorts to develop the new risk calculator. The first was 5638 subjects who all underwent a prostate biopsy for prostate cancer detection. The second was 979 men diagnosed with prostate cancer with long-term survival data. Two regression models were used to create multivariable nomograms and an online prostate cancer risk calculator was developed.Of the 5638 patients who underwent a prostate biopsy, 629 (11%) were diagnosed with aggressive prostate cancer (Gleason Score 7[4+3] or more). Of the 979 patients who underwent treatment for prostate cancer, the 10-year overall survival (OS) was 49.6% (95% confidence interval [CI] 46.6-52.9). The first multivariable nomogram for cancer risk had a concordance index of 0.74 (95% CI 0.72, 0.76), and the second nomogram to predict survival had a concordance index of 0.71 (95% CI 0.69-0.72). The next-generation prostate cancer risk calculator was developed online and is available at: http://riskcalc.org/ProstateCA_Screen_Tool.We have developed the next-generation prostate cancer risk calculator that incorporates a patient's life expectancy based on age and comorbidity. This approach will better evaluate prostate cancer risk. Future studies examining other populations will be needed for validation.
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Project description:As the proteomics field continues to expand, scientists are looking to integrate cross-disciplinary tools for studying protein structure, function, and interactions. Protein purification remains a key tool for many characterization studies. Calmodulin (CaM) is a calcium-binding messenger protein with over a hundred downstream binding partners, and is involved in a host of physiological processes, from learning and memory to immune and cardiac function. To facilitate biophysical studies of calmodulin, researchers have designed a site-specific labeling process for use in bioconjugation applications while maintaining high levels of protein activity. Here, we present a platform for selective conjugation of calmodulin directly from clarified cell lysates under bioorthogonal reaction conditions. Using a chemoenzymatically modified calmodulin, we employ popular click chemistry reactions for the conjugation of calmodulin to Sepharose resin, thereby streamlining a previously multi-step purification and conjugation process. We show that this "next-generation" calmodulin-Sepharose resin is not only easy to produce, but is also able to purify more calmodulin-binding proteins per volume of resin than traditional calmodulin-Sepharose resins. We expect these methods to be translatable to other proteins of interest and to other conjugation applications such as surface-based assays for the characterization of protein-protein interaction dynamics.
| S-EPMC5986150 | biostudies-literature