The Transcript Integrity Index (TII) provides a standard measure of sperm RNA
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA828260 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR18825300_1.fastq.gz | Fastqsanger.gz | |||
| SRR18825300_2.fastq.gz | Fastqsanger.gz | |||
| SRR18825301_1.fastq.gz | Fastqsanger.gz | |||
| SRR18825301_2.fastq.gz | Fastqsanger.gz | |||
| SRR18825302_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 80 |
Similar Datasets
Project description:Human sperm RNA-seq was performed and sequences used for the generation of a RNA integrity index capable of assessing samples with high RNA fragmentation. A two-prong approach was used including both manual and computational analysis. This identified a series of sperm RNAs that are consistently intact, and acceptable for use in determining sample RNA quality. These RNAs function in roles related to spermatogenesis and/or fertilization.
2022-04-26 | GSE201081 | GEO
Project description:Achieved biospecimens annotated with patient clinical characteristics are unique resources for translational research. However, RNA extracted from the achieved tissues is often degraded. RNA degradation can have a significant impact on the measure of transcript abundance that can lead to an increase rate of erroneous differentially expressed genes. Here, we are presenting the transcript integrity number (TIN) algorithm to measure the RNA degradation at transcript level. When applied to RNA-seq datasets generated from human brain Glioblastome cell line, human peripheral blood mononuclear cells, and metastatic castration resistant prostate cancer (mCRPC) clinical tissues, TIN provided a more reliable and more sensitive measure of RNA degradation than RIN, as demonstrated by much higher concordance with the RNA fragment size estimated from read pairs. More importantly, when comparing 10 mCRPC samples with lower RNA quality to another 10 samples with higher RNA quality, we demonstrated that calibrating gene quantification with TIN scores could mitigate RNA degradation effects and greatly improve gene expression analysis. The detected differentially expressed genes before TIN correction were predominantly ribosomal genes. However, when we adjusted gene quantifications with the corresponding TIN scores, we found differentially expressed genes were highly enriched in prostate cancer specific pathways. When further evaluating the performance of TIN correction using synthetic spike-in transcripts with predetermined abundance in RNA-seq data generated from Sequencing Control Consortium (SEQC), we found TIN adjustment had a better control of false positives and false negatives (sensitivity = 0.89, specificity = 0.91), as compared to gene expression analysis results without TIN correction (sensitivity =0.98, specificity = 0.50). RNA sequencing of 20 bone-metastatic castration resistant prostate cancer (mCRPC) using Illumina HiSeq 2500. Out of 20 mCRPC samples, 10 samples have relative low RNA integrity and another 10 samples have relative higher RNA integrity as measured by Agilent RIN score.
2016-02-19 | E-GEOD-70285 | biostudies-arrayexpress
Project description:Achieved biospecimens annotated with patient clinical characteristics are unique resources for translational research. However, RNA extracted from the achieved tissues is often degraded. RNA degradation can have a significant impact on the measure of transcript abundance that can lead to an increase rate of erroneous differentially expressed genes. Here, we are presenting the transcript integrity number (TIN) algorithm to measure the RNA degradation at transcript level. When applied to RNA-seq datasets generated from human brain Glioblastome cell line, human peripheral blood mononuclear cells, and metastatic castration resistant prostate cancer (mCRPC) clinical tissues, TIN provided a more reliable and more sensitive measure of RNA degradation than RIN, as demonstrated by much higher concordance with the RNA fragment size estimated from read pairs. More importantly, when comparing 10 mCRPC samples with lower RNA quality to another 10 samples with higher RNA quality, we demonstrated that calibrating gene quantification with TIN scores could mitigate RNA degradation effects and greatly improve gene expression analysis. The detected differentially expressed genes before TIN correction were predominantly ribosomal genes. However, when we adjusted gene quantifications with the corresponding TIN scores, we found differentially expressed genes were highly enriched in prostate cancer specific pathways. When further evaluating the performance of TIN correction using synthetic spike-in transcripts with predetermined abundance in RNA-seq data generated from Sequencing Control Consortium (SEQC), we found TIN adjustment had a better control of false positives and false negatives (sensitivity = 0.89, specificity = 0.91), as compared to gene expression analysis results without TIN correction (sensitivity =0.98, specificity = 0.50).
2016-02-19 | GSE70285 | GEO
Project description:New index for the evaluation of mRNA integrity
| PRJEB28215 | ENA
Project description:BackgroundStored biological samples with pathology information and medical records are invaluable resources for translational medical research. However, RNAs extracted from the archived clinical tissues are often substantially degraded. RNA degradation distorts the RNA-seq read coverage in a gene-specific manner, and has profound influences on whole-genome gene expression profiling.ResultWe developed the transcript integrity number (TIN) to measure RNA degradation. When applied to 3 independent RNA-seq datasets, we demonstrated TIN is a reliable and sensitive measure of the RNA degradation at both transcript and sample level. Through comparing 10 prostate cancer clinical samples with lower RNA integrity to 10 samples with higher RNA quality, we demonstrated that calibrating gene expression counts with TIN scores could effectively neutralize RNA degradation effects by reducing false positives and recovering biologically meaningful pathways. When further evaluating the performance of TIN correction using spike-in transcripts in RNA-seq data generated from the Sequencing Quality Control consortium, we found TIN adjustment had better control of false positives and false negatives (sensitivity = 0.89, specificity = 0.91, accuracy = 0.90), as compared to gene expression analysis results without TIN correction (sensitivity = 0.98, specificity = 0.50, accuracy = 0.86).ConclusionTIN is a reliable measurement of RNA integrity and a valuable approach used to neutralize in vitro RNA degradation effect and improve differential gene expression analysis.
| S-EPMC4739097 | biostudies-literature
Project description:The phi X 174 bacteriophage was first sequenced in 1977, and has since become the most widely used standard in molecular biology and next-generation sequencing. However, with the advent of affordable DNA synthesis and de novo gene design, we considered whether we could engineer a synthetic genome, termed SynX, specifically tailored for use as a universal molecular standard. The SynX genome encodes 21 synthetic genes that can be in vitro transcribed to generate matched mRNA controls, and in vitro translated to generate matched protein controls. This enables the use of SynX as a matched control to compare across genomic, transcriptomic and proteomic experiments. The synthetic genes provide qualitative controls that measure sequencing accuracy across k-mers, GC-rich and repeat sequences, as well as act as quantitative controls that measure sensitivity and quantitative accuracy. We show how the SynX genome can measure DNA sequencing, evaluate gene expression in RNA sequencing experiments, or quantify proteins in mass spectrometry. Unlike previous spike-in controls, the SynX DNA, RNA and protein controls can be independently and sustainably prepared by recipient laboratories using common molecular biology techniques, and widely shared as a universal molecular standard.
2024-03-22 | PXD035035 | Pride
Project description:Researchers may be interested in finding proteomics runs, which have been deposited into online repositories, that are similar to their own data. However, it is difficult to measure the similarity of a pair of proteomics runs. Here, we present a new method, MS1Connect, that only uses intact peptide scans to calculate the similarity between a pair of runs. We show evidence that the MS1Connect score accurately measures the similarity between two proteomics runs. Specifically, we show that MS1Connect outperforms baseline methods for predicting the species a sample originated. In addition, we show that MS1Connect scores are highly correlated with similarities based o peptide fragment scans by observing a high correlation between MS1Connect scores and the Jaccard index between the sets of confidently detected peptides for a pair of runs.
2023-01-05 | PXD027791 | Pride
Project description:Although thousands of genetically modified mouse strains have been cryopreserved by sperm freezing, the likelihood of cryorecovery success cannot be accurately predicted using conventional sperm parameters. The objective of the present study was to assess the extent to which measurement of a sperm DNA fragmentation index (DFI) can predict sperm quality and fertility after cryopreservation. Using a modified TUNEL assay, we measured and correlated the DFI of frozen-thawed sperm from 83 unique mutant mouse strains with sperm count, motility and morphology. We observed a linear inverse correlation between sperm DFI and sperm morphology and motility. Further, sperm DFI was significantly higher from males with low sperm counts compared to males with normal sperm counts (P?<?0.0001). Additionally, we found that viable embryos derived using sperm from males with high DFI (62.7?±?7.2% for IVF and 73.3?±?8.1% for ICSI) failed to litter after embryo transfer compared to embryos from males with low DFI (20.4?±?7.9% for IVF and 28.1?±?10.7 for ICSI). This study reveals that measurement of DFI provides a simple, informative and reliable measure of sperm quality and can accurately predict male mouse fertility.
| S-EPMC7052244 | biostudies-literature
Project description:Intracytoplasmic sperm injection is a popular form of in vitro fertilization, where single sperm are selected by a clinician and injected into an egg. Whereas clinicians employ general morphology-based guidelines to select the healthiest-looking sperm, it remains unclear to what extent an individual sperm's physical parameters correlate with the quality of internal DNA cargo-a measurement that cannot be obtained without first damaging the sperm. Herein, a single-cell DNA fragmentation index (DFI) assay is demonstrated, which combines the single-cell nature of the acridine orange test with the quantitative aspect of the sperm chromatin structure assay, to create a database of DFI-scored brightfield images. Two regression predictive models, linear and nonlinear regression, are used to quantify the correlations between individual sperm morphological parameters and DFI score (with model test r at 0.558 and 0.620 for linear and nonlinear regression models, respectively). The sample is also split into two categories of either relatively good or bad DFIs and a classification predictive model based on logistic regression is used to categorize sperm, resulting in a test accuracy of 0.827. Here, the first systematic study is presented on the correlation and prediction of sperm DNA integrity from morphological parameters at the single-cell level.
| S-EPMC6685501 | biostudies-literature
Project description:Mitochondrial diversity study of Xiphinema index
| PRJEB26007 | ENA