The Transcript Integrity Index (TII) provides a standard measure of sperm RNA
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE201081 | GEO | 2022/04/26
REPOSITORIES: GEO
Similar Datasets
Project description:The Transcript Integrity Index (TII) provides a standard measure of sperm RNA
| PRJNA828260 | ENA
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: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: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:Plant material from sperm and egg cells, zygotes 12 and 24 hours after pollination (hap) and apical and basal cells was collected using manual dissection. From these cell types RNA Seq libraries were prepared and gene expression profiles were analysed
2017-09-05 | GSE98379 | GEO
Project description:The aim of the study was to determine the influence of tissue degeneration due to prolonged storage of tissues on RNA integrity and the miRNA expression profile using microarrays. There is some dispute as to which RNA integrity level is still acceptable for miRNA expression profiling by microarrays. Some authors claim that miRNAs are stable even in degraded total RNA, others say the opposite. Therefore, we wanted to clarify if miRNA are stable in degraded tissues and which miRNAs are the most susceptible to RNA degradation.
2017-07-17 | GSE93632 | GEO
Project description:The discovery of RNAs (e.g. mRNAs, non-coding RNAs) in sperm has opened the possibility that sperm may function in delivering additional paternal information aside from solely providing the DNA1. Increasing evidence now suggests that sperm small non-coding RNAs (sncRNAs) can mediate intergenerational transmission of paternally acquired phenotypes, including mental stress2, 3 and metabolic disorders4-6. How sperm sncRNAs encode paternal information remains unclear, but the mechanism may involve RNA modifications. Here we show that deletion of a mouse tRNA methyltransferase, DNMT2, abolished sperm sncRNA-mediated transmission of high-fat diet (HFD)-induced metabolic disorders to offspring. Dnmt2 deletion prevented the elevation of RNA modifications (m5C, m2G) in sperm 30-40nt RNA fractions that are induced by HFD. Also, Dnmt2 deletion altered the sperm small RNA expression profile, including levels of tRNA-derived small RNAs (tsRNAs) and rRNA-derived small RNAs (rsRNA-28S), which might be essential in composing a sperm RNA ‘coding signature’ that is needed for paternal epigenetic memory. Finally, we show that Dnmt2-mediated m5C contributes to the secondary structure and biological properties of sncRNAs, implicating sperm RNA modifications as an additional layer of paternal hereditary information.
2018-03-06 | GSE97645 | GEO
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:Chromatin packaging in sperm protects it against DNA fragmentation, and the importance of proper chromatin packaging for boar fertility outcome has become increasingly evident. Little is known however about the molecular mechanisms underlying differences in sperm DNA fragmentation and an understanding of the genes controlling this sperm parameter could help in selecting the best boars for AI use. The aim of this study was to identify differentially expressed genes in testis of Norsvin Landrace and Duroc boars with good and bad sperm DNA fragmentation using transcriptome sequencing and to use the data for polymorphism search. RNA sequence reads were obtained using Illumina technology and mapped by TopHat using the Ensembl pig database. Differentially expressed genes and pathways were analyzed using the R Bioconductor packages edgeR and goseq respectively. Using a false discovery rate of 0.05, 309 and 375 genes were found displaying significant differences in expression level between the good and bad condition in Landrace and Duroc respectively. Of the differentially expressed genes, 72 were found in common for the two breeds. Gene ontology analysis revealed that terms common for the two breeds included extracellular matrix, extracellular region and calcium ion binding. Additionally, different metabolic processes were enriched in Landrace and Duroc, whereas immune response ontologies were found to be important in Landrace. SNP detection in Landrace/Duroc identified 53182/53931 variants in 10924/10748 transcripts and of these, 1573/1827 SNPs occurred in 189/241 unique genes that were also differentially expressed. Possible high impact variants were detected using SnpEff. Transcriptome sequencing identified differentially expressed genes and nucleotide variants related to differences in sperm DNA fragmentation, and functional annotation of the genes pointed towards important biochemical pathways. This study provides insights into the genetic network underlying this trait and is a first step towards using sperm DNA fragmentation for predicting boar fertility.
2017-09-01 | GSE74934 | GEO