Dataset Information

MiRNA-Seq identifies a serum miRNA panel which can detect and monitor liver disease in pediatric cystic fibrosis

ABSTRACT: Purpose: Cystic fibrosis (CF)-associated liver disease (CFLD) is a hepatobiliary complication of CF. Current diagnostic modalities rely on non-specific assessments, while liver biopsy is the gold standard to assess severity of disease. Using miRNA-sequencing we investigated the use of serum miRNA to diagnose and monitor CFLD progression in children with CF. Methods: This was a cross-sectional cohort study of the circulatory miRNA signature of 90 children grouped by clinical, biochemical and imaging assessments as follows: healthy controls (n=30), CF patients with no evidence of liver disease (CFnoLD, n=30) and CFLD (n=30). Serum miRNAs were analysed by miRNA-sequencing. Following total circulatory RNA extraction, RNA samples were pooled together to create three libraries (i.e., 10 patients/library) per study cohort. Libraries were prepared using the Ion Total RNA-Seq Kit v2 protocol (Thermo Fisher, Revision E) and sequenced on the Ion Proton System, using the Ion PI Chip v3 following the Ion PI Hi-Q Sequencing 200 Kit protocol (Thermo Fisher, Revision C). Selected differentially expressed serum miRNA candidates were further validated in 124 individual children serum samples by qRT-PCR and statistical analysis performed to evaluate utility to predict CFLD and hepatic fibrosis severity validated by liver biopsy. Results: The nine libraries sequenced by the Ion Proton System produced 64,658,545 total reads. During processing of the sequencing data, we noticed significant low counts mapped from the CFnoLD library 3. Following principal component analysis this library was confirmed to be an outlier and excluded from the analysis. For the remaining libraries, initial threshold filtering was performed by discarding miRNAs with 10 or less counts and normalized for compositional bias in sequenced libraries and library size. After threshold filtering, 659 miRNAs were identified with a minimum average count of 10.

ORGANISM(S): Homo sapiens

PROVIDER: GSE111754 | GEO | 2018/07/27

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Data independent acquisition (DIA or DIA/SWATH ) mass spectrometry has emerged as a primary measurement strategy in the field of quantitative proteomics. diaPASEF is a recent adaptation that leverages trapped ion mobility spectrometry (TIMS) to improve selectivity and increase sensitivity. The complex fragmentation spectra generated by co-isolation of peptides in DIA mode are most typically analyzed with reference to prior knowledge in the form of spectral libraries. The best established method for generating libraries uses data dependent acquisition (DDA) mode, or DIA mode if appropriately deconvoluted, often including offline fractionation to increase depth of coverage,to create spectral libraries. More recently strategies for spectral library generation based on gas phase fractionation (GPF), where a representative sample is injected serially using narrow window DIA methods designed to cover different slices of the precursor space, have been introduced and performed comparably to deep offline fractionation-based libraries for DIA data analysis. Here, we investigated whether an analogous GPF-based library building approach that accounts for the ion mobility (IM) dimension is useful for the analysis of diaPASEF data and can remove the need for offline fractionation. To enable a rapid library development approach for diaPASEF we designed a GPF acquisition scheme covering the majority of multiply charged precursors in the m/z vs 1/K0 space requiring 7 injections of a representative sample and compared this with libraries generated by direct deconvolution-based analysis of diaPASEF data or by deep offline fractionation and ddaPASEF. . We found that the GPF based library outperformed library generation by direct deconvolution of the diaPASEF data, and performed comparably to deep offline fractionation libraries, when analysing diaPASEF data acquired from 200ng of commercial HeLa digest. With the ion mobility integrated GPF scheme we establish a pragmatic approach to rapid and comprehensive library generation for the analysis of diaPASEF data.

Dataset Information

MiRNA-Seq identifies a serum miRNA panel which can detect and monitor liver disease in pediatric cystic fibrosis

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets