Dataset Information

Pathological and physiological cardiac hypertrophy

ABSTRACT: This project is the comparison of protein profiles for pathological and physiological mouse cardiac hypertrophy

INSTRUMENT(S): LTQ

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Heart

DISEASE(S): Cardiovascular System Disease

SUBMITTER: Hye-Kyeong Kwon

LAB HEAD: Zee-Yong Park

PROVIDER: PXD010165 | Pride | 2018-07-30

REPOSITORIES: Pride

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Comparative proteomic analysis of mouse models of pathological and physiological cardiac hypertrophy, with selection of biomarkers of pathological hypertrophy by integrative Proteogenomics.

Kwon Hye Kyeong HK Jeong Hyobin H Hwang Daehee D Park Zee-Yong ZY

Biochimica et biophysica acta. Proteins and proteomics 20180723

To determine fundamental characteristics of pathological cardiac hypertrophy, protein expression profiles in two widely accepted models of cardiac hypertrophy (swimming-trained mouse for physiological hypertrophy and pressure-overload-induced mouse for pathological hypertrophy) were compared using a label-free quantitative proteomics approach. Among 3955 proteins (19,235 peptides, false-discovery rate < 0.01) identified in these models, 486 were differentially expressed with a log<sub>2</sub> fo ...[more]

PMID: 30048702

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Project description:Accurate and comprehensive de novo transcriptome profiling in heart is a central issue to better understand cardiac physiology and diseases. Although significant progress has been made in genome-wide profiling for quantitative changes in cardiac gene expression, current knowledge offers limited insights to the total complexity in cardiac transcriptome at individual exon level. To develop more robust bioinformatic approaches to analyze high-throughput RNA sequencing (RNA-Seq) data, with the focus on the investigation of transcriptome complexity at individual exon and transcript levels. In addition to overall gene expression analysis, the methods developed in this study were used to analyze RNA-Seq data with respect to individual transcript isoforms, novel spliced exons, novel alternative terminal exons, novel transcript clusters (i.e., novel genes) and long non-coding RNA genes. We applied these approaches to RNA-Seq data obtained from mouse hearts following pressure-overload induced by trans-aortic constriction. Based on experimental validations, analyses of the features of the identified exons/transcripts, and expression analyses including previously published RNA-Seq data, we demonstrate that the methods are highly effective in detecting and quantifying individual exons and transcripts. Novel insights inferred from the examined aspects of the cardiac transcriptome open ways to further experimental investigations. Our work provided a comprehensive set of methods to analyze mouse cardiac transcriptome complexity at individual exon and transcript levels. Applications of the methods may infer important new insights to gene regulation in normal and disease hearts in terms of exon utilization and potential involvement of novel components of cardiac transcriptome. Left ventricular tissues were collected from C57BL/6 mice after 1 week (hypertrophy stage, HY) and 8 weeks post trans-aortic constriction (TAC) procedure (heart failure stage, HF), respectively, and their corresponding Sham controls (Sham-HY, Sham-HF). To conduct RNA-Seq analysis, total RNAs from six TAC and Sham-operated mice at the HY stage and four TAC and corresponding Sham mice at the HF stage were obtained.

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