6 research outputs found
Genomic structural variations lead to dysregulation of important coding and non-coding RNA species in dilated cardiomyopathy
The transcriptome needs to be tightly regulated by mechanisms that include transcription factors, enhancers, and repressors as well as non-coding RNAs. Besides this dynamic regulation, a large part of phenotypic variability of eukaryotes is expressed through changes in gene transcription caused by genetic variation. In this study, we evaluate genome-wide structural genomic variants (SVs) and their association with gene expression in the human heart. We detected 3,898 individual SVs affecting all classes of gene transcripts (e.g., mRNA, miRNA, lncRNA) and regulatory genomic regions (e.g., enhancer or TFBS). In a cohort of patients (n = 50) with dilated cardiomyopathy (DCM), 80,635 non-protein-coding elements of the genome are deleted or duplicated by SVs, containing 3,758 long non-coding RNAs and 1,756 protein-coding transcripts. 65.3% of the SV-eQTLs do not harbor a significant SNV-eQTL, and for the regions with both classes of association, we find similar effect sizes. In case of deleted protein-coding exons, we find downregulation of the associated transcripts, duplication events, however, do not show significant changes over all events. In summary, we are first to describe the genomic variability associated with SVs in heart failure due to DCM and dissect their impact on the transcriptome. Overall, SVs explain up to 7.5% of the variation of cardiac gene expression, underlining the importance to study human myocardial gene expression in the context of the individual genome. This has immediate implications for studies on basic mechanisms of cardiac maladaptation, biomarkers, and (gene) therapeutic studies alike
Influence of Next-Generation Sequencing and Storage Conditions on miRNA Patterns Generated from PAXgene Blood
Whole
blood derived miRNA signatures determined by Next-Generation
Sequencing (NGS) offer themselves as future minimally invasive biomarkers
for various human diseases. The PAXgene system is a commonly used
blood storage system for miRNA analysis. Central to all miRNA analyses
that aim to identify disease specific miRNA signatures, is the question
of stability and variability of the miRNA profiles that are generated
by NGS. We characterized the influence of five different conditions
on the genome wide miRNA expression pattern of human blood isolated
in PAXgene RNA tubes. In detail, we analyzed 15 miRNomes from three
individuals. The blood was subjected to different numbers of freeze/thaw
cycles and analyzed for the influence of storage at â80 or
8 °C. We also determined the influence of blood collection and
NGS preparations on the miRNA pattern isolated from a single individual,
which has been sequenced 10 times. Here, five PAXGene tubes were consecutively
collected that have been split in two replicates, representing two
experimental batches. All samples were analyzed by Illumina NGS. For
each sample, approximately 20 million NGS reads have been generated.
Hierarchical clustering and Principal Component Analysis (PCA) showed
an influence of the different conditions on the miRNA patterns. The
effects of the different conditions on miRNA abundance are, however,
smaller than the differences that are due to interindividual variability.
We also found evidence for an influence of the NGS measurement on
the miRNA pattern. Specifically, hsa-miR-1271-5p and hsa-miR-182-5p
showed coefficients of variation above 100% indicating a strong influence
of the NGS protocol on the abundance of these miRNAs
Influence of Next-Generation Sequencing and Storage Conditions on miRNA Patterns Generated from PAXgene Blood
Whole
blood derived miRNA signatures determined by Next-Generation
Sequencing (NGS) offer themselves as future minimally invasive biomarkers
for various human diseases. The PAXgene system is a commonly used
blood storage system for miRNA analysis. Central to all miRNA analyses
that aim to identify disease specific miRNA signatures, is the question
of stability and variability of the miRNA profiles that are generated
by NGS. We characterized the influence of five different conditions
on the genome wide miRNA expression pattern of human blood isolated
in PAXgene RNA tubes. In detail, we analyzed 15 miRNomes from three
individuals. The blood was subjected to different numbers of freeze/thaw
cycles and analyzed for the influence of storage at â80 or
8 °C. We also determined the influence of blood collection and
NGS preparations on the miRNA pattern isolated from a single individual,
which has been sequenced 10 times. Here, five PAXGene tubes were consecutively
collected that have been split in two replicates, representing two
experimental batches. All samples were analyzed by Illumina NGS. For
each sample, approximately 20 million NGS reads have been generated.
Hierarchical clustering and Principal Component Analysis (PCA) showed
an influence of the different conditions on the miRNA patterns. The
effects of the different conditions on miRNA abundance are, however,
smaller than the differences that are due to interindividual variability.
We also found evidence for an influence of the NGS measurement on
the miRNA pattern. Specifically, hsa-miR-1271-5p and hsa-miR-182-5p
showed coefficients of variation above 100% indicating a strong influence
of the NGS protocol on the abundance of these miRNAs
Genomic structural variations lead to dysregulation of important coding and nonâcoding RNA species in dilated cardiomyopathy
Abstract The transcriptome needs to be tightly regulated by mechanisms that include transcription factors, enhancers, and repressors as well as nonâcoding RNAs. Besides this dynamic regulation, a large part of phenotypic variability of eukaryotes is expressed through changes in gene transcription caused by genetic variation. In this study, we evaluate genomeâwide structural genomic variants (SVs) and their association with gene expression in the human heart. We detected 3,898 individual SVs affecting all classes of gene transcripts (e.g., mRNA, miRNA, lncRNA) and regulatory genomic regions (e.g., enhancer or TFBS). In a cohort of patients (n = 50) with dilated cardiomyopathy (DCM), 80,635 nonâproteinâcoding elements of the genome are deleted or duplicated by SVs, containing 3,758 long nonâcoding RNAs and 1,756 proteinâcoding transcripts. 65.3% of the SVâeQTLs do not harbor a significant SNVâeQTL, and for the regions with both classes of association, we find similar effect sizes. In case of deleted proteinâcoding exons, we find downregulation of the associated transcripts, duplication events, however, do not show significant changes over all events. In summary, we are first to describe the genomic variability associated with SVs in heart failure due to DCM and dissect their impact on the transcriptome. Overall, SVs explain up to 7.5% of the variation of cardiac gene expression, underlining the importance to study human myocardial gene expression in the context of the individual genome. This has immediate implications for studies on basic mechanisms of cardiac maladaptation, biomarkers, and (gene) therapeutic studies alike