Analysis of interactions between the epigenome and structural mutability of the genome using Genboree workbench tools

Coarfa, Cristian; Pichot, Christina S.; Jackson, Andrew; Tandon, Arpit; Amin, Viren; Raghuraman, Sriram; Paithankar, Sameer; Lee, Adrian V.; McGuire, Sean E.; Milosavljevic, Aleksandar

doi:10.1186/1471-2105-15-s7-s2

Cited by 16 publications

(16 citation statements)

References 91 publications

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“…The Epigenome Roadmap project contains mRNA-seq data from stem cells and primary ex vivo tissues selected to represent the normal counterparts of tissues and organ systems frequently involved in human disease. We used the Genboree Workbench 43 to analyze mRNA-seq expression data for the MFN2 region from 69 samples. As input, we provided a customized bed file of 10 bp intervals spanning the MFN2 region.…”

Section: In Silico Cross-tissue Analysismentioning

confidence: 99%

Integrative Multi-omic Analysis of Human Platelet eQTLs Reveals Alternative Start Site in Mitofusin 2

Simon

Chen

Edelstein

et al. 2016

The American Journal of Human Genetics

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Platelets play a central role in ischemic cardiovascular events. Cardiovascular disease (CVD) is a major cause of death worldwide. Numerous genome-wide association studies (GWASs) have identified loci associated with CVD risk. However, our understanding of how these variants contribute to disease is limited. Using data from the platelet RNA and expression 1 (PRAX1) study, we analyzed cis expression quantitative trait loci (eQTLs) in platelets from 154 normal human subjects. We confirmed these results in silico by performing allele-specific expression (ASE) analysis, which demonstrated that the allelic directionality of eQTLs and ASE patterns correlate significantly. Comparison of platelet eQTLs with data from the Genotype-Tissue Expression (GTEx) project revealed that a number of platelet eQTLs are platelet specific and that platelet eQTL peaks localize to the gene body at a higher rate than eQTLs from other tissues. Upon integration with data from previously published GWASs, we found that the trait-associated variant rs1474868 coincides with the eQTL peak for mitofusin 2 (MFN2). Additional experimental and computational analyses revealed that this eQTL is linked to an unannotated alternate MFN2 start site preferentially expressed in platelets. Integration of phenotype data from the PRAX1 study showed that MFN2 expression levels were significantly associated with platelet count. This study links the variant rs1474868 to a platelet-specific regulatory role for MFN2 and demonstrates the utility of integrating multi-omic data with eQTL analysis in disease-relevant tissues for interpreting GWAS results.

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Section: In Silico Cross-tissue Analysismentioning

confidence: 99%

Integrative Multi-omic Analysis of Human Platelet eQTLs Reveals Alternative Start Site in Mitofusin 2

Simon

Chen

Edelstein

et al. 2016

The American Journal of Human Genetics

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“…24 Regions of interest were mapped to enrichment data using the Genboree Workbench tool. 25 Values corresponding to histone enrichment in peripheral blood and brain tissue were averaged for all CpGs of a given region, and graphed based on the magnitude of relative enrichment using Excel (Microsoft).…”

Section: Discussionmentioning

confidence: 99%

“…Significant regions were annotated with available Roadmap Epigenomics enrichment data (Release 9) for seven histone modifications (H3K4me1, H3K4me3, H3K9me3, H3K27me3, H3K36me3, H3K9ac and H3K27ac) in six brain regions (the anterior caudate, cyngulate gyrus, middle hippocampus, inferior temporal lobe, mid frontal lobe, and substantia nigra) and two blood cell types (naïve CD4 and CD8 T cells) . Regions of interest were mapped to enrichment data using the Genboree Workbench tool . Values corresponding to histone enrichment in peripheral blood and brain tissue were averaged for all CpGs of a given region, and graphed based on the magnitude of relative enrichment using Excel (Microsoft).…”

Section: Methodsmentioning

confidence: 99%

Investigation of correlations between DNA methylation, suicidal behavior and aging

et al. 2017

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Objectives: Suicidal behavior (SB) is a major cause of mortality for patients diagnosed with bipolar disorder (BD). In this study, we investigated epigenetic differences in BD participants with and without a history of SB. Methods:We used suicidality scores constructed from Schedule for Clinical Assessments in Neuropsychiatry (SCAN) interview questions about suicidal thought and behavior to identify individuals from a BD cohort of n=452; participants with the most extreme high (H-SB, n=18) and most extreme low (L-SB, n=22) scores were used as cases and controls, respectively. Epigenome-wide DNA methylation patterns were compared between the two groups using the Illumina Infinium Human Methylation 450 BeadChip microarray. DNA methylation age was compared to chronological tissue age. Results:We observed highly significant differences in methylation between cases and controls in three genomic regions enriched for epigenetic modifications corresponding to gene regulatory regions. BD participants with a history of SB showed less overall methylation in the 5′ untranslated region of Membrane palmitoylated protein 4 (MPP4) (P=7.42×10 ), while exon 1 of Nucleoporin 133 (NUP133) was less methylated in controls (P=1.17x10 -6 ). Moreover, we observed a greater correlation between DNA methylation age and tissue age in controls (r=.91, P<.0001) than in the H-SB group (r=.83, P<.0001). Conclusions:We report significant findings at three loci based on a methylome scan of participants with BD for an SB phenotype, and potentially altered molecular aging in suicide attempters. Despite the small sample size, our proof-of-concept study highlights the potential for epigenetic factors to be useful in understanding the molecular underpinnings of suicide with the ultimate aim of its prevention. whereby predictive factors are described as proximal, such as substance use, mood disorders and adherence to treatment, and distal, such as a family history of SB and adverse childhood experiences.Suicidal ideation and completion have also been associated with

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“…Small RNA-seq data from EVs were processed using the Genboree Workbench 40,41,48 exceRpt pipeline 39 to assess content by: (1) First removing reads that map to UniVec contaminants, 45S, 5S and mitochondiral rRNAs; (2) mapping reads sequentially to human miRNAs (mirBase), tRNAs (gtRNAdb), piRNAs(piRNABank), GENCODE and circRNAs (cirBase); (3) mapping unmapped reads from (2) to exogenous miRNAs and rRNAs; (4) finally mapping unmapped reads from (3) to all genomes in ensembl and NCBI. Parameter settings and Genboree output files are available on Zenodo (see data availability).…”

Section: Evs Small Rna-seqmentioning

confidence: 99%

Longitudinal Saliva Omics Responses to Immune Perturbation: A Case Study

Mias

Singh

Rogers

et al. 2020

Preprint

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Saliva omics, a rapidly developing field for non-invasive diagnostics, may be utilized for monitoring very young or elderly populations, as well as individuals in remote locations. In this study, multiple saliva omics from an individual were monitored over 100 timepoints, over three periods involving: (i) hourly sampling over 24 hours without intervention, (ii) hourly sampling over 24 hours including immune system activation using the standard 23-valent pneumococcal polysaccharide vaccine, (iii) daily sampling for 33 days profiling the post-vaccination response. At each timepoint total saliva transcriptome and proteome were profiled, and salivary extracellular vesicles were derived, from which small-RNA sequencing was used to determine RNA, miRNA, piRNA and bacterial RNA components. The two 24-hour periods were used in a paired analysis to reveal vaccination responses. Temporal trends were classified and collective behavior revealed broad immune-responses captured in saliva, both at the innate as well as the adaptive response time frames. 1 Year Vaccination 24 hourly samples TFH2 24 hourly samples TFH1 P P S V 2 3 Results Samples and AssaysWe followed a single individual (m, 38, Caucasian), in general good health (has reported chronic sinusitis) over the span of a year. To observe whether the effects of perturbation can be profiled in saliva we carried out the profiling over 3 time frames. In the first 24 hr time frame (TFH1) we established a baseline, obtaining a saliva sample from the subject hourly without perturbation over his standard routine. In the second 24 hr time frame (TFH2), the subject was vaccinated with pneumococcal polysaccharide vaccine (PPSV23) within 3.5 hrs of waking up (at 10.30 am), while otherwise maintaining a similar routine as in the first period (including food intake and meal timing), and again saliva samples were taken hourly. We should note here that the subject reported fever ∼7.5 hours post the vaccination (between timepoints at 5 and 6 pm), lasting for about 4 hrs (10 pm). The two time periods, TFH1 and TFH2, were treated as paired and combined in the analysis below (TF∆) to identify changes induced by the vaccination, by effectively removing daily normal routine effects for this individual. Additionally, in the third time frame (TFD) we monitored the subject daily for over a month, pre-and post-vaccination to identify potential immune changes over both innate and adaptive time frames, Fig. 1.The daily samples were all taken at 8 am, to limit variability. Saliva was sampled both for downstream total RNA profiling, mass spectrometry proteomics, as well as for extraction of extracellular vesicles which were profiled for a variate of small RNA 2/19

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Analysis of interactions between the epigenome and structural mutability of the genome using Genboree workbench tools

Cited by 16 publications

References 91 publications

Integrative Multi-omic Analysis of Human Platelet eQTLs Reveals Alternative Start Site in Mitofusin 2

Integrative Multi-omic Analysis of Human Platelet eQTLs Reveals Alternative Start Site in Mitofusin 2

Investigation of correlations between DNA methylation, suicidal behavior and aging

Longitudinal Saliva Omics Responses to Immune Perturbation: A Case Study

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