10 research outputs found

    Genomic analyses with biofilter 2.0: knowledge driven filtering, annotation, and model development

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    BACKGROUND: The ever-growing wealth of biological information available through multiple comprehensive database repositories can be leveraged for advanced analysis of data. We have now extensively revised and updated the multi-purpose software tool Biofilter that allows researchers to annotate and/or filter data as well as generate gene-gene interaction models based on existing biological knowledge. Biofilter now has the Library of Knowledge Integration (LOKI), for accessing and integrating existing comprehensive database information, including more flexibility for how ambiguity of gene identifiers are handled. We have also updated the way importance scores for interaction models are generated. In addition, Biofilter 2.0 now works with a range of types and formats of data, including single nucleotide polymorphism (SNP) identifiers, rare variant identifiers, base pair positions, gene symbols, genetic regions, and copy number variant (CNV) location information. RESULTS: Biofilter provides a convenient single interface for accessing multiple publicly available human genetic data sources that have been compiled in the supporting database of LOKI. Information within LOKI includes genomic locations of SNPs and genes, as well as known relationships among genes and proteins such as interaction pairs, pathways and ontological categories. Via Biofilter 2.0 researchers can: • Annotate genomic location or region based data, such as results from association studies, or CNV analyses, with relevant biological knowledge for deeper interpretation • Filter genomic location or region based data on biological criteria, such as filtering a series SNPs to retain only SNPs present in specific genes within specific pathways of interest • Generate Predictive Models for gene-gene, SNP-SNP, or CNV-CNV interactions based on biological information, with priority for models to be tested based on biological relevance, thus narrowing the search space and reducing multiple hypothesis-testing. CONCLUSIONS: Biofilter is a software tool that provides a flexible way to use the ever-expanding expert biological knowledge that exists to direct filtering, annotation, and complex predictive model development for elucidating the etiology of complex phenotypic outcomes

    Transcriptional activation of Jun and Fos members of the AP-1 complex is a conserved signature of immune aging that contributes to inflammaging.

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    Diverse mouse strains have different health and life spans, mimicking the diversity among humans. To capture conserved aging signatures, we studied long-lived C57BL/6J and short-lived NZO/HILtJ mouse strains by profiling transcriptomes and epigenomes of immune cells from peripheral blood and the spleen from young and old mice. Transcriptional activation of the AP-1 transcription factor complex, particularly Fos, Junb, and Jun genes, was the most significant and conserved aging signature across tissues and strains. ATAC-seq data analyses showed that the chromatin around these genes was more accessible with age and there were significantly more binding sites for these TFs with age across all studied tissues, targeting pro-inflammatory molecules including Il6. Age-related increases in binding sites of JUN and FOS factors were also conserved in human peripheral blood ATAC-seq data. Single-cell RNA-seq data from the mouse aging cell atlas Tabula Muris Senis showed that the expression of these genes increased with age in B, T, NK cells, and macrophages, with macrophages from old mice expressing these molecules more abundantly than other cells. Functional data showed that upon myeloid cell activation via poly(I:C), the levels of JUN protein and its binding activity increased more significantly in spleen cells from old compared to young mice. In addition, upon activation, old cells produced more IL6 compared to young cells. In sum, we showed that the aging-related transcriptional activation of Jun and Fos family members in AP-1 complex is conserved across immune tissues and long- and short-living mouse strains, possibly contributing to increased inflammation with age

    Global increases in both common and rare copy number load associated with autism.

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    Children with autism have an elevated frequency of large, rare copy number variants (CNVs). However, the global load of deletions or duplications, per se, and their size, location and relationship to clinical manifestations of autism have not been documented. We examined CNV data from 516 individuals with autism or typical development from the population-based Childhood Autism Risks from Genetics and Environment (CHARGE) study. We interrogated 120 regions flanked by segmental duplications (genomic hotspots) for events >50 kbp and the entire genomic backbone for variants >300 kbp using a custom targeted DNA microarray. This analysis was complemented by a separate study of five highly dynamic hotspots associated with autism or developmental delay syndromes, using a finely tiled array platform (>1 kbp) in 142 children matched for gender and ethnicity. In both studies, a significant increase in the number of base pairs of duplication, but not deletion, was associated with autism. Significantly elevated levels of CNV load remained after the removal of rare and likely pathogenic events. Further, the entire CNV load detected with the finely tiled array was contributed by common variants. The impact of this variation was assessed by examining the correlation of clinical outcomes with CNV load. The level of personal and social skills, measured by Vineland Adaptive Behavior Scales, negatively correlated (Spearman's r = -0.13, P = 0.034) with the duplication CNV load for the affected children; the strongest association was found for communication (P = 0.048) and socialization (P = 0.022) scores. We propose that CNV load, predominantly increased genomic base pairs of duplication, predisposes to autism

    Tris(1,3-dichloro-2-propyl)phosphate Induces Genome-Wide Hypomethylation within Early Zebrafish Embryos

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    Tris­(1,3-dichloro-2-propyl)­phosphate (TDCIPP) is a high-production volume organophosphate-based plasticizer and flame retardant widely used within the United States. Using zebrafish as a model, the objectives of this study were to determine whether (1) TDCIPP inhibits DNA methyltransferase (DNMT) within embryonic nuclear extracts; (2) uptake of TDCIPP from 0.75 h postfertilization (hpf, 2-cell) to 2 hpf (64-cell) or 6 hpf (shield stage) leads to impacts on the early embryonic DNA methylome; and (3) TDCIPP-induced impacts on cytosine methylation are localized to CpG islands within intergenic regions. Within this study, 5-azacytidine (5-azaC, a DNMT inhibitor) was used as a positive control. Although 5-azaC significantly inhibited zebrafish DNMT, TDCIPP did not affect DNMT activity <i>in vitro</i> at concentrations as high as 500 μM. However, rapid embryonic uptake of 5-azaC and TDCIPP from 0.75 to 2 hpf resulted in chemical- and chromosome-specific alterations in cytosine methylation at 2 hpf. Moreover, TDCIPP exposure predominantly resulted in hypomethylation of positions outside of CpG islands and within intragenic (exon) regions of the zebrafish genome. Overall, these findings provide the foundation for monitoring DNA methylation dynamics within zebrafish as well as identifying potential associations among TDCIPP exposure, adverse health outcomes, and DNA methylation status within human populations
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