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Abstract
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@@ -769,16 +782,41 @@ Do not include graphs, charts, tables, or illustrations in your abstract.
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\begin_layout Standard
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+Transplant rejection mediated by adaptive immune response is the major challenge
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+ to long-term graft survival.
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+ Rejection is treated with immune suppressive drugs, but early diagnosis
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+ is essential for effective treatment.
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+ Memory lymphocytes are known to resist immune suppression, but the precise
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+ regulatory mechanisms underlying immune memory are still poorly understood.
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+ High-throughput genomic assays like microarrays, RNA-seq, and ChIP-seq
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+ are heavily used in the study of immunology and transplant rejection.
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+ Here we present 3 analyses of such assays in this context.
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+ First, we re-analyze a large data set consisting of H3K4me2, H3K4me3, and
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+ H3K27me3 ChIP-seq data and RNA-seq data in naïve and memory CD4 T-cells
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+ using modern bioinformatics methods designed to address deficiencies in
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+ the data and extend the analysis in several new directions.
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+ All 3 histone marks are found to occur in broad regions and are enriched
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+ near promoters, but the radius of promoter enrichment is found to be larger
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+ for H3K27me3.
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+ We observe that both gene expression and promoter histone methylation in
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+ naïve and memory cells converges on a common signature 14 days after activation
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+, consistent with differentiation of naïve cells into memory cells.
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+ The location of histone modifications within the promoter is also found
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+ to be important, with asymmetric associations with gene expression for
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+ peaks located the same distance up- or downstream of the TSS.
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+ Second, we demonstrate the effectiveness of fRMA as a single-channel normalizat
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+ion for using expression arrays to diagnost transplant rejection in a clinical
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+ diagnostic setting, and we develop a custom fRMA normalization for a previously
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+ unsupported array platform.
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+ For methylation arrays, we adapt methods designed for RNA-seq to improve
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+ the sensitivity of differential methylation analysis by modeling the heterosked
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+asticity inherent in the data.
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+ Finally, we present and validate a novel method for RNA-seq of cynomolgus
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+ monkey blood samples using complementary oligonucleotides to prevent wasteful
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+ over-sequencing of globin genes.
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+ These results all demonstrate the usefulness of a toolbox full of flexible
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+ and modular analysis methods in analyzing complex high-throughput assays
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+ in contexts ranging from basic science to translational medicine.
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\end_layout
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\begin_layout Standard
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