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%% This BibTeX bibliography file was created using BibDesk.
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%% http://bibdesk.sourceforge.net/
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-%% Created for Ryan C. Thompson at 2016-05-03 16:44:49 -0700
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+%% Created for Ryan C. Thompson at 2016-06-10 07:30:41 -0700
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%% Saved with string encoding Unicode (UTF-8)
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+@article{lamere2016,
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+ Abstract = {The epigenetic determinants driving the responses of CD4 T cells to antigen are currently an area of active research. Much has been done to characterize helper T-cell subsets and their associated genome-wide epigenetic patterns. In contrast, little is known about the dynamics of histone modifications during CD4 T-cell activation and the differential kinetics of these epigenetic marks between naive and memory T cells. In this study, we have detailed the dynamics of genome-wide promoter H3K4me2 and H3K4me3 over a time course during activation of human naive and memory CD4 T cells. Our results demonstrate that changes to H3K4 methylation occur relatively late after activation (5 days) and reinforce activation-induced upregulation of gene expression, affecting multiple pathways important to T-cell activation, differentiation and function. The dynamics and mapped pathways of H3K4 methylation are distinctly different in memory cells, which have substantially more promoters marked by H3K4me3 alone, reinforcing their more differentiated state. Our study provides the first data examining genome-wide histone modification dynamics during CD4 T-cell activation, providing insight into the cross talk between H3K4 methylation and gene expression, and underscoring the impact of these marks upon key pathways integral to CD4 T-cell activation and function.Genes and Immunity advance online publication, 12 May 2016; doi:10.1038/gene.2016.19.},
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+ Author = {LaMere, S. A. and \textbf{Ryan C. Thompson} and Komori, H. K. and Mark, A. and Salomon, D. R.},
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+ Date-Added = {2016-06-10 14:29:31 +0000},
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+ Date-Modified = {2016-06-10 14:30:40 +0000},
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+ Journal = {Genes Immun.},
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+ Month = {May},
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+ Title = {{{P}romoter {H}3{K}4 methylation dynamically reinforces activation-induced pathways in human {C}{D}4 {T} cells}},
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+ Year = {2016}}
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+
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@article{globin-reduction,
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Author = {\textbf{Ryan C. Thompson} and Terri Gelbart and Steven R. Head and Phillip Ordoukhanian and Courtney Mullen and Dongmei Han and Dora M. Berman and Amelia Bartholomew and Norma S. Kenyon and Daniel R. Salomon},
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Date-Added = {2016-05-03 23:39:31 +0000},
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@@ -16,14 +26,6 @@
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Title = {Optimizing yield of deep {RNA} sequencing for gene expression profiling of peripheral blood samples from cynomolgus monkeys ({Macaca} fascicularis)},
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Year = {2016}}
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-@article{lamere2016,
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- Author = {Sarah A. LaMere and \textbf{Ryan C. Thompson} and H. Kiyomi Komori and Adam Mark and Daniel R. Salomon},
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- Date-Added = {2016-02-09 20:48:26 +0000},
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- Date-Modified = {2016-02-11 02:42:14 +0000},
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- Journal = {Genes and Immunity (accepted)},
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- Title = {Promoter {H3K4} methylation dynamically reinforces activation-induced pathways in human {CD4} {T} cells},
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- Year = {2016}}
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-
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@article{Scott036061,
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Abstract = {RNA-mediated oligonucleotide Annealing, Selection, and Ligation (RASL-seq) is a method to measure the expression of hundreds of genes in thousands of samples for a fraction of the cost of competing methods. However, enzymatic inefficiencies of the original protocol and the lack of open source software to design and analyze RASL-seq experiments have limited its widespread adoption. We recently reported an Rnl2-based RASL-seq protocol (RRASL-seq) that offers improved ligation efficiency and a probe decoy strategy to optimize sequencing usage. Here, we describe an open source software package, RASLseqTools, that provides computational methods to design and analyze RASL-seq experiments. Furthermore, using data from a large RRASL-seq experiment, we demonstrate how normalization methods can be used for characterizing and correcting experimental, sequencing, and alignment error. We provide evidence that the three principal predictors of RRASL-seq reproducibility are barcode/probe sequence dissimilarity, sequencing read depth, and normalization strategy. Using dozens of technical and biological replicates across multiple 384-well plates, we find simple normalization strategies yield similar results to more statistically complex methods.},
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Author = {Scott, Erick R. and Larman, H. Benjamin and Torkamani, Ali and Schork, Nicholas J. and Wineinger, Nathan and Nanis, Max and \textbf{Ryan C. Thompson} and Beheshti Zavareh, Reza B. and Lairson, Luke L. and Schultz, Peter G. and Su, Andrew I.},
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