PAG XXI, 2013 - DNA methylation as a source of epigenetic regulation in the Pacific oysters

<p>Presented at the Aquaculture Workshop at PAG XXI, San Deigo CA 2013.</p> <p>This material is based upon work supported by the National Science Foundation under Grant Number 1158119.</p> <p>Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.</p

Facilitating analysis of genomic variation in Olympia oysters

<p>This dataset includes genomic intervals (BED format) to facilitate RADSeq design and functional annotation of SNPs in Olympia oysters (<em>Ostrea lurida</em>). </p> <p>The files include a transcriptome (FASTA format) and the following 8 genomic interval files (BED format):</p> <p><strong>Oly_snps_bed:</strong> location of SNPs with variant annotated in the name column<br><strong>Oly_geneID_bed:</strong> these intervals cover the entire length of the transcript and are annoated with the SwissProt ID in the name column<br><strong>Oly_regionofblasthits_bed:</strong> these intervals cover only the region of homology between the subject and query for the blastx output<br><strong>Oly_inducible_bed:</strong> these intervals cover the entire length of the transcript for those genes associated with the following GOSlim IDs: <em>cell-cell signaling, signal transduction, cell adhesion, development, stress response</em><br><strong>Oly_housekeeping_bed:</strong> these intervals cover the entire length of the transcript for those genes associated with the following GOSlim IDs: <em>DNA metabolism, RNA metabolism, protein metabolism</em><br><strong>Oly_EcoRIsites_bed:</strong> location of EcoRI restriction sites<br><strong>Oly_NotIsites_bed:</strong> location of NotI restriction sites<br><strong>Oly_SbfI_bed:</strong> location of SbfI restriction sites</p> <p>This dataset was generated as part of the requirements for FISH 546: Bioinformatics for Environmental Science.  The slides for the final presentation are included (FISH546.pdf)</p> <p>The original data for the transcriptome, blastx annotations and SNP tables can be found here:<br>Transcriptome characterization of the Olympia oyster and pinto abalone. Steven Roberts, Emma Timmins-Schiffman. figshare.<br>http://dx.doi.org/10.6084/m9.figshare.156431. Retrieved 18:14, Mar 18, 2013 (GMT)</p> <p> </p

Qualifying Exam

<p>This dataset is the product of my qualifying exams.</p> <p>The questions cover a range of topics including epigenetics and the host pathogen relationship, reproductive biology of oysters, estrogen signalling and understanding effects of various enviromental stresses on shellfish.  </p> <p>This document was prepared over (a nervewracking) 5 days, includes personal opinions, and is unedited - so pardon the typos.</p

Crassostrea gigas high-throughput bisulfite sequencing (gill tissue)

<p>This fileset contains genomic feature tracks from methylation-enriched high-throughput bisulfite sequencing and RNA-seq analysis for Pacific oyster (<em>Crassostrea gigas</em>) gill tissue. Feature tracks were developed to be viewed with Integrative Genomics Viewer (http://www.broadinstitute.org/igv/) in conjunction with the <em>C. gigas</em> genome (Fang et al. 2012). All data and instructions are also available at http://oystergen.es/bigill.</p> <p>File descriptions:</p> <p><em>BiGill_CpG_methylation.igv</em> - Location and proportion of methylation for all analyzed CpG dinucleotides with greater than 5x coverage.</p> <p><em>BiGill_exon_clc_rpkm.igv</em> - Exon-specific gene expression values (RPKM) from RNA-seq analysis.</p> <p><em>BiGill_igv_charlie.xml</em> - A session file, which loads methylation and RNA-seq feature tracks as well as the location of C.gigas genome features.</p> <p><em>Query to derive_CG_AllData_IGV.txt</em> - Query (SQLShare) used to derive the methylation feature track from the original methratio output (http://goo.gl/5LGq9Q)</p> <p>Reference:</p> <p>Fang X, Li L, Luo R, Xu F, Wang X, Zhu Y, Yang L, Huang Z. 2012. Genomic data from the Pacific oyster (<em>Crassostrea gigas</em>). GigaScience. http://dx.doi.org/10.5524/100030.</p

Preprint: A context specific role for DNA methylation in bivalves

<p>An unrefereed manuscript version of an article, as submitted for review to the journal <em>Briefings in Functional Genomics</em>. </p> <p>The manuscript was revised and later accepted for publication. </p> <p>A link to the final draft of the manuscript will be made available once published.</p> <p><br></p

Nanostring

<p>This dataset contains the raw data and summary documention of a collaboration between M. Gavery and SR Roberts and Nanostring Inc. to evaluate DNA methylation in Pacific oysters using Nanostring's nCounter technology</p

DNA methylation coverage in two tissues of the Pacific Oyster

<p>This work aims at characterizing and comparing DNA methylation in two tissues in the Pacific oyster using the methylKit R package. Bisulfite sequencing was used to examine genome-wide DNA methylation in the oyster gonad tissue and MBD-Seq was used to examine methylation in the gill tissue.  The R script used for these analyses has been provided along with some visualization outputs comparing gill and gonad tissue from the Pacific oyster.  </p> <p> </p

qPCR corroboration of an RNA-Seq experiment

<p>This fileset includes data on qPCR corroboration of an RNA-Seq experiment published in Comparative Biochemistry and Physiology Part D: Genomics and Proteomics:<em> Characterizing short read sequencing for gene discovery and RNA-Seq analysis in Crassostrea gigas</em> (Gavery & Roberts 2012). In this study we wanted to investigate how qPCR technology using individuals corroborated with RNA-seq analysis of pooled individuals. Overall, two general trends were observed. First, directionality of expression was congruent for a majority of the assayed genes. For those targets that were not in agreement, the difference in expression between the samples was within 2 fold. This observation is consistent with previous studies examining the correlation between RNA-seq and qPCR (e.g. Marioni et al., 2008, Beane et al., 2011). Second, the fold difference between samples was generally larger by RNA-seq analysis. For example, for all 4 genes determined to be significantly different by both analyses (DPGN, GSPA, GP17A and HMG2) the fold difference was larger for the RNA-seq analysis than for qPCR. Previous studies have also indicated that RNA-seq analysis reports larger fold differences than qPCR or microarray analysis (Hoen et al., 2008). The genes identified as not significantly different (CALL, GNRR2 and TIMP3) using RNA-seq had the lowest number of mapped reads. Aside from these general trends, there were differences observed between between these orthologous methods. There could be multiple explanations for these discrepancies, which are described.</p

DNA Methylation Patterns in Crassostrea gigas

<p>Poster presented at the NSA conference in Nashville in 2013.  This research uses the Pacific Oyster as a model organism to characterize the distribution and identify potential functions of DNA methylation.  We examined genome-wide methylation patterns to elucidate the mechanisms by which DNA methylation impacts transcriptional processes.</p> <p>___________________________________________</p> <p>This material is based upon work supported by the National Science Foundation under Grant Number 1158119.</p> <p>Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.</p