Author Archives: Morgan Eisenlord

Wnt Signaling KEGG Pathway

Below is the the KEGG pathway for the Wnt Signaling Pathway in purple sea urchins (green). I have added all the contegs found significantly enriched in the Pycnopodia  transcriptome. They are in the red and blue boxes. The numbers after each term show the log fold change (red = negative, blue = positive). between the animals with clinical signs and those without. I have not looked through the other annotated genes yet for to see if there are more relating to the wnt signaling pathway there.

Echinoderm_WntPathway_KEGG_SS

Here is my working copy of the gene list I am working from. I have not added all my references in yet but have UniProt information and some of the references included.

Contigs_Wnt_8-20-14

 

Where can a naked armadillo and a dishevelled porcupine be found?

The Wnt pathway! http://web.stanford.edu/group/nusselab/cgi-bin/wnt/reporters. Play the video to see a baby Zebrafish expressing Tcf/Lef-miniP:dGFP.

My post today will be covering the weekend as well as today, so it will be appropriately long. The last few days have been quite busy as we work through all the sea star transcriptome data and got to participate in the RCN meeting on Marine Infectious diseases. It was an honor meet so many scientists focused on disease ecology and to hear many great talks over the weekend.

I have struggling with posting every day since I like to have a complete story to tell when I write, however, looking back at my posts and those of my classmates I can see what a great tool it will be moving forward. This is something I will be working on in the future to incorporate into my daily note taking. It is different to post with an audience in mind, but good I think. My work is always better when I need to explain it to someone else and that is how this feels, just more permanent.

The last few days I have focused on the significantly enriched sea star genes falling within the “adhesion” biological function category. I took a subset of the genes, and Reyn and Ruth looked at the other. For my set, I went through each one and looked up the function of the protein it encoded and other proteins associated with it. It was difficult to find papers focusing on echinoderms for all of the genes, but for the ones that could find them for I did. I noted if the gene was higher of lower expressed in the control vs. experimental animals, what the value of the log change was, and what the p-value was.

Clear grouping of gene functions started to turn up right away. There were several genes involved in the extracellular matrix and another set in mutable collagenous tissue. Here is the list of genes I looked at with notes on the reference relating to them and a summery of their function taken from UniProt: Adhesion-ME References listed

After going through the list I grouped the genes based on function (highlighted in the doc) and started looking up papers based on the potential interacting pathways. While the Wnt pathway was not well represented in my list I had many genes that were regulated by it so started searching for the related Wnt genes in the lists of immune and cytokine genes. In the diseased animals there is a general lowering of expression relative to the controls in Wnt and Frizzled, and an increased expression of genes associated with the Adherin Junctions (cell-cell adhesion). The Wnt/beta-Catenin pathway regulates the extracellular matrix through activation of beta-Catenin, but is also involved in mutable collagenous tissue through beta-Catenin mediated integrin signaling. The disruption of the Wnt/beta-Catenin pathway is associated with disease in vertebrates. A disruption of this pathway is seen in many types of cancer. It is well characterized in echinoderms due to the sea urchin genome. I then compared the list of genes I had hand curated to the genes discussed in Croce_2006_EvolutionConservedWntPathways_SeaUrchin. Since this paper describes only the genes found and characterized in the sea star genome there is more confidence that these are coding for a protein in the Wnt/beta-Catenin pathway. My next step was to search all the significant enriched genes on the list against those mentioned in Croce et al 2006.

So…what is going on in our challenge experiment Pycnopodias? The table below contains the list that I have evaluated and placed as a likely part of the wnt pathway or linked to through the literature. I have started to map them onto a pathway (human) of the wnt/beta-catenin pathway. I will wait until that is more complete before uploading it. There are several more wnt genes found in the immune category that I have yet to look at in relation to the ones I have here to see where they fit. A few of the ones here (the 2 spondins in particulare) have literature on them but I have not determined if it is relevant to echinoderms. This list does not reflect the interactions but the one I will post tomorrow will.

log2FoldChange pvalue ID Protein names Broad Group Found in Croce et al 2006?
6.69463 8.14E-21 Q8IUX8 Epidermal growth factor-like protein 6 Adhesion no
5.569046 3.87E-17 Q9BUD6 Spondin-2 Adhesion no
4.483540943 1.79E-06 Q9QYP1 Low-density lipoprotein receptor-related protein 4 Immune no
3.07154 6.60E-09 Q00651 Integrin alpha-4 Adhesion no
2.939162 4.26E-06 Q9Y2D8 Afadin- and alpha-actinin-binding protein (ADIP) Adhesion no
2.638696126 2.61E-10 Q99N43 Kremen protein 1 Immune yes
2.612389 0.00782 Q90W79 Contactin-5 Adhesion no
2.178693 7.64E-04 Q9C0A0 Contactin-associated protein-like 4 Adhesion no
2.147782 4.10E-03 Q5RD64 Contactin-associated protein-like 2 Adhesion no
1.801941 1.07E-03 Q4JIM4 Presenilin-1 Adhesion no
1.539407 0.001994 O14522 Receptor-type tyrosine-protein phosphatase T Adhesion no
1.467166 0.000402 P35223 Catenin beta Adhesion yes
1.226512 4.60E-03 O94985 Calsyntenin-1 Adhesion no
-1.41984295 0.006131503 Q8NCW0 Kremen protein 2 Immune Yes
-1.930118114 0.003009238 Q6FHJ7 Secreted frizzled-related protein 4 Immune yes
-2.262594994 0.001609021 Q5BL72 Frizzled-7 Immune yes
-2.41329 6.24E-07 Q9HCB6 Spondin-1 Adhesion no
-3.66822 5.43E-07 Q9VBW3 Tyrosine kinase receptor Cad96Ca Adhesion no

Clevers_2006_WntBetaCateninSigDisease covers wnt/beta-catenin signaling involvement in human disease. Deregulation of the system leads to cancers in many cases. Another paper on inhibitors and activators is particularly interesting since it several of the genes I have identified are inhibitors (Cruciat_2013_WntInhibitors&Activators).

After completing the analysis of the wnt gene I will look at the adhesion set of genes. The two are linked so there will be overlap in the interacting proteins. The first step in looking at this (as with the last set) will be to find as many of my significantly enriched genes as I can that are associated with echinoderms. The echinoderm adhesome is described here: Whittaker_2006_TheEchinodermAdhesome.

The last step is to merge to the two sets of interacting proteins that I am most confident in (from the echinoderm literature) so the connections between them become clearer. After that I will add the genes annotated to other organisms to fill in where they fit.

 

 

Pisaster Survivorship update, Summer 2014, San Juan Islands

An update on my non-class related research, but very relevant to the work we are doing on the sea star transcriptome.

The tides were low last week so the sea star survey team went out to get the end of summer surveys done in the intertidal. We finished surveys at 11 of our 12 intertidal sites. Thanks to Mo Turner, Bella Bledsoe, Zula Mucyo, and Robyn Roberts for working hard in the field last week to make sure we got the data. You guys are the best field team ever! There will be one more set of surveys at a subset of the sites at the beginning of September, then the tides are not low again during the day until next spring, so this was a critical tide to cover.  I really missed going out in the field this last time since there was so much change happening.

Here is the latest graphs, courtesy of Mo Turner. Stars considered healthy only if they displayed no signs on tissue degradation or lesions. The graphs are copied below but please open the power point to see them in more detail.

Pisaster Survivorship

Survivorship

Population includes all the symptomatic, non-symptomatic, and dead individuals that we  surveyed for disease prevalence, while the graph above only includes the non-symptomatic individuals.

Population

I will now start looking at the prevalence data in depth to try to understand what the conditions for an outbreak are and why the timing differed between regions and sites. I will be looking at relationships between sites off the islands that have been repeatedly surveyed as well. The big question is how will this look in the spring. Hopefully we can use this to better understand the disease as the focus shifts to recovery in the coming years.

 

 

 

 

Oysters, clams, and mussels, oh my!

Yesterday I got the results back from the qPCR that I sent out at the start of the class. This was a very interesting set of samples. It included clams from several sites with sea star wasting disease and a set of oysters exposed to sick sea stars in the lab. It is similar to the experiment looking at bivalve filtering with the eelgrass and laby. The results are below and I will discus them tomorrow morning with the group.

Bivalve Graphs (8-12-14_ME_Updated)

Today I got continued looking up the genes which I have been finding associated with echinoderm immunity and healing in the literature. I have been working back from the papers, looking the gene up in the DEG’s instead of the other way around. I have been making notes on the excel file and will post it when I get enough done.

I worked through the whole enrichment analysis today from RNAseq to data visualization. It was really fun and I go it all to work! It was really great to have Lauren’s workflow posted so I could check through it when I got stuck. I will post my IPython notebook tomorrow since when I let the lab maxine had not refreshed yet. I have downloaded Anaconda so the I can start working on IPython on my won computer.

Allison and I got our week 3 video done! She will be posting it in her notebook. Check it out!

Interesting papers!

Today I have been researching the genes involved in the innate immune response in echinoderms as well as markers of pathogen infection. I have been going through the interesting genes individually and also looking into the literature. Here are some interesting papers that have come up so far.

A review on using next gen sequencing to find viruses in insects:

Sijun_etal_Viruses2011_NextGenerationSequencingInsectVirusDiscovery

Also, this great chapter on echinoderm immunity:

14Soderhall_Smith_

 

 

 

This mornings post is an summery of the work I did on Friday and finished up over the weekend. There was a lot of coding and great visualizations! Lauren gave us a WGCNA tutorial. Below is the R code.

source(“http://bioconductor.org/biocLite.R”)
biocLite(“impute”)
install.packages(“WGCNA”)

library(WGCNA);
# The following setting is important, do not omit.
options(stringsAsFactors = FALSE);
#Read in the female liver data set
SSData = read.csv(“Phel_rnaseq_normalized_expression.csv”);
# Take a quick look at what is in the data set:
dim(SSData);
names(SSData);

datExpr0 = as.data.frame(t(SSData

));
names(datExpr0) = SSData$Contig;
rownames(datExpr0) = names(SSData)

;
datExpr0

datExpr=datExpr0

gsg = goodSamplesGenes(datExpr0, verbose = 3);
gsg$allOK
collectGarbage();

powers = c(c(1:10), seq(from = 12, to=20, by=2))
# Call the network topology analysis function
sft = pickSoftThreshold(datExpr, powerVector = powers, verbose = 5)
# Plot the results:
sizeGrWindow(9, 5)
par(mfrow = c(1,2));
cex1 = 0.9;
# Scale-free topology fit index as a function of the soft-thresholding power
plot(sft$fitIndices[,1], -sign(sft$fitIndices[,3])*sft$fitIndices[,2],
xlab=”Soft Threshold (power)”,ylab=”Scale Free Topology Model Fit,signed R^2″,type=”n”,
main = paste(“Scale independence”));
text(sft$fitIndices[,1], -sign(sft$fitIndices[,3])*sft$fitIndices[,2],
labels=powers,cex=cex1,col=”red”);
# this line corresponds to using an R^2 cut-off of h
abline(h=0.90,col=”red”)
# Mean connectivity as a function of the soft-thresholding power
plot(sft$fitIndices[,1], sft$fitIndices[,5],
xlab=”Soft Threshold (power)”,ylab=”Mean Connectivity”, type=”n”,
main = paste(“Mean connectivity”))
text(sft$fitIndices[,1], sft$fitIndices[,5], labels=powers, cex=cex1,col=”red”)

net = blockwiseModules(datExpr, power = 10,
TOMType = “unsigned”, minModuleSize = 9,
reassignThreshold = 0, mergeCutHeight = 0.25,
numericLabels = TRUE, pamRespectsDendro = FALSE,
saveTOMs = TRUE,
saveTOMFileBase = “femaleMouseTOM”,
verbose = 3)

sizeGrWindow(12, 9)
# Convert labels to colors for plotting
mergedColors = labels2colors(net$colors)
# Plot the dendrogram and the module colors underneath
plotDendroAndColors(net$dendrograms[[1]], mergedColors[net$blockGenes[[1]]],
“Module colors”,
dendroLabels = FALSE, hang = 0.03,
addGuide = TRUE, guideHang = 0.05)

After that we worked on finding DEG’s that were interesting and categorizing them based on function for those with a high fold number. Overall, just continuing to sort out what is happening in the massive immune response the exposed animals display.

How to enter IPython Notebooks to WordPress

1. Open my notebook in the mirrored maxine

2. Copy the URL of the notebook into http://nbviewer.ipython.org/

3. Now, copy the nbviewer URL for the notebook into the quotes in the code below and add to the post.

[iframe src="http://owl.fish.washington.edu/lilmax/diseases/Morgan/EnrichedProcesses.txt" width="100%" same_height_as="window" scrolling="yes"]

Sea Star Immune Response

Some pretty pictures from today. These are showing the genes differentially expressed in the exposed vs. the non-exposed sea stars. The immune response is lighting up clearly. After making this I worked on coding to get through the enrichment but had to stop when SQLShare stopped working, likely due to all the pressure our class was putting on it running these huge files!

I worked on finding the literature on sea star immunity and the genes involved in regulating echinoderm structural integrity, as well as some of the genes identified top hits today.

We heard great talks from Reyn, Ruth, Rachel and Cody tonight. Really interesting stuff!

I have a theory that the pathogen is disrupting the mutable collagenous tissues (MCT) somehow. Interested in getting the groups thoughts on this. In Lauren’s top ten down regulated and up regulated genes there are several involved in MCT and extracellular matrix: Heparanase, Collagenase 3 (MMP-13!), Fibropellin-3, and Myocilin. MCT is involved especially exciting to see on here as it is involved in the tensile function of the stars. limb loss, and regeneration. Below is the PhD and published paper of a researcher who did a lot of work on MCT in echinoderms.

 

Ribeiro_etal_2012PLOS_Ecinoderms_MutableCollagenousTissue

Ribeiro_PhDThesis_UniversidadedoPorto2011_EcinodermMutableCollagenousTissues

Hillier_etal_Genomics2007_OlfactomedinProteinsUrchins

Now, I know these two are about vertebrates but bear with me. Take a look at the cellular mechanisms involved and the pathogen connection. It is pretty cool.

Cardiovasc Res-2006-Rutschow-646-56-1

Cardiovasc Res-2002-Li-235-47

Another interesting gene is Cytochrome P450 monooxygenase. Sure there is something newer on this but still a good paper. This one has xenobiotic functions and is lower in the exposed animals.

Cytochrome P450 monooxygenase system in echinoderms

Here are a few more interesting papers on echinoderm ceolomocytes.

Sharlaimove_etal.CellTissueRes_2014_StarfishCoelomicCells

Franco_etal_Proteomics2011_ProteomeSeaStarCoelomocytes

Revigo figures from today! These are from the differentially expresed genes in the sea star Look at the bright red dot showing up for immune response.

Revigo figures from today! These are from the differentially expressed genes in the sea star Look at the bright red dot showing up for immune response.

Screen Shot 2014-08-07 at 10.31.54 PM