Outreach event with Maritime High School Nov 12 2024

Today we hosted an outreach event with Maritime High School! We hosted ~35 students for several activities. Here is a quick overview of the activities that we did in the lab. We split the students into two groups since it was a large group.

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PolyIC Immune Priming Protocols

This post describes previous protocols for PolyIC immune priming in oysters using emmersion/bath methods. We will use these protocols to design PolyIC exposure in oysters at Point Whitney.

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Sequence depth subsampling test with Mcap2020 ITS2 dataset

This post details test for subsampling thresholds in the Montipora capitata early life history timeseries dataset. The purpose of these tests is to determine the minimum read depth to detect differences between treatment groups for future sequencing runs.

Prepare data

Load metadata.

#create metadata and load
Metadata<-read.csv("Mcap2020/Data/ITS2/ITS2_Metadata.csv")
rownames(Metadata) <- Metadata$sample_name
Metadata <- Metadata %>%
  select(code, hpf, group, lifestage)
Metadata <- as.matrix(Metadata)
Metadata <- sample_data(data.frame(Metadata))

Load profile level data.

#load data for taxonomy
tax0 <- read_tsv(
  file  = "Mcap2020/Data/ITS2/mcap.profiles.absolute.abund_and_meta.txt",
  n_max = 6) %>%
  dplyr::select(-2) %>% 
  gather(UID, value, -1) %>% 
  spread(1, value) %>%
  clean_names()

tax1 <- as.matrix(tax0[, -1], dimnames = list(tax0$uid, colnames(tax0[-1])))
rownames(tax1) <- tax0$uid
tax <- tax_table(tax1)

#load data for count matrix 
otu0 <- read_tsv(
  file  = "Mcap2020/Data/ITS2/mcap.profiles.absolute.abund_and_meta.txt", col_names = TRUE) 

list<-c("UID", "sample_name", "8", "9")
colnames(otu0)<-list

otu0<-otu0%>%
  select(-1) %>%
  dplyr::slice(7:n()) %>%
  mutate_at(2:ncol(.), as.numeric)

otu1 <- as.matrix(otu0[, -1])
rownames(otu1) <- otu0$sample_name
otu <- otu_table(otu1, taxa_are_rows = FALSE)

#combine to phyloseq object
coral <- phyloseq(otu, tax, Metadata)
coral

Note that taxa 8 is Clade C and taxa 9 is Clade D.

Next load the data for coral strain level information.

#gather the taxonomy names  
taxnames <- read_tsv(
  file  = "Mcap2020/Data/ITS2/mcap.seqs.absolute.abund_only.txt",
  n_max = 0) %>%
  select(-1) %>%
  names(.)

#extract clade letter  
tax0 <- data_frame(
  DIV = taxnames,
  clade = str_extract(DIV, "[A-Z]")
)

tax1 <- as.matrix(tax0)
rownames(tax1) <- tax0$DIV
tax <- tax_table(tax1)

otu0 <- read_tsv(
  file  = "Mcap2020/Data/ITS2/mcap.seqs.absolute.abund_and_meta.txt") %>%
  select(-1, )

otu1 <- as.matrix(otu0[, 37:113])
rownames(otu1) <- otu0$sample_name
otu <- otu_table(otu1, taxa_are_rows = FALSE)

coralDIV <- phyloseq(otu, tax, Metadata)
coralDIV

Now save the object.

save(coral, coralDIV, file = "Mcap2020/Data/ITS2/ITS2_phyloseq.RData")

Build DIV Data

Load the data.

load("Mcap2020/Data/ITS2/ITS2_phyloseq.RData")
coralDIV

View the number of sequence counts in our dataset.

Samps<-read_tsv(file  = "Mcap2020/Data/ITS2/mcap.seqs.absolute.abund_and_meta.txt")

hist(Samps$post_taxa_id_absolute_symbiodiniaceae_seqs, breaks=30)

Samps$post_taxa_id_absolute_symbiodiniaceae_seqs

We have >10,551 sequences for all of our samples.

Generate tree.

random_tree = rtree(ntaxa(coralDIV), rooted=TRUE, tip.label=taxa_names(coralDIV))

Merge phyloseq data.

phylo_coral_DIV = merge_phyloseq(coralDIV, Metadata, random_tree)
phylo_coral_DIV

Filter out samples with low numbers in groups (n=1 per group) from phyloseq object.

phylo_coral_DIV<-ps_filter(phylo_coral_DIV, lifestage != "Metamorphosed Polyp (183 hpf)")
phylo_coral_DIV<-ps_arrange(phylo_coral_DIV, lifestage)

Reorder lifestage.

levels(as.factor(sample_data(phylo_coral_DIV)$lifestage))

sample_data(phylo_coral_DIV)$lifestage = factor(sample_data(phylo_coral_DIV)$lifestage, levels = c("Egg (1 hpf)","Embryo (5 hpf)","Embryo (38 hpf)","Embryo (65 hpf)", "Larvae (93 hpf)", "Larvae (163 hpf)", "Larvae (231 hpf)", "Metamorphosed Polyp (231 hpf)", "Attached Recruit (183 hpf)", "Attached Recruit (231 hpf)"))

levels(as.factor(sample_data(phylo_coral_DIV)$lifestage))

Assign object to a shorter name.

GP1 = phylo_coral_DIV
GP1

Display sample sequencing depth.

min(sample_sums(GP1))

We will attempt subsampling at the minimum count (10,551 sequences) and in steps decreasing from 10551, 8000, 6000, 4000, 2000, 1000, 500.

DIV level analysis

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Intro to DVC Workshop

Today, I attended a workshop through the UW eScience Data Science postdoc group for an introduction to DVC, a version-control platform.

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December 2022 Goals

Writing

  1. Revise Montipora capitata 2020 time series figures
    • Conceptual
    • Metabolomic
    • Gene Expression
    • Physiology
    • Integration
  2. Revise Montipora capitata 2020 time series text to PNAS short format
  3. Work with Emma to revise results of E5 time series manuscript
  4. Reanalyze TagSeq data to new M. capitata genome
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November 2022 Goals

Writing

  1. Full draft of E5 results section for the 2020 time series project
  2. Submit proofs for Pocillopora acuta diversity paper~
  3. Revise Montipora capitata 2020 time series metabolomics and gene expression figures and associated text
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October 2022 Goals

Writing

  1. First draft of E5 time series results section and outline of discussion section
  2. Submit proofs for science education paper
  3. Start Montipora capitata 2020 time series revisions
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September 2022 Goals

Writing

  1. First draft of E5 time series results section and outline of discussion section
  2. Submit revision for Pocillopora acuta genetic diversity paper
  3. Go over Montipora capitata 2020 time series revisions with HP
  4. Start Montipora capitata 2020 time series revisions
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August 2022 Goals

Writing

  1. Finish and send final draft of Montipora capitata ontogeny 2020 manuscript to co-authors
  2. First draft of E5 time series manuscript by end of August with full results and outline of discussion section
  3. Submit final revision for science education manuscript
  4. Write methods and results section of Montipora capitata larval temperature exposure 2021 project
  5. Submit revision for Pocillopora acuta genetic diversity paper
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June 2022 Goals

Writing

  1. Write results of Montipora capitata development manuscript
  2. Draft results of E5 time series manuscript
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May 2022 Goals

Writing

  1. Methods and results of Montipora capitata development manuscript
  2. Submit final revision of science identity manuscript (delayed until August 2022)
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March 2022 Goals

Writing

  1. Write results of Montipora capitata development manuscript
  2. Start discussion of Montipora capitata development manuscript
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February 2022 Goals

Writing

  1. Finish methods of Montipora capitata development manuscript
  2. Write results of Montipora capitata development manuscript
  3. Start discussion of Montipora capitata development manuscript
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Analyzing 16S Mothur Results in R

This post details analyzing relative abundance and diversity metrics in R output from mothur analysis of 16S data for the 2020 early life history Montipora capitata time series.

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16S Pipeline in Mothur

This post details 16S data analysis using the Mothur pipeline for the 2020 Montipora capitata developmental time series.

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January 2022 Goals

Publications

  1. Revise and submit intraspecific diversity paper
  2. Write methods for Pocillopora acuta thermal exposure paper
  3. Outline revisions for Life History energetics perspective paper
  4. Outline results section of E5 timeseries manuscript
  5. Finish methods and write results of Montipora capitata development manuscript
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ITS2 and 16s Extractions

This posts describes extraction protocols for ITS2 and 16s sequencing for the 2020 Montipora capitata developmental time series.

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December 2021 Goals

Publications

  1. Revise and submit intraspecific diversity paper
  2. Finish revisions and submit larval thermal conditioning paper
  3. Outline revisions for Life History energetics perspective paper
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Metabolomics WGCNA Analysis Part 1

This posts describes weighted gene co-expression analysis (WGCNA) applied to metabolmoics data from the 2020 Montipora capitata early life history developmental time series.

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November 2021 Goals

Proposals and applications

  1. Submit education paper revisions to CBE - Life Sciences Education (November 9)
  2. Submit Science Incubator proposal (November 10)
  3. Submit NSF OCE proposal (November 12)
  4. Prepare E5 time series talk for Moorea LTER Annual Meeting in early December
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Mcapitata Spawning and Fertilization July 2020

Collection, fertilization, and rearing of Montipora capitata spawned gametes during the July 2020 spawning at the Hawaii Institute of Marine Biology in collaboration with C. Drury and J. Hancock in the Gates Coral Lab.

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